Empirical pattern of plant-pollinator spatial networks

SABATINO MALENA; GILARRANZ, LUIS J.; AIZEN MARCELO

Kastenienbaum

Workshop; Workshop on Biodiversity Dynamics in Coevolutionary Meta-ecosystems (COMETA); 2018

Eawag

Understanding how the coevolutionary process alters ecosystem dynamics and functioning across landscapes is becoming increasingly important as climate and land-use change, and the spread of invasive species are changing ecosystems worldwide. In this vein, developing how the coevolutionary process alters ecosystem dynamics and functioning across heterogeneous landscapes is becoming increasingly important. In this vein, developing theoretical models that integrate empirical data is critical to improve our predictions on the spatio-temporal dynamics of diverse ecological communities and thus on ecosystems functioning. Such integration might facilitate the exploration of patterns of coexistence among species, their role in ecosystem functioning, and the risk of collapse of coevolved ecosystems across different spatial and temporal scales. This exploration is of critical importance for several reasons. First, the extinction of species caused by human-generated disturbances occurs at an unprecedented rate, and yet most models predicting extinction rates often assume that species evolve independently of one another. Although eco-evolutionary approaches of species interactions are increasingly common, studies connecting coevolution of interaction networks at small scales to investigate the large-scale association between biodiversity function and meta-ecosystem dynamics are at an incipient stage. Finally, many experiments and empirical studies have shown convergence of time scales between ecological and evolutionary processes, but there is still a gap in understanding how ecological and coevolutionary dynamics shape ecological interactions in a spatial and temporal context, the meta-ecosystem.The project COMETA will develop approaches to join coevolutionary dynamics, meta-ecosystems and interaction networks, by synthesizing spatial and trait-interaction data in species-rich meta-ecosystems. We aim to contribute to the understanding of coevolution and ecosystem function in species- and interaction-rich networks at different spatial scales. Our main challenge will be to integrate models across an increasing level of complexity. We will focus on implementing analytic tools and testing them with empirical patterns from datasets containing many species and their interactions, sites and traits.