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Camera surveys commonly are used by managers and hunters to estimate white-tailed deer Odocoileus virginianus density and demographic rates. Though studies have documented biases and inaccuracies in the camera survey methodology, camera traps remain popular due to ease of use, cost-effectiveness, and ability to survey large areas. Because recruitment is a key parameter in ungulate population dynamics, there is a growing need to test the effectiveness of camera surveys for assessing fawn recruitment. At Savannah River Site, South Carolina, we used six years of camera-based recruitment estimates (i.e. fawn:doe ratio) to predict concurrently collected annual radiotag-based survival estimates. The coefficient of determination (R2) was 0.445, indicating some support for the viability of cameras to reflect recruitment. We added two years of data from Fort Bragg Military Installation, North Carolina, which improved R2 to 0.621 without accounting for site-specific variability. Also, we evaluated the correlation between year-to-year changes in recruitment and survival using the Savannah River Site data; R2 was 0.758, suggesting that camera-based recruitment could be useful as an indicator of the trend in survival. Because so few researchers concurrently estimate survival and camera-based recruitment, examining this relationship at larger spatial scales while controlling for numerous confounding variables remains difficult. Future research should test the validity of our results from other areas with varying deer and camera densities, as site (e.g. presence of feral pigs Sus scrofa) and demographic (e.g. fawn age at time of camera survey) parameters may have a large influence on detectability. Until such biases are fully quantified, we urge researchers and managers to use caution when advocating the use of camera-based recruitment estimates.
Over the last decades, many wild goose populations have increased significantly and are now causing conflicts with socioeconomic and biological interests. To mitigate impacts of rapid population increases, population control by increasing harvest has been attempted. In this study we seek to guide the design of a regional autumn goose hunting organisation in agricultural landscapes by identifying areas suitable for hunting, which have high probability of occurrence of pink-footed geese Anser brachyrhynchus and/or a short return time by geese to fields subject to hunting. To identify areas suitable for hunting in Nord-Trøndelag County, mid-Norway, we used species distributions models (SDMs), a broadly accepted tool in conservation planning for spatial refuge organisation. The prediction was that the highest probability of goose occurrence exists for large fields, away from small roads and near water bodies serving as safe roosting sites. Additionally, return time was predicted to be shortest for large fields near roosting sites and away from big roads. A combined map of goose occurrence and return time showed similar prediction for high goose occurrence and short return time; hence areas most suitable for hunting are large fields, close to roost sites and away from roads. If hunters and landowners are willing to coordinate goose hunting at a landscape level, they can use the prediction maps as guidance, with the likely benefit that they collectively can shoot more geese. Such local and regional organisation can become a powerful tool in the harvest management of geese.
Anthropogenic changes to the landscape such as fertilization and mowing schemes have been correlated with goslings obtaining a higher weight gain during the first weeks of their life, which in turn increases breeding success and survival at the adult stage. As goose numbers rise, conflicts with farmers become stronger as the birds use agricultural sites for foraging. In this study, habitat choice for individually marked greylag geese from four different rearing conditions, categorized by their temporal application of fertilizer, was documented over a seventeen-year period. Weekly observations took place on a resident population of wild greylag geese within the Ooijpolder, the Netherlands. The region comprises of areas dedicated to nature restoration as well as agricultural use. In essence, we infer the habitat choice of greylag geese from the frequency of sightings of individually marked geese in different habitat patches, and model habitat choice as a function of rearing conditions, age, and seasonality. Despite a general preference for agricultural grassland, about 40% of the habitat choice was determined by the rearing condition of geese. Interestingly, geese reared in restored meadows, a less favorable rearing habitat, exhibited strong habitat fidelity and preferred to forage in meadows in the spring. Habitat choice was furthermore influenced by age of adult geese and seasonal changes in plant availability. We discuss management implications of our results on habitat choice in an agricultural landscape for increasing resident goose populations. An efficient management measure would be the limitation of goose access to improved grassland during rearing period in the spring.
The accuracy of global positioning system (GPS) locations obtained from study animals tagged with GPS monitoring devices has been a concern as to the degree it influences assessments of movement patterns, space use, and resource selection estimates. Many methods have been proposed for screening data to retain the most accurate positions for analysis, based on dilution of precision (DOP) measures, and whether the position is a two dimensional or three dimensional fix. Here we further explore the utility of these measures, by testing a Telonics GEN3 GPS collar's positional accuracy across a wide range of environmental conditions. We found the relationship between location error and fix dimension and DOP metrics extremely weak (r2adj ∼ 0.01) in our study area. Environmental factors such as topographic exposure, canopy cover, and vegetation height explained more of the variance (r2adj = 15.08%). Our field testing covered sites where sky-view was so limited it affected GPS performance to the degree fix attempts failed frequently (fix success rates ranged 0.00–100.00% over 67 sites). Screening data using PDOP did not effectively reduce the location error in the remaining dataset. Removing two dimensional fixes reduced the mean location error by 10.95 meters, but also resulted in a 54.50% data reduction. Therefore screening data under the range of conditions sampled here would reduce information on animal movement with minor improvements in accuracy and potentially introduce bias towards more open terrain and vegetation.
The elusive Caspian red deer Cervus elaphus maral lives at low densities in rugged forest habitats of the Caucasus and the south Caspian region, and its declining population requires urgent attention. We here address the precision and reliability of dung counts (fecal standing crop approach FSC) and camera trapping (random encounter model REM) for estimating its population size. We surveyed 36 km of strip transects arranged in systematic random design and applied 1585 camera trap nights of effort in the mountainous forest habitats of Golestan National Park, Iran. We also conducted a dung decay analysis of 80 samples. Dung decay rates were not habitat-specific and the mean time to decay was 141.8 ± 15.1 days, i.e. only ca 52% of the most reliable estimate available for red deer dung. Estimated deer population size and density from dung counts was lower (194 ±46 individuals, 0.46 ±0.11 individuals km-2, 2012–2013) than from REM (257 ±84 individuals, 0.61 ± 0.20 individuals km-2, 2011), but this difference was insignificant. Both these estimates confirm a sharp decline of the population from an estimated 2096 animals in the 1970s. Density estimates reached a stable level and were most precise at a sampling effort of 15 transects (FSC) and 1345 camera trap-days (REM). Our results confirm that FSC and REM can both be reliable for assessing populations of Cervidae.
Elk Cervus canadensis nelsoni in the Black Hills, South Dakota, have been declining since 2006 and there is concern by resource managers and hunters that puma Puma concolor predation may be contributing to declining herds. We evaluated characteristics at sites where puma successfully killed elk in the Black Hills of South Dakota. We evaluated characteristics at coarse (79-ha plots) and fine (0.2-ha plot) scales across the landscape. Our primary objective was to obtain a better understanding of vegetation and terrain characteristics that may have facilitated greater susceptibility of elk to predation by puma. We evaluated effects of road density, terrain heterogeneity, probability of elk use, and vegetation variables at 62 puma kill sites of elk and 186 random sites to identify key landscape attributes where elk were killed by puma. Elk were killed by puma in high use areas. Elk were also killed in areas that had greater amounts of edge and intermediate ruggedness at the coarse scale. Further, elk were killed in areas with greater small tree density and woody debris at the fine scale. High germination rates of ponderosa pine trees are unique to the Black Hills and provide dense patches of cover for puma. We hypothesize that cover from small trees and woody debris provided conditions where puma could stalk elk in areas with optimal security cover for elk. We suggest managers implement vegetation management practices that reduce small tree density and woody debris in areas with greater density of meadow—forest edge if they are interested in potentially diminishing hiding cover for puma in elk high use areas.
A recent study of Sitka black-tailed deer Odocoileus hemionus sitkensis demonstrated that opportunistic fawn capture yielded left-truncated data and ultimately resulted in overestimating fawn survival and spurious ecological model inference compared to neonates captured via vaginal implant transmitters (VITs). Given the ecological and economic value of ungulates worldwide and the importance of neonate survival to understanding population dynamics, the potential biases in survival estimates and causes of mortality caused by left-truncation must be transparent. Herein, we used a VIT-based dataset from white-tailed deer Odocoileus virginianus to examine potential problems with left-truncated data. We manipulated our original VIT-based dataset by randomly assigning age-at-capture to create three hypothetical opportunistic samples. We used the Kaplan—Meier estimator to quantify fawn survival to 16 weeks of age for the original and hypothetical datasets. Additionally, we compared the relative importance of mortality causes between the datasets. Survival for the original, VIT-based dataset was 0.121 (SE = 0.043), while hypothetical datasets yielded overestimates (ranging from 0.191 to 0.234). The hypothetical opportunistic samples overestimated coyote predation as a source of mortality, while underestimating starvation. Because management actions rely on accurate estimates of survival and causes of mortality, we recommend that neonatal survival studies consider biases caused by capture method. For robust estimates of survival, VIT-based samples appear to provide better estimates of survival, as opportunistic samples are biased high. We encourage future work to elucidate the potential for neonate capture technique to affect cause-specific mortality.