Data associated with "Mapping the planet's critical areas for biodiversity and people" Abstract: Meeting climate change, conservation, and sustainable development commitments requires consideration of synergies among targets. We evaluate the spatial congruence of ecosystems providing globally high levels of nature’s contributions to people (“critical natural assets”), terrestrial biodiversity, and areas of high development potential across 14 major sectors. Our results show that conserving 30% of global land area could meet representation goals for 26,709 terrestrial vertebrate species and provide 60% of ten of nature’s contributions to people. However, more than half of global land area (53%) is needed to meet biodiversity targets while maintaining near-current levels (90%) of nature’s contributions. Nearly half of these areas (23% of global land area) are also highly suitable for development, indicating potential conflicts among conservation, climate and development goals. This dataset contains outputs of spatial optimizations run using prioritizr (https://prioritizr.net/index.html) on February 27 2022. Datasets include tabular summaries (CSV format) and raster files (TIF format). Raster files are at a spatial resolution of 10 km unless otherwise indicated. Raster values are 0-1, where 1 means the grid cell was selected to achieve a particular target, 0 means the grid cell was not selected, and values between 0 and 1 indicate a grid cell was partially selected. Four variations of the spatial optimization were run. Each zip file contains the outputs from one of these four variations: NCP (Nature's contributions to people) only File name: output_NCP_only_27Feb2022.zip NCP only with protected areas (PAs) "locked in" (that is, PA grid cells always selected in every solution) File name: output_NCP_PA_27Feb2022.zip NCP and biodiversity File name: output_NCP_Biod_27Feb2022.zip NCP and biodiversity, with protected areas (PAs) locked in File name: output_NCP_Biod_PA_27Feb2022.zip Within each variation, 19 different spatial optimizations were run, with NCP targets ranging from 5%-95% in 5% increments. (0% and 100% were also included but those results are not meaningful.) For the NCP-only scenarios, 19 different spatial optimizations were run, each at several different spatial resolutions (2km, 3km, 5km, and 10km). This was not practical for the runs which included biodiversity due to the large number of species features (26,709), so those were run only at 10km. CSV filenames indicate the set of prioritizations summarized in the table. For example, "scenarios_10km_NCP_Biod.csv" contains a summary of the scenarios that include NCP as well as biodiversity. Raster filenames within ZIP files indicate the NCP (ecosystem service) target (for example, es-5 indicates a target of 5%) Whether biodiversity was included or not (for example, biod-1 indicates biodiversity was included, biod-0 indicates it was not) The land area budget constraint (no constraint was set, so budget-100) and the spatial resolution (10km) "solution_es-90_biod-1_budget-100_resolution-10km_10km.tif" Indicates an NCP target of 90% (es-90), biodiversity included, and a spatial resolution of 10km. Four additional files were included, which are the result of summing the rasters from each of one of the above four variations. Raster values range from 0-19, where 19 indicates grid cells selected in all scenarios, 0 indicates grid cells selected in 0 scenarios. Higher values (e.g. 19) indicate cells with the highest levels of NCP globally in the least amount of area. ncp_10km_sum - NCP only scenario, all rasters summed. ncp_pa_10km_sum - NCP scenario with protected areas locked in, all rasters summed. ncp_biod_10km_sum - NCP and biodiversity scenario, all rasters summed. ncp_biod_pa_10km_sum - NCP and biodiversity scenario, protected areas locked in, all rasters summed.

Version uploaded September 23 2022, as a test