Functional traits and metacommunity theory reveal that habitat filtering and competition maintain bird diversity in a human shared landscape
Cite this dataset
Eyster, Harold N.; Srivastava, Diane; Kreitzman, Maayan; Chan, Kai (2022). Functional traits and metacommunity theory reveal that habitat filtering and competition maintain bird diversity in a human shared landscape [Dataset]. Dryad. https://doi.org/10.5061/dryad.34tmpg4nt
Human shared landscapes cover much of Earth, yet their conservation value is contested. This controversy may persist because previous studies have examined species diversity, rather than the processes through which such diversity is maintained. For example, a site exhibiting high diversity may not actually bolster populations if the diversity is only maintained through net immigration. Recent research has begun to isolate the processes that maintain metacommunities and develop functional trait methods to identify these processes. However, the processes underlying bird communities remain obscure. Here, we leverage metacommunity theory, functional trait partitioning, and a Bayesian multispecies abundance model to assess whether a shared landscape – woody perennial polyculture farms – bolsters bird diversity. Such farms grow multiple species of food-producing woody perennials together with vegetative groundcover. We surveyed birds and their in situ functional traits across the US Midwest in traditional agriculture, woody perennial polyculture, prairie, and woods. We found that woody perennial polycultures exhibited the highest bird diversity and were the most preferred by many species (including threatened ones). Moreover, our functional trait analysis suggests that this diversity is maintained through habitat filtering and competition, rather than merely immigration. Thus, shared landscapes can likely conserve birds by providing a distinct habitat. These results suggest that woody perennial polyculture farms offer substantial potential to support bird populations in the US Midwest. Our study demonstrates the utility of in situ functional trait partitioning within a Bayesian framework to unmask ecological processes and help assess the conservation value of landscapes.
This data was collected in the US Midwest in summer 2018, and processed using R and Stan.
R, Stan, text editor.
Ekhagastiftelsen, Award: 2017-52
University of British Columbia, Award: University Doctoral Fellowship
Natural Sciences and Engineering Research Council of Canada, Award: Discovery Grant RGPIN-2020-05032