Slopes of Avian Species-Area Relationships, Human Population Density, and Environmental Factors

There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species–area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species–area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km × 10 km) and regional (290 km × 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.

Stand and within-stand factors influencing Golden-winged Warbler use of regenerating stands in the central Appalachian Mountains

The Golden-winged Warbler (Vermivora chrysoptera) is currently being considered for protected status under the U.S. Endangered Species Act. The creation of breeding habitat in the Appalachian Mountains is considered a conservation priority for this songbird, which is dependent on extensively forested landscapes with adequate availability of young forest. We modeled abundance of Golden-winged Warbler males in regenerating harvested forest stands that were 0-17 years postharvest at both mid-Appalachian and northeast Pennsylvania regional scales using stand and within-stand characteristics of 222 regenerating stands, 2010-2011. Variables that were most influential at the mid-Appalachian scale were different than those in the northeast region. Across the mid-Appalachian ecoregion, the proportion of young forest cover, i.e., shrub/scrub cover, within 1 km of regenerating stands best explained abundance of Golden-winged Warblers. Golden-winged Warbler response was best explained by a concave quadratic relationship in which abundance was highest with 5-15% land in young forest cover. We also found evidence that the amount of herbaceous cover, i.e., the amount of grasses and forbs, within a regenerating stand positively influenced abundance of Golden-winged Warblers. In northeastern Pennsylvania, where young forest cover is found in high proportions, the distance to the nearest regenerating stand best explained variation in abundance of Golden-winged Warblers. Abundance of Golden-winged Warblers was <1 male per survey when another regenerating stand was >1500 m away. When modeling within-stand features in the northeast region, many of the models were closely ranked, indicating that multiple variables likely explained Golden-winged Warbler response to within-stand conditions. Based on our findings, we have proposed several management guidelines for land managers interested in creating breeding habitat for Golden-winged Warblers using commercial timber operations. For example, we recommend when managing for Golden-winged Warblers in the central Appalachian Mountains that managers should strive for 15% young forest in a heavily forested landscape (>70% forest cover) and cluster stands within 1-2 km of other young forest habitats.