Environmental context shapes the relationship between grass consumption and body size in African herbivore communities
Data files
Feb 09, 2024 version files 64.21 KB
Abstract
Though herbivore grass dependence has been shown to increase with body size across herbivore species, it is unclear whether this relationship holds at the community level. Here we evaluate whether grass consumption scales positively with body size within African large mammalian herbivore communities and how this relationship varies with environmental context. We used stable carbon isotope and community occurrence data to investigate how grass dependence scales with body size within 23 savanna herbivore communities throughout eastern and central Africa. We found that dietary grass fraction increased with body size for the majority of herbivore communities considered, especially when complete community data were available. However, the slope of this relationship varied, and rainfall seasonality and elephant presence were key drivers of the variation—grass dependence increased less strongly with body size where rainfall was more seasonal and where elephants were present. We found also that the dependence of the herbivore community as a whole on grass peaked at intermediate woody cover. Intraspecific diet variation contributed to these community-level patterns: common hippopotamus (Hippopotamus amphibius) and giraffe (Giraffa camelopardalis) ate less grass where rainfall was more seasonal, whereas Cape buffalo (Syncerus caffer) and savanna elephant (Loxodonta africana) grass consumption were parabolically related to woody cover. Our results indicate that general rules appear to govern herbivore community assembly, though some aspects of herbivore foraging behavior depend upon local environmental context.
README
This 'README_file_Herbivore community assembly.txt' file was generated on 2024-01-23 by JOEL O. ABRAHAM
GENERAL INFORMATION
Title of Dataset: Environmental context shapes the relationship between grass consumption and body size in African herbivore communities
Author Information
A. Principal Investigator Contact Information
Name: Joel O. Abraham
Institution: Princeton University
Email: joeloa@princeton.eduB. Associate or Co-investigator Contact Information
Name: J. Tyler Faith
Institution: University of Utah
Email: jfaith@nhmu.utah.eduDate of data collection (approximate): 2023-08-01 to 2024-01-13
Geographic location of data collection: eastern and central Africa; compiled from existing literature/data sources
Information about funding sources that supported the collection of the data:
Joel O. Abraham was supported by the NSF GRFP
J. Tyler Faith was supported by NSF grants CNH-1826666 and 2224318
SHARING/ACCESS INFORMATION
Licenses/restrictions placed on the data: None.
Links to publications that cite or use the data: TBD
Links to other publicly accessible locations of the data: TBD
Links/relationships to ancillary data sets: NA
Was data derived from another source? YES
A. List source(s):
Cerling, T.E., Andanje, S.A., Blumenthal, S.A., Brown, F.H., Chritz, K.L., Harris, J.M., et al. (2015). Dietary changes of large herbivores in the Turkana Basin, Kenya from 4 to 1 Ma. PNAS, 112, 11467–11472.
Fick, S.E. & Hijmans, R.J. (2017). WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37, 4302–4315.
Rowan, J., Beaudrot, L., Franklin, J., Reed, K.E., Smail, I.E., Zamora, A., et al. (2020). Geographically divergent evolutionary and ecological legacies shape mammal biodiversity in the global tropics and subtropics. Proceedings of the National Academy of Sciences, 117, 1559–1565.
Venter, Z.S., Cramer, M.D. & Hawkins, H.-J. (2018). Drivers of woody plant encroachment over Africa. Nat Commun, 9, 2272.
Wilman, H., Belmaker, J., Simpson, J., Rosa, C. de la, Rivadeneira, M.M. & Jetz, W. (2014). EltonTraits 1.0: Species-level foraging attributes of the world’s birds and mammals. Ecology, 95, 2027–2027.Recommended citation for this dataset:
Abraham, J.O., Rowan, J., O'Brien, K., Sokolowski, K.G., and Faith, J.T. (2024).Environmental context shapes the relationship between grass consumption and body size in African herbivore communities, Dryad, Dataset.
DATA & FILE OVERVIEW
- File List: README_file_Herbivore community assembly.txt: README file explaining how the dataset was generated and the data contained in the dataset EcoEvo_Abraham et al_community level diet data.csv: EcoEvo_Abraham et al_community covariates.csv:
METHODOLOGICAL INFORMATION
Description of methods used for collection/generation of data:
We quantified local grass dependence from a dataset of stable isotope data collected from across eastern and central Africa, Cerling et al. (2015).
We identified which species were missing local data using a dataset of herbivore community composition, Rowan et al. (2020).
We then computed regional species-level averages for those community members missing local diet data, also from the aforementioned stable isotope dataset.
We extracted species-level body mass estimates from EltonTraits (Wilman et al. 2014).
We downloaded shapefiles for each community from the World Database on Protected Areas (WDPA).
Using these shapefiles, we extracted environmental covariates for each herbivore community: we calculated mean annual rainfall, mean rainfall seasonality, mean annual temperature, and mean temperature seasonality for each community from climatic data layers downloaded from WorldClim 2.0 (Fick and Hijmans 2017);
we extracted estimates of woody cover for each community from a data layer of fractional woody cover for sub-Saharan Africa (Venter et al. 2018).Methods for processing the data:
NAInstrument- or software-specific information needed to interpret the data:
NA - R was used to generate community covariates data but is not necessary for using the dataStandards and calibration information, if appropriate:
NAEnvironmental/experimental conditions:
NADescribe any quality-assurance procedures performed on the data:
NAPeople involved with sample collection, processing, analysis and/or submission:
All data were compiled and extracted by Joel O. Abraham.
DATA-SPECIFIC INFORMATION FOR: EcoEvo_Abraham et al_community level diet data.csv
Number of variables: 10
Number of cases/rows: 443
Variable List:
Ecosystem - the abbreviation for the herbivore community to which the data correspond
Protected_area - the name of the protected area from which stable isotope data were collected and environmental covariates were extracted
Type - whether the data were local (directly from Cerling et al. 2015), regional (species-level averages derived from Cerling et al. 2015), or global (pulled from global diet data compilations because that species was not present in Cerling's dataset).
Species - the scientific name of the community member
Order - the order to which the community member belongs
Family - the family to which the community member belongs
C4_mean - the mean dietary grass fraction estimate for the community member
C4_SD - the estimated standard deviation in dietary grass fraction for the community member
C4_N - the number of samples used to generate the estimated dietary grass fraction mean and standard deviation
Body_mass - the body mass of the community member, in kilograms (kg)Missing data codes:
'NA'Specialized formats or other abbreviations used:
NA
DATA-SPECIFIC INFORMATION FOR: EcoEvo_Abraham et al_community covariates.csv
Number of variables: 19
Number of cases/rows: 23
Variable List:
Ecosystem - the abbreviation for the herbivore community to which the data correspond
Community_name - the full name of the herbivore community to which the data correspond
Park_name - the name of the protected area from which stable isotope data were collected and environmental covariates were extracted
WDPA_PID - the unique ID assigned to the protected area by the World Database on Protected Areas
Latitude - the latitudinal centroid of samples collected for each community
Longitude - the longitudinal centroid of samples collected for each community
Complete_community_data - whether or not community composition data were available for the community
Elephant - whether or not elephants were present within a community
SpN - the number of herbivore species present in the community
Woody_cover_mean - the average woody cover for the protected area corresponding to the herbivore community
Woody_cover_SD - the standard deviation in woody cover for the protected area corresponding to the herbivore community
MATemp_mean - mean annual temperature (in degrees Celcius) for the protected area corresponding to the herbivore community
MATemp_SD - standard deviation in mean annual temperature (in degrees Celcius) for the protected area corresponding to the herbivore community
TempS_mean - mean temperature seasonality (measured as the standard deviation of temperature across the seasonal cycle) for the protected area corresponding to the herbivore community
TempS_SD - standard deviation in temperature seasonality (the standard deviation of temperature across the seasonal cycle) for the protected area corresponding to the herbivore community
MARain_mean - mean annual rainfall (in millimeters) for the protected area corresponding to the herbivore community
MARain_SD - standard deviation in mean annual rainfall (in millimeters) for the protected area corresponding to the herbivore community
RainS_mean - mean rainfall seasonality (measured as the coefficient of variation [standard deviation divided by the mean] in precipitation throughout the year) for the protected area corresponding to the herbivore community
RainS_SD - standard deviation in rainfall seasonality (measured as the coefficient of variation [standard deviation divided by the mean] in precipitation throughout the year) for the protected area corresponding to the herbivore communityMissing data codes:
'NA'Specialized formats or other abbreviations used:
NA
Methods
We quantified local grass dependence from a dataset of stable isotope data collected from across eastern and central Africa, Cerling et al. (2015). We identified which species were missing local data using a dataset of herbivore community composition, Rowan et al. (2020). We then computed regional species-level averages for those community members missing local diet data, also from the aforementioned stable isotope dataset.
We extracted species-level body mass estimates from EltonTraits (Wilman et al. 2014).
We downloaded shapefiles for each community from the World Database on Protected Areas (WDPA). Using these shapefiles, we extracted environmental covariates for each herbivore community: we calculated mean annual rainfall, mean rainfall seasonality, mean annual temperature, and mean temperature seasonality for each community from climatic data layers downloaded from WorldClim 2.0 (Fick and Hijmans 2017); we extracted estimates of woody cover for each community from a data layer of fractional woody cover for sub-Saharan Africa (Venter et al. 2018).