provide example of research topic about agriculture and fisheries

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156 Hot Agriculture Research Topics For High Scoring Thesis

Are you preparing an agriculture research paper or dissertation on agriculture but stuck trying to pick the right topic? The title is very important because it determines how easy or otherwise the process of writing the thesis will be. However, this is never easy for many students, but you should not give up because we are here to offer some assistance. This post is a comprehensive list of the best 156 topics for agriculture projects for students. We will also outline what every part of a thesis should include. Keep reading and identify an interesting agriculture topic to use for your thesis paper. You can use the topics on agriculture as they are or change them a bit to suit your project preference.

What Is Agriculture?

Also referred to as farming, agriculture is the practice of growing crops and raising livestock. Agriculture extends to processing plants and animal products, their distribution and use. It is an essential part of local and global economies because it helps to feed people and supply raw materials for different industries.

The concept of agriculture is evolving pretty fast, with modern agronomy extending to complex technology. For example, plant breeding, agrochemicals, genetics, and relationship to emerging disasters, such as global warming, are also part of agriculture. For students studying agriculture, the diversity of the subject is a good thing, but it can also make selecting the right research paper, thesis, or dissertation topics a big challenge.

How To Write A Great Thesis: What Should You Include In Each Section?

If you are working on a thesis, it is prudent to start by understanding the main structure. In some cases, your college/ university professor or the department might provide a structure for it, but if it doesn’t, here is an outline:

• Thesis Topic This is the title of your paper, and it is important to pick something that is interesting. It should also have ample material for research.
• Introduction This takes the first chapter of a thesis paper, and you should use it to set the stage for the rest of the paper. This is the place to bring out the objective of the study, justification, and research problem. You also have to bring out your thesis statement.
• Literature Review This is the second chapter of a thesis statement and is used to demonstrate that you have comprehensively looked at what other scholars have done. You have to survey different resources, from books to journals and policy papers, on the topic under consideration.
• Methodology This chapter requires you to explain the methodology that was used for the study. It is crucial because the reader wants to know how you arrived at the results. You can opt to use qualitative, quantitative, or both methods.
• Results This chapter presents the results that you got after doing your study. Make sure to use different strategies, such as tables and graphs, to make it easy for readers to understand.
• Discussion This chapter evaluates the results gathered from the study. It helps the researcher to answer the main questions that he/she outlined in the first chapter. In some cases, the discussion can be merged with the results chapter.
• Conclusion This is the summary of the research paper. It demonstrates what the thesis contributed to the field of study. It also helps to approve or nullify the thesis adopted at the start of the paper.

Interesting Agriculture Related Topics

This list includes all the interesting topics in agriculture. You can take any topic and get it free:

• Food safety: Why is it a major policy issue for agriculture on the planet today?
• European agriculture in the period 1800-1900.
• What are the main food safety issues in modern agriculture? A case study of Asia.
• Comparing agri-related problems between Latin America and the United States.
• A closer look at the freedom in the countryside and impact on agriculture: A case study of Texas, United States.
• What are the impacts of globalisation on sustainable agriculture on the planet?
• European colonisation and impact on agriculture in Asia and Africa.
• A review of the top five agriculture technologies used in Israel to increase production.
• Water saving strategies and their impacts on agriculture.
• Homeland security: How is it related to agriculture in the United States?
• The impact of good agricultural practices on the health of a community.
• What are the main benefits of biotechnology?
• The Mayan society resilience: what was the role of agriculture?

Sustainable Agricultural Research Topics For Research

The list of topics for sustainable agriculture essays has been compiled by our editors and writers. This will impress any professor. Start writing now by choosing one of these topics:

• Cover cropping and its impact on agriculture.
• Agritourism in modern agriculture.
• review of the application of agroforestry in Europe.
• Comparing the impact of traditional agricultural practices on human health.
• Comparing equity in agriculture: A case study of Asia and Africa.
• What are the humane methods employed in pest management in Europe?
• A review of water management methods used in sustainable agriculture.
• Are the current methods used in agricultural production sufficient to feed the rapidly growing population?
• A review of crop rotation and its effects in countering pests in farming.
• Using sustainable agriculture to reduce soil erosion in agricultural fields.
• Comparing the use of organic and biological pesticides in increasing agricultural productivity.
• Transforming deserts into agricultural lands: A case study of Israel.
• The importance of maintaining healthy ecosystems in raising crop productivity.
• The role of agriculture in countering the problem of climate change.

Unique Agriculture Research Topics For Students

If students want to receive a high grade, they should choose topics with a more complicated nature.This list contains a variety of unique topics that can be used. You can choose from one of these options right now:

• Why large-scale farming is shifting to organic agriculture.
• What are the implications of groundwater pollution on agriculture?
• What are the pros and cons of raising factory farm chickens?
• Is it possible to optimise food production without using organic fertilisers?
• A review of the causes of declining agricultural productivity in African fields.
• The role of small-scale farming in promoting food sufficiency.
• The best eco-strategies for improving the productivity of land in Asia.
• Emerging concerns about agricultural production.
• The importance of insurance in countering crop failure in modern agriculture.
• Comparing agricultural policies for sustainable agriculture in China and India.
• Is agricultural technology advancing rapidly enough to feed the rapidly growing population?
• Reviewing the impact of culture on agricultural production: A case study of rice farming in Bangladesh.

Fun Agricultural Topics For Your Essay

This list has all the agricultural topics you won’t find anywhere else. It contains fun ideas for essay topics on agriculture that professors may find fascinating:

• Managing farm dams to support modern agriculture: What are the best practices?
• Native Americans’ history and agriculture.
• Agricultural methods used in Abu Dhabi.
• The history of agriculture: A closer look at the American West.
• What impacts do antibiotics have on farm animals?
• Should we promote organic food to increase food production?
• Analysing the impact of fish farming on agriculture: A case study of Japan.
• Smart farming in Germany: The impact of using drones in crop management.
• Comparing the farming regulations in California and Texas.
• Economics of pig farming for country farmers in the United States.
• Using solar energy in farming to reduce carbon footprint.
• Analysing the effectiveness of standards used to confine farm animals.

Technology And Agricultural Related Topics

As you can see, technology plays a significant role in agriculture today.You can now write about any of these technology-related topics in agriculture:

• A review of technology transformation in modern agriculture.
• Why digital technology is a game changer in agriculture.
• The impact of automation in modern agriculture.
• Data analysis and biology application in modern agriculture.
• Opportunities and challenges in food processing.
• Should artificial intelligence be made mandatory in all farms?
• Advanced food processing technologies in agriculture.
• What is the future of genetic engineering of agricultural crops?
• Is fertiliser a must-have for success in farming?
• Agricultural robots offer new hope for enhanced productivity.
• Gene editing in agriculture: Is it a benefit or harmful?
• Identify and trace the history of a specific technology and its application in agriculture today.
• What transformations were prompted by COVID-19 in the agricultural sector?
• Reviewing the best practices for pest management in agriculture.
• Analysing the impacts of different standards and policies for pest management in two countries of your choice on the globe.

Easy Agriculture Research Paper Topics

You may not want to spend too much time writing the paper. You have other things to accomplish. Look at this list of topics that are easy to write about in agriculture:

• Agricultural modernization and its impacts in third world countries.
• The role of human development in agriculture today.
• The use of foreign aid and its impacts on agriculture in Mozambique.
• The effect of hydroponics in agriculture.
• Comparing agriculture in the 20th and 21st centuries.
• Is it possible to engage in farming without water?
• Livestock owners should use farming methods that will not destroy forests.
• Subsistence farming versus commercial farming.
• Comparing the pros and cons of sustainable and organic agriculture.
• Is intensive farming the same as sustainable agriculture?
• A review of the leading agricultural practices in Latin America.
• Mechanisation of agriculture in Eastern Europe: A case study of Ukraine.
• Challenges facing livestock farming in Australia.
• Looking ahead: What is the future of livestock production for protein supply?

Emerging Agriculture Essay Topics

Emerging agriculture is an important part of modern life. Why not write an essay or research paper about one of these emerging agriculture topics?

• Does agriculture help in addressing inequality in society?
• Agricultural electric tractors: Is this a good idea?
• What ways can be employed to help Africa improve its agricultural productivity?
• Is education related to productivity in small-scale farming?
• Genome editing in agriculture: Discuss the pros and cons.
• Is group affiliation important in raising productivity in Centre Europe? A case study of Ukraine.
• The use of Agri-Nutrition programs to change gender norms.
• Mega-Farms: Are they the future of agriculture?
• Changes in agriculture in the next ten years: What should we anticipate?
• A review of the application of DNA fingerprinting in agriculture.
• Global market of agricultural products: Are non-exporters locked out of foreign markets for low productivity?
• Are production technologies related to agri-environmental programs more eco-efficient?
• Can agriculture support greenhouse mitigation?

Controversial Agricultural Project For Students

Our team of experts has searched for the most controversial topics in agriculture to write a thesis on. These topics are all original, so you’re already on your way towards getting bonus points from professors. However, the process of writing is sometimes not as easy as it seems, so dissertation writers for hire will help you to solve all the problems.

• Comparing the mechanisms of US and China agricultural markets: Which is better?
• Should we ban GMO in agriculture?
• Is vivisection a good application or a necessary evil?
• Agriculture is the backbone of modern Egypt.
• Should the use of harmful chemicals in agriculture be considered biological terror?
• How the health of our planet impacts the food supply networks.
• People should buy food that is only produced using sustainable methods.
• What are the benefits of using subsidies in agriculture? A case study of the United States.
• The agrarian protests: What were the main causes and impacts?
• What impact would a policy requiring 2/3 of a country to invest in agriculture have?
• Analysing the changes in agriculture over time: Why is feeding the world population today a challenge?

Persuasive Agriculture Project Topics

If you have difficulty writing a persuasive agricultural project and don’t know where to start, we can help. Here are some topics that will convince you to do a persuasive project on agriculture:

• What is the extent of the problem of soil degradation in the US?
• Comparing the rates of soil degradation in the United States and Africa.
• Employment in the agricultural sector: Can it be a major employer as the population grows?
• The process of genetic improvement for seeds: A case study of agriculture in Germany.
• The importance of potatoes in people’s diet today.
• Comparing sweet potato production in the US to China.
• What is the impact of corn production for ethanol production on food supply chains?
• A review of sustainable grazing methods used in the United States.
• Does urban proximity help improve efficiency in agriculture?
• Does agriculture create economic spillovers for local economies?
• Analysing the use of sprinkle drones in agriculture.
• The impact of e-commerce development on agriculture.
• Reviewing the agricultural policy in Italy.
• Climate change: What does it mean for agriculture in developed nations?

Advanced Agriculture Project Topics

A more difficult topic can help you impress your professor. It can earn you bonus points. Check out the latest list of advanced agricultural project topics:

• Analysing agricultural exposure to toxic metals: The case study of arsenic.
• Identifying the main areas for reforms in agriculture in the United States.
• Are developed countries obligated to help starving countries with food?
• World trade adjustments to emerging agricultural dynamics and climate change.
• Weather tracking and impacts on agriculture.
• Pesticides ban by EU and its impacts on agriculture in Asia and Africa.
• Traditional farming methods used to feed communities in winter: A case study of Mongolia.
• Comparing the agricultural policy of the EU to that of China.
• China grew faster after shifting from an agro to an industrial-based economy: Should more countries move away from agriculture to grow?
• What methods can be used to make agriculture more profitable in Africa?
• A comprehensive comparison of migratory and non-migratory crops.
• What are the impacts of mechanical weeding on soil structure and fertility?
• A review of the best strategies for restoring lost soil fertility in agricultural farmlands: A case study of Germany.

Engaging Agriculture Related Research Topics

When it comes to agriculture’s importance, there is so much to discuss. These engaging topics can help you get started in your research on agriculture:

• Agronomy versus horticultural crops: What are the main differences?
• Analysing the impact of climate change on the food supply networks.
• Meat processing laws in Germany.
• Plant parasites and their impacts in agri-production: A case study of India.
• Milk processing laws in Brazil.
• What is the extent of post-harvest losses on farming profits?
• Agri-supply chains and local food production: What is the relationship?
• Can insects help improve agriculture instead of harming it?
• The application of terraculture in agriculture: What are the main benefits?
• Vertical indoor farms.
• Should we be worried about the declining population of bees?
• Is organic food better than standard food?
• What are the benefits of taking fresh fruits and veggies?
• The impacts of over-farming on sustainability and soil quality.

Persuasive Research Topics in Agriculture

Do you need to write a paper on agriculture? Perfect! Here are the absolute best persuasive research topics in agriculture:

• Buying coffee produced by poor farmers to support them.
• The latest advances in drip irrigation application.
• GMO corn in North America.
• Global economic crises and impact on agriculture.
• Analysis of controversies on the use of chemical fertilisers.
• What challenges are facing modern agriculture in France?
• What are the negative impacts of cattle farms?
• A closer look at the economics behind sheep farming in New Zealand.
• The changing price of energy: How important is it for the local farms in the UK?
• A review of the changing demand for quality food in Europe.
• Wages for people working in agriculture.

Work With Experts To Get High Quality Thesis Paper

Once you pick the preferred topic of research, it is time to get down and start working on your thesis paper. If writing the paper is a challenge, do not hesitate to seek thesis help from our experts. We work with ENL writers who are educated in top universities. Therefore, you can trust them to carry out comprehensive research on your paper and deliver quality work to impress your supervisor. Students who come to us for assistance give a high rating to our writers after scoring top grades or emerging top in class. Our trustworthy experts can also help with other school assignments, thesis editing, and proofreading. We have simplified the process of placing orders so that every student can get assistance quickly and affordably. You only need to navigate to the ordering page to buy a custom thesis paper online.

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Potential impacts of climate change on agriculture and fisheries production in 72 tropical coastal communities

Joshua e. cinner.

1 ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, QLD 4811 Australia

Iain R. Caldwell

Lauric thiault.

2 National Center for Scientific Research, PSL Université Paris, CRIOBE, USR 3278, CNRS-EPHE-UPVD, Maison des Océans, 195 rue Saint-Jacques, 75005 Paris, France

3 Moana Ecologic, Rocbaron, France

4 Private Fisheries and Environment Consultant, Lau, Morobe Papua New Guinea

Julia L. Blanchard

5 Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS Australia

6 Center for Marine Socioecology, Hobart, TAS Australia

7 Institute of Marine Science (ICM-CSIC) & Ecopath International Initiative (EII), Barcelona, 08003 Spain

Amy Diedrich

8 College of Science and Engineering, James Cook University, Building 142, Townsville, QLD 4811 Australia

9 Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, QLD 4811 Australia

Tyler D. Eddy

10 Centre for Fisheries Ecosystems Research, Fisheries & Marine Institute, Memorial University of Newfoundland, St. John’s, NL Canada

Jason D. Everett

11 School of Mathematics and Physics, University of Queensland, Brisbane, QLD Australia

12 CSIRO Oceans and Atmosphere, Queensland Biosciences Precinct, St Lucia, QLD Australia

13 Centre for Marine Science and Innovation, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW Australia

Christian Folberth

14 Biodiversity and Natural Resources Program, International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria

Didier Gascuel

15 DECOD (Ecosystem Dynamics and Sustainability), Institut Agro / Inrae / Ifremer, Rennes, France

Jerome Guiet

16 Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA USA

Georgina G. Gurney

Ryan f. heneghan.

17 School of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD Australia

Jonas Jägermeyr

18 NASA Goddard Institute for Space Studies, New York City, NY USA

19 Columbia University, Climate School, New York, NY 10025 USA

20 Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany

Narriman Jiddawi

21 Institute for Marine Science, University of Dar Es Salaam, Zanzibar, Tanzania

Rachael Lahari

22 Environment and Marine Scientist, New Ireland Province, Papua New Guinea

John Kuange

23 Wildlife Conservation Society, Goroka, EHP Papua New Guinea

Wenfeng Liu

24 Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083 China

Olivier Maury

25 MARBEC, IRD, Univ Montpellier, CNRS, Ifremer, Sète, France

Christoph Müller

Camilla novaglio, juliano palacios-abrantes.

26 Center for Limnology, University of Wisconsin – Madison, Wisconsin, WI USA

27 Institute for the Oceans and Fisheries, The University of British Columbia, Vancouver, BC Canada

Colleen M. Petrik

28 Scripps Institution of Oceanography, University of California, San Diego, CA 92093 USA

Ando Rabearisoa

29 Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA USA

Derek P. Tittensor

30 Department of Biology, Dalhousie University, Halifax, NS B3H 4R2 Canada

31 United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge, CB3 0DL UK

Andrew Wamukota

32 School of Environmental and Earth Sciences, Pwani University, P.O. Box 195, Kilifi, Kenya

Richard Pollnac

33 Department of Marine Affairs, University of Rhode Island, Kingston, RI 02881 USA

34 School of Marine & Environmental Affairs, University of Washington, 3707 Brooklyn Avenue NE, Seattle, WA 98105 USA

Associated Data

The de-identified exposure, sensitivity, and material style of life data generated in this study for each community can be accessed through Zenodo 76 [10.5281/zenodo.6496413]. All outputs from the FishMIP model ensemble are available via ISIMIP [ https://www.isimip.org/gettingstarted/data-access/ ]. Raw social survey data are not available because our verbal informed consent made it clear that only aggregated data would be published. The sample sizes and proportions of each community included in the social surveys can be found in the Supplementary Data  file . Base layer map data in Fig.  1c and Supplementary Figures  5 , 8 , and 9 is from Natural Earth, which is freely available through their website (naturalearthdata.com). The SEDAC gridded populating density of the world dataset used to identify a subset of random locations can be found at the following: https://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density-rev11/data-download .

Code used to analyse and visualize results is available through Zenodo 76 [10.5281/zenodo.6496413].

Climate change is expected to profoundly affect key food production sectors, including fisheries and agriculture. However, the potential impacts of climate change on these sectors are rarely considered jointly, especially below national scales, which can mask substantial variability in how communities will be affected. Here, we combine socioeconomic surveys of 3,008 households and intersectoral multi-model simulation outputs to conduct a sub-national analysis of the potential impacts of climate change on fisheries and agriculture in 72 coastal communities across five Indo-Pacific countries (Indonesia, Madagascar, Papua New Guinea, Philippines, and Tanzania). Our study reveals three key findings: First, overall potential losses to fisheries are higher than potential losses to agriculture. Second, while most locations (> 2/3) will experience potential losses to both fisheries and agriculture simultaneously, climate change mitigation could reduce the proportion of places facing that double burden. Third, potential impacts are more likely in communities with lower socioeconomic status.

Responses of agriculture and fisheries to climate change are interlinked, yet rarely studied together. Here, the authors analyse more than 3000 households from 5 tropical countries and forecast mid-century climate change impacts, finding that communities with higher fishery dependence and lower socioeconomic status communities face greater losses.

Introduction

Climate change is expected to profoundly impact key food production sectors, with the tropics expected to suffer losses in both fisheries and agriculture. For example, by 2100 tropical areas could lose up to 200 suitable plant growing days per year due to climate change 1 . Likewise, fishable biomass in the ocean could drop by up to 40% in some tropical areas 2 , 3 . While understanding the magnitude of losses that climate change is expected to create in key food production sectors is crucial, it is the social dimensions of vulnerability that determine the degree to which societies are likely to be affected by these changes 4 – 8 . Vulnerability is the degree to which a system is susceptible to and unable to cope with the effects of change. It is comprised of exposure (the degree to which a system is stressed by environmental or social conditions), the social dimensions of sensitivity (the state of susceptibility to harm from perturbations), and adaptive capacity (people’s ability to anticipate, respond to, and recover from the consequences of these changes) 4 , 9 . Together, the exposure and sensitivity domains are referred to as “potential impacts”, which are the focus of this article.

Incorporating key social dimensions of vulnerability is particularly important because many coastal communities simultaneously rely on both agriculture and fisheries to varying degrees 10 , yet assessments of climate change impacts and the policy prescriptions that come from them often consider these sectors in isolation 1 , 5 , 11 – 14 . Recently, studies have begun to look at the simultaneous impacts of climate change on both fisheries and agriculture at the national level 15 , 16 , but this coarse scale does not capture whether people simultaneously engage with- and are likely to be affected by- changes in these sectors. Indeed, whether households engage in both fisheries and agriculture 10 will determine whether people have the knowledge, skills, and capital to substitute sectors if one declines, or alternatively, make them particularly susceptible to the potential double burden of a combined decline across sectors 15 . Thus, more localised analyses incorporating key social dimensions of vulnerability are required to better understand how combined impacts to fisheries and agriculture may affect coastal communities.

Here, we combine a measure of exposure based on model projections of losses to exploitable marine biomass (here dubbed fisheries catch potential) and agriculture from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) Fast Track phase 3 dataset with a measure of sensitivity based on survey data about material wealth and engagement in fisheries, agriculture, and other occupational sectors from >3,000 households across 72 tropical coastal communities in five countries (see Supplementary Data  file ). We answer the following questions: 1) What are the potential impacts of projected changes to fisheries catch potential and agriculture on coastal communities?, 2) How much will mitigation measures reduce these potential impacts?, and 3) Are lower socioeconomic status coastal communities facing more potential impacts from climate change than their wealthier counterparts? We show that: fisheries tend to be more impacted than agriculture although there is substantial within-country variability; climate change mitigation can reduce the number of locations experiencing a double burden (i.e. losses to both fisheries and agriculture); and communities with lower socioeconomic status will experience the most severe climate change impacts.

Our study has three key results. First, we find that overall possible impacts on fisheries catch potential is higher than possible impacts on agriculture, but there can be substantial within-country variability in both exposure and sensitivity (Fig.  1 ). Specifically, exposure under the high-emissions Shared Socioeconomic Pathway 8.5 scenario (which has tracked historic cumulative CO 2 emissions 17 , but has been recently critiqued for over-projecting CO 2 emissions and economic growth 18 ) indicates substantive losses by mid-century to fisheries catch potential [Fig.  1 ; 14.7% +/− 4.3% (SE) mean fisheries catch potential loss]. To put these projected losses in perspective, Sala et al 19 . found that strategically protecting 28% of the ocean could increase food provisioning by 5.9 million tonnes, which is just 6.9% of the 84.4 million tons of marine capture globally in 2018 20 . Thus, the mean expected fisheries catch potential losses are approximately double that which could be buffered by strategic conservation. Model run agreement about the directionality of change for projected impacts to fisheries catch potential was high (SSP5-8.5: 84.7 + /− 4.5% (SE); SSP1-2.6: 89.2 + /− 4.06% (SE)). Interestingly, crop models projected that agricultural productivity (based on rice, maize, and cassava- see methods) is expected to experience small average gains across the 72 sites (1.2% +/− 1.5% (SE) mean agricultural gain), with a large response range between sites and crops (Supplementary Fig.  1 ). However, the average gains are not significantly different from zero ( t  = −0.80, df = 5.0, p  = 0.46), and model run agreement about directionality of change was lower for agriculture (SSP5-8.5: 69.1 + /− 4.82% (SE); SSP1-2.6: 70.4 +/− 3.27% (SE)). These projected agricultural gains are driven exclusively by rice (Supplementary Fig.  1 ), which has particularly large model disagreement 14 , 21 . Excluding rice shows an average decline in agricultural production by mid-century, since maize and cassava show consistent median losses under both SSP1-2.6 and SSP5-8.5 climate scenarios (Supplementary Fig.  1 ). Significantly greater losses in fisheries catch potential compared to agriculture productivity are apparent not only for our study sites (i.e. 15.9 + /− 5.6% (SE) greater; t  = 2.81, df = 4.97, p  = 0.0379), but also for a random selection of 4746 (10% of) coastal locations in our study countries with populations >25 people per km 2 (Fig.  2 ). Among those random sites, fisheries catch potential losses are an average of 15.6 + /− 5.1% (SE) greater than agriculture productivity changes ( t  = 3.06, df = 5.00, p  = 0.0282). Differences between expected losses at our sites and the randomly selected sites are small for agriculture (Cohen’s D for SSP5-8.5 = -0.31, SSP1-2.6 = −0.35) and negligible for fisheries catch potential (Cohen’s D for SSP5-8.5 = -0.02, SSP1-2.6 = -0.03), indicating that our sites are not particularly biased towards high or low exposure for the study region. Not only is the level of exposure generally higher in fisheries compared to agriculture, but the sensitivity is on average nearly twice as high (Fig.  1a, b ; 0.077 + /− 0.007 mean fisheries sensitivity; 0.04 +/− 0.01 mean agricultural sensitivity; t  = 3.0, df = 2.26, p value =0.0815).

Potential impacts comprise the exposure (y-axis, measured in potential losses, with error bars showing 25th and 75th percentiles) and sensitivity (x-axis, measured as level of dependence by households). Model run agreement (shown as colour gradient) highlights the proportion of ( a ) crop model runs ( n  = 20), ( b ) fisheries model runs ( n  = 16), and ( c ) average of agriculture and fisheries model runs that agree about the direction of change per site. Point shapes indicate country of each community. Inset map in Supplementary Fig.  9 .

Black dots, histograms, and dotted lines (for mean exposures) represent our study sites ( n = 72). Grey dots, histograms, and dotted lines represent a random selection of 10% of coastal cells with population densities >25 people/km 2 from our study countries ( n = 4746).

Our analysis also reveals high within-country variability in potential impacts (i.e. both exposure and sensitivity), particularly for fisheries (Fig.  1 ) - a finding that may be masked in studies looking at national-level averages 15 , 16 . Looking only at the mean expected losses can obscure the more extreme fisheries catch potential losses projected for many communities (Figs.  1 , ​ ,2). 2 ). For example, under SSP5-8.5, our Indonesian sites are projected to experience very close to the average fisheries catch potential losses among our study sites (15.9 + /− 2.1%SE), but individual sites range from 6.5-32% losses (Fig.  1b ). There is also substantial within-country variation in how communities are likely to experience climate change impacts, based on their sensitivity (Fig.  1a, b ). For example, in the Philippines, exposure to fisheries is consistently moderate (range 8.9-12.6% loss), but sensitivity ranges from our lowest (0.001) to our highest recorded scores (0.32). There is also within-country variability in model agreement, particularly for the agricultural models in Indonesia, where agricultural model agreement ranges from 50-85% and fisheries model agreement ranges from 56-100% for SSP5-8.5, and 50-80% and 50-94%, respectively, for SSP1-2.6.

The second key result from our integrated assessment reveals that some locations will bear a double burden of losses to fisheries and agriculture simultaneously, but mitigation efforts that reduce greenhouse gas emissions could curb these losses. Specifically, under SSP5-8.5, 64% of our study sites are expected to lose productivity in fisheries and agriculture simultaneously (Fig.  3a ), but this would reduce to 37% of sites under the low emissions scenario SSP1-2.6 (Fig.  3b ). Again, the effect of mitigation is consistent in the random selection of 4746 sites (Supplementary Fig.  2 ), with 70% of randomly selected sites expected to experience a double burden under SSP5 8.5, and 47% under SSP1 2.6. Many of the sites expected to experience the highest losses to both fisheries catch potential and agriculture have moderate to high sensitivity (Fig.  3a , Supplementary Fig.  3 ), which means the impacts of these changes could be profoundly felt by coastal communities.

a Under SSP5-8.5 agricultural losses (y-axis) plotted against fisheries losses (x-axis), with bubble size revealing the overall sensitivity and colour revealing the fisheries-agricultural relative sector dependency of each community’s sensitivity. b Potential benefits of mitigation shown by the potential losses for each community change going from the high emissions scenario (SSP5-8.5 in red) to a low emissions scenario (SSP1-2.6 in yellow).

Over a third of our sites (36% under SSP5-8.5) are expected to experience increases in agriculture (due to CO 2 fertilization effects that fuel potential increases particularly in rice yields) while experiencing losses in fisheries catch potential. For these sites, a question of critical concern is whether the potential gains in agriculture could help offset the losses in fisheries catch potential. The answer to this lies in part in the degree of substitutability between sectors. Our survey of 3,008 households reveals high variation among countries, and even within some countries in the degree of household occupational multiplicity incorporating both agriculture and fisheries sectors (Table  1 ). 31% of households in our study engaged in both fishing and agriculture, though this ranged from 10% of households in the Philippines to 77% of households in Papua New Guinea. This means that the degree to which agricultural gains might possibly offset some fisheries losses at the household scale is very context dependent. Our survey also revealed that 17% of households were involved in agriculture but not fisheries, ranging from 33% in Madagascar to 3% in our Papua New Guinean study communities. Alternatively, more than a third of households surveyed in Indonesia and Philippines were involved in fisheries but not agriculture (36% and 37% respectively), compared to a low value of 16% in Madagascar. In 12% of the Philippines communities surveyed (n = 3), not a single household was engaged in agriculture. Thus, for 32% of households across our sample, including some entire communities, potential agricultural gains will not offset potential fisheries losses. In these locations building adaptive capacity to buffer change will be critical 9 .

Proportion of surveyed households in each study country engaged in both agriculture and fisheries, agriculture but not fisheries, and fisheries but not agriculture.

Note: proportions do not add up to 1 because some households were not engaged in agriculture or fisheries.

Our third key result is that coastal communities with lower socioeconomic status are more likely to experience potential impacts than communities of higher socioeconomic status across the climate mitigation scenarios (SSP1-2.6 and SSP5-8.5; Fig.  4 ). Specifically, we examined the relationship between the average material style of life (a metric of wealth based on material assets; see methods) in a community and the relative potential impacts of simultaneous fisheries catch potential and agriculture losses (measured as the Euclidean distance of sensitivity and exposure from the origin). Importantly, socioeconomic status is related to both sensitivity and exposure (Supplementary Fig.  4 ). In other words, low socioeconomic status communities tend to have higher sensitivity to fisheries and agriculture than the wealthy, and are significantly more likely to be exposed to climate change impacts. Our findings regarding the relationship between socioeconomic status and sensitivity are consistent with a broad body of literature that shows how people tend to move away from natural resource-dependent occupations as they become wealthier 10 , 22 – 25 . One potential interpretation of our findings is that alternative livelihood programs (e.g. jobs outside the fisheries or agricultural sectors, such as the service industry) could reduce sensitivity in lower socioeconomic status communities. However, decades of research on livelihood diversification has highlighted a multitude of reasons why alternative livelihood projects frequently fail 26 , including that they do not provide high levels of non-economic satisfactions (e.g., social, psychological, and cultural) 27 – 29 , as well as cultural barriers to switching occupations (e.g. caste systems) 30 , and attachment to identity and place 31 . Alternative occupations need to provide some of the same satisfactions, including basic needs (safety, income), social and psychological needs (time away from home, community in which you live, etc.), and self-actualization (adventure, challenge, opportunity to be own boss, etc.). For example, fishing attracts individuals manifesting a personality configuration referred to as an externalizing disposition, which is characterized by a need for challenges, adventure, and risk. Fishing can be extremely satisfying for people with this personality complex, while many alternative occupations can lead to job dissatisfaction, which has negative social and psychological consequences 32 , 33 . Research has shown that recreational fishing captain or guide jobs produce some of the same satisfactions as fishing and have been successfully introduced as alternative occupations 33 . Despite these limited successes, alternative livelihood programs frequently fail and are not a viable substitute for mitigating climate change for the ~6 million coral reef fishers globally 34 .

Black lines are predictions from linear mixed-effects models (with country as random effect) and grey bands are standard errors. Statistical significance ( p ) and fit ( R 2 ) of the mixed-effects models are also shown: (m) = marginal R 2 , (c) = conditional R 2 . Point shape and colour indicate country.

Our study is an important first step in examining the potential simultaneous impacts to fisheries catch potential and agriculture in coastal communities, but has some limitations, some of which could be addressed in future studies. First, our measure of exposure was dynamic (i.e., it was projected into the future), while our measures of sensitivity and material wealth were static (i.e., from a single point in time) and did not consider potential changes over time. Although there are projections of how national-scale measures of wealth (e.g. gross domestic product; GDP) may change in the future, there are no reliable projections for household- or community-scale changes to material wealth or livelihoods. As an additional analysis, we examined observed changes in sensitivity and material wealth over 15 and 16 years, respectively, in two Papua New Guinean coastal communities (Fig.  5 ). We found that, over the observed time frame (2001-2016), which is approximately half that of the predicted time frame of exposure, sensitivity scores were extremely stable, particularly in Ahus (Fig.  5 ). Similarly, material wealth was also reasonably stable over time, but did reflect a shift in both communities toward more houses being built out of sturdier material (e.g., wood plank walls and floor, metal roofs). Importantly, while there were absolute changes to material wealth in both communities, the relative position stayed very similar. Although these data do not allow us to make inferences about what will happen into the future, they do highlight that, at least in decadal timeframes, these indicators are reasonably stable. One alternative approach may have been to assume that projected national-scale changes to GDP would apply evenly across each coastal community within a country (i.e., adjust the intercept of both material wealth and correlated sensitivity for each country relative to the projected changes in GDP). However, given the wide spread of material wealth and sensitivity scores within countries, we ultimately were less comfortable with the assumptions inherent in the approach (i.e., that national-scale changes would affect all communities in a country equally) than with the caveat that our metrics were static.

b shows how the communities change along the first two axes of a principal component analysis (i.e., PC1 and PC2), based on 16 household-scale material items, with black text and grey lines indicate the relative contribution of each material item to principal components.

Second, there are key limitations and assumptions to the models we used. For example, many tropical small-scale fisheries target seagrass 35 and coral reef habitats 34 , which are not represented in the global ensemble models. Additionally, the ensemble models were developed at relatively low spatial resolution (e.g. 1° cells), and are not designed to capture higher-resolution structures and processes. Our approach for dealing with this was to make transparent the degree of ensemble model run agreement about the direction of change, which relies on the assumption that we have greater confidence in projections that have higher model run agreement. Another limitation is that there may be discrepancies between the total consumer biomass (see method) in the absence of fishing that is outputed by the models used here and what would actually be harvested by fishers since total consumer biomass can include both target and non-target species as well as other taxa entirely. Despite these limitations, we assumed that total consumer biomass is directly related to potential fisheries yields 11 . Likewise, we included just three crops in the agricultural models (rice, maize, and cassava), which are key in the study region, with many study countries growing 2 or more of these crops. For example, in 2020 Indonesia was the 4th largest producer of rice in the world, the 5th largest producer of cassava, and the 8th largest producer of maize 36 . However, subsistence agriculture in Papua New Guinea is dominated by banana and yams, for which agricultural yield projections were not available. We used an unweighted average of projected changes in these three crops to represent a portfolio of small-scale agriculture, with a sensitivity test based on agricultural projections weighted by current yields/production area proportions of current yields (Supplementary Fig.  1 ). Finally, it is important to keep key model assumptions in mind when interpreting these data. For example, the agricultural models assumed no changes in farm management or climate change adaptation over time, while the fisheries models do not explicitly resolve predation impacts from higher trophic levels on phytoplankton.

Third, our sensitivity metric examined a somewhat narrow aspect of what makes people sensitive to climate change. Sensitivity is thought to contain dimensions of economic, demographic, psychological, and cultural dependency 37 . Our metric was based on people’s engagement in natural resource-based livelihoods, which primarily captures the economic dimensions (although livelihoods do provide cultural and psychological contributions to people 26 , 28 , 29 , 31 , 38 ).

Fourth, our study explicitly focused on the potential impacts of climate change in 72 Indo-Pacific coastal communities by examining their sensitivity and exposure, but our methodology did not enable us to incorporate adaptive capacity. Adaptive capacity is a latent trait that enables people to adapt to and take advantage of the opportunities created by change 39 , 40 , and is critically important in determining the fate of coastal communities under climate change. Adaptive capacity is thought to consist of dimensions of assets, flexibility, social organisation, learning, socio-cognitive, and agency 9 , 41 , 42 . Unfortunately, indicators of these dimensions of adaptive capacity were not collected in a standardised manner across all of the different projects comprising this study.

Fifth, we investigated the potential impacts of climate change on two key food production sectors, but there may be other climate change impacts which have much more profound impacts on people’s wellbeing. For example, sea level rise may destroy homes and other infrastructure 43 , while heat waves may result in direct mortality 44 . Last, we used shared socioeconomic pathway exploratory scenarios that bracket the full range of scenario variability (SSP5-8.5 and SSP1-2.6). At the time of publication, these were the only scenarios available for both fisheries and agriculture using the ISIMIP Fastrack Phase 3 dataset. Future publications may wish to explore additional scenarios.

Our study quantifies the potential impacts of climate change on key food production sectors in tropical coastal communities across a broad swath of the Indo-Pacific. We find that both exposure and sensitivity to fisheries is generally higher than to agriculture, but some places may experience losses from both sectors simultaneously. These losses may be compounded by other drivers of change, such as overfishing or soil erosion, which is already leading to declining yields 45 , 46 . Simultaneous losses to both fisheries catch potential and agriculture will limit people’s opportunity to adapt to changes through switching livelihoods between food production sectors 9 . This will especially be the case in lower socioeconomic status communities where dependence on natural resources is higher 10 . Together, our integration of model projections and socioeconomic surveys highlight the importance of assessing climate change impacts across sectors, but reveals important mismatches between the scale at which people will experience the impacts of climate change and the scale at which modelled projections about climate change impacts are currently available.

Sampling of coastal communities

Here, we integrated data from five different projects that had surveyed coastal communities across five countries 47 – 50 . Between 2009 and 2015, we conducted socioeconomic surveys in 72 sites from Indonesia ( n  = 25), Madagascar ( n  = 6), Papua New Guinea ( n  = 10), the Philippines ( n  = 25), and Tanzania (Zanzibar) ( n  = 6). Site selection was for broadly similar purposes- to evaluate the effects of various coastal resource management initiatives (collaborative management, integrated conservation and development projects, recreational fishing projects) on people’s livelihoods in rural and peri-urban villages. Within each project, sites were purposively selected to be representative of the broad range of socioeconomic conditions (e.g., population size, levels of development, integration to markets) experienced within the region. We did not survey strictly urban locations (i.e., major cities). Because our sampling was not strictly random, care should be taken when attempting to make inferences beyond our specific study sites.

We surveyed between 13 and 150 households per site, depending on the population of the communities and the available time to conduct interviews per site. All projects employed a comparable sampling design: households were either systematically (e.g., every third house), randomly sampled, or in the case of three villages, every household was surveyed (a census) (see Supplementary Data  file ). Respondents were generally the household head, but could have been other household members if the household head was not available during the study period (i.e. was away). In the Philippines, sampling protocol meant that each village had an even number of male and female respondents. Respondents gave verbal consent to be interviewed.

The following standard methodology was employed to assess material style of life, a metric of material assets-based wealth 48 , 51 . Interviewers recorded the presence or absence of 16 material items in the household (e.g., electricity, type of walls, type of ceiling, type of floor). We used a Principal Component Analysis on these items and kept the first axis (which explained 34.2% of the variance) as a material wealth score. Thus, each community received a mean material style of life score, based on the degree to which surveyed households had these material items, which we then scaled from 0 to 1. We also conducted an exploratory analysis of how material style of life has changed in two sites in Papua New Guinea (Muluk and Ahus villages) over fifteen and sixteen-year time span across four and five-time periods (2001, 2009, 2012, 2016, and 2002, 2009, 2012, 2016, 2018), respectively, that have been surveyed since 2001/2002 52 . These surveys were semi-panel data (i.e. the community was surveyed repeatedly, but we did not track individuals over each sampling interval) and sometimes occurred in different seasons. For illustrative purposes, we plotted how these villages changed over time along the first two principal components.

Sensitivity

We asked each respondent to list all livelihood activities that bring in food or income to the household and rank them in order of importance. Occupations were grouped into the following categories: farming, cash crop, fishing, mariculture, gleaning, fish trading, salaried employment, informal, tourism, and other. We considered fishing, mariculture, gleaning, fish trading together as the ‘fisheries’ sector, farming and cash crop as the ‘agriculture’ sector and all other categories into an ‘off-sector’.

We then developed three distinct metrics of sensitivity based on the level of dependence on agriculture, fisheries, and both sectors together. Each metric incorporates the proportion of households engaged in a given sector (e.g., fisheries), whether these households also engage in occupations outside of this sector (agriculture and salaried/formal employment; referred to as ‘linkages’ between sectors), and the directionality of these linkages (e.g., whether respondents ranked fisheries as more important than other agriculture and salaried/formal employment) (Eqs.  1 – 3 )

where S A , S F and S AF are a community’s sensitivity in the context of agriculture, fisheries and both sectors, respectively. A, F and AF are the number of households relying on agriculture-related occupations within that community, fishery-related and agriculture- and fisheries-related occupations within the community, respectively. NA, NF and NAF are the number of households relying on non-agriculture-related, non-fisheries-related, and non-agriculture-or-fisheries-related occupations within the community, respectively. N is the number of households within the community. r a , r f and r af are the number of times agriculture-related, fisheries-related and agriculture-and-fisheries-related occupations were ranked higher than their counterpart, respectively. r na , r nf and r naf are the number of times non-agriculture, non-fisheries, and non-agriculture-and-fisheries-related occupations were ranked higher than their counterparts. As with the material style of life, we also conducted an exploratory analysis of how joint agriculture-fisheries sensitivity has changed over time in a subset of sites (Muluk and Ahus villages in Papua New Guinea) that have been sampled since 2001/2002 52 . Although our survey methodology has the potential for bias (e.g. people might provide different rankings based on the season, or there might be gendered differences in how people rank the importance of different occupations 53 ), our time-series analysis suggest that seasonal and potential respondent variation do not dramatically alter our community-scale sensitivity metric.

To evaluate the exposure of communities to the impact of future climates on their agriculture and fisheries sectors, we used projections of production potential from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) Fast Track phase 3 experiment dataset of global simulations. Production potential of agriculture and fisheries for each of the 72 community sites and 4746 randomly selected sites from our study countries with coastal populations >25 people/km 2 were projected to the mid-century (2046–2056) under two emission scenarios (SSP1-2.6, and SSP5-8.5) and compared with values from a reference historical period (1983–2013).

For fisheries exposure (E F ), we considered relative change in simulated total consumer biomass (all modelled vertebrates and invertebrates with a trophic level >1). For each site, the twenty nearest ocean grid cells were determined using the Haversine formula (Supplementary Fig.  5 ). We selected twenty grid cells after a sensitivity analysis to determine changes in model agreement based on different numbers of cells used (1, 3, 5, 10, 20, 50, 100; Supplementary Figs.  6 – 7 ), which we balanced off with the degree to which larger numbers of cells would reduce the inter-site variability (Supplementary Fig.  8 ). We also report 25th and 75th percentiles for the change in marine animal biomass across the model ensemble. Projections of the change in total consumer biomass for the 72 sites were extracted from simulations conducted by the Fisheries and marine ecosystem Model Intercomparison Project (FishMIP 3 , 54 ). FishMIP simulations were conducted under historical, SSP1-2.6 (low emissions) and SSP5-8.5 (high emissions) scenarios forced by two Earth System Models from the most recent generation of the Coupled Model Intercomparison project (CMIP6); 55 GFDL-ESM4 56 and IPSL-CM6A-LR 57 . The historical scenario spanned 1950–2014, and the SSP scenarios spanned 2015–2100. Nine FishMIP models provided simulations: APECOSM 58 , 59 , BOATS 60 , 61 , DBEM 2 , 62 , DBPM 63 , EcoOcean 64 , 65 , EcoTroph 66 , 67 , FEISTY 68 , Macroecological 69 , and ZooMSS 11 . Simulations using only IPSL-CM6A-LR were available for APECOSM and DBPM, while the remaining 7 FishMIP models used both Earth System Model forcings. This resulted in 16 potential model runs for our examination of model agreement, albeit with some of these runs being the same model forced with two different ESMs. Thus, the range of model agreement could range from 8 (half model runs indicating one direction of change, and half indicating the other) to 16 (all models agree in direction of change). Model outputs were saved with a standardised 1° spatial grid, at either a monthly or annual temporal resolution.

For agriculture exposure (E A ), we used crop model projections from the Global Gridded Crop model Intercomparison Project (GGCMI) Phase 3 14 , which also represents the agriculture sector in ISIMIP. We used a window of 11×11 cells centred on the site and removed non-land cells (Supplementary Fig.  5 ). The crop models use climate inputs from 5 CMIP6 ESMs (GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL), downscaled and bias-adjusted by ISIMIP and use the same simulation time periods. We considered relative yield change in three rain-fed and locally relevant crops: rice, maize, and cassava, using outputs from 4 global crop models (EPIC-IIASA, LPJmL, pDSSAT, and PEPIC), run at 0.5° resolution. These 4 models with 5 forcings generate 20 potential model runs for our examination of model agreement. Yield simulations for cassava were only available from the LPJmL crop model. All crop model simulations assumed no adaptation in growing season and fertilizer input remained at current levels. Details on model inputs, climate data, and simulation protocol are provided in ref. 14 . At each site, and for each crop, we calculated the average change (%) between projected vs. historical yield within 11×11 cell window. We then averaged changes in rice, maize and cassava to obtain a single metric of agriculture exposure (E A ).

We also obtained a composite metric of exposure (E AF ) by calculating each community’s average change in both agriculture and fisheries:

Potential Impact

We calculated relative potential impact as the Euclidian distance from the origin (0) of sensitivity and exposure.

Sensitivity test

To determine whether our sites displayed a particular exposure bias, we compared the distributions of our sites and 4746 sites that were randomly selected from 47,460 grid cells within 1 km of the coast of the 5 countries we studied which had population densities >25 people/km 2 , based on the SEDAC gridded populating density of the world dataset ( https://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density-rev11/data-download ).

We used Cohen’s D to determine the size of the difference between our sites and the randomly selected sites.

Validating ensemble models

We attempted a two-stage validation of the ensemble model projections. First, we reviewed the literature on downscaling of ensemble models to examine whether downscaling validation had been done for the ecoregions containing our study sites.

While no fisheries ensemble model downscaling had been done specific to our study regions, most of the models of the ensemble have been independently evaluated against separate datasets aggregated at scales down to Large Marine Ecosystems (LMEs) or Exclusive Economic Zones (EEZs) (see 11 ). For example, the DBEM was created with the objective of understanding the effects of climate change on exploited marine fish and invertebrate species 2 , 70 . This model roughly predicts species’ habitat suitability; and simulates spatial population dynamics of fish stocks to output biomass and maximum catch potential (MCP), a proxy of maximum sustainable yield 2 , 62 , 71 . Compared with spatially-explicit catch data from the Sea Around Us Project (SAUP; www.seaaroundus.org ) 70 there were strong similarities in the responses to warming extremes for several EEZs in our current paper (Indonesia and Philippines) and weaker for the EEZs of Madagascar, Papua New Guinea, and Tanzania. At the LME level, DBEM MCP simulations explained about 79% of the variation in the SAUP catch data across LMEs 72 . The four LMEs analyzed in this paper (Agulhas Current; Bay of Bengal; Indonesian Sea; and Sulu-Celebes Sea) fall within the 95% confidence interval of the linear regression relationship 62 . Another example, BOATS, is a dynamic biomass size-spectrum model parameterised to reproduce historical peak catch at the LME scale and observed catch to biomass ratios estimated from the RAM legacy stock assessment database (in 8 LMEs with sufficient data). It explained about 59% of the variability of SAUP peak catch observation at the LME level with the Agulhas Current, Bay of Bengal, and Indonesian Sea catches reproduced within +/-50% of observations 61 . The EcoOcean model validation found that all four LMEs included in this study fit very close to the 1:1 line for overserved and predicted catches in 2000 64 , 65 . DBPM, FEISTY, and APECOSM have also been independently validated by comparing observed and predicted catches. While the models of this ensemble have used different climate forcings when evaluated independently, when taken together the ensemble multi-model mean reproduces global historical trends in relative biomass, that are consistent with the long term trends and year-on-year variation in relative biomass change (R 2 of 0.96) and maximum yield estimated from stock assessment models (R 2 of 0.44) with and without fishing respectively 11 .

Crop yield estimates simulated by GGCMI crop models have been evaluated against FAOSTAT national yield statistics 14 , 73 , 74 . These studies show that the models, and especially the multi-model mean, capture large parts of the observed inter-annual yield variability across most main producer countries, even though some important management factors that affect observed yield variability (e.g., changes in planting dates, harvest dates, cultivar choices, etc.) are not considered in the models. While GCM-based crop model results are difficult to validate against observations, Jägermeyr et al 14 . show that the CMIP6-based crop model ensemble reproduces the variability of observed yield anomalies much better than CMIP5-based GGCMI simulations. In an earlier crop model ensemble of GGCMI, Müller et al. 74 show that most crop models and the ensemble mean are capable of reproducing the weather-induced yield variability in countries with intensely managed agriculture. In countries where management introduces strong variability to observed data, which cannot be considered by models for lack of management data time series, the weather-induced signal is often low 75 , but crop models can reproduce large shares of the weather-induced variability, building trust in their capacity to project climate change impacts 74 .

We then attempted to validate the models in our study regions. For the crop models, we examined production-weighted agricultural projections weighted by current yields/production area (Supplementary Fig.  1 ). We used an observational yield map (SPAM2005) and multiplied it with fractional yield time series simulated by the models to calculate changes in crop production over time, which integrates results in line with observational spatial patterns. The weighted estimates were not significantly different to the unweighted ones (t = 0.17, df = 5, p = 0.87). For the fisheries models, our study regions were data-poor and lacked adequate stock assessment data to extend the observed global agreement of the sensitivity of fish biomass to climate during our reference period (1983-2013). Instead, we provide the degree of model run agreement about the direction of change in the ensemble models to ensure transparency about the uncertainty in this downscaled application.

To account for the fact that communities were from five different countries we used linear mixed-effects models (with country as a random effect) for all analyses. All averages reported (i.e. exposure, sensitivity, and model agreement) are estimates from these models. In both our comparison of fisheries and agriculture exposure and test of differences between production-weighted and unweighted agriculture exposure we wanted to maintain the paired nature of the data while also accounting for country. To accomplish this we used the differences between the exposure metrics as the response variable (e.g. fisheries exposure minus agriculture exposure), testing whether these differences are different from zero. We also used linear mixed-effects models to quantify relationships between the material style of life and potential impacts under different mitigation scenarios (SSP1-2.6 and 8.5), estimating standard errors from 1000 bootstrap replications. To further explore whether these relationships between the material style of life and potential impacts were driven by exposure or sensitivity, we conducted an additional analysis to quantify relationships between the material style of life and: 1) joint fisheries and agricultural sensitivity; 2) joint fisheries and agricultural exposure under different mitigation scenarios. We present both the conditional R 2 (i.e., variance explained by both fixed and random effects) and the marginal R 2 (i.e., variance explained by only the fixed effects) to help readers compare among the material style of life relationships.

Reporting summary

Further information on research design is available in the  Nature Research Reporting Summary linked to this article.

Supplementary information

Acknowledgements.

J.E.C. is supported by the Australian Research Council (CE140100020, FT160100047, DP110101540, and DP0877905). This work was undertaken as part of the Consultative Group for International Agricultural Research (CGIAR) Research Program on Fish Agri-Food Systems (FISH) led by WorldFish. T.D.E acknowledges support from the Natural Sciences and Engineering Research Council of Canada (RGPIN-2021-04319). M.C. and J.S. acknowledge support from the Spanish project ProOceans (RETOS-PID2020-118097RB-I00) and the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) to the Institute of Marine Science (ICM-CSIC). G.G.G. acknowledges support from an Australian Research Council Discovery Early Career Research Award (DE210101918). C.M.P. acknowledges support from NOAA grants NA20OAR4310441 and NA20OAR4310442. M.C. acknowledges the financial support of Ministerio de Ciencia e Innovación, Proyectos de I+D+I (RETOS-PID2020-118097RB-I00, ProOceans) and the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S).

Author contributions

J.E.C. conceived of the study and hosted a workshop with G.G.G., A.D., and R.P. to operationalise the concept. J.E.C., G.G.G., R.P., J.K., N.J., A.R., R.L., A.W., and A.D. provided socioeconomic data. J.J., C.M., C.F., W.L. contributed crop model simulations. J.B., M.C., J.S., T.E., J.E., D.G., J.G., R.F.H., C.N., J.P.A., C.P., and D.T. contributed fisheries model simulations. L.T., J.J., R.F.H., T.E., and I.R.C. analysed the data and all authors contributed to the writing of the manuscript.

Peer review

Peer review information.

Nature Communications thanks Simon Fraval and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.  Peer reviewer reports are available.

Data availability

Code availability, competing interests.

The authors declare no competing interests.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The online version contains supplementary material available at 10.1038/s41467-022-30991-4.

Advancing the Science of Climate Change (2010)

Chapter: 10 agriculture, fisheries, and food production, chapter ten agriculture, fisheries, and food production.

M eeting the food needs of a still-growing and more affluent global population—as well as the nearly one billion people who already go without adequate food—presents a key challenge for economic and human security (see Chapter 16 ). Many analysts estimate that food production will need to nearly double over the coming several decades (Borlaug, 2007; FAO, 2009). Recent trends of using food crops for fuel (e.g., corn ethanol) or displacing food crops with fuel crops, along with potential opportunities for reforesting land for carbon credits, may amplify the food security challenge by increasing competition for arable land (Fargione et al., 2008). Climate change increases the complexity of meeting these food needs because of its multiple impacts on agricultural crops, livestock, and fisheries. The potential ability of agricultural and fishery systems to limit climate change adds yet another dimension to be considered.

Questions that farmers, fishers, and other decision makers are asking or will be asking about agriculture, fisheries, and food production in the context of climate change include the following:

How will climate change affect yields?

How will climate change affect weeds and pests, and will I need more pesticides or different technology to maintain or increase yields?

Will enough water be available for my crops? Will the risk of flooding or drought increase?

Should I change to more heat-resistant or slower-growing crop varieties?

What new market opportunities should I take advantage of? How will competitors in other regions be affected?

What adjustments do I need to make to guarantee the sustainability of the fisheries under my management?

How will climate change affect my catch? Will I need new equipment and technology? Will regulations change?

How will climate change affect the availability of food in domestic and international markets? Will food become more expensive? Will food security increase or decrease?

How can changes in agricultural production and practices contribute to reduc-

tions in greenhouse gas emissions or dampen regional-scale impacts related to climate change?

The scientific knowledge summarized in this chapter illustrates how agriculture will be influenced by climate change, and it explores the less well understood impacts of climate change on fisheries. The chapter also indicates how agricultural management may provide opportunities to reduce net human greenhouse gas (GHG) emissions, and it offers insight into the science needed for adaptation in agriculture systems as well as food security issues. Finally, the chapter provides examples of a broad range of research that is needed to understand the impacts of climate change on food production systems and to develop strategies that assist in both limiting the magnitude of climate change through management practices and reducing vulnerability and increasing adaptive capacity in regions and populations in the United States and other parts of the world.

CROP PRODUCTION

Crop production will be influenced in multiple ways by climate change itself, as well as by our efforts to limit the magnitude of climate change and adapt to it. Over the past two decades, numerous experimental studies have been carried out on crop responses to increases in average temperature and atmospheric CO 2 concentrations (often referred to as carbon fertilization), and mathematical models depicting those relationships (singly or in combination) have been developed for individual crops. Fewer experiments and models have evaluated plant responses to climate-related increases in air pollutants such as ozone, or to changes in water or nutrient availability in combination with CO 2 and temperature changes. A recently published report of the U.S. Climate Change Science Program (CCSP, 2008e) summarized the results from experimental and modeling analyses for the United States. Results of experimental studies, for example, indicate that many crop plants, including wheat and soybeans, respond to elevated CO 2 with increased growth and seed yield, although not uniformly so. Likewise, elevated CO 2 also reduces the conductance of CO 2 and water vapor through pores in the leaves of some plants, with resulting improvements in water use efficiency and, potentially, improved growth under drought conditions (Leakey et al., 2009). On the other hand, studies carried out in the field under “free air CO 2 enrichment” environments indicate that growth response is often smaller than expected based on more controlled studies (e.g., Leakey et al., 2009; Long et al., 2006). The response of crop plants to carbon fertilization in field environments hence remains an important area of research (see Research Needs section at the end of the chapter).

Some heat-loving crop plants such as melons, sweet potatoes, and okra also respond positively to increasing temperatures and longer growing seasons; but many other crops, including grains and soybeans, are negatively affected, both in vegetative growth and seed production, by even small increases in temperature ( Figure 10.1 ). Many important grain crops tend to have lower yields when summer temperatures increase, primarily because heat accelerates the plant’s developmental cycle and reduces the duration of the grain-filling period (CCSP, 2008b; Rosenzweig and Hillel, 1998). In some crop plants, pollination, kernel set, and seed size, among other variables, are harmed by extreme heat (CCSP, 2008b; Wolfe et al., 2008). Studies also indicate that some crops such as fruit and nut trees are sensitive to changes in seasonality, reduced cold periods, and heat waves (Baldocchi and Wong, 2008; CCSP, 2008e; Luedeling et al., 2009).

Most assessments conclude that climate change will increase productivity of some crops in some regions, especially northern regions, while reducing production in others (CCSP, 2008b; Reilly et al., 2003), an expected result given the range of projected climate changes and diversity of food crops around the world. The Intergovernmental Panel on Climate Change (IPCC) suggests, with medium confidence, that moderate warming (1.8°F to 5.4°F [1°C to 3°C]) and associated increases in CO 2 and changes in precipitation would benefit crop and pasture lands in middle to high latitudes but decrease yields in seasonally dry and low-latitude areas (Easterling et al., 2007). This response to intermediate temperature increases would generate a situation of midlatitude “winners” in developed countries and low-latitude “losers” in developing coun-

FIGURE 10.1 Growth rates (green) and reproductive response (purple) versus temperature for corn (left) and soybean (right). The curves show that there is a temperature range (colored bars) within which the plants can optimally grow and reproduce, and that growth and reproduction are less efficient at temperatures above this range. The curves also show that, above a certain temperature, the plants cannot reproduce. SOURCE: USGCRP (2009a).

tries, thus magnifying rather than reducing existing inequities in food availability and security. The IPCC also concludes with medium to low confidence that, on the whole, global food production is likely to decrease with increases in average temperatures above 5.4°F (3°C).

Regional assessments of agricultural impacts in the United States (e.g., CCSP, 2008b, and references therein) suggest that over the next 30 years, the benefits of elevated CO 2 will mostly offset the negative effects of increasing temperature (see below for limits in modeling conducted to date). In northern regions of the country, many crops may respond positively to increases in temperature and atmospheric CO 2 concentrations. In the Midwest corn belt and more southern areas of the Great Plains, positive crop responses to elevated CO 2 may be offset by negative responses to increasing temperatures; rice, sorghum, and bean crops in the South would see negative growth impacts (CCSP, 2008b). In California, where half the nation’s fruit and vegetable crops are grown, climate change is projected to decrease yields of almonds, walnuts, avocados, and table grapes by up to 40 percent by 2050 (Lobell et al., 2007). As temperatures continue to rise, crops will increasingly experience temperatures above the optimum for growth and reproduction. Adaptation through altered crop types, planting dates, and other management options is expected to help the agricultural sector, especially in the developed world (Burke et al., 2009; Darwin et al., 1995). However, regional assessments for other areas of the world consistently conclude that climate change presents a serious risk to critical staple crops in sub-Saharan Africa, where adaptive capacity is expected to be less than in the industrialized world (Jones and Thornton, 2003; Parry et al., 2004). Parts of the world where agriculture depends on water resources from glacial melt, including the Andean highlands, the Ganges Plain, and portions of East Africa, are also at risk due to the worldwide reduction in snowpack and the retreat of glaciers (Bradley et al., 2006; Kehrwald et al., 2008; also see Chapter 8 ).

While models of crop responses to climate change have generally incorporated shifts in average temperature, length of growing season, and CO 2 fertilization, either singly or in combination, most have excluded expected changes in other factors that also have dramatic impacts on crop yields. These critical factors include changes in extreme events (such as heat waves, intense rainfall, or drought), pests and disease, and water supplies and energy use (for irrigation). Extreme events such as heavy downpours are already increasing in frequency and are projected to continue to increase (CCSP, 2008b; Rosenzweig et al., 2001). Intense rainfalls can delay planting, increase root diseases, damage fruit, and cause flooding and erosion, all of which reduce crop productivity. Drought frequency and intensity are likely (Christensen et al., 2007) to increase in several regions that already experience water stress, especially in developing

countries where investments have focused on disaster recovery more than adaptive capacity (e.g., Mirza, 2003).

Changes in water quantity and quality due to climate change are also expected to affect food availability, stability, access, and utilization. This will increase the vulnerability of many farmers and decrease food security, especially in the arid and semiarid tropics and in the large Asian and African deltas (Bates and Kundzewicz, 2008). As noted in Chapter 8 , freshwater demand globally will grow in coming decades, primarily due to population growth, increasing affluence, and the need for increased production of food and energy. Climate change is exacerbating these issues, and model simulations under various scenarios indicate that many regions face water resource challenges, especially in regions that depend on rainfall or irrigation from snowmelt (Hayhoe et al., 2007; Kapnick and Hall, 2009; Maurer and Duffy, 2005). As a result, many regions face critical decisions about modifying infrastructure and pricing policies as climate change progresses.

Many weeds, plant diseases, and insect pests benefit from warming (and from elevated CO 2 , in the case of most weed plants), sometimes more than crops; as temperatures continue to rise, many weeds, diseases, and pests will also expand their ranges (CCSP, 2008b; Garrett et al., 2006; Gregory et al., 2009; Lake and Wade, 2009; McDonald et al., 2009). In addition, under higher CO 2 concentrations, some herbicides appear to be less effective (CCSP, 2008b; Ziska, 2000; Ziska et al., 1999). In the United States, aggressive weeds such as kudzu, which has already invaded 2.5 million acres of the southeast, is expected to expand its range into agricultural areas to the north (Frumhoff, 2007). Worldwide, animal diseases and pests are already exhibiting range extensions from low to middle latitudes due to warming (CCSP, 2008b; Diffenbaugh et al., 2008). While these and other changes are expected to have negative impacts on crops, their impact on food production at regional or national scales has not been thoroughly evaluated.

Similar to crop production, commercial forestry will be affected by many aspects of climate change, including CO 2 fertilization, changes in length of growing season, changing precipitation patterns, and pests and diseases. Models project that global timber production could increase through a poleward shift in the locations where important forest species are grown, largely as a result of longer growing seasons. Enhanced growth due to carbon fertilization is also possible (Norby et al., 2005). However, experimental results and models typically do not account for limiting factors such as pests, weeds, nutrient availability, and drought; these limiting factors could potentially offset or even dominate the effects of longer growing seasons and carbon fertilization (Angert et al., 2005; Kirllenko and Sedjo, 2007; Norby et al., 2005).

LIVESTOCK PRODUCTION

Livestock respond to climate change directly through heat and humidity stresses, and they are also affected indirectly by changes in forage quantity and quality, water availability, and disease. Because heat stress reduces milk production, weight gain, and reproduction in livestock, production of pork, beef, and milk is projected to decline with warming temperatures, especially those above 5.4°F (3°C; Backlund et al., 2008) ( Figure 10.2 ). In addition, livestock losses due to heat waves are expected to increase, with the extreme heat exacerbated by rising minimum nighttime temperatures as well as increasing difficulties in providing adequate water (CCSP, 2008b).

Increasing temperatures may enhance production of forage in pastures and rangelands, except in already hot and dry locations. Longer growing seasons may also extend overall forage production, as long as precipitation and soil moisture are sufficient; however, uncertainty in climate model precipitation projections makes this difficult to determine. Although CO 2 enrichment stimulates production on many rangelands and pastures, it also reduces forage quality, shifts the dominant grass species toward those with lower food quality, and increases the prevalence of nonforage weeds (CCSP, 2008b; Eakin and Conley, 2002). In northern Sonora, Mexico, for example, buffelgrass, which was imported from Africa and improved in the United States, is increasingly planted as livestock pasture in arid conditions. However, the grass has become an

FIGURE 10.2 Percent change in milk yield from 20th-century (1850 to 1985) climate conditions to projected 2040 climate conditions made using two different models of future climate (bold versus italicized numbers) in different regions of the United States. The bold values are associated with the model that exhibits more rapid warming. SOURCE: CCSP (2008e).

aggressive invader, spreading across the Sonoran Desert landscape and into Arizona and overrunning important national parks and reserves (Arriaga et al., 2004). Overall, changes in forage are expected to lead to an overall decline in livestock productivity.

FISHERIES AND AQUACULTURE PRODUCTION

Over one billion people around the world rely on seafood as their primary source of protein, and roughly three billion people obtain at least 15 percent of their total protein intake from seafood (FAO, 2009). Global demand for seafood is growing at a rapid rate, fueled by increases in human population, affluence, and dietary shifts (York and Gossard, 2004). While demand for seafood is increasing, the catch of wild seafood has been declining slightly for 20 years (Watson and Pauly, 2001). Meeting the growth in demand has only been possible by rapid growth in marine aquaculture. The United States consumes nearly five billion pounds of seafood a year, ranking it third globally behind China and Japan. This large consumption, however, comes primarily from fish caught outside the nation’s boundary waters. Nearly 85 percent of U.S. consumption is imported, and that fraction is increasing (Becker, 2010). Therefore, consumption of food from the sea links the United States to nearly all the world’s ocean ecosystems.

Marine Fisheries

The impacts of climate change on marine-based food systems are far less well known than impacts on agriculture, but there is rapidly growing evidence that they could be severe (see Chapter 9 ). This is especially problematic given that a sizeable fraction of the world’s fisheries are already overexploited (Worm et al., 2009) and many are also subject to pollution from land or under stress from the decline of critical habitats like coral reefs and wetlands (Halpern et al., 2008; Sherman et al., 2009).

Year-to-year climate variability has long been known to cause large fluctuations in fish stocks, both directly and indirectly (McGowan et al., 1998; Stenseth et al., 2002), and this has always been a challenge for effective fisheries management (Walters and Parma, 1996). Similar sensitivity to longer time-scale variations in climate has been documented in a wide range of fish species from around the globe (Chavez et al., 2003; Steele, 1998), and this portends major changes in fish populations under future climate change scenarios. Successful management of fisheries will require an improved ability to forecast population fluctuations driven by climate change; this in turn demands significant new investments in research, including research on various management options (e.g., Mora et al., 2009). Fundamental shifts in management prac-

tices may be needed. For example, restoration planning for depleted Chinook salmon populations in the Pacific Northwest needs to account for the spatial shift in salmon habitat (Battin et al., 2007). An added complexity is that, because most of the fish catch comes from open oceans under international jurisdiction, any management regime will need to be negotiated and accepted by multiple nations to be effective.

Fished species tend to be relatively mobile, either as adults or young (larvae drifting in the plankton). As a result, their distributions can shift rapidly compared to those of land animals. In recent decades, geographical shifts toward the poles of tens to hundreds of kilometers have been documented for a wide range of marine species in different areas (Grebmeier et al., 2006; Lima et al., 2006; Mueter and Litzow, 2008; Sagarin et al., 1999; Zacherl et al., 2003). Model projections for anticipated changes by 2050 suggest a potentially dramatic rearrangement of marine life (Cheung et al., 2009). Although such projections are based upon relatively simple models and should be treated as hypotheses, they suggest that displacements of species ranges may be sufficiently large that the fish species harvested from any given port today may change dramatically in coming decades. Fishers in many Alaskan ports are already facing much longer commutes as distributions of target species have shifted (CCSP, 2009b).

Such projected shifts in fisheries distributions are likely to be most pronounced for U.S. fisheries in the North Pacific and North Atlantic, where temperature increases are likely to be greatest and will be coupled to major habitat changes driven by reduced sea ice (CCSP, 2009b). Abrupt warming in the late 1970s, which was associated with a regime shift in the Pacific Decadal Oscillation, greatly altered the marine ecosystem composition in the Gulf of Alaska (Anderson and Piatt, 1999). Rapid reductions in ice-dominated regions of the Bering Sea will very likely expand the habitat for subarctic piscivores such as arrowtooth flounder, cod, and pollock. Because there are presently only fisheries for cod and pollock, arrowtooth flounder may experience significant population increases with broad potential consequences to the ecosystem (CCSP, 2009b).

The effects of ocean acidification from increased absorption of CO 2 by the sea (see Chapters 6 and 9 ) may be even more important for some fisheries than other aspects of climate change, although the overall impact of ocean acidification remains uncertain (Fabry et al., 2008; Guinotte and Fabry, 2008). Many fished species (e.g., invertebrates such as oysters, clams, scallops, and sea urchins) produce shells as adults or larvae, and the production of shells could be compromised by increased acidification (Fabry et al., 2008; Gazeau et al., 2007; Hofmann et al . , 2008). Many other fished species rely on shelled plankton, such as pteropods and foraminifera, as their primary food source. Projected declines in these plankton species could have catastrophic impacts

on fished species higher in the food chain. Finally, acidification can disrupt a variety of physiological processes beyond the production of shells. Hence, the potential impacts of acidification—especially in combination with other climate changes on marine fish-eries—is potentially enormous, but the details remain highly uncertain (NRC, 2010f).

Aquaculture and Freshwater Fisheries

Today, approximately a third of seafood is grown in aquaculture, and that number rises to half if seafood raised for animal feed is included. As the fastest growing source of animal protein on the planet, aquaculture is widely touted as critical for meeting growing demands for food. Although aquaculture avoids some of the climate impacts associated with wild fish harvesting, others (e.g., ocean acidification) are equally challenging. Indeed, the current predominance of aquaculture facilities in estuaries and bays may exacerbate some of the impacts of ocean acidification (Miller et al., 2009). In addition, since different forms of aquaculture may require a variety of other natural resources such as water, feed, and energy to produce seafood, there may be much broader indirect impacts of climate change on this rapidly growing industry.

Freshwater fisheries face most of the same challenges from climate change as those in saltwater, as well as some that are unique. Forecasting the consequences of warming on fish population dynamics is complicated, because details of future climate at relatively small geographic scales (e.g., seasonal and daily variation, regional variation across watersheds) are critical to anticipating fish population responses (Littell et al., 2009). Yet, as noted in Chapter 6 , regional and local aspects of climate change are the hardest to project. Expected effects include elevated temperatures, reduced dissolved oxygen (Kalff, 2002), increased stratification of lakes (Gaedke et al., 1998; Kalff, 2002), and elevated pollutant toxicity (Ficke et al., 2007). Although the consequences of some of these changes are predictable when taken one at a time, the complex nature of interactions between their effects makes forecasting change for even a single species in a single region daunting (Littell et al., 2009). In addition to altering these physical and chemical characteristics of freshwater, climate change will also alter the quantity, timing, and variability of water flows (Mauget, 2003; Ye et al., 2003; Chapter 8 ). Climate-driven alterations of the flow regime will add to the decades or even centuries of alterations of stream and river flows through other human activities (e.g., urbanization, water withdrawals, dams; Poff et al., 2007). Finally, changes in lake levels that will result from changed patterns of precipitation, runoff, groundwater flows, and evaporation could adversely affect spawning grounds for some species, depending on bathymetry. While the full ramifications of these changes for freshwater fish require further analysis, there is evidence that coldwater fish such as salmon and trout will be especially

sensitive to them. For example, some projections suggest that half of the wild trout population of the Appalachians will be lost; in other areas of the nation, trout losses could range as high as 90 percent (Williams et al., 2007).

Globally, precipitation is expected to increase overall, and more of it is expected to occur in extreme events and as rain rather than snow, but anticipated regional changes in precipitation vary greatly and are highly uncertain (see Chapter 8 ). As a result, major alterations of stream and lake ecosystems are forecast in coming decades, but the details remain highly uncertain (Ficke et al., 2007). Although freshwater fish and invertebrates are typically as mobile as their marine counterparts, their ability to shift their range in response to climate change may be greatly compromised by the challenges of moving between watersheds. In contrast to the rapid changes in species ranges in the sea (Perry et al., 2005), freshwater fish and invertebrates may be much more constrained in their poleward range shifts in response to climate change, especially in east-west stream systems (Allan et al., 2005; McDowall, 1992).

In the United States, per capita consumption of fish and shellfish from the sea and estuaries is more than 15 times higher than consumption of freshwater fish (EPA, 2002); nevertheless, freshwater fish are important as recreation and as food for some U.S. populations. Globally, however, freshwater and diadromous fish (fish that migrate between fresh- and saltwater) account for about a quarter of total fish and shellfish consumption (Laurenti, 2007) and in many locations serve as the predominant source of protein (Bayley, 1981; van Zalinge et al., 2000). Given the large uncertainty in how climate change impacts on freshwater ecosystems will affect the fisheries they support, this important source of food and recreation is at considerable risk.

SCIENCE TO SUPPORT LIMITING CLIMATE CHANGE BY MODIFYING AGRICULTURAL AND FISHERY SYSTEMS

Food production systems are not only affected by climate change, but also contribute to it. Agricultural activities release significant amounts of CO 2 , methane (CH 4 ), and nitrous oxide (N 2 O) to the atmosphere (Cole et al., 1997; Paustian et al., 2004; Smith et al., 2007). CO 2 is released largely from decomposition of soil organic matter by microorganisms or burning of live and dead plant materials (Janzen, 2004; Smith, 2004); decomposition is enhanced by vegetation removal and tillage of soils. CH 4 is produced when decomposition occurs in oxygen-deprived conditions, such as wetlands and flooded rice systems, and from digestion by many kinds of livestock (Matson et al., 1998; Mosier et al., 1998). N 2 O is generated by microbial processes in soils and manures, and the flux of N 2 O into the atmosphere is typically enhanced by fertilizer use,

especially when applied in excess of plant needs (Robertson and Vitousek, 2009; Smith and Conen, 2004). The 2007 IPCC assessment concluded, with medium certainty, that agriculture accounts for about 10 to 12 percent of total global human-caused emissions of GHGs, including 60 percent of N 2 O and about 50 percent of CH 4 (Smith et al., 2007). The Environmental Protection Agency (EPA) estimates that about 32 percent of CH 4 emissions and 67 percent of N 2 O emissions in the United States are associated with agricultural activities (EPA, 2009b).

Typically, the projected future of global agriculture is based on intensification—increasing the output per unit area or time—which is typically achieved by increasing or improving inputs such as fertilizer, water, pesticides, and crop varieties, and thereby potentially reducing agricultural demands on other lands (e.g., Borlaug, 2007). Given this projected intensification, global N 2 O emissions are predicted to increase by about 50 percent by 2020 (relative to 1990) due to increasing use of fertilizers in agricultural systems (EPA, 2006; Mosier and Kroeze, 2000). If CH 4 emissions grow in direct proportion to increases in livestock numbers, then global livestock-related CH 4 production is expected to increase by 60 percent up to 2030 (Bruinsma, 2003); in the United States, the EPA (2006) forecasts that livestock-related CH 4 emissions will increase by 21 percent between 2005 and 2020. Projected changes in CH 4 emissions from rice production vary but are generally smaller than those associated with livestock (Bruinsma, 2003; EPA, 2006).

The active management of agricultural systems offers possibilities for limiting these fluxes and offsetting other GHG emissions. Many of these opportunities use current technologies and can be implemented immediately, permitting a reduction in emissions per unit of food (or protein) produced, and perhaps also a reduction in emissions per capita of food consumption. For example, changes in feeds and feeding practices can reduce CH 4 emissions from livestock, and using biogas digesters for manure management can substantially reduce CH 4 and N 2 O emissions while producing energy. Changes in management of fertilizers, and the development of new fertilizer application technologies that more closely match crop demand—sometimes called precision or smart farming—can also reduce N 2 O fluxes. It may also be possible to develop and adopt new rice cultivars that emit less CH 4 or otherwise manage the soil-root microbial ecosystem that drives emissions (Wang et al., 1997). Alternatively, organic agriculture or its fusion into other crop practices may reduce emissions and other environmental problems. To date, however, there has been little research on the willingness of farmers and the agricultural sector in general to adopt practices that would reduce emissions, or on the kinds of education, incentives, and institutions that would promote their use.

Beyond limiting the trace gases emitted in agricultural practice, there are opportunities for offsetting GHG emissions more broadly by managing agricultural landscapes to absorb and store carbon in soils and vegetation (Scherr and Sthapit, 2009). For example, minimizing soil tillage yields multiple benefits by increasing soil carbon storage, improving and maintaining soil structure and moisture, and reducing the need for inorganic fertilizers, as well as reducing labor, mechanization, and energy costs. Such practices may also have beneficial effects on biodiversity and other ecosystem services provided by surrounding lands and can be made economically attractive to farmers (Robertson and Swinton, 2005; Swinton et al., 2006). Incorporating biochar (charcoal from fast-growing trees or other biomass that is burned in a low-oxygen environment) has also been proposed as a potentially effective way of taking carbon out of the atmosphere; the resulting biochar can be added to soils for storage and improvement of soil quality (Lehmann and Joseph, 2009), although there has been some debate about the longevity of the carbon storage (Lehmann and Sohi, 2008; Wardle et al., 2008). Shifting agricultural production systems to perennial instead of annual crops, or intercropping annuals with perennial plants such as trees, shrubs, and palms, could also store carbon while producing food and fiber. Biofuel systems that depend on perennial species rather than food crops could be an integral part of such a system. Research is needed to develop these options and to test their efficacy. Most important, a landscape approach would be required in order to plan for carbon storage in conjunction with food and fiber production, conservation, and other land uses and the ecosystem services they provide.

Land clearing and deforestation have been major contributors to GHG emissions over the past several centuries, although as fossil fuel use has grown, land use contributions have become proportionally less important. Still, tropical deforestation alone accounted for about 20 percent of the carbon released to the atmosphere from human activities from 2000 to 2005 (Gullison et al., 2007) and 17 percent of all long-lived GHGs in 2004 (Barker et al., 2007). Reducing deforestation and restoring vegetation in degraded areas could thus both limit climate change and provide linked ecosystem and social benefits (see Chapter 9 ). It is not yet clear, however, how such programs would interact with other forces operating on agriculture to affect overall land uses and emissions. Finally, as with all proposed emissions-limiting land-management approaches, it is critical that attention be paid to consequences for all GHGs, not just a single target gas (Robertson et al., 2000), and to all aspects of the climate system, including reflectivity of the land surface (Gibbard et al., 2005; Jackson et al., 2008), as well as co-benefits in conservation, agricultural production, water resources, energy, and other sectors.

SCIENCE TO SUPPORT ADAPTATION IN AGRICULTURAL SYSTEMS

The ability of farmers and the entire food production, processing, and distribution system to adapt to climate change will contribute to, and to some extent govern, the ultimate impacts of climate change on food production. Adaptation strategies may include changes in location as well as in-place changes such as shifts in planting dates and varieties; expansion of irrigated or managed areas; diversification of crops and other income sources; application of agricultural chemicals; changes in livestock care, infrastructure, and water and feed management; selling assets or borrowing credit (Moser et al., 2008; NRC, 2010a; Wolfe et al., 2008). At the broadest level, adaptation also includes investment in agricultural research and in institutions to reduce vulnerability. This is because the ability of farmers and others to adapt depends in important ways on available technology, financial resources and financial risk-management instruments, market opportunities, availability of alternative agricultural practices, and importantly, access to, trust in, and use of information such as seasonal forecasts (Cash, 2001; Cash et al., 2006a). It also depends on specific institutional arrangements, including property rights, social norms, trust, monitoring and sanctions, and agricultural extension institutions that can facilitate diversification (Agrawal and Perrin, 2008). Not all farmers have access to such strategies or support institutions, and smallholders—especially those with substantial debt, and the landless in poor countries—are most likely to suffer negative effects on their livelihoods and food security. Smallholder and subsistence farmers will suffer complex, localized impacts of climate change (Easterling et al., 2007).

Integrated assessment models, which combine climate models with crop models and models of the responses of farmers and markets, have been used to simulate the impacts of climate changes on productivity and also on factors such as farm income and crop management. Some modeling studies have included adaptations in these integrated assessments (McCarl, 2008; Reilly et al., 2003), for example by adjusting planting dates or varieties and by reallocating crops according to changes in profitability. For the United States, these studies usually project very small effects of climate change on the agricultural economy, and, in some regions, positive increases in productivity and profitability (assuming adaptation through cropping systems changes). As noted earlier with regard to climate-crop models, assessments have not yet included potential impacts of pests and pathogens or extreme events, nor have they included site- and crop-specific responses to climate change or variations. Moreover, even integrated assessment models that include adaptation do not include estimates of rates of technological change, costs of adaptation, or planned interventions (Antle, 2009). Thus, our understanding of the effects climate change will have on U.S. agriculture and on

international food supplies, distribution, trade, and food security remains quite limited and warrants further research.

As they have in the past, both autonomous adaptations by farmers and planned interventions by governments and other institutions to facilitate, enable, and inform farmers’ responses will be important in reducing potential damages from climate change and other related changes. Investments in crop development, especially in developing countries, have stagnated since the 1980s (Pardey and Beintema, 2002), although recent investments by foundations may fill some of the void. Private-sector expenditures play an important role, especially in developed countries, and some companies are engaging in efforts to develop varieties well suited for a changing climate (Burke et al., 2009; Wolfe et al., 2008).

Government investments in new or rehabilitated irrigation systems (of all sizes) and efficient water use and allocation technologies, transportation infrastructure, financial infrastructure such as availability of credit and insurance mechanisms (Barnett et al., 2008; Gine et al., 2008; World Bank, 2007), and access to fair markets are also important elements of adaptation (Burke et al., 2009). Likewise, investments in participatory research and information provision to farmers have been a keystone of past agricultural development strategies (e.g., through extension services in both developed and developing countries) and no doubt will remain so in the future. Finally, the provision of social safety nets (e.g., formal and informal sharing of risks and costs, labor exchange, crop insurance programs, food aid during emergencies, public works programs, or cash payments), which have long been a mainstay of agriculture in the developed world, will remain important (Agrawal, 2008; Agrawal and Perrin, 2008). These considerations need to be integrated into development planning.

It is important that agriculture be viewed as an integrated system. As noted above, the United States and the rest of the world will be simultaneously developing strategies to adapt agriculture to climate change, to utilize the potential of agricultural practices and other land uses to reduce the magnitude of climate change, and to increase agricultural production to meet rising global demands. With careful analysis and institutional design, these efforts may be able to complement one another while also enhancing our ability to improve global food security. However, without such integrated analysis, various practices and policies could easily work at cross purposes, moving the global food production system further from, rather than closer to, sustainability. For example, increased biofuel production would decrease reliance on fossil fuels but could increase demand for land and food resources (Fargione et al., 2008).

FOOD SECURITY

Food security is defined as a “situation that exists when all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (Schmidhuber and Tubiello, 2007). The four dimensions of food security are availability (the overall ability of agricultural systems to meet food demand), stability (the ability to acquire food during income or food price shocks), access (the ability of individuals to have adequate resources to acquire food), and utilization (the ability of the entire food chain to deliver safe food). Climate change affects all four dimensions directly or indirectly; all can be affected at the same time by nonclimatic factors such as social norms, gender roles, formal and informal institutional arrangements, economic markets, and global to local agricultural policies. For example, utilization can be affected through the impact of warming on spoilage and foodborne disease, while access can be affected by changing prices in the fuels used to transport food. Most studies have focused on the first dimension—the direct impact of climate change on the total availability of different agricultural products. Models that account for the other three dimensions need to be developed to identify where people are most vulnerable to food insecurity (Lobell et al., 2008; see also Chapter 4 ).

Because the food system is globally interconnected, it is not possible to view U.S. food security, or that of any other country, in isolation. Where food is imported—as is the case for a high percentage of seafood consumed in the United States—prices and availability can be directly affected by climate change impacts in other countries. Climate change impacts anywhere in the world potentially affect the demand for agricultural exports and the ability of the United States and other countries to meet that demand. Food security in the developing world also affects political stability, and thereby U.S. national security (see Chapter 16 ). Food riots that occurred in many countries as prices soared in 2008 are a case in point (Davis and Belkin, 2008). Over the past 30 years, there has been dramatic improvement in access to food as real food prices have dropped and incomes have increased in many parts of the developing world (Schmidhuber and Tubiello, 2007). Studies that project the number of people at risk of hunger from climate change indicate that the outcome strongly depends on socioeconomic development, since affluence tends to reduce vulnerability by enlarging coping capacity (Schmidhuber and Tubiello, 2007). Clearly, international development strategies and climate change are inextricably intertwined and require coordinated examination.

RESEARCH NEEDS

Given the challenges noted in the previous section, it is clear that expanded research efforts will be needed to help farmers, development planners, and others engaged in the agricultural sector to understand and respond to projected impacts of climate change on agriculture. There may also be opportunities to limit the magnitude of future climate change though changes in agricultural practices; it will be important to link such strategies with adaptation strategies so they complement rather than undermine each other. Identifying which regions, human communities, fisheries, and crops and livestock in the United States and other parts of the world are most vulnerable to climate change, developing adaptation approaches to reduce this vulnerability, and developing and assessing options for reducing agricultural GHG emissions are critical tasks for the nation’s climate change research program. Focus is also needed on the developing world, where the negative effects of climate change on agricultural and fisheries production tend to coincide with people with low adaptation capacity. Some specific research areas are listed below.

Improve models of crop response to climate and other environmental changes. Crop plants and timber species respond to multiple and interacting effects—including temperature, moisture, extreme weather events, CO 2 , ozone, and other factors such as pests, diseases, and weeds—all of which are affected by climate change. Experimental studies that evaluate the sensitivity of crops to such factors, singly and in interaction, are needed, especially in ecosystem-scale experiments and in environments where temperature is already close to optimal for crops. Many assessments model crop response to climate-related variables while assuming no change in availability of water resources, especially irrigation. Projections about agricultural success in the future need to explicitly include such interactions. Of particular concern are assumptions about water availability that include consideration of needs by other sectors. The reliability of water resources for agriculture when there is competition from other uses needs to be evaluated in the context of coupled human-environment systems, ideally at regional scales. Improved understanding of the response of farmers and markets to production and prices and also to policies and institutions that affect land and resource uses is needed; incorporation of that information in models will aid in designing effective agricultural strategies for limiting and adapting to climate change.

Improve models of response of fisheries to climate change. Sustainable yields from fisheries require matching catch limits with the growth of the fishery. Climate variation already makes forecasting the growth of fish populations difficult, and future climate change will increase this critical uncertainty. Studies of connections between

climate and marine population dynamics are needed to enhance model frameworks for fisheries management. In addition, there is considerable uncertainty about differences in sensitivity among and within species to ocean acidification (NRC, 2010f). This inevitable consequence of increasing atmospheric CO 2 is poorly understood, yet global in scope. Most fisheries are subject to other stressors in addition to warming, acidification, and harvesting, and the interactions of these other stresses need to be analyzed and incorporated into models. Finally, these efforts need to be linked to the analysis of effective institutions and policies for managing fisheries.

Expand observing and monitoring systems. Satellite, aircraft, and ground-based measures of changes in crops yields, stress symptoms, weed invasions, soil moisture, ocean productivity, and other variables related to fisheries and crop production are possible but not yet carried out systematically or continuously. Monitoring of the environmental and social dynamics of food production systems on land and in the oceans is also needed to enable assessments of vulnerable systems or threats to food security. Monitoring systems will require metrics of vulnerability and sustainability to provide early warnings and develop adaptation strategies.

Assess food security and vulnerability in the context of climate change. Effective adaptation will require integration of knowledge and models about environmental as well as socioeconomic systems in order to project regional food supplies and demands, understand appropriate responses, to develop institutional approaches for adapting under climate variability and climate change, and to assess implications for food security (NRC, 2009k). Scenarios that evaluate implications of climate change and adaptation strategies for food security in different regions are needed, as are models that assess shifting demands for meat and seafood that will influence price and supply. Approaches, tools, and metrics are needed to assess the differential vulnerability of various human-environment systems so that investments can be designed to reduce potential harm (e.g., through interventions such as the development of new crop varieties and technologies, new infrastructure, social safety nets, or other adaptation measures). A concerted research effort is needed both for conducting assessments and to support the development and implementation of options for adaptation. Surprisingly, relatively little effort has been directed toward identification of geographic areas where damages to agriculture or fisheries could be caused by extreme events (hurricanes, drought, hypoxia); where there is or will be systematic loss of agricultural area due to sea level rise, erosion, and saltwater intrusion; or where there will be changes in average conditions (e.g., extent of sea ice cover, and warming of areas that are now too cold for agriculture) that could lead to broad-scale changes—positive or negative—in the type and manner of agricultural and fisheries production.

Evaluate trade-offs and synergies in managing agricultural lands. Improved integrated assessment approaches and other tools are needed to evaluate agricultural lands and their responses to climate change in the context of other land uses and ecosystem services. Planning approaches need to be developed for avoiding adaptation responses that place other systems (or other generations) at risk—for example, by converting important conservation lands to agriculture, allocating water resources away from environmental or urban needs, or overuse of pesticides and fertilizers. Integrated assessments would help to evaluate both trade-offs (e.g., conservation versus agriculture) and co-benefits (e.g., increasing soil carbon storage while also enhancing soil productivity and reducing erosion) of different actions that might be taken in the agricultural sector to limit the magnitude of climate change or adapt to its impacts.

Evaluate trade-offs and synergies in managing the sea. The oceans provide a wide range of services to humans, but conflicts over use of the oceans are often magnified because of the absence of marine spatial planning and relatively weak international marine regulatory systems. Efforts to limit the magnitude of climate change are causing society to consider the sea for new sources of energy (e.g., waves, tides, thermal gradients), while the opening of ice-free areas in the Arctic is encouraging exploration of offshore reserves of minerals and fossil fuels. Without analyses of the looming tradeoffs between these emerging uses and existing services, such as fisheries and recreation, conflicts will inevitably grow. New approaches for analyses of such trade-offs are needed as an integral component of marine spatial planning.

Develop and improve technologies, management strategies, and institutions to reduce GHG emissions from agriculture and fisheries and to enhance adaptation to climate change. Research on options for reducing emissions from the agricultural sector is needed, including new technologies, evaluation of effectiveness, costs and benefits, perceptions of farmers and others, and policies to promote implementation. Technologies such as crop breeding and new cropping systems could dramatically increase the sector’s adaptive capacity. Research on the role of entitlements and institutional barriers in influencing mitigation or adaptation responses; the effectiveness of governance structures; interactions of national and local policies; and national security implications of climate-agriculture interactions are also needed.

Climate change is occurring, is caused largely by human activities, and poses significant risks for—and in many cases is already affecting—a broad range of human and natural systems. The compelling case for these conclusions is provided in Advancing the Science of Climate Change , part of a congressionally requested suite of studies known as America's Climate Choices. While noting that there is always more to learn and that the scientific process is never closed, the book shows that hypotheses about climate change are supported by multiple lines of evidence and have stood firm in the face of serious debate and careful evaluation of alternative explanations.

As decision makers respond to these risks, the nation's scientific enterprise can contribute through research that improves understanding of the causes and consequences of climate change and also is useful to decision makers at the local, regional, national, and international levels. The book identifies decisions being made in 12 sectors, ranging from agriculture to transportation, to identify decisions being made in response to climate change.

Advancing the Science of Climate Change calls for a single federal entity or program to coordinate a national, multidisciplinary research effort aimed at improving both understanding and responses to climate change. Seven cross-cutting research themes are identified to support this scientific enterprise. In addition, leaders of federal climate research should redouble efforts to deploy a comprehensive climate observing system, improve climate models and other analytical tools, invest in human capital, and improve linkages between research and decisions by forming partnerships with action-oriented programs.

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Fishing as a livelihood, a way of life, or just a job: considering the complexity of “fishing communities” in research and policy

• Original Research
• Published: 10 August 2022
• Volume 33 , pages 265–280, ( 2023 )

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• Claudia E. Delgado-Ramírez 1 ,
• Yoshitaka Ota 2 &
• Andrés M. Cisneros-Montemayor   ORCID: orcid.org/0000-0002-4132-5317 3  

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In the scientific literature on fisheries, the concept of community is often used broadly to indicate a place-based group whose members are dedicated to fisheries and have relatively homogeneous economic, social, and cultural interests. However, this categorical perspective to scope a “fishing community” is not necessarily an insightful approach to explore diverse social relationships with the marine environment, fishwork, and management in a practical context, and risks mismatches with science-based recommendations for management and policy. Drawing from ethnographic work, we highlight different historical and cultural dynamics from four case studies from fisheries in northwest Mexico. We identify key factors that help contextualize fishwork relationships, related to the importance of fishing practices on worldviews, daily routines, and income. These are used to derive three configurations (livelihood, way of life, and job) that describe and give analytical content to the notion of these fishing communities. Our use of a typology is not intended to generalize them or provide universal categories, but rather to convey to a broad range of fisheries scientists the importance of considering social contexts in the places in which we work and learn, and a set of guiding questions that may help in this regard. Contextualizing the importance of historical and cultural factors in scoping community units beyond occupational or geographical characteristics is essential for identifying and addressing (in)equitable processes and outcomes in fisheries sectors, research, and management.

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Acknowledgements

The authors acknowledge support from the Nippon Foundation Ocean Nexus Center at EarthLab, University of Washington. We thank Dr. Pedro González-Espinosa for his help preparing Figure 1 .

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Delgado-Ramírez, C.E., Ota, Y. & Cisneros-Montemayor, A.M. Fishing as a livelihood, a way of life, or just a job: considering the complexity of “fishing communities” in research and policy. Rev Fish Biol Fisheries 33 , 265–280 (2023). https://doi.org/10.1007/s11160-022-09721-y

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Introduction, review approach, key findings, category i: well-established science and advice topics in ices, category ii: less-established science and advice topics in ices, discussion: future perspectives, identifying operational fleet capacity targets and capacity adjustment strategies, informing policy on key interactions determining fisheries responses to management, acknowledgements, conflict of interest, author contributions, data availability, integrating economics into fisheries science and advice: progress, needs, and future opportunities.

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O Thébaud, J R Nielsen, A Motova, H Curtis, F Bastardie, G E Blomqvist, F Daurès, L Goti, J Holzer, J Innes, A Muench, A Murillas, R Nielsen, R Rosa, E Thunberg, S Villasante, J Virtanen, S Waldo, S Agnarsson, D Castilla Espino, R Curtin, G DePiper, R Doering, H Ellefsen, J J García del Hoyo1, S Gourguet, P Greene, K G Hamon, A Haynie, J B Kellner, S Kuikka, B Le Gallic, C Macher, R Prellezo, J Santiago Castro-Rial, K Sys, H van Oostenbrugge, B M J Vastenhoud, Integrating economics into fisheries science and advice: progress, needs, and future opportunities, ICES Journal of Marine Science , Volume 80, Issue 4, May 2023, Pages 647–663, https://doi.org/10.1093/icesjms/fsad005

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While the science supporting fisheries management has generally been dominated by the natural sciences, there has been a growing recognition that managing fisheries essentially means managing economic systems. Indeed, over the past seven decades, economic ideas and insights have increasingly come to play a role in fisheries management and policy. As an illustration of this, the International Council for the Exploration of the Sea (ICES) has been actively seeking to expand the scope of its scientific expertise beyond natural sciences [another inter-governmental marine science organization which has done this over the same period is the North Pacific Marine Science organization (PICES)]. In particular, the recently created ICES Working Group on Economics set out to review current work and key future needs relating to economic research and management advice on marine capture fisheries. This article presents the results of this review and addresses how economic research can be incorporated into the science of ICES to provide integrated perspectives on fisheries systems that can contribute to the provision of advice in support of policy development and management decision-making for sustainable uses of living marine resources.

Over the past seven decades, economic ideas and insights have increasingly come to play a role in fisheries management and policy. Central to the early development of this literature, Gordon ( 1954 ) and Scott ( 1955 ) laid the foundations of the economic rationale for fisheries management by contrasting resource extraction under open access with optimal management aimed at maximizing economic yield. Clark and Munro ( 1975 ) also studied fisheries management as a capital theory problem, allowing economists to use a diversity of well-developed analytical tools to evaluate the efficient intertemporal use of fishery resources. Extending the discrete choice random utility model developed by (McFadden, 1974 ), (Eales and Wilen, 1986 ) and later (Holland and Sutinen, 2000 ) demonstrated the capacity to predict location choices in commercial fisheries. Location choice models have also been applied to the study of recreational fisheries (Bockstael and Opaluch, 1983 ; Bockstael et al ., 1989 ; McConnell et al ., 1995 ). For an extensive review of applied location choice models, see Girardin et al . ( 2017 ). Key to these and other contributions has been the increasing availability of economic data and the ability of economics to grapple with the identification of incentives driving fisher behaviour, as well as the evaluation of the costs and benefits associated with policy interventions.

In many instances, economic analyses have actively informed policy design (Wilen, 2000 ; Anderson, 2015 ), although scholars have noted that the full potential for contributions of fisheries economics to policy has yet to be realized (Hanna, 2011 ; Knapp, 2012 ). Underlying fisheries economics contributions is the recognition that how different policy options interact with stakeholders’ incentives impacts the likelihood of achieving management objectives. For example, early economic studies of fisheries management under an industry-wide total allowable catch (TAC) provided an understanding of harvesters’ incentives to further engage in capital investment (so-called “capital stuffing”), with the resulting race to fish and dissipation of profit (Homans and Wilen, 1997 ). Other studies emphasized the incentives for input substitution in input-managed fisheries, questioning the usefulness of such controls in practice (Dupont, 1991 ). Many fisheries policy innovations were introduced in light of these economic insights, in particular the various approaches for allocating harvest rights to different user groups (Shotton, 2001 ; OECD, 2006 ). The work of (Christy, 1973 ) was instrumental to the introduction of Individual Transferable Quotas (ITQs), which has become a widespread tool for fisheries management. In such management regimes, rather than setting industry-wide catch limits only, the regulator allocates individual catch shares with the intent that these will provide fishermen with more secure rights to fish, thereby limiting perverse incentives (Costello et al ., 2008 ).

Given that efficient allocation of scarce resources is central to economics (Samuelson et al ., 2019 ), assessing trade-offs is consubstantial to the discipline. Indeed, trade-off analysis is embedded in how economists quantify economic value. As a measure of value, economists typically use differences in net benefits from a policy intervention compared to no policy, or differences in net benefits with and without a shock to the system such as an ecological disturbance or an industrial accident (e.g. an oil spill). In supporting fisheries management, application of economic analysis has largely focused on informing decisions on how to best allocate limited resources such as time, capital, and fish stocks to attain the highest net benefits to society (see e.g. Dichmont et al ., 2010 ; Pereau et al ., 2012 ; Guillen et al ., 2013 ). Economic analysis has also paid attention to costs in fisheries, both fixed and variable, and how these can help understand the development of the industry and the influence of policy (e.g. Sala et al ., 2018 ).

In setting the general principles that allow understanding of incentives and trade-offs, early fisheries economics work was largely normative and theoretical (Wilen, 2000 ). Research over the past three decades has seen a strong development of empirical research, with increasing availability of empirical information and computing power (Andersen, 2013 ), as well as the recruitment of economists working in national marine laboratories. A number of complex bio-economic methods and models have also recently been developed and implemented for different fisheries around the world (see Nielsen et al ., 2018a for a review and Thébaud et al ., 2014 for a discussion of key challenges). In contrast to earlier economic literature focusing on stylized biological models, the population dynamics in these models are of similar complexity to stock assessment models currently used in fishery advice. As a result, this new literature has significantly contributed to bridging the gap between ecological and economic perspectives on fishery systems (Doyen et al ., 2013 ; Nielsen et al ., 2018a ). For example, in Australia, where the policy objective is set to achieve maximum economic yield (MEY) in commercial fisheries, bio-economic models are used on a regular basis to support management decisions (Dichmont et al ., 2010 ; Pascoe et al ., 2014 ; Pascoe et al ., 2016 ). In the northeast US Gulf of Maine, bio-economic models of recreational fisher behaviour are used to set annual management specifications for Atlantic cod ( Gadus morhua ) and Atlantic haddock ( Melanogrammus aeglefinus ) stocks (Lee et al ., 2017 ). Indeed, the application of fisheries economics has been able to rely on a growing diversity of economic models and data, including the collection of cost and earnings data for commercial fishing operations (Thunberg et al ., 2015 ; STECF, 2020 ; Werner et al ., 2020 ). Other techniques enable economists to assess the welfare changes associated with policy interventions on non-market ecosystem services (ES), such as surveys of willingness to pay for the conservation of marine protected species that interact with fisheries (Wallmo and Lew, 2012 ).

While the science supporting fisheries management has generally been dominated by the natural sciences, there has been a growing recognition among natural scientists (Hilborn, 2007 ) that managing fisheries means managing economic and social systems (Charles, 2005 ). Indeed, international guidelines have increasingly highlighted the need to account for ecological, economic, and social goals in managing fisheries for sustainability as part of ecosystem-based fisheries management (Pikitch et al ., 2004 ). This resulted in the explicit inclusion of socio-economic considerations in fisheries policies around the world as well as in scientific advice, leading, for example, to initial discussions on incorporating fisheries economics into the work of the International Council for the Exploration of the Sea (ICES) as far back as 1971 (ICES, 2003 ). It is only in recent years, however, that efforts by ICES have materialized to expand the scope of scientific expertise to incorporate contributions from the social sciences. According to its current strategic plan (ICES. 2021. Strategic Plan. 18 pp. http://doi.org/10.17895/ices.pub.7460 ), the vision of ICES is “to be a world-leading marine science organization, meeting societal needs for impartial evidence on the state and sustainable use of our seas and oceans”. Based on this vision, ICES defines its mission as advancing and sharing scientific understanding of marine ecosystems and the services they provide, and using this knowledge to generate state-of-the-art advice for meeting conservation, management, and sustainability goals. This has led ICES to broaden its scientific priorities (ICES, 2019: Strategic Plan, pp. 18–19, https://issuu.com/icesdk/docs/ices_stategic_plan_2019_web ), which now include elucidating the present and future states of not only natural but also social systems, placing the understanding of human behaviour, incentives, and values as central to the work of the organization.

These priorities have led to a move towards the broadening of the science-base of ICES to fully include social sciences, and to discussions on how to expand upon the conventional information basis largely centred on biological/ecological information to more explicit consideration of the social and economic dimensions associated with policy development and management choices. This inclusion of a marine socio-ecological systems perspective (Link et al ., 2017 ) has led to new initiatives within ICES, including the Strategic Initiative on Human Dimensions (SIHD: https://www.ices.dk/community/groups/Pages/SIHD.aspx ) and the initiation of new working groups, including the Working Group on Economics (WGECON). These efforts have been undertaken to promote progress in the integration of economics into ICES science and advice. As one of its first tasks, WGECON (see https://www.ices.dk/community/groups/Pages/WGECON.aspx ) set out to review the status and progress made in applying fisheries economics in ICES marine areas to policy topics and research of relevance to fisheries managers.

This article presents the results of this review. Through examination of a selection of key topics of current ICES and global relevance to fisheries science and policy, we illustrate how economic research can provide an improved understanding of the ways in which fisheries develop and respond to change and of the trade-offs associated with alternative scenarios and management strategies. As such, the article addresses the question of how contributions from economic research can be incorporated into the scientific advice of an organization such as ICES, eventually contributing to informing policy development and management decision-making for sustainable uses of living marine resources.

Section 2 presents the review approach, based on consultation with experts in the field and a systematic process of synthesizing and reviewing the state of the art in applied fisheries economics research. Section 3 presents a synthesis of the extent to which existing research is currently used in supporting fisheries policy. We show that a strong body of applied fisheries economics research exists, covering a broad range of topics at the core of fisheries management, but that only some of this work is incorporated in the advice supporting policy implementation. Section 4 identifies the potential for further developments of direct relevance to the science supporting management advice internationally. We conclude by highlighting the key steps that can be taken to support a stronger integration of economics into fisheries science and advice.

The review relied mainly on expert assessment drawn from the expertise of WGECON, a group composed of >50 economists and fisheries experts from 16 countries, including European and North American researchers specializing in marine living resource economics. The group met annually from 2018 to 2020 and established an initial list of 12 key contemporaneous commercial fishery management topics central to economic research and analyses that were perceived to be of high relevance to ICES scientific and advisory work.

For each of these topics, the members of the group reviewed both current and future research priorities. The group first considered the research currently conducted and advice provided as part of ICES work and more broadly in fisheries management, including the economic issues relating to the topic that economists have examined, the evaluation methods and tools available, as well as the data available and indicators used. Next, the group assessed key future needs for research and integration into ICES science, including issues and questions that could be documented, evaluation methods and tools that should be developed, data and indicators that needed to be made available, and the associated information flow from research to policy support.

The information collected from group members was first compiled in shorthand format for each topic. Based on these synthetic reports, sub-groups, typically consisting of two moderators and two reviewers, developed revised and elaborated report texts and summary sheets for each topic (see Supplementary Material Section B ). The reports and summary sheets were systematically reviewed by at least two other members of the group, leading to revised summary sheets and report text. A final round of revisions was carried out during a final meeting where both moderators and reviewers participated in the process, leading to the material presented in this article.

The identified topics were classified into two broad categories ( Table 1 ). The first category was commercial fisheries management topics, on which ICES science and advice are well established in disciplines other than economics. These topics were ordered from the older, standard topics to the more recent and complex ones. The second category was topics the group perceived to be important to consider for sustainable fisheries yet not commonly included in the standard science supporting advice. These topics were ranked by increasing level of complexity.  Table 1 summarizes the topics in both categories and the key research questions addressed under each.

Topics considered in the review.

The connections between these different topics were repeatedly and extensively discussed by the group, highlighting the importance of bringing the different topics under each category into integrated approaches in order to inform fisheries management.  Figure 1 summarizes the 12 topics considered in the review and illustrates the interconnectedness between them, which is also reflected in the key findings section hereafter.

Graphical representation of the topics for science and advice considered in the review. See  Table 1 for the identification of questions addressed under each of the topics illustrated.

To complement the work of the expert group, an international survey among fisheries economists was carried out in collaboration with the European Association of Fisheries Economists (EAFE) during 2019. Members of the North American Association of Fisheries Economists (NAAFE) were also invited to respond. The aim of the survey was to evaluate whether the key topics identified by the WGECON experts were indeed representative of the core contributions that fisheries economics can provide to support management advice, and to identify any other topics that should also be included. Survey respondents were asked about key fishery economic topics and were asked to rank the relative importance of each of these topics in terms of research and management advice. The survey was conducted through an online form that was circulated to the EAFE and NAAFE mailing lists. To increase the response rate and discuss preliminary results, a specific session was organized during the 2019 EAFE Conference in Santiago de Compostela, Spain. Additionally, a presentation of WGECON and the survey were given during the 2019 NAAFE Forum in Halifax, Canada. Additional paper questionnaires were also administered to survey participants during the two conferences.

In total, 36 responses to the survey were collected through fisheries economics networks. Responses confirmed the list of 12 topics but also identified the major additional, cross-cutting theme of climate change impacts that is mobilizing increasing research attention in the profession (other emerging topics such as pollution, regionalization of management, and coastal community studies were mentioned as important topics for future work). Because of its cross-cutting nature, this was not included as a separate topic in the review but rather considered in terms of how research on the 12 topics might assist in addressing the issues arising from climate-related impacts on ecosystems and the economy.

The results of the review for the 12 key topics are summarized in this section, highlighting the advances in applied fisheries economic research that are relevant to ICES work.  Table 2 provides a qualitative overview of the assessment by WGECON of the degree to which research on these topics has advanced to a stage where the key issues relating to each topic are being addressed, both in research as well as in management advice. This assessment includes the methods, tools, data, and indicators that have been developed and are being used in formal advisory processes at national and/or international levels. In what follows, we provide the main arguments for these assessments for each of the 12 topics, as well as selected key references to the relevant state-of-the-art literature in fisheries economics. For more detailed assessment information and additional references to literature published outside the economics journals on each topic, the reader is referred to Section A of the Supplementary Material .

Progress in the availability and use in advice of work on issues, methods, and tools, and data and indicators for each topic, within and outside ICES.

Colour scale indicates the extent to which the research is available and used/applied in the science supporting the advice, according to the views of the expert group. Dark green: used/applied; Medium green: fully available; light green: only partially available. “Within ICES” refers to research that is being conducted within ICES member countries. “Outside ICES” refers to research that is being conducted in countries outside ICES.

Topic I: TAC setting in output-based management systems

Early fisheries economics research largely centred on redirecting attention from the strictly biological focus of fisheries science to consideration of issues such as wealth dissipation, fleet misallocation, or the low income of fishers (Scott, 1989 ). Efforts thus focused on extending the biological production function and its response to alternative regulatory regimes (Clark and Munro, 1975 ; Clark, 1980 ; Scott, 1989 ). At the same time, output controls such as TAC limits were becoming a common instrument to help sustain fisheries harvests internationally, with strong developments in the science of population dynamics. Earlier economic work studied how TACs can interact with fleet incentives to result in overcapacity and reduced economic returns (Homans and Wilen, 1997 ). With the growing availability of economic data on fishing activities, a range of applied bio-economic models were developed and are being used to inform management. However, with some notable exceptions (Dichmont et al ., 2010 ; Pascoe et al ., 2016 ), these models have mainly focused on impact assessments, evaluating the economic consequences of alternative TACs set based on biological objectives, either achieving maximum sustainable yield or avoiding unwanted biological outcomes of fishing (see Supplementary Material for references to the large body of literature that has developed in this field in the ICES context). In parallel, significant steps have been made in the bio-economic modelling literature to build directly on the biological models routinely used to inform TAC setting, in particular age- or size-structured models of fish population dynamics (Pascoe and Mardle, 2001 ; Tahvonen, 2009 ; Macher et al ., 2018 ; Tahvonen et al ., 2018 ). Given that they largely capture the key dimensions considered in identifying fishing mortality targets in fisheries management advice, we argue that these models can be directly used to examine strategies that consider economic objectives, including MEY (Grafton et al ., 2010 ). With the increased availability of economic data on fishing fleets across ICES regions, these models constitute a strong set of tools for addressing many of the research questions identified under the different topics that follow.

Topic II: mixed species fisheries management

Models have been applied to the question of managing so-called mixed fisheries, where fleets targeting mixes of species interact through differing levels of contributions to the mortality of given fish stocks in given areas and seasons while also differing in their levels of economic dependency on these stocks (Holland and Sutinen, 2000 ). This has led to further empirical analysis of the structure of profit functions in fisheries and to a better understanding of observed industry structures and their evolution over time (Squires, 1988 ; Weninger, 2001 ). Research has also focused on aggregate fishery-level production relationships to determine the economic importance of bycatch species in a fishery and optimal bycatch rules (Larson et al ., 1998 ). Economic models of bycatch have included incentives that may exist in multi-species fisheries for fishermen to modify their fishing strategies (Birkenbach et al ., 2020 ), as well as responses to TAC and quota allocation decisions for target and bycatch species (Marchal et al ., 2011 ; Holzer and DePiper, 2019 ). A broad range of simulation methods have been developed for evaluating the sustainability and distributional effects of management strategies pursuing biological targets such as single stock MSY (and associated ranges) or multi-species MSY, as well as economic targets such as single- and multi-fleet MEY and/or social targets such as employment (Voss et al ., 2014 ; Ulrich et al ., 2016 ; Nielsen et al ., 2018a ). Multi-criteria assessment methods, such as viable control, have been developed to evaluate strategies satisfying a set of ecological, social, and economic constraints (Gourguet et al ., 2013 ; Doyen et al ., 2017 ; Briton et al ., 2020 ). Recent modelling efforts make use of the latest biological and economic knowledge to examine the benefits of strategies aimed at economic multispecies management objectives as well as dealing with variability and uncertainty (Lagarde et al ., 2018 ; Voss et al ., 2021 ). However, while these methods and tools are widely available and have been used to support management in other parts of the world, to date they have not generally been used in management advice at ICES.

Topic III: area-based and spatial management

As the importance of spatial structure in the distribution of fish populations and the need to account for this in designing spatially explicit management measures has become increasingly acknowledged, so has research focused on describing, explaining, and predicting the spatial allocation of fishing activities and their interactions with the spatial dynamics of fish resources (Eales and Wilen, 1986 ; Sanchirico and Wilen, 1999 ; Holland and Sutinen, 2000 ; Smith, 2000 ; Smith et al ., 2009 ; Dépalle et al ., 2021 ). The analyses have particularly been used to examine the potential bio-economic consequences of spatial management measures such as closed areas and marine protected areas (Hannesson, 1998 ), with more recent work highlighting the importance of considering economic behaviour in examining the potential benefits of such measures (Smith and Wilen, 2003 ; Haynie and Layton, 2010 ; Albers et al ., 2020 ).

In the context of ICES, recent ad hoc initiatives have examined balancing spatially resolved environmental and fisheries economics considerations; an example being the risks of habitat degradation and protective measures adopted as part of deep-sea access regulations. However, to date, ICES has not implemented any advice that incorporates economic or social considerations into spatial fisheries management. This contrasts with other regions where studies of the economic consequences of spatial management have been conducted and are being considered by advisory bodies (Bisack and Sutinen, 2006 ; Abbott and Haynie, 2012 ).

Topic IV: adjustment of capacity to resource potential

Rights-based fishery management approaches aimed at removing the race-to-fish incentives due to the common-pool nature of marine fish stocks should eliminate the need to manage fishing capacity (Homans and Wilen, 1997 ). However, the pervasiveness of policies focused on biological and social considerations has led to a need for capacity management and the development of research to support this endeavour (Pascoe, 2007a ). Economists have particularly focused on the short-term measurement of fishing capacity using output-based measures of observed production given the technical characteristics of fishing fleets and prevailing conditions in the fishery (Kirkley et al ., 2002 ). While robust methods are now available to carry out such measurements, their use to date to inform policy has remained limited. Instead, input-based definitions of fishing capacity have been predominantly used as part of multi-criteria evaluation approaches such as the EU capacity balance indicator guidelines. These guidelines require an annual evaluation of several bio-economic indicators of excess capacity of EU fleets ( https://stecf.jrc.ec.europa.eu/reports/balance ), leading to mandatory national plans to address excess capacity. Concurrently, public buyback programmes have often been seen as a preferred capacity reduction instrument, as they are voluntary and compensate industry members for capacity reductions (Pascoe, 2007a ). This has led to a large body of work investigating the outcomes of alternative designs for such programmes (Campbell, 1989 ; Weninger and McConnell, 2000 ; OECD, 2009 ; Holzer et al ., 2017 ). Factors influencing capacity, such as capital investment (including fishing rights) ownership (Nostbakken et al ., 2011 ), entry and exit dynamics of fishing capacity in fisheries (Tidd et al ., 2011 ), or technical progress in fisheries (Squires, 1992 ), have been extensively considered. Underlying these endeavours is research into the implications of governmental support policies for the fishing sector on capacity, fish stocks, and fisher welfare (Clark et al ., 2005 ; Martini and Innes, 2018 ; Smith, 2019 ). The impacts on capacity of incentive-based approaches to regulating access to fisheries resources have also rapidly developed (see Topic VII below). Finally, the alternative approach of using bio-economic models to help identify long-term target capacity levels, both in input and output terms, has also made strong advances (see Topics I and II above). The extent to which these different lines of research and sets of analytical tools can effectively inform fisheries policy and management in the ICES area, however, remains limited.

Topic V: data-limited situations

For several species, stocks, fleets, and fisheries, a lack of data limits the ability to develop appropriate fisheries management advice on matters such as limitations on levels of total catch in single or multi-species fisheries, the spatial and seasonal management of fishing, or the designation of spatial restrictions on fishing. With the growing literature on applied economic analyses of fisheries, there has been increasing acknowledgement of the information limitations and uncertainty that need to be explicitly considered in developing tools that can effectively support policy. This led to an early recognition that, even under economic, biological, and implementation uncertainty, an understanding of the likely responses of fishers to regulations could provide useful information, alongside efforts to develop more complete bio-economic approaches (Bockstael and Opaluch, 1983 ). Related research has considered the implications of uncertainty for the determination of optimal management strategies (Andersen, 1982 ; Charles and Munro, 1985 ; Sethi et al ., 2005 ; Gourguet et al ., 2014 ; Tromeur et al ., 2021 ). Studies have also focused on methods to enable economic analyses while explicitly accounting for the limited information available (Pascoe, 2007b ; Sanchirico et al ., 2008 ; Pascoe et al ., 2014 ; Gacutan et al ., 2019 ). For user groups such as small-scale and recreational fishing activities, data limitations tend to be particularly acute. A growing body of economic research has been devoted to providing a better understanding of these sectors (Zeller et al ., 2006 ; Schuhbauer and Sumaila, 2016 ; Abbott et al ., 2022 ).

Topic VI: shared stocks management

A further extension of fisheries economics has dealt with the added complexity associated with managing fisheries that are shared by several states, with potentially conflicting management strategies due to diverging incentives for fish stock preservation, fishing effort costs, or consumer preferences (Munro, 1979 ). Building on game theory, approaches to eliciting the likely outcomes of international fisheries management have been proposed (Bailey et al ., 2010 ; Hannesson, 2011 ; Costello and Molina, 2021 ), with a growing number of empirical applications. Empirical analysis has also shown that the status of fisheries dependent on shared stocks is generally poorer than that of fisheries under single jurisdictions (McWhinnie, 2009 ). Despite the insights economic research provides into the determinants of international fisheries management, this research has remained largely academic with few actual applications to policy.

Topic VII: fishing rights allocation

Fishing rights, in particular quota allocation, are a key foundation of many fisheries and their management in ICES member countries. In many ways, rights-based management represents the interplay between traditional ICES biological advice and how management bodies implement that advice. Economics can play a key role in helping understand this interplay, especially in relation to the political economy of converting scientific advice into fishing opportunities (Bellanger et al ., 2016 ). Fisheries economic research on fishing rights has focused on both conceptual (Arnason, 1990 ; Boyce, 2004 ; Costello and Deacon, 2007 ) and empirical applications examining the rationalization of commercial fisheries using ITQs (Dupont et al ., 2002 ; Weninger and Waters, 2003 ; Grainger and Costello, 2016 ; Birkenbach et al ., 2017 ). Economic research has in fact investigated a broad range of rights-based management approaches (Shotton, 2001 ; Costello and Kaffine, 2008 ; Thébaud et al ., 2012 ), including territorial use rights (Wilen et al ., 2012 ). Further extensions of fishing rights research have included allocation between commercial and recreational fisheries in the presence of incompletely defined rights (Holzer and McConnell, 2014 ) and defining temporal fishing allocations taking into account the finer spatial and temporal scales at which the race to fish may occur (Huang and Smith, 2014 ). Despite this strong scientific expertise and active research efforts, which are being undertaken in ICES countries on the processes by which fishing rights are allocated among individual fishers, economic analysis of the biological, economic, and social impacts of fishing rights has typically not been included in the research undertaken by ICES or in the advice it produces.

Topic VIII: sustainability of small-scale fisheries (SSF)

With the global quest for sustainable fisheries, international interest has developed regarding the economic, social, and ecological impacts of small-scale fisheries. The reasons for this interest are manifold. First, while a large fraction of the fisheries management research has historically focused on large-scale fishing activities, relatively less attention has been granted to SSF, despite the fact that these have been shown to represent significant sources of food and employment, as well as important cultural services, in many regions of the world (Zeller et al ., 2006 ; Schuhbauer and Sumaila, 2016 ). Second, the observed impacts of fisheries management regimes on rural and remote coastal communities that depend on fisheries have also raised growing concerns (Copes and Charles, 2004 ; Sutherland and Edwards, 2022 ). Third, SSF tend to operate in areas in high demand for other sectors (e.g. recreational activities, aquaculture, renewable energy, coastal development), which often leads to spatial conflicts. Fourth, a branch of research has developed that emphasizes the potential role of institutional regimes that may help address the common-pool resource problem (Schlager and Ostrom, 1992 ; Copes and Charles, 2004 ). To date, research on the economics of SSF and their management has centred on gaining an understanding of their economic, social, and biological dimensions, as well as their interactions with other activities. Key interactions of interest include other industrial fishing fleets harvesting the same stocks, recreational fisheries pursuing the same stocks or operating on the same grounds, as well as other competing sectors. This line of research has led to an increase in the knowledge base as well as the quantity and quality of SSF data available, even extending to the cultural ecosystem services associated with these fisheries (Ropars-Collet et al ., 2017 ; Andersson et al ., 2021 ). However, this information has only recently begun to be considered in the work of some ICES working groups, with a focus on the presentation of information on these fisheries and the communities that depend on them in integrated assessments.

Topic IX: links between the catch sector and markets for fish

An important focus of fisheries economics has been concerned with markets for fish. Research has particularly centred on issues such as the expected long-term drop in fish production of open access fisheries with resulting increased prices of fish (Copes, 1970 ), and on the importance of taking into account the consequences of fisheries management on consumer and producer welfare (Hanemann and Strand, 1993 ; Lee and Thunberg, 2013 ; Costello et al ., 2020 ). Economic research on market price effects has included the relationship between complementary or substitute species in the markets for fish products (Gordon et al ., 1993 ), as well as the influence of price differences on choices of markets and product forms (Asche and Hannesson, 2002 ). The economic implications of interactions between ex-vessel prices and increasing levels of processing sector concentration (Clark and Munro, 1980 ) have also been studied. In addition, over the last 20 years, economic studies have considered consumers’ preferences for fisheries certification and willingness to pay for eco-labelled seafood (Blomquist et al ., 2015 ; Fonner and Sylvia, 2015 ; Ankamah-Yeboah et al ., 2020 ), as well as the effects these consumer-driven schemes have on production systems and/or fishers’ behaviour (Roheim et al ., 2018 ). However, despite the key role of market processes in understanding the economic responses of fisheries systems to management, this research is not commonly considered in fisheries management advice internationally.

Topic X: diversification of commercial fishing

Two economic drivers for diversification of a firm are lower production costs by diversifying to similar products (economies of scope; Panzar and Willig, 1981 ) and to reduce risk by focusing on multiple products with unrelated risk profiles in line with modern portfolio theory (Markowitz, 1952 ). In fisheries, this may involve multiple fishing operations (Bockstael and Opaluch, 1983 ), such as using multiple gears to target different species (Kasperski and Holland, 2013 ), as well as expanding the range of activities to other sectors, such as tourism or processing (Nostbakken et al ., 2011 ). Diversification has implications for fisheries management since it alters the incentives driving fishing choices or strategies, depending on the opportunity costs of fishing (i.e. earnings in alternative activities). For example, fishers might increase engagement in a specific fishery during periods with low earnings in other fisheries. The regulation of diversified fisheries can also be examined from the perspective of risk management strategies (Sanchirico et al ., 2008 ; Gourguet et al ., 2014 ). Economic research has used a wide range of mathematical and statistical methods to examine diversification strategies, their impacts on incentives, and the implications for fisheries management (see, e.g. Huang and Smith, 2014 ; Holland et al ., 2017 ). This has been possible due to the availability of data for within-fisheries analyses, regarding, e.g. fishing effort, gear use, catch composition, fish prices, and operating costs. Less analysis of diversification outside the fishing sector has been possible due to the more limited availability of data regarding alternative activities to fishing. To date, despite its importance in understanding the responses of fisheries to management, this research is not regularly incorporated into fisheries management advice internationally.

Topic XI: fisheries-aquaculture connections

The analysis of interactions between wild-capture fisheries and aquaculture has also attracted research interest with respect to the ways in which the development of aquaculture may affect the status of fisheries, both conceptually (Anderson, 1985 ) and empirically (Asche et al ., 2001 ). Control over the biological process and technical development (Anderson, 2002 ; Asche, 2008 ) have led to tremendous growth in the productivity of the aquaculture industry, improving its competitiveness relative to wild fisheries (Nielsen et al ., 2021 ), for input factors (Ankamah-Yeboah et al ., 2021 ), and in the supply chain (Asche and Smith, 2018 ). Fisheries and aquaculture compete in the same global markets with common price determination processes (Anderson et al ., 2018 ); consequently, fishers and fish farmers influence each other’s incentives and strategies (Valderrama and Anderson, 2010 ). Furthermore, the sectors compete for space, and there are biological interactions in the form of genetic contamination, disease, and environmental externalities (Asche et al ., 2022 ), which lead to novel management issues (Nielsen, 2012 ). Additional interactions relate to the fishing sector providing raw materials for aquaculture in the form of feed and seeds for capture-based aquaculture (Naylor et al ., 2000 ; Tveterås and Tveterås, 2010 ). Notably, while research on the social and economic dimensions of aquaculture has steadily developed over the past two decades, leading to the formation of ICES working groups ( https://www.ices.dk/community/groups/Pages/WGSEDA.aspx ), this work has not yet specifically considered the economic interactions between fisheries and aquaculture.

Topic XII: valuation of ecosystem services

With growing concern for the scale of human impacts on the biosphere, interest has developed in combining ecology and economics to understand the interactions between ecosystems and human systems giving rise to ES (Polasky and Segerson, 2009 ). Identifying and quantifying the market and non-market services supported by ecosystems that contribute to human well-being has indeed been the focus of growing research efforts over the last 50 years, including in the marine realm (Smith, 1993 ; Costanza et al ., 1997 ; Boyd and Banzhaf, 2007 ; Bateman et al ., 2011 ; Barbier, 2012 ; Pendleton et al ., 2016 ). In this literature, commercial fisheries have been considered both a provider of provisioning and cultural ecosystem services and a sector that may impact other supporting and regulating services provided by marine ecosystems. Economic assessment of ES is usually applied in the context of ecosystem-based approaches to fisheries management (EBFM) and in support of the management of competing interests in the exploitation of marine resources. Approaches range from the measurement of the economic contribution of ecosystem functions and services through applied natural capital accounting to the integration of biological processes and functions into economic models to examine the consequences of alternative development and management patterns for fisheries. While wide-ranging internationally, comparable datasets of the monetary or non-monetary value of ES across countries do not currently exist, but initiatives to progress these data are under way as part of broader initiatives to establish reporting standards on the blue economy (Jolliffe et al ., 2021 ). Research on the understanding and valuation of ecosystem services is currently being pursued in several ICES working groups. However, to date, this work has not been incorporated into the fisheries science and advice of the organization.

Our review conveys that a large body of applied fisheries economics research has developed, especially over the past three decades, which provides information of direct relevance to various dimensions of fisheries management advice. Beyond this assessment of existing research in applied fisheries economics, the group also identified the potential for further developments of direct relevance to the science supporting management advice internationally. These are discussed below, keeping to the list of key topics that structured the review but reorganizing them into three key areas for future research and emphasizing their relevance to future developments in ICES work. These key areas are the provision of ecological-economic advice, assisting with the identification of fishing capacity targets and capacity adjustment strategies, and informing policy in relation to key interactions determining the responses of fisheries systems to management.

Providing ecological-economic advice

Models and data are now largely available to evaluate the socio-economic impacts of TAC setting by taking into account the possibilities for fishers to adjust to TAC constraints through changes in fishing strategies and fishing capacities at producer, industry, or country levels. Such an impact assessment can also address effects on markets (e.g. price responses to changed landings), uncertainties in the management system (e.g. the use of precautionary buffers), or issues of compliance. In addition to these impact assessments, we believe that existing models and data could be used to carry out ex-ante evaluations of TAC strategies to achieve bio-economic objectives such as MEY in single species fisheries, as is already routinely the case in Australia (Pascoe et al ., 2016 ). These assessments can also incorporate social goals associated with alternative management options, as has been demonstrated in applied co-viability analyses (Briton et al ., 2020 ).

Extending such analyses to the optimization of mixed-fisheries systems could also provide a broader perspective on the fishery-wide benefits associated with TAC strategies that may involve reducing single-species TACs below what would generate maximum single-species returns or yields. Standardized data, robust and validated economic methods, and integrated models allowing for the study of critical problems in mixed fisheries are available to evaluate mixed fisheries management options (Nielsen et al ., 2018a ). However, methods to track and assess the dynamic interactions that occur in mixed fisheries in response to management interventions require more research. Assessing the full impacts of mixed-fisheries management strategies requires better capturing fisher behaviour regarding the choices of gear, effort levels, and allocation of effort between areas and seasons (Hutton et al ., 2004 ; Dépalle et al ., 2021 ), as well as other vessel adaptations and resulting changes in fishing efficiency (van Putten et al ., 2012 ). Ex-post evaluations of management measures can also be used to complement ex-ante approaches and test realized outcomes against ex-ante predictions, thus helping better understand the actual industry responses to economic incentives and alternative regulatory obligations. This could inform the evaluation of alternative approaches to distributing catch across stocks and years as part of long-term management plans seeking to address issues of bycatch and discards (such as under the landing obligation in the EU). Developing methods and tools enabling stakeholder engagement in such evaluations (see, e.g. Macher et al ., 2018 ) is also likely to strengthen the uptake of evaluation results as part of adaptive management decision-making processes.

Support for the development, maintenance, and uptake of models and data seems essential to progress in this area of bio-economic advice. Standardized data collection protocols are required regarding fishing effort and landings, as well as economic data, using common dimensions regarding key fishery, fleet, and vessel characteristics. In general, the availability of information at the individual-vessel level will be preferable, as this allows data to be aggregated at any scale required. Indeed, individual-based models have been increasingly developed and applied in mixed fisheries management advice (Nielsen et al ., 2018a ), although this demands complex and very data demanding methods.

Contributing to the development of approaches to deal with data-limited situations

While bio-economic models have been developed and applied to a range of fisheries around the world, it seems unrealistic to expect that the data-rich approach of developing full analytical models for the many data-poor fish stocks will ever be possible (indeed, the cost of data collection and model development to achieve this may exceed the additional value derived from the information produced by these models). Hence, there is a need to explore new approaches that can both capture the total economic activity of the fleets (i.e. include information relating to the revenues and costs associated with the catch of all stocks) and link this to the best available understanding of the biological status of the stocks. Fisheries biologists have developed a range of data-poor methods for fisheries assessments, based on the life history characteristics of the fish caught or on catch and effort data. Similar approaches can be carried out with respect to bio-economic assessments, and initial efforts have shown that limited information on the revenues and costs associated with fishing may be used to identify reference points for the management of fisheries that take into account economic objectives (Pascoe et al ., 2014 ). With these first results in mind, economists could contribute to the efforts devoted to addressing data-limited fisheries assessments, which usually start with a meta-analysis aimed at integrating the knowledge from existing reports and data sets that may help decrease the uncertainty arising from limited data. Such knowledge can also be used to set priors in Bayesian statistical approaches, allowing to carry out value-of-information analysis and identifying the variables having an impact on the ranking of decision options and thus needing to be estimated more precisely. Further uncertainties due to data-limited situations can be described using risk assessment frameworks such as the pedigree matrix or probability-based harvest control rules (Goti-Aralucea, 2019 ). Lastly, research is also needed on how to deal with and effectively communicate uncertainty and stochasticity in assessments and advice, both in fisheries economics and in the broader field of fisheries science.

Analysing trade-offs associated with area-based and spatial management

Spatially resolved economic analysis of fisheries focuses on associating fishing stakeholders at the vessel, fleet, and community levels to chosen fishing areas and quantifying the importance of these areas in terms of catch rates and profitability. Based on behavioural change scenarios, the economic consequences of spatial restrictions on fishing on the re-allocation of effort in space and time and to métiers can be estimated (Blau and Green, 2015 ). Such preliminary analyses provide the economic information needed for trade-off analyses as well as reducing the potential for surprises in the outcomes (Wilen et al ., 2002 ). Research in ICES could incorporate existing models to assess the past performance of spatial management to project possible paths for alternative futures, as well as the fleets likely to be impacted by a proposal. This would enable impact assessment of changes in fishing pressure on the biological and ecosystem components with effects propagating to the economics of the fishery. While ICES hosts many data sets that could help condition such impact assessment models, a major obstacle would still be the limited data collection or resolution of data collected on certain variables (e.g. catch), which currently does not fit the spatial and time resolutions that matter to stakeholders and policymakers.

Increasingly, the above spatial fisheries management considerations need to be cast in the context of broader marine spatial planning aimed at allocating ocean space from an ecosystem-based management perspective (Katsanevakis et al ., 2011 ). This includes both conflicts between fisheries and other maritime activities and the potential for co-locating activities. The benefits of co-locating uses such as wind farms with fisheries have begun to be investigated (Stelzenmüller et al ., 2021 ), but very few practical examples exist. More scientific effort should be put into elucidating the possible ecological-economic effects of reserving space to windfarms, from local to overall effects on marine biodiversity and fishing opportunities (e.g. Bastardie et al ., 2014 ). While relative economic returns have only rarely been considered before introducing spatial management measures, integrating measures of economic benefits into existing ecological models would allow assessment of how these benefits may be distributed across ICES regions and among beneficiaries such as local communities, the tourism sector, or different fishing vessels. Such assessments should consider whether compensation should be considered in the course of implementing the measures as well as the timespan over which the benefits accrue and uncertainty regarding the outcomes of the spatial measures (e.g. including climate change effects). Such integrated understanding could provide new knowledge on hotly debated topics to inform policymakers’ decisions. Examples of this could include case studies documenting the possible fishing effort displacement in response to the implementation of conservation areas (e.g. in the EU, Natura 2000 designated areas) that might require costly short-run adaptation of fishing strategies balanced with possible long-term benefits from improved productivity of the exploited ecosystem (e.g. Bastardie et al ., 2020 ). Another example would be the evaluation of large-scale exclusion scenarios such as those associated with “Brexit” that would lead to excluding the EU fleet from the UK Economic Exclusive Zone (Dépalle et al ., 2020 ).

Having clearly stated long-term objectives that can guide the definition of operational targets in developing fisheries management measures is a necessary requirement for achieving sustainable fisheries. For example, the EU’s CFP aims to ensure the exploitation of living marine resources in sustainable economic, environmental, and social conditions by achieving MSY. Efforts to translate this overall objective into operational targets for fishing capacity and to design alternative approaches to achieving such targets could benefit from the accumulated knowledge we find on this issue in the fisheries economics literature. As an intergovernmental organization that brings together broad knowledge from its 20 member countries across the Atlantic, ICES is well suited to provide guidance regarding the approaches and methods that may be best applied to manage fishing capacity in local circumstances.

Development of guidance could include assessing whether the long-standing “balance” indicators in the EU ( https://stecf.jrc.ec.europa.eu/reports/balance ) adequately address the challenges of adjusting fishing capacity to the production potential of fish stocks. These short-term assessments could be complemented with long-term analyses to help identify economically optimal objectives for fleet structure. Beyond EU countries, a similar assessment of the extent to which policy objectives strike a balance between fishing capacity and fishing opportunities would appear relevant across ICES countries.

Further advice could be provided through overviews of the role factors such as subsidies, nominal limitations on gross tonnage caps, market-based measures, or other factors play in influencing fishing capacity in each country. Additional insights could be gained from comparisons of national action plans for fleet capacity adjustments and assessments of alternative capacity adjustment approaches.

Informing the allocation of fishing rights: key issues and best-practice evaluation methods

In addition to informing capacity management, much more economic insights could be provided regarding the difficult but unavoidable question of how to allocate fishing possibilities to reduce the race-to-fish incentives driving the development of excess capacity. Involving ICES in the coordination of research efforts across its member countries to improve understanding of the alternative allocation approaches and their consequences in terms of management, equity, and sustainability objectives would seem particularly relevant. Such coordinated research efforts would enable providing independent guidelines that could be made available to a broad range of stakeholders within ICES countries on design considerations in fishing rights allocation. Such guidelines could include: (i) structured approaches to the key economic questions to consider; (ii) empirically tested methods and tools to address these questions, and (iii) key data sets and indicators required for the analyses of alternative designs of the allocation of fishing possibilities. A review of national administrative databases holding either quota, fishing rights, swaps, or actual fishing activity data to help build up an evidence base of how rights are effectively distributed could also be undertaken. Methods could then be developed to relate this evidence base to performance measures under alternative management approaches.

Accounting for SFF in sustainability assessments

In determining operational sustainability targets and examining trade-offs associated with alternative management strategies, it is important to account for the ecological impacts, cultural values, and economic significance of SSF. Having a better understanding of the structure of SSF and of their importance to household income alongside that from other sources would enable more comprehensive assessment of the economic consequences of fisheries management on coastal communities (Bueno and Basurto, 2009 ; Colburn et al ., 2016 ). Studying the synergies and competition between SSF and large-scale fishing along the supply chain would also help improve our understanding of the linkages between fisheries management, markets, and welfare effects.

While a harmonized definition of SSF might seem useful to establish, a “one size fits all” definition of SSF may not be suitable for local management purposes (García-Flórez et al ., 2014 ; Rousseau et al ., 2019 ; Smith and Basurto, 2019 ). Additionally, research is needed to set boundaries between recreational fishing and SSF. Current definitions may not adequately capture the socio-economic differences between these sectors, such as motivation for fishing. Hence, more research is needed to find the balance between a general definition of support fisheries management advice and the incorporation of the specific characteristics of local SSF.

Meeting these research needs has been hampered by important data gaps. Filling these gaps requires improvements in the information collected (e.g. the distribution of activities within fishing communities, ownership of fishing rights, and income from fishing and other businesses) and the accuracy of data collected by national and international data collection programmes. Higher resolution spatial data regarding SSF is also needed to allow a more robust economic spatial analysis of SSF fishing grounds (Breen et al ., 2014 ; Gacutan et al ., 2019 ). Here also, efforts to engage stakeholders in carrying out the research and developing management advice may facilitate progress.

Informing shared stocks management

A strength of ICES is its ability to coordinate research efforts across its member countries. In this endeavour, ICES can aim to improve the general level of understanding of shared stock management issues and coordinate research across countries to improve the science supporting policy and the development of relevant advice about the impacts of changing established allocation approaches. Our review shows that economics can provide an understanding of both the incentives and other factors at play in shared stock management and the likely outcomes and trade-offs associated with different TAC allocations. In addition, the process for developing TACs and other conservation measures itself warrants further research, as this is key to understanding why certain measures are adopted and others are not. More could also be learned with respect to allocation of fishing possibilities at multiple decision levels (e.g. individual companies, POs, regional authorities, nations) and non-fishing related interests (e.g. processing, fishing rights holders, broader community interests, other industry interests). Improving shared stock allocation processes calls for research in political science, political economics, and applications of public choice theory. The role of additional factors influencing incentives for cooperative management and compliance with management regulations, such as financial support policies for the fisheries sector, should also be taken into account in these analyses.

Including ecological processes in the assessment of shared stock harvest strategies offers promising developments to deal with current and future shifts in stock distributions and the ensuing need for adaptive approaches to allocate quotas (e.g. historic catch shares versus zonal distribution of stocks). Despite improved data availability in many countries, a lack of standardization, compatibility, and sometimes comparability in the types of data collected remains an impediment to better analyses. These difficulties may be related to the potential disincentives for negotiators and the industry in making economic information available when initiating negotiations on conservation objectives and/or access right allocations between parties. Economic analysis can also help assess the potential for long-term harvest strategies to minimize such disincentives, thereby leading to improved data quality.

We find that a large research effort in fisheries economics has been devoted to analysis of how interactions between specific fisheries and other components of fisheries social–ecological systems affect how these systems respond to management. Key interactions to consider include the connections between the catch sector and markets, the diversification of commercial fishing, fisheries-aquaculture interactions, as well as broader interactions between fisheries and the provision of ecosystem services.

Accounting for interactions between the catch sector and markets

Research on implications of different fisheries management options on value chain structure as well as understanding wider market issues and forces has grown rapidly, and must continue. The information produced by such research could be beneficial when considering the regional and global impacts of fisheries management strategies (Mullon et al ., 2009 ; Roheim et al ., 2018 ; Costello et al ., 2020 ; Chávez et al ., 2021 ). Some ICES countries currently estimate the expected economic outcomes associated with agreed quota allocations when these are announced. Economists could provide guidance on such an approach, as well as highlight price effects, supply chain tipping points, and the feedback loops with fishing effort and ensuing fishing mortality. Consumer preference and the effects of labelling schemes are still an active area of research in fisheries economics, and there is a further need to investigate the externalities generated by fisheries and how these effects can be related to markets and consumer demand. Above all, because management can be a driving force for fish prices or market outlets, this linkage should be better documented by fishery science and considered when defining management scenarios. The integration of markets into bio-economic modelling could help advance fishery science in this domain.

This research can rely on existing methods and tools, but researchers and experts from different research communities should be encouraged to share their methods, models, and experiences. Data collected for market and demand analysis must meet data formats that most often do not align with those needed for fisheries science. Therefore, future research in ICES with a focus on the linkages between ecosystem-based fisheries management on the one hand and markets and value chains on the other should contribute to and help design data formats (e.g. regarding ex-vessel production or processing) that enable both dimensions to be explored simultaneously, supported by a strong interaction between research groups and data collecting agencies.

Taking into account diversification of commercial fishing

A better understanding of the impacts of diversification on fishers, coastal communities, and the ecosystem would reduce the risks of biased assessments of the potential impacts of fisheries management in the ICES area. Yet, the economic incentives to diversify and how they affect the success of fisheries management are poorly documented in current research, despite the importance of such diversification strategies in determining the economic risks faced by fishers (Abbott et al ., 2023 ). Briton et al . ( 2021 ) highlighted the need to better understand the possibilities for fishers to change species mix and thus adjust to changed management or market conditions, taking the example of an Australian fishery. Holland et al . ( 2017 ) found that fisheries management might restrict individual fishers’ ability to reduce income risk through diversification, despite the importance of such diversification in the face of changing productivity and distribution of fish stocks. The role of income sources from outside the fishing sector is even less frequently analysed in economics, although it is well known to be important in many fisheries (Nielsen et al ., 2018b ; Hoff et al ., 2021 ). Our understanding of alternative sources of income or non-pecuniary aspects such as cultural and job satisfaction would benefit from interdisciplinary work (Holland et al ., 2020 ). Furthering, the economic analysis of diversification will also require the addition of socio-economic data at vessel level, on within-fisheries diversification (e.g. in mixed-fisheries), as well as regarding other sectors towards which fishers can diversify.

Evaluating the implications of fisheries-aquaculture connections

In the context of the Sustainable Development Goals (SDGs), ICES could participate in the elaboration of scenarios for fisheries and aquaculture to achieve SDG goals 14 (life below water), 12 (sustainable consumption and production), and 3 (good health) as seafood is a major source of valuable nutrients for people. The continuous growth in aquaculture and the many links to catch-based fisheries call for more research on the interactions between the two sectors. Possible research questions include how these sectors compete at the fish market and in local communities, and how they can coexist and even potentially benefit from each other. Such studies require geographically disaggregated economic and employment data on fisheries and aquaculture production and mar-kets.

A possible way forward would be to develop an assessment of the competition and impacts of aquaculture development within the value chain as a whole, focusing on specific species as well as broader sets of products and integrating socio-economic as well as environmental management issues. Bio-economic modelling, value chains, and regulatory analyses could be used to address these issues, whereas time series econometrics can provide relevant information related to interactions on markets for wild and farmed fish (Jiménez-Toribio et al ., 2007 ; Bjørndal and Guillen, 2017 ).

Interactions with the provision of ecosystem services

The push for EBFM is leading to a need to better incorporate the broader interactions between fisheries and the provision of ES into management advice in the future. This includes considering ES when assessing the potential impacts of TACs on fisheries’ socio-ecological systems. Such assessments should include the existing understanding of tipping points or thresholds for maintaining ES. Moreover, economic ES assessment could help inform the evaluation of trade-offs associated with marine spatial planning, supporting policymakers in assessing the social welfare outcomes of marine spatial plans.

Providing such advice requires the collection of disaggregated economic data at finer spatial and temporal resolutions, as well as the ability to link this economic data with the other categories of data (e.g. regarding biodiversity, marine habitats, the impacts of fishing and other activities, etc.) used in multidisciplinary frameworks for full ES assessment. Such data gaps could be filled using surveys, which would require some standardization and generalization of the approaches on how to value marine ES.

There has been an increasing demand for fisheries science and management advice to address economic evaluations and analyses. Our review clearly shows that economic research can provide important contributions to ICES science and advice in line with the objectives highlighted in the organization’s strategic plan. Moreover, economic insights can contribute to scientific programmes and organizations working towards achieving the UN SDGs relating to the conservation and sustainable use of living marine resources. In many cases, we identify sets of methods and tools that can be used in a broad range of contexts, for which best practice recommendations can be provided as to how they should be used in applied research and management advice. The increased availability of cost and earnings data regarding fishing operations across ICES regions has helped make significant progress in this regard. Continuing efforts and support towards the collection of such data will be key. We also identify a range of other data that can support further applications of economic analyses to the different fisheries management topics considered in our review.

For some key topics, contributing to management advice may involve integrating economic analyses into current practice. For example, while steps have been taken to incorporate economic considerations in the assessment of mixed fishery management options in the European Union, methods and data are available that can directly inform trade-off analyses associated with managing these fisheries. Another example is the incorporation of economic analyses and indicators in the production of social-ecological status assessments such as the ICES Ecosystem, Fisheries, and Aquaculture Overviews. We feel that these overviews would more effectively inform policymakers, managers, and stakeholders by integrating many of the topics listed in our review. Such an endeavour should eventually lead the economic considerations identified in this review to become an integral part of marine science and scientific advice regarding the use and conservation of marine resources in ICES areas as well as other regions of the world.

Future work should focus on demonstrations of the ways in which relevant economic research, methods, tools, and data can be included in fisheries management advice. Applications of such analyses could also inform the ecosystem and fisheries overviews. This has already begun as part of a number of existing working groups in ICES dedicated to the analysis of economic and social dimensions, leading to the expansion of social sciences capabilities as these groups develop and interact with other disciplines on the different topics we identified in developing integrated assessment approaches. Such integrative support tools, knowledge, and advice could be an entry point for engaging stakeholders in holistic assessments of the impacts of fishing sustainably.

These economic analyses can rely on already well-structured research capacity, data, methods, and tools. However, the dedicated inclusion of economics and economists into the ICES strategic plan and its capacity to further grow in the network through the establishment of focused groups such as ICES WGECON is relatively new. Our survey of economists showed that economists have been only marginally involved in ICES activities. One-third of respondents had not participated in ICES conferences and/or symposia in the last five years, while another third had participated only once. Lack of economic topics and time were mentioned as main factors behind low participation levels, a limitation that should be progressively lifted as the presence of fisheries economics in ICES work increases. While the majority of respondents (75%) showed interest in the development of Integrated Ecosystem Assessments, many also said they would increase their participation in ICES activities if funding was available to support their participation. The growth potential is there, especially with the development of activities such as the MSEAS conference ( https://www.ices.dk/events/symposia/MSEAS/Pages/MSEAS.aspx ), training courses, and cross-cutting meetings such as those recently organized in relation to the interactions between windfarms and commercial fishing ( https://www.ices.dk/news-and-events/news-archive/news/Pages/WKSEIOWFC.aspx ). Hence, a key challenge for further developing economic contributions to fisheries science and advice remains the ability to support an effective engagement of economists, including early-career ones, in the regular research work of organizations such as ICES. In addition, the engagement of economists in collaborative groups supporting advisory and decision-making processes at multiple scales may also be a key feature that could help mainstream economics into such processes.

We would like to thank the ICES secretariat for its support in organizing face-to-face and online meetings of the ECON working group and in developing the online survey of fisheries economists. We also express our gratitude to the three reviewers for their thoughtful suggestions, which helped us improve the manuscript.

The authors have no conflicts of interest to declare.

OT, JRN, AM, and HC coordinated the review and the conception of the paper. All authors participated in the identification and development of the review topics. The authors identified as Topic Coordinators in section B of the supplementary material led the initial writing up of the review summaries for each topic. The authors identified as Topic Reviewers reviewed and edited these summaries. OT led the writing of the manuscript. FB, GEB, FD, LG, JH, JI, AM, AnM, ArM, JRN, RN, RR, OT, ET, SV, JV, and SW coordinated the writing up and revisions of sections of the paper relating to the different topics. All authors contributed to editing the manuscript and approved the final draft. OT and BLG led the survey of fisheries economists, and AM helped analyse the results.

The review data underlying this article are available in the article and in its online supplementary material . The survey data of fisheries economists will be shared upon reasonable request with the corresponding author.

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Articles on Fish farming

Displaying 1 - 20 of 38 articles.

Permaculture showed us how to farm the land more gently. Can we do the same as we farm the sea?

Scott Spillias , CSIRO

Farming tuna on land heralded as a win for sustainability – but there are serious concerns around animal welfare

Wasseem Emam , University of Stirling

Some people are willing to pay more for sustainable seafood - new research

Julia Bronnmann , University of Southern Denmark ; Andreea L. Cojocaru , University of Stavanger , and Frank Asche , University of Florida

Confusion at the fish counter: How to eat fish responsibly

Jenny Weitzman , Dalhousie University

Aquaponic farming: harnessing natural processes for an urban circular economy

Paul Wolf , ESCP Business School and Sylvie Geisendorf , ESCP Business School

The demand for luxury shellfish is polluting the ocean with plastic

Leah Bendell , Simon Fraser University

Feeding the world: archaeology can help us learn from history to build a sustainable future for food

Kelly Reed , University of Oxford

How your diet contributes to nutrient pollution and dead zones in lakes and bays

Donald Scavia , University of Michigan

Farmed salmon is now a staple in diets – but what they eat matters too

Dave Little , University of Stirling and Richard Newton , University of Stirling

Feeding farm animals seaweed could help fight antibiotic resistance and climate change

Lauren Ford , Queen's University Belfast and Pamela Judith Walsh , Queen's University Belfast

Cage farming can protect Lake Victoria’s fish. But regulations need tightening

James Njiru , Kenya Marine and Fisheries Research Institute

How to feed a growing population healthy food without ruining the planet

Sandro Demaio , University of Copenhagen ; Jessica Fanzo , Johns Hopkins University , and Mario Herrero , CSIRO

Here’s the seafood Australians eat (and what we should be eating)

Anna Farmery , University of Wollongong ; Gabrielle O'Kane , University of Canberra , and Gilly Hendrie , CSIRO

We can eat our fish and fight climate change too

Philip A Loring , University of Guelph and Ratana Chuenpagdee , Memorial University of Newfoundland

Fish farming at industrial scale: a Turkish case study

Irmak Ertör , Universitat Autònoma de Barcelona

The future of food is ready for harvest

Charles Z. Levkoe , Lakehead University

How changing the world’s food systems can help to protect the planet

Elwyn Grainger-Jones , CGIAR System Organization

How to reduce slavery in seafood supply chains

Trevor J Ward , University of Technology Sydney

How to make global food systems more sustainable

Kathleen Kevany , Dalhousie University

Salmon farms are in crisis – here’s how scientists are trying to save them

Lyndsay Christie , University of Bath

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Professor of Aquatic Resources Development, University of Stirling

Honorary fellow, The University of Melbourne

Professor of Computer Science, University of Sheffield

Professor of Food Policy, City, University of London

Honorary Research Fellow, Scottish Association for Marine Science

Professor, University of Tasmania

Senior Principal Research Scientist - Oceans and Atmosphere, CSIRO

Chief Research Scientist, Food Systems and the Environment, CSIRO

Project Researcher, Research Institute for Humanity and Nature

Senior Lecturer in Urban Geography, University of Salford

Head Scientist, Instituto Español de Oceanografía (IEO - CSIC)

Professor Emeritus of Environment and Sustainability, University of Michigan

Impact Fellow, University of Stirling

Professor of Biology and a marine plant biologist, University of Cape Town

Associate Professor, Melbourne School of Population and Global Health, The University of Melbourne

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Fisheries and Aquaculture

Fisheries and aquaculture research papers/topics, fishermen’s willingness to pay for fisheries management: the case of lake zeway, ethiopia.

Abstract: Lake Zeway fishery is threatened with problems of overexploitation and consequently unrecovered resources resulting in loss of its potentials due to mismanagement. This study identified the determinants of fishermen’s willingness to pay for fishery management and measured mean fishermen’s willingness to pay for lake Zeway fishery management. A two-stage random sampling techniques was applied to identify sample fishermen’s from Adami Tulu Gido Kombolcha, Zeway Dugda and Dugda ...

ANALYSIS OF FACTORS AFFECTING FISH CATCH LEVELS FROM LAKE TANA, ETHIOPIA

Abstract: Agriculture plays vital role in Ethiopian economy. However, despite its importance and potential, the sector has remained at subsistence level. One of the traditional sources of animal protein of the developing world is through livestock rearing. Unfortunately, the livestock production is under increasing pressure from the combined effects of human population growth, shortage of grazing land and desertification. Therefore, it is important to look for a better and cheap, alternative...

Using Ulva (Chlorophyta) for the Production of Biomethane and Mitigation Against Coastal Acidification

In South Africa the green macroalga Ulva armoricana is the main species of macroalgae cultured. The species is currently the largest aquaculture (2884.61 tonnes) product by weight with a corresponding capacity for biogas (CH4) production. We have shown that biotransformation of U. armoricana to Liquefied Petroleum Gas (LPG) is viable and economically feasible as a clean fuel. pH toxicity tests showed that U. armoricana can be used as a health index, under potentially increased CO2 concentrati...

Moving Toward Sustainable Aquaculture for Rural Sustainability and Development in Kenya. A Case of Vihiga County

Kenya has a tremendous great potential for growth in the aquaculture sector. To attain the sustainable development goal of zero hunger, the government is needed to encourage fish culture among the rural communities. The study's objective is to investigate the elements that affect the sustainable development of fresh water Aquaculture in Kenya a Vihiga County case. The purpose of the research is to determine how production characteristics and extension affect the long-term sustainability of fr...

A Comparison of the Growth of the Nile Tilapia (Oreochromis Niloticus, Linnaeus, 1758) Fingerlings Fed with Blue Crown® And Skretting® Commercial Feeds

ABSTRACTA comparison of the growth of the Nile tilapia (Oreochromis niloticus)fingerlings fed with Blue crown® and Skretting® commercial feeds was studiedfor a period of 8 weeks. A total of sixty fingerlings of Oreochromis niloticuswere used. The treatments showed significant difference (p0.05)between   the   two   feeds.  Some   water   quality   parameters   assessed   during   theexperiment indicated that only the dissolved oxygen was significantly differentbetween the two treatments (p

Determination Of Thermal Tolerance, Density And Distribution Of The Mangrove Crabs, Perisesarma Guttatum (Sesarmidae) And Uca Urvillei (Ocypodidae) At Gazi-Bay, Kenya

Abstract Mangrove crabs are important in ecosystem functioning including; bioturbation of the soil resulting in soil particle size distribution, sediment aeration, reduction in sediment salinity and nutrient recycling and thus are fundamental for the viability of mangrove forests which are in turn important to the coastal communities’ livelihoods. Mangroves are intertidal forested wetlands confined to the tropical and subtropical regions. They play important role as habitat for animals, pro...

Nutrient Composition of Trachurus trachurus (Atlantic Horse Mackerel) Smoked With Sawdust and Different Fire Woods (Dialium guineensis AND Pentaclethra macrophylla)

ABSTRACT Trachurus trachurus (Atlantic horse mackerel) was smoked with two different fire woods Di'alium guineensis and Pentaclethra macrohylla and sawdust using a traditional smoking kiln and a constructed sawdust stove sited in the fish farm of Michael Okpara University of agriculture Umudike. The frozen fish sample was weighed, eviscerated and washed properly with clean water. During smoking the temperature of the heat was taken, duration of smoking period was also noted in smoking p...

Chemical Analysis and Nutritional Assessment of Artocarpus heterophyllus Lam. (Jack Fruit) Defatted Seeds used as Additive in Feed for Clarias gariepinus post juveniles

Abstract A 49-day feeding trial was carried out with feeds supplemented with microgram quantities of the defatted seeds of Artocarpus heterophyllus in the diets of Clarias gariepinus at the post juveinile stage. Five diets at 40% crude protein were formulated containing 0, 15, 30, 45 and 60x106 µg DAH seed as additive. Each dietary treatment was replicated three times with 10 fish per replicate. Proximate composition of the defatted seed showed that it was rich in protein, carbohydrate and ...

Assessment of Genetic Structure of Clarias Gariepinus, Burchell, 1822 Population in Asejire Lake

Abstract Wild brood-stock is a major genetic reservoir for sustainable culture of Clarias gariepinus. This has been observed to be declining in major freshwater dams in Nigeria. There is inadequate information on factors responsible for this decline and their effects on genetic structuring of the fish resources in these dams. This study therefore investigated genetic structure of C. gariepinus in relation to environmental condition of Asejire Dam.    The Dam was spatially divided into Oyo...

Economic Efficiency Of Fishing Among Marine And Lagoon Artisanal Fisherfolks In Lagos State, Nigeria

ABSTRACT Fishing is a major source of livelihood for rural and peri-urban communities along coastal waters. The operation of artisanal fisherfolks is threatened by increasing overfishing of inshore waters, inadequate credit facilities, insufficient fishing input subsidies and inadequate extension services. These had negative implications on their efficiency hence their well-being.  In order to enhance their performance, the efficiency of the fisherfolks, profitability and challenges were ex...

The Effect of Walnut (Tetracarpidium conophorum) Leaf and Onion (Allium cepa) Bulb Residues on the Growth Performance and Nutrient Utilization of Clarias gariepinus Juveniles

Abstract Feeding trial were conducted in experimental tanks (50 x 34 x 27 cm) to assess the growth responses and nutrient utilization of Walnut Leaf (WL) and Onion Bulb (OB) residues in Clarias gariepinus. Nine experimental diets: control (0%), OB2 (0.5%), OB3 (1.0%), OB4 (1.5%), OB5 (2.0%), WL6 (0.5%), WL7 (1.0%), WL8 (1.5%) and WL9 (2.0%) were formulated and replicated thrice at 40% crude protein. Fish (mean weight 7.39±0.02 g and length 10.37±1.24 cm) were fed twice daily at 3% body wei...

Epidemiology Of Edwardsiella Infections In Farmed Fish In Morogoro, Tanzania

ABSTRACT A cross sectional study was undertaken from November 2016 to April 2017 to find out whether Edwardsiella infections exist in farmed fish in Morogoro. The prevalence of infection, risk factors and fish haematological parameters were established. A total of 270 fish were sampled from 24 ponds. Each fish was clinically examined and aseptically swabs of kidney, liver and spleen and pond water were collected for bacteriology. Bacteria were cultured onto Tryptic soya agar and Salmonella-S...

Abstract A 49-day feeding trial was carried out with feeds supplemented with microgram quantities of the defatted seeds of Artocarpus heterophyllus in the diets of Clarias gariepinus at the post juveinile stage. Five diets at 40% crude protein were formulated containing 0, 15, 30, 45 and 60x106 µg DAH seed as additive. Each dietary treatment was replicated three times with 10 fish per replicate. Proximate composition of the defatted seed showed that it was rich in protein, carbohydrate ...

Assessment Of Trace Metals Pollution Along The Central Namibian Marine Coastline: Using Choromytilus Meridionalis (Black Mussel) As Indicator Organisms

ABSTRACT This study was carried out at four stations along the Central Namibian marine coastline towns (Walvis Bay, Swakopmund, Henties Bay and Cape Cross) to assess trace metals pollution using Choromytilus meridionalis as indicator organism. Samples were collected using randomized sampling techniques during winter and summer months of 2012. EPA 3050B and ICP-OES protocols were used to digest and assimilate the samples. Data were analysed using a 4x2x3 factorial model of a completely random...

Stock Separation Of The Shallow-Water Hake Merluccius Capensis In The Benguela Using Otolith Shape Analysis And Parasite Infestation

Abstract The fishing industry is an important sector in Namibia with hake contributing about one third of the total commercial catch. Merluccius capensis, the shallow water hake, forms the bulk of this resource. Studies on the distribution of spawners and juveniles, spawning areas and genetics have proposed three stock structure hypotheses of M. capensis in the Benguela: (1) one stock throughout, (2) one in the northern and one in the southern Benguela or (3) three stocks: one in the norther...

Projects, thesis, seminars, research papers, termpapers topics in Fisheries & Aqauculture. Fisheries & Aquaculture projects, thesis, seminars and termpapers topic and materials

Popular Papers/Topics

The socio-economic analysis of small scale fish farming enterprise in lagos state fish farm estate, ikorodu, nigeria, fish pond construction and management, assessment of socio-economic and ecological activities of oyan and opeji lakes, ogun state, nigeria, characterization of genetic strains in clariid species, clarias gariepinus and heterobranchus bidorsalis using microsatellite markers, morphometric and meristics characteristics of erpetoichthys calabaricus from wetland of ogun water-side local government area, report on industrial attachment undertaken at kenya marine and fisheries research institute attachment period 12th june to 04th august 2017, aquatic ecological survey, analysis of the nutritional values of feed compounded from locally available materials, application of biotechnology for genetic improvement in fish farming a case of african catfish clarias gariepinus, assesment of catfish growth in relation to feeding and change in water quality in dry lands, casestudy of seku, kitui., influence of stocking density on the growth and survival of post fry of the african mud catfish (clarias gariepinus), survival and growth rate of clarias gariepinus larvae fed with artemia salina and inert diet., effect of dietary supplementation of inulin and vitamin c on the growth, hematology, innate immunity, and resistance of nile tilapia (oreochromis niloticus), effect of probiotics on the survival, growth and challenge infection in tilapia nilotica (oreochromis niloticus).

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