‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology

Non-parallel changes in songbird migration timing are not explained by changes in stopover duration

Shifts in the timing of animal migration are widespread and well-documented; however, the mechanism underlying these changes is largely unknown. In this study, we test the hypothesis that systematic changes in stopover duration—the time that individuals spend resting and refueling at a site—are driving shifts in songbird migration timing. Specifically, we predicted that increases in stopover duration at our study site could generate increases in passage duration—the number of days that a study site is occupied by a particular species—by changing the temporal breadth of observations and vise versa. We analyzed an uninterrupted 46-year bird banding dataset from Massachusetts, USA using quantile regression, which allowed us to detect changes in early-and late-arriving birds, as well as changes in passage duration. We found that median spring migration had advanced by 1.04 days per decade; that these advances had strengthened over the last 13 years; and that early-and late-arriving birds were advancing in parallel, leading to negligible changes in the duration of spring passage at our site (+0.07 days per decade). In contrast, changes in fall migration were less consistent. Across species, we found that median fall migration had delayed by 0.80 days per decade, and that changes were stronger in late-arriving birds, leading to an average increase in passage duration of 0.45 days per decade. Trends in stopover duration, however, were weak and negative and, as a result, could not explain any changes in passage duration. We discuss, and provide some evidence, that changes in population age-structure, cryptic geographic variation, or shifts in resource availability are consistent with increases in fall passage duration. Moreover, we demonstrate the importance of evaluating changes across the entire phenological distribution, rather than just the mean, and stress this as an important consideration for future studies.

Evaluating and presenting uncertainty in model-based unconstrained ordination

Variability in ecological community composition is often analyzed by recording the presence or abundance of taxa in sample units, calculating a symmetric matrix of pairwise distances or dissimilarities among sample units and then mapping the resulting matrix to a low-dimensional representation through methods collectively called ordination. Unconstrained ordination only uses taxon composition data, without any environmental or experimental covariates, to infer latent compositional gradients associated with the sampling units. Commonly, such distance-based methods have been used for ordination, but recently there has been a shift toward model-based approaches. Model-based unconstrained ordinations are commonly formulated using a Bayesian latent factor model that permits uncertainty assessment for parameters, including the latent factors that correspond to gradients in community composition. While model-based methods have the additional benefit of addressing uncertainty in the estimated gradients, typically the current practice is to report point estimates without summarizing uncertainty. To demonstrate the uncertainty present in model-based unconstrained ordination, the well-known spider and dune data sets were analyzed and shown to have large uncertainty in the ordination projections. Hence to understand the factors that contribute to the uncertainty, simulation studies were conducted to assess the impact of additional sampling units or species to help inform future ordination studies that seek to minimize variability in the latent factors. Accurate reporting of uncertainty is an important part of transparency in the scientific process; thus, a model-based approach that accounts for uncertainty is valuable. An R package, UncertainOrd, contains visualization tools that accurately represent estimates of the gradients in community composition in the presence of uncertainty.

Estimating seed and pollen dispersal kernels from genetic data demonstrates a high pollen dispersal capacity for an endangered palm species

PREMISE OF THE STUDY

Seed and pollen dispersal are key processes shaping plant population dynamics and maintaining genetic diversity. The essence of these processes is the movement of propagules from a parental tree to the site of propagule establishment. The estimation of plant dispersal kernels has remained challenging due to the difficulty of making direct observations. We estimated the dispersal capacity of the endangered palm Euterpe edulis, whose seeds are dispersed by vertebrates and pollen by insects.

METHODS

We used a hierarchical Bayesian model with genetic data from reproductive plants, juveniles, and embryos to estimate dispersal kernels. Our analyses account for genotyping error and uncertainty in parental assignment.

KEY RESULTS

We found that seeds were dispersed at most a few hundred meters, but pollen was dispersed up to several kilometers. We hypothesize that this long-distance pollen dispersal is generated mainly by euglossine bees, whereas the main dispersal vectors for short-distance seed dispersal are thrushes. The long-distance dispersal of pollen suggests a high level of gene flow that should maintain genetic diversity of E. edulis. Despite the relation between long-distance dispersal and genetic diversity, we observed low genetic diversity and inbreeding within the local population, which are probably due to restricted gene flow due to the low density of this population and its aggregated spatial distribution.

CONCLUSIONS

We conclude that if conservation actions are able to restore the population density of E. edulis, the recovery of its genetic diversity will be facilitated because of its high dispersal capacity, especially with regard to pollen.

Stream acidification and reduced aquatic prey availability are associated with dietary shifts in an obligate riparian Neotropical migratory songbird

Streams and their surrounding riparian habitats are linked by reciprocal exchanges of insect prey essential to both aquatic and terrestrial consumers. Aquatic insects comprise a large proportion of total prey in riparian habitats and are opportunistically exploited by terrestrial insectivores; however, several species of songbirds are known to preferentially target aquatic prey via specialized foraging strategies. For these songbirds, reduced availability of aquatic insects via stream acidification may result in compensatory changes in provisioning during the nesting period, thereby influencing both adult and nestling diet composition. In this study, we used DNA metabarcoding to test the hypothesis that an obligate riparian Neotropical migratory songbird, the Louisiana Waterthrush (Parkesia motacilla), expands its diet to compensate for the loss of preferred aquatic prey taxa (primarily pollution-sensitive Ephemeroptera, Plecoptera, and Trichoptera) as a result of stream acidification. Our results revealed that both adult and nestling waterthrush exhibited an increase in dietary richness and niche breadth resulting from the consumption of terrestrial prey taxa in acidified riparian habitats. In contrast, compensatory dietary shifts were not observed in syntopic Neotropical migrant species known to primarily provision terrestrial prey taxa. In addition to providing support for our hypothesis that waterthrush compensate for stream acidification and aquatic prey limitations by expanding their diet, our findings highlight the vulnerability of Louisiana Waterthrush to anthropogenic disturbances that compromise stream quality or reduce the availability of pollution-sensitive aquatic insects.

Partitioning detectability components in populations subject to within-season temporary emigration using binomial mixture models

Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model's potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3-5 surveys each spring and fall 2010-2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability.

Abundance, biomass production, nutrient content, and the possible role of terrestrial salamanders in Missouri Ozark forest ecosystems

The transfer of energy and nutrients largely depends on the role of animals in the movement of biomass between trophic levels and ecosystems. Despite the historical recognition that amphibians could play an important role in the movement of biomass and nutrients, very few studies have provided reliable estimates of abundance and density of amphibians to reveal their true importance. Here, we provide robust estimates of abundance and density of a dominant species, the Southern Redback Salamander (Plethodon serratus Grobman, 1944), in the oak forest ecosystem of the Ozark Highlands in Missouri. We then use the abundance and density estimates to calculate biomass and nutrient content of salamanders at our study sites in the Ozark forests. Salamanders at the Sinkin Experimental Forest comprise a large amount of protein, energy, and nutrients that greatly exceed estimates derived some 35 years ago in the Hubbard Brook Experimental Forest, New Hampshire. Our estimates (7 300 – 12 900 salamanders·ha−1) are 2–4 times greater than the values reported by Burton and Likens (1975a, Ecology, 56: 1068–1080; 1975b, Copeia, 1975: 541–546). Furthermore, we show that density estimates of other small plethodontid species reported in the literature are nearly an order of magnitude greater than that reported by Burton and Likens. We believe this indicates that previous results have underestimated the importance of salamander biomass, nutrient, and energy flux, and their functional role in regulating invertebrates and carbon retention in forest ecosystems.