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 features (e.g., forest coverage) have been shown to influence wind turbine collision rates by bats onshore, and similar features may be related to risk offshore. In response to rapidly developing offshore wind energy development, I assessed the factors affecting coastal and offshore presence of tree bats. I continuously gathered tree bat nightly 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. I used generalized additive models to describe nightly tree bat occurrence in relation to multiple factors. I found that sites either indicated maternity or migratory patterns in their seasonal occurrence pattern that were associated with local roosting resources (i.e., presence of forest). Across all sites, nightly occurrence was negatively related to wind speed and positively related to temperature and visibility. Using predictive performance metrics, I concluded that the model was highly predictive for the Virginia coast. My findings were consistent with other studies—tree bat occurrence probability and presumed mortality risk to offshore wind-energy collisions is highest on nights with low wind speed, high temperature and visibility during spring and fall. The high predictive model performance I observed provides a basis for which managers, using a similar monitoring and modeling regime, could develop an effective curtailment-based mitigation strategy.
Although information at fixed points is helpful for managing specific sites, large questions remain on certain aspects of tree bat migration, in part because direct evidence (i.e., tracking of individuals) has been difficult to obtain so far. For instance, patterns in fall behavior such as the timing of migration events, the existence of migratory pathways, consistencies in the direction of travel, the drivers of over-water flight, and the activity states of residents (or bats in stopover) remain unstudied in the mid-Atlantic. The recently established Motus Wildlife Tracking System, an array of ground-based receiver stations, provides a new technique to track individual bats via the ability to detect course-scale movement paths of attached very high frequency radio-tags. To reveal patterns in migration, and to understand drivers of over-water flight, I captured and radio-tagged 115 eastern red bats (Lasiurus borealis) and subsequently tracked their movements. For the bats with evidence of large movements, most traveled in a southwesterly direction whereby paths were often oriented interior toward the continental landmass rather than being oriented along the coastline. This observation challenges earlier held beliefs that bats closely follow linear landscape features, such as the coast, when migrating. I documented bats traveling across wide sections of the Chesapeake and Delaware bays confirming the species' ability to travel across large water bodies. This behavior typically occurred in the early hours of the night and during favorable flying conditions such as low wind speeds, warm temperatures, and/or during sudden increases in temperature associated with the passage of cold fronts. For bats engaging in site residency through the fall, the proportion of night-hours in which bats were in a resting state (and possibly torpor), increased with colder temperatures and the progression of the fall season. My study demonstrated that bats may be at risk to offshore wind turbine collisions off the mid-Atlantic, but that this risk might be minimal if most bats are migrating toward the interior landscape rather than following the coast. Nonetheless, if flight over large water bodies such as Chesapeake and Delaware bays is a viable proxy for over-ocean flight, then collision risk at offshore wind turbines may be somewhat linked to atmospheric, seasonal timing, or other effects, and therefore some level of predictable and manageable with mitigations options such as smart curtailment. / Master of Science / In eastern North America on the mid-Atlantic and Northeast coasts, a group of bat species named "tree bats" engage in seasonal migrations—generally shifting north in spring and south in fall. On the East coast, it is known that eastern red bats and silver-haired bats will occasionally fly over the ocean during these periods. Although this behavior is somewhat hard to explain due to their reliance on trees for day-time roosting, it raises concern conservation concerns due to the current and future rapid development of offshore wind energy turbines. This is compounded by the fact that collision rates with turbines are high for this species group in general and highest in the fall migratory season. The fall period is also when bats may be attracted to tall structures such as turbines and when most offshore flight happens. Nevertheless, bats are sensitive to atmospheric conditions such as temperature and wind speed, and other factors influence their propensity to fly (and be at risk to turbine strikes). So, understanding these drivers may aid in understanding the conditions that present the highest risk to strike at offshore wind turbines.
In response to rapid offshore wind development in the Atlantic, I recorded bats in coastal Virginia, USA from 2012–2019, using acoustic monitors—devices that collect the echolocation vocalizations of bats. I found that tree bat visitation offshore or on barrier islands was associated with wind speed, temperature, visibility, and seasonality. Using statistical modeling, I developed a predictive tool to assess occurrence probabilities at varying levels of wind speed, temperature, and seasonality. Probability of occurrence and therefore assumed risk to collision was highest on high temperature and visibility nights, low wind speed nights, and during the spring and fall seasons. Therefore, I suggest a similar modeling regime could be used to predict the occurrence of bats at offshore wind sites to inform potential mitigation efforts.
Next, I attempted to answer broader questions about tree bat migratory behavior such as attempting to identify migratory pathways throughout the mid-Atlantic. The Motus Wildlife Tracking System gives researchers the ability to directly track individuals over long-distances with radio-transmitters and ground-based receiver stations. Using Motus, I captured and radio-tagged >100 tree bats, which were of majority eastern red bats and tracked their movements throughout the mid-Atlantic region. I found that movements were not oriented along the coastline, which challenged previously held beliefs that bats use the coast during migration. Tree bats also traversed large bodies of water, the Chesapeake and Delaware bays, confirming the ability for this group to fly over-water. Through statistical modeling, I found that these over-water bouts were early in the night and related to advantageous flying conditions such as low wind speeds, high temperatures, and during periods of sudden temperature increase (which could be linked to the passage of cold weather fronts). Offshore collision risk to tree bats may be somewhat minimal if most bats orient inland, rather than coastal for their migration movement. Nevertheless, for those bats that do fly over the ocean, if crossing large waterbodies is a viable proxy for over-ocean movement, then this behavior is linked to multiple factors, of which can be used to predict occurrences and even potentially predict and manage risk to collision.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/107784 |
| Date | 18 January 2022 |
| Creators | True, Michael C. |
| Contributors | Fish and Wildlife Conservation, Ford, W. Mark, Catlin, Daniel Herbert, Higdon, David |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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