Utilizing gradient simulations for quantifying community‐level resistance and resilience

Abstract

AbstractResilience is a complex, multidimensional property of ecosystems that describes how ecosystems respond to disturbance and likely results from the interactions of species and their environments across temporal and spatial scales. Due to the complexity in how ecosystems function and respond to disturbance, measuring resilience is a challenge. Gradient analysis provides a familiar, yet somewhat neglected framework for understanding and characterizing resilience. With simulations parameterized on existing biomonitoring data, we used distance‐based measures in ordination space to characterize community‐level resilience, here defined as a function of resistance and recovery. Our simulations and analyses involved five steps: (1) We generated regional species pools by simulating species distributions across environmental gradients; (2) we sampled from these regional species pools to emulate temporal changes in reference (i.e., minimally disturbed) and impacted communities responding to disturbance; (3) we performed ordinations on observations from both impacted and reference communities to summarize multivariate data; (4) we calculated distance‐based measures for individual community trajectories in the ordinations to quantify their relative resistance and resilience; and (5) we compared these distance‐based metrics between reference and impacted communities. We conclude with an empirical example demonstrating the lack of resistance of the Harp Lake (Ontario, Canada) zooplankton community to invasion relative to the changes observed among minimally disturbed reference communities. Overall, distance measures on ordinations provide a simple and effective visual framework to quantify the relative resistance and resilience of communities to disturbance, and our simulation approach provides a novel technique to develop and evaluate quantitative metrics related to ecosystem or community‐level processes.