Diet breadth
Diet breadth is another trait with important implications for bees’
functional roles and responses to environmental change. Because this
trait indicates a bee species’ range of floral host species, it can
determine susceptibility to habitat loss, pollination services, and
vulnerability to phenological mismatch. Two thirds (66 studies; 68.0%)
of the studies in our analysis considered the diet breadth of their
focal species (Figure 2d). The majority of these studies classified diet
breadth categorically (60 of 66 studies; 90.9%). Most commonly, studies
classified bee species as either oligolectic or polylectic, sourcing
data from the literature and adhering to the definition that oligolectic
species collect pollen from within a single plant family (Supplementary
Table 3). Definitions varied, however, and less than half of studies
defined these terms at all, whether through written definitions or
citations (26 of 60 studies; 43.4%). Importantly, diet breadth can be
conceptualized as a continuous variable with large variation in the
degree of specialization (Cane and Sipes, 2006; Danforth et al., 2019).
Several studies accounted for the diversity of diet specialization
states by additionally including such terms as “mesolectic” and
“monolectic” (Hall et al., 2019; Hung et al., 2019; Hung et al., 2021;
Moretti et al., 2009; Ricotta & Moretti, 2011; sensu Cane &
Sipes, 2006). A minority of studies made efforts to account for the
continuous nature of diet breadth by treating it as a numeric variable
(in 6 of 66 studies; 9.1%). Studies varied in their approaches to
quantifying diet breadth numerically, whether as simply the number of
host plant species (Rader et al., 2014), through network analysis (Raiol
et al., 2021), or by diversity metrices that consider the phylogenetic
breadth of host plant species (Bartomeus et al., 2018; Campbell et al.,
2022; Lichtenberg et al., 2017). It is important to note that these
metrics often depend on detailed visitation data, and can be sensitive
to effects of sampling bias (Blüthgen, 2010). Providing details on the
data source (e.g., pollen load data, expert knowledge, visitation data)
is crucial for promoting data reuse in future studies.