Geology topics

Douglas A. Keinath

Publications and source records attributed to Douglas A. Keinath.

5 recordsLinked to original sources

USGS2025

When do single-species occupancy models outperform multispecies models?

Occupancy models have become increasingly popular for species monitoring and assessment, in part, because detection/non-detection data are readily obtained using a variety of methods. Multispecies occupancy models (MSOMs) can yield more accurate parameter estimates than single-species models (SSOMs) with less data through their hierarchical structure, making MSOMs an attractive option when species are hard to detect or when data collection is constrained, leading to sparse datasets. Such constraints may arise from limited sampling resources, but also occur in rare species monitoring or where preliminary results are desired to inform adaptive management. Further, experimental habitat treatments often impose spatial constraints on sampling based on the scale of their implementation. Whether a MSOM outperforms SSOMs depends on the volume of data, characteristics of the ecological community, research goals of a study and how these factors align with modeling assumptions. We performed a simulation study of hypothetical pollinator communities under varying sampling intensities for scenarios in which experimental habitat treatments produced different community-level effects. We fit occupancy models to simulated datasets and assessed model performance. At lower sampling intensities (< 20 spatial replicates and < 4 temporal replicates), MSOM community-level treatment effect estimates were biased. Even at twice this sampling intensity, SSOMs yielded more accurate species-specific effect estimates in treatment effect scenarios with high variance. In some cases, MSOMs can pull species in the tails of distributions too far toward the community mean effect, which risks incorrect conclusions concerning whether treatments help or harm individual species. When quantifying species-specific effects is the main objective, particularly for rarely observed species, SSOMs are more robust to outliers across a range of community response scenarios. Researchers can use this information to inform study design, guide simulation studies and decide whether the higher precision of MSOMs outweighs risks of improperly estimated effects for some species.

Ecology and Evolution↗

USGS2025

Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design

Bayesian hierarchical models are ubiquitous in ecology. Random effect model structures are often employed that treat individual effects as deviations from larger population-level effects. In this way individuals are assumed to be "exchangeable" samples. Ecologists may address this exchangeability assumption intuitively, but might in certain modeling contexts ignore it altogether, including in situations where it may have large implications for study design. Multispecies occupancy models based on detection/non-detection data are an approach that can be utilized by those tasked with monitoring rare and endangered species because most literature suggests that, compared to single species occupancy models, improved parameter estimates are assured. Yet, we illustrate through a power analysis how sampling requirements to detect experimental treatment effects vary tremendously depending on whether the species exchangeability assumption is met. The degree to which species in a community respond similarly to covariates governs the ability to accurately estimate parameters using multispecies occupancy models. Detecting small or moderate changes in occupancy resulting from habitat restoration treatments may be impossible for small datasets (e.g., < 36 sampling locations, each surveyed < 8 times) even with a paired treatment-control design if the exchangeability assumption is violated. By contrast, when the assumption is met, small effects may be confidently estimated with as few as 12 sampling locations (6 pairs) and 6-8 survey events. Often, it may be impossible to know whether the exchangeability assumption is met. The statistical power needed to accurately estimate species-specific effects using detection/non-detection multispecies occupancy models depends on the unknown values of treatment effects and whether responses by species in the community diverge. When the species exchangeability assumption is violated, and at lower levels of sampling effort, multispecies occupancy models may provide worse inference than single species occupancy models.

BioRxiv↗

USGS2024

Western and McKay's bumble bees occupancy trends and future projections

The Western and McKay's bumble bees, originally petitioned for listing as subspecies of the Western bumble bee (Bombus occidentalis) were previously among the most common western bumble bee species but have declined since the late 1990s (Graves et al. 2021). This report details an occupancy analysis utilizing pre-existing and newly collected bumble bee survey data to evaluate potential mechanisms associated with species trends across their distributions in western North America. In addition to evaluating spatially explicit changes in occupancy trends, we also sought to assess how widespread environmental conditions and stressors influence occupancy. Although changing climate, land cover, pesticides, and pathogens have all been identified as potential mechanisms for declines (Cameron et al. 2011, Kerr et al. 2015, Soroye et al. 2020), previous studies have not tied most climate hypotheses to bumble bee life histories or evaluated combined effects of more than 2 of these mechanisms at multi-state/ multiprovince scales. Using a scenario-based approach across climate models, emissions, and land cover scenarios, we projected future occupancy to mid-century (2050-2059). This analysis was conducted to support the Species Status Assessment (SSA) for Western and Mckay’s bumble bees being administered by the U.S. Fish & Wildlife Service (USFWS).

Report↗

USGS2023

Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides

The acute decline in global biodiversity includes not only the loss of rare species, but also the rapid collapse of common species across many different taxa. The loss of pollinating insects is of particular concern because of the ecological and economic values these species provide. The western bumble bee ( Bombus occidentalis ) was once common in western North America, but this species has become increasingly rare through much of its range. To understand potential mechanisms driving these declines, we used Bayesian occupancy models to investigate the effects of climate and land cover from 1998 to 2020, pesticide use from 2008 to 2014, and projected expected occupancy under three future scenarios. Using 14,457 surveys across 2.8 million km 2 in the western United States, we found strong negative relationships between increasing temperature and drought on occupancy and identified neonicotinoids as the pesticides of greatest negative influence across our study region. The mean predicted occupancy declined by 57% from 1998 to 2020, ranging from 15 to 83% declines across 16 ecoregions. Even under the most optimistic scenario, we found continued declines in nearly half of the ecoregions by the 2050s and mean declines of 93% under the most severe scenario across all ecoregions. This assessment underscores the tenuous future of B. occidentalis and demonstrates the scale of stressors likely contributing to rapid loss of related pollinator species throughout the globe. Scaled-up, international species-monitoring schemes and improved integration of data from formal surveys and community science will substantively improve the understanding of stressors and bumble bee population trends.

Proceedings of the National Academy of Sciences↗

USGS2018

Identifying holes in the greater sage-grouse conservation umbrella

The umbrella species concept, wherein multiple species are indirectly protected under the umbrella of a reserve created for one, is intended to enhance conservation efficiency. Although appealing in theory and common in practice, empirical tests of the concept have been scarce. We used a real-world, semi-protected reserve established to protect a high-profile umbrella species (greater sage-grouse [ Centrocercus urophasianus ]) to investigate 2 potential mechanisms underlying the concept's successful application: reserve size and species similarity. We estimated how much habitat protection the established reserve provided to 52 species of conservation concern associated with vegetation communities where greater sage-grouse occur. To illustrate the importance of reserve size, we compared the effectiveness of the established reserve to alternative greater sage-grouse reserves of various sizes and to simulated reserves of equal size but sited with no regard for greater sage-grouse. We further assessed whether key species’ traits were associated with different levels of protection under the umbrella reserve. The established umbrella reserve protected 82% of the state's greater sage-grouse population and 0–63% of the habitat of the background species examined. The reserve outperformed equally sized, simulated reserves for only 12 of 52 background species. As expected, larger alternative reserves served as better umbrellas, but regardless of reserve size, not all species received equal protection. The established reserve was most effective at protecting the habitat of species that were most similar to the umbrella species (i.e., avian species, those highly associated with sagebrush plant communities, and those with widespread habitat). In contrast, the habitat of species with restricted distributions, particularly when combined with vegetation associations not closely matching the umbrella species, was not protected as well by the umbrella reserve. Such species require additional, targeted attention to achieve conservation objectives. Successful application of the umbrella species concept requires careful consideration of the characteristics of the umbrella species, the reserve delineated on its behalf, and the similarity of the umbrella species to its purported background species.

Wyoming↗