• Energy Research

This repository contains the supplementary files for: Allen BJ, Hill DJ, Burke AM, Clark M, Marchant R, Stringer LC, Williams DR, Lyon C. 2024. Projected future climatic forcing on the global distribution of vegetation types. Philosophical Transactions of the Royal Society B. Description of files This repository contains the BIOME4 output files, the R code used to analyse them, and a selection of data tables summarising the results. netCDFs.zip - The raw BIOME4 outputs cleaned.zip - The cleaned biome datasets, as .csv files, describing the biome attributed to each cell in each time slice, for biomes and megabiomes, and with different human footprints (from the HYDE dataset) removed ranges.zip - Summary tables describing the latitudinal ranges, in each hemisphere, of each biome for each time slice centroids.zip - Summary tables describing the shift of each biome's centroid, in each hemisphere, between time slices counts.zip - Summary tables describing the number of grid cells not adjacent to their attributed biome in the previous time slice biome_conversion.txt - The table for converting between biome and megabiome attribution R_code.zip - All R code used to conduct analyses Description of R code The R code is subdivided into the following files: Read_nc.R - Code to read in netCDF files (containing BIOME4 outputs), clean, add area of cells, and convert to .csv Read_footprint.R - Code to cut the HYDE anthrome footprints out of the BIOME4 outputs Matrix_comparison.R - Code calculating the proportion of area changing biomes over time (creates Figure 2a & 3a) Biome_overlap.R - Code calculating the overlap of area attributed to each biome over time (creates Figure 2b & 3b) Unoccupiable_cells.R - Code calculating the proportion of cells attributed to a biome which are not adjacent to that same biome in the previous time slice (creates Figure S5) Biome_share.R - Code showing the change in total area for each biome over time (creates Figure S6 & S7) Centroid_shift.R - Code calculating the latitudinal ranges and centroids for each biome over time (creates Figure S8) Patchiness.R - Code calculating the number of patches of each biome over time (creates Figure S9)

This repository contains the supplementary files for: Allen BJ, Hill DJ, Burke AM, Clark M, Marchant R, Stringer LC, Williams DR, Lyon C. 2024. Projected future climatic forcing on the global distribution of vegetation types. Philosophical Transactions of the Royal Society B. Description of files This repository contains the BIOME4 output files, the R code used to analyse them, and a selection of data tables summarising the results. netCDFs.zip - The raw BIOME4 outputs cleaned.zip - The cleaned biome datasets, as .csv files, describing the biome attributed to each cell in each time slice, for biomes and megabiomes, and with different human footprints (from the HYDE dataset) removed ranges.zip - Summary tables describing the latitudinal ranges, in each hemisphere, of each biome for each time slice centroids.zip - Summary tables describing the shift of each biome's centroid, in each hemisphere, between time slices counts.zip - Summary tables describing the number of grid cells not adjacent to their attributed biome in the previous time slice biome_conversion.txt - The table for converting between biome and megabiome attribution R_code.zip - All R code used to conduct analyses Description of R code The R code is subdivided into the following files: Read_nc.R - Code to read in netCDF files (containing BIOME4 outputs), clean, add area of cells, and convert to .csv Read_footprint.R - Code to cut the HYDE anthrome footprints out of the BIOME4 outputs Matrix_comparison.R - Code calculating the proportion of area changing biomes over time (creates Figure 2a & 3a) Biome_overlap.R - Code calculating the overlap of area attributed to each biome over time (creates Figure 2b & 3b) Unoccupiable_cells.R - Code calculating the proportion of cells attributed to a biome which are not adjacent to that same biome in the previous time slice (creates Figure S5) Biome_share.R - Code showing the change in total area for each biome over time (creates Figure S6 & S7) Centroid_shift.R - Code calculating the latitudinal ranges and centroids for each biome over time (creates Figure S8) Patchiness.R - Code calculating the number of patches of each biome over time (creates Figure S9)

Thought for food To have any hope of meeting the central goal of the Paris Agreement, which is to limit global warming to 2°C or less, our carbon emissions must be reduced considerably, including those coming from agriculture. Clark et al. show that even if fossil fuel emissions were eliminated immediately, emissions from the global food system alone would make it impossible to limit warming to 1.5°C and difficult even to realize the 2°C target. Thus, major changes in how food is produced are needed if we want to meet the goals of the Paris Agreement. Science , this issue p. 705

Thought for food To have any hope of meeting the central goal of the Paris Agreement, which is to limit global warming to 2°C or less, our carbon emissions must be reduced considerably, including those coming from agriculture. Clark et al. show that even if fossil fuel emissions were eliminated immediately, emissions from the global food system alone would make it impossible to limit warming to 1.5°C and difficult even to realize the 2°C target. Thus, major changes in how food is produced are needed if we want to meet the goals of the Paris Agreement. Science , this issue p. 705

Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO 2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services. This article is part of the theme issue ‘Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere’.

Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO 2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services. This article is part of the theme issue ‘Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere’.

AbstractAgriculture is the largest single source of environmental degradation, responsible for over 30% of global greenhouse gas (GHG) emissions, 70% of freshwater use and 80% of land conversion: it is the single largest driver of biodiversity loss (Foley JA, Science 309:570–574, 2005, Nature 478:337–342, 2011; IPBES. Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. IPBES Secretariat, Bonn, 2019; Willett W et al. The Lancet 393:447–492, 2019). Agriculture also underpins poor human health, contributing to 11 million premature deaths annually. While too many still struggle from acute hunger, a growing number of individuals, including in low to middle-income countries (LMICs), struggle to access healthy foods. Greater consideration for, and integration of, biodiversity in agriculture is a key solution space for improving health, eliminating hunger and achieving nature-positive development objectives.This rapid evidence review documents the best available evidence of agriculture’s relationships with biodiversity, drawing on the contributions of leading biodiversity experts, and recommends actions that can be taken to move towards more biodiversity/nature-positive production through the delivery of integrated agricultural solutions for climate, biodiversity, nutrition and livelihoods. The analysis, which takes a whole-of-food-system approach, brings together a large body of evidence. It accounts for aspects not typically captured in a stand-alone primary piece of research and indicates where there are critical gaps.