South African global environmental change literature 2000-2018

These data were used to assess how much research has been directed towards biological invasions in South Africa relative to other elements of global change and form part of a published book chapter. Using Web of Science, we systematically reviewed literature relevant to South African ecosystems published between 2000 and 2018 and relating to biological invasions, climate change, overharvesting, habitat change, pollution, and/or atmospheric CO2 (search term details are provided below). We identified 1149 relevant papers, which appear in this dataset. These were scored in terms of their coverage of drivers and driver interactions that affect biodiversity or ecosystem services. Search terms used to identify relevant global change literature in South Africa We used an advanced search in the ISI Web of Science to identify potentially relevant research in South Africa. We constrained the search to use only the Science Citation index Expanded and Book Citation Index - Science, using a Timespan of 2000-2018. We performed six separate searches for each of the drivers and combined the results, removing any duplicate studies that were identified. The search terms used were: For Alien species TS = ((Invasiv* OR alien* OR exotic* OR non-native OR "non native" OR non-indigenous OR "non-indigenous" AND species) AND "South Africa*" AND (ecosystem* OR biodiversity) AND (impact* OR effect* OR trend*)) For Climate change TS = (“climate change” AND “South Africa*” AND (ecosystem* OR biodiversity) AND (impact* OR effect* OR trend*)) For CO2 TS = ((CO2 OR "carbon dioxide") AND "South Africa*" AND (ecosystem* OR biodiversity) AND (impact* OR effect* OR trend*)) For Overharvesting TS = ((*harvesting OR *exploitation OR "resource use" OR "resource-use" OR hunting OR fishing OR extract*) AND "South Africa*" AND (ecosystem* OR biodiversity) AND (impact* OR effect* OR trend*)) For Pollution TS = (((pollut* OR *toxic* OR chemic* OR nitro* OR nitr* OR N2 OR phosph* OR sewage OR sewerage OR *plastic* OR acid*) AND "South Africa*" AND (ecosystem* OR biodiversity) AND (impact* OR effect* OR trend*))) For Habitat change TS = (("habitat change" OR "land cover" OR "land transformation" OR "land use" OR landuse OR land-use OR land-cover OR agriculture OR forestry OR mining OR ploughing OR erosion OR *fire OR disturbance* OR desertification OR aridification OR degradation OR "habitat alteration" OR fragmentation OR *trawling) AND "South Africa*" AND (ecosystem* OR biodiversity) AND (impact* OR effect* OR trend*)) For each unique publication identified, we read the title and abstract and removed any studies that took place outside of South Africa (including those conducted in neighbouring countries such as Namibia, Swaziland and Lesotho) as well as those deemed to be beyond the study scope. The latter category included experimental studies with no clear link to a future time period (e.g. impacts of very high carbon dioxide concentrations), studies that valued ecosystem services as well as those that described restoration efforts, purely ecological studies, with no direct consideration of change drivers, studies that detailed management options for biodiversity and ecosystem services (including studies on biological control of invasive species) and descriptions of new alien species or their establishment. The final dataset that was scored consisted of 1149 papers. For each paper, we read the title and abstract and recorded (binary 0 or 1) as many direct driver effects on biodiversity and ecosystem services (out of the possible 6) or interactions of drivers. For example, a paper that demonstrated the impacts of drought on pollutant concentrations, with subsequent eutrophication and algal blooms would be counted as a direct effect of pollution on biodiversity and ecosystem services as well as an interaction of “Climate on pollution” and “Pollution on habitat”. We also recorded the environment (terrestrial, freshwater or marine and estuarine) in which the study took place.This research was supported by the DST-NRF Centre for Invasion Biology and the South African National Research Foundation (Grant 109467 and 118591)