Tom Rodhouse | USGS Science

USGS2021

Spatial Gaussian processes improve multi-species occupancy models when range boundaries are uncertain and nonoverlapping

Species distribution models enable practitioners to analyze large datasets of encounter records and make predictions about species occurrence at unsurveyed locations. In omnibus surveys that record data on multiple species simultaneously, species ranges are often nonoverlapping and misaligned with the administrative unit defining the spatial domain of interest (e.g., a state or province). Consequently, some species display differentially restricted extents within a study area. Assuming hard boundaries based on expert opinion or published range maps to restrict species occurrence predictions implies a false sense of certainty in model-based inferences. We propose a multi-species occupancy model with a spatial Gaussian process on site-specific effects for each species as a model-based solution. Specifying informative Bayesian hyperpriors on the spatial hyperparameters encapsulates broad-scale correlation among site occupancy probabilities for each species. We fit this model to acoustic detection/nondetection data collected with autonomous recording units during summer of 2016–2019 throughout Oregon and Washington, USA, on 15 bat species. We found vast improvements in spatial predictions of spotted bat ( Euderma maculatum ), canyon bat ( Parastrellus hesperus ), and Brazilian free-tailed bat ( Tadarida brasiliensis ) when the available environmental predictors were insufficient for characterizing their restricted ranges within the region. In contrast, widespread species ( Lasionycteris noctivagans , Myotis californicus , Myotis evotis , Myotis volans ) were appropriately modeled using only environmental predictors, such as percentage forest cover and cliff and canyon cover. Utilizing spatial Gaussian processes within a community or multi-species model incorporates uncertainty in range boundaries and allows for simultaneous predictions for the entire faunal assemblage even if species have nonoverlapping or restricted ranges within a spatial domain of interest. Such modeling improvements are essential if species distribution models are to accurately inform monitoring, species recovery plans, and other conservation efforts.

Ecology and Evolution↗

USGS2020

Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance

Sagebrush steppe ecosystems are threatened by human land-use legacies, biological invasions, and altered fire and climate dynamics. Steppe protected areas are therefore of heightened conservation importance but are few and vulnerable to the same impacts broadly affecting sagebrush steppe. To address this problem, sagebrush steppe conservation science is increasingly emphasizing a focus on resilience to fire and resistance to non-native annual grass invasion as a decision framework. It is well-established that the positive feedback loop between fire and annual grass invasion is the driving process of most contemporary steppe degradation. We use a newly developed ordinal zero-augmented beta regression model fit to large-sample vegetation monitoring data from John Day Fossil Beds National Monument, USA, spanning 7 years to evaluate fire responses of two native perennial foundation bunchgrasses and two non-native invasive annual grasses in a repeatedly burned, historically grazed, and inherently low-resilient protected area. We structured our model hierarchically to support inferences about variation among ecological site types and over time after also accounting for growing-season water deficit, fine-scale topographic variation, and burn severity. We use a state-and-transition conceptual diagram and abundances of plants listed in ecological site reference conditions to formalize our hypothesis of fire-accelerated transition to ecologically novel annual grassland. Notably, big sagebrush ( Artemisia tridentata ) and other woody species were entirely removed by fire. The two perennial grasses, bluebunch wheatgrass ( Pseudoroegneria spicata ) and Thurber's needlegrass ( Achnatherum thurberianum ) exhibited fire resiliency, with no apparent trend after fire. The two annual grasses, cheatgrass ( Bromus tectorum ) and medusahead ( Taeniatherum caput-medusae ), increased in response to burn severity, most notably medusahead. Surprisingly, we found no variation in grass cover among ecological sites, suggesting fire-driven homogenization as shrubs were removed and annual grasses became dominant. We found contrasting responses among all four grass species along gradients of topography and water deficit, informative to protected-area conservation strategies. The fine-grained influence of topography was particularly important to variation in cover among species and provides a foothold for conservation in low-resilient, aridic steppe. Broadly, our study demonstrates how to operationalize resilience and resistance concepts for protected areas by integrating empirical data with conceptual and statistical models.

Oregon↗