Year: 2026
Type: article
Abstract: From invasive predators displacing wildlife to medically deployed bacteriophages eliminating pathogens, biological invasions by exploiters are a fundamental driver of extinction, with implications for both conservation and medicine. Resident victim populations facing such invasions can sometimes avoid extinction through adaptation, a process known as evolutionary rescue. Here, an analytical approximation is derived for the probability of evolutionary rescue from invading exploiters, focusing on how rescue depends on a key exploiter trait-victim specificity. Rescue is shown to be most likely either when invaders are slow-spreading, resident-dependent specialists whose failure to encounter suitable victims buys time for mutation, or when invaders are fast-spreading generalists that rapidly relieve standing genetic variation of intraspecific competition. For both the generalist and specialist cases, increased resident growth rates are shown to often promote rescue by boosting mutational input and mutant fitness. However, a key exception to this pattern-and the central result of the study-is that a lower resident birth rate can sometimes facilitate rescue relative to a higher one by indirectly diminishing the effect of demographic stochasticity on mutant establishment. Through this weakening of stochasticity, a lower density-independent birth rate primarily promotes rescue from generalists, whereas a competition-induced lower birth rate can also appreciably aid rescue from specialists. Overall, the results suggest that victim specificity can reshape evolutionary rescue by dynamically coupling the rate of resident decline to the growth rate of the stressor driving the decline, potentially altering how resident life history affects rescue.
Source: Journal of Evolutionary Biology
DOI: 10.1093/jeb/voag081
Author: Alexander Longcamp
Institution: Mississippi State University
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Life on land
Open Access status: hybrid
Estimated APC paid: $3,123
OpenAlex ID: W7204246391
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