Geology topics

Gabrielle A. Berr

Publications and source records attributed to Gabrielle A. Berr.

3 recordsLinked to original sources

USGS2025

Assessing uncertainty in forecasts of refugia for Joshua trees using high-density distribution data

Joshua trees ( Yucca brevifolia and Yucca jaegeriana ) are iconic, foundational species of the Mojave and Sonoran Deserts in North America. Due to their ecosystem importance, long generation times, and low resilience to disturbance, these hybridizing sister species are increasingly the focus of conservation efforts. Predicting Joshua tree responses to impending climate variability, along with the extent of suitable future habitat and/or climate refugia, is critical to ongoing management planning. Previous modeling efforts have been hampered by incomplete distribution data and are now out-of-date with the most recent global climate projections. We used a high-resolution, field-validated distributional database of nearly complete presence and absence records, along with a simulation of dispersal, to project Joshua tree distributions into future time periods and Coupled Model Intercomparison Project phase 6 (CMIP6) emissions scenarios. Overall, our models predict widespread habitat loss with limited availability of newly suitable habitat. Under the highest emissions scenario (SSP5–8.5), we project that up to 80% of current habitat may become unsuitable by 2100. Even so, our models predict a larger area of potential refugia than some previous efforts, particularly in the southern parts of the range, where we project persistent refugia through 2100. We also found a non-negligible influence of baseline climate period (the period used to represent “current” climate) on predicted future habitat probabilities. Simulations of dispersal based on the Joshua tree's limited capacity suggest that over 25% of suitable future habitat could be inaccessible, while much of the remaining future habitat area consists of refugia within the upper elevations of the species' current range. An increasing frequency of wildfire appears to be the greatest rangewide threat to future suitable habitat for Joshua trees, followed by renewable energy development. Over 80% of future suitable habitat occurs on federally managed lands, including up to 47% within Bureau of Land Management-administered areas and 15% within National Park Service units.

Arizona, California, Nevada, Utah↗

USGS2024

Most random-encounter-model density estimates in camera-based predator-prey studies are unreliable

Population estimates are often required for identifying relationships between predators and their prey and to inform conservation and management actions. The random encounter model (REM) estimates population density of wildlife lacking individually unique markings, based on photographs or videos from remote camera-traps. However, the REM has strict sampling and input requirements that can be problematic, particularly for predators and other species which use landscapes non-randomly. Using data from a predator and its co-occurring prey, we found that placing cameras to target the predator, which may be implemented to achieve minimum sample sizes, inflated both predator and prey density estimates. Further, borrowing movement velocity (day range) values from other studies, species, or time periods caused substantial changes in density estimates. A comprehensive literature review revealed that 91% of REM density estimates in published predator–prey studies used data from non-random cameras or borrowed movement velocities and therefore did not satisfy REM requirements. Consequently, most REM density estimates from predator–prey ecology studies are likely not of the quality or reliability necessary for informing effective wildlife conservation or management.

Nevada↗

USGS2023

Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon

Introduction: Forecasting range shifts in response to climate change requires accurate species distribution models (SDMs), particularly at the margins of species' ranges. However, most studies producing SDMs rely on sparse species occurrence datasets from herbarium records and public databases, along with random pseudoabsences. While environmental covariates used to fit SDMS are increasingly precise due to satellite data, the availability of species occurrence records is still a large source of bias in model predictions. We developed distribution models for hybridizing sister species of western and eastern Joshua trees ( Yucca brevifolia and Y. jaegeriana , respectively), iconic Mojave Desert species that are threatened by climate change and habitat loss. Methods: We conducted an intensive visual grid search of online satellite imagery for 672,043 0.25 km 2 grid cells to identify the two species' presences and absences on the landscape with exceptional resolution, and field validated 29,050 cells in 15,001 km of driving. We used the resulting presence/absence data to train SDMs for each Joshua tree species, revealing the contemporary environmental gradients (during the past 40 years) with greatest influence on the current distribution of adult trees. Results: While the environments occupied by Y. brevifolia and Y. jaegeriana were similar in total aridity, they differed with respect to seasonal precipitation and temperature ranges, suggesting the two species may have differing responses to climate change. Moreover, the species showed differing potential to occupy each other's geographic ranges: modeled potential habitat for Y. jaegeriana extends throughout the range of Y. brevifolia , while potential habitat for Y. brevifolia is not well represented within the range of Y. jaegeriana . Discussion: By reproducing the current range of the Joshua trees with high fidelity, our dataset can serve as a baseline for future research, monitoring, and management of this species, including an increased understanding of dynamics at the trailing and leading margins of the species' ranges and potential for climate refugia.

Frontiers Ecology and Evolution↗