Mean Species Abundance, Projections, Single Horizon, Global (v1.0)

Technical Description

The Mean Species Abundance (MSA) metric serves as an indicator of the intactness of local biodiversity. MSA values range from 0 to 1, with 1 indicating a completely intact species assemblage, and 0 indicating the local extinction of all original species. MSA is determined by comparing the current abundance of individual species under certain pressures to their abundance in an undisturbed or natural reference state. The calculation includes only those species that are present in the undisturbed state, and disregards any increase in species abundance from the reference to the impacted state. This approach prevents the indicator from being skewed by species that thrive in disturbed habitats. The MSA data is produced using the GLOBIO model by Schipper et al., 2020 which assesses local terrestrial biodiversity intactness using the mean species abundance (MSA) indicator, which is influenced by six human pressures: land use, road disturbance, fragmentation, hunting, atmospheric nitrogen deposition, and climate change. At the heart of the model are established quantitative relationships between these pressures and their impacts, derived from comprehensive terrestrial biodiversity databases.

GLOBIO integrates these pressure-impact relationships with data on past, present, or future levels of these pressures, often sourced from the IMAGE model which is an integrated assessment model that simulates the global environmental consequences of human activities. This integration produces maps that display MSA values for each pressure. These maps are then merged to calculate overall MSA values, as shown in the figure. Subsequently, MSA values are compiled into larger, user-defined regions. Additionally, the model quantifies how each pressure contributes to MSA losses in each region. Furthermore, GLOBIO incorporates a method to enhance the resolution of coarse-grained land-use data to finer-grained maps (currently at 10 arc-seconds; approximately 300 meters at the equator). This enhancement addresses the low spatial resolution of global land-use models, which typically overlook the spatial variability in land-use patterns. The downscaling process involves distributing regional totals or demands for each land-use type across grid cells within a region, prioritizing cells based on their suitability for the specific land-use type.

Schipper et al., 2020 evaluated the changes in terrestrial biodiversity intactness, as indicated by the mean species abundance (MSA) metric, across three shared socio-economic pathways (SSPs) combined with varying levels of climate change based on representative concentration pathways (RCPs). These pathways included a sustainability-oriented future (SSP1xRCP2.6), a middle of the road scenario (SSP3xRCP6.0), and a future dependent on fossil fuels (SSP5xRCP8.5). The GLOBIO model was initially updated to enhance its functionality which involved integrating new modules for downscaling land use, and quantifying impacts of hunting in the tropics, along with updated modules to assess the effects of climate change, land use, habitat fragmentation, and nitrogen pollution. Using the refined model, projections for terrestrial biodiversity intactness from 2015 to 2050 were generated, analyzing the effects of land use and climate changes associated with the selected scenarios.

This dataset contains the following fields:

• mean_species_abundance: The projected mean species abundance for a location represented as a floating point number between 0 to 1. A score of 0 means that the area is projected to be completely destroyed. A score of 1 means that the area is projected to be largely intact.