Moving in the anthropocene: global reductions in terrestrial mammalian movements

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission

Data from: Accounting for tagging-to-harvest mortality in a Brownie tag-recovery model by incorporating radio-telemetry data

The Brownie tag-recovery model is useful for estimating harvest rates but assumes all tagged individuals survive to the first hunting season; otherwise, mortality between time of tagging and the hunting season will cause the Brownie estimator to be negatively biased. Alternatively, fitting animals with radio transmitters can be used to accurately estimate harvest rate but may be more costly. We developed a joint model to estimate harvest and annual survival rates that combines known-fate data from animals fitted with transmitters to estimate the probability of surviving the period from capture to the first hunting season, and data from reward-tagged animals in a Brownie tag-recovery model. We evaluated bias and precision of the joint estimator, and how to optimally allocate effort between animals fitted with radio transmitters and inexpensive ear tags or leg bands. Tagging-to-harvest survival rates from >20 individuals with radio transmitters combined with 50–100 reward tags resulted in an unbiased and precise estimator of harvest rates. In addition, the joint model can test whether transmitters affect an individual's probability of being harvested. We illustrate application of the model using data from wild turkey, Meleagris gallapavo, to estimate harvest rates, and data from white-tailed deer, Odocoileus virginianus, to evaluate whether the presence of a visible radio transmitter is related to the probability of a deer being harvested. The joint known-fate tag-recovery model eliminates the requirement to capture and mark animals immediately prior to the hunting season to obtain accurate and precise estimates of harvest rate. In addition, the joint model can assess whether marking animals with radio transmitters affects the individual's probability of being harvested, caused by hunter selectivity or changes in a marked animal's behavior

Evaluating Inter-Rater Reliability and Statistical Power of Vegetation Measures Assessing Deer Impact

Long-term vegetation monitoring projects are often used to evaluate how plant communities change through time in response to some external influence. Here, we evaluate the efficacy of vegetation monitoring to consistently detect changes in white-tailed deer browsing effects. Specifically, we compared inter-rater reliability (Cohen’s κ and Lin’s concordance correlation coefficient) between two identically trained field crews for several plant metrics used by Pennsylvania state agencies to monitor deer browsing impact. Additionally, we conducted a power analysis to determine the effect of sampling scale (1/2500th or 1/750th ha plots) on the ability to detect changes in tree seedling stem counts over time. Inter-rater reliability across sampling crews was substantial for most metrics based on direct measurements, while the observational based Deer Impact Index (DII) had only moderate inter-rater reliability. The smaller, 1/2500th ha sampling scale resulted in higher statistical power to detect changes in tree seedling stem counts due to reduced observer error. Overall, this study indicates that extensive training on plant identification, project protocols, and consistent data collection methods can result in reliable vegetation metrics useful for tracking understory responses to white-tailed deer browsing. Smaller sampling scales and objective plant measures (i.e., seedling counts, species richness) improve inter-rater reliability over subjective measures of deer impact (i.e., DII). However, considering objective plant measures when making a subjective assessment regarding deer browsing effects may also improve DII inter-rater reliability

Species_Code_List_2014

List of species names for abbreviation codes used in Tree_Data_2014.csv, Seedling_Data_2014.csv, and Cover_Data_204.cs

Turkey Case Study

Very-high frequency (VHF) collar and reward-tag data for a case study on wild turkey in Pennsylvania from 2010-2012. The data is in the format required by program SURVIV, and the additional code to run the integrated Brownie tag-recovery and known-fate model is included

White-tailed Deer Case Study

Very-high frequency (VHF) collar and reward-tag data for a case study on white-tailed deer in Pennsylvania from 2009-2011. The data is in the format required by program SURVIV, and the additional code to run the integrated Brownie tag-recovery and known-fate model is included

Data from: Soil chemistry, and not short-term (1-2 year) deer exclusion, explains understory plant occupancy in forests affected by acid deposition

The loss of species diversity and plant community structure throughout the temperate deciduous forests of North America have often been attributed to overbrowsing by white-tailed deer (Odocoileus virginanus). Slow species recovery following removal from browsing, or reduction in deer density, has been termed a legacy effect of past deer herbivory. However, vegetation legacy effects have also coincided with changes to soil chemistry throughout the northeastern United States. In this paper, we assess the viability of soil chemistry (i.e. pH, extractable nutrients, and extractable metals) and other factors (topography, light, overstory basal area, and location) as alternative explanations for a lack of vegetation recovery. We compared the relative effects of soil chemistry, site conditions, and short-term (1-2 year) deer exclusion on single-species occupancy probabilities of 10 plant taxa common to oak-hickory forests in central Pennsylvania. We found detection for all modeled species was constant and high (p > 0.65), and occupancy probability of most taxa was best explained by at least 1 soil chemistry parameter. Specifically, ericaceous competing vegetation was more likely to occupy acidic (pH < 3.5), base cation poor (K < 0.20 cmolc/kg) sites, while deer-preferred plants were less likely to occur when soil manganese exceeded 0.1 cmolc/kg. Short-term deer exclusion did not explain occupancy of any plant taxon, and site conditions were of nominal importance. This study demonstrates the importance of soil chemistry in shaping plant community composition in the northcentral Appalachians, and suggests soil as an alternative, or additional, explanation for deer vegetation legacy effects. We suggest that the reliance on phyto-indicators of deer browsing effects may overestimate the effects of browsing if those species are also limited by unfavorable soil conditions. Future research should consider study designs that address the complexity of deer forest interactions, especially in areas with complex site-vegetation histories

Tree_Data_2014

Overstory tree measurements (>=5" dbh) at 24 sampling sites at Rothrock and Bald Eagle state forests in central Pennsylvania. See Vegetation_Metadata_2014.csv and Vegetation_Metadata_2014.csv for specific column descriptions and data formatting

Caution is warranted when using animal space-use and movement to infer behavioral states

Abstract Background Identifying the behavioral state for wild animals that can’t be directly observed is of growing interest to the ecological community. Advances in telemetry technology and statistical methodologies allow researchers to use space-use and movement metrics to infer the underlying, latent, behavioral state of an animal without direct observations. For example, researchers studying ungulate ecology have started using these methods to quantify behaviors related to mating strategies. However, little work has been done to determine if assumed behaviors inferred from movement and space-use patterns correspond to actual behaviors of individuals. Methods Using a dataset with male and female white-tailed deer location data, we evaluated the ability of these two methods to correctly identify male-female interaction events (MFIEs). We identified MFIEs using the proximity of their locations in space as indicators of when mating could have occurred. We then tested the ability of utilization distributions (UDs) and hidden Markov models (HMMs) rendered with single sex location data to identify these events. Results For white-tailed deer, male and female space-use and movement behavior did not vary consistently when with a potential mate. There was no evidence that a probability contour threshold based on UD volume applied to an individual’s UD could be used to identify MFIEs. Additionally, HMMs were unable to identify MFIEs, as single MFIEs were often split across multiple states and the primary state of each MFIE was not consistent across events. Conclusions Caution is warranted when interpreting behavioral insights rendered from statistical models applied to location data, particularly when there is no form of validation data. For these models to detect latent behaviors, the individual needs to exhibit a consistently different type of space-use and movement when engaged in the behavior. Unvalidated assumptions about that relationship may lead to incorrect inference about mating strategies or other behaviors