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Data & R code for: Paquette & Hargreaves 'Biotic interactions are more often important at species' warm vs. cool range edges'

Cite this dataset

Hargreaves, Anna (2021). Data & R code for: Paquette & Hargreaves 'Biotic interactions are more often important at species' warm vs. cool range edges' [Dataset]. Dryad.


Predicting which ecological factors constrain species distributions is a fundamental ecological question and critical to forecasting geographic responses to global change. Darwin hypothesized that abiotic factors generally impose species’ high-latitude and high-elevation (typically cool) range limits, whereas biotic interactions more often impose species’ low-latitude/low-elevation (typically warm) limits, but empirical support has been mixed. Here, we clarify three predictions arising from Darwin’s hypothesis, and show that previously mixed support is partially due to researchers testing different predictions. Using a comprehensive literature review (885 range limits), we find that biotic interactions, including competition, predation, and parasitism, contributed to >60% of range limits, and influenced species’ warm limits more often than cool limits. Abiotic factors contributed more often than biotic interactions to cool range limits, but temperature contributed frequently to both cool and warm limits. Our results suggest that most range limits will be sensitive to climate warming, but warm-limit responses will depend strongly on biotic interactions.


There are two sets of data: data on potentially range-limiting factors (one file for cool limits and one file for warm limits), and data for locations of each data point (again, one file for cool limits, one for warm limits).

See Supplementary Materials for full description. In brief:

We searched Web of Science for studies published up to the end of 2019 that assessed the causes of species’ high latitude/elevation (hereafter ‘cool’) or low latitude/elevation (hereafter ‘warm’) range limits. To increase coverage in areas with few studies, we repeated the search in Spanish and French and did a targeted search for studies from Africa. We screened results for studies that assessed the importance of at least one biotic or abiotic factor in causing a cool or warm range limit.

We extracted data for each potentially range-limiting factor assessed, separating data by study and species whenever possible. For each study x taxon x range limit (latitude or elevation, cool or warm, separated by continent or ocean if applicable), we identified the potential range-limiting factors assessed, such that each factor a study assessed at a given range limit contributed 1 data point.  We noted whether each factor was biotic or abiotic (‘factor type’) and what category of factor it was.  Multiple assessments of a factor category (e.g. max. and mean annual temperature) at one species’ range limit would contribute one data point.  Factors outside these categories were assigned as ‘other’.

We collected various meta-data about each data point, as explained in the 'column headings explained' sheet.

We assessed whether each factor contributed to the given range limit (‘yes’ or ‘no’), determined from statistical results, figures, and author arguments when necessary. Data and reasoning behind these decisions are given in separate columns. If a study considered >1 measure of one factor (e.g. summer and winter temperature), we deemed the factor (temperature in this example) supported if any measure contributed to the range limit.  For studies in Cahill et al. (2014), we used their conclusions unless a) data were grouped across species or studies, in which case we ungrouped data and reassessed conclusions for each species/study, or b) we spot checked the study and could not find evidence to support the conclusion.  These decisions are also detailed in the data.


Natural Sciences and Engineering Research Council, Award: Discovery Grant to ALH, Undergraduate Student Research Award to AP