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      Buzz-Pollinated Crops: A Global Review and Meta-analysis of the Effects of Supplemental Bee Pollination in Tomato

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          Abstract

          Buzz-pollinated plants require visitation from vibration producing bee species to elicit full pollen release. Several important food crops are buzz-pollinated including tomato, eggplant, kiwi, and blueberry. Although more than half of all bee species can buzz pollinate, the most commonly deployed supplemental pollinator, Apis mellifera L. (Hymenoptera: Apidae; honey bees), cannot produce vibrations to remove pollen. Here, we provide a list of buzz-pollinated food crops and discuss the extent to which they rely on pollination by vibration-producing bees. We then use the most commonly cultivated of these crops, the tomato, Solanum lycopersicum L. (Solanales: Solanaceae), as a case study to investigate the effect of different pollination treatments on aspects of fruit quality. Following a systematic review of the literature, we statistically analyzed 71 experiments from 24 studies across different geopolitical regions and conducted a meta-analysis on a subset of 21 of these experiments. Our results show that both supplemental pollination by buzz-pollinating bees and open pollination by assemblages of bees, which include buzz pollinators, significantly increase tomato fruit weight compared to a no-pollination control. In contrast, auxin treatment, artificial mechanical vibrations, or supplemental pollination by non-buzz-pollinating bees (including Apis spp.), do not significantly increase fruit weight. Finally, we compare strategies for providing bee pollination in tomato cultivation around the globe and highlight how using buzz-pollinating bees might improve tomato yield, particularly in some geographic regions. We conclude that employing native, wild buzz pollinators can deliver important economic benefits with reduced environmental risks and increased advantages for both developed and emerging economies.

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          lmerTest Package: Tests in Linear Mixed Effects Models

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            Conducting Meta-Analyses inRwith themetaforPackage

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              Fitting Linear Mixed-Effects Models using lme4

              Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. 51 pages, including R code, and an appendix
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                Author and article information

                Contributors
                Role: Subject Editor
                Journal
                J Econ Entomol
                J Econ Entomol
                jee
                Journal of Economic Entomology
                Oxford University Press (US )
                0022-0493
                1938-291X
                April 2021
                22 February 2021
                22 February 2021
                : 114
                : 2
                : 505-519
                Affiliations
                [1 ] Department of Biological and Environmental Sciences, University of Stirling. Stirling , Scotland, UK
                [2 ] School of Natural and Environmental Sciences, Newcastle University , Newcastle upon Tyne, UK
                Author notes
                Corresponding author, e-mail: mario.vallejo@ 123456stir.ac.uk
                Author information
                https://orcid.org/0000-0001-9185-9643
                https://orcid.org/0000-0002-5663-8025
                Article
                toab009
                10.1093/jee/toab009
                8042731
                33615362
                9943466a-fb4e-471c-a3c0-c15ee0eaf40f
                © The Author(s) 2021. Published by Oxford University Press on behalf of Entomological Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 October 2020
                : 07 January 2021
                Page count
                Pages: 15
                Funding
                Funded by: Leverhulme Trust, DOI 10.13039/501100000275;
                Award ID: RPG-2018–235
                Categories
                Reviews
                AcademicSubjects/SCI01382

                agriculture,bee,buzz pollination,tomato,pollinator
                agriculture, bee, buzz pollination, tomato, pollinator

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