info:eu-repo/semantics/article
Seeing through the static: the temporal dimension of plant–animal mutualistic interactions
Fecha
2021-01Registro en:
CaraDonna, Paul J.; Burkle, Laura A.; Schwarz, Benjamin; Resasco, Julian; Knight, Tiffany M.; et al.; Seeing through the static: the temporal dimension of plant–animal mutualistic interactions; Wiley Blackwell Publishing, Inc; Ecology Letters; 24; 1; 1-2021; 149-161
1461-023X
CONICET Digital
CONICET
Autor
CaraDonna, Paul J.
Burkle, Laura A.
Schwarz, Benjamin
Resasco, Julian
Knight, Tiffany M.
Benadi, Gita
Blüthgen, Nico
Dormann, Carsten F.
Fang, Qiang
Fründ, Jochen
Gauzens, Benoit
Kaiser Bunbury, Christopher N.
Winfree, Rachael
Vazquez, Diego P.
Resumen
Most studies of plant–animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human-driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant–animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.