Evaluating the conservation risks of aggregate harvest management in a spatially-structured herring fishery

Benson, Ashleen J.; Cox, Sean P.; Cleary, Jaclyn S.

doi:10.1016/j.fishres.2015.02.003

Cited by 23 publications

(15 citation statements)

References 48 publications

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“…These activities create trade-offs among commercial roe fisheries that remove spawning adults, which truncates adult age structure and reduces abundance, vs. those that remove only eggs from shorelines (Shelton et al 2014). Unfortunately, a core uncertainty for herring management, as for many species, is the extent of movement between areas (Flostrand et al 2009, Benson et al 2015, Jones et al 2017, Levin et al 2016. Similar uncertainty surrounds spatial variation in spawning biomass (Siple and Francis 2016), which may result in part from the degree of demographic synchrony between areas (e.g., synchrony in recruitment).…”

Section: Pacific Herring Case Study In British Columbia's Central Coastmentioning

confidence: 99%

“…Addressing spatial inequity in risk exposure requires confronting these economic and logistical trade-offs. For species such as Pacific herring that have volatile spatiotemporal dynamics and complex migratory phenology (Benson et al 2015), polycentric governance structures where governing authorities are nested at different spatial scales may help balance these trade-offs by addressing the problems of fit between ecosystems, social systems, and management agencies (Young 2002, Berkes 2006, Borgstr€ om et al 2006, Folke et al 2007, Biggs et al 2012, von der Porten et al 2016. Such systems can capitalize on scale-specific ecological knowledge (including local, traditional, and scientific knowledge), scientific capacity and socioeconomic experience to (1) guide decision analyses, (2) co-coordinate data collection and harvest allocation in space, and (3) test policies (e.g., in the Maine Lobster fishery; Acheson 2003).…”

Section: Linking Harvest Dynamics To Spatial Variation In Population mentioning

confidence: 99%

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Spatial variation in exploited metapopulations obscures risk of collapse

Okamoto

Hessing‐Lewis

Samhouri

et al. 2020

Ecological Applications

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Unanticipated declines among exploited species have commonly occurred despite harvests that appeared sustainable prior to collapse. This is particularly true in the oceans where spatial scales of management are often mismatched with spatially complex metapopulations. We explore causes, consequences, and potential solutions for spatial mismatches in harvested metapopulations in three ways. First, we generate novel theory illustrating when and how harvesting metapopulations increases spatial variability and in turn masks local‐scale volatility. Second, we illustrate why spatial variability in harvested metapopulations leads to negative consequences using an empirical example of a Pacific herring metapopulation. Finally, we construct a numerical management strategy evaluation model to identify and highlight potential solutions for mismatches in spatial scale and spatial variability. Our results highlight that spatial complexity can promote stability at large scales, however, ignoring spatial complexity produces cryptic and negative consequences for people and animals that interact with resources at small scales. Harvesting metapopulations magnifies spatial variability, which creates discrepancies between regional and local trends while increasing risk of local population collapses. Such effects asymmetrically impact locally constrained fishers and predators, which are more exposed to risks of localized collapses. Importantly, we show that dynamically optimizing harvest can minimize local risk without sacrificing yield. Thus, multiple nested scales of management may be necessary to avoid cryptic collapses in metapopulations and the ensuing ecological, social, and economic consequences.

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Section: Pacific Herring Case Study In British Columbia's Central Coastmentioning

confidence: 99%

Section: Linking Harvest Dynamics To Spatial Variation In Population mentioning

confidence: 99%

Spatial variation in exploited metapopulations obscures risk of collapse

Okamoto

Hessing‐Lewis

Samhouri

et al. 2020

Ecological Applications

View full text Add to dashboard Cite

show abstract

“…A fish population that is defined genetically as one stock may comprise many geographic or behavioral components with varying degrees of segregation (e.g., Booke 1981;Hedger et al 2004;Syedang et al 2010). Although managing stocks for these components may be unattractive due to increasing complexity, it is an important step toward developing appropriate models for management actions and interpreting spatial changes in stock distribution (e.g., Hedger et al 2004;Benson et al 2015;Solmundsson et al 2015). Failure to incorporate stock complexity into population models may result in depletion of subgroups within the population, leading to unknown consequences for the overall population and local ecosystem (Solmundsson et al 2005;Zemeckis et al 2014).…”

Section: Catchment and Dispersal Areasmentioning

confidence: 99%

Spawning Site Fidelity, Catchment, and Dispersal of Common Snook along the East Coast of Florida

et al. 2016

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A population's fidelity to spawning sites and variation in the strength of site fidelity among individuals are influential components of fish population dynamics. The literature on fidelity to aggregation sites is dominated by studies on marine species, whereas less is known about the fidelity of euryhaline species to spawning aggregation sites. We used passive acoustic telemetry to quantify intra-annual and interannual site fidelity and resident habitat associated with spawning sites (inlets) for 280 sexually mature Common Snook Centropomus undecimalis through an array of more than 200 receivers deployed in rivers, estuaries, inlets, and nearshore waters along 320 km of Florida's Atlantic coast. Fish were detected four times as often at and made twice as many trips to a primary spawning inlet than to secondary inlet sites. Fish displayed interannual site fidelity, returning to the primary inlet for as many as five consecutive reproductive seasons. Overall, individuals returned to their primary inlet (return rate [RR] D 0.54) more often than they changed sites between years (straying rate [SR] D 0.29), but variation in RRs and SRs between inlets suggested a spatial effect on interannual site fidelity. During the nonspawning season, fish generally resided less than 40 km to the northwest of their primary inlet. The 95% kernel density estimates (KDEs) for catchment area and dispersal area averaged 220 km 2 and overlapped greatly for five out of six inlets. The 50% KDE did not overlap between inlets, suggesting that each spawning site had a corresponding winter resident habitat supporting a group of fish that were primarily associated with that inlet. The inclusion of telemetry data in traditional measures of site fidelity allowed for the identification and accurate description of behavioral polymorphism and may be applied to other fish species when spatial substructuring is suspected.

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“…Boudreau, Shackell, Carson, & Heyer, ; Ehrlén & Morris, ; Elith & Leathwick, ). In marine systems, local population processes are obscured, for example local depletion of weaker subpopulation or persistent high fishing pressure on local concentrations, if fine‐scale population spatial structure is overlooked (Benson, Cox, & Cleary, ; Boudreau et al, ), which may lead to over‐exploitation of local fish populations. Locally depleted populations may not be easily replenished by recolonization (Boudreau et al, ; Kuo, Mandal, Yamauchi, & Hsieh, ).…”

Section: Introductionmentioning

confidence: 99%

A novel spatiotemporal stock assessment framework to better address fine‐scale species distributions: Development and simulation testing

et al. 2019

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Characterizing population distribution and abundance over space and time is central to population ecology and conservation of natural populations. However, species distribution models and population dynamic models have rarely been integrated into a single modelling framework. Consequently, fine‐scale spatial heterogeneity is often ignored in resource assessments. We develop and test a novel spatiotemporal assessment framework to better address fine‐scale spatial heterogeneities based on theories of fish population dynamic and spatiotemporal statistics. The spatiotemporal model links species distribution and population dynamic models within a single statistical framework that is flexible enough to permit inference for each state variable through space and time. We illustrate the model with a simulation–estimation experiment tailored to two exploited marine species: snow crab (Chionoecetes opilio, Oregoniidae) in the Eastern Bering Sea and northern shrimp (Pandalus borealis, Pandalidae) in the Gulf of Maine. These two species have different types of life history. We compare the spatiotemporal model with a spatially aggregated model and systematically evaluate the spatiotemporal model based on simulation experiments. We show that the spatiotemporal model can recover spatial patterns in population and exploitation pressure as well as provide unbiased estimates of spatially aggregated population quantities. The spatiotemporal model also implicitly accounts for individual movement rates and can outperform spatially aggregated models by accounting for time‐and‐size varying selectivity caused by spatial heterogeneity. We conclude that spatiotemporal modelling framework is a feasible and promising approach to address the spatial structure of natural resource populations, which is a major challenge in understanding population dynamics and conducting resource assessments and management.

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Evaluating the conservation risks of aggregate harvest management in a spatially-structured herring fishery

Cited by 23 publications

References 48 publications

Spatial variation in exploited metapopulations obscures risk of collapse

Spatial variation in exploited metapopulations obscures risk of collapse

Spawning Site Fidelity, Catchment, and Dispersal of Common Snook along the East Coast of Florida

A novel spatiotemporal stock assessment framework to better address fine‐scale species distributions: Development and simulation testing

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