Replacement of habitat specialist by generalist species in fragmented landscapes: a multi-taxa evaluation of alternative causal hypothesis

• Grant number: 20/04354-5
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: July 01, 2021
• End date: January 24, 2023
• Field of knowledge: Biological Sciences - Ecology - Applied Ecology
• Principal Investigator: Renata Pardini
• Grantee: Marina Zanin Gregorini
• Host Institution: Instituto de Biociências (IB). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Anthropogenic environmental disturbances have led to what has been termed biotic homogenization, a global pattern arising from the replacement of specialist and endemic species by generalist and widespread species. Despite the strong empirical evidence supporting it from around the world, species replacement may be caused by multiple ecological processes; yet, there are few formal tests of alternative causal hypotheses to explain this pattern. We will investigate the processes underlying species replacement in landscapes affected by habitat loss and fragmentation - the major threat to global biodiversity. To do so, we will focus on multiple taxa from the Atlantic Forest, a hyperdiverse and globally threatened biome, appropriate as a study model given the abundance of available biological data. Using a high-quality dataset encompassing 2.507 sampling locations and 13 taxa sampled in the field, we will investigate three alternatives hypotheses to explain species replacement: environmental filtering - species replacement results directly and exclusively from the environmental changes associated with habitat loss and fragmentation; competitor release - habitat loss and fragmentation lead directly to the decline of specialists, reducing the competitive suppression and indirectly "realising" the ecological space for generalists; generalist invasion - habitat loss and fragmentation lead directly to the increase of generalists, and indirectly, via competition, to the decline of specialists. We will test the fit of the data to structural equation models - a technique that allows the evaluation of direct and indirect causal effects - representing the three alternative hypothesis. (AU)