Collaborative Research: Scaling Properties of Ecological Variation in Complex Dynamical Systems

PROJECT SUMMARY Overview: The responses of complex biological systems to fluctuating environmental conditions are poorly characterized, despite the relevance of these relationships for understanding how systems will cope in a time of significant environmental change. In this project, we will investigate how variance in the external environment is translated into the variance of populations that exhibit complex dynamics. First, the project will work to identify dynamic properties that allow populations to be robust to changes in environmental variation in analytically tractable one-dimensional systems. Second, our team will explore similar effects in more realistic ecological systems including lagged density-dependence models and enemy-victim models where energy at one-level is transferred to another. Such systems often have highly nonlinear interaction rates, we will show how this nonlinearity can translate into robustness to external noise. Finally, we will look for the impact of these variance stabilizing effects at a macroecological-level by testing for variance stabilization in a broad range of animal population count data. This part of the project will provide a strong empirical link to theory and determine how the structure of dynamical systems plays a role in their robustness to extrinsic fluctuations. Intellectual Merit: Nearly all measurable biological processes are highly variable in time. This variation arises due to the open nature of biological systems and the difficulty in collecting data across organizational scales. Only a handful of studies have explored the properties of biological systems that are robust to changes in extrinsic noise-levels despite the necessity of all forms of life to handle variation in their environment. This project will be the first to link the dynamical properties of biological systems to their robustness to variation in the environment. While our project focuses mostly on ecological dynamics, these analyses will be relevant to any biological systems that exhibit highly nonlinear interactions among their components. Broader Impacts: One prediction of global environmental change is that the amount of variation in the climate is expected to change even faster than the average conditions. An important component of this work is supporting the development of a new generation of transdisciplinary scientists and thinkers. We will be funding several local undergraduate researchers, giving them a unique opportunity to integrate their training in biology, mathematics, and programming through the development of a software tool to access a novel database of population time series in the R software analysis. We will also work to develop freely available educational material that explores the fundamental differences of stochastic and deterministic model and emphasizes the importance of considering stochastic fluctuations in wildlife conservation and management. The postdocs on this project will also teach several free workshops to graduate students, postdocs, and professionals, providing critical support for interdisciplinary training in an EPSCoR (Hawai`i) state that requires developing diverse economic opportunities more than ever. Furthermore, all knowledge developed in this project will be disseminated via open-source code and publications, and we will discuss our results at national and international conferences. 2052413