The value of local habitat heterogeneity and productivity when estimating avian species richness and species of concern

Abstract

As the quality and quantity of natural habitats decrease, pressure increases to better understand species-habitat interactions and how animal communities respond to habitat changes. We assessed the relative importance of local habitat heterogeneity and productivity measures as predictors of avian species richness and compared these results to models for species of conservation concern (SCC). We derived three-dimensional habitat heterogeneity and productivity measures from light detection and ranging data and hyperspectral imagery, and then used a Bayesian multi-species hierarchical framework to model avian species richness and occupancy. We found both habitat heterogeneity and productivity were important factors for determining avian community richness. Three-dimensional habitat heterogeneity and productivity metrics accurately predicted species richness at a local scale and were especially important to use within habitat guilds (i.e., alpha diversity). When scaling up to community richness across multiple habitat types (i.e., gamma diversity), two-dimensional (surface level) productivity and heterogeneity metrics became important additions to the three-dimensional metrics when estimating total avian richness. We also tested the utility of these metrics for predicting occupancy of SCC and compared community-level relationships to species-specific relationships. Species of conservation concern differed from the broader avian community with regard to local habitat heterogeneity and productivity measures. Species of conservation concern had different relationship habitat metrics than the greater avian community. Three-dimensional measures of habitat heterogeneity and productivity predicted avian richness across the landscape, yet also highlighted the different habitat structure needs of SCC compared with the greater avian community.

Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward

“…(N C /N TV ) • 100 Abbreviation: ALS, airborne laser scanning. vegetation structure differ between guilds (Cooper et al, 2020;Goetz et al, 2007;Jones et al, 2013;Peura et al, 2016;Vogeler et al, 2014;Weisberg et al, 2014). Recently, ALS-derived vegetation structure data proved useful for quantifying niche overlap/ separation (Koma, Grootes, et al, 2021).…”

Effects of local climate and habitat heterogeneity on breeding-bird assemblages of semi-natural grasslands

“…Shannon habitat diversity based on habitat types is a rather coarse proxy for habitat heterogeneity, usually not reflecting the sometimes high three-dimensional structural diversity within a certain habitat type (cf. Cooper et al 2020). Nevertheless, we detected a positive effect of Shannon habitat diversity on both overall species richness and density of breeding birds in plots of calcareous grasslands.…”

Harmonizing spatial scales and ecological theories to predict avian richness and functional diversity within forest ecosystems

“…Three-dimensional structural vegetation heterogeneity also creates varied microclimates that allow species to persist in otherwise inhospitable environments (Huey et al, 2012), which will be increasingly important as climate continues to change. Habitat heterogeneity does predict avian richness at a local scale based on three-dimensional structure (Cooper et al, 2020a) and can scale up to a national level using satellite-based metrics (Huang et al, 2014;Farwell et al, 2020). However, little is known about the degree of similarity in habitat heterogeneity within or between biomes.…”