Geology topics

Rogelio M. Rodriguez

Publications and source records attributed to Rogelio M. Rodriguez.

3 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↗

USGS2018

Improving geographically extensive acoustic survey designs for modeling species occurrence with imperfect detection and misidentification

Acoustic recording units (ARUs) enable geographically extensive surveys of sensitive and elusive species. However, a hidden cost of using ARU data for modeling species occupancy is that prohibitive amounts of human verification may be required to correct species identifications made from automated software. Bat acoustic studies exemplify this challenge because large volumes of echolocation calls could be recorded and automatically classified to species. The standard occupancy model requires aggregating verified recordings to construct confirmed detection/non‐detection datasets. The multistep data processing workflow is not necessarily transparent nor consistent among studies. We share a workflow diagramming strategy that could provide coherency among practitioners. A false‐positive occupancy model is explored that accounts for misclassification errors and enables potential reduction in the number of confirmed detections. Simulations informed by real data were used to evaluate how much confirmation effort could be reduced without sacrificing site occupancy and detection error estimator bias and precision. We found even under a 50% reduction in total confirmation effort, estimator properties were reasonable for our assumed survey design, species‐specific parameter values, and desired precision. For transferability, a fully documented r package, OCacoustic, for implementing a false‐positive occupancy model is provided. Practitioners can apply OCacoustic to optimize their own study design (required sample sizes, number of visits, and confirmation scenarios) for properly implementing a false‐positive occupancy model with bat or other wildlife acoustic data. Additionally, our work highlights the importance of clearly defining research objectives and data processing strategies at the outset to align the study design with desired statistical inferences.

Ecology and Evolution↗