Prior choice and data requirements of Bayesian multivariate hierarchical models fit to tag-recovery data: The need for power analyses.

Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag-recovery data. In these applications, increasingly negative correlation between survival and recovery has been interpreted as evidence for increasingly additive harvest mortality. The power of these hierarchal models to detect nonzero correlations has rarely been evaluated, and these few studies have not focused on tag-recovery data, which is a common data type. We assessed the power of multivariate hierarchical models to detect negative correlation between annual survival and recovery. Using three priors for multivariate normal distributions, we fit hierarchical effects models to a mallard (Anas platyrhychos) tag-recovery data set and to simulated data with sample sizes corresponding to different levels of monitoring intensity. We also demonstrate more robust summary statistics for tag-recovery data sets than total individuals tagged. Different priors led to substantially different estimates of correlation from the mallard data. Our power analysis of simulated data indicated most prior distribution and sample size combinations could not estimate strongly negative correlation with useful precision or accuracy. Many correlation estimates spanned the available parameter space (-1,1) and underestimated the magnitude of negative correlation. Only one prior combined with our most intensive monitoring scenario provided reliable results. Underestimating the magnitude of correlation coincided with overestimating the variability of annual survival, but not annual recovery. The inadequacy of prior distributions and sample size combinations previously assumed adequate for obtaining robust inference from tag-recovery data represents a concern in the application of Bayesian hierarchical models to tag-recovery data. Our analysis approach provides a means for examining prior influence and sample size on hierarchical models fit to capture-recapture data while emphasizing transferability of results between empirical and simulation studies.

Date of marine annulus formation in Atlantic salmon (Salmo salar) and implications for retrospective growth analyses using scales.

Fish scales have increasingly been used to quantify annual and seasonal growth trends and in efforts to relate growth to environmental conditions. Understanding the timing of formation of an annulus (a group of narrowly spaced circuli) is critical when assessing the influence of marine ecosystem conditions on seasonal growth patterns of Atlantic salmon, yet the literature does not provide consistent answers regarding the timing or drivers of marine annulus formation. This study demonstrates a novel method for estimating stock-specific annulus formation timing based on marked individuals with known emigration and return/recovery dates. An equation was applied to estimate the date of annulus completion for Atlantic salmon (Salmo salar) using known dates, number of circuli after the most recent annulus and marine circulus deposition rate. Five marine circulus deposition rate scenarios were tested, some of which accounted for individual, seasonal and age-related variability and others which use previously published marine circulus deposition rates. Based on these results, an argument is presented to reconsider the practice of assigning annulus formation dates to winter solstice in favour of dates estimated by a scenario that accounts for individual, seasonal and age-related variation in circulus deposition. This scenario suggests that annulus formation occurs between mid-February and late March. In this case, the annulus would be formed during the coldest part of the year in the primary overwintering area for North American Atlantic salmon.

Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland.

With warmer springs, herbivores migrating to Arctic breeding grounds may experience phenological mismatches between their energy demands and the availability of high quality forage. Yet, how the timing of the start of the season and herbivore arrival influences forage quality is often unknown. In coastal western Alaska, approximately one million migratory geese arrive each spring to breed, where foliar %N and C:N ratios are linked to gosling survival and population growth. We conducted a three-year experiment where we manipulated the start of the growing season using warming chambers and grazing times using captive Pacific black brant (Branta bernicla nigricans) to examine how the timing of these events influences the quality of an important forage species. Our results suggest that grazing timing plays a much greater role than an advanced growing season in determining forage quality. All top models included grazing timing, and suggested that compared to typical grazing timing, early grazing significantly reduced foliar %C by 6% and C:N ratios by 16%, while late goose grazing significantly reduced foliar %N by 15% and increased foliar C:N ratios by 21%. While second-ranking top models included the effect of season, the advanced growing season effect was not significant and only reduced %N by 4%, increased %C by <1%, and increased C:N ratios by 5% compared to an ambient growing season. In summary, in years where geese arrive early, they will consume higher quality forage when they arrive and throughout the season, while in years that geese arrive late they will consume lower quality forage when they arrive and for the remainder of the season. When the growing season starts has only a minor influence on this pattern. Our findings suggest that cues determining migration and arrival times to breeding areas are important factors influencing forage quality for geese in western Alaska.

Direct effects of warming increase woody plant abundance in a subarctic wetland.

Both the direct effects of warming on a species' vital rates and indirect effects of warming caused by interactions with neighboring species can influence plant populations. Furthermore, herbivory mediates the effects of warming on plant community composition in many systems. Thus, determining the importance of direct and indirect effects of warming, while considering the role of herbivory, can help predict long-term plant community dynamics. We conducted a field experiment in the coastal wetlands of western Alaska to investigate how warming and herbivory influence the interactions and abundances of two common plant species, a sedge, Carex ramenskii, and a dwarf shrub, Salix ovalifolia. We used results from the experiment to model the equilibrium abundances of the species under different warming and grazing scenarios and to determine the contribution of direct and indirect effects to predict population changes. Consistent with the current composition of the landscape, model predictions suggest that Carex is more abundant than Salix under ambient temperatures with grazing (53% and 27% cover, respectively). However, with warming and grazing, Salix becomes more abundant than Carex (57% and 41% cover, respectively), reflecting both a negative response of Carex and a positive response of Salix to warming. While grazing reduced the cover of both species, herbivory did not prevent a shift in dominance from sedges to the dwarf shrub. Direct effects of climate change explained about 97% of the total predicted change in species cover, whereas indirect effects explained only 3% of the predicted change. Thus, indirect effects, mediated by interactions between Carex and Salix, were negligible, likely due to use of different niches and weak interspecific interactions. Results suggest that a 2°C increase could cause a shift in dominance from sedges to woody plants on the coast of western Alaska over decadal timescales, and this shift was largely a result of the direct effects of warming. Models predict this shift with or without goose herbivory. Our results are consistent with other studies showing an increase in woody plant abundance in the Arctic and suggest that shifts in plant-plant interactions are not driving this change.