Rapid assessment of management options for promoting stock rebuilding in data-poor species under climate change.

The development of species recovery plans requires considering likely outcomes of different management interventions, but the complicating effects of climate change are rarely evaluated. We examined how qualitative network models (QNMs) can be deployed to support decision making when data, time, and funding limitations restrict use of more demanding quantitative methods. We used QNMs to evaluate management interventions intended to promote the rebuilding of a collapsed stock of blue king crab (Paralithodes platypus) (BKC) around the Pribilof Islands (eastern Bering Sea) to determine how their potential efficacy may change under climate change. Based on stakeholder input and a literature review, we constructed a QNM that described the life cycle of BKC, key ecological interactions, potential climate-change impacts, relative interaction strengths, and uncertainty in terms of interaction strengths and link presence. We performed sensitivity analyses to identify key sources of prediction uncertainty. Under a scenario of no climate change, predicted increases in BKC were reliable only when stock enhancement was implemented in a BKC hatchery-program scenario. However, when climate change was accounted for, the intervention could not counteract its adverse impacts, which had an overall negative effect on BKC. The remaining management scenarios related to changes in fishing effort on BKC predators. For those scenarios, BKC outcomes were unreliable, but climate change further decreased the probability of observing recovery. Including information on relative interaction strengths increased the likelihood of predicting positive outcomes for BKC approximately 5-50% under the management scenarios. The largest gains in prediction precision will be made by reducing uncertainty associated with ecological interactions between adult BKC and red king crab (Paralithodes camtschaticus). Qualitative network models are useful options when data are limited, but they remain underutilized in conservation.

Evaluación Rápida de las Opciones de Manejo para la Promoción de la Recuperación de Especies con Deficiencia de Datos bajo el Cambio Climático Resumen El desarrollo de los planes de recuperación de especies requiere de la consideración de los resultados probables de las diferentes intervenciones de manejo, pero los efectos agravantes del cambio climático rara vez están incluidos en esta evaluación. Examinamos cómo los modelos cualitativos de redes (QNMs) pueden implementarse para apoyar la toma de decisiones cuando los datos, el tiempo y el financiamiento sufren limitaciones que restringen el uso de métodos cuantitativos más demandantes. Usamos los QNMs para evaluar las intervenciones de manejo con la intención de promover el repoblamiento del colapsado cangrejo rey azul (Paralithodes platypus) (BKC) alrededor de las islas Pribilof (oriente del Mar de Bering) y así determinar cómo su eficiencia potencial puede modificarse bajo el cambio climático. Con base en aportaciones de los grupos de interés y una revisión bibliográfica construimos una QNM que describía el ciclo de vida del BKC, sus interacciones ecológicas importantes, impactos potenciales del cambio climático, fortalezas relativas de interacción, y la incertidumbre en relación con las fortalezas de interacción y la presencia de vínculos. Realizamos análisis de sensibilidad para identificar las fuentes clave de incertidumbre en la predicción. Bajo un escenario de ausencia de cambio climático, los incrementos pronosticados en la población de BKC fueron confiables solamente cuando el reforzamiento de la población se realizó en un escenario de programa de cultivo de BKC. Sin embargo, cuando se incluyó el cambio climático, la intervención de conservación no pudo contrarrestar los impactos adversos del cambio climático, lo cual tuvo un efecto negativo generalizado sobre los BKC. Los escenarios de manejo restantes estuvieron relacionados con los cambios en los esfuerzos de pesca sobre los depredadores del BKC. Para los estos últimos escenarios, los resultados de la población de BKC no fueron confiables, pero el cambio climático disminuyó todavía más la probabilidad de observar una recuperación. La inclusión de información sobre las fortalezas relativas de interacción incrementó la posibilidad de predecir los resultados de la población de BKC en ∼ 5 - 50% bajo los escenarios de manejo. Las mayores ganancias en la precisión de la predicción se lograrán reduciendo la incertidumbre asociada con las interacciones ecológicas entre los BKC adultos y el cangrejo rey rojo (Paralithodes camtschaticus). Los modelos cualitativos de redes son opciones útiles cuando los datos son limitados, pero permanecen subutilizados en la conservación.

Energetically relevant predator-prey body mass ratios and their relationship with predator body size.

Food web structure and dynamics depend on relationships between body sizes of predators and their prey. Species-based and community-wide estimates of preferred and realized predator-prey mass ratios (PPMR) are required inputs to size-based size spectrum models of marine communities, food webs, and ecosystems. Here, we clarify differences between PPMR definitions in different size spectrum models, in particular differences between PPMR measurements weighting prey abundance in individual predators by biomass (r bio) and numbers (r num). We argue that the former weighting generates PPMR as usually conceptualized in equilibrium (static) size spectrum models while the latter usually applies to dynamic models. We use diet information from 170,689 individuals of 34 species of fish in Alaskan marine ecosystems to calculate both PPMR metrics. Using hierarchical models, we examine how explained variance in these metrics changed with predator body size, predator taxonomic resolution, and spatial resolution. In the hierarchical analysis, variance in both metrics emerged primarily at the species level and substantially less variance was associated with other (higher) taxonomic levels or with spatial resolution. This suggests that changes in species composition are the main drivers of community-wide mean PPMR. At all levels of analysis, relationships between weighted mean r bio or weighted mean r num and predator mass tended to be dome-shaped. Weighted mean r num values, for species and community-wide, were approximately an order of magnitude higher than weighted mean r bio, reflecting the consistent numeric dominance of small prey in predator diets. As well as increasing understanding of the drivers of variation in PPMR and providing estimates of PPMR in the north Pacific Ocean, our results demonstrate that that r bio or r num, as well as their corresponding weighted means for any defined group of predators, are not directly substitutable. When developing equilibrium size-based models based on bulk energy flux or comparing PPMR estimates derived from the relationship between body mass and trophic level with those based on diet analysis, weighted mean r bio is a more appropriate measure of PPMR. When calibrating preference PPMR in dynamic size spectrum models then weighted mean r num will be a more appropriate measure of PPMR.

Stable Isotope Applications for Understanding Shark Ecology in the Northeast Pacific Ocean.

Stable isotopes are used to address a wide range of ecological questions and can help researchers and managers better understand the movement and trophic ecology of sharks. Here, we review how shark studies from the Northeast Pacific Ocean (NEP) have employed stable isotopes to estimate trophic level and diet composition and infer movement and habitat-use patterns. To date, the number of NEP shark studies that have used stable isotopes is limited, suggesting that the approach is underutilized. To aid shark researchers in understanding the strengths and limitations of the approach, we provide a brief overview of carbon and nitrogen stable isotope trophic discrimination properties (e.g., change in δ15N between predator and prey), tissue sample preparation methods specific to elasmobranchs, and methodological considerations for the estimation of trophic level and diet composition. We suggest that stable isotopes are a potentially powerful tool for addressing basic questions about shark ecology and are perhaps most valuable when combined and analysed with other data types (e.g., stomach contents, tagging data, or other intrinsic biogeochemical markers).

Implications of scaled δ15N fractionation for community predator-prey body mass ratio estimates in size-structured food webs.

Nitrogen stable isotope ratios (δ(15) N) may be used to estimate community-level relationships between trophic level (TL) and body size in size-structured food webs and hence the mean predator to prey body mass ratio (PPMR). In turn, PPMR is used to estimate mean food chain length, trophic transfer efficiency and rates of change in abundance with body mass (usually reported as slopes of size spectra) and to calibrate and validate food web models. When estimating TL, researchers had assumed that fractionation of δ(15) N (Δδ(15) N) did not change with TL. However, a recent meta-analysis indicated that this assumption was not as well supported by data as the assumption that Δδ(15) N scales negatively with the δ(15) N of prey. We collated existing fish community δ(15) N-body size data for the Northeast Atlantic and tropical Western Arabian Sea with new data from the Northeast Pacific. These data were used to estimate TL-body mass relationships and PPMR under constant and scaled Δδ(15) N assumptions, and to assess how the scaled Δδ(15) N assumption affects our understanding of the structure of these food webs. Adoption of the scaled Δδ(15) N approach markedly reduces the previously reported differences in TL at body mass among fish communities from different regions. With scaled Δδ(15) N, TL-body mass relationships became more positive and PPMR fell. Results implied that realized prey size in these size-structured fish communities are less variable than previously assumed and food chains potentially longer. The adoption of generic PPMR estimates for calibration and validation of size-based fish community models is better supported than hitherto assumed, but predicted slopes of community size spectra are more sensitive to a given change or error in realized PPMR when PPMR is small.

Seasonal carbonate chemistry covariation with temperature, oxygen, and salinity in a fjord estuary: implications for the design of ocean acidification experiments.

Carbonate chemistry variability is often poorly characterized in coastal regions and patterns of covariation with other biologically important variables such as temperature, oxygen concentration, and salinity are rarely evaluated. This absence of information hampers the design and interpretation of ocean acidification experiments that aim to characterize biological responses to future pCO2 levels relative to contemporary conditions. Here, we analyzed a large carbonate chemistry data set from Puget Sound, a fjord estuary on the U.S. west coast, and included measurements from three seasons (winter, summer, and fall). pCO2 exceeded the 2008-2011 mean atmospheric level (392 µatm) at all depths and seasons sampled except for the near-surface waters (< 10 m) in the summer. Further, undersaturated conditions with respect to the biogenic carbonate mineral aragonite were widespread (Ωar<1). We show that pCO2 values were relatively uniform throughout the water column and across regions in winter, enriched in subsurface waters in summer, and in the fall some values exceeded 2500 µatm in near-surface waters. Carbonate chemistry covaried to differing levels with temperature and oxygen depending primarily on season and secondarily on region. Salinity, which varied little (27 to 31), was weakly correlated with carbonate chemistry. We illustrate potential high-frequency changes in carbonate chemistry, temperature, and oxygen conditions experienced simultaneously by organisms in Puget Sound that undergo diel vertical migrations under present-day conditions. We used simple calculations to estimate future pCO2 and Ωar values experienced by diel vertical migrators based on an increase in atmospheric CO2. Given the potential for non-linear interactions between pCO2 and other abiotic variables on physiological and ecological processes, our results provide a basis for identifying control conditions in ocean acidification experiments for this region, but also highlight the wide range of carbonate chemistry conditions organisms may currently experience in this and similar coastal ecosystems.

Evaluating δ(15)N-body size relationships across taxonomic levels using hierarchical models.

Ecologists routinely set out to estimate the trophic position of individuals, populations, and species composing food webs, and nitrogen stable isotopes (δ(15)N) are a widely used proxy for trophic position. Although δ(15)N values are often sampled at the level of individuals, estimates and confidence intervals are frequently sought for aggregations of individuals. If individual δ(15)N values are correlated as an artifact of sampling design (e.g., clustering of samples in space or time) or due to intrinsic groupings (e.g., life history stages, social groups, taxonomy), such estimates may be biased and exhibit overly optimistic confidence intervals. However, these issues can be accommodated using hierarchical modeling methods. Here, we demonstrate how hierarchical models offer an additional quantitative tool for investigating δ(15)N variability and we explicitly evaluate how δ(15)N varies with body size at successively higher levels of taxonomic aggregation in a diverse fish assemblage. The models take advantage of all available data, better account for uncertainty in parameters estimates, may improve inferences on coefficients corresponding to groups with small to moderate sample sizes, and partition variation across model levels, which provides convenient summaries of the 'importance' of each level in terms of unexplained heterogeneity in the data. These methods can easily be applied to diet-based studies of trophic position. Although hierarchical models are well-understood and established tools, their benefits have yet to be fully reaped by stable isotope and food web ecologists. We suggest that hierarchical models can provide a robust framework for conceptualizing and statistically modeling trophic position at multiple levels of aggregation.