Geology topics

Michael C. True

Publications and source records attributed to Michael C. True.

4 recordsLinked to original sources

USGS2023

Fall migration, oceanic movement, and site residency patterns of eastern red bats (Lasiurus borealis) on the mid-Atlantic Coast

Along the mid-Atlantic coast of the United States, eastern red bats ( Lasiurus borealis ) are present during fall mating and migration, though little is currently known about most aspects of bat migration. To reveal migration patterns, and understand drivers of over-water flight, we captured and radio-tagged 115 eastern red bats using novel technology, and subsequently tracked and described their movements throughout the region. We compared over-water flight movements to randomly generated patterns using a use-availability framework, and subsequently used a generalized linear mixed effects model to assess the relationship of over-water flight to atmospheric variables. We used hidden Markov models to assess daily activity patterns and site residency. Most bats with long-distance movements traveled in a southwesterly direction, however path vectors were often oriented interior toward the continental landmass rather than along the coastline. We observed that some bats transited wide sections of the Chesapeake and Delaware bays, confirming their ability to travel across large water bodies. This over-water flight typically occurred in the early hours of the night and during favorable flying conditions. If flight over large water bodies is a proxy for over-ocean flight, then collision risk at offshore wind turbines – a major source of migratory bat fatalities – may be linked nightly to warm temperatures that occur early in the fall season. Risk, then, may be somewhat predictable and manageable with mitigation options linking wind-energy operation to weather conditions and seasonality.

Delaware, Maryland, New Jersey, Virginia↗

USGS2022

Unique land cover classification to assess day-roost habitat selection of northern long-eared bats on the Coastal Plain of North Carolina, USA

Reproductively successful and over-wintering populations of the endangered northern long-eared bat ( Myotis septentrionalis ) have recently been discovered on the Coastal Plain of North Carolina. Empirical data on resource selection within the region is limited, likely hindering management of these coastal forests. Our objectives were to determine roosting home range size, selection of day-roost tree species, second- and third-order roosting habitat selection, and to quantify the overall availability of resources in the surrounding landscape. We found core and peripheral roosting home range estimates were large, yet similar to observations from other areas of contiguous forests. Prior to juvenile volancy, female northern long-eared bats appear to select red maple ( Acer rubrum ), water ash ( Fraxinus caroliniana ), and loblolly pine ( Pinus taeda ) as day-roosts, but then use sweetgum ( Liquidambar styraciflua ), swamp bay ( Persea palustris ), and water tupelo ( Nyssa aquatica ) after juvenile volancy. At the second-order spatial scale, roosting home ranges were associated with woody wetlands farther from anthropogenic development and open water. However, within the third-order scale, northern long-eared bats were associated with undeveloped woody wetlands and upland forests, areas containing shorter trees and occurring proximal to open water. Peripheral and core areas were predicted to comprise approximately 20% of the local landscape. Our results show that complex and large tracts of woody wetlands juxtaposed with upland forests in this part of the Coastal Plain may be important for northern long-eared bats locally, results largely consistent with species management efforts in eastern North America.

North Carolina↗

USGS2021

Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development

In eastern North America, “tree bats” (Genera: Lasiurus and Lasionycteris ) are highly susceptible to collisions with wind energy turbines and are known to fly offshore during migration. This raises concern about ongoing expansion of offshore wind-energy development off the Atlantic Coast. Season, atmospheric conditions, and site-level characteristics such as local habitat (e.g., forest coverage) have been shown to influence wind turbine collision rates by bats onshore, and therefore may be related to risk offshore. Therefore, to assess the factors affecting coastal presence of bats, we continuously gathered tree bat occurrence data using stationary acoustic recorders on five structures (four lighthouses on barrier islands and one light tower offshore) off the coast of Virginia, USA, across all seasons, 2012–2019. We used generalized additive models to describe tree bat occurrence on a nightly basis. We found that sites either indicated maternity or migratory seasonal occurrence patterns associated with local roosting resources, i.e., presence of trees. Across all sites, nightly occurrence was negatively related to wind speed and positively related to temperature and visibility. Using predictive performance metrics, we concluded that our model was highly predictive for the Virginia coast. Our findings were consistent with other studies—tree bat occurrence probability and presumed mortality risk to offshore wind-energy collisions is highest on low wind speed nights, high temperature and visibility nights, and during spring and fall. The high predictive model performance we observed provides a basis for which managers, using a similar monitoring and modeling regime, could develop an effective curtailment-based mitigation strategy.

Virginia↗

USGS2021

Forecasting the distribution of a range-expanding bat reveals future response to climate change and habitat

Many terrestrial vertebrate species are exhibiting geographic distribution changes including poleward range limit shifts in response to increases in regional temperature. Bats are a highly mobile taxa capable of rapid responses to changes in abiotic or biotic conditions. In North America, recent extralimital records of the non-hibernating Lasiurus seminolus (Seminole bat) have been attributed to climate change, however such attributions remain speculative and potentially subject to sampling bias in the form of increased recent sampling efforts at latitudes north of the historical range. We used historical occurrence records and simple environmental variables within a Maxent modeling framework to model the historical distribution of suitable areas for this species. We transferred the model using near current environmental conditions and measured the ability of the model to capture the apparent expansion in distribution using recent extralimital occurrence records. This measure indicated a distribution expansion, largely attributed to increasing minimum temperatures. We used the model to forecast the expansion in distribution of suitable areas at three 20-year intervals and various climate change scenarios and provide extrapolation risk maps for each scenario. Although increasing temperatures may increase potentially occupiable areas, the species is associated with forests and often roosts in Pinus spp. (pines). This suitable habitat is reduced in presence to the northwest of the species’ range, which may constrain the future species expansion despite favorable temperatures. We demonstrated this effect by mapping limiting factors through future climate change scenarios. We discovered a broad shift of effects that constrained the distribution from minimum temperature to a metric of evergreen cover type as time and climate intensity increased. Although uncertainties exist, we predict further expansion of the Seminole bat widely over the next 60 years across the eastern United States where suitable habitat and climate conditions converge. Our results appear consistent with other bat species showing similar range extensions and in turn provide further evidence that bats may serve as bioindicators of global change.

Alabama, Arkansas, Florida, Georgia, Illinois, Ind↗