Water economics of African savanna herbivores: How much does plant moisture matter?
Data files
Jan 16, 2025 version files 70.77 GB
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2021_moTU_taxon_per_sample.csv
23 KB
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2022_moTU_taxon_per_sample.csv
11.47 KB
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Audio_Data.zip
70.76 GB
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Bushbuck_GPS.csv
2.21 MB
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Early_dry_diet_RRA.csv
3.32 KB
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Fecal_H2O_historical.csv
12.22 KB
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Fecal_H2O.csv
4.53 KB
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Kudu_GPS.csv
14.02 MB
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Late_dry_diet_RRA.csv
4.31 KB
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Mid_dry_diet_RRA.csv
5.50 KB
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Plant_H2O.csv
7.93 KB
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Plant_trait_data.csv
1.34 KB
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README.md
6.71 KB
Abstract
Water is an essential and often limiting resource that pervades all aspects of animal ecology. Yet, water economics are grossly understudied relative to foraging and predation, leaving ecologists ill-equipped to predict how the intensifying disruption of hydrological regimes worldwide will impact communities. For savanna herbivores, reliance on surface water can increase exposure to predators and competitors, and thus strategies that reduce the need to drink are advantageous. Yet, the extent to which increasing dietary water intake while decreasing water loss enables animals to forego drinking remains unknown.
We studied water budgets of sympatric African savanna antelopes that differ in size, bushbuck (Tragelaphus sylvaticus, ~35 kg) and kudu (T. strepsiceros, ~140 kg). We hypothesized that both species compensate for seasonally declining water availability by increasing consumption of moisture-rich plants and reducing fecal water loss, and that these adjustments are sufficient for small-bodied—but not large-bodied—herbivores to avoid spending more time near permanent water sources as the dry season advances. We tested our predictions using temporally explicit data on antelope movements, diets, plant traits, and drinking behavior in Gorongosa National Park, Mozambique.
Water content declined between the early and late dry seasons in roughly half of plant taxa consumed by antelope. Although both species reduced fecal water loss and shifted their diets towards relatively moisture-rich plants as the dry season progressed, dietary water intake still declined. Contrary to expectation, kudu reduced selection for surface water in the late dry season without adjusting total time spent drinking, whereas bushbuck increased selection for surface water.
We developed a generalizable approach for parsing the importance of dietary and surface water for large herbivores. Our results underscore that variation in surface-water dependence is a key organizing force in herbivore communities but also show that simple allometric predictions about the behavioral and ecological consequences of this variation are unreliable. Understanding wildlife water economics is a research frontier that will be essential for predicting changes in species distribution and community composition as temperatures rise and droughts intensify.
README: Water economics of African savanna herbivores: How much does plant moisture matter?
https://doi.org/10.5061/dryad.w0vt4b936
Description of the data and file structure
This is the README file for datasets contained in the publication: Jeremy A. Van Driessche, Simon Chamaillé-Jammes, Ciara M. Nutter, Arjun B. Potter, Robert M. Pringle, and Ryan A. Long, Water economics of African savanna herbivores: how much does plant moisture matter? Journal of Animal Ecology, 2025.
Files and variables
1. 2021_moTU_taxon_per_sample.csv
Species = ‘Bushbuck’ or ‘Kudu’
Date = day the fecal sample was collected
Season_dry = ‘mid’ or ‘late’; distinguishes whether the fecal sample was collected during the middle (July/August 2021) or late (September/October 2021) dry season
Sample_ID = fecal sample identifier
Columns E-BN represent molecular operational taxonomic units (mOTUs) assigned to plant taxa in Gorongosa National Park, Mozambique. Values in cells represent relative read abundance of mOTUs in each fecal sample.
2. 2022_moTU_taxon_per_sample.csv
Species = ‘Bushbuck’ or ‘Kudu’
Date = day the fecal sample was collected
Season_dry = ‘early’; all fecal samples in 2022 were collected during the early (May/June 2022) dry season
Sample_ID = fecal sample identifier
Columns E-BK represent molecular operational taxonomic units (mOTUs) assigned to
plant taxa in Gorongosa National Park, Mozambique. Values in cells represent relative read abundance of mOTUs in each fecal sample.
3. Bushbuck_GPS.csv
collarID = individual bushbuck collar number (n = 12)
date = date of each GPS location
time = local (Central Africa Time) time of each GPS location
latitude = latitude of GPS location in decimal degrees
longitude = longitude of GPS location in decimal degrees
near_dist_m = distance (in meters) from each GPS location to the nearest water source
h2o_type = ‘river’ or ‘pan’; distinguishes whether the water source nearest to each GPS location was a river or a perennial pan
4. Kudu_GPS.csv
collarID = individual kudu collar number (n = 12)
date = date of each GPS location
time = local (Central Africa Time) time of each GPS location
latitude = latitude of GPS location in decimal degrees
longitude = longitude of GPS location in decimal degrees
near_dist_m = distance (in meters) from each GPS location to the nearest water source
h2o_type = ‘river’ or ‘pan’; distinguishes whether the water source nearest to each GPS location was a river or a perennial pan
5. Early_dry_diet_RRA.csv
Sequence_ID = mOTU identifier
Plant_species_ID = plant taxon (associated with corresponding mOTUs) commonly consumed by bushbuck and/or kudu in Gorongosa National Park, Mozambique.
Species_sampled_for_H2O = plant(s) sampled to estimate mean preformed water content during the early-dry season.
Columns D-T represent bushbuck and kudu fecal samples collected in the early-dry season. Values in cells are relative read abundances (RRA) for each plant taxon.
Row 24 shows the summed RRA for each fecal sample.
6. Mid_dry_diet_RRA.csv
Sequence_ID = mOTU identifier
Plant_species_ID = plant taxon (associated with corresponding mOTUs) commonly consumed by bushbuck and/or kudu in Gorongosa National Park, Mozambique.
Species_sampled_for_H2O = plant(s) sampled to estimate mean preformed water content during the mid-dry season.
Columns D-AJ represent bushbuck and kudu fecal samples collected in the mid-dry season. Values in cells are relative read abundances (RRA) for each plant taxon.
Row 25 shows the summed RRA for each fecal sample.
7. Late_dry_diet_RRA.csv
Sequence_ID = mOTU identifier
Plant_species_ID = plant taxon (associated with corresponding mOTUs) commonly consumed by bushbuck and/or kudu in Gorongosa National Park, Mozambique.
Species_sampled_for_H2O = plant(s) sampled to estimate mean preformed water content during the late-dry season.
Columns D-Z represent bushbuck and kudu fecal samples collected in the late-dry season. Values in cells are relative read abundances (RRA) for each plant taxon.
Row 25 represents summed RRA for each fecal sample.
8. Fecal_H2O.csv
sampleID = fecal sample identifier
Julian_day = Juian day the fecal sample was collected
species = ‘Bushbuck’ or ‘Kudu’
season_dry = ‘early’, ‘mid’, or ‘late’; distinguishes whether the fecal sample was collected during the early (May/June 2022), middle (July/August 2021), or late (September/October 2021) dry season
Preformed_H2O = estimated water content of each fecal sample (%)
9. Fecal_H2O_historical.csv
Species_Common_Name = ‘Bushbuck’ or ‘Kudu’
Collection_Date = date each fecal sample was collected (2014 – 2022)
Julian_day = Julian day each fecal sample was collected
RRA = total proportion of diet comprised of plant taxa for which we had measured values of water content. Minimum threshold for inclusion was ≥ 80% (0.80)
Preformed_H2O = estimated water content of each fecal sample (%)
10. Plant_H2O.csv
Species = plant taxon commonly consumed by bushbuck and/or kudu in Gorongosa National Park, Mozambique during the dry season.
Season_dry = ‘early’, ‘mid’, or ‘late’; distinguishes whether the plant sample was collected during the early (May/June 2022), middle (July/August 2021), or late (September/October 2021) dry season
Preformed_H2O = measured water content of each plant sample (%)
11. Plant_trait_data.csv
Species = plant taxon commonly consumed by bushbuck and/or kudu in Gorongosa National Park, Mozambique during the dry season.
Leaf_Mass_per_Area = mean leaf mass per area
Plant_Height_m = mean plant height in meters
12. Audio Data (contained in Zip file)
Audio data from 7 female kudu. Files contain audio (.wav) recordings obtained from biologgers affixed to 7 female kudu collars during 2021. Folders are named with kudu collar IDs and each contains a series of continuous, consecutive recordings beginning the moment of audio logger activation and ending with battery failure (6–51 days after deployment; x̅ = 33.7 days). Each .wav file is named as “audio_date_time” in ~1-hr segments, with the date displayed as day month year (e.g., 010821 for August 1st, 2021) and the time displayed as hour minute second.
Code/software
Data files included in this package are either comma-delimited text files (.csv) or audio files (.wav) that can be viewed/listened to using standard spreadsheet or audio software (e.g., Microsoft Excel, Windows Media Player).