The pollination and seed dispersal activities of bats are particularly significant on the arid Channel Islands due to their numerous endemic and endangered plant species, which were historically diminished by introduced grazing animals. Since bats are also ecosystem indicators, their growing presence could signify that the island continues to recover, and inform management by identifying high biodiversity areas and guiding restoration initiatives.This study used non-invasive, passive acoustic monitoring methods, and identified bat species on Santa Rosa Island by analyzing echolocation calls using wildlife sound analysis software. Objectives included investigating spatiotemporal variations and abiotic factors that influence bat activity indices. Preliminary results suggest that, on SRI, wind conditions significantly reduced bat activity by a factor of -0.11 (p-value = 0.0004) and that there is no association between lunar illumination and bat activity on SRI (p-value = 0.069). It was found that there is no correlation between wind speed and lunar illumination, nor a combined effect on the number of bats detected (p-value= 0.50). Analysis of spatiotemporal relationships indicate that the species composition of the sites were substantially different (p-value = 0.022). There was no significant difference in activity of migratory and resident bats at the nursery (p-value = 0.432); however, resident bats were more active at the bunkhouse (p-value = 0.016), which could be due to the different types of habitats offered at each site. This study detected 20 species of bats that have never been recorded on the Channel Islands, including threatened and endangered species. It is important to consider that acoustic detectors only register the number of times a bat triggers them, and do not provide a count of bat populations. Nevertheless, this data serves as a starting point for the manual identification of live specimens on the Channel Islands.

Oral Presentation

10:45am – 12:15pm
Del Norte 2530

Biology

The rocky intertidal zone is a dynamic ecosystem with fluctuations of multiple environmental stressors during tidal cycles including temperature, wind, and emersion. Long term biological and environmental monitoring provides insight into how intertidal communities respond to these cycles, including during extreme events. Climate change has increased the frequency of these extreme events (e.g. heat waves), making it critical that we understand the biological impacts to predict community composition in the future. We have consistently surveyed sessile species and collected temperature data at two sites on Santa Rosa Island, Skunk Point and Bechers Bay, since 2015. A total of 20 point intercept species plots (100 counts per plot) split across four zones (low, mid, high, and splash) have been co-located with iButton thermochron temperature loggers to correlate species coverage with thermal conditions at each plot. In addition to temperature logging, wind data was collected from NOAA’s offshore buoys and low tide emersion was predicted by comparing the known plot heights with local tide data. On top of this, satellite data from NOAA provides chlorophyll and par readings for our two sites. When combined together, these covariates and percent coverage values can be turned into correlative and predictive models that provide valuable information on rocky intertidal conditions. Established correlative models give insight into how species trend with different covariates, while predictive models can hold immense value in their power to inform both scientists and policymakers of the potential effects of climate change as time moves forward.

Oral Presentation

10:45am – 12:15pm
Del Norte 2530

Biology