Mitigation of Habitat "Take": Application to Habitat Conservation Planning

One of the most important provisions of the U.S. Endangered Species Act precludes the "taking" of listed species on both public and private land. In past Endangered Species Act litigation, take has been broadly interpreted to include the destruction or modification of habitats as well as the direct killing of animals. This requirement created an extensive burden on private landowners to provide habitats for listed species. This burden was substantially lessened when the ESA was modified in 1982 to allow incidental takings conditioned on preparation of a satisfactory "habitat conservation plan." Because the majority of listed species are imperiled due to habitat modification, most habitat conservation plans must demonstrate defensible methods to mitigate against incidental habitat loss. A review of HCPs for the Northern Spotted Owl ( Strix occidentalis), and other species, indicates that mitigation solutions are often arbitrary, lacking an empirical foundation in the species' life history requirements. Based on data from the Spotted Owl, we illustrate a biologically based method for estimating the areal requirements necessary to mitigate against the take of essential habitats. Toward this goal we adopt the concept of "core area," that portion of an animal's home range that receives disproportionate use. We estimated core areas by means of the adaptive kernel density function and tested against a null distribution of animal use that assumes a bivariate, uniform distribution of locations within the home range. The method we illustrate, which is defensible, repeatable, and empirical, is a clear improvement over the ad hoc methods used in many habitat conservation plans. Further, the methods we propose should be applicable to a large number of terrestrial species for which home range is a meaningful concept.     

Predicting abundance of desert riparian birds: validation and calibration of the Effective Area Model.

Reliable prediction of the effects of landscape change on species abundance is critical to land managers who must make frequent, rapid decisions with long-term consequences. However, due to inherent temporal and spatial variability in ecological systems, previous attempts to predict species abundance in novel locations and/or time frames have been largely unsuccessful. The Effective Area Model (EAM) uses change in habitat composition and geometry coupled with response of animals to habitat edges to predict change in species abundance at a landscape scale. Our research goals were to validate EAM abundance predictions in new locations and to develop a calibration framework that enables absolute abundance predictions in novel regions or time frames. For model validation, we compared the EAM to a null model excluding edge effects in terms of accurate prediction of species abundance. The EAM outperformed the null model for 83.3% of species (N=12) for which it was possible to discern a difference when considering 50 validation sites. Likewise, the EAM outperformed the null model when considering subsets of validation sites categorized on the basis of four variables (isolation, presence of water, region, and focal habitat). Additionally, we explored a framework for producing calibrated models to decrease prediction error given inherent temporal and spatial variability in abundance. We calibrated the EAM to new locations using linear regression between observed and predicted abundance with and without additional habitat covariates. We found that model adjustments for unexplained variability in time and space, as well as variability that can be explained by incorporating additional covariates, improved EAM predictions. Calibrated EAM abundance estimates with additional site-level variables explained a significant amount of variability (P < 0.05) in observed abundance for 17 of 20 species, with R2 values >25% for 12 species, >48% for six species, and >60% for four species when considering all predictive models. The calibration framework described in this paper can be used to predict absolute abundance in sites different from those in which data were collected if the target population of sites to which one would like to statistically infer is sampled in a probabilistic way.     

Conserving tigers in working landscapes

Tiger (Panthera tigris) conservation efforts in Asia are focused on protected areas embedded in human‐dominated landscapes. A system of protected areas is an effective conservation strategy for many endangered species if the network is large enough to support stable metapopulations. The long‐term conservation of tigers requires that the species be able to meet some of its life‐history needs beyond the boundaries of small protected areas and within the working landscape, including multiple‐use forests with logging and high human use. However, understanding of factors that promote or limit the occurrence of tigers in working landscapes is incomplete. We assessed the relative influence of protection status, prey occurrence, extent of grasslands, intensity of human use, and patch connectivity on tiger occurrence in the 5400 km² Central Terai Landscape of India, adjacent to Nepal. Two observer teams independently surveyed 1009 km of forest trails and water courses distributed across 60 166‐km² cells. In each cell, the teams recorded detection of tiger signs along evenly spaced trail segments. We used occupancy models that permitted multiscale analysis of spatially correlated data to estimate cell‐scale occupancy and segment‐scale habitat use by tigers as a function of management and environmental covariates. Prey availability and habitat quality, rather than protected‐area designation, influenced tiger occupancy. Tiger occupancy was low in some protected areas in India that were connected to extensive areas of tiger habitat in Nepal, which brings into question the efficacy of current protection and management strategies in both India and Nepal. At a finer spatial scale, tiger habitat use was high in trail segments associated with abundant prey and large grasslands, but it declined as human and livestock use increased. We speculate that riparian grasslands may provide tigers with critical refugia from human activity in the daytime and thereby promote tiger occurrence in some multiple‐use forests. Restrictions on human‐use in high‐quality tiger habitat in multiple‐use forests may complement existing protected areas and collectively promote the persistence of tiger populations in working landscapes.     

Efficient species-level monitoring at the landscape scale

Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance.