Dataset Information

Bee pollination outperforms pesticides for oilseed crop production and profitability.

ABSTRACT: Nature-based agriculture that reduces dependency on chemical inputs requires using ecological principles for sustainable agro-ecosystems, aiming to balance ecology, economics and social justice. There is growing evidence that pollinator-dependent crops with high insect, particularly bee, pollination service can give higher yields. However, the interacting effects between insect pollination and agricultural inputs on crop yields and farm economics remain to be established to reconcile food production with biodiversity conservation. We quantified individual and combined effects of pesticides, insect pollination and soil quality on oilseed rape (Brassica napus L.) yield and gross margin, using a total of 294 farmers' fields surveyed between 2013 and 2016. We show that yield and gross margins are greater (15-40%) in fields with higher pollinator abundance than in fields with reduced pollinator abundance. This effect is, however, strongly reduced by pesticide use. Greater yields may be achieved by either increasing agrochemicals or increasing bee abundance, but crop economic returns were only increased by the latter, because pesticides did not increase yields while their costs reduced gross margins.

SUBMITTER: Catarino R

PROVIDER: S-EPMC6790783 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Bee pollination outperforms pesticides for oilseed crop production and profitability.

Catarino Rui R Bretagnolle Vincent V Perrot Thomas T Vialloux Fabien F Gaba Sabrina S

Proceedings. Biological sciences 20191009 1912

Nature-based agriculture that reduces dependency on chemical inputs requires using ecological principles for sustainable agro-ecosystems, aiming to balance ecology, economics and social justice. There is growing evidence that pollinator-dependent crops with high insect, particularly bee, pollination service can give higher yields. However, the interacting effects between insect pollination and agricultural inputs on crop yields and farm economics remain to be established to reconcile food produc ...[more]

PMID: 31594515

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Project description:Insect pollinators provide an essential ecosystem service by transferring pollen to crops and native vegetation. The extent to which pollinator communities vary both spatially and temporally has important implications for ecology, conservation and agricultural production. However, understanding the complex interactions that determine pollination service provisioning and production measures over space and time has remained a major challenge. Remote sensing technologies (RST), including satellite, airborne and ground based sensors, are effective tools for measuring the spatial and temporal variability of vegetation health, diversity and productivity within natural and modified systems. Yet while there are synergies between remote sensing science, pollination ecology and agricultural production, research communities have only recently begun to actively connect these research areas. Here, we review the utility of RST in advancing crop pollination research and highlight knowledge gaps and future research priorities. We found that RST are currently used across many different research fields to assess changes in plant health and production (agricultural production) and to monitor and evaluate changes in biodiversity across multiple landscape types (ecology and conservation). In crop pollination research, the use of RST are limited and largely restricted to quantifying remnant habitat use by pollinators by ascertaining the proportion of, and/or isolation from, a given land use type or local variable. Synchronization between research fields is essential to better understand the spatial and temporal variability in pollinator dependent crop production. RST enable these applications to be scaled across much larger areas than is possible with field-based methods and will facilitate large scale ecological changes to be detected and monitored. We advocate greater use of RST to better understand interactions between pollination, plant health and yield spatial variation in pollinator dependent crops. This more holistic approach is necessary for decision-makers to improve strategies toward managing multiple land use types and ecosystem services.

Project description:Multiple interacting factors drive recent declines in wild and managed bees, threatening their pollination services. Widespread and intensive monitoring could lead to more effective management of wild and managed bees. However, tracking their dynamic populations is costly. We tested the effectiveness of an inexpensive, noninvasive and passive acoustic survey technique for monitoring bumble bee behavior and pollination services. First, we assessed the relationship between the first harmonic of the flight buzz (characteristic frequency) and pollinator functional traits that influence pollination success using flight cage experiments and a literature search. We analyzed passive acoustic survey data from three locations on Pennsylvania Mountain, Colorado to estimate bumble bee activity. We developed an algorithm based on Computational Auditory Scene Analysis that identified and quantified the number of buzzes recorded in each location. We then compared visual and acoustic estimates of bumble bee activity. Using pollinator exclusion experiments, we tested the power of buzz density to predict pollination services at the landscape scale for two bumble bee pollinated alpine forbs (Trifolium dasyphyllum and T. parryi). We found that the characteristic frequency was correlated with traits known to affect pollination efficacy, explaining 30-52% of variation in body size and tongue length. Buzz density was highly correlated with visual estimates of bumble bee density (r = 0.97), indicating that acoustic signals are predictive of bumble bee activity. Buzz density predicted seed set in two alpine forbs when bumble bees were permitted access to the flowers, but not when they were excluded from visiting. Our results indicate that acoustic signatures of flight can be deciphered to monitor bee activity and pollination services to bumble bee pollinated plants. We propose that applications of this technique could assist scientists and farmers in rapidly detecting and responding to bee population declines.

Dataset Information

Bee pollination outperforms pesticides for oilseed crop production and profitability.

Publications

Bee pollination outperforms pesticides for oilseed crop production and profitability.

Similar Datasets

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