Biodiversity loss has been among the central topics in public, policy, and scientific debate for several decades. While its accelerating pace and impacts are well recognised, translating the vast amounts of biodiversity data into reliable indicators that can inform policy remains a challenge, requiring considerable time and technical effort.
That’s where B-Cubed comes in. Through our information campaign, “How to Be Cubed,” we will explore how our automated data pipelines transform raw biodiversity data into meaningful indicators for decision-makers. We will follow the pathway from building species occurrence cubes, to modelled cube approaches, and biodiversity indicators, exemplifying how our data pipelines support biodiversity monitoring. You can learn all about our project results from our legacy booklet.
Understanding biodiversity through indicators
B-Cubed translates the complex multidimensional information contained in its aggregated or modelled data cubes into biodiversity indicators. These meaningful measures help policymakers and other stakeholders understand biodiversity status and trends. All of the indicators are contained within the b3verse – an open-source software ecosystem that enables the streamlined production of biodiversity indicators based on occurrence cubes. There are four main indicator packages:
1. Biodiversity indicators (b3gbi)
The b3gbi R package is a computational tool designed to efficiently analyse large-scale species occurrence data, such as those from GBIF, to produce consistent insights into global biodiversity trends. It works by processing species occurrence cubes to automatically calculate standardised indicators (e.g., species richness and change over time), quantify uncertainty, and
present results through customisable maps and time series.
How can b3gbi benefit biodiversity policy?
It can improve the accessibility, reproducibility, and reliability of biodiversity analyses to better support conservation and environmental decision-making.
2. Phylogenetic diversity indicators (pdindicatoR)
The pdindicatoR package was developed to facilitate producing phylogenetic diversity (PD) maps from user-provided phylogenetic trees and GBIF species occurrence cubes. Phylogenetic diversity (PD) is a measure of biodiversity which takes evolution into account. The workflow output highlights phylogenetic diversity hotspots and quantifies the proportion of PD currently safeguarded within existing protected areas.
How can pdindicatoR benefit biodiversity policy?
It can be used as a tool to locate hotspots of phylogenetic diversity, guide conservation planning by identifying priority regions for protection, and assisting with long-term monitoring and reporting on PD conservation status.
3. Impacts of alien taxa indicators (impIndicator)
The impIndicator package presents a straightforward method for estimating the harm caused by alien (non-native) species, using freely available data and a clear, step-by-step process. By combining information about where these alien species occur (from online databases) with the evaluations of their ecological effects, this practical tool gives an “impact value”, that reflects both how widespread a species is and how serious its negative effects can be.
How can impIndicator benefit biodiversity policy?
It can help identify which non-native species are likely to be problematic, allowing managers to address the urgent future problems. This helps guide actions to protect biodiversity and maintain healthy ecosystems.
4. Indicators of robustness (dubicube)
The dubicube package tackles the need to assess the reliability and interpretability of biodiversity indicators derived from species occurrence data by implementing methods to evaluate data robustness, identify limitations in spatial, temporal, and taxonomic coverage, and quantify how sensitive indicators are to individual species.
How can dubicube benefit biodiversity policy?
It can reduce the risk of overconfidence in indicator results and improve transparency in analysis.
Additional packages such as ebvcube and trias extend functionality toward integration with global data infrastructures and specific policy-relevant domains. You can learn how to use the packages and check out the example workflow for calculating indicators in our practical guide. You can also check out the B-Cubed indicator factsheets to get acquainted with the different indicators and their role in the workflow.
We would love to hear your feedback on B-Cubed’s indicators, so feel free to email us at info@b-cubed.eu or check out the GitHub pages for b3gbi, pdindicatoR, impIndicator, and dubicube.
In case you have any other questions, check out our FAQ page.
