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.