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Tracking unstable states: ecosystem dynamics in a changing world
Author(s) -
Arumugam Ramesh,
Lutscher Frithjof,
Guichard Frédéric
Publication year - 2021
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/oik.08051
Subject(s) - metacommunity , regime shift , alternative stable state , biological dispersal , environmental change , ecosystem , ecology , psychological resilience , climate change , environmental science , biology , population , psychology , demography , sociology , psychotherapist
Ecological systems can show complex and sometimes abrupt responses to environmental change, with important implications for their resilience. Theories of alternate stable states have been used to predict regime shifts of ecosystems as equilibrium responses to sufficiently slow environmental change. The actual rate of environmental change is a key factor affecting the response, yet we are still lacking a non‐equilibrium theory that explicitly considers the influence of this rate of environmental change. We present a metacommunity model of predator–prey interactions displaying multiple stable states, and we impose an explicit rate of environmental change in habitat quality (carrying capacity) and connectivity (dispersal rate). We study how regime shifts depend on the rate of environmental change and compare the outcome with a stability analysis in the corresponding constant environment. Our results reveal that in a changing environment, the community can track states that are unstable in the constant environment. This tracking can lead to regime shifts, including local extinctions, that are not predicted by alternative stable state theory. In our metacommunity, tracking unstable states also controls the maintenance of spatial heterogeneity and spatial synchrony. Tracking unstable states can also lead to regime shifts that may be reversible or irreversible. Our study extends current regime shift theories to integrate rate‐dependent responses to environmental change. It reveals the key role of unstable states for predicting transient dynamics and long‐term resilience of ecological systems to climate change.