Estimate Pollination Potential with ESTIMAP Jörg Priess OpenNESS-CANA Minisymposium, Analandia, 2015-06-23

INTRODUCTION – Pollination Service Pollination by insects is an important ecosystem service, as many crops and fruits rely on or benefit from it [1]. (regional examples: coffee, fruits, vegetables) Loss of insect pollinators has been observed in different regions around the globe as a result of habitat loss and agricultural intensification. The impact assessment of recent land-use changes as well possible future developments on insect pollination (-potential) is therefore of high interest for different stakeholders, such as farmers and policy-makers [2]. Using the ESTIMAP approach [3] we aim at assessing these impacts for the Rio Claro region for recent and possible future land-use changes. [1] Klein et al. 2007. Importance of pollinators in changing landscapes for world crops. Proceedings of the Royal Society B: Biological Sciences 274, 303–313. [2] Zulian, G., Maes, J., Paracchini, M., 2013. Linking Land Cover Data and Crop Yields for Mapping and Assessment of Pollination Services in Europe. Land 2, 472–492. [3] Zulian, et al., 2013. ESTIMAP: ecosystem services mapping at European scale. Publications Office, Luxembourg.

Method - ESTIMAP ESTIMAP structure modified from [3] ESTIMAP approach to estimate the relative pollinator abundance based on land-use / land-cover specific nesting and foraging scores combined with species-specific flight distances Habitat and floral scores adapted from ESTIMAP and adjusted for land-use classes considered in Rio Claro Focus on wild bees as pollinators Typical maximum flight distances taken from studies conducted in the region Spatial resolution: to be decided ESTIMAP structure modified from [3]

Method – ESTIMAP 2 Floral Availability and Nesting Sites (borrowed from Germany)

Method – ESTIMAP 3 Strong influence of single factors on RPP (from Central Germany) left: flight distances of Ricketts et al. right: flight distances of Zulian et al.

Method – ESTIMAP 4 Strong influence of single factors on RPP (from Central Germany) left: Activity pattern based on °C of 2050 right: RPP based on left

ESTIMAP – Results (from Saxony) Results highly sensitive to temperature & max flight distance Other parameters such as road-side vegetation show clear but less strong impact on RPP (see figure below) Urgently needed: Model Validation So far only nice maps!  Relevance?

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