Multi-scale factors influencing detection, site occupancy and resource use by foraging bats in the Ozark Highlands of Missouri

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file (viewed on March 23, 2009)Vita.Thesis (Ph.D.) University of Missouri-Columbia 2007.Conservation of bat populations requires understanding the associations between bats and their use of resources. We used maximum likelihood to estimate probability of site occupancy using acoustic data for ten species of bats. We evaluated a priori hypotheses for both probability of detection and site occupancy using AIC. Time, temperature, moisture, vegetative clutter, and date influenced detection probability. Response to spatial scale varied by species. Habitat, patch, and landscape characteristics influenced site occupancy and varied among species. We evaluated use of resource utilization functions (RUFs) to assess habitat and landscape factors affecting foraging resource use by red bats, Lasiurus borealis. Highest foraging use was associated with open deciduous forest on ridges and upland drainages in areas close to non-forest edge and relatively high road density. Resource selection was variable among individuals, geographic location and stage of lactation. Management strategies that provide a range of composition and structural diversity will favor foraging use by L. borealis.Includes bibliographical reference

Development of an LC-MS/MS Method for Non-Invasive Biomonitoring of Neonicotinoid and Systemic Herbicide Pesticide Residues in Bat Hair

With over a quarter of the world’s bats species facing extinction, there is a need for ecotoxicological studies to assess if acute and sublethal exposure to newer pesticides such as neonicotinoids and carbonates contribute to population declines. Pesticide exposure studies in bats have been limited to terminal sampling methods, therefore we developed a non-invasive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method utilizing hair trimmings. The hair of big brown bats (Eptesicus fuscus) was collected and pooled by county to assess the best extraction solvent and solid-phase-extraction (SPE) clean-up cartridges. Using the best performing extraction solvent, methanol, and the best performing SPE cartridge, Chromabond HR-X, we developed an optimized multiple reaction monitoring (MRM) LC-MS/MS method for simultaneous determination of 3 neonicotinoids, clothianidin, imidacloprid, and thiamethoxam; 1 carbonate, carbaryl; and 4 systemic herbicides, 2,4-D, atrazine, dicamba, and glyphosate. The optimized protocol yielded the detection of 3–8 of the compounds in the county-level bat hair pools. 2,4-D, glyphosate, and imidacloprid were found in all samples with two of the county-level hair samples having glyphosate concentrations of over 3500 pg/mg of hair. This approach has great potential to facilitate non-terminal ecotoxicological studies assessing the effects of subacute (chronic) pesticide exposure in threatened and endangered bat species and other species experiencing population declines

Bat wing biometrics: using collagen–elastin bundles in bat wings as a unique individual identifier

The ability to recognize individuals within an animal population is fundamental to conservation and management. Identification of individual bats has relied on artificial marking techniques that may negatively affect the survival and alter the behavior of individuals. Biometric systems use biological characteristics to identify individuals. The field of animal biometrics has expanded to include recognition of individuals based upon various morphologies and phenotypic variations including pelage patterns, tail flukes, and whisker arrangement. Biometric systems use 4 biologic measurement criteria: universality, distinctiveness, permanence, and collectability. Additionally, the system should not violate assumptions of capture–recapture methods that include no increased mortality or alterations of behavior. We evaluated whether individual bats could be uniquely identified based upon the collagen–elastin bundles that are visible with gross examination of their wings. We examined little brown bats (Myotis lucifugus), northern long-eared bats (M. septentrionalis), big brown bats (Eptesicus fuscus), and tricolored bats (Perimyotis subflavus) to determine whether the “wing prints” from the bundle network would satisfy the biologic measurement criteria. We evaluated 1,212 photographs from 230 individual bats comparing week 0 photos with those taken at weeks 3 or 6 and were able to confirm identity of individuals over time. Two blinded evaluators were able to successfully match 170 individuals in hand to photographs taken at weeks 0, 3, and 6. This study suggests that bats can be successfully re-identified using photographs taken at previous times. We suggest further evaluation of this methodology for use in a standardized system that can be shared among bat conservationists

Within-season temporal variation in bat counts.

<p>Relative abundance and approximate 95% confidence intervals during December-March for (A) <i>M. lucifugus</i>, (B) <i>P. subflavus</i>, (C) <i>M. sodalis</i>, and (D) <i>M. septentrionalis</i>. Relative abundance was set equal to 1.0 at the maximum expected value.</p

Timing of hibernation surveys across years.

<p>Box plots showing date of hibernacula surveys during 1999–2011.</p

Long-term population trajectories.

<p>Expected relative abundance and approximate 95% confidence intervals during 1999–2011 for (A) <i>M. lucifugus</i>, (B) <i>P. subflavus</i>, (C) <i>M. sodalis</i>, and (D) <i>M. septentrionalis</i>. Relative abundance was set equal to 1.0 at the maximum expected value. Two trajectories are shown for each bat species: the trajectory with abundance estimates corrected for survey date of bat counts (in blue), and the uncorrected trajectory (red).</p

Improved Analysis of Long-Term Monitoring Data Demonstrates Marked Regional Declines of Bat Populations in the Eastern United States

<div><p>Bats are diverse and ecologically important, but are also subject to a suite of severe threats. Evidence for localized bat mortality from these threats is well-documented in some cases, but long-term changes in regional populations of bats remain poorly understood. Bat hibernation surveys provide an opportunity to improve understanding, but analysis is complicated by bats' cryptic nature, non-conformity of count data to assumptions of traditional statistical methods, and observation heterogeneities such as variation in survey timing. We used generalized additive mixed models (GAMMs) to account for these complicating factors and to evaluate long-term, regional population trajectories of bats. We focused on four hibernating bat species – little brown myotis (<i>Myotis lucifugus</i>), tri-colored bat (<i>Perimyotis subflavus</i>), Indiana myotis (<i>M. sodalis</i>), and northern myotis (<i>M. septentrionalis</i>) – in a four-state region of the eastern United States during 1999–2011.</p><p>Our results, from counts of nearly 1.2 million bats, suggest that cumulative declines in regional relative abundance by 2011 from peak levels were 71% (with 95% confidence interval of ±11%) in <i>M. lucifugus</i>, 34% (±38%) in <i>P. subflavus</i>, 30% (±26%) in <i>M. sodalis</i>, and 31% (±18%) in <i>M. septentrionalis</i>. The <i>M. lucifugus</i> population fluctuated until 2004 before persistently declining, and the populations of the other three species declined persistently throughout the study period. Population trajectories suggest declines likely resulted from the combined effect of multiple threats, and indicate a need for enhanced conservation efforts. They provide strong support for a change in the IUCN Red List conservation status in <i>M. lucifugus</i> from Least Concern to Endangered within the study area, and are suggestive of a need to change the conservation status of the other species. Our modeling approach provided estimates of uncertainty, accommodated non-linearities, and controlled for observation heterogeneities, and thus has wide applicability for evaluating population trajectories in other wildlife species.</p></div

Model selection.

<p>Shown are information criteria for fit of models including the fixed and random effects of (A) <i>M. lucifugus</i>, (B) <i>P. subflavus</i>, (C) <i>M. sodalis</i>, and (D) <i>M. septentrionalis</i>. Fixed effects are <i>Day</i>, smoothed <i>Day</i>, <i>Year</i>, and smoothed <i>Year</i>, and the random effects are <i>Route</i> and <i>Route</i> nested in <i>Location</i>. Best models were selected on the basis of Akaike's Information Criterion (AIC). DF are the degrees of freedom, Δ<i>_i</i> is the difference in AIC between the top-ranked and listed model, and <i>w_i</i> is the Akaike weight, the weight of evidence for each model in the set given the data (where 1.00 represents the highest likelihood of the model relative to other models). The number of models examined varied for each species because some random effects were not applicable for some species, due to the particular survey routes used.</p