Geology topics

Patricia C. Ormsbee

Publications and source records attributed to Patricia C. Ormsbee.

5 recordsLinked to original sources

USGS2019

Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors

Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat ( Myotis lucifugus ) and the hoary bat ( Lasiurus cinereus ). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat ( = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat ( = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.

Oregon, Washington↗

USGS2019

North American Bat Monitoring Program regional protocol for surveying with stationary deployments of echolocation recording devices: Narrative version 1.0, Pacific Northwestern US

The outbreak of white-nose syndrome (WNS) and the growing awareness of the risks to bats from wind power generating facilities have driven radical changes to North American bat conservation. Over the last decade, formerly common species such as the little brown myotis (Myotis lucifugus) and hoary bat (Lasiurus cinereus) have experienced unprecedented mortality rates and are now facing non-trivial extinction risk. In response to this change, federal land management agencies such as the US National Park Service, US Fish and Wildlife Service, US Forest Service, US Bureau of Land Management and state wildlife management agencies such as the Oregon Department of Fish and Wildlife and Idaho Fish and Game have invested in collaborative, interagency bat monitoring to close the gap in information about bat welfare and to inform bat conservation strategies. Bats are notoriously difficult to track and study and there remains a paucity of fundamental information about the seasonal patterns of bat activity and habitat use and population distributions and abundances. Moreover, because bats are so highly mobile and difficult to survey (e.g., nocturnal flight), this information needs to be contextualized at broad regional (e.g., 10,000 km2) and range-wide extents. Delimiting bat populations at local scales (e.g., 100 km2) is very difficult and it is not clear, for example, how a declining trend in local (e.g., a small park unit) patterns of bat activity or relative abundance should be interpreted without broader context. In recognition of these challenges, a plan for coordinated continental-scale monitoring of bats, the North American Bat Monitoring Program (NABat) was developed (Loeb et al. 2015). The centerpiece of the plan is the use of a spatially-balanced randomized master sample of grid-cell sample units from a grid-based sampling frame to provide the architecture for collaboration and the statistical foundation for making inferences about bat populations across broad regions and entire bat geographic ranges. The plan outlines general goals, survey design, and field methods for both summertime acoustic surveys of bats as well as winter and summer counts of bats in hibernacula and maternity colonies but it does not provide field-level protocol and standard operating procedures for consistent and efficient implementation. This regional protocol provides these details for one component of NABat, the deployment of stationary acoustic detectors to record bats during summer, as is called for by the NABat plan. This protocol was written specifically to provide guidance and consistency across the Pacific Northwestern US (N. California [California Department of Fish and Wildlife Northern Region], Idaho, Washington, and Oregon; US Fish and Wildlife Service Region 1 and portion of Region 8 [in Northern California and Klamath Basin]; US Forest Service Region 6 and portions of Regions 1 and 5 in Idaho; and the Upper Columbia Basin, North Coast Cascades, and Klamath Networks of the National Park Service). This region has internal cohesion, sharing a distinct bat faunal assemblage of 15 species (with several additional species occurring on the southern periphery of the region), and a long history of collaborative bat monitoring beginning with the interagency Bat Grid Program which operated from 2003-2010 across Oregon and Washington (US Forest Service Region 6). This protocol will be coordinated and implemented by the Northwestern Bat Hub, on behalf of the collective interagency partnership. The Northwestern Bat Hub is housed on the Oregon State University-Cascades campus and leverages pooled partner funds and resources to maintain a small staff that coordinates and conducts monitoring, provides training and oversight, ensures high-quality data quality and control, and analyzes data and reports on results.

California, Idaho, Oregon, Washington↗

USGS2015

Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline

Aim Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making. Location Oregon and Washington, USA. Methods We developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km 2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines. Results Forest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis ( Myotis thysanodes ), canyon bat ( Parastrellus hesperus ) and pallid bat ( Antrozous pallidus ) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience. Main conclusions Landscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.

Oregon, Washington↗

USGS2014

Accounting for false-positive acoustic detections of bats using occupancy models

1. Acoustic surveys have become a common survey method for bats and other vocal taxa. Previous work shows that bat echolocation may be misidentified, but common analytic methods, such as occupancy models, assume that misidentifications do not occur. Unless rare, such misidentifications could lead to incorrect inferences with significant management implications. 2. We fit a false-positive occupancy model to data from paired bat detector and mist-net surveys to estimate probability of presence when survey data may include false positives. We compared estimated occupancy and detection rates to those obtained from a standard occupancy model. We also derived a formula to estimate the probability that bats were present at a site given its detection history. As an example, we analysed survey data for little brown bats Myotis lucifugus from 135 sites in Washington and Oregon, USA. 3. We estimated that at an unoccupied site, acoustic surveys had a 14% chance per night of producing spurious M. lucifugus detections. Estimated detection rates were higher and occupancy rates were lower under the false-positive model, relative to a standard occupancy model. Un-modelled false positives also affected inferences about occupancy at individual sites. For example, probability of occupancy at individual sites with acoustic detections but no captures ranged from 2% to 100% under the false-positive occupancy model, but was always 100% under a standard occupancy model. 4. Synthesis and applications. Our results suggest that false positives sufficient to affect inferences may be common in acoustic surveys for bats. We demonstrate an approach that can estimate occupancy, regardless of the false-positive rate, when acoustic surveys are paired with capture surveys. Applications of this approach include monitoring the spread of White-Nose Syndrome, estimating the impact of climate change and informing conservation listing decisions. We calculate a site-specific probability of occupancy, conditional on survey results, which could inform local permitting decisions, such as for wind energy projects. More generally, the magnitude of false positives suggests that false-positive occupancy models can improve accuracy in research and monitoring of bats and provide wildlife managers with more reliable information.

Oregon, Washington↗

USGS2012

Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus , the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species–energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during &sim;50% of the surveys in occupied sample units. The overall naïve estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to &sim;0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (&sim;0.04–0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America.

Ecological Applications↗