Empirical evidence for effects of invasive American Bullfrogs on occurrence of native amphibians and emerging pathogens.

Invasive species and emerging infectious diseases are two of the greatest threats to biodiversity. American Bullfrogs (Rana [Lithobates] catesbeiana), which have been introduced to many parts of the world, are often linked with declines in native amphibians via predation and the spread of emerging pathogens such as amphibian chytrid fungus (Batrachochytrium dendrobatidis [Bd]) and ranaviruses. Although many studies have investigated the potential role of bullfrogs in the decline of native amphibians, analyses that account for shared habitat affinities and imperfect detection have found limited support for clear effects. Similarly, the role of bullfrogs in shaping the patch-level distribution of pathogens is unclear. We used eDNA methods to sample 233 sites in the southwestern USA and Sonora, Mexico (2016-2018) to estimate how the presence of bullfrogs affects the occurrence of four native amphibians, Bd, and ranaviruses. Based on two-species, dominant-subordinate occupancy models fitted in a Bayesian context, federally threatened Chiricahua Leopard Frogs (Rana chiricahuensis) and Western Tiger Salamanders (Ambystoma mavortium) were eight times (32% vs. 4%) and two times (36% vs. 18%), respectively, less likely to occur at sites where bullfrogs occurred. Evidence for the negative effects of bullfrogs on Lowland Leopard Frogs (Rana yavapaiensis) and Northern Leopard Frogs (Rana pipiens) was less clear, possibly because of smaller numbers of sites where these native species still occurred and because bullfrogs often occur at lower densities in streams, the primary habitat for Lowland Leopard Frogs. At the community level, Bd was most likely to occur where bullfrogs co-occurred with native amphibians, which could increase the risk to native species. Ranaviruses were estimated to occur at 33% of bullfrog-only sites, 10% of sites where bullfrogs and native amphibians co-occurred, and only 3% of sites where only native amphibians occurred. Of the 85 sites where we did not detect any of the five target amphibian species, we also did not detect Bd or ranaviruses; this suggests other hosts do not drive the distribution of these pathogens in our study area. Our results provide landscape-scale evidence that bullfrogs reduce the occurrence of native amphibians and increase the occurrence of pathogens, information that can clarify risks and aid the prioritization of conservation actions.

Linking robust spatiotemporal datasets to assess and monitor habitat attributes of a threatened species.

Accessibility of multispectral, multitemporal imagery combined with recent advances in cloud computing and machine learning approaches have enhanced our ability to model habitat characteristics across broad spatial and temporal scales. We integrated a large dataset of known nest and roost sites of a threatened species, the Mexican spotted owl (Strix occidentalis lucida), in the southwestern USA with Landsat imagery processed using the Continuous Change Detection and Classification (CCDC) time series algorithm on Google Earth Engine. We then used maximum entropy modeling (Maxent) to classify the landscape into four 'spectral similarity' classes that reflected the degree to which 30-m pixels contained a multispectral signature similar to that found at known owl nest/roost sites and mapped spectral similarity classes from 1986-2020. For map interpretation, we used nationally consistent forest inventory data to evaluate the structural and compositional characteristics of each spectral similarity class. We found a monotonic increase of structural characteristics typically associated with owl nesting and roosting over classes of increasing similarity, with the 'very similar' class meeting or exceeding published minimum desired management conditions for owl nesting and roosting. We also found an increased rate of loss of forest vegetation typical of owl nesting and roosting since the beginning of the 21st century that can be partly attributed to increased frequency and extent of large (≥400 ha) wildfires. This loss resulted in a 38% reduction over the 35-year study period in forest vegetation most similar to that used for owl nesting and roosting. Our modelling approach using cloud computing with time series of Landsat imagery provided a cost-effective tool for landscape-scale, multidecadal monitoring of vegetative components of a threatened species' habitat. Our approach could be used to monitor trends in the vegetation favored by any other species, provided that high-quality location data such as we presented here are available.