Seed Dispersal Workshop Proposal; Annapolis, MD - Spring, 2016

University Of Maryland, College Park, College Park MD

Investigators

Abstract

Dispersal is a key process in the spread of populations, in biodiversity patterns from local to global scales, in gene flow and potential adaptation in novel environments, and in species responses to global change. Global change processes, such as climate change and fragmentation, alter local habitat conditions of species, and also the ecology and evolution of dispersal. These changes affect the ability of species to move or adapt in response to these processes. This workshop will assemble a diverse group of ecologists and mathematical biologists who study dispersal across scales, methodologies, and systems and who will bring together knowledge of existing empirical information, theoretical concepts, and mathematical approaches. The primary outcome of the workshop will be an evaluation of how data can be integrated with theoretical predictions and novel analytical, computational, and statistical advances for studying dispersal. The outcome will contribute to the ability to respond to global change. Collaborations among scientists will also be fostered. A workshop will identify current gaps in our understanding of the role of seed dispersal in plant populations and determine how to address these outstanding gaps in order to move towards a predictive understanding of plant populations under global change. Seed dispersal ecology is largely based on short-term, local-scale empirical studies for a small number of species or on theoretical dispersal models that often make simplified assumptions. These factors limit generality the ability to make quantitative predictions. By integrating data with models, the workshop will lead to computer experiments to a) gain a mechanistic understanding of the role of dispersal in plant population dynamics; b) test theoretical predictions using empirical data; and c) conduct sensitivity analyses to determine the robustness of conclusions to the type of available data, to missing data, and to different types of models. Gaps in knowledge and obstacles to progress will be identified, and scientific networking will be enhanced.