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Updated: Jun 24, 2026
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Field Experiments of Pollination Ecology: The Case of Lycoris sanguinea var. sanguinea
Published on: November 25, 2016
Modelling pollination services across agricultural landscapes.
Eric Lonsdorf1, Claire Kremen, Taylor Ricketts
1Conservation and Science Dept, Lincoln Park Zoo, Chicago, IL 60614, USA. ericlonsdorf@lpzoo.org
Annals of Botany
|March 28, 2009
Summary
A new model predicts pollinator abundance using landscape data, showing promise for crop pollination. Further research is needed to refine predictions by including fine-scale floral and nesting resources.
Area of Science:
- Ecology
- Conservation Biology
- Agricultural Science
Background:
- Pollination by animals is a vital ecosystem service for crop production.
- Understanding landscape contributions to pollinator health is crucial for maintaining this service.
- Quantitative models are needed to assess and manage pollinator populations.
Purpose of the Study:
- To describe and test the first quantitative model predicting pollinator abundance on a landscape.
- To evaluate the model's accuracy using data from diverse agricultural regions.
- To identify factors influencing model performance and guide future improvements.
Main Methods:
- The model integrates data on pollinator nesting and floral resources, and foraging distances.
- It predicts relative pollinator abundance in nesting habitats and on farms.
- Model outputs were validated against field data from coffee, sunflower, and watermelon crops in Costa Rica and the USA.
Main Results:
- The model successfully explained up to 80% of variance in pollinator abundance in Costa Rica and California.
- Predictions for pollinator abundance in the New Jersey-Pennsylvania (NJPA) region were less accurate.
- Model performance in NJPA may be limited by the exclusion of fine-scale landscape resources.
Conclusions:
- Model sensitivity analyses highlight the critical role of fine-scale nesting and floral resources.
- The developed model offers a quantitative framework for evaluating policy and land-use planning for pollination conservation.
- Further research focusing on finer-scale resource assessments is recommended for enhanced predictive accuracy.
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