Selective extinctions resulting from random habitat destruction lead to under-estimates of local and regional biodiversity loss in a manipulative field experiment.

Land-use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper, we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual-based, sample-based, and spatially clustered, to those derived from a commonly used extinction estimation method, the species-area relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within-mesocosm) and regional (treatment-wide) scales. Despite the stochastic nature of our small-scale, short-term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example, when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait-based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.

Low Abundance of Three Tick Species in the Piedmont of North Carolina.

Multiple species of ticks, including Ixodes scapularis (Say, Ixodida:Ixodidae), Amblyomma americanum (L., Ixodida:Ixodidae), and Dermacentor variabilis (Say, Ixodida:Ixodidae), occur in high and increasing abundance in both the northeast and southeast United States. North Carolina is at the nexus of spread of these species, with high occurrence and abundance of I. scapularis to the north and A. americanum to the south. Despite this, there are few records of these species in the Piedmont of North Carolina, including the greater Charlotte metropolitan area. Here, we update the known occurrence and abundance of these species in the North Carolina Piedmont. We surveyed for ticks using cloth drags, CO2 traps, and leaf litter samples at a total of 79 sites within five locations: Mecklenburg County, South Mountains State Park, Stone Mountain State Park, Duke Forest, and Morrow Mountain State Park, all in North Carolina, during the late spring, summer, and fall seasons of 2019. From these surveys, we had only 20 tick captures, illuminating the surprisingly low abundance of ticks in this region of North Carolina. Our results indicate the possibility of underlying habitat and host factors limiting tick distribution and abundance in the North Carolina Piedmont.