Ramm, Katharina; Raymond, Joanna; Brown, Calum; Arneth, Almut; Rounsevell, Mark D A: Biodiversity Pressure Index (BPI) for Europe for three different SSP-RCP scenarios (2020-2100) [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.997283 (dataset in review)
Abstract:
The BPI (Biodiversity Pressure Index) is a European dataset on annual human pressure exerted on biodiversity between 2020 and 2100 with a spatial resolution of ~ 1 km at the equator. We have produced data for three different SSP-RCP scenarios (SSP1-RCP2.6, SSP3-RCP7.0, SSP5-RCP8.5). The scenarios are a combination of climate projections, mainly based on CO2 emissions (RCP scenarios) and potential future developments of anthropogenic drivers on climate change (SSP scenarios). The SSP-RCP combinations are for example used in IPCC assessments: https://www.ipcc.ch/report/sixth-assessment-report-cycle/. The data shows the potential human pressure per pixel for terrestrial land areas in Europe. It is based on model products from CRAFTY-EU, PLUM v2, LPJ-GUESS, ISIMIP3 and observational/statistical data on mining and pesticides, all 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 under different future pathways.
The BPI consists of a set of datasets (land use, land use transitions, fertiliser use, pesticides use, nighttime lights, imports, mining, precipitation anomaly, temperature anomaly). Each of them was harmonised to matching projection, resolution, extent and subsequently normalised on a scale from 0 to 1+, where 1 is the global maximum of 2020. Meaning that values above one are higher than the global maximum in the baseline year. Each individual input variable was then summed up per pixel resulting in the cumulative BPI. The data was processed using R.
References:
CRAFTY [webpage]. https://landchange.imk-ifu.kit.edu/CRAFTY
ISIMIP [webpage]. https://www.isimip.org/
LPJ-GUESS [webpage]. https://web.nateko.lu.se/lpj-guess/
PLUM [webpage]. https://landsymm.earth/plum
Brown, Calum; Seo, Bumsuk; Rounsevell, Mark D A (2019): Societal breakdown as an emergent property of large-scale behavioural models of land use change. Earth System Dynamics, 10(4), 809-845, https://doi.org/10.5194/esd-10-809-2019
Coverage:
Latitude: 54.000000 * Longitude: 14.800000
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Binary Object | Binary | Ramm, Katharina | |||
| 2 | Binary Object (Media Type) | Binary (Type) | Ramm, Katharina | |||
| 3 | Binary Object (File Size) | Binary (Size) | Bytes | Ramm, Katharina | ||
| 4 | File content | Content | Ramm, Katharina |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0) (License comes into effect after moratorium ends)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
486 data points