Parameterization of the InVEST Crop Pollination Model to spatially predict abundance of wild blueberry (Vaccinium angustifolium Aiton) native bee pollinators in Maine, USA
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- 作者：Shannon C. Groffa ; scgroff@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Cynthia S. Loftinb ; cynthia.loftin@maine.edu" class="auth_mail" title="E-mail the corresponding author ; Frank Drummondc ; Frank_Drummond@umit.maine.edu" class="auth_mail" title="E-mail the corresponding author ; Sara Bushmannc ; sara.bushmann@maine.edu" class="auth_mail" title="E-mail the corresponding author ; Brian McGillc ; brian.mcgill@maine.edu" class="auth_mail" title="E-mail the corresponding author
- 关键词：Bee community ; Prediction ; Model ; Maine ; Blueberry ; Landscape ; Expert
- 刊名：Environmental Modelling & Software
- 出版年：2016
- 出版时间：May 2016
- 年：2016
- 卷：79
- 期：Complete
- 页码：1-9
- 全文大小：614 K
文摘
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The expert opinion-informed InVEST model was less reliable than the sensitivity analyses-informed model.
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Proportion of deciduous/mixed forest within 2000 m also predicted within-field bee abundance.
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InVEST provides reliable bee abundance predictions at the landscape extent in Maine.