A central and classic question in ecology is what causes populations to fluctuate in abundance. Understanding the interaction between natural drivers of fluctuating populations and human exploitation ...is an issue of paramount importance for conservation and natural resource management. Three main hypotheses have been proposed to explain fluctuations: (i) species interactions, such as predator-prey interactions, cause fluctuations, (ii) strongly nonlinear single-species dynamics cause fluctuations, and (iii) environmental variation cause fluctuations. We combine a general fisheries model with data from a global sample of fish species to assess how two of these hypothesis, nonlinear single-species dynamics and environmental variation, interact with human exploitation to affect the variability of fish populations. In contrast with recent analyses that suggest fishing drives increased fluctuations by changing intrinsic nonlinear dynamics, we show that single-species nonlinear dynamics alone, both in the presence and absence of fisheries, are unlikely to drive deterministic fluctuations in fish; nearly all fish populations fall into regions of stable dynamics. However, adding environmental variation dramatically alters the consequences of exploitation on the temporal variability of populations. In a variable environment, (i) the addition of mortality from fishing leads to increased temporal variability for all species examined, (ii) variability in recruitment rates of juveniles contributes substantially more to fluctuations than variation in adult mortality, and (iii) the correlation structure of juvenile and adult vital rates plays an important and underappreciated role in determining population fluctuations. Our results are robust to alternative model formulations and to a range of environmental autocorrelation.
Indices of abundance are the bedrock for stock assessments or empirical management procedures used to manage fishery catches for fish populations worldwide, and are generally obtained by processing ...catch-rate data. Recent research suggests that geostatistical models can explain a substantial portion of variability in catch rates via the location of samples (i.e. whether located in high- or low-density habitats), and thus use available catch-rate data more efficiently than conventional "design-based" or stratified estimators. However, the generality of this conclusion is currently unknown because geostatistical models are computationally challenging to simulation-test and have not previously been evaluated using multiple species. We develop a new maximum likelihood estimator for geostatistical index standardization, which uses recent improvements in estimation for Gaussian random fields. We apply the model to data for 28 groundfish species off the U.S. West Coast and compare results to a previous "stratified" index standardization model, which accounts for spatial variation using post-stratification of available data. This demonstrates that the stratified model generates a relative index with 60% larger estimation intervals than the geostatistical model. We also apply both models to simulated data and demonstrate (i) that the geostatistical model has well-calibrated confidence intervals (they include the true value at approximately the nominal rate), (ii) that neither model on average under- or overestimates changes in abundance, and (iii) that the geostatistical model has on average 20% lower estimation errors than a stratified model. We therefore conclude that the geostatistical model uses survey data more efficiently than the stratified model, and therefore provides a more cost-efficient treatment for historical and ongoing fish sampling data.
Individuals relying on natural resource extraction for their livelihood face high income variability driven by a mix of environmental, biological, management, and economic factors. Key to managing ...these industries is identifying how regulatory actions and individual behavior affect income variability, financial risk, and, by extension, the economic stability and the sustainable use of natural resources. In commercial fisheries, communities and vessels fishing a greater diversity of species have less revenue variability than those fishing fewer species. However, it is unclear whether these benefits extend to the actions of individual fishers and how year-to-year changes in diversification affect revenue and revenue variability. Here, we evaluate two axes by which fishers in Alaska can diversify fishing activities. We show that, despite increasing specialization over the last 30 years, fishing a set of permits with higher species diversity reduces individual revenue variability, and fishing an additional permit is associated with higher revenue and lower variability. However, increasing species diversity within the constraints of existing permits has a fishery-dependent effect on revenue and is usually (87% probability) associated with increased revenue uncertainty the following year. Our results demonstrate that the most effective option for individuals to decrease revenue variability is to participate in additional or more diverse fisheries. However, this option is expensive, often limited by regulations such as catch share programs, and consequently unavailable to many individuals. With increasing climatic variability, it will be particularly important that individuals relying on natural resources for their livelihood have effective strategies to reduce financial risk.
Identifying the existence and magnitude of density dependence is one of the oldest concerns in ecology. Ecologists have aimed to estimate density dependence in population and community data by ...fitting a simple autoregressive (Gompertz) model for density dependence to time series of abundance for an entire population. However, it is increasingly recognized that spatial heterogeneity in population densities has implications for population and community dynamics. We therefore adapt the Gompertz model to approximate local densities over continuous space instead of population-wide abundance, and allow productivity to vary spatially using Gaussian random fields. We then show that the conventional (nonspatial) Gompertz model can result in biased estimates of density dependence (e.g., identifying oscillatory dynamics when not present) if densities vary spatially. By contrast, the spatial Gompertz model provides accurate and precise estimates of density dependence for a variety of simulation scenarios and data availabilities. These results are corroborated when comparing spatial and nonspatial models for data from 10 years and ~100 sampling stations for three long-lived rockfishes (
Sebastes
spp.) off the California, USA coast. In this case, the nonspatial model estimates implausible oscillatory dynamics on an annual time scale, while the spatial model estimates strong autocorrelation and is supported by model selection tools. We conclude by discussing the importance of improved data archiving techniques, so that spatial models can be used to reexamine classic questions regarding the existence and magnitude of density dependence in wild populations.
Environmental forces can create spatially synchronous dynamics among nearby populations. However, increased climate variability, driven by anthropogenic climate change, will likely enhance synchrony ...among spatially disparate populations. Population synchrony may lead to greater fluctuations in abundance, but the consequences of population synchrony across multiple scales of biological organization, including impacts to putative competitors, dependent predators or human communities, are rarely considered in this context.
Chinook salmon Oncorhynchus tshawytscha stocks distribute across the Northeast Pacific, creating spatially variable portfolios that support large ocean fisheries and marine mammal predators, such as killer whales Orcinus orca. We rely on a multi‐population model that simulates Chinook salmon ocean distribution and abundance to understand spatial portfolios, or variability in abundance within and among ocean distribution regions, of Chinook salmon stocks across 17 ocean regions from Southeast Alaska to California.
We found the expected positive correlation between the number of stocks in an ocean region and spatial portfolio strength; however, increased demographic synchrony eroded Chinook salmon spatial portfolios in the ocean. Moreover, we observed decreased resource availability within ocean fishery management jurisdictions but not within killer whale summer habitat. We found a strong portfolio effect across both Southern Resident and Northern Resident killer whale habitats that was relatively unaffected by increased demographic synchrony, likely a result of the large spatial area included in these habitats. However, within the areas of smaller fishing management jurisdictions we found a weakening of Chinook salmon portfolios and increased but inconsistent likelihood of low abundance years as demographic synchrony increased.
We suggest that management and conservation actions that reduce spatial synchrony can enhance short‐term ecosystem resilience by promoting the stabilizing effect multiple stocks have on aggregate Chinook salmon populations and overall resource availability.
This paper provides one of the first examples of a spatial portfolio effect applied at a scale relevant to predators and fisheries. The study demonstrates the value and applicability of understanding how environmental conditions influence spatially structured population dynamics.
1. Coasts and estuaries contain among the most productive and ecologically important habitats in the world and face intense pressure from current and projected human activities, including coastal ...development. Seagrasses are a key habitat feature in many estuaries perceived to be in widespread decline owing to human actions. 2. We use spatio-temporal models and a 41-year time series from 100s of km of shoreline which includes over 160 000 observations from Puget Sound, Washington, USA, to examine multiscale trends and drivers of eelgrass (Zostera spp.) change in an urbanizing estuary. 3. At whole estuary scale (100s of km), we find a stable and resilient eelgrass population despite a more than doubling of human population density and multiple major climactic stressors (e.g. ENSO events) over the period. However, the aggregate trend is not reflected at the site scale (10s of km), where some sites persistently increase while others decline. 4. Site trends were spatially asynchronous; adjacent sites sometimes exhibited opposite trends over the same period. Substantial change in eelgrass occurred at the subsite (0-1 km) scale, including both complete local loss and dramatic increase of eelgrass. 5. Metrics of local human development including shoreline armouring, upland development (imperviousness) and human density provide no explanatory power for eelgrass population change at any spatial scale. 6. Our results suggest that the appropriate scale for understanding eelgrass change is smaller than typically assumed (approximately 1- to 3-km scale) and contrasts strongly with previous work. 7. Synthesis. Despite ongoing conservation concern over seagrasses world-wide, eelgrass in Puget Sound has been highly resilient to both anthropogenic and environmental change over four decades. Our work provides general methods that can be applied to understand spatial and temporal scales of change and can be used to assess hypothesized drivers of change.
Pacific and Atlantic herring populations (genus Clupea) commonly experience episodic collapse and recovery. Recovery time durations are of great importance for the sustainability of fisheries and ...ecosystems. We collated information from 64 herring populations to characterize herring fluctuations and determine the time scales at low biomass and at high and low recruitment, and use generalized linear models and Random Survival Forests to identify the most important bottom‐up, top‐down and intrinsic factors influencing recovery times. Compared to non‐forage fish taxa, herring decline to lower minima, recover to higher maxima and show larger changes in biomass, implying herring are more prone to booms and busts than non‐forage fish species. Large year classes are more common in herring, but occur infrequently and are uncorrelated among regionally grouped stocks, implying local drivers of high recruitment. Management differs between Pacific and Atlantic herring fisheries, where at similarly low biomass, Pacific fisheries tend to be closed while Atlantic fisheries remain open. This difference had no apparent effect on herring recovery times, which averaged 11 years, although most stocks with longer recovery periods had not yet recovered at the end of the observation period. Biomass recovery is best explained by median recruitment and variability in sea surface height anomalies and sea surface temperatures—higher variability leads to shorter recovery times. In addition, the duration of recruitment failure is closely linked with low biomass. While recovery times rely on the nature of the relationship between spawning biomass and recruitment, they are still largely governed by complex and uncertain processes.
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.
Abstract
Euphausiids, or krill, are important energy links between primary producers and higher trophic levels in the California Current Ecosystem (CCE), but a thorough understanding of their ...variability at the coast-wide scale is limited. Using fisheries acoustics data collected during biennial joint US–Canada Integrated Ecosystem and Acoustic Trawl Surveys for Pacific hake (Merluccius productus), we developed a time series (n = 8 years; 2007–2019 odd years inclusive, and 2012) of krill abundance and examined relationships with environmental factors. Krill were located in waters off the west coasts of the United States and Canada, primarily in shallow basins and on the continental shelf, with greatest kernel density estimates near Cape Mendocino and the Juan de Fuca eddy system. Coast-wide krill abundance was variable, and lowest in 2015 during an extended marine heat wave, when 91% were located in British Columbia. Using hierarchical generalized additive models, we predicted greatest krill abundance in cooler waters (0.2°C below the time series average), within 10–20 km of the shelf break, and in bottom depths between 200 and 400 m. This newly developed coast-wide time series of krill abundance and distribution will inform ecosystem-based fisheries management efforts, and offers additional opportunities for studies of krill-dependent fish, seabirds, and marine mammals.
Heterogeneity in human responses and decision‐making can contribute to the resilience of social–ecological systems in the face of environmental, political and economic pressures. In fishery systems ...worldwide, the ability of harvesters to maintain a diverse portfolio of fishing strategies is important for building adaptive capacity. We used a case‐study approach to examine the complexity of factors that inhibit or promote diversification in fisheries of Alaska, one of the major fishing regions of the world. Through a combination of harvest records and literature review, we explored shifts in participation and portfolio diversity in Alaskan fisheries over three decades. The four case‐studies examined the responses of fishers, fleets and communities to multiple, intersecting pressures, including biological declines, market and price dynamics, fishery privatization and the 1989 Exxon Valdez oil spill. These cases illustrate how stressors acting at multiple scales can encourage or constrain opportunities for diversification, and that these opportunities may be spread inequitably across participants. Overall, we found evidence for reduced participation and increasing specialization in Alaskan commercial fisheries. While numerous factors explain these trends, policies like individual quota systems and the increasing cost of entry into fisheries are forcing consolidation at local to regional scales. A portfolio approach to managing fisheries that reduces barriers to diversification and includes broad representation of resource users and communities in management may help to maintain opportunity and choice for fishers.
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