A physiological perspective on fisheries‐induced evolution

Hollins, Jack; Thambithurai, Davide; Koeck, Barbara; Crespel, Amélie; Bailey, David M.; Cooke, Steven J.; Lindström, Jan; Parsons, Kevin J.; Killen, Shaun S.

doi:10.1111/eva.12597

Cited by 73 publications

(82 citation statements)

References 177 publications

(222 reference statements)

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“…Firstly, capture of fish by fishing gears should be thought to consist of several stages over several spatial scales (Dyer et al., 2009; Hollins et al., 2018; Rudstam, Magnuson, & Tonn, 1984). At the broadest scale, habitat selection may preclude any capture by fishing gear—that is, fish would never be directly exposed to gears unless they share the same space as fishers (Hollins et al., 2018). However, quantifying the isolated and cumulative selective effects of multiple capture stages is extremely difficult, especially when we currently have little or no knowledge of the social and physiological influences on trap vulnerability.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, individuals with a higher metabolic rate also tend to be less social, presumably to reduce competition for food items with potential groupmates. These links between individual metabolic rate and behavior may also be highly relevant for determining which individual fish are most vulnerable to capture in fishing scenarios (Alós, Palmer, Rosselló, & Arlinghaus, 2016; Diaz Pauli & Sih, 2017; Hollins et al., 2018; Kern, Robinson, Gass, Godwin, & Langerhans, 2016; Killen, Nati, & Suski, 2015). For instance, individuals with a higher metabolic rate may be more likely to encounter traps if they spend more time searching for food or be more willing to enter a discovered trap if they are bolder or more attracted to bait (Hollins et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…These links between individual metabolic rate and behavior may also be highly relevant for determining which individual fish are most vulnerable to capture in fishing scenarios (Alós, Palmer, Rosselló, & Arlinghaus, 2016; Diaz Pauli & Sih, 2017; Hollins et al., 2018; Kern, Robinson, Gass, Godwin, & Langerhans, 2016; Killen, Nati, & Suski, 2015). For instance, individuals with a higher metabolic rate may be more likely to encounter traps if they spend more time searching for food or be more willing to enter a discovered trap if they are bolder or more attracted to bait (Hollins et al, 2018). Within and across species, SMR can also be functionally related to the maximum metabolic rate achievable by an animal (MMR), due to increased maintenance costs of increased mitochondrial density, muscle mass, and cardiovascular machinery even when the individual is at rest (Auer, Killen, & Rezende, 2017; Killen, Glazier, et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

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Shoal size as a key determinant of vulnerability to capture under a simulated fishery scenario

Thambithurai

Hollins

Leeuwen

et al. 2018

Ecology and Evolution

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Group living is widespread among animals and has a range of positive effects on individual foraging and predator avoidance. For fishes, capture by humans constitutes a major source of mortality, and the ecological effects of group living could carry‐over to harvest scenarios if fish are more likely to interact with fishing gears when in social groups. Furthermore, individual metabolic rate can affect both foraging requirements and social behaviors, and could, therefore, have an additional influence on which fish are most vulnerable to capture by fishing. Here, we studied whether social environment (i.e., social group size) and metabolic rate exert independent or interactive effects on the vulnerability of wild zebrafish (Danio rerio) to capture by a baited passive trap gear. Using video analysis, we observed the tendency for individual fish to enter a deployed trap when in different shoal sizes. Fish in larger groups were more vulnerable to capture than fish tested individually or at smaller group sizes. Specifically, focal fish in larger groups entered traps sooner, spent more total time within the trap, and were more likely to re‐enter the trap after an escape. Contrary to expectations, there was evidence that fish with a higher SMR took longer to enter traps, possibly due to a reduced tendency to follow groupmates or attraction to conspecifics already within the trap. Overall, however, social influences appeared to largely overwhelm any link between vulnerability and metabolic rate. The results suggest that group behavior, which in a natural predation setting is beneficial for avoiding predators, could be maladaptive under a trap harvest scenario and be an important mediator of which traits are under harvest associated selection.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Shoal size as a key determinant of vulnerability to capture under a simulated fishery scenario

Thambithurai

Hollins

Leeuwen

et al. 2018

Ecology and Evolution

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“…, Hollins et al. ). The relative catchability of individuals of a population susceptible to capture by a fishing gear type is explained, in part, by various heritable traits that vary within a population.…”

Section: Theoretical and Observed Evidence Of Pelagic Mpas Achieving mentioning

confidence: 99%

Do static and dynamic marine protected areas that restrict pelagic fishing achieve ecological objectives?

2019

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There has been a recent proliferation of large‐scale marine protected areas (MPAs) containing pelagic habitats. These contribute substantially toward meeting the area‐based goal of Aichi Biodiversity Target 11 and to managing pelagic ecosystem pressures, including fishing. We assessed theoretical and empirical evidence for the achievement of ecological objectives by static and dynamic spatial management of pelagic fisheries. Exceptionally few studies have assessed ecological responses to MPAs that constrain pelagic fisheries, leaving substantial uncertainty over their efficacy. Assessments have provided a limited basis for causal inferences and have not evaluated whether other management tools would be more effective. Pelagic MPAs have relatively high promise to mitigate fisheries bycatch of species of conservation concern with “slow” life history traits and that form temporally and spatially predictable hotspots, and for some species, to protect habitats important for critical life history stages. It would be challenging to design MPAs to maintain absolute biomass levels of target stocks near targets and above limits: MPAs would need to be extensive to account for broad and variable distributions, and account for catch risk outside of the MPA, including from displaced fishing effort and fishing‐the‐line. For non‐overexploited stocks, which is the status of most target pelagic species and their prey, there would likely be little response in absolute stock biomass to an MPA. While pelagic MPAs have a higher promise of increasing target stocks’ local abundance, evidence with a robust basis for inferring causality is needed. Reducing fishing mortality of prey species might not affect the biomass of their pelagic predators because prey species experience light fishing pressure and because there may be a weak correlation between the absolute abundance of forage fish and their predators. There is an especially limited basis for predicting the effects of MPAs on fisheries‐induced evolution (FIE) in pelagic species. We describe how pelagic MPAs could be designed to achieve five ecological objectives without causing cross‐taxa conflicts and exacerbating FIE. To fill substantial gaps in knowledge, we prescribe counterfactual‐based modeling of time series data of standardized catch records to infer causation in assessments of ecological responses to pelagic MPAs.

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“…; Hollins et al. ). For example, the extensive harvest of Atlantic Cod Gadus morhua in maritime Canada resulted in a declining average body mass as well as earlier maturation time over the ~20‐year monitoring period, suggesting FIE (Olsen et al.…”

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confidence: 99%

Comparative Behavior of Wild Bluegill Captured Inside and Outside of a Long‐Standing Aquatic Protected Area

et al. 2020

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In recreational fisheries it is understood that individual fish that exhibit bolder personality traits have a tendency to be removed from the population (i.e., fishing mortality via harvest or catch‐and‐release mortality), while more timid individuals remain. The use of aquatic protected areas (APAs) has been promoted as a means of offsetting the negative consequences that are associated with fishing mortality by protecting the full suite of phenotypes. However, little work has investigated whether APAs are able to maintain heterogeneity in behavioral traits in wild fish. We attempted to address this question by using wild Bluegill Lepomis macrochirus from Lake Opinicon, a freshwater system consisting of both an APA and heavily fished areas. The Bluegill were obtained via angling from three zones in the lake: the main lake area (i.e., fished), the APA (which has been in place since the 1940s), and a transitional zone between these two areas. In the laboratory, the Bluegill were subjected to two behavioral assessments, a Z‐maze and a flight‐initiation‐distance (FID) test, to address differences in boldness and risk‐taking between these populations. No significant effects of capture zone were detected for any of the behavioral metrics that were assessed in the maze trial. However, individuals that originated from the main lake population had significantly higher FID scores than the fish from the transitional zone and the APA did, indicating that they were more timid. Our results suggest that fisheries activities may only be acting only on specific traits, which may explain some of the null results that are presented here. Nevertheless, our study provides evidence that APAs are providing a reservoir of less timid individuals, which is consistent with an evolutionarily enlightened management strategy.

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A physiological perspective on fisheries‐induced evolution

Cited by 73 publications

References 177 publications

Shoal size as a key determinant of vulnerability to capture under a simulated fishery scenario

Shoal size as a key determinant of vulnerability to capture under a simulated fishery scenario

Do static and dynamic marine protected areas that restrict pelagic fishing achieve ecological objectives?

Comparative Behavior of Wild Bluegill Captured Inside and Outside of a Long‐Standing Aquatic Protected Area

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