Abstract
We initiated a multi-year, pre-construction study in summer 2006 to investigate patterns of bat activity at the proposed Hoosac Wind Energy Project (HWEP) in northwestern Massachusetts. The primary objectives of this study were to: 1) determine levels and patterns of activity of different phonic groups of bats using the proposed HWEP prior to construction; 2) correlate bat activity with weather and other environmental variables; and, 3) combine results from this study with those from similar efforts to determine if indices of pre-construction bat activity can be used to predict post-construction bat fatalities at proposed wind facilities. We report results from two years of pre-construction data collection.
We recorded echolocation calls of bats with Anabat II zero-crossing ultrasonic detectors, programmed to record calls beginning ½-hour prior to sunset and ending ½-hour after sunrise each day of the study from 27 July – 11 November 2006, and 1 June – 31 October 2007. We used 5 meteorological towers to position acoustic microphones at 10, 31.5, and 39.2 m above ground level (agl). We identified 2 broad phonic groups, high frequency bats frequency (≥ 33 kHz, mostly Myotis spp., red bats [Lasiurus borealis] and tri-colored bats [Perimyotis subflavus]), low frequency bats (<33 kHz, hoary bats [Lasiurus cinereus], big brown bats [Eptesicus fuscus], and silver-haired bats [Lasionycteris noctivagans]). We also identified a third phonic group, hoary bats, because this species is vulnerable to wind development and because their echolocation sequences are relatively easy to distinguish among other low frequency bats. In 2006, we recorded a total of 2,424 and 1,364 high frequency and low frequency bat passes, respectively. Hoary bats comprised 30 % (n = 410) of low frequency passes. In 2007, we recorded a total of 7,739 and 2,063 high frequency and low frequency passes, respectively. Hoary bats comprised 13 % (n = 267) of low frequency passes.
Seasonally, bat activity was highest between mid-July and mid-August for all phonic groups. However, timing and intensity of peak activity differed between years. Flight altitude was consistent between years, but differed among phonic groups. We detected high frequency bats more frequently at 10 m. Although activity by low frequency bats was more evenly distributed among the three heights, the majority of passes were recorded from higher altitudes (i.e., 31 m and 39 m agl). We also detected hoary bat passes more frequently at higher altitudes.
Our models incorporated location, temperature and several win d speed measurements. Temperature and location were consistently the most important factors in our models. We found a positive relationship with bat activity and temperature, particularly at temperatures >12° C. In general, both the probability of activity and estimated number of calls from each phonic group increased as much as 39% for every 1° C increase in temperature. Bat activity was highest at Bakke 2 followed by Crum 1, Crum 2 and Bakke 1. However, location alone explained only 2 – 8% of the variation in activity. While some measure of wind speed often was important, it never explained more than an additional 3.6% of the variation in activity. The HWEP has higher mean nightly wind speeds than other sites where comparable data have been gathered, which may explain why the relationship between activity and wind was not as strong as previously documented.
As this study was conducted at a single proposed wind energy facility located on forested ridges in northwestern Massachusetts the statistical inferences are limited to this site. To improve statistical power and determine whether our findings reflect patterns of bat activity on similar forested ridges with comparable vegetation composition and topography, additional studies are required at sites with similar characteristics in the region. Despite acoustic and meteorological equipment malfunctions, we were able to quantify the spatial (vertical and horizontal) and temporal (seasonal and yearly) activity patterns of bats. These data may provide useful information for predicting when, where, and which bats may be most at risk of interacting with wind turbines at the HWEP. Moreover, specific timings and locations of peak activity may further refine the use of curtailment as a mitigation option.