Data from: The ecology of encroachment: Identifying the species and plant ecological strategies driving African savanna change
Data files
Jul 16, 2026 version files 18.81 MB
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GCB_coords_worldclim_2025.xlsx
18.61 MB
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GCB_traits_2025.xlsx
180.90 KB
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README.md
16.22 KB
Abstract
This dataset compiles information on woody species in African savannas and grasslands, including 63 identified encroacher species and a broader set of non-encroachers across six dominant genera: Combretum, Dichrostachys, Prosopis, Senegalia, Terminalia, and Vachellia. The dataset includes species identity, encroacher status, functional traits (maximum height, plant habit, spinescence, nitrogen fixation potential), climatic variables (temperature and precipitation metrics), and geographic range estimates. Data values are numeric (e.g., climatic and range data), categorical (e.g., encroacher status, habit, nitrogen fixation), and factor variables (e.g., genus, clade). The dataset is structured to allow analyses of ecological patterns, trait associations, and species’ responses to environmental gradients. It is suitable for reuse in studies of functional ecology, species distribution, climate niche modeling, and management of woody encroachment. All data were compiled from published sources, databases, and georeferenced occurrence records; no human or animal subjects were involved.
Dataset DOI: 10.5061/dryad.1c59zw49s
Description of the data and file structure
Data Description:
The dataset was compiled to investigate the ecological traits and environmental tolerances of woody plant species driving encroachment in African savannas and grasslands. Data were collected across six dominant woody genera (Combretum, Dichrostachys, Prosopis, Senegalia, Terminalia, and Vachellia). For each species, information was collated on:
- Species identity and taxonomy (Genus, Species, Clade),
- Encroacher status (encroacher vs. non-encroacher)
- Climatic niche variables (median and range of temperature and precipitation) - calculated using worldclim data
- Geographic range size estimates - calculated using alphahull package in R
- Functional traits relevant to survival and establishment, including maximum plant height, plant habit, spinescence, and nitrogen-fixation potential - synthesised from published literature
Data were extracted from published sources, global climate databases (WorldClim), and trait databases, and processed to ensure consistency across species. Missing values were removed for analyses requiring complete datasets. This dataset supports comparative analyses of encroacher vs. non-encroacher species, enabling reuse for ecological modeling, trait-based assessments, and conservation planning.
NAindicates that data were not available for a given species or variable. These values represent missing data and should not be interpreted as zero or absence.
Files and variables
File: GCB_coords_worldclim_2025.xlsx
Description: Contains species occurrence records and associated climatic data.
Variables
- X – Row index / unique identifier (—); Not used in models
- GBIF_species – Species name from GBIF occurrences (—); Used to link occurrences to traits and climatic data
- decimalLatitude – Latitude of occurrence point (Decimal degrees); Used to extract bioclimatic variables
- decimalLongitude – Longitude of occurrence point (Decimal degrees); Used to extract bioclimatic variables
- bio_1 – Annual Mean Temperature (°C); Predictor in GLMM for trait-environment relationships
- bio_2 – Mean Diurnal Range (Mean of monthly (max temp – min temp)) (°C); Predictor
- bio_3 – Isothermality (bio_2 / bio_7 × 100) (%); Predictor
- bio_4 – Temperature Seasonality (standard deviation ×100) (°C); Predictor
- bio_5 – Max Temperature of Warmest Month (°C); Predictor
- bio_6 – Min Temperature of Coldest Month (°C); Predictor
- bio_7 – Temperature Annual Range (bio_5 – bio_6) (°C); Predictor
- bio_8 – Mean Temperature of Wettest Quarter (°C); Predictor
- bio_9 – Mean Temperature of Driest Quarter (°C); Predictor
- bio_10 – Mean Temperature of Warmest Quarter (°C); Predictor
- bio_11 – Mean Temperature of Coldest Quarter (°C); Predictor
- bio_12 – Annual Precipitation (mm); Predictor
- bio_13 – Precipitation of Wettest Month (mm); Predictor
- bio_14 – Precipitation of Driest Month (mm); Predictor
- bio_15 – Precipitation Seasonality (Coefficient of Variation) (%); Predictor
- bio_16 – Precipitation of Wettest Quarter (mm); Predictor
- bio_17 – Precipitation of Driest Quarter (mm); Predictor
- bio_18 – Precipitation of Warmest Quarter (mm); Predictor
- bio_19 – Precipitation of Coldest Quarter (mm); Predictor
File: GCB_traits_2025.xlsx
Description: Contains the climatic variables, geographic range size (alpha X), and functional traits for the models.
Variables
- Clade – Taxonomic clade (Categorical)
- Genus – Taxonomic genus (Categorical)
- Species – Full species name (Categorical)
- Encroacher – Species encroacher status (Binary)
- Invasive – Species invasive status (Binary)
- N_fix_potential – Species nodulation (ability to fix nitrogen) (Yes / No)
- Region – Species indigenous region (Categorical)
- Max_height – Maximum species height (Metres)
- Dispersal – Seed dispersal method (Categorical)
- Ecosystem – Species native biome (Categorical)
- Spines – Presence of spines / spinescence (Yes / No)
- Habit – Species habit (Categorical)
- convex – Average convexity range (Continuous)
- alpha1 – Average alpha1 range (Continuous)
- alpha2 – Average alpha2 range (Continuous)
- alpha3 – Average alpha3 range (Continuous)
- alpha4 – Average alpha4 range (Continuous)
- alpha5 – Average alpha5 range (Continuous)
- alpha6 – Average alpha6 range (Continuous)
- bio_1_lower – Mean annual temperature (lower range) (°C)
- bio_1_upper – Mean annual temperature (upper range) (°C)
- bio_12_lower – Mean annual precipitation (lower range) (mm)
- bio_12_upper – Mean annual precipitation (upper range) (mm)
- bio_1_median – Median annual mean temperature (°C)
- bio_12_median – Median annual precipitation (mm)
- bio_1_range – Range of mean annual temperature (°C)
- bio_12_range – Range of annual precipitation (mm)
Code/software
- The dataset is provided as Microsoft Excel files (
.xlsx) and can be viewed with any spreadsheet software, including free options such as:- LibreOffice Calc
- Google Sheets
- OpenOffice Calc
- No specialized code is required to view or use the data.
Access information
Other publicly accessible locations of the data:
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Encroacher status was derived from the following sources:
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Missing values are represented as NA. These indicate that no value was available for the corresponding trait for a given observation (e.g. no valid measurement was obtained). NA denotes missing data and should not be interpreted as zero or "not applicable."
Species were selected from six dominant woody genera in African savannas and grasslands. Encroacher status was assigned based on documented impacts on ecosystem structure and function. Functional trait data were compiled from published literature, botanical databases, and herbarium records, including maximum height, plant habit, spinescence, and nitrogen fixation capacity. Climatic variables (mean annual temperature, temperature range, mean temperature of coldest quarter, annual precipitation, precipitation seasonality, precipitation wettest quarter, precipitation driest quarter) were extracted from georeferenced occurrence points using WorldClim datasets (v2, 1970–2000). Geographic range sizes were calculated using alpha-hull polygons based on species occurrence records.
Data were processed to ensure completeness; rows with missing values in key variables were removed. Numeric trait and climate variables were scaled where appropriate. Categorical and factor variables were standardized for consistency (e.g., genus names, encroacher status). The dataset is provided is excel with clearly labeled columns for each variable type.
