This chapter uses the community model to repeat many of the classic impact calculations of a single stock on the entire community. Here, a focus is the appearance of trophic cascades initiated by the removal of large predators. When a component of an ecosystem is perturbed, the effects are not isolated to the component itself but cascade through the ecosystem. Perturbations are mainly propagated through the predator–prey interactions. The chapter also considers the trade-offs between a forage fishery and a consumer fishery, and the extension of the maximum sustainable yield (MSY) concept to the community, before finally returning to the single-stock aspects.
{"title":"Community Effects of Fishing","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.16","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.16","url":null,"abstract":"This chapter uses the community model to repeat many of the classic impact calculations of a single stock on the entire community. Here, a focus is the appearance of trophic cascades initiated by the removal of large predators. When a component of an ecosystem is perturbed, the effects are not isolated to the component itself but cascade through the ecosystem. Perturbations are mainly propagated through the predator–prey interactions. The chapter also considers the trade-offs between a forage fishery and a consumer fishery, and the extension of the maximum sustainable yield (MSY) concept to the community, before finally returning to the single-stock aspects.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129384226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-16DOI: 10.23943/princeton/9780691192956.003.0004
K. H. Andersen
This chapter shows how the population size spectrum can be calculated using the vital rates of the individuals within the population: the growth rate, the reproduction rate, and the mortality as functions of size. It discusses the physiological mortality at length, and attempts to estimate its value from meta-analyses of mortality and growth rate in fish. In obtaining solutions of the population size spectrum, the chapter follows two parallel tracks: a simplified analytical solution, and a full numerical solution. The analytical solution offers insights into the governing scaling relationships between asymptotic size and population-level measures, such as spawning stock biomass, reproductive output, and lifetime reproductive output. Meanwhile, the numerical solution allows us to explore the effects of size-based fishing in the next chapter.
{"title":"Demography","authors":"K. H. Andersen","doi":"10.23943/princeton/9780691192956.003.0004","DOIUrl":"https://doi.org/10.23943/princeton/9780691192956.003.0004","url":null,"abstract":"This chapter shows how the population size spectrum can be calculated using the vital rates of the individuals within the population: the growth rate, the reproduction rate, and the mortality as functions of size. It discusses the physiological mortality at length, and attempts to estimate its value from meta-analyses of mortality and growth rate in fish. In obtaining solutions of the population size spectrum, the chapter follows two parallel tracks: a simplified analytical solution, and a full numerical solution. The analytical solution offers insights into the governing scaling relationships between asymptotic size and population-level measures, such as spawning stock biomass, reproductive output, and lifetime reproductive output. Meanwhile, the numerical solution allows us to explore the effects of size-based fishing in the next chapter.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127036925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter follows the size-structure of the entire marine ecosystem. It shows how the Sheldon spectrum emerges from predator–prey interactions and the limitations that physics and physiology place on individual organisms. How predator–prey interactions and physiological limitations scale with body size are the central assumptions in size spectrum theory. To that end, this chapter first defines body size and size spectrum. Next, it shows how central aspects of individual physiology scale with size: metabolism, clearance rate, and prey size preference. On that basis, it is possible to derive a power-law representation of the size spectrum by considering a balance between the needs of an organism (its metabolism) and the encountered prey, which is determined by the spectrum, the clearance rate, and the size preference. Lastly, the chapter uses the solution of the size spectrum to derive the expected size scaling of predation mortality.
{"title":"Size Spectrum Theory","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.6","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.6","url":null,"abstract":"This chapter follows the size-structure of the entire marine ecosystem. It shows how the Sheldon spectrum emerges from predator–prey interactions and the limitations that physics and physiology place on individual organisms. How predator–prey interactions and physiological limitations scale with body size are the central assumptions in size spectrum theory. To that end, this chapter first defines body size and size spectrum. Next, it shows how central aspects of individual physiology scale with size: metabolism, clearance rate, and prey size preference. On that basis, it is possible to derive a power-law representation of the size spectrum by considering a balance between the needs of an organism (its metabolism) and the encountered prey, which is determined by the spectrum, the clearance rate, and the size preference. Lastly, the chapter uses the solution of the size spectrum to derive the expected size scaling of predation mortality.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122036536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter looks into the differences and similarities between the two groups of fish: the teleosts and the elasmobranchs. In the data analyses done so far in this volume, the fish most considered were the teleosts (Teleostei), which represent by far the dominant group, in terms of both biomass and living number of species. Second in line comes the cartilaginous fishes—the elasmobranchs (sharks, rays, skates, and sawfish). This chapter describes the differences between teleosts and elasmobranchs from a population dynamics perspective. It shows that the main difference between the two groups is in their offspring size strategy: teleosts make small offspring; elasmobranchs make large offspring. The chapter uses this difference to quantify the sensitivity of elasmobranchs to fishing relative to teleosts. It also develops an evolutionary explanation for why the offspring size strategy differs between teleosts and elasmobranchs.
{"title":"Teleosts versus Elasmobranchs","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.12","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.12","url":null,"abstract":"This chapter looks into the differences and similarities between the two groups of fish: the teleosts and the elasmobranchs. In the data analyses done so far in this volume, the fish most considered were the teleosts (Teleostei), which represent by far the dominant group, in terms of both biomass and living number of species. Second in line comes the cartilaginous fishes—the elasmobranchs (sharks, rays, skates, and sawfish). This chapter describes the differences between teleosts and elasmobranchs from a population dynamics perspective. It shows that the main difference between the two groups is in their offspring size strategy: teleosts make small offspring; elasmobranchs make large offspring. The chapter uses this difference to quantify the sensitivity of elasmobranchs to fishing relative to teleosts. It also develops an evolutionary explanation for why the offspring size strategy differs between teleosts and elasmobranchs.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126141376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter outlines four future research questions where the size- and trait-based theory can be applied: stochasticity, behavioral ecology, coupling to primary production, and thermal ecology and climate change. The chapter first argues that differences in growth can be modeled with the size-based framework by introducing stochasticity into the feeding interaction. Next, the chapter contends that the behavioral response to food and predation risk has potentially big implications for community dynamics because it changes a key element in the model—namely, the interaction between individuals. On the matter of production, the chapter demonstrates that changing the carrying capacity or the productivity of the resource changes the food environment for the fish and that changes in the primary–secondary production would also have an impact on the carrying capacity of the stock-recruitment relation. Finally, the chapter looks at how increasing temperatures affect fish populations and communities on at least two time scales: on the short term is the direct physiological response to a temperature increase in terms of increasing metabolic demands. On the longer time scale is the ecological response where some species in a community will be replaced by other, better adapted, species.
{"title":"The Size- and Trait-Based Approach","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.17","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.17","url":null,"abstract":"This chapter outlines four future research questions where the size- and trait-based theory can be applied: stochasticity, behavioral ecology, coupling to primary production, and thermal ecology and climate change. The chapter first argues that differences in growth can be modeled with the size-based framework by introducing stochasticity into the feeding interaction. Next, the chapter contends that the behavioral response to food and predation risk has potentially big implications for community dynamics because it changes a key element in the model—namely, the interaction between individuals. On the matter of production, the chapter demonstrates that changing the carrying capacity or the productivity of the resource changes the food environment for the fish and that changes in the primary–secondary production would also have an impact on the carrying capacity of the stock-recruitment relation. Finally, the chapter looks at how increasing temperatures affect fish populations and communities on at least two time scales: on the short term is the direct physiological response to a temperature increase in terms of increasing metabolic demands. On the longer time scale is the ecological response where some species in a community will be replaced by other, better adapted, species.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121530054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-16DOI: 10.23943/princeton/9780691192956.003.0001
K. H. Andersen
This chapter provides some context on the overall themes and theory of this volume. Throughout, the theory is applied to relevant problems in fisheries science: impact of fishing on demography, fisheries reference points, evolutionary impact assessments, stock recovery, ecosystem-based fisheries management, and so on, as well as to basic ecological and evolutionary questions. The chapter begins by addressing the motivations for a new theory of fish stocks and fish communities. It also considers what problems such a theory should address and how such a theory can be formulated. From here, the chapter discusses what makes a good theory and the peculiar challenges fish ecology represents.
{"title":"Nothing as Practical as a Good Theory","authors":"K. H. Andersen","doi":"10.23943/princeton/9780691192956.003.0001","DOIUrl":"https://doi.org/10.23943/princeton/9780691192956.003.0001","url":null,"abstract":"This chapter provides some context on the overall themes and theory of this volume. Throughout, the theory is applied to relevant problems in fisheries science: impact of fishing on demography, fisheries reference points, evolutionary impact assessments, stock recovery, ecosystem-based fisheries management, and so on, as well as to basic ecological and evolutionary questions. The chapter begins by addressing the motivations for a new theory of fish stocks and fish communities. It also considers what problems such a theory should address and how such a theory can be formulated. From here, the chapter discusses what makes a good theory and the peculiar challenges fish ecology represents.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130089095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter focuses on a generalization of a classic consumer-resource model with a single population embedded in a community. It develops this physiologically structured consumer-resource model by extending the static model in Chapter 4. The chapter then studies how density dependence emerges in the model, and how it changes the population size spectrum. Finally, the chapter explores how some of the standard fisheries impact assessments from Chapter 5 are changed when density dependence is in the form of competition or cannibalism. Specifically, it shows how the appearance of late-life density dependence rocks one of the cornerstones of contemporary fisheries management: that we should fish only the largest fish. In some cases, it turns out that yield is instead maximized by fishing juveniles.
{"title":"Consumer-Resource Dynamics and Emergent Density Dependence","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.14","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.14","url":null,"abstract":"This chapter focuses on a generalization of a classic consumer-resource model with a single population embedded in a community. It develops this physiologically structured consumer-resource model by extending the static model in Chapter 4. The chapter then studies how density dependence emerges in the model, and how it changes the population size spectrum. Finally, the chapter explores how some of the standard fisheries impact assessments from Chapter 5 are changed when density dependence is in the form of competition or cannibalism. Specifically, it shows how the appearance of late-life density dependence rocks one of the cornerstones of contemporary fisheries management: that we should fish only the largest fish. In some cases, it turns out that yield is instead maximized by fishing juveniles.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125023598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter calculates the abundance (or biomass) of all species in a community as a function of their asymptotic size. It develops a purely analytical theory of the asymptotic size trait distribution in a fish community. The theory is based upon the Sheldon community spectrum developed in Chapter 2, and the new theory is used here to formulate an “extended” Sheldon conjecture. The analytic theory describes only a steady-state solution, which is of limited use for impact assessments of fishing; that requires a dynamic trait-based size spectrum model, which is next developed. To conclude, the chapter demonstrates how the trait-based model can be extended to model specific stocks embedded in a food web.
{"title":"Trait Structure of the Fish Community","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.15","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.15","url":null,"abstract":"This chapter calculates the abundance (or biomass) of all species in a community as a function of their asymptotic size. It develops a purely analytical theory of the asymptotic size trait distribution in a fish community. The theory is based upon the Sheldon community spectrum developed in Chapter 2, and the new theory is used here to formulate an “extended” Sheldon conjecture. The analytic theory describes only a steady-state solution, which is of limited use for impact assessments of fishing; that requires a dynamic trait-based size spectrum model, which is next developed. To conclude, the chapter demonstrates how the trait-based model can be extended to model specific stocks embedded in a food web.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127853224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter develops a basic evolutionary impact assessment of fishing. It does so by combining the size-based theory developed in chapters 3 and 4 with classic quantitative genetics. The impact assessment estimated the selection responses resulting from size-selective fishing on three main life-history traits: size at maturation, growth rate, and investment in reproduction. The predicted selection responses from a fishing mortality comparable to F msy are on the order of magnitude of 0.1 percent per year, smallest for size at maturation and largest for the investment in reproduction. The responses increase roughly proportional to the fishing mortality, so overfishing will not only result in depleted stocks and suboptimal yield production, but it will also lead to faster fisheries-induced evolution.
{"title":"Fisheries-Induced Evolution","authors":"K. H. Andersen","doi":"10.2307/j.ctvb938mm.10","DOIUrl":"https://doi.org/10.2307/j.ctvb938mm.10","url":null,"abstract":"This chapter develops a basic evolutionary impact assessment of fishing. It does so by combining the size-based theory developed in chapters 3 and 4 with classic quantitative genetics. The impact assessment estimated the selection responses resulting from size-selective fishing on three main life-history traits: size at maturation, growth rate, and investment in reproduction. The predicted selection responses from a fishing mortality comparable to F\u0000 msy are on the order of magnitude of 0.1 percent per year, smallest for size at maturation and largest for the investment in reproduction. The responses increase roughly proportional to the fishing mortality, so overfishing will not only result in depleted stocks and suboptimal yield production, but it will also lead to faster fisheries-induced evolution.","PeriodicalId":162394,"journal":{"name":"Fish Ecology, Evolution, and Exploitation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130797017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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