Species redistribution creates unequal outcomes for multispecies fisheries under projected climate change.

Climate change drives species distribution shifts, affecting the availability of resources people rely upon for food and livelihoods. These impacts are complex, manifest at local scales, and have diverse effects across multiple species. However, for wild capture fisheries, current understanding is dominated by predictions for individual species at coarse spatial scales. We show that species-specific responses to localized environmental changes will alter the collection of co-occurring species within established fishing footprints along the U.S. West Coast. We demonstrate that availability of the most economically valuable, primary target species is highly likely to decline coastwide in response to warming and reduced oxygen concentrations, while availability of the most abundant, secondary target species will potentially increase. A spatial reshuffling of primary and secondary target species suggests regionally heterogeneous opportunities for fishers to adapt by changing where or what they fish. Developing foresight into the collective responses of species at local scales will enable more effective and tangible adaptation pathways for fishing communities.

Recommendations for quantifying and reducing uncertainty in climate projections of species distributions.

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

The shadow model: how and why small choices in spatially explicit species distribution models affect predictions.

The use of species distribution models (SDMs) has rapidly increased over the last decade, driven largely by increasing observational evidence of distributional shifts of terrestrial and aquatic populations. These models permit, for example, the quantification of range shifts, the estimation of species co-occurrence, and the association of habitat to species distribution and abundance. The increasing complexity of contemporary SDMs presents new challenges-as the choices among modeling options increase, it is essential to understand how these choices affect model outcomes. Using a combination of original analysis and literature review, we synthesize the effects of three common model choices in semi-parametric predictive process species distribution modeling: model structure, spatial extent of the data, and spatial scale of predictions. To illustrate the effects of these choices, we develop a case study centered around sablefish (Anoplopoma fimbria) distribution on the west coast of the USA. The three modeling choices represent decisions necessary in virtually all ecological applications of these methods, and are important because the consequences of these choices impact derived quantities of interest (e.g., estimates of population size and their management implications). Truncating the spatial extent of data near the observed range edge, or using a model that is misspecified in terms of covariates and spatial and spatiotemporal fields, led to bias in population biomass trends and mean distribution compared to estimates from models using the full dataset and appropriate model structure. In some cases, these suboptimal modeling decisions may be unavoidable, but understanding the tradeoffs of these choices and impacts on predictions is critical. We illustrate how seemingly small model choices, often made out of necessity or simplicity, can affect scientific advice informing management decisions-potentially leading to erroneous conclusions about changes in abundance or distribution and the precision of such estimates. For example, we show how incorrect decisions could cause overestimation of abundance, which could result in management advice resulting in overfishing. Based on these findings and literature gaps, we outline important frontiers in SDM development.

Limited evidence for sardine and anchovy asynchrony: re-examining an old story.

Asynchronous fluctuations in abundance between species with similar ecological roles can stabilize food webs and support coexistence. Sardine (Sardinops spp.) and anchovy (Engraulis spp.) have long been used as an example of this pattern because low-frequency variation in catches of these species appears to occur out of phase, suggesting that fisheries and generalist predators could be buffered against shifts in productivity of a single species. Using landings data and biomass and recruitment estimates from five regions, we find that species do not have equivalent peak abundances, suggesting that high abundance in one species does not compensate for low abundance in the other. We find that globally there is a stronger pattern of asynchrony in landings compared to biomass, such that landings data have exaggerated the patterns of asynchrony. Finally, we show that power to detect decadal asynchrony is poor, requiring a time series more than twice the length of the period of fluctuation. These results indicate that it is unlikely that the dynamics of these two species are compensatory enough to buffer fisheries and predators from changes in abundance, and that the measurements of asynchrony have largely been a statistical artefact of using short time series and landings data to infer ecology.

Old-Growth Fishes Become Scarce under Fishing.

Researchers have long recognized the importance of ecological differences at the species level in structuring natural communities yet until recently have often overlooked the influence of intraspecific trait variation, which can profoundly alter community dynamics [1]. Human extraction of living resources can reduce intraspecific trait variation by, for example, causing truncation of age and size structure of populations, where numbers of older individuals decline far more with exploitation than younger individuals. Age truncation can negatively affect population and community stability, increasing variability in population and community biomass [2-6], reducing productivity [7-10] and life-history diversity in traits such as the spatial and temporal pattern of reproduction and migration [4, 11-16]. Here, we quantified the extent of age truncation in 63 fished populations across five ocean regions, as measured by how much the proportions of fish in the oldest age groups declined over time. The proportion of individuals in the oldest age classes decreased significantly in 79% to 97% of populations (compared to historical or unfished values, respectively), and the magnitude of decline was greater than 90% in 32% to 41% of populations. The pervasiveness and intensity of age truncation indicates that fishing is likely reducing the stability of many marine communities. Our findings suggest that more emphasis should be given to management measures that reduce the impact of fishing on age truncation, including no-take areas, slot limits that prohibit fishing on all except a narrow range of fish sizes, and rotational harvesting.

Marine reserves can enhance ecological resilience.

The goals of ecosystem-based management (EBM) include protecting ecological resilience, the magnitude of a perturbation that a community can withstand and remain in a given state. As a tool to achieve this goal, no-take marine reserves may enhance resilience by protecting source populations or reduce it by concentrating fishing in harvested areas. Here, we test whether spatial management with marine reserves can increase ecological resilience compared to non-spatial (conventional) management using a dynamic model of a simplified fish community with structured predation and competition that causes alternative stable states. Relative to non-spatial management, reserves increase the resilience of the desired (predator-dominated) equilibrium state in both stochastic and deterministic environments, especially under intensive fishing. As a result, spatial management also increases the feasibility of restoring degraded (competitor-dominated) systems, particularly if combined with culling of competitors or stock enhancement of adult predators.

Beyond connectivity: how empirical methods can quantify population persistence to improve marine protected-area design.

Demographic connectivity is a fundamental process influencing the dynamics and persistence of spatially structured populations. Consequently, quantifying connectivity is essential for properly designing networks of protected areas so that they achieve their core ecological objective of maintaining population persistence. Recently, many empirical studies in marine systems have provided essential, and historically challenging to obtain, data on patterns of larval dispersal and export from marine protected areas (MPAs). Here, we review the empirical studies that have directly quantified the origins and destinations of individual larvae and assess those studies' relevance to the theory of population persistence and MPA design objectives. We found that empirical studies often do not measure or present quantities that are relevant to assessing population persistence, even though most studies were motivated or contextualized by MPA applications. Persistence of spatial populations, like nonspatial populations, depends on replacement, whether individuals reproduce enough in their lifetime to replace themselves. In spatial populations, one needs to account for the effect of larval dispersal on future recruitment back to the local population through local retention and other connectivity pathways. The most commonly reported descriptor of larval dispersal was the fraction of recruitment from local origin (self-recruitment). Self-recruitment does not inform persistence-based MPA design because it is a fraction of those arriving, not a fraction of those leaving (local retention), so contains no information on replacement. Some studies presented connectivity matrices, which can inform assessments of persistence with additional knowledge of survival and fecundity after recruitment. Some studies collected data in addition to larval dispersal that could inform assessments of population persistence but which were not presented in that way. We describe how three pieces of empirical information are needed to fully describe population persistence in a network of MPAs: (1) lifetime fecundity, (2) the proportion of larvae that are locally retained (or the full connectivity matrix), and (3) survival rate after recruitment. We conclude by linking theory and data to provide detailed guidance to empiricists and practitioners on field sampling design and data presentation that better informs the MPA objective of population persistence.

Comparative demography of skates: life-history correlates of productivity and implications for management.

Age-structured demographic models were constructed based on empirical estimates of longevity and maturity for five deepwater Bering Sea skates to investigate how observed differences in life history parameters affect population growth rates. Monte Carlo simulations were used to incorporate parameter uncertainty. Estimated population growth rates ranged from 1.045 to 1.129 yr(-1) and were lower than those reported for other Alaskan skates and most chondrichthyans. Population growth rates of these and other high-latitude skates increased with relative reproductive lifespan, but displayed no significant relationship with body size or depth distribution, suggesting that assemblage shifts may be difficult to predict for data-poor taxa. Elasticity analyses indicated that juvenile and adult survival had greater per-unit effects on population growth rates than did egg-case survival or fecundity. Population growth rate was affected more by uncertainty in age at maturity than maximum age. The results of this study indicate that if skates are deemed to be a management concern, gear modifications or depth-specific effort controls may be effective.