DOI: 10.5061/dryad.qfttdz0hm
title: Negative impacts of dominance on bee communities: Does the influence of invasive honey bees differ from native bees?

description: Invasive species can reach high abundances and dominate native
 environments. One of the most impressive examples of ecological invasions
 is the spread of the African sub-species of the honey bee throughout the
 Americas, starting from its introduction in a single locality in Brazil.
 The invasive honey bee is expected to more negatively impact bee community
 abundance and diversity than native dominant species, but this has not
 been tested previously. We developed a comprehensive and systematic bee
 sampling scheme, using a protocol deploying 11,520 pan traps across
 regions and crops for three years in Brazil. We found that invasive honey
 bees are now the single most dominant bee species. Such dominance has not
 only negative consequences for abundance and species richness of native
 bees but also for overall bee abundance (i.e., strong “numerical” effects
 of honey bees). Contrary to expectations, honey bees did not have stronger
 negative impacts than other native bees achieving similar levels of
 dominance (i.e., lack of negative “identity” effects of honey bees). These
 effects were remarkably consistent across crop species, seasons and years,
 and were independent from land-use effects. Dominance could be a proxy of
 bee community degradation and more generally of the severity of ecological
 invasions.
description: (1) GENERAL INFORMATION (1.1) Author
 Information     A. Principal Investigator Contact
 Information<br>         Name: Lucas Garibaldi<br>       
  Institution: Instituto de Investigaciones en Recursos Naturales,
 Agroecología y Desarrollo Rural (IRNAD)<br>         Address: Mitre
 630, CP 8400, San Carlos de Bariloche, Río Negro, Argentina.<br>   
      Email:lgaribaldi@unrn.edu.ar     B. Associate or
 Co-investigator Contact Information<br>         Name: Guaraci Duran
 Cordeiro<br>         Institution: University of Salzburg. Department
 of Biosciences<br>         Address: Hellbrunnerstr. 34, 5020,
 Salzburg, Austria<br>         Email: guaradc@gmail.com
   (1.2) Date of data collection: 2010-08-19 -
 2014-05-28   (1.3) Geographic
 location of data collection: Brazilian States - Amazonas, Bahia, Ceará,
 Goiás, Mato Grosso, Pará, Paraiba, Rio de Janeiro, Rio Grande do Sul
     (1.4) Information about funding
 sources that supported the collection of the data: This Project was
 supported by the Global Environment Fund (GEF) and coordinated globally by
 the United Nations Food and Agriculture Organization (FAO), with support
 from the United Nations Environment Programme (UNEP). In Brazil it was
 coordinated by the Ministry of the Environment (MMA), with support of the
 Brazilian Fund for Biodiversity (FUNBIO). We also appreciate funding from
 Agencia Nacional de Promoción Científica y Tecnológica (PICT 2015-2333,
 PICT-2018-00941), Universidad Nacional de Río Negro (PI 40-B-567),
 Conselho Nacional de Desenvolvimento Científico e Tecnológico
 (305062/2007-7, 556042/2009-3, 556406/2009-5, 305836/2012-9,
 304689/2015-7, 303894/2018-0, 556616/2019-0 and 308358/2019-8), Fundação
 de Amparo à Pesquisa do Estado do Rio de Janeiro (203.321/2017), and the
 2017-2018 Belmont Forum and BiodivERsA joint call for research proposals
 (under the BiodivScen ERA-Net COFUND programme and with the funding
 organisations AEI, NWO, ECCyT and NSF.  
 (2) METHODOLOGICAL INFORMATION (2.1)
 Description of methods used for collection/generation of data: Bee
 sampling followed the protocol in LeBuhn et al. (2016). At each site, one
 plot with 15 pan traps (they were made from 150 ml plastic white bowls of
 9 cm diameter painted fluorescent blue, fluorescent yellow or left
 unpainted [white] and filled with soapy water) was deployed within the
 crop and another plot with 15 pan traps adjacent in the surrounding
 area LeBuhn, G., S. Droege, E. Connor, B.
 Gemmill-Herren, and N. Azzu. 2016. Protocol to detect and monitor
 pollinator communities: Guidance for practitioners.
 (2.2) Methods for processing the data: The abundance of all bees,
 the abundance of native bees, and species richness were modeled through a
 general linear mixed-effects approach in R (version 3.6.3, lme4 package,
 lmer function, Gaussian error distribution) (Bates et al. 2015, R Core
 Team 2020) and performed by multi-model inference based on the corrected
 Akaike’s Information Criterion<br> (AICc) (Harrison et al.
 2018). Bates, D., M. Maechler, B. Bolker, and S.
 Walker. 2015. Fitting linear mixed-effects models using lme4. Journal of
 Statistical Software 67:1–48.<br> Harrison, X. A., L. Donaldson, M.
 E. Correa-Cano, J. Evans, D. N. Fisher, C. E. D. Goodwin, B. S. Robinson,
 D. J. Hodgson, and R. Inger. 2018. A brief introduction to mixed effects
 modelling and multi-model inference in ecology. PeerJ 2018:1–32.<br>
 R Core Team. 2020. R: A language and environment for statistical
 computing. R Foundation for Statistical Computing, Vienna,
 Austria. (2.3) Environmental/experimental conditions:
 The data were sampled in a large-scale across the highly-heterogeneous
 environments of Brazil.   (3)
 DATA-SPECIFIC INFORMATION FOR: [GARIBALDIreadme.txt]
 (3.1) Number of variables:   9 (3.2) Number of
 cases/rows:      768 (3.3). Variable List:<br>
 study_system - variable that combined crop species, sampling season and
 year (categorical)  <br> total_abundance - total abundance accounted
 by the most-abundant species (numerical)<br> native_abundance -
 abundance of native bees (numerical)   <br> richness - richness of
 species (numerical)<br> dominance - dominance of species
 (numerical)<br> honey_bee_dominance - dominance of honey bee; yes:
 honey bee is most dominant species, no: honey bee is not most dominant
 species (categorical)<br> blooming_status - status of blooming
 during the bee sampling; yes: the crop was flowering, no: the crop was not
 flowering (categorical)<br> isolation - distance to natural or
 semi-natural habitats (numerical)<br> pan_trap_placement - pantraps
 were placed inside or outside the crop field (categorical)