DOI: 10.5061/dryad.n5tb2rbtn
title: Coutinho et al. 2021 - Landscape structure is a major driver of bee functional diversity in crops

description: The study of functional diversity can support the understanding of how
 changes at the landscape affects the roles of organisms in biological
 communities and consequently their ecological functions such as
 pollination. Different aspects of functional diversity have been addressed
 in recent years. Understanding those effects on landscape patterns is a
 key step to target ecological intensification. Still, elucidating those
 relationships requires studies in multiple spatial scales since effects
 and consequences are different considering biological groups and
 interactions. In that sense, by using a multitrait approach we evaluated
 whether the landscape structure and/or local environment characteristics
 could explain the functional richness, divergence and dispersion of bee
 communities in agroecosystems. In addition, we investigated to which
 extent  this approach help to predict effects on pollination
 services. This study was conducted in an agroecosystem situated in
 "Chapada Diamantina" region, State of Bahia, Brazil. Bees were
 collected using two complementary techniques (entomological nets and pan
 traps) in 27 sample units distributed orthogonally along a gradient of
 agriculture and landscape diversity. Bees were classified according to
 their response traits (e.g. body size, nesting location) and effect traits
 (e.g means of pollen transportation, specialty in obtaining some
 resource).The Akaike Information Criterion (AIC) was used to select the
 best models created through the additive combination of landscape
 descriptors (landscape diversity, mean patch shape and local vegetation
 structure) at the local, proximal and broad landscape levels. Our results
 indicate that both landscape heterogeneity and configuration matter in
 explaining the three properties of bee functional diversity. We indicate
 that different properties of functional diversity are influenced by
 different landscape descriptors, at different spatial scales. In this
 sense, including conjunct strategies, in different spatial scales,
 considering different ecological processes is a more relevant way to think
 about land use scenarios in a perspective to contemplate functional
 diversity.
description: Biological data were collected
 along a gradient of landscape proportion of agriculture and habitat types
 diversity at a 3 km scale. Two complementary sampling strategies were
 used: passive through the use of pan traps (Cane et al. 2000) and active,
 through entomological nets (Moreira et al. 2015). For the collection with
 pan traps, we used the three most common colors to attract bees:  yellow,
 white and blue. Blue and yellow traps also had ultraviolet radiation (Cane
 et al. 2000). In each pan trap was placed 120ml of water and approximately
 five drops of neutral detergent to break the surface tension.. The pan
 traps were installed at a height of 1m from the ground using 25mm diameter
 PVC pipes and perforated metal ribbons, used as support for 18mm diameter
 colored dishes. Traps were distant 5m from each other in an equidistant
 triangular shape, where each one was positioned at a vertex of this
 triangle. At each sampling point, three groups of three plates of
 different colors were installed, totaling nine pan traps for each sampling
 point (Figure 2). This set of nine pan traps formed a larger triangle in
 each sample unit. Each group of three was 15m from the nearest
 group. The active sampling with entomological nets was
 made by two collectors walking through two isosceles triangles, within a
 reference hexagon with 25 m sides (Figure 3). All floral visitors seen on
 the flowers were collected with the nets between 07:30 and 17:30. For
 logistic reasons, the set of 30 sample units was divided into two groups
 of 15 along the study region. To avoid possible systematic effects of
 seasonality, each group was sampled every two months between January and
 November 2011, corresponding to two rainy seasons and two dry seasons.
 Each sample unit was sampled for 40 hours throughout the entire campaign.
 Collectors alternated the units they sampled, to minimize possible
 systematic effects on collection (Moreira et al. 2015). For the
 statistical analysis we used only 27 sample points, due to logistic
 difficulties associated with three of the sampling points during the
 collection period.
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