Biodiversity metrics are frequently used to guide conservation planning because they can summarize biogeographical attributes of plant and animal communities quickly and at multiple scales. Attributes include habitat features of high conservation value, representativeness, and redundancy of biological communities. We conducted a rapid ecological assessment of resident avian species in the west-central mountainous region of Puerto Rico in 2015, a landscape dominated by coffee cultivation. We focused on this landscape because shade-grown and restored shade-grown coffee plantations offer an opportunity to complement protected habitat (e.g., reserves) to enhance species persistence. We used species richness, which tallies the number of unique species, and a quadratic entropy index of diversity, which incorporates interspecific taxonomic differentiation to evaluate species representativeness and redundancy across sun- and shade-grown coffee plantations and secondary forest. We surveyed 120 sites, calculating both metrics using species-specific occupancy probabilities estimated from community-level occupancy models. Species representativeness and redundancy were high as neither metric was able to discriminate among habitat types, possibly because plant communities were redundant, and the avian community was dominated by species adept at exploiting altered habitats. Similarly, we could not discriminate among avian communities modeling each biodiversity metric as a function of site-specific habitat covariates. Our findings and available knowledge on avian community demographics suggest that conservation strategies could couple protected habitat (e.g., reserves) and restored habitat (e.g., coffee plantations) to enhance species diversity and persistence across human-modified landscapes.
|Publication Subtype||Journal Article|
|Title||Using biodiversity metrics to guide conservation planning in altered tropical landscapes|
|Series title||Caribbean Naturalist|
|Publisher||Eagle Hill Publications|
|Contributing office(s)||Coop Res Unit Atlanta|
|Google Analytic Metrics||Metrics page|