Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives

Two types of ecological thresholds are now being widely used to develop conservation targets: breakpoint-based thresholds represent tipping points where system properties change dramatically, whereas classification thresholds identify groups of data points with contrasting properties. Both breakpoint-based and classification thresholds are useful tools in evidence-based conservation. However, it is critical that the type of threshold to be estimated corresponds with the question of interest and that appropriate statistical procedures are used to determine its location. On the basis of their statistical properties, we recommend using piecewise regression methods to identify breakpoint-based thresholds and discriminant analysis or classification and regression trees to identify classification thresholds.

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.