Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed-area net surveys (“net counts”) and fixed-width transect counts (“transect counts”) at 47 early-successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey- and site-covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non-detection data collected via point-counts, line-transects and distance sampling for Bombus spp. are unlikely to yield species-specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators.
|Number of pages||11|
|Journal||Journal of Applied Entomology|
|State||Published - Apr 2019|
Bibliographical noteFunding Information:
We thank the following individuals and agencies for their support and land access: Sproul State Forest and Moshannon State Forest. Funding was provided by the Indiana University of Pennsylvania BURE fund and the United States Department of Agriculture Natural Resources Conservation Service (68-7482-12-502), through the Conservation Effects Assessment Project. We are very grateful to Joan Milam and Sam Droege for their comments on early versions of this manuscript. We are also very grateful to three anonymous reviewers spend considerable time strengthening this manuscript. Funders of our project did not have any influence on the content of the submitted manuscript nor did they require approval of the final manuscript to be published. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
We thank the following individuals and agencies for their support and land access: Sproul State Forest and Moshannon State Forest. Funding was provided by the Indiana University of Pennsylvania BURE fund and the United States Department of Agriculture Natural Resources Conservation Service (68‐7482‐12‐502), through the Conservation Effects Assessment Project. We are very grateful to Joan Milam and Sam Droege for their comments on early versions
© 2018 Blackwell Verlag GmbH
- detection probability
- distance modelling
ASJC Scopus subject areas
- Agronomy and Crop Science
- Insect Science