Biology subjects

Shoemaker, L. G.

Publications and source records attributed to Shoemaker, L. G..

7 recordsLinked to original sources

bioRxiv2025

Dispersal kernels influence the magnitude of environmental, biotic, and stochastic effects on the maintenance of metacommunity diversity

Dispersal plays a central role in shaping patterns of diversity in metacommunities. However, a primary focus on emigration rates may mischaracterize dispersal effects that actually arise from dispersal kernels. Kernels describe probabilistic movements between donor and recipient patches, but the influence of kernel shape on metacommunity diversity remains unclear. We used simulations to measure how kernels affect diversity across metacommunity scales and ecological contexts. We disentangled causes of these patterns using a novel approach quantifying the effects of environmental filtering, competition, stochasticity, and dispersal on fitness. Although metacommunities with shallow kernels followed expectations where emigration increased alpha-but decreased beta- and gamma-diversity, metacommunities with steeper kernels did not. Steeper kernels maintained regional diversity by reducing interspecific competition and stochastic extinctions, with dispersal conferring weaker benefits but less homogenization. Our work suggests dispersal kernels and emigration rates jointly regulate exposure to environmental variation and the balance of assembly mechanisms in metacommunities.

ecology↗

bioRxiv2025

Neighbor density-dependent facilitation promotescoexistence and internal oscillation

The ability of species to form diverse communities is not fully understood. Species are known to interact in various ways with their neighborhood. Despite this, common models of species coexistence assume that per capita interactions are constant and competitive, even as the environment changes. In this study, we investigate how neighbor density-dependent variation in the strength and sign of species interactions changes species and community dynamics. We show that by including these sources of variation, predictions of ecological dynamics are significantly improved compared to outcomes of typical models that hold interaction strengths constant. We compared how well models based on different functions of neighbor density and identity did in describing population trajectories (i.e., persistence over time) and community dynamics (i.e., temporal stability, synchrony and degree of oscillation) in simulated two-species communities and a real diverse annual plant system. In our simulated communities, we found the highest level of coexistence between species pairs when species interactions varied from competitive to facilitative according to neighbor density (i.e., following a sigmoid function). Introducing within-guild facilitation through a nonlinear bounded function allowed populations, both simulated and empirical, to avoid extinction or runaway growth. In fact, nonlinear bounded functions (i.e., exponential and sigmoid functions) predicted population trends over time within the range of abundances observed over the last 10 years. With the sigmoid function, the simulated communities of two species displayed a higher probability of synchrony and oscillation than other functional forms. These simulated communities did not always show temporal stability but were predicted to coexist. Overall, varying species interactions lead to realistic ecological trajectories and community dynamics when bounded by asymptotes based on neighbor density. These findings are important for advancing our understanding of how diverse communities are sustained and for operationalizing ecological theory in the study of the real world.

ecology↗

bioRxiv2021

Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach

1Modeling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species-interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighboring species from the diverse community that had non-generic interactions with our focal species. This sparse modeling approach facilitates exploration of species-interactions in diverse communities while maintaining a manageable number of parameters.

ecology↗

bioRxiv2021

Seed banks alter metacommunity diversity: the interactive effects of competition, germination, and survival

Dispersal and dormancy are two common strategies allowing for species persistence and the maintenance of ecological diversity in variable environments. However, theory and empirical tests of spatial diversity patterns tend to examine either mechanism in isolation. Here, we developed a stochastic, spatially explicit metacommunity model incorporating seed banks with varying germination and survival rates. We found that dormancy and dispersal had interactive, nonlinear effects on the maintenance and distribution of metacommunity diversity, where scale-dependent effects of seed banks were modified by local competitive interactions and dispersal. The interplay between seed germination and survival regulated the benefits of seed banks for diversity. Our study shows that the role of seed banks depends critically on spatial processes, and that classic predictions for how dispersal affects metacommunity diversity can be strongly influenced by dormancy. Together, these results highlight the need to consider both temporal and spatial storage when predicting multi-scale patterns of diversity.

ecology↗

bioRxiv2019

Quantifying the relative importance of competition, predation, and environmental variation for species coexistence

1Coexistence theory and food web theory are two cornerstones of the longstanding effort to understand how species coexist. Although competition and predation are known to act simultaneously in communities, theory and empirical study of the two processes continue to be developed independently. Here, we integrate modern coexistence theory and food web theory to simultaneously quantify the relative importance of predation, competition, and environmental fluctuations for species coexistence. We first examine coexistence in a classic multi-trophic model, adding complexity to the food web using a novel machine learning approach. We then apply our framework to a parameterized rocky intertidal food web model, partitioning empirical coexistence dynamics. We find that both environmental fluctuation and variation in predation contribute substantially to species coexistence. Unexpectedly, covariation in these two forces tends to destabilize coexistence, leading to new insights about the role of bottom-up versus top-down forces in both theory and the rocky intertidal ecosystem.

ecology↗

bioRxiv2019

A new variance ratio metric to detect the timescale of compensatory dynamics

Understanding the mechanisms governing ecological stability - why a property such as primary productivity is stable in some communities and variable in others - has long been a focus of ecology. Compensatory dynamics, in which anti-synchronous fluctuations between populations buffer against fluctuations at the community level, is a key theoretical mechanism of stability. Classically, compensatory dynamics have been quantified using a \"variance ratio\" approach that compares the ratio between community variance and aggregate population variance, such that a lower ratio indicates compensation and a higher ratio indicates synchrony among species fluctuations. However, population dynamics may be influenced by different drivers that operate on different timescales, and evidence from aquatic systems indicates that communities can be compensatory on some timescales and synchronous on others. The variance ratio and related metrics cannot reflect this timescale-specificity, yet have remained popular, especially in terrestrial systems. Here, we develop a timescale-specific variance ratio approach that formally decomposes the classical variance ratio according to the timescales of distinct contributions. The approach is implemented in a new R package, called tsvr, that accompanies this paper. We apply our approach to a long-term, multi-site grassland community dataset. Our approach demonstrates that the degree of compensation versus synchrony in community dynamics can vary by timescale. Across sites, population variability was typically greater over longer compared to shorter timescales. At some sites, minimal timescale-specificity in compensatory dynamics translated this pattern of population variability into a similar pattern of greater community variability on longer compared to shorter timescales. But at other sites, differentially stronger compensatory dynamics at longer compared to shorter timescales produced lower-than-expected community variability on longer timescales. Within every site there were plots that exhibited shifts in the strength of compensation between timescales. Our results highlight that compensatory versus synchronous dynamics are intrinsically timescale-dependent concepts, and our timescale-specific variance ratio provides a metric to quantify timescale-specificity and relate it back to the classic variance ratio.

ecology↗

bioRxiv2016

The Evolution of Primate Body Size: Left-skewness, Maximum Size, and Cope’s Rule

Body size is a key physiological, ecological, and evolutionary characteristic of species. Within most major clades, body size distributions follow a right-skewed pattern where most species are relatively small while a few are orders of magnitude larger than the median size. Using a novel database of 742 extant and extinct primate species sizes over the past 66 million years, we find that primates exhibit the opposite pattern: a left-skewed distribution. We investigate the long-term evolution of this distribution, first showing that the initial size radiation is consistent with plesiadapiformes (an extinct group with an uncertain ancestral relationship to primates) being ancestral to modern primates. We calculate the strength of Copes Rule, showing an initial tendency for descendants to increase in size relative to ancestors until the trend reverses 40 million years ago. We explore when the primate size distribution becomes left-skewed and study correlations between body size patterns and climactic trends, showing that across Old and New World radiations the body size distribution initially exhibits a right-skewed pattern. Left-skewness emerged early in Old World primates in a manner consistent with a previously unidentified possible maximum body size, which may be mechanistically related to primates encephalization and complex social groups.

evolutionary biology↗