Biology subjects

Danforth, B. N.

Publications and source records attributed to Danforth, B. N..

3 recordsLinked to original sources

bioRxiv2024

Fine-Scale Models of Bee Species Diversity and Habitat in New York State

Anthropogenic drivers of global change threaten bee diversity and the ecosystem services bees provide. Despite their importance, the conservation of bee pollinators is complicated by limited and often heavily biased occurrence data. A recent state-wide survey of insect pollinators across New York, United States generated a large spatial dataset of bee species occurrence records from community scientists, historical collections, and survey efforts. Using a combination of the state survey records with occurrence data from across the contiguous United States, we applied an ensemble modeling approach using balanced random forest and small bivariate generalized linear models to predict the distributions of most of the states bee species. We predicted the spatial distribution of bee species richness using a stacked species distribution model with climate, land cover, and soil covariates. To inform bee diversity conservation, we predicted spatial variation for each species and groups of species sharing similar life history traits. We also estimated statewide distribution of range-size rarity, ecological uniqueness, and climate exposure. We found that the richness of modeled species is high across the state, with the greatest richness in regions with low soil clay content and intermediate forest cover. The fine spatial scale and extent of our gridded data layers match the scale of conservation action in the state, providing an opportunity to incorporate wild bee diversity into broader statewide conservation planning. Conserving New York States bee pollinators is not straightforward, and decisions should be based on broader conservation priorities that incorporate bee biodiversity indicators into decision-making. Here, we encourage the inclusion of these vital pollinators in conservation decisions by leveraging the best available data and methods robust to small sample sizes to provide spatially explicit data products representing the distribution of bee diversity across the state of New York.

ecology↗

bioRxiv2024

Forecasting the Effects of Global Change on a Bee Biodiversity Hotspot

The Mojave and Sonoran Deserts, recognized as a global hotspot for bee biodiversity, are experiencing habitat degradation from urbanization, utility-scale solar energy (USSE) development, and climate change. In this study, we evaluated the current and future distribution of bee diversity in the region, assessed how protected areas safeguard bee species richness, and predicted how global change may affect bees across the region. Using Joint Species Distribution Models (JSDMs) of 148 bee species, we project changes in species distributions, occurrence area, and richness across the region under four global change scenarios between 1971 and 2050. We evaluated the threat posed by USSE development and predicted how climate change will affect the suitability of protected areas for conservation. Our findings indicate that changes in temperature and precipitation do not uniformly affect bee richness across the region. Protected areas in the Sonoran and Mojave Deserts are projected to experience mean losses of up to 5.8 species, whereas protected areas at higher elevations and transition zones may gain up to 7.8 species. Outside protected areas, bee diversity is threatened by urbanization and USSE development. Areas prioritized for future USSE development have an average species richness of 4.2 species higher than the study area average, and lower priority areas have 8.2 more species. USSE zones are expected to experience declines of 2.7 to 8.0 species by 2050 due to climate change alone. Despite the importance of solitary bees for pollination, their diversity is often overlooked in land management decisions. Our results show the utility of JSDMs for extending the usability of existing data-limited bee species records, easing the inclusion of these species in conservation and land management decision-making. The multiple threats from global change drivers underscore the importance of including ecologically vital, though often data-limited, species in land-use decisions.

ecology↗

bioRxiv2023

Advancing bee conservation in the US: gaps and opportunities in data collection and reporting

Bee conservation in the U.S. is currently hindered by challenges associated with assessing the status and trends of a diverse group of >3000 species, many of which are rare, endemic to small areas, and/or exhibit high inter-annual variation in population size. Fundamental information about the distribution of most species across space and time, thus, is lacking yet urgently needed to assess population status, guide conservation plans, and prioritize actions among species and geographies. Using wild bee data from two public data repositories representing the contiguous U.S., we evaluated the availability and sufficiency of data for use in species assessments of wild bees. We also examined the number of bee species recorded in each U.S. state and the proportion of species with recent records (2012-2021). Although efforts to monitor bees continue to grow, there remains a massive paucity of data. Exceedingly few records (0.04%) reported both sampling protocol and effort, greatly limiting the usefulness of the data. Few species or locations have adequate publicly available data to support analyses of population status or trends, and fewer than half of species have sufficient data to delineate geographic range. Despite an exponential increase in data submissions since the 2000s, only 47% of species were reported within the last decade, which may be driven by how data are collected, reported, and shared, or may reflect troubling patterns of local or large-scale declines and extirpations. Based on our analysis, we provide recommendations to improve the quality and quantity of data that can be used to detect, understand, and respond to changes in wild bee populations.

ecology↗