A hierarchical framework for mapping pollination ecosystem service potential at the local scale

verfasst von

Marie Perennes, Tim Diekötter, Jens Groß, Benjamin Burkhard

Abstract

Wild bees play a major role in the cultivation of crops for human use, in the reproduction of many wild plants and are a key component of biodiversity. Mainly due to human activities, wild bees, like other insects, face a rapid decline in Europe. Understanding species distribution can help to design efficient conservation measures. Species distribution can also be used to estimate pollination ecosystem service potential, which can benefit the production of crops relying on pollination and the reproduction of wild plant communities. The presence of pollinators depends on a combination of environmental and biotic factors, each playing a determining role at different spatial scales. We therefore developed a model composed as a hierarchical framework for environmental predictors: climatic data and Land Use/Land Cover (LULC) variables at the European scale and species-specific habitat information at the local scale. The model combines the advantages of two different existing approaches: pollinator species distribution predictions based on their environmental requirements and knowledge on bee species life-history traits and habitats. This paper presents the predicted distribution of twenty-five wild bee species of the Andrena genus in an agricultural region in Northern Germany. We used oilseed rape pollinators as a case study and compared the potential pollination services to the potential demand in the Case Study Area. The developed framework allows to determine the capacity of landscapes to support pollination ecosystem services from wild bees at the local scale, which can support the identification of vulnerable areas and the design of local scale measures for habitat improvement and for conservation. The hierarchical approach leaves potential for further adaptations in order to improve the prediction of wild bee species dynamics and factors influencing their spatial distribution.

Organisationseinheit(en)

Institut für Physische Geographie und Landschaftsökologie
Arbeitsgruppe Physische Geographie

Externe Organisation(en)

Christian-Albrechts-Universität zu Kiel (CAU)
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.

Typ

Artikel

Journal

Ecological Modelling

Band

444

ISSN

0304-3800

Publikationsdatum

15.03.2021

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Ökologische Modellierung

Ziele für nachhaltige Entwicklung

SDG 15 – Lebensraum Land

Elektronische Version(en)

https://doi.org/10.1016/j.ecolmodel.2021.109484 (Zugang: Offen)