Telemetry-validated nitrogen stable isotope clocks identify ocean-to-estuarine habitat shifts in mobile organisms

Throughout their life history, many animals transition among heterogeneous environments to facilitate behaviours such as reproduction, foraging and predator avoidance. The dynamic environmental and biological conditions experienced by mobile species are integrated in the chemical composition of their tissues, providing retrospective insight into movement. Here, we present a unique application of nitrogen stable isotope clocks (‘isotopic clocks’), which integrate tissue turnover rates, consumer stable isotope ratios and habitat-specific isotope baselines to predict time-since-immigration and the timing of habitat shifts in a migratory species. Nitrogen stable isotope values of blood plasma collected from juvenile sand tiger sharks Carcharias taurus, a species known to undertake seasonal movements between ocean and estuarine environments, were used to derive estimates of time-since-immigration and the timing of seasonal habitat shifts undertaken by this species. Nitrogen isotopic clocks estimated for 65 juvenile sand tiger sharks sampled across 6 years indicated that individual sharks predominantly arrived to estuarine habitats between June and July, with some individuals arriving as early as mid-May. These estimates were validated by comparing isotope-derived estuarine arrival times with those from acoustically tracked individuals. The median estuarine arrival day estimates from our isotopic approach aligned with estimates from acoustic telemetry for each sampling population. Sensitivity analyses indicated that isotopically inferred time-since-immigration and estuarine arrival estimates were robust to variation in isotopic turnover rate and diet tissue discrimination factors under multiple modelling scenarios. This suggests that parameterization of the nitrogen isotopic clock provides reliable estimates of time-since-immigration and day of arrival into new habitats if isotopic variation exists between origin and new locations. Our study presents a unique application of telemetry-validated isotope clocks to derive retrospective estimates of time-since-immigration and timing of habitat shifts for animals that seasonally traverse heterogeneous environments. This approach can be readily applied across many temporal and spatial scales, and to other species and ecosystems, to facilitate rapid assessment of changes in animal habitat use and broader ecosystem structure

Energetic consequences of resource use diversity in a marine carnivore

Understanding how intraspecific variation in the use of prey resources impacts energy metabolism has strong implications for predicting long-term fitness and is critical for predicting population-to-community level responses to environmental change. Here, we examine the energetic consequences of variable prey resource use in a widely distributed marine carnivore, juvenile sand tiger sharks (Carcharias taurus). We used carbon and nitrogen isotope analysis to identify three primary prey resource pools—demersal omnivores, pelagic forage, and benthic detritivores and estimated the proportional assimilation of each resource using Bayesian mixing models. We then quantified how the utilization of these resource pools impacted the concentrations of six plasma lipids and how this varied by ontogeny. Sharks exhibited variable reliance on two of three predominant prey resource pools: demersal omnivores and pelagic forage. Resource use variation was a strong predictor of energetic condition, whereby individuals more reliant upon pelagic forage exhibited higher blood plasma concentrations of very low-density lipoproteins, cholesterol, and triglycerides. These findings underscore how intraspecific variation in resource use may impact the energy metabolism of animals, and more broadly, that natural and anthropogenically driven fluctuations in prey resources could have longer term energetic consequences

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future