OPUS: CRS -- A Cross-Scale Synthesis in a Disturbance-Mediated System: Integrating Population, Community, and Metacommunity Perspectives

University Of Connecticut, Storrs CT

Investigators

Abstract

We live in a time of rapid environmental change, challenging the ability of species to persist and of ecosystems to thrive. Thus, it is important to understand how living things respond to environmental disturbances. This project will use a long-term data set to determine how hurricanes and droughts in Puerto Rico have affected the lives of snails and slugs. These creatures may seem trivial but are not -- they play an important role in forests by breaking down dead plants and recycling nutrients. Yet, they are increasingly threatened by unusually strong hurricanes and harsh droughts. The main goal of this project is to predict how populations and groups of species change over time. How resistant or vulnerable are snails and slugs to environmental change, and why? What can we learn from them? In addition to new analyses of long-term data, the researcher will synthesize results of his past work, focusing on changes that take place at different scales and thatare somehow linked across those scales. The project will also help break down disciplinary barriers by offering courses that bring together teams of students and faculty from basic and applied environmental sciences, statistics and geography to learn together about tough environmental challenges. Synthetic research will produce theoretical and empirical discoveries that integrate perspectives on disturbance and succession, cross-scale interactions, and metacommunities. A monograph will focus on conceptual refinement and integration of theory on disturbance and succession with that on metacommunities. A second monograph will focus on long-term spatiotemporal patterns at the levels of populations, communities, and metacommunities. Population-level attributes include incidence (presence-absence) and abundance, whereas community-level attributes comprise species richness, evenness, dominance, diversity, and rarity. Each metric will be decomposed into spatial components based on multiplicative and additive models to understand how the hierarchical spatial structure responds to disturbances and subsequently changes during secondary succession. Metacommunity analyses will integrate process-based (i.e., patch dynamics, species sorting, mass effects, and neutrality) and pattern-based (i.e., coherence, range turnover, and range boundary clumping) approaches for understanding the ways in which metacommunities change over time in a hurricane-prone system. A hierarchical approach to variance decomposition will be used to quantify unique variation explained by environmental characteristics, spatial variation of unknown origin, and spatially structured environmental variation. Several emerging statistical approaches for understanding spatiotemporal variation will be explored, including (1) intervention analysis or segmented regression; (2) extended generalized linear mixed model frameworks; and (3) multivariate time series approaches and simultaneous inference procedures that accommodate Poisson or negative binomial error terms for rare or uncommon species. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.