Biology subjects

Munch, S. B.

Publications and source records attributed to Munch, S. B..

4 recordsLinked to original sources

bioRxiv2025

A nonequilibrium framework for community responses to pulse perturbations

Understanding responses of ecological communities to shocks that displace species abundances is of paramount importance given the increasing frequency of extreme climatic events. However, current theory on responses to such pulse perturbations focuses on equilibrium points and we lack a unified framework that accommodates other common, but more complicated, types of population fluctuations such as transients and cycles. Here we introduce this frame-work by deriving metrics that quantify the minimum, typical, and maximum amplification of perturbed abundances under nonequilibrium population dynamics. By simulating models under several nonequilibrium scenarios, we demonstrate that these metrics accurately characterize the full range of amplification of perturbed abundances in the short and long terms. Notably, we show that perturbation amplification depends strongly on community state in the short term, but this state dependency vanishes in the long term. Overall, our framework enables stability analysis for model and natural communities that do not exhibit equilibrium dynamics.

ecology↗

bioRxiv2024

Ecological synchrony in human-modified landscapes under a changing climate

Different aspects of ecological systems, biotic or abiotic, often fluctuate in coordinated patterns over space and time. Such high concordance between ecological processes is often referred to as ecological synchrony. Anthropogenic activities, including and beyond climate change, have the potential to alter ecological synchrony by disrupting or enhancing existing synchrony. Despite many local studies, we have a limited systematic understanding of how ecological synchrony is shaped by management in human-dominated landscapes at regional to continental scales. From a macrosystems perspective, we review how anthropogenic activities, particularly beyond climate change, alter ecological synchrony across levels of ecological organization, from the ecosystem level to the population level. For each level, we use a large-scale case study to demonstrate ways to quantify the impacts of human modifications on synchrony using big data from remote sensing, surveys, and observatory networks. For example, we detected possible homogenization of population dynamics of bird species in North America. These changes in ecological synchrony, although in different forms, often represent challenges to ecological and social systems. Collaborative research efforts that integrate emerging open data streams moving forward will be able to provide insights into the effects of different anthropogenic drivers and the consequences of changes in synchrony.

ecology↗

bioRxiv2024

Revealing unseen dynamical regimes of ecosystems from population time-series data

Many ecosystems can exist in alternative dynamical regimes for which small changes in an environmental driver can cause sudden jumps between regimes. However, predicting the dynamics of regimes that occur under unobserved levels of the environmental driver has remained an unsolved challenge in ecology with important implications for conservation and management. Here we show that integrating population time-series data and information on the putative driver into an empirical dynamic model allows us to predict new dynamical regimes without the need to specify a population dynamics model. As a proof of concept, we demonstrate that we can accurately predict fixed-point, cyclic, or chaotic dynamics under unseen driver levels for a range of simulated models. For a model with an abrupt population collapse, we show that our approach can anticipate the regime that follows the tipping point. We then apply our approach to data from an experimental microbial ecosystem and from a lake planktonic ecosystem. We find that we can reconstruct transitions away from chaos in the experimental ecosystem and anticipate the dynamics of the oligotrophic regime in the lake ecosystem. These results lay the groundwork for making rational decisions about preventing, or preparing for, regime shifts in natural ecosystems.

ecology↗

bioRxiv2024

Quantifying irreversibility of ecological systems

Irreversibility--the asymmetry of population dynamics when played forward versus backward in time--is a fundamental property of ecological dynamics. Despite its early recognition in ecology, irreversibility has remained a high-level and unquantifiable concept. Here, we introduce a quantitative framework rooted in non-equilibrium statistical physics to measure irreversibility in general ecological systems. Through theoretical analyses, we demonstrate that irreversibility quantifies the degree to which a system is out of equilibrium, a property not captured by traditional ecological metrics. We validate this prediction empirically across diverse ecological systems structured by different forces, such as rapid evolution, nutrient availability, and temperature. In sum, our study provides a rigorous formalism for quantifying irreversibility in ecological systems, with the potential to integrate dynamical, energetic, and informational perspectives in ecology.

ecology↗