• Energy Research

Abstract Limiting global warming to a 1.5°C temperature rise requires drastic emissions reductions and removal of carbon-dioxide from the atmosphere. Most modelled pathways for 1.5°C assume substantial removals in the form of biomass energy with carbon capture and storage, which brings with it increasing risks to biodiversity and food security via extensive land-use change. Recently, multiple efforts to describe and quantify potential removals via ecosystem-based approaches have gained traction in the climate policy discourse. However, these options have yet to be evaluated in a systematic and scientifically robust way. We provide spatially explicit estimates of ecosystem restoration potential quantified with a Dynamic Global Vegetation Model. Simulations covering forest restoration, reforestation, reduced harvest, agroforestry and silvopasture were combined and found to sequester an additional 93 Gt C by 2100, reducing mean global temperature increase by ∼0.12°C (5%–95% range 0.06°C–0.21°C) relative to a baseline mitigation pathway. Ultimately, pathways to achieving the 1.5°C goal garner broader public support when they include land management options that can bring about multiple benefits, including ecosystem restoration, biodiversity protection, and resilient agricultural practices.

JULES is a community model available for use after registering on the JULES repository (https://code.metoffice.gov.uk/trac/jules). The model version used here was r9448, which is a branch of vn4.8 with updates to represent harvesting of bioenergy crops and for running IMOGEN in inverse mode (using specified temperature pathways instead of specified concentration pathways). To use JULES-IMOGEN, patterns from 34 GCMs are needed, which are available from https://doi.org/10.5285/343885af-0f5e-4062-88e1-a9e612f77779. JULES requires a series of input files (initial conditions, model grid, CO2 concentration, land-use per grid cell, soil parameters, etc.). These are provided in the “ancillary_files” directory of the dataset. JULES can be run with a system called Rose, which stores model settings. We also include an excel spreadsheet with the suites used for the Harper et al. (2018) paper. The suites are available from https://code.metoffice.gov.uk/trac/roses-u (registration required). The original IMAGE land use data is available from https://data.knmi.nl/datasets?q=PBL. We used v17 land fractions from SSP2-SPA0-RCP1.9 and SSP2-SPA2-RCP2.6. These were regridded from half degree to the N48 resolution using ESMF Regrid patch interpolation method from NCAR Command Language (http://ncl.ucar.edu/Document/Functions/ESMF/ESMF_regrid.shtml). The actual fractions used in the simulations are in both the input and output files. For further details, see Harper et al. (https://doi.org/10.1038/s41467-018-05340-z). The experimental design is the same as in Comyn-Platt et al. (https://doi.org/10.1038/s41561-018-0174-9), which also has a linked dataset for the historical period. This dataset includes six sets of model output from JULES/IMOGEN simulations. Each set includes output from JULES (the Joint UK Land Environment Simulator) run with 34 climate change patterns from 2000-2099. The outputs provide carbon stocks and variables related to the surface energy budget to understand the implications of land-based climate mitigation.

Many attempts to scale conservation actions have failed to deliver their intended benefits, caused unintended harm or later been abandoned, hampering efforts to bend the curve on biodiversity loss. Here we encourage those calling for scaling to pause and reflect on past scaling efforts, which offer valuable lessons: the total impact of an action depends on both its effectiveness and scalability; effectiveness can change depending on scale for multiple reasons; feedback processes can change socio-ecological conditions influencing future adoption; and the drive to scale can incentivize bad practices that undermine long-term outcomes. Cutting across these themes is the recognition that monitoring scaling can enhance evidence-informed adaptive management, reporting and research. We draw on evidence and concepts from disparate fields, explore new linkages between often isolated concepts and suggest strategies for practitioners, policymakers and researchers. Reflecting on these five lessons may help in the scaling of effective conservation actions in responsible ways to meet the triple goals of reversing biodiversity loss, combating climate change and supporting human wellbeing.

Abstract Nature-based solutions to climate change are growing policy priorities yet remain hard to quantify. Here we use remote sensing to quantify direct and indirect benefits from community-led agroforestry by The International Small group and Tree planting program (TIST) in Kenya. Since 2005, TIST-Kenya has incentivised smallholder farmers to plant trees for agricultural benefit and to sequester CO2. We use Landsat-7 satellite imagery to examine the effect on the historically deforested landscape around Mount Kenya. We identify positive greening trends in TIST groves during 2000-2019 relative to the wider landscape. These groves cover 27,198 hectares, and a further 27,750 hectares of neighbouring agricultural land is also positively influenced by TIST. This positive ‘spill-over’ impact of TIST activity occurs at up to 360m distance. TIST also benefits local forests, e.g. through reducing fuelwood and fodder extraction. Our results show that community-led initiatives can lead to successful landscape-scale regreening on decadal timescales.

Global Tipping Points is led by Professor Tim Lenton from the University of Exeter’s Global Systems Institute with the support of more than 200 researchers from over 90 organisations in 26 countries. This is the introduction to The Global Tipping Points Report, launched at COP28 on 6 December 2023. The report is an authoritative assessment of the risks and opportunities of both negative and positive tipping points in the Earth system and society. It was funded by the Global Systems Institute, University of Exeter and the Bezos Earth Fund. The full report can be accessed at: 10.5281/zenodo.15188117