A ‘Landscape physiology’ approach for assessing bee health highlights the benefits of floral landscape enrichment and semi-natural habitats View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-01-13

AUTHORS

Cédric Alaux, Fabrice Allier, Axel Decourtye, Jean-François Odoux, Thierry Tamic, Mélanie Chabirand, Estelle Delestra, Florent Decugis, Yves Le Conte, Mickaël Henry

ABSTRACT

Understanding how anthropogenic landscape alteration affects populations of ecologically- and economically-important insect pollinators has never been more pressing. In this context, the assessment of landscape quality typically relies on spatial distribution studies, but, whether habitat-restoration techniques actually improve the health of targeted pollinator populations remains obscure. This gap could be filled by a comprehensive understanding of how gradients of landscape quality influence pollinator physiology. We therefore used this approach for honey bees (Apis mellifera) to test whether landscape patterns can shape bee health. We focused on the pre-wintering period since abnormally high winter colony losses have often been observed. By exposing colonies to different landscapes, enriched in melliferous catch crops and surrounded by semi-natural habitats, we found that bee physiology (i.e. fat body mass and level of vitellogenin) was significantly improved by the presence of flowering catch crops. Catch crop presence was associated with a significant increase in pollen diet diversity. The influence of semi-natural habitats on bee health was even stronger. Vitellogenin level was in turn significantly linked to higher overwintering survival. Therefore, our experimental study, combining landscape ecology and bee physiology, offers an exciting proof-of-concept for directly identifying stressful or suitable landscapes and promoting efficient pollinator conservation. More... »

PAGES

40568

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep40568

DOI

http://dx.doi.org/10.1038/srep40568

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020854820

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28084452


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