DOI: 10.5061/dryad.8pk0p2ntj
title: Data from: Using joint species distribution modelling to identify climatic and non-climatic drivers of Afrotropical ungulate distributions

description: The relative importance of the different processes that determine the
 distribution of species and the assembly of communities is a key question
 in ecology. The distribution of any individual species is affected by a
 wide range of environmental variables as well as through interactions with
 other species; the resulting distributions determine the pool of species
 available to form local communities at fine spatial scales. A challenge in
 community ecology is that these interactions (e.g., competition,
 facilitation, etc.) often are not directly measurable. Here, we used
 Hierarchical Modelling of Species Communities (HMSC), a recently developed
 framework for joint species distribution modelling, to estimate the role
 of biotic effects alongside environmental factors using latent variables.
 We investigate the role of these factors determining species distributions
 in communities of Artiodactyla, Perissodactyla and Proboscidea in the
 Afrotropics, an area of peak species richness for hoofed mammals. We also
 calculate pairwise trait dissimilarity between these species, from a
 mixture of morphological and behavioural traits, and investigate the
 relationship between dissimilarity and estimated residual co-occurrence in
 the model. We find that while ungulate distributions appear to be
 predominantly determined (~70%) by climatic variables, such as
 precipitation, a substantial proportion of the variance in ungulate
 species distributions (~30%) can also be attributed to modelled latent
 variables that likely represent a combination of dispersal barriers and
 biotic factors. Although we find only a weak relationship between residual
 co-occurrence and trait dissimilarity, we suggest that our results may
 show evidence that biotic factors, likely influenced by historical
 barriers to species dispersal, are important in determining species
 communities over a continental area. The HMSC framework can be used to
 provide insight into factors affecting community assembly at broad scales,
 and to make more powerful predictions about future species distributions
 as we enter an era of increasing impacts from anthropogenic change.
description: Data were collected as described in the manuscript.  
description: # Data from: **Climatic Variables Alone do not Determine Ungulate
 Distributions in the Afrotropics** --- This repository contains all data
 used for the paper "Climatic Variables Alone do not Determine
 Ungulate Distributions in the Afrotropics". ## Description of the
 Data and file structure
 **Presab_plus_climate_variables_PROTECTEDAREASONLY_Res10arcminutes.csv,
 \_OpenHabitats.csv, \_TropicalForests.csv** These three files contain
 presence/absence data for all ungulate species included in the analysis
 for all points in the **Afrotropics at 10 arcminute resolution**, with
 data derived from IUCN species range maps processed using the letsR
 package. Additionally, they contain environmental data for all points in
 the matrix for all 19 bioclimatic variables (from WorldClim) and land
 cover data (from the FAO Land and Water Division.)
 **Trait_Data_AllUngulates.csv** This file contains all trait data used in
 the calculation of Gower's Distance. ## Sharing/Access Information
 Other data (i.e. shp files for species ranges, protected areas boundaries)
 used in this analysis is not posted in order to comply with policies on
 reposting and/or redistribution of unmodified data, however, for more
 details on these, please feel free to contact the corresponding author
 (**Alex Cranston**) All data was derived from the following sources: 1.
 Shapefiles for species' distributions (except rhinos) taken from:
 IUCN. (2018). The IUCN Red List of Threatened Species (spatial data).
 Version 2018-2 .
 [https://www.iucnredlist.org](https://www.iucnredlist.org). Downloaded on
 9 November 2021. Rhino distributions taken from Rookmaaker, K., &
 Antoine, P.-O. (2012). New maps representing the historical and recent
 distribution of the African species of rhinoceros: Diceros bicornis,
 Ceratotherium simum and Ceratotherium cottoni. Pachyderm, 52, 91–96.
 Retrieved from
 [https://pachydermjournal.org/index.php/pachyderm/article/view/311](https://pachydermjournal.org/index.php/pachyderm/article/view/311). 2. Global Land Cover map taken from: Latham, J., Cumani, R., Rosati, I., & Bloise, M. (2014). FAO Global Land Cover (GLC-SHARE) Beta-Release 1.0 Database. FAO Land and Water Division. [https://data.apps.fao.org/map/catalog/sru/api/records/7f4f5ce4-9a3e-406f-bae6-efe63867329a](https://data.apps.fao.org/map/catalog/sru/api/records/7f4f5ce4-9a3e-406f-bae6-efe63867329a) 3. Bioclimatic variables taken from: 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(12), 4302-4315. [https://doi.org/https://doi.org/10.1002/joc.5086](https://doi.org/https://doi.org/10.1002/joc.5086) 4. Shapefiles for African protected areas taken from: UNEP-WCMC, & IUCN. Protected Planet: The World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) [Online]. UNEP-WCMC and IUCN. Retrieved June 2022 from [www.protectedplanet.net](http://www.protectedplanet.net) 5. Shapefiles for African biomes taken from: Dinerstein, E., Olson, D., Joshi, A., Vynne, C., Burgess, N. D., Wikramanayake, E., Hahn, N., Paminteri, S., Hedao, P., Noss, R., Hansen, M., Locke, H., Ellis, E. C., Jones, B., Barber, C. V., Hayes, R., Kormos, C., Martin, V., Crist, E., Sechrest, W., Price, L., Baillie, J. E. M., Weeden, D., Suckling, K., Davis, C., Sizer, N., Moore, R., Thau, D., Birch, T., Potapov, P.,Turubanova, S., Tyukavina, A., de Souza, N., Pintea, L., Brito, J. C., Llewellyn, O. A., Miller, A. G., Patzelt, A., Ghazanfar, S. A., Timberlake, J., Klser, H., Shennan-Farpn, Y., Kindt, R., Lilles, J. B., van Breugel, P., Graudal, L., Voge, M., Al-Shammari, K. F., & Saleem, M. (2017). An ecoregion-based approach to protecting half the terrestrial realm. BioScience, 67(6), 534-545. [https://doi.org/10.1093/biosci/bix014](https://doi.org/10.1093/biosci/bix014) 6. Trait data for body mass and body length taken from: Soria, C. D., Pacifici, M., Di Marco, M., Stephen, S. M., & Rondinini, C.. 2021. COMBINE: a coalesced mammal database of intrinsic and extrinsic traits. Ecology 102( 6):e03344. 10.1002/ecy.3344 7. Trait data on diet mostly taken from: Gagnon, M., Chew, A. E., (2000) Dietary Preferences in Extant African Bovidae, Journal of Mammalogy, 81(2), 490511,[https://doi.org/10.1644/1545-1542(2000)081&lt;0490:DPIEAB&gt;2.0.CO;2](https://doi.org/10.1644/1545-1542\(2000\)081&lt;0490:DPIEAB&gt;2.0.CO;2) 8. Additional trait data on diet estimated using Schlitter, D. A., Ferguson, A. W., & McDonough, M. M. (2014). Mammals of Africa (Vol. I-VI.). Journal of Mammalogy, 95(6), 1299-1303.999. 9. Additional trait on migratory behaviour taken from Abraham, J. O., Hempson, G. P., Faith, J. T., & Staver, A. C.(2022). Seasonal strategies differ between tropical and extratropical herbivores. Journal of Animal Ecology, 91, 681–692. [https://doi.org/10.1111/1365-2656.13651](https://doi.org/10.1111/1365-2656.13651)