Metacommunity ecology considers both the local- and regional-scale factors that influence community assembly. Previous work has identified dispersal, niche differentiation, and habitat heterogeneity as crucial parameters that determine metacommunity dynamics and stability in response to disturbance. However, it remains unclear whether the parameter combinations that are predicted to confer stability do so over long time scales and across ecosystem types. The ecosystems in the NSF Long-Term Ecological Research (LTER) network vary in habitat heterogeneity; likewise, the species assemblages within them exhibit varying degrees of niche differentiation and dispersal ability. Using LTER datasets, the investigators aim to synthesize the general relationships between metacommunity parameters and stability across a diverse range of ecosystems and over long temporal scales. To do so, they will characterize metacommunity stability across a disturbance gradient, estimate metacommunity parameters, assess how well estimated parameters predict stability over time, and parameterize metacommunity simulation models with LTER data to identify the major predictors of metacommunity stability. Final products from this working group include an R package containing metacommunity time series datasets and relevant analyses, a synthesis of metacommunity stability and sensitivity to disturbance across the LTER network, and a prospectus detailing the application of simulations for understanding metacommunity dynamics.
Don’t stick your hand in there – a story about caution and observation on the reefs of Moorea.
2023 Year in Review: a year of self reflection and investment in our future
Meandering Through the Mangrove Forests of the Florida Coastal Everglades
Burning Down the House Party
At the helm of ChANGE: driving forward a new experiment
Burned forest, bleached reef: LTER sites adapt to learn from disturbance
Tiny But Mighty: How Flies Shape Agroecosystems
Sea urchins mothers can help their offspring withstand marine heatwaves
LTER at AGU, 2023