Showing papers by "William J. McShea published in 2020"

An empirical evaluation of camera trap study design: How many, how long and when?

Abstract: 1. Camera traps deployed in grids or stratified random designs are a well-established survey tool for wildlife but there has been little evaluation of study design parameters. 2. We used an empirical subsampling approach involving 2225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design (number of sites, duration and season of sampling) and their influence on the estimation of three ecological metrics (species richness, occupancy, detection rate) for mammals. 3. We found that 25-35 camera locations were needed for precise estimates of species richness, depending on scale of the study. The precision of species-level estimates of occupancy was highly sensitive to occupancy level, with 0.75) species, but more than 150 sites likely needed for rare (<0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted for habitat variability within the study area. Running a camera at a site for 2 weeks was most efficient for detecting new species, but 3-4 weeks were needed for precise estimates of local detection rate, with no gains in precision observed after 1 month. Metrics for all mammal communities were sensitive to seasonality, with 37-50% of the species at the sites we examined fluctuating significantly in their occupancy or detection rates over the year. This effect was more pronounced in temperate sites, where seasonally sensitive species varied in relative abundance by an average factor of 4-5, and some species were completely absent in one season due to hibernation or migration. 4. We recommend the following guidelines to efficiently obtain precise estimates of species richness, occupancy and detection rates with camera trap arrays: run each camera for 3-5 weeks across 40-60 sites per array. We recommend comparisons of detection rates be model-based and include local covariates to help account for small-scale variation. Furthermore, comparisons across study areas or times must account for seasonality, which had strong impacts on mammal communities in both tropical and temperate sites.,We used camera trap data already available through repositories or collaborators. Most data came from the eMammal or TEAM repositories. We also used one data set (China) from collaborators that was not already archived. All camera traps were set similarly, in being placed on a tree at 0.5m facing parallel to the ground, with no bait. A variety of camera models were used, but all had infrared flashes and fast (<0.5s) trigger times. Camera trap designs were either regular (grid) or stratified random.,For this paper we wanted to asess the importance of three things to camera trap study design: amount of locations surveyed (spatial), amount of time each survey ran (temporal), and rather season mattered (seasonal). We broke into three teams to analyze these data, and used three slightly different collections of data for each team. Thus, you will find three datasets labeled as to which analyses they were part of: spatial, temporal, or seasonal. All data is presented as raw detection data, giving the date, time, and species for each time photograph was recorded. These are organized as 'deployments' representing a time period a camera was placed in a given location. We are including a TXT file with the Data Dictionary from eMammal that describes all the standard fields. A few files have additional fields we added that should be self explanatory.,

Born‐digital biodiversity data: Millions and billions

Abstract: wileyonlinelibrary.com/journal/ddi | 1 Museum specimens have always provided the most basic informa‐ tion about the spatial distribution of life on earth: which species live where and when. These records have formed the basis for our biodiversity range maps, biogeography and conservation planning (Suarez & Tsutsui, 2004). As the pace of global change accelerates, we need more biodiversity data to monitor how species are respond‐ ing, which are most in need of conservation efforts, and what kinds of impacts these efforts deliver (Dirzo et al., 2014). A recent paper by Farley, Dawson, Goring, and Williams (2018) discussed ecology's transition into the era of big data and showed exponential increases in biodiversity records in the Global Biodiversity Information Facility (GBIF) and other museum databases. A growing digital archive should put us in a good position to monitor change. However, another recent paper by Malaney and Cook (2018) showed that traditional museums actually are not keep‐ ing pace. Mammal specimen collecting in the United States reached its peak around 1990 and has dropped by a factor of three since then, with fewer than 5,000 specimens collected annually in recent years. That this is the situation for North American mammals—one of the world's best surveyed faunas—sheds stark light on what poor resolution incoming specimens will provide to understand changes in our global biodiversity. But what, then, explains the mismatch be‐ tween the increases in GBIF data and the decreases in actual spec‐ imen collection? Received: 26 October 2018 | Revised: 7 August 2019 | Accepted: 28 August 2019 DOI: 10.1111/ddi.12993

Retreat of large carnivores across the giant panda distribution range.

Abstract: As both a flagship and umbrella species, the giant panda (Ailuropoda melanoleuca) is one of the most heavily invested species in conservation. Here, we report the wide distribution range retreat of the leopard (Panthera pardus, 81% loss), snow leopard (P. uncia, 38%), wolf (Canis lupus, 77%) and dhole (Cuon alpinus, 95%) from protected areas in the giant panda distribution range since the 1960s. The present findings indicate the insufficiency of giant panda conservation for protecting these large carnivore species and suggest that future conservation efforts should target restoring ecosystems with high trophic complexity to facilitate the recovery of large carnivore populations.

Effectiveness of management zoning designed for flagship species in protecting sympatric species.

Abstract: Flagship species have been used widely as umbrella species (i.e., species with large home range whose protection often provides protection for sympatric species) in the management of China's nature reserves. This conflation of flagship and umbrella species is best represented by the giant panda (Ailuropoda melanoleuca) and other large, endangered mammals designated as conservation targets in site selection and planning of reserves. Few empirical studies have tested the effectiveness of flagship species as surrogates for a broader range of sympatric species. Using extensive camera-trap data, we examined the effectiveness of management zones designated to protect flagship (target) species in conserving sympatric species in 4 wildlife reserves (Gutianshan, Changqing, Laohegou, and Wolong). We tested whether the progression from peripheral to core zones was associated with an increasing habitat association for both target and sympatric species. The distribution patterns of the study species across the zones in each reserve indicated a disparity between management zones and the species' habitat requirements. Management zone was included in the final model for all target species, and most of them had higher occurrence in core zones relative to less-protected zones, but zone was not a predictor for most of the sympatric species. When management zone was associated with the occurrence of sympatric species, threatened species generally had higher detections in core zones, whereas common species had higher detections outside of the core zone. Our results suggested that reserve planning based on flagship species does not adequately protect sympatric species due to their specialized habitat requirements. We recommend re-examining the effectiveness of management zoning and urge a multispecies and reserve-wide monitoring plan to improve protection of China's wildlife.

Temporal population variability in local forest communities has mixed effects on tree species richness across a latitudinal gradient

Abstract: Among the local processes that determine species diversity in ecological communities, fluctuation-dependent mechanisms that are mediated by temporal variability in the abundances of species populations have received significant attention. Higher temporal variability in the abundances of species populations can increase the strength of temporal niche partitioning but can also increase the risk of species extinctions, such that the net effect on species coexistence is not clear. We quantified this temporal population variability for tree species in 21 large forest plots and found much greater variability for higher latitude plots with fewer tree species. A fitted mechanistic model showed that among the forest plots, the net effect of temporal population variability on tree species coexistence was usually negative, but sometimes positive or negligible. Therefore, our results suggest that temporal variability in the abundances of species populations has no clear negative or positive contribution to the latitudinal gradient in tree species richness.

Incorporating local habitat heterogeneity and productivity measures when modelling vertebrate richness

Abstract: Declining species richness is a global concern; however, the coarse-scale metrics used at regional or landscape levels might not accurately represent the important habitat characteristics needed to estimate species richness. Currently, there exists a lack of knowledge with regard to the spatial extent necessary to correlate remotely sensed habitat metrics to species richness and animal surveys. We provide a protocol for determining the best scale to use when merging remotely sensed habitat and animal survey data as a step towards improving estimates of vertebrate species richness on broad scales. We test the relative importance of fine-resolution habitat heterogeneity and productivity metrics at multiple spatial scales as predictors of species richness for birds, frogs and mammals using a Bayesian approach and a combination of passive monitoring technologies. Model performance was different for each taxonomic group and dependent on the scale at which habitat heterogeneity and productivity were measured. Optimal scales included a 20-m radius for bats and frogs, an 80-m radius for birds and a 180-m radius for terrestrial mammals. Our results indicate that optimal scales do exist when merging remotely sensed habitat measures with ground-based surveys, but they differ between vertebrate groups. Additionally, the selection of a measurement scale is highly influential to our understanding of the relationships between species richness and habitat characteristics.