Marty L. Leonard | Geology Reports

USGS2024

Advanced quantitative precipitation information: Improving monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay area

Advanced Quantitative Precipitation Information (AQPI) is a synergistic project that combines observations and models to improve monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay Area. As an experimental system, AQPI leverages more than a decade of research, innovation, and implementation of a statewide, state-of-the-art network of observations, and development of the next generation of weather and coastal forecast models. AQPI was developed as a prototype in response to requests from the water management community for improved information on precipitation, riverine, and coastal conditions to inform their decision-making processes. Observation of precipitation in the complex Bay Area landscape of California’s coastal mountain ranges is known to be a challenging problem. But, with new advanced radar network techniques, AQPI is helping fill an important observational gap for this highly populated and vulnerable metropolitan area. The prototype AQPI system consists of improved weather radar data for precipitation estimation; additional surface measurements of precipitation, streamflow, and soil moisture; and a suite of integrated forecast modeling systems to improve situational awareness about current and future water conditions from sky to sea. Together these tools will help improve emergency preparedness and public response to prevent loss of life and destruction of property during extreme storms accompanied by heavy precipitation and high coastal water levels—especially high-moisture laden atmospheric rivers. The Bay Area AQPI system could potentially be replicated in other urban regions in California, the United States, and worldwide.

California↗

USGS2016

Weather as a proximate explanation for fission–fusion dynamics in female northern long-eared bats

Fission–fusion dynamics appear common among temperate bats where females form roost groups that change in size and composition, as females switch roosts almost daily. One hypothesis for frequent roost switching is that females move to find suitable thermal conditions as ambient conditions change. Tests of this hypothesis have, however, been conducted mostly at roosts in artificial structures where microclimate is relatively stable. The goal of our study was to determine whether roost switching and roost use by northern long-eared bats, Myotis septentrionalis , that roost in trees are related to ambient conditions. We used generalized linear fixed effects models to explore the influence of roost characteristics and changes in ambient conditions on the likelihood of roost switching. We used canonical correlation analyses to examine the relationship between ambient conditions and roost characteristics. Roost switching was indeed linked to ambient conditions together with characteristics of roosts on the previous day; the best descriptors of roost switching differed between the two geographical regions we analysed. In Nova Scotia, females were less likely to switch roosts when it rained, particularly if they were in roosts below surrounding canopy whereas they were more likely to switch roosts when they were in roosts of high decay. Females roosted in shorter trees in earlier decay classes on warm days, as well as on windy and rainy days. In Kentucky, females were more likely to switch roosts at high temperatures, particularly when they were in roosts in high decay. Females roosted in shorter, decayed trees on warm days, and in less decayed trees with small diameter on windy and rainy days. Our results suggest bats switch roosts in response to changes in ambient conditions to select suitable roosting conditions, which may explain some of the proximate factors shaping fission–fusion dynamics of bats.

Animal Behaviour↗