Data from: Consequences of climatic thresholds for projecting fire activity and ecological change

Aim: Ecological properties governed by threshold relationships can exhibit heightened sensitivity to climate, creating an inherent source of uncertainty when anticipating future change. We investigated the impact of threshold relationships on our ability to project ecological change outside the observational record (e.g., the 21st century), using the challenge of predicting late‐Holocene fire regimes in boreal forest and tundra ecosystems. Location: Boreal forest and tundra ecosystems of Alaska. Time period: 850–2100 CE. Major taxa studied: Not applicable. Methods: We informed a set of published statistical models, designed to predict the 30‐year probability of fire occurrence based on climatological normals, with downscaled global climate model data for 850–1850 CE. To evaluate model performance outside the observational record and the implications of threshold relationships, we compared modelled estimates with mean fire return intervals estimated from 29 published lake‐sediment palaeofire reconstructions. To place our results in the context of future change, we evaluate changes in the location of threshold to burning under 21st‐century climate projections. Results: Model–palaeodata comparisons highlight spatially varying accuracy across boreal forest and tundra regions, with variability strongly related to the summer temperature threshold to burning: sites closer to this threshold exhibited larger prediction errors than sites further away from this threshold. Modifying the modern (i.e., 1950–2009) fire–climate relationship also resulted in significant changes in modelled estimates. Under 21st‐century climate projections, increasing proportions of Alaskan tundra and boreal forest will approach and surpass the temperature threshold to burning, with > 50% exceeding this threshold by > 2 °C by 2070–2099. Main conclusions: Our results highlight a high sensitivity of statistical projections to changing threshold relationships and data uncertainty, implying that projections of future ecosystem change in threshold‐governed ecosystems will be accompanied by notable uncertainty. This work also suggests that ecological responses to climate change will exhibit high spatio‐temporal variability as different regions approach and surpass climatic thresholds over the 21st century.READMECodeContains all the individual Matlab and R scripts, including customized functions, needed to conduct the analyses and produce the results presented in the main text of the manuscript.code.7zDataContains the ancillary data, pre-processed data, and citations for the raw datasets needed to conduct the analyses described in the manuscript.data.7zFiguresContains the figures from the publication in three different formats at 600 dpi resolution (MATLAB .fig, .jpeg, and .tif formats).figures.7zMetadataDocumentation/description of this archive using FGDC standards in an xml format, including geographic metadata for the raster datasets generated during the workflow of the analysis. This metadata was originally generated using Tkme (version 3.0.5) by Peter N. Schweitzer and updated using the USGS Metadata Wizard (version 2.0.3). The thesaurus used for keyword selection was the Global Change Master Directory (version 8.6, 2018).metadata.7zResultsSeries of results produced from processing the raw data stored in the '\data\' directory using the code provided.results.7zz_GISS-E2-R.7zOne of four 7z compressed files for the downscaled 30-yr climatologies for each GCM from 850-1850 CE. These are separated into individual files due to their large storage size (~5 GB). Each of these compressed files should be extracted into the following directories to recreate the analyses: ..\results\⁩3_gcm_30yr_climatologies⁩\used_in_analysis\[GCM]\z_MPI-ESM-LR.7zTwo of four 7z compressed files for the downscaled 30-yr climatologies for each GCM from 850-1850 CE. These are separated into individual files due to their large storage size (~5 GB). Each of these compressed files should be extracted into the following directories to recreate the analyses: ..\results\⁩3_gcm_30yr_climatologies⁩\used_in_analysis\[GCM]\z_MPI-ESM-P.7zThree of four 7z compressed files for the downscaled 30-yr climatologies for each GCM from 850-1850 CE. These are separated into individual files due to their large storage size (~5 GB). Each of these compressed files should be extracted into the following directories to recreate the analyses: ..\results\⁩3_gcm_30yr_climatologies⁩\used_in_analysis\[GCM]\z_MRI-CGCM3.7zFour of four 7z compressed files for the downscaled 30-yr climatologies for each GCM from 850-1850 CE. These are separated into individual files due to their large storage size (~5 GB). Each of these compressed files should be extracted into the following directories to recreate the analyses: ..\results\⁩3_gcm_30yr_climatologies⁩\used_in_analysis\[GCM]\Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: ARC-1023669, ARC-1023477, EF-1241846, EF-160635