DOI: 10.5061/dryad.82vs647
title: Data from: Consequences of climatic thresholds for projecting fire activity and ecological change

description: 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
 &gt; 50% exceeding this threshold by &gt; 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.
description: 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]\