North American Bat Monitoring Program in British Columbia: 2021 Data Summary and Activity Trend Analyses (2016 – 2021)
Bibliographic record
Abstract
The North American Bat Monitoring (NABat; Loeb et al. 2015) program is a multi-agency initiative administered by the US Geological Survey (USGS).NABat efforts in BC aim to collect critical baseline data to inform conservation and immediate and long-term management decisions on spatial scales ranging from local/regional to continental.Wildlife Conservation Society Canada has coordinated and implemented the program in British Columbia since 2016 through partnerships and engagements with bat biologists and naturalists across the province.The primary goal of NABat is to establish species diversity and relative activity/abundance data before, during and after white-nose syndrome (WNS) arrives in the province.WNS is a deadly fungal disease that has been decimating hibernating bat populations as it spreads from the point of initial discovery in New York State and from a secondary point introduction in Washington State.We have successfully completed our first six years of NABat monitoring in B.C. with a total of 52 operating grid cells, 20 of which are part of our original 22 grid cells.These data provide baselines for pre-white-nose syndrome (WNS) bat distribution and activity data in the province that can be used to gauge changes moving forward using trend analyses.In this report we describe the acoustic NABat monitoring program and summarize the acoustic NABat data in BC.Specifically, we provide:1) descriptions of NABat objectives; 2) progress to date, including annual sample sizes; 3) locations and site information from all grid cells in BC; 4) tabulated acoustic results from both stationary and transect sampling, including species, relative activity (stationary detectors), and relative abundance (transects) for all NABat in BC data; 5) discussion of findings and the monitoring process, including challenges, solutions, successes, significance of results, and lessons learned; and 6) future directions.We summarize bat acoustic activity recorded by stationary detectors and mobile transects throughout the sixth year of NABat in BC.In 2021 we surveyed 52 of 55 current grid cells and once again detected all species of bats thought to occur in BC (17).Three grid cells were not monitored in 2021 due to wildfire and COVID-19-related logistical and safety concerns.Species distribution changes and updated maps are described below.Acoustics is one of several tools used to inventory bats.Because some otherwise disparate bat species can have substantial overlap in acoustic signatures, species confirmation in some locations, especially where out-of-range species have been detected, is needed before species presence should be considered confirmed.This is more applicable for some species than others.For example, although acoustically detected in some SW BC grid cells, Mexican Free-tailed Bats have yet to be confirmed in the province.Similarly, Canyon Bats have been recorded at some detectors in the Okanagan and Boundary regions, but this species has yet to be confirmed north of the Washington border. WCS Canada Bat Conservation Program 5 | P a g eWe also present an updated set of modelling results from our comprehensive statistical analysis examining trends in acoustic activity data at regional and provincial scales.Our initial models have produced preliminary trends identifying significant decreases in activity from Big Brown Bat, decreases in activity from Townsend's Big-eared Bat and Long-eared Myotis, and no significant changes in activity of the remaining species in BC, including Little Brown Myotis.These activity estimates do not necessarily indicate changes in abundance but they may be useful indicators of changes in bat populations in specific regions that should be considered for management decisions, particularly when combined with other sources of data.As more years of data are collected, increasing sample sizes in each grid cell and accounting for more inter-annual variation, estimates are expected to improve in reliability and power.This also applies to estimates at regional and provincial scales as we fill in gaps in our monitoring network across the range of a species.Recent analyses of BC data conducted by the continental NABat program (US Geological Survey) reveal similar changes in occupancy on a provincial level.Their independent analyses based on a slightly different suite of covariates and focussed on occupancy rather than activity, revealed a small non-significant increase in occupancy of Little Brown Myotis in BC and a significant continental scale decrease in occupancy for this species.In 2021 we initiated a partnership with Alaska Department of Fish and Game to establish an Alaska-BC NABat Hub, with the goal of coordinating our efforts and pooling our data to improve regional trend estimates.This new partnership provides critical data, particularly in the Alaska "panhandle" region bordering northwestern BC, where our sampling efforts have so far been relatively sparse.WCS Canada spearheaded the creation of a new provincial scale NABat Steering Committee with our major partners (BC Parks, BC Ministry of Environment and Climate Change Strategy) and a BC-US NABat Advisory Committee with US Geological Survey (Continental NABat program), Canadian Wildlife Health Cooperative (Canadian NABat Coordinator) and members of the provincial NABat Steering Committee.These committees will guide the course of our program over the long term helping to ensure it is efficient and effective at all scales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".