Landscape Resilience Model for Evaluating Ecosystem Recovery Capacity After Habitat Disturbances

Abstract

Wildfire, drought, land conversion, and extreme climatic events are increasing in occurrence and scale to disturb habitat processes that support populations of wild animals, and are often creating landscapes that are fragmented such that species recolonization or population recovery is patchy in both space and time. Current methods of measuring post-disturbance recovery have been primarily                           single-indicator-based, measuring vegetation greenness or patch size, and provide little information on the restoration of wildlife populations, trophic interactions, and dispersal pathways. This paper proposes a Landscape Resilience Model that would assess the capacity of the ecosystem to recover after an animal-induced habitat disturbance, incorporating the recovery of the habitat structure, the recolonization pattern of species, the population demographic rebound, and the restoration of functional connectivity between habitat patches into one single comparable Resilience Value. The model focuses on recovery as a multi-stage, cyclical process not just a return to a previous baseline, based on concepts of adaptive cycle thinking and landscape connectivity science. The model has not yet been tested empirically across a variety of biomes, but the indicators used provide a coherent framework for comparing recovery processes among disturbed sites, prioritizing conservation activities, and identifying landscapes where recovery is threatened. Validation by field, across taxa and disturbance types, is recommended as a direction for future research.