/* DATA DESCRIPTION: Citation: Ramm, Katharina; Brown, Calum; Arneth, Almut; Rounsevell, Mark D A (2025): Global Biodiversity Pressure Index (BPI) between 1990 and 2020 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.969567 Abstract: The BPI (Biodiversity Pressure Index) is a global dataset on annual human pressure exerted on biodiversity between 1990-2020 at 0.1° (~ 10 km at the equator) spatial resolution. It shows the potential human pressure on a scale from 0-1 on a per pixel basis for terrestrial land areas. It is based on data products derived from observations, modelling and national statistics and integrates multiple open data streams reflecting the five IPBES-defined drivers of biodiversity loss: land use, resource extraction, climate change, environmental pollution and invasive species. The data of the BPI can be used to e.g. identify areas of high and low pressure, to perform regional and temporal change analysis of pressures and it can help to tailor protective measures to the underlying pressures and thus likely increase the success of biodiversity protection. The BPI is provided in two different forms: 1) Normalised [0-1] data in absolute terms, i.e. not transformed etc. 2) Normalised [0-1] data in relative terms, i.e. ranked data to reduce skewness The BPI consists of a set of global datasets. Each of them was harmonised to matching projection, resolution, extent and subsequently normalised on a scale from 0 to 1. Each individual input variable was then summed up per pixel resulting in the cumulative BPI. After the addition, the BPI was again normalised to [0-1]. For the relative BPI, we ranked all individual inputs in percentiles to reduce skewness of the data. All other processing steps were the same. The data was processed using R and Python. Keyword(s): biodiversity pressure; global; human pressures; IPBES drivers Supplement to: Ramm, Katharina; Brown, Calum; Arneth, Almut; Rounsevell, Mark D A (preprint): Expansion and increase of human pressures on global land ecosystems between 1990 and 2020. biorxiv;, 2026.04.16.718867v2, https://doi.org/10.64898/2026.04.16.718867 Source: Chatham House - 'resourcetrade.earth' (2023). https://resourcetrade.earth FAOSTAT - Pesticides Use (2023). Food and Agriculture Organization of the United Nations, https://www.fao.org/faostat/en/#data/RP Jackson, Alice; Edwards, D P; Morton, Oscar (2023): National spatial and temporal patterns of the global wildlife trade. Global Ecology and Conservation, 48, e02742, https://doi.org/10.1016/j.gecco.2023.e02742 Li, Xuecao; Zhou, Yuyu; Zhao, Min; Zhao, Xia (2020): A harmonized global nighttime light dataset 1992–2018. Scientific Data, 7(1), 168, https://doi.org/10.1038/s41597-020-0510-y Maus, Victor; Giljum, Stefan; da Silva, Dieison M; Gutschlhofer, Jakob; da Rosa, Robson; Luckeneder, Sebastian; Gass, Sidnei L B; Lieber, Mirko; McCallum, Ian (2022): An update on global mining land use. Scientific Data, 9(1), 433, https://doi.org/10.1038/s41597-022-01547-4 Muñoz Sabater, J (2019): ERA5-Land hourly data from 1950 to present [dataset]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/CDS.E2161BAC Tian, Hanqin; Bian, Zihao; Shi, Hao; Qin, Xiaoyu; Pan, Naiqing; Lu, Chaoqun; Pan, Shufen; Tubiello, Francesco N; Chang, Jinfeng; Conchedda, Giulia; Liu, Junguo; Mueller, Nathaniel; Nishina, Kazuya; Xu, Rongting; Yang, Jia; You, Liangzhi; Zhang, Bowen (2022): History of anthropogenic Nitrogen inputs (HaNi) to the terrestrial biosphere: a 5 arcmin resolution annual dataset from 1860 to 2019. Earth System Science Data, 14(10), 4551-4568, https://doi.org/10.5194/essd-14-4551-2022 Winkler, Karina; Fuchs, Richard; Rounsevell, Mark D A; Herold, Martin (2021): Global land use changes are four times greater than previously estimated. Nature Communications, 12(2501), https://doi.org/10.1038/s41467-021-22702-2 Coverage: MEDIAN LATITUDE: 0.000000 * MEDIAN LONGITUDE: 0.000000 * SOUTH-BOUND LATITUDE: -90.000000 * WEST-BOUND LONGITUDE: -180.000000 * NORTH-BOUND LATITUDE: 90.000000 * EAST-BOUND LONGITUDE: 180.000000 Event(s): GlobCover * LATITUDE START: 90.000000 * LONGITUDE START: -180.000000 * LATITUDE END: -90.000000 * LONGITUDE END: 180.000000 Comment: Data variables included in the BPI are: land use/cover (Winkler et al. 2021) land use/cover transitions (Winkler et al. 2021), mining (Maus et al. 2022), wildlife trade (Jackson et al. 2023), temperature and precipitation (ERA5 Land), fertiliser use (Tian et al. 2022), pesticides use (based on FAOSTAT), nighttime lights (Li et al. 2020), trade (Chatham House). Parameter(s): netCDF file (netCDF) * PI: Ramm, Katharina (https://orcid.org/0009-0005-4596-8917, katharina.ramm@kit.edu) netCDF file (File Size) [Bytes] (netCDF (Size)) * PI: Ramm, Katharina (https://orcid.org/0009-0005-4596-8917, katharina.ramm@kit.edu) File content (Content) * PI: Ramm, Katharina (https://orcid.org/0009-0005-4596-8917, katharina.ramm@kit.edu) Documentation file (DOCS) * PI: Ramm, Katharina (https://orcid.org/0009-0005-4596-8917, katharina.ramm@kit.edu) License: Creative Commons Attribution 4.0 International (CC-BY-4.0) (URI: https://creativecommons.org/licenses/by/4.0/) Status: Curation Level: Enhanced curation (URI: https://wiki.pangaea.de/wiki/Curation_levels) Size: 6 data points Files: All files referred to in data matrix can be downloaded in one go as ZIP or TAR (PANGAEA user account required). To download single files, use the filename from data matrix appended to "https://download.pangaea.de/dataset/969567/files/". */ netCDF netCDF (Size) [Bytes] Content DOCS BPI_1990_2020_absolute_values.nc 1.5 GBytes Normalised [0-1] data in absolute terms, i.e. not transformed etc. BPI_1990-2020_absolute_values_header.txt BPI_1990_2020_relative_values.nc 1.5 GBytes Normalised [0-1] data in relative terms, i.e. ranked data to reduce skewness BPI_1990-2020_relative_values_header.txt