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Transforming biodiversity governance through improving evidence and diversifying values of nature in scenarios and models
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Abstract
The Kunming-Montreal Global Biodiversity Framework (KM-GBF) sets ambitious 2030 targets and 2050 goals but lacks the scenario and modelling infrastructure needed to link national actions to global outcomes. Tracing the evolution of biodiversity scenarios and models, from Limits to Growth, the Millennium Ecosystem Assessment and the SSP-RCP framework to the Nature Futures Framework (NFF), we review 65 modelling resources spanning biodiversity, ecosystems, ecosystem services, drivers and integrated systems across terrestrial, freshwater and marine realms. We assess their capacity to integrate the state of nature relevant to KM-GBF Goals and the drivers and interventions of the 2030 action targets to assess whether models can inform the National Biodiversity Strategies and Action Plans and National Reports for progress tracking and policy evaluation. We also analyse scenario analysis capabilities and how models reflect diverse values of nature from global to subnational scales with policy-relevant applications. We find that substantial technical capacity exists in the reviewed models to inform KM-GBF using the NFF. However, models have limited capacity in detecting changes in nature and attributing those changes to specific drivers or interventions. We identify three priorities for building a coherent evidence infrastructure: (1) integrating scenario analysis across the full KM-GBF policy cycle across scales; (2) standardizing causally informed monitoring and modelling to generate conservation evidence; and (3) strengthening cross-sectoral, multilevel coordination among scientific and policy communities. Coordinated, interoperable model development alongside continued innovation, sustained by institutional commitment and capacity-building, can transform the KM-GBF from an aspiration into implementation mechanisms for realizing equitable nature-positive futures.
DOI
https://doi.org/10.31223/X5F204
Subjects
Life Sciences
Keywords
scenarios, models, indicators, Global Biodiversity Framework, Nature Futures Framework, detection-and-attribution science, multiscale, policy support
Dates
Published: 2026-06-07 16:49
Last Updated: 2026-10-05 14:22
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License
CC-BY Attribution-NonCommercial 4.0 International
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Conflict of interest statement:
None
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