The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality

Sáez, A., Morales, J. M. , Morales, C. L., Harder, L. D. and Aizen, M. A. (2018) The costs and benefits of pollinator dependence: empirically based simulations predict raspberry fruit quality. Ecological Applications, 28(5), pp. 1215-1222. (doi: 10.1002/eap.1720) (PMID:29575300)

Abstract

Globally, agriculture increasingly depends on pollinators to produce many seed and fruit crops. However, what constitutes optimal pollination service for pollinator-dependent crops remains unanswered. We developed a simulation model to identify the optimal pollination service that maximizes fruit quality in crops. The model depicts the pollination (i.e., autonomous self-fertilization, pollen deposition) and post-pollination (i.e., pollen germination, and time from germination to ovule fertilization) processes leading to fruit and seed set and allows for negative flower–pollinator interactions, specifically pistil damage. We parameterized and validated the model based on empirical observations of commercial raspberry in western Argentina. To assess the effects of pollination intensity for fruit production, we conducted simulations over a range of visit number per flower by the two primary managed pollinators worldwide, Apis mellifera and Bombus terrestris. Simulations identified that ~15–35 visits per flower by A. mellifera or ~10–20 visits by B. terrestris provide adequate pollination and maximize raspberry fruit quality (i.e., estimated as the proportion of ovules that develop into drupelets). Visits in excess of these optima reduce simulated fruit quality, and flowers receiving >670 honey bee visits or >470 bumble bee visits would produce fruits of poorer quality than those receiving no bee visits. The simulations generated consistent, unbiased predictions of fruit quality for 12 raspberry fields. This model could be adapted easily to other animal-pollinated crops and used to guide efficient pollinator management in any agro-ecosystem.

• Item Type: Articles
• Additional Information: Research Funding: National Research Council of Argentina CONICET Argentine National Fund of Research. Grant Numbers: PICT 2012-3015, PICT 2015-2333 Natural Sciences and Engineering Research Council of Canada. Grant Number: RGPIN/107375-2012
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Morales, Professor Juan
• Authors: Sáez, A., Morales, J. M., Morales, C. L., Harder, L. D., and Aizen, M. A.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: Ecological Applications
• Publisher: Wiley
• ISSN: 1051-0761
• ISSN (Online): 1939-5582
• Published Online: 24 March 2018