Sustainable development and nature conservation take place in heterogenous socio-economic, environmental, and policy contexts characterized by unevenly distributed biodiversity1,2. Hence, conservation-related indicator maps calculated at the level of entire countries provide high-level overviews critical for raising awareness but often inform little about the management actions taken or needed at relevant scales3–6. Overcoming these limitations requires subnational maps based on steadily improving spatial data layers that account for the uneven distribution of biodiversity within countries. Such maps enable the assignment of responsibilities between parties and amongst conservation actors, reveal the need for complementarity in governance and action within and across state boundaries, and help ensure progress towards conservation and the Sustainable Development Goals (SDGs), while “leaving no one behind”, a core value and promise of the United Nations 2030 Agenda for Sustainable Development7. However, although available at increasing resolution, spatial data layers are not always used for breaking down indicators from the national scale to the scale at which policy-making, planning, and conservation happen.
Mountains are a textbook example in this context. They host exceptionally rich and functionally important biodiversity8,9; differ in their species’ diversity, spatial distribution10, and levels of endemism across latitudinal, longitudinal, and elevational gradients; and represent distinct social-ecological systems and landscape units11 that fall under different jurisdictions within and between countries. As such, they constitute pertinent conservation units and are acknowledged as a conservation priority12 in the face of accelerating global change. Yet, reporting on mountain ecosystem conservation in the context of the 2030 Agenda for Sustainable Development (SDG indicator 15.4.1, coverage by protected areas of important sites for mountain biodiversity13) is performed at the scale of entire nations. This is the case despite the existence of mountain delineations enabling the reporting on biodiversity protection at the level of mountain ranges and systems11,14. Here, we first address this gap by applying our most recent mountain inventory11 to generate spatially disaggregated annual maps of SDG indicator 15.4.1. By doing so, we use the mountain context as an example to illustrate the feasibility of spatially-explicit reporting. Secondly, as the site-based methodology for calculating mountain biodiversity conservation under the 2030 Agenda for Sustainable Development13 does not follow the area-based approach promoted by the Convention on Biological Diversity for calculating the protection of important areas for biodiversity in the new Kunming-Montreal Global Biodiversity Framework15, we perform area-based calculations of SDG indicator 15.4.1, compare the outcomes, and highlight differences and complementarities. To enable the use of these results by different groups within science, management, and policy, we developed a web platform to explore and compare spatio-temporal trends in the indicator at different scales and according to different calculations (https://www.gmba.unibe.ch/services/indicators/sdg_1541). Further, we provide one-page summaries for countries and mountain systems (Fig. 1, https://doi.org/10.5281/zenodo.6626930) and the R code to replicate the results at mountain range-level (https://github.com/GMBA-biodiversity/SDG15.4.1_Calculator) as open access material.
The disaggregation of SDG indicator 15.4.1 (Fig. 1A) demonstrates that with protection levels of Key Biodiversity Areas (KBAs, areas that contribute significantly to the global persistence of biodiversity16) varying from 0 to 100% across mountain ranges within countries (e.g. Bhutan or Switzerland, Table S1, Fig. 1A(2)&(4)) the information content of country-level indicators is limited. Disaggregated calculations reveal the spatial variability in biodiversity protection within and across countries that is concealed in unique country-level averages17 and indicate where – and by how much – protection needs to increase. Our approach thus enables annual reporting at spatial scales relevant for policymaking, prioritization, and management18, and contributes to improving the coherence of environmental policies for mountains across scales.
The disaggregation further reveals differences in how well countries protect their shares of transboundary mountain systems. In the European Alps, for example (Fig. 2), levels of protection are lower in Switzerland (≈ 30%) than in neighboring countries (≈ 70% (Italy) to > 95% (Germany)). Given that mountain ecosystems, species, and most environmental threats do not stop at political boundaries, such differences are likely to undermine conservation efforts. Our results therefore enable the informed assignment of responsibilities between parties and support the implementation of transboundary conservation as a process of international cooperation19,20 to overcome the social, economic, and environmental challenges that mountain biodiversity and its beneficiaries are facing.
Comparing the site- and area-based approaches for calculating the levels of protection of mountain KBAs (Table S1, Fig. S2, S3) reveals important differences between values and clarifies the consequences of the assumptions underlying current calculations. Differences between area- and site-based country-level values reach up to 45 percentage points (e.g. Mongolia 2020: 94.4 and 49.3%, respectively), which highlights the importance and consequences of methodological choices and calls for caution in the choice of reporting metrics. Most importantly, it calls for the careful interpretation of computed values. The current site-based approach calculates the average percentage coverage by protected areas (PAs) and Other Effective Area-based Conservation Measures of all mountainous KBAs within a country13. The “mountainous” classification is based on a minimum overlap of 5% between a KBA and terrain that is considered in mountains according to the mountain definition of the World Concervation Monitoring Center21. This implies that mountainous KBAs can consist of sizeable portions of hills and lowlands, especially if they are very large. Further, according to the site-based calculation, PAs are intersected with entire KBAs and not only with their strictly mountainous fractions. Accordingly, the percentage PA for any given KBA is attributed to mountains even when the PA covers the lowland parts of the mountain KBAs. Finally, the treatment of all KBAs as equal regardless of their size (Fig. 1D) helps account for the fact that smaller sites are particularly effective for conservation, especially for range restricted species. However, this can lead to inflated indicator values, in particular if the size distribution of KBAs is skewed towards smaller sites (Fig. S2, S3).
The area-based calculation sums the actual area of mountain terrain (sensu11,22) that intersects with KBAs and calculates what percentage of this terrain is protected. Accordingly, indicator values only increase with increasing area of protected mountain KBAs. By using a more conservative mountain definition that mostly excludes less rugged hills and lowlands, and by defining mountain KBAs as the actual area of land that is both mountainous and of significance for biodiversity, the area-based method overcomes the issue of reporting on the coverage by PAs of land that is not in fact in mountains. Area-based values thereby reflect efforts to protect areas of importance for the persistence of biodiversity that are both large and strictly located in mountains.
Currently, SDG indicator 15.4.1 quantifies at the national level the average percentage coverage by PAs of sites – as opposed to areas – important for mountain biodiversity persistence that are (partly) located in mountains13. The area-based calculation of SDG indicator 15.4.1 at subnational level sheds a different and complementary light on mountain biodiversity protection and highlights areas within mountain regions in need of subnational to international conservation efforts. Disaggregation and area-based calculations do not resolve the known shortcomings of KBAs for reporting on biodiversity conservation23,24. However, they support the area-based approach promoted within the Kunming-Montreal Global Biodiversity Framework and called for under e.g. headline indicator 3.1 (coverage of protected areas and OECMs) and associated component indicators. Moreover, the methodological considerations are holding analogously for other biodiversity-area definitions (e.g. Important Bird/Fungus/Plant Areas, Alliance for Zero Extinction sites, Prime Butterfly Areas24).
Our work on SDG indicator 15.4.1 highlights the need for transparency and caution with regard to the methods and assumptions underlying metrics for informing on sustainability and conservation. With our online resources, we offer tools to support science-based decision-making for complex mountain environments. We enable users to perform their own calculations and comparisons at the relevant scale, understand what indicators mean and conceal, and explore time series across mountains as well as differences based on various methods and assumptions. Our online resources support users across sectors and institutions in correctly interpreting the metrics on which decisions and management are based.