DOI: 10.5061/dryad.m37pvmdcd
title: Impacts of African elephants and other environmental drivers on trees nested in by critically endangered white-backed vultures

description: The decline of white-backed vultures (Gyps africanus, hereafter termed
 vultures) across Africa highlights the need to understand their
 habitat and nesting requirements, especially in protected areas
 where African elephants (Loxodonta africana) can impact the trees in which
 vultures build their nests. Our study aimed to assess the impact
 that elephants have on trees containing vulture nests in the
 Associated Private Nature Reserves (APNR) of South Africa’s savanna
 system through three separate but interlinked assessments. We
 first assessed the tree species used by vultures for nesting and
 compared their size and elephant impact scores between riparian
 and woodland habitats. We assessed how elephant presence or
 absence affects the size of Senegalia nigrescens, a key tree
 species, and compared vulture nests in an adjacent elephant-free
 area. Lastly, we modeled environmental factors influencing
 vulture nest and tree persistence using data from 2008-2020.
 Vultures utilised 10 tree species, with riparian trees supporting nests
 being significantly taller, with larger DBHs, and experienced
 lower elephant impact compared to woodland trees, which were more
 heavily impacted by elephants. Less robust species like
 S. nigrescens were more vulnerable to elephant damage, primarily
 bark-stripping, and less likely to host vulture nests. Our
 results show that vultures prefer the largest, least impacted trees
 for nesting, favouring those with greater stability and
 longevity. We suggest that although elephants influence the
 overall height range of trees to vultures, strong gusts of wind have a
 strong negative contribution on vulture nest persistence and that
 only a relatively small number of trees died during the 12-year
 study in comparison to fallen nests. We recommend further research
 into elephant impact thresholds on trees and vulture nest
 selection. Monitoring treefall and regeneration rates will help
 predict when vultures may face a shortage of suitable nesting trees.
description: <em>Dataset Collection:</em> The
 dataset was collected through detailed field surveys conducted between
 2008 and 2020 in the Associated Private Nature Reserves (APNR) and the
 adjacent Air Force Base Hoedspruit (AFB), located in South Africa’s
 savanna system. The surveys were designed to assess the impact of African
 elephants on trees utilized by white-backed vultures (<em>Gyps
 africanus</em>) for nesting. The surveys focused
 on three objectives: Measuring the
 morphometric traits (height, diameter at breast height [DBH]) and elephant
 impact scores of various tree species used for nesting by vultures, across
 both riparian and woodland habitats. Comparing the
 characteristics and impact levels of nesting and control trees
 (non-nesting) of the key species <em>Senegalia nigrescens</em>
 in areas with and without elephants. Investigating
 the long-term persistence of <em>S. nigrescens</em> trees with
 vulture nests under varying ecological and environmental
 pressures. Data collection involved
 marking tree locations using GPS, measuring tree height with VolCalc
 software, and recording DBH using a standardized approach. Elephant impact
 was scored on a scale of 0-5 using an established framework (Walker, 1976;
 Helm & Witkowski, 2013) to classify damage ranging from minor
 bark-stripping to complete tree mortality. Additional covariates were
 recorded, including the presence of ants, termites, and shelf-bracket
 fungus, fire scars, distance to the nearest road and water source, and
 annual rainfall and wind gust data obtained from local weather stations.
 Historical data from the Elephants Alive NGO and aerial census records
 provided complementary information for long-term analysis.
 <em>Dataset Processing:</em> The
 collected data were processed and analyzed using R software (version
 4.3.0). A suite of statistical tests and models was employed to address
 specific research objectives. These included: 
 <strong>Descriptive Statistics</strong>:
 Summarizing morphometric and environmental variables for trees in riparian
 versus woodland habitats. <strong>Comparative
 Analyses</strong>: Mann-Whitney U-tests and Kruskal-Wallis one-way
 ANOVA were used to identify significant differences in tree
 characteristics, elephant impact scores, and habitat effects.
 <strong>Persistence Analyses</strong>: Kaplan-Meier
 survival analyses were conducted to compare tree and nest survival rates
 over the 12-year study period. Mortality rates for trees and nests were
 calculated to identify key periods of decline. 
 <strong>Hazard Modeling</strong>: Cox proportional-hazards
 models were applied to explore the effects of environmental covariates
 (e.g., wind gusts, tree height, DBH) on tree and nest persistence.
 Continuous variables were scaled and centered to improve interpretability
 and model convergence. Stepwise backward selection, followed by forward
 validation, was used to refine models for robustness.
 The resulting dataset provides a comprehensive view
 of the relationships between elephants, trees, and white-backed vulture
 nesting ecology, facilitating insights into tree persistence and nest-site
 suitability under environmental pressures. The data were cleaned and
 verified for consistency and accuracy before final analysis.
 <strong>References</strong> Helm,
 C.V. and Witkowski, E.T.F. 2013. Continuing decline of a keystone tree
 species in the Kruger National Park, South Africa. African Journal of
 Ecology 51(2), pp. 270–279. doi:<br>10.1111/aje.12032.
 Walker, S.H. 1976. An approach to the monitoring of changes in
 the composition and utilization of woodland and savanna vegetation. South
 African Journal of Wildlife Research 6(1), pp. 1–32.
description: # Impacts of African elephants and other environmental drivers on trees
 nested in by critically endangered white-backed vultures
 [https://doi.org/10.5061/dryad.m37pvmdcd](https://doi.org/10.5061/dryad.m37pvmdcd) ## Description of the data and file structure The data was collected to investigate the impact of African elephants on trees used by critically endangered white-backed vultures (*Gyps africanus*) for nesting. The study was conducted in South Africa's savanna system, focusing on the Associated Private Nature Reserves (APNR) and Air Force Base Hoedspruit (AFB), where elephants are present and absent, respectively. The experimental efforts involved: 1. **Multispecies Assessment**: Identifying tree species used for vulture nesting, measuring tree morphometrics, and evaluating elephant impact across riparian and woodland habitats. 2. **Elephant Influence**: Comparing tree characteristics and elephant impact scores for *Senegalia nigrescens*, the primary nesting tree species, in areas with and without elephants. 3. **Persistence Trends**: Monitoring the long-term survival of vulture nests and nesting trees over 12 years, while modeling environmental factors such as wind gusts, rainfall, and proximity to water sources that influence tree and nest persistence. This dataset supports a deeper understanding of how ecological drivers, including elephants, affect the availability and quality of nesting habitats for vultures, thereby informing conservation and management strategies for both species and their shared ecosystems. ### Files and variables #### File: Cook\_et\_al\_2024\_WildlifeBiology\_DataDepository.xlsx **Description:** Impacts of African Elephants and Other Environmental Drivers on Trees Nested by Critically Endangered White-Backed Vultures * **Authors**: Robin M. Cook, Ed T. Witkowski, Michelle D. Henley * **Contact Information**: [robinmichaelcook@gmail.com](mailto:robinmichaelcook@gmail.com) * **Date of Data Collection**: 2008–2020 * **Geographic Location**: Associated Private Nature Reserves (APNR) and Air Force Base Hoedspruit (AFB), South Africa The Excel file contains a metadata tab for each data tab, complete with variable descriptions. Further information regarding the dataset can be obtained by contacting the lead author (Robin Cook; [robinmichaelcook@gmail.com](mailto:robinmichaelcook@gmail.com)) or the Director of Elephants Alive (Dr. Michelle Henley; [michelephant@savetheelephants.org](mailto:michelephant@savetheelephants.org)). ## Variables ### Objective 1: Multispecies Assessment * **Objective 1_Species_Codes**: Contains species codes for tree and nesting data. * **Objective 1_Species_Data**: Includes tree morphometrics (e.g., height, diameter at breast height [DBH]), elephant impact scores (scale 0-5), and nesting preferences by vultures across riparian and woodland habitats. ### Objective 2: Influence of Elephants * **Objective 2_Elephant eff_Codes**: Contains codes for site classification (e.g., with or without elephants). * **Objective 2_Elephant eff_Data**: Provides morphometric data and impact scores for trees in areas with and without elephants, focusing on *Senegalia nigrescens*. ### Objective 3: Persistence Trends * **Objective 3_Survival_Codes**: Describes codes used for survival analysis of trees and nests. * **Objective 3_Survival_Data**: Tracks long-term survival of trees and nests, including covariates such as wind gusts, proximity to roads, and rainfall. * **Objective 3_NestFall_Codes**: Definitions for variables related to vulture nest falls. * **Objective 3_NestFall_Data**: Details environmental and impact factors contributing to nest falls. * **Objective 3_TreeFall_Codes**: Definitions for variables related to treefalls. * **Objective 3_TreeFall_Data**: Includes factors affecting treefall events (e.g., elephant impact, fire scars). --- ## Data Collection and Processing * **Data Collection**: * Field measurements of tree morphometrics and elephant impact scores were conducted annually from 2008–2020. * Variables such as termite presence, distance to water, and wind gust data were recorded or derived using GIS and weather stations. * Long-term persistence trends were tracked for individual trees and nests using aerial and ground surveys. * **Data Processing**: * The data underwent cleaning and validation before analysis. * Statistical analyses included Kaplan-Meier survival models and Cox proportional hazards models, implemented in R (version 4.3.0). * Continuous variables were scaled and centered to improve interpretability and model performance. --- ## Usage Notes * Missing data are represented as `NA`. * Data files are provided in `.xlsx` format, and variable definitions can be found in the respective `_Codes` sheets. * Refer to the accompanying R scripts for details on analysis workflows. ## Code/software For data analysis and replication of the results presented in the manuscript, the following software and packages were used: * **R** (version 4.3.0): A free and open-source statistical programming language used for data cleaning, visualization, and statistical modeling. * Key R packages used: * **survival**: For Kaplan-Meier survival analysis. * **coxme**: For Cox proportional hazards modeling. * **ggplot2**: For data visualization. * **dplyr** and **tidyr**: For data manipulation and cleaning.