1. Estimate Pollination Potential with ESTIMAP
Jörg Priess
OpenNESS-CANA Minisymposium, Analandia,

2. 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 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., Linking Land Cover Data and Crop Yields for Mapping and Assessment of Pollination Services in Europe. Land 2, 472–492. [3] Zulian, et al., ESTIMAP: ecosystem services mapping at European scale. Publications Office, Luxembourg.

3. 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]

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

5. 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.

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

7. 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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SEITE 8
© J. Priess