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Schematic illustration of a hypothetical retrospective evolutionary impact assessment aiming to quantify the consequences of past fisheries-induced evolution (FIE) from the genetic trait to a global utility function. All curves, therefore, show effects of changes in the genetic component of the trait in question. The assessment compares time series of quantities of interest from an evolutionary scenario (continuous lines) with those from a non-evolutionary scenario (dashed lines) given a particular fishing regime. (a) This example focuses on FIE in a stock's average age at maturation and assumes that FIE causes fish to mature at earlier ages and smaller sizes. (b) In the evolutionary scenario, fishing results in more rapid decreases in spawning-stock biomass (SSB) and in the average body size of spawners. (c) This will influence ecosystem services: provisioning services decline because of a more strongly reduced yield, and cultural services decline, for example, because of the loss of desirable large fish. (d) This implies secondary effects on the associated socioeconomic values or utility components: direct-use values are diminished because of a less valuable total yield, and non-use values are diminished because of the loss of existence value. (e) The loss of values from provisioning and cultural services can be assessed jointly, in terms of a global utility function, which is found to decline more strongly as a result of FIE. Note that although FIE may often lead to earlier maturation at smaller sizes, as shown in this example, under particular circumstances, it may result in delayed maturation.
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Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries-induce...
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Context 1
... types of EvoIA help address distinct challenges arising from FIE: (i) quantification of the losses or gains in utility that may result from FIE and (ii) evaluation of alternative management regimes while accounting for the potential effects of FIE. The first type, illustrated in Fig. 3, quantifies the conse- quences of FIE by including or removing the effect of FIE in a simulated fishery system. To evaluate alternative scenarios, statistical or process-based models or both are needed: an evolutionary sce- nario allowing the genetic component of traits to change in response to fishing, and a corresponding ...
Context 2
... of the target stock and other ecosystem elements and address how these demographic changes impact relevant ecosystem services and utility components (for an application to recovery dynamics, see Enberg et al. 2009). A further step could integrate utility components into a global util- ity function. In the hypothetical example illustrated in Fig. 3, this integration (i.e. the step from Fig. 3d to e) includes the direct-use value from provisioning services and the non-use value from cultural ser- vices. The example shows how a relatively small change in a genetic trait may sometimes result in a significant negative impact on global utility. How- ever, in other cases, FIE may have ...
Context 3
... elements and address how these demographic changes impact relevant ecosystem services and utility components (for an application to recovery dynamics, see Enberg et al. 2009). A further step could integrate utility components into a global util- ity function. In the hypothetical example illustrated in Fig. 3, this integration (i.e. the step from Fig. 3d to e) includes the direct-use value from provisioning services and the non-use value from cultural ser- vices. The example shows how a relatively small change in a genetic trait may sometimes result in a significant negative impact on global utility. How- ever, in other cases, FIE may have little negative impact on utility, or may even ...
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Climate change is impacting the composition and functioning of virtually every ecosystem on Earth, and disrupting the productivity of exploited ones. Species are rapidly adjusting to their changing environments through evolutionary and/or plastic phenotypic changes in behavioural, physiological, phenological and life‐history traits. Size‐selective...
Citations
... Predicting the response of ecological systems to global change through the evolution of individuals' traits, such as size and feeding rates, is a challenge for modern theoretical ecology (Brown et al. 2004, Woodward et al. 2005. This is especially urgent in the context of fisheries management when harvesting increases (Laugen et al. 2014), or for anticipating how agrosystems' communities would evolve in response to agricultural practices change (Loeuille et al. 2013). ...
Body size or mass is one of the main factors underlying food webs structure. A large number of evolutionary models have shown that indeed, the adaptive evolution of body size (or mass) can give rise to hierarchically organised trophic levels with complex between and within trophic interactions. However, these models generally make strong arbitrary assumptions on how traits evolve, casting doubts on their robustness. In particular, biomass conversion efficiency is always considered independent of the predator and prey size, which contradicts with the literature. In this paper, we propose a general model encompassing most previous models which allows to show that relaxing arbitrary assumptions gives rise to unrealistic food webs. We then show that considering biomass conversion efficiency dependent on species size is certainly key for food webs adaptive evolution because realistic food webs can evolve, making obsolete the need of arbitrary constraints on traits' evolution. We finally conclude that, on the one hand, ecologists should pay attention to how biomass flows into food webs in models. On the other hand, we question more generally the robustness of evolutionary models for the study of food webs.
... Increasing fractions of shy fish in angling-exploited stocks would have consequences for stock assessment and all fisheries operating with hook and line. boldness | reproductive fitness | harvest selection | telemetry | timidity A nticipating and preparing for future evolutionary changes within harvested populations whether by fishing or hunting is critical for sustainable natural resource management and successful conservation of ecosystems (1)(2)(3)(4)(5)(6). Harvest-induced evolution is a concern for both commercial and recreational fisheries, and harvest from recreational fisheries now frequently exceeds harvest from commercial fisheries in some marine fish and most inland fish populations (7). ...
... Accordingly, it is possible that natural selection acts also on pike activity, but we did not have sufficient sampling years to detect it. In general, our study represents a snapshot of potential long-term selection dynamics, and the long-term evolutionary outcomes of the trait selection we document remain unknown and can only be revealed by a multigeneration monitoring program (3,72). ...
Significance
Fish are harvested nonrandomly, potentially inducing selection pressures and adaptations of phenotypes that could impede sustainable natural resource management. To assess the potential for fishing-induced selection, natural selection must also be considered, which represents a challenge in broadcast spawning fish in the wild. We compared harvest and natural selection on size and behavioral traits in a wild northern pike ( Esox lucius ) population. Harvest and natural selection on body size operated in opposition. Harvest but not natural selection acted directly on behavior, favoring timid fish. Simulations revealed fisheries selection on body size is likely not easily addressable using traditional length-based regulations and may thus be inevitable. Intensive recreational angling can therefore promote the development of small, inactive, shy, and difficult-to-capture fish.
... Fishing activity is inserted into these patterns, removing biomass and affecting the populations and the ecosystem (i.e. Grbec et al., 2002;Tourre et al., 2007;Bakun et al., 2009;Laugen et al., 2014). ...
Banco Chinchorro coral reef is an important protected marine area in Mexico, due to its biodiversity and ecosystem services, which has experienced overfishing of Lobatus gigas, Panulirus argus, and several target fish species. We aimed to build a model that was balanced (Ecopath) and spatially-explicit (Ecospace) to assess the application of different management strategies on the ecosystem. The spatial model for Banco Chinchorro reef distinguished the following five subsystems: Cueva de Tiburones, La Caldera, La Baliza, El Colorado, and El Chankay. Outcomes showed that benthic autotrophs comprised of the highest biomass in the whole system, followed by small benthic epifauna and sponges. Concerning ecosystem growth and development, Banco Chinchorro reef achieved a Total System Throughput of 144,980.7 g ww m⁻² year⁻¹, an Ascendency of 184,988.0 g ww m⁻² year⁻¹*bit, and a Development Capacity equal to 304,287.4 g ww m⁻² year⁻¹*bits. The A/C and Ov/C ratios reached 40.69% and 59.31%, respectively. The mean trophic level of the catch was estimated as 3.09, indicating that fishing is concentrated on species located at a high trophic level. Spatial-dynamic simulations showed that exploitation exerted separately, by subsystem, resulted in higher direct and indirect effects than fishing throughout the whole ecosystem. These results suggest that habitat rotation for harvest would not be advised.
... Fishing activity is inserted into these patterns, removing biomass and affecting the populations and the ecosystem (i.e. Grbec et al., 2002;Tourre et al., 2007;Bakun et al., 2009;Laugen et al., 2014). ...
The Humboldt Current Large Marine Ecosystem (HCLME) is a salient feature of the southeastern Pacific, along the South American coast of Chile and Peru. It is associated with coastal upwelling which generates a very productive ecosystem. However, due to a variety of interconnected biophysical processes at diverse temporal and spatial scales, production varies greatly in time and space. The interplay of the biophysical environment, biological processes involving valuable resources on international markets, the socio-political context, and some management decisions, has shaped the daily life of the HCLME fisheries, marked by booms and busts, offering wealth for short periods of time, followed by collapses. These collapses are generally interpreted as the consequence of a lack of appropriate management, so that a variety of increasingly stricter regulations have been implemented. Nevertheless, this has not significantly reduced the temporal variability of the fisheries landings, which is broadly characterized by a peaks and troughs pattern. While the HCLME is one of the most productive marine ecosystems on Earth, along with a great biophysical and biological variability, it is also a huge but fragile exploited social-ecological system. Modelers can help to understand how to continuously adapt in order to deal with recurrent fisheries “crises,” which, as we are beginning to learn, may simply be an expression of the variability inherent in this complex system. Furthermore, it is essential to increase our capacity to adapt to the expected consequences of climate change.
... Fishing activity is inserted into these patterns, removing biomass and affecting the populations and the ecosystem (i.e. Grbec et al., 2002;Tourre et al., 2007;Bakun et al., 2009;Laugen et al., 2014). ...
One of the great scientific challenges for the management of fish resources is to address the question of how much biomass must remain in the sea after fishing in order to maintain the functions of the ecosystem. We define this fishing limit as an ecosystem limit reference point, ELRP, that could be used for marine resource management. The basic concept is that the entropy of the ecosystem changes when biomass is removed, and if the removal exceeds a certain threshold, the ecosystem will lose its capacity to recover and its ability to adopt a different organizational pattern. For fishing, we can define the ELRP as a harvest rate to be applied to each species group in the ecosystem. We illustrate this concept with the sardine fishery of the central Gulf of California and offer a criterion for approaching concerns about the exploitation of small pelagic fishes in many parts of the world. The ELRP shown here also contributes to the maintenance of ecosystem function by providing a specific harvest rate. This rate permits the estimation of the remaining biomass at sea as a limit for maintaining ecosystem sustainability by adopting a precautionary management policy.
... Fishing activity is inserted into these patterns, removing biomass and affecting the populations and the ecosystem (i.e. Grbec et al., 2002;Tourre et al., 2007;Bakun et al., 2009;Laugen et al., 2014). ...
Anthropogenic pressures threaten marine biodiversity at multiple scales and challenge scientists to understand and mitigate human impacts on marine biodiversity. Facing such a challenge, recent approaches that bridge community ecology and conservation planning can broaden the theoretical foundations of strategies aimed to ensure the resilience and functional diversity of marine food webs. We here summarize metrics used to describe patterns of ecological interactions that account for the overall community architecture, such as nestedness and modularity. In addition, we discuss approaches to characterize species topological roles within food webs in order to identify sets of interacting species that act as the backbone of marine biodiversity and ecosystem functions. We argue that combining empirical data and dynamic network modeling is key to foster the integrative understanding of ecological, evolutionary, and anthropogenic processes shaping marine food webs, which requires theoretical ecologists and practitioners to work together in long-term, system-level strategies to conserve marine biodiversity and improve the sustainability of fisheries.
... In order to respond to this demand some studies have been developed on the selective evolution of fishing resources, in order to understand the changes caused by behavioural traits, physiology and morphology of the captured species, with the purpose of avoiding the stock's point of noreturn. For this reason, quantifying and predicting the effect of the evolution in the fishing sector must constitute a research priority [9]. ...
... An improvement on previous models came from the study of Laugen et al. [9], which addresses the evaluation of the fishing evolution impact awareness (EvoIA). This project modelled the evolution of fishing gear which impacts the maritime ecosystem, promoting the adoption of more adequate management measures to promote sustainable fishing. ...
The demographic pressure entails over-exploitation of the coastal regions and the consumption of marine resources in a non-sustainable manner, jeopardizing the species renewal. Several species are currently facing great threat of disappearing from Portuguese coastal waters, namely the Sardina pilchardus, due to illegal, unregulated or not reported fishing. The Portuguese Navy performs regular surveillance and monitoring of fishing activities for law enforcement. Those actions gather useful information about the fishing activity, specifically about the types of fishing gear used. Since the geo-spatial data on a regular map, by itself, was not enough to present a clear picture regarding the predominant type of fishing gears used for captured sardine in the Portuguese coastal areas, we applied an artificial neural network to georeferenced information in order to derive a new layer with the areas where the fishing gears used for Sardina pilchardus fishing are most likely to be found.
... To engage this need, studies have been developed on the selective development of fish resources, in order to try to understand the observable changes in behavioural traits, physiology and morphology of the species captured in order to avoid such stocks reaching a point of no return. Therefore, quantifying and predicting the effect of developments affecting fisheries and fishing industry should be a research priority [8]. ...
... The improvement from the above-mentioned models, has roots in the study of Laugen et al. [8], which addresses the evolutionary impact assessment of fisheries (EvoIA). This project models the evolution of fishing practices in marine ecosystems, thus suggesting the adoption of the most appropriate management measures for fisheries sustainability. ...
The Portuguese Navy is responsible for monitoring the largest Exclusive Economic Zone in Europe. The most captured species in this area are Scomber colias and Trachurus trachurus, commonly called Mackerel and Horse Mackerel, respectively. One of the Navy’s missions is pursuing actions of fishing surveillance to verify the compliance of proceedings with the species’ fishing activity regulation. This monitoring actions originate data that represents a sample of the fishing activity in the area. The collected data, analysed with adequate data mining techniques, makes it possible to extract useful information to better understand the fishing activity related to Mackerel and Horse Mackerel, even if the full data set cannot be disclosed. With this in mind the authors used a non-supervised learning technique, the K-Means algorithm, which grouped data in clusters by its similarity and made a summarized description of each cluster with the purpose of releasing a general overview of such records. The information obtained from the clusters led the authors to deepen the study by performing a comparison of the monthly average quantity recorded per vessel for the two species in order to infer about the relation between captured quantity Mackerel and Horse Mackerel over time.
... Existing cases of EBFM implementation serve to strengthen its primary principles in preserving marine food web interactions, accounting for the incidental impact of fisheries on the ecosystem (particularly those related to non-target species) as well as considering the socioeconomic context of the human demand for fish (see Ruckelshaus et al. 2008). Recognising the observed FIMA in individual fish and the potential adverse effects it could have on prey−predator interactions, EBFM should account for eco-evolutionary processes and their persistent negative consequences (see Jørgensen et al. 2007, Laugen et al. 2014 in order to accomplish a truly holistic approach to natural resource management. By definition, holistic fisheries management should acknowledge all structural levels and processes in an 'ecosystem' and an 'evosystem' with respect to their independent and coupled effects (see Fowler et al. 2013). ...
Competitive interactions between marine mammals and fisheries represent some of the most complex challenges in marine resource management worldwide. The development of commercial fisheries and recovering marine mammal populations have contributed to a decrease in fish availability. Whilst ecosystem-based fisheries management (EBFM) can counteract this decrease, achieving the EBFM objectives faces certain major obstacles including insufficient or unreliable data, inapplicable assessment models, as well as
inadequate management decisions that do not account for fisheries-induced morphological alterations (FIMA) and marine mammal management. Despite a body of evidence addressing various aspects of marine mammal−fisheries competition, little is known about the effects of marine mammal−fisheries biological interactions
affecting the fish viability and food web stability. We review the research on marine mammal−fisheries competitive biological interactions (hereafter biological competition) by focussing on
(1) the prerequisites for marine mammal−fisheries biological competition and the relevant methodologies to explore them and (2) recent studies revealing the implications of FIMA and trophic
interactions for the biological competition. We also discuss the implications of FIMA, eco-evolutionary feedback and prey−predator dynamics for EBFM implementation in contemporary harvested
ecosystems. Our main findings reveal a lack of data about marine mammals’ prey choice and selectivity, the need for better representation of marine mammals in modelling approaches
and lastly, the necessity for additional research linking FIMA, trophic interactions and the EBFM objectives. To conclude, interdisciplinary approaches may serve to link all of the efforts needed to effectively and holistically support the implementation of EBFM.
... Understanding mechanistic links between individual traits and susceptibility to capture is essential for predicting the capacity of fishing gears to elicit phenotypic change in exploited populations (Horodysky et al., 2015;Ward et al., 2016;Hollins et al., 2018) and provide effective fisheries management (Laugen et al., 2014). Active gears (including trawls and seine nets) pursue or encircle targeted fish with nets, and exploit fish behavioural responses, including shoaling, to elicit capture. ...
... Establishing mechanistic links between individual phenotypic traits and vulnerability to capture is an important component of fisheries management (Laugen et al., 2014;Horodysky et al., 2015;Ward et al., 2016). In our study, we found that fish with higher anaerobic capacity spent less time swimming within the trawl net, in accordance with previous experimental work (Killen et al., 2015a). ...
... However, this experiment also shows that this effect is context specific, making the strength of this selectivity in the wild difficult to determine. The impact of this erosion of phenotypic diversity is difficult to predict, but evolutionary impacts of fisheries harvest has implications for the recovery and sustainability of exploited fish stocks (Enberg et al., 2009;Heino et al., 2013;Laugen et al., 2014), as well as the economic viability of fisheries themselves (Eikeset et al., 2013). Considering the role of anaerobic metabolism in predator prey dynamics (Kaufman et al., 2006;Killen et al. 2015a), selective removal of slow swimming individuals could result in exploited fish stocks becoming less available to predators, or otherwise alter food web dynamics (Claireaux et al., 2018). ...
Impacts of fisheries-induced evolution may extend beyond life history traits to more cryptic aspects of biology, such as behaviour and physiology. Understanding roles of physiological traits in determining individual susceptibility to capture in fishing gears and how these mechanisms change across contexts is essential to evaluate the capacity of commercial fisheries to elicit phenotypic change in exploited populations. Previous work has shown that metabolic traits related to anaerobic swimming may determine individual susceptibility to capture in trawls, with fish exhibiting higher anaerobic performance more likely to evade capture. However, high densities of fish aggregated ahead of a trawl net may exacerbate the role of social interactions in determining an individual fish’s behaviour and likelihood of capture, yet the role of social environment in modulating relationships between individual physiological traits and vulnerability to capture in trawls remains unknown. By replicating the final moments of capture in a trawl using shoals of wild minnow (Phoxinus phoxinus), we investigated the role of individual metabolic traits in determining susceptibility to capture among shoals of both familiar and unfamiliar conspecifics. We expected that increased shoal cohesion and conformity of behaviour in shoals of familiar fish would lessen the role of individual metabolic traits in determining susceptibility to capture. However, the opposite pattern was observed, with individual fish exhibiting high anaerobic capacity less vulnerable to capture in the trawl net, but only when tested alongside familiar conspecifics. This pattern is likely due to stronger cohesion within familiar shoals, where maintaining a minimal distance from conspecifics, and thus staying ahead of the net, becomes limited by individual anaerobic swim performance. In contrast, lower shoal cohesion and synchronicity of behaviours within unfamiliar shoals may exacerbate the role of stochastic processes in determining susceptibility to capture, disrupting relationships between individual metabolic traits and vulnerability to capture.
