Table 3 A non-exhaustive list of potential uses of the bii4africa dataset.

Quantifying ecosystem integrity/condition across space and through time

The first goal of the post-2020 Global Biodiversity Framework is to increase the ‘area, connectivity and integrity of natural ecosystems’. The dataset can be used towards assessing ecosystem condition, e.g., mapping the Biodiversity Intactness Index²⁸.

Assessing the severity of functional decline for the IUCN Red List of Ecosystems

Aggregated indices of ecosystem health or condition are proposed as one option for quantifying functional decline for the IUCN Red List of Ecosystems⁵⁴. The dataset could enable such a quantification.

Quantifying relative population abundance and biodiversity composition indicators

This dataset could be used towards quantifying several composite biodiversity indicators, e.g., Essential Biodiversity Variables⁵⁵; Multidimensional Biodiversity Index¹²; Ecosystem Integrity Index^56,57; Biodiversity Intactness Index^28,29; and Mean Species Abundance metric (GLOBIO)^18,43. Several of these are also proposed indicators in the Global Biodiversity Framework.

Setting conservation and restoration goals and/or monitoring progress towards these goals

The dataset could be used to assess progress towards restoring ‘intactness’ in a region. The data could also be used in prioritisation exercises to identify ecosystems for restoration action to maximise improvements in biodiversity intactness.

Assessing the impact of regional development plans

Large-scale infrastructure and agriculture projects are planned across sub-Saharan Africa (e.g., Laurance et al.⁵⁸). This dataset could be used to predict the impacts of such development plans on biodiversity intactness.

Considering biodiversity sensitivity to development

The data could identify the types of taxa that are particularly sensitive to development, to inform Environmental Impact Assessments and other development plans.

Identifying indicator species groups

Species groups with lower intactness scores are more vulnerable to environmental or developmental change, and monitoring their populations could give early warnings of system degradation.

Assessing trends in how diverse species respond to land use activities

The data could be analysed to test hypotheses and explore trends across species groups and/or land uses.

Species ecological (as opposed to taxonomic) classifications

The species response groups presented in this dataset (Supplementary Table 1) may be useful for a range of applications that require species to be organised into ‘functional’ (as opposed to purely taxonomic) categories.

Zoonotic disease risk and mitigation assessments

The dataset could be used in identifying and monitoring species groups (and areas, if spatialised) to prevent zoonotic and epizootic disease outbreaks.

Characterising novel ecosystems

Intactness scores >1 depict species groups that respond positively to human land use activities, thus contributing to understanding novel ecosystems⁵⁹.

Parameterising, calibrating and validating models of biodiversity in a changing world

Biodiversity models are used to predict biodiversity patterns across space and through time (e.g., Di Marco et al.⁶⁰; Harfoot et al.⁶¹; Schipper et al.¹⁸) under changing land use conditions. This dataset could be used to parameterise, calibrate, or validate such models.

Climate change research

The approach taken in this paper offers opportunities for natural and/or experimental designs to test interactions of biodiversity, land use and climate change across variable spatial and temporal scales.

Informing future research and training in biodiversity

The species groups and land uses for which there were either few scores or large expert score variability highlight knowledge gaps that require further study. These knowledge gaps could also be used to guide future scientist training efforts.

Comparison with other regions, taxonomic groups or time periods

A similar expert-elicited approach could be used to estimate intactness scores for other regions/taxonomic groups (e.g., invertebrates), allowing for comparison with this dataset. The approach could be repeated in the future to assess how knowledge on land use impacts on biodiversity abundance has changed.

List of biodiversity experts to contact for data, collaboration, etc.

The 200 participating experts (see author list and contributions, and https://bii4africa.org/category/experts/) can serve as points of contact for global initiatives looking to aggregate data or build collaborations.