Mon, Aug 15, 2022: 2:45 PM-3:00 PM
513F
Background/Question/MethodsUnderstanding the drivers of species turnover along latitudinal gradients remains a major goal in community ecology. The species-sorting hypothesis (SSH) proposes that species diversity is mediated from a metacommunity to local communities by abiotic environmental gradients; harsh habitats act as strong “filters” preventing species from becoming established, thus lowering local diversity, while benign environments allow species to immigrate to local communities more readily, increasing local diversity. In these latter cases, slower-acting biotic interactions, such as competition, may play a larger role in regulating species diversity over long time periods. If the SSH is true, species at high latitudes will experience restricted immigration from a metacommunity resulting in local communities that are best modeled by low immigration rates. Conversely, species at low latitudes will face less restriction when immigrating from a metacommunity, resulting in local communities that are best modeled by relatively high immigration rates. To test for these latitudinal “filtering” effects we used Breeding Bird Survey data to simulate local community diversity under a range of immigration parameters. We then used Approximate Bayesian Computation to determine the immigration parameters that best modeled observed rates of diversity and explored the relationship between latitude and best-fit immigration parameters using regression analysis.
Results/ConclusionsPreliminary simulations from Eastern North America show that most communities, regardless of latitude, are most accurately modeled using relatively low rates of immigration. Surprisingly, we also found that communities at high latitudes were better modeled using marginally higher rates of immigration, a result that directly contradicts the SSH. The positive relationship between immigration and latitude was significant, though contributed very little to model variance in regression analysis. These results suggest that species undergo intense immigration filtering from a metacommunity at all latitudes, and that low-latitude species may in fact face increased intensity of filtering relative to their high-latitude counterparts. As such, models that assume neutral metacommunity dynamics or those that assume low levels of species filtering at low latitudes may underestimate the importance of dispersal barriers in these locations. We intend to investigate these same patterns in Central and Western North America, and to investigate whether variation in rates of immigration is best explained by latitude alone or with abiotic covariates such as temperature or rainfall. The results of this study contribute to our understanding of the degree to which environmental filtering may drive species community turnover at large spatial scales.
Results/ConclusionsPreliminary simulations from Eastern North America show that most communities, regardless of latitude, are most accurately modeled using relatively low rates of immigration. Surprisingly, we also found that communities at high latitudes were better modeled using marginally higher rates of immigration, a result that directly contradicts the SSH. The positive relationship between immigration and latitude was significant, though contributed very little to model variance in regression analysis. These results suggest that species undergo intense immigration filtering from a metacommunity at all latitudes, and that low-latitude species may in fact face increased intensity of filtering relative to their high-latitude counterparts. As such, models that assume neutral metacommunity dynamics or those that assume low levels of species filtering at low latitudes may underestimate the importance of dispersal barriers in these locations. We intend to investigate these same patterns in Central and Western North America, and to investigate whether variation in rates of immigration is best explained by latitude alone or with abiotic covariates such as temperature or rainfall. The results of this study contribute to our understanding of the degree to which environmental filtering may drive species community turnover at large spatial scales.