Geology topics

Eve Bohnett

Publications and source records attributed to Eve Bohnett.

3 recordsLinked to original sources

USGS2025

Assessing survey design for long-term population trend detection in piping plovers

Determining appropriate spatio-temporal scales for monitoring migratory shorebirds is challenging. Effective surveys must detect population trends without excessive or insufficient sampling, yet many programs lack formal evaluations of survey effectiveness. Using data from 2012 to 2019 on Louisiana’s barrier islands (Whiskey, west Raccoon, east Raccoon, and Trinity), we assessed how spatial and temporal scales influence population trend inference for piping plovers ( Charadrius melodus ). Point count data were aggregated to grid sizes from 50 to 200 m and analyzed using Bayesian dynamic occupancy models. We found occupancy and colonization estimates varied by spatial resolution, with space–time autocorrelation common across scales. Smaller islands (east and west Raccoon) yielded higher trend detection power due to better detectability, while larger islands (Trinity and Whiskey) showed lower power. Detectability, more than sampling frequency, drove trend inference. Models incorporating spatial autocorrelation outperformed traditional Frequentist approaches but showed poorer fit at coarser scales. These findings underscore how matching analytical scale to ecological processes and selecting appropriate models can influence predictions. Power analysis revealed that increasing survey frequency may improve inference, especially in low-detectability areas. Overall, our study highlights how careful scale selection, model diagnostics, and survey design can enhance monitoring efficiency and support long-term conservation of migratory shorebirds.

Louisiana↗

USGS2023

Shorebird monitoring using spatially explicit occupancy and abundance

Loss of habitat and human disturbance are major factors in the worldwide decline of shorebird populations, including that of the threatened migratory piping plover ( Charadrius melodus ). From 2013 to 2018, we conducted land-based surveys of the shorebird community every other week during the peak piping plover season (September to March). We assessed the ability of a thin plate spline occupancy model to identify hotspot locations on Whiskey Island, Louisiana, for the piping plover and four additional shorebird species (Wilson’s plover ( Charadrius wilsonia ), snowy plover ( Charadrius nivosus ), American oystercatcher ( Haematopus palliatus ), and red knot ( Calidris canutus )). By fitting single-species occupancy models with geographic thin plate spline parameters, hotspot priority regions for conserving piping plovers and the multispecies shorebird assemblage were identified on the island. The occupancy environmental covariate, distance to the coastline, was weakly fitting, where the spatially explicit models were heavily dependent on the spatial spline parameter for distribution estimation. Additionally, the detectability parameters for Julian date and tide stage affected model estimations, resulting in seemingly inflated estimates compared to assuming perfect detection. The models predicted species distributions, biodiversity, high-use habitats for conservation, and multispecies conservation areas using a thin-plate spline for spatially explicit estimation without significant landscape variables, demonstrating the applicability of this modeling approach for defining areas on a landscape that are more heavily used by a species or multiple species.

Louisiana↗

USGS2022

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle ( Glyptemys insculpta ) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λ mean = 0.952, 95% CI: 0.87–1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

Journal of Environmental Management↗