2015/10/24 by Jean‐François Arnoldi, Michel Loreau, Arnoldi, Jean-François +3 · 2 citations
Environmental Science · #92B05 #Biological Physics (physics.bio-ph) #Ecology and Vegetation Dynamics Studies #Ecosystem dynamics and resilience #FOS: Biological sciences #FOS: Physical sciences #Populations and Evolution (q-bio.PE) #Sustainability and Ecological Systems Analysis
paper · pdf · doi:10.48550/arxiv.1510.07120
openalex publication_date 2015/10/24 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
In theoretical studies, the most commonly used measure of ecological\nstability is resilience: ecosystems asymptotic rate of return to equilibrium\nafter a pulse-perturbation -or shock. A complementary notion of growing\npopularity is reactivity: the strongest initial response to shocks. On the\nother hand, empirical stability is often quantified as the inverse of temporal\nvariability, directly estimated on data, and reflecting ecosystems response to\npersistent and erratic environmental disturbances. It is unclear whether and\nhow this empirical measure is related to resilience and reactivity. Here, we\nestablish a connection by introducing two variability-based stability measures\nbelonging to the theoretical realm of resilience and reactivity. We call them\nintrinsic, stochastic and deterministic invariability; respectively defined as\nthe inverse of the strongest stationary response to white-noise and to\nsingle-frequency perturbations. We prove that they predict ecosystems worst\nresponse to broad classes of disturbances, including realistic models of\nenvironmental fluctuations. We show that they are intermediate measures between\nresilience and reactivity and that, although defined with respect to persistent\nperturbations, they can be related to the whole transient regime following a\nshock, making them more integrative notions than reactivity and resilience. We\nargue that invariability measures constitute a stepping stone, and discuss the\nchallenges ahead to further unify theoretical and empirical approaches to\nstability.\n