IBS   24490
INSTITUTO DE BIOLOGIA SUBTROPICAL
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Complex dynamics of tree cavities and nest webs in the Americas
Autor/es:
NORRIS, ANDREA R; WIEBE, KAREN L.; MARTIN, KATHY; IBARRA, JOSÉ TOMÁS; ALTAMIRANO, TOMÁS; COCKLE, KRISTINA L; TRZCINSKI, M. KURTIS; EDWORTHY, AMANDA B.
Lugar:
Vancouver
Reunión:
Congreso; International Ornithological Congress; 2018
Resumen:
The Nest Web concept represents tree-cavity-nesting communities as hierarchical, commensal networks, whereby nesting cavities flow upward from trees to cavity producers (e.g., woodpeckers, decay organisms) to a diverse assemblage of non-excavators (e.g., parrots, songbirds). These nest webs are dynamic, complex, and often resilient. They include non-hierarchical feedback loops, such as facultative excavation, inter-guild predation and competition. For >20 years we studied >4000 nesting cavities in temperate British Columbia, Canada (1995-2016), temperate Chile (2010-2018) and subtropical Argentina (2006-2018), to examine the dynamics of cavity-nesting communities over time, at scales from individual cavities to whole nest webs. Individual cavities in large old-growth trees persisted longest. Cavities became larger as they aged, and were occupied by a succession of vertebrates (excavators, then small-bodied non-excavators, and finally large-bodied non-excavators). Cavities produced 0?43 fledglings/cavity over their lifetime, but cavities with higher nest success were occupied fewer times by fewer species. At the nest web scale in Canada, an abundant facultative excavator declined in importance in the Nest Web during an insect outbreak that attracted obligate excavators, but then dramatically increased cavity production following wildfires. Logging resulted in disproportional biodiversity losses when it targeted key network hubs (large trees; Chile, Argentina) but not when a critical nesting tree species was retained (Canada). A nest web approach helped us understand interspecific interactions and test network theory; because these networks are strongly influenced by outside sources of uncertainty and non-linearity, a Complex Systems Science approach may improve predictions about their long-term dynamics.