Data from: Moving beyond Bergmann and Converse Bergmann: Can competition or food resources drive spatial variation in body size?
Data files
Sep 28, 2026 version files 259 KB
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All_Size_Data.csv
245.24 KB
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README.md
4.56 KB
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Reference_Dataset_for_LengthWeight_Conversion.csv
4.43 KB
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Site-Level_Size_Abundance_Summaries.csv
3.07 KB
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Site-Level_Temp_Data.csv
1.71 KB
Abstract
Hypothesis testing for body size trends along elevational and latitudinal gradients is dominated by Bergmann’s rule predicting larger size in colder environments and Converse Bergmann’s rule predicting smaller size where summers are shorter. Despite the mixed to poor support for Bergmann’s and Converse Bergmann’s rules, alternative hypotheses are virtually untested along environmental gradients. Here we aim to contrast Bergmann’s and Converse Bergmann’s rules with alternative spatial hypotheses for intraspecific body size variation: intensity of competition and quantity of food resources across elevationally distributed sites. We use individuals from 11 species of carrion beetles (Staphylinidae: Silphinae) collected across 30 sites in two mountain ranges (Front Range and San Juan Mountains, Colorado, USA). We measure beetle body size (elytral length, estimated weight), quantify food availability, and estimate interference and exploitative competition from community abundance. Predictions of Bergmann’s rule and competition lacked support. Two of ten species supported Converse Bergmann’s rule. In contrast, within-site body size variation was significantly associated with local food abundance. Where food resources were abundant intraspecific body sizes spanned from very small to very large. Resource-poor sites yielded fewer, but uniform, average-sized individuals. Alternative aspects of life history can outweigh climate in shaping insect body size, thus potentially underlying inconsistent elevational body size patterns across studies.
Dataset DOI: 10.5061/dryad.pk0p2nh5p
Files and variables
File: Reference_Dataset_for_LengthWeight_Conversion.csv
Description: Reference dataset of beetles live-caught in Boulder County that were frozen and weighed before elytral length measurements were taken. As these individuals were not preserved in ethanol prior to length measurement, their weights could be used to estimate species-specific length-weight relationships. Weights provided in other datasets are estimated from lengths using slopes derived from this reference data.
Variables
- Species: Full species names.
- Length_mm: Average of 3 elytral length measurements to the nearest 0.01 millimeter.
- Weight_g: Weight in grams measured to the nearest 0.1 milligrams.
File: All_Size_Data.csv
Description: Size data for all individuals measured for elytral length and included in analyses. All weights are estimates. For a full description of the project these beetles were collected as a part of, see McCain et al. 2018 in Journal of Biogeography.
Variables
- Range: Mountain Range of the two sampled including Front Range and San Juan Mountains.
- Transect: Transect of the two per mountain range.
- Site: Site name.
- Trap: Trap identifier. For some traps, exact ID was lost during sample collection or processing and missing identifiers are represented with a "?" as in Trap M?E.
- Elevation_m: Average trap elevation in meters.
- Elevation_km: Average trap elevation in kilometers.
- Species: Species name.
- Tribe: Tribe name corresponding to the species name.
- Length_mm: Average of 3 elytral length measurements to the nearest 0.01 millimeter.
- Estimated_weight_g: Estimated weight calculated from reference dataset in grams.
- Estimated_weight_mg: Estimated weight calculated from reference dataset in milligrams.
File: Site-Level_Size_Abundance_Summaries.csv
Description: Aggregated mean and range lengths and weights for each site and overall mammal and carrion beetle abundances at those sites for assessment of alternative hypotheses.
Variables
- Site: Site name.
- Species: Species Name.
- MeanLength_mm: Average elytral length in millimeters at a given site for a given species.
- MeanWeight_g: Average estimated weight in grams at a given site for a given species.
- MeanWeight_mg: Average estimated weight in milligrams at a given site for a given species.
- RangeLength_mm: Range in elytral length in millimeters at a given site for a given species.
- RangeWeight_g: Range in estimated weight in grams at a given site for a given species.
- RangeWeight_mg: Range in estimated weight in milligrams at a given site for a given species.
- Abundance: Abundance at a given site for a given species during year of sampling.
- Site_MKNA: Site-level mammal abundance measured as Most Known Alive during year of sampling.
- Site_CB_Abundance: Site-level total carrion beetle abundance during year of sampling.
- Site_Nicrophorini_Abundance: Site-level total Nicrophorini abundance during year of sampling.
File: Site-Level_Temp_Data.csv
Description: Site-level averages for temperature data including mean annual temperature, number of days above zero, and standard deviation of daily mean air temperature.
Variables
- Range: Mountain Range of the two sampled including Front Range and San Juan Mountains.
- Transect: Transect of the two per mountain range.
- Site: Site name.
- Mean_Annual_Temp_: Mean annual temp in Celsius obtained from PRISM 30 year averages at 800-meter resolution.
- Days_mean_air_temp_above_0: Number of days in the sampling year with an average air temperature above 0 Celsius. Daily mean air temperature for each site was obtained from temperature sensors placed at each site for 1 year with gaps in data interpolated. For three sites (MRS, Saddle, Sundance) values are missing as data logger failures especially during winter months prevented an estimate of number of days above 0 Celsius with high confidence.
- StdDev_in_Mean_Daily_Air_Temp_C: Standard deviation in the mean daily air temperature in Celsius. Daily mean air temperature for each site was obtained from temperature sensors placed at each site for 1 year with gaps in data interpolated.
Code/software
Analyses conducted in R Version 4.4.3 with packages tidyverse, lme4, sjPlot, performance, ggpubr, and ggplot2.
