Modeling local spatial patterns of wild bee diversity in Pennsylvania apple orchards
The positive correlation between landscape area of semi-natural habitat and wild pollinator richness and abundance in agroecosystems has been well studied. However, we lack a deep understanding of local scale floral resource and nest provisioning for wild bees necessary to optimize implementation of pollinator conservation practices.
The primary objective of this study was to use a spatially interactive landscape pollination model (hereafter, the Lonsdorf model) to represent field scale spatial patterns of wild bee abundance and richness within a heterogeneous landscape in the mid-Atlantic USA.
We parameterized the Lonsdorf model with high resolution aerial imagery and insight from a previously published floristic study. To test the Lonsdorf model predictions, field studies were conducted to measure wild bee abundance and species richness in apple orchards as a function of distance from a forest edge.
Field measurements indicated apple pollinator abundance and species richness significantly decreased with increasing distance from the forest edge. The Lonsdorf model pollination service score was highly sensitive to changes in resource provisioning in orchard and non-crop areas, and including resource rich forest and forest edge habitats in the model significantly improved pollination service estimates.
We demonstrated a novel application of the Lonsdorf model at a field scale to predict trends in pollination service provisioning as a factor of local habitat features. With sufficiently detailed inputs, the Lonsdorf model is a promising tool to quantify field scale pollination service deficits, guiding more cost effective habitat supplementation and other conservation efforts.
KeywordsForest edge Lonsdorf model Malus domestica Pollination Spatial modeling Wild bees
We would like to thank Amanda Ritz, Dr. Katie Ellis, Kathy Wholaver, Lot Miller, and Edwin Winzeler at the Penn State University Fruit Research and Extension Center for field and lab work; David & Steve Slaybaugh, Scott Slaybaugh, Eddie Diveley Jr., and Brian Knouse the participating growers in the study; Leo R. Donovall, Sam Droege, and Dr. Jason Gibbs for bee identification; Dr. Ottar Bjornstad for statistical assistance, and Dr. Eric Lonsdorf for suggestions on model implementation, and two anonymous reviewers for very helpful manuscript feedback. This research was funded by the United States Department of Agriculture Specialty Crops Research Initiative (USDA-SCRI) grant PEN04398, USDA-SCRI Coordinated Agricultural Project grant MICL05063, and the State Horticultural Association of Pennsylvania.
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