This is the first field study of its kind to combine radio telemetry, passive samplers, and pesticide accumulation in tissues to characterize the amphibian exposome as it relates to pesticides. Understanding how habitat drives exposure in individuals (i.e., their exposome), and how that relates to individual health is critical to managing species in an agricultural landscape where pesticide exposure is likely. We followed 72 northern leopard frogs (Lithobates pipiens) in two agricultural wetlands for insight into where and when individuals are at high risk of pesticide exposure. Novel passive sampling devices (PSDs) were deployed at sites where telemetered frogs were located, then moved to subsequent locations as frogs were radio-tracked. Pesticide concentration in PSDs varied by habitat and was greatest in agricultural fields where frogs were rarely found. Pesticide concentrations in frogs were greatest in spring when frogs were occupying wetlands compared to late summer when frogs occupied terrestrial habitats. Our results indicate that habitat and time of year influence exposure and accumulation of pesticides in amphibians. Our study illustrates the feasibility of quantifying the amphibian exposome to interpret the role of habitat use in pesticide accumulation in frogs to better manage amphibians in agricultural landscapes.

Although wildfire plays an important role in maintaining biodiversity in many ecosystems, fire management to protect human assets is often carried out by different agencies than those tasked for conserving biodiversity. In fact, fire risk reduction and biodiversity conservation are often viewed as competing objectives. Here we explored the role of management through private land conservation and asked whether we could identify private land acquisition strategies that fulfill the mutual objectives of biodiversity conservation and fire risk reduction, or whether the maximization of one objective comes at a detriment to the other. Using a fixed budget and number of homes slated for development, we simulated 20 years of housing growth under alternative conservation selection
strategies, and then projected the mean risk of fires destroying structures and the area and configuration of important habitat types in San Diego County, California, USA. We found clear differences in both fire risk projections and biodiversity impacts based on the way conservation lands are prioritized for selection, but these differences were split between two distinct groupings. If no conservation lands were purchased, or if purchases were prioritized based on cost or likelihood of development, both the projected fire risk and biodiversity impacts were much higher than if conservation lands were purchased in areas with high fire hazard or high species richness. Thus, conserving land focused on either of the two objectives resulted in nearly equivalent mutual benefits for both. These benefits not only resulted from preventing development in sensitive areas, but they were also due to the different housing patterns and arrangements that occurred as development was displaced from those areas. Although biodiversity conflicts may still arise using other fire management strategies, this study shows that mutual objectives can be attained through land-use planning in this region. These results likely generalize to any place where high species richness overlaps with hazardous wildland vegetation.

Many utility scale renewable energy projects are currently proposed across the Mojave Ecoregion. Agencies that manage biological resources throughout this region need to understand the potential impacts of these renewable energy projects and their associated infrastructure (for example, transmission corridors, substations, access roads, etc.) on species movement, genetic exchange among
populations, and species’ abilities to adapt to changing environmental conditions. Understanding these
factors will help managers select appropriate project sites and possibly mitigate for anticipated effects of management activities. We used species distribution models to map habitat for 15 species across the Mojave Ecoregion to aid regional land-use management planning. Models were developed using a common 1 × 1 kilometer resolution with maximum entropy and generalized additive models. Occurrence data were compiled from multiple sources, including VertNet (vertnet.org/index.php), HerpNET (http://www.herpnet.org), and MaNIS (http://manisnet.org), as well as from internal U.S. Geological Survey databases and other biologists. Background data included 20 environmental covariates representing terrain, vegetation, and climate covariates. This report summarizes these environmental covariates and species distribution models used to predict habitat for the 15 species across the Mojave Ecoregion.