Radiotelemetry is the standard method for monitoring wild turkey (Meleagris gallapavo) movements and habitat use. Spatial data collected using telemetry‐based monitoring are frequently inaccurate due to triangulation error. However, new technology, such as Global Positioning Systems (GPS) has increased ecologists' ability to accurately evaluate animal movements and habitat selection. We evaluated the efficacy of micro‐GPS backpack units for use on wild turkeys. We tested a micro‐GPS developed specifically for avian species that incorporated a GPS antenna with a lightweight rechargeable battery and a very high frequency (VHF) transmitter. We conducted a series of static tests to evaluate performance in varying types of vegetative canopy cover and terrain. After static testing, we deployed micro‐GPS on 8 adult male Rio Grande wild turkeys (M. g. intermedia) trapped in south Texas and 2 adult females trapped in the Texas panhandle. Micro‐GPS units collected 26,439 locations out of 26,506 scheduled attempts (99.7% fix rate) during static testing. Mean distance error across all static tests was 15.5 m (SE = 0.1). In summer 2009, we recovered micro‐GPS from 4 tagged males and both females to evaluate data collection. Units on males acquired approximately 2,500 locations over a 65‐day test period (94.5% fix rate). We recovered units from the 2 females after 19 days and 53 days; those units acquired 301 and 837 locations, respectively, for a 96% fix rate. Cost analysis indicated that VHF will be cost effective when 1 location per day is required up to 181 days, but micro‐GPS becomes less expensive as frequency of daily locations increases. Our results indicate that micro‐GPS have the potential to provide increased reliable data on turkey movement ecology and habitat selection at a higher resolution than conventional VHF telemetric methods. © 2011 The Wildlife Society.

. Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning. Ecosphere 4(3):42. http://dx.doi.org/10.1890/ES12-000352.1Abstract. Advances in remotely sensed data for characterizing habitat have enabled development of spatially explicit predictive species distribution models (SDM) that can be essential tools for management. SDMs commonly use coarse-grain metrics, such as forest patch size or patch connectivity, over broad spatial extents. However, species distributions are likely driven in part by local, fine-grained habitat conditions. Conservation and management are often planned and applied locally, where coarse predictions may be uninformative or not sufficiently precise. We investigated the integration of high-resolution LiDAR (Light Detection and Ranging) with avian point sampling data to develop a detection-corrected occupancy model to quantify habitat-occurrence relationships for two species with different habitats: the endangered golden-cheeked warbler (Setophaga chrysoparia) and black-capped vireo (Vireo atricapilla) on a military installation in central Texas. We compared occupancy models that used only the more conventional, coarse remotely sensed metrics to models that also incorporated high-resolution LiDAR-derived metrics for vegetation height and canopy cover, to assess their use for predicting distributions. Models including LiDAR-derived vegetation height and canopy cover metrics were competitive for both species, and models without LiDAR-derived vegetation height had substantially lower model weights and explanatory strength. Area under curve estimates for the highest ranked models were high for warblers (0.864) and moderate for vireos (0.746). Using the best supported models for each species, we predicted the occurrence distribution for both species. The resulting predictions provide a decision support tool that enables assessment of the status, impacts, and mitigation of impacts to endangered species habitat on the installation due to land management and military training activities that is more standardized and accurate than current assessment approaches based on visual gestalt of habitat and expert opinion. Additionally, although previous species distribution models have been created for our focal species, most fail to match the grain and extent of most management actions or include local, fine-grained metrics that influence distributions. In contrast, we demonstrate that use of LiDAR with species occurrence data can provide precision and resolution at a scale that is relevant ecologically and to the operational scale of most conservation and management actions.

Rio Grande wild turkey (Meleagris gallopavo intermedia) nests suffer high predation rates exceeding 65%, which may limit recruitment. We evaluated post‐nesting movements of reproductively active female Rio Grande wild turkeys. We monitored 194 nesting attempts between 2005 and 2010 and documented 17% and 32% overall apparent nest success for the Edwards Plateau and Central Rio Grande Plains study regions, respectively. Rio Grande wild turkey hens move approximately 1.2 km (SD = 0.7) between nesting attempts within a nesting season and approximately 1.4 km (SD = 1.6) between initial nesting attempts among years. Rio Grande wild turkey hens selected open areas with moderate woody cover for nesting (${\bar {x}}$ = 37.7%; range = 3.0–88.2%). Patchiness of vegetation in the nesting landscape also was borne out by typically low edge‐to‐area ratios (${\bar {x}}$ = 0.20; range = 0.040–0.732). We found no clear pattern in movement distance and either landscape composition or edge‐to‐area ratio for within or between breeding season nest site selection for either the Edwards Plateau or Central Rio Grande Plains study region. Based on our results, movement distances post‐nest failure do not seem to influence habitat selection. © 2012 The Wildlife Society.

No abstract

Conserving habitat is increasingly challenging as human populations grow. Remote-sensing technology has provided a means to delineate species' habitat on large spatial scales. However, by combining habitat delineations with predictions of species' occurrence, habitat models can provide additional utility applications for conservation by allowing us to forecast how changing environmental and landscape conditions affect species' occurrence and distribution. We demonstrate how a spatially explicit habitat occupancy model for the golden-cheeked warbler (Setophaga chrysoparia) can be used as an impact assessment and conservation planning tool. We used predictions of patch-level occupancy rates and created several scenarios that simulated the removal or protection of warbler habitats. Resulting changes to habitat structure and availability were used to assess the resulting impacts of removal or protection on the occurrence probability for remaining habitat patches. By recalculating occupancy based on changes to habitat, our approach provides the ability to assess and compare impacts of location and orientation of development so that the least harmful option relative to predicted occurrence can be chosen. Potential applications of our modeling approach are many because our methods provide a useful tool for identifying potential impacts and assisting with mitigation efforts focused on the conservation and management of a species. ß 2012 The Wildlife Society.