Increasing parameter accuracy of an agriculturally focused, spatially-explicit bee abundance model

Increasing parameter accuracy of an agriculturally focused, spatially-explicit bee abundance model

Summary

Efforts to promote native bee habitat around lowbush blueberry fields in Maine may be more effective if native bee abundance in the landscape surrounding these fields could be predicted accurately. The InVEST Crop Pollination Model is a spatially-explicit model that uses land cover data to predict bee abundance in crop and non-crop cover types in agricultural landscapes. Application of this model requires bee habitat suitability scores that are typically informed by expert knowledge.  Uncertainty that results from expert-derived scores potentially affects model prediction accuracy.  My proposed research will use field surveys to quantify bee communities in non-crop land cover types in Maine’s lowbush blueberry growing regions.  I hypothesize that field data-derived parameters will improve accuracy of model-predicted bee abundance compared to accuracy of expert opinion-derived parameters. This research will be the first comparison of expert opinion and bee community data from non-focal crops used to parameterize the InVEST Crop Pollination model. The information gained from this research will also be applied in a tool developed for lowbush blueberry growers to predict native bee abundance in their crop fields.

Objectives/Performance Targets

Objective 1: Quantify bee community richness and abundance in non-blueberry cover types throughout Maine’s lowbush blueberry growing region.

Collaborator Frank Drummond collected bees in eight non-blueberry cover types throughout Summer 2014. Those bees are being identified and will be used to inform future field surveys and early model runs for Objective 2 to be completed in 2015.

Objective 2: Compare predicted bee abundance from a spatially-explicit bee abundance model informed by expert opinion to abundance informed by bee community field data.

I intend to collect bees through field surveys in the summers of 2015 and 2016, guided by F. Drummond’s surveys in 2014, to inform the model. Work on this objective will begin in fall 2015.

Objective 3: Develop a pollination tool for lowbush blueberry growers that presents information on native bee communities in and around crop fields, including an estimate of pollination service on their crop fields

We are using current output of the InVEST model based solely on expert opinion to develop a web based landscape visualization tool using participatory modeling techniques. The tool will be made available through the UMaine Cooperative Extension website; the InVEST model output is displayed over a background of Google Maps-style aerial photography. I presented an early version of the tool in November 2014 to wild blueberry growers for their feedback, which largely was positive. We are refining the tool and seeking further feedback from wild blueberry growers throughout winter 2015 through multiple forums: 1:1 meetings, small group workshops, and large group workshops. The tool is expected to be finished in summer 2015 and will be updated with model output informed by field-collected data in winter 2016.

Accomplishments/Milestones

In June 2014, work began on the web tool. We received additional funding from the University of Maine Sustainability Solutions Initiative to support participatory development of the web tool; this complements the ecological development of the tool funded by NESARE and will make the finished tool more relevant to its intended audience, the wild blueberry growers. We accelerated our plan for beginning this work owing to interest from the grower community and project collaborators in soliciting and providing feedback during early stages of tool development. As such, we are informing the tool initially by expert opinion, and we will finalize the tool (expected finish date: Summer 2015) with information learned from field-collected data during 2015 (with future revisions as data are available).

In summer 2014, Frank Drummond conducted preliminary field surveys in eight non-blueberry cover types. Many bees were collected and are pending identification for further analysis, which will inform field surveys in 2015 and 2016.

Impacts and Contributions/Outcomes

In November 2014, I presented an early version of the web-based tool to the advisory board of the Wild Blueberry Commission of Maine, which includes growers, researchers, and lobbyists. Feedback was largely positive: growers are interested in mapping techniques and are excited to learn about pollinator communities around their blueberry fields.

Growers recognize the importance of pollinators, especially wild bees, however, they lack information needed to assess bee communities where they reside in the area around their blueberry fields. The web tool will promote agricultural sustainability by estimating for growers the potential abundance of bees in habitats around their fields; this information will demonstrate the connection between land cover type and bee abundance, and provide access to Cooperative Extension information describing techniques for enhancing and conserving pollinator communities. Additionally, field-collected data will more accurately inform the predictive accuracy of the InVEST Crop Pollination Model applied on wild blueberry fields in Maine. Ultimately, this information will encourage growers to pursue pollinator conservation practices by applying the web tool.

In December 2014, I presented a poster describing the development of the web tool at the Maine State EPSCoR Conference, a meeting focused on sustainable practices in future development and resource use.

Du Clos, B., Hanes, S.P., Loftin, C.S., and F.A. Drummond. A landscape-level pollinator habitat assessment tool for wild blueberry growers. Wild Blueberry Commission Advisory Board Meeting, 11/2014. Brunswick, ME. Oral.

Du Clos, B., Hanes, S.P., Loftin, C.S., and F.A. Drummond. A web-based tool for grower assessment of native bee abundance in the wild blueberry production landscape. Maine EPSCoR State Conference. 12/2014. Orono, ME. Poster.

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