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Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models
Open accessPublished version of a preprint
Abstract
Abstract. Recent climate changes increases fire-prone weather conditions and likely affects fire occurrence, which might impact ecosystem functioning, biogeochemical cycles, and society. Prediction of how fire impacts may change in the future is difficult because of the complexity of the controls on fire occurrence and burned area. Here we aim to assess how process-based fire-enabled Dynamic Global Vegetation Models (DGVMs) represent relationships between controlling factors and burned area. We developed a pattern-oriented model evaluation approach using the random forest (RF) algorithm to identify emergent relationships between climate, vegetation, and socioeconomic predictor variables and burned area. We applied this approach to monthly burned area time series for the period 2005–2011 from satellite observations and from DGVMs from the Fire Model Inter-comparison Project (FireMIP) that were run using a common protocol and forcing datasets. The satellite-derived relationships indicate strong sensitivity to climate variables (e.g. maximum temperature, number of wet days), vegetation properties (e.g. vegetation type, previous-season plant productivity and leaf area, woody litter), and to socioeconomic variables (e.g. human population density). DGVMs broadly reproduce the relationships to climate variables and some models to population density. Interestingly, satellite-derived responses show a strong increase of burned area with previous-season leaf area index and plant productivity in most fire-prone ecosystems which was largely underestimated by most DGVMs. Hence our pattern-oriented model evaluation approach allowed to diagnose that current fire-enabled DGVMs represent some controls on fire to a large extent but processes linking vegetation productivity and fire occurrence need to be improved to accurately simulate the role of fire under global environmental change.
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“Further, coupled weather-fire models now capture the unfolding of complex landscape-scale events over a period of days (Coen, Stavros, & Fites-Kaufman, 2018), while global models continue to improve their representation of fire frequency, burned area and seasonality across years to decades (Forkel et al., 2019;Hantson et al., 2016).”
From Fire as a fundamental ecological process: Research advances and frontiers (2020) · cites this paper as Forkel et al., 2019
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“is about 3 × 10(8) ha, accounting for 3% of the global land area (Giglio et al., 2013; Forkel et al., 2019).”
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“Recent global attribution studies have revealed that climate change is actively increasing the burnt area in many locations (Burton et al 2024), driving more burning in certain ecosystems through enhanced vegetation growth (i.e., greening) and hotter, drier conditions (Forkel et al 2019).”
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“Forkel et al., 2019 .”
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“Although some researchers have analyzed wildfires using the burned area (Belenguer-Plomer et al. 2019; Forkel et al. 2019), to the best of our knowledge, few works have addressed the study of wildfires burned areas adopting our approach, that is, including socio-economic factors and applying a spatio-temporal formulat…”
BackgroundA data-driven prediction model for Fennoscandian wildfires
Bakke, S. J., Wanders, N., van der Wiel, K., & Tallaksen, L. (2021) · doi:10.5194/nhess-2021-384
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Futuring: Trends in Fire Science and Management
Rego, F. C., Morgan, P., Fernandes, P. M., & Hoffman, C. M. (2021) · Springer textbooks in earth sciences, geography and environment · doi:10.1007/978-3-030-69815-7_14 · Cited by 2
Metadata
- Authors
- Forkel, M., Andela, N., Harrison, S. P., Lasslop, G., van Marle, M., Chuvieco, E., Dorigo, W., Forrest, M., Hantson, S., Heil, A., Li, F., Melton, J., Sitch, S., Yue, C., & Arneth, A.
- Affiliations
- TU Wien (AT)
- Goddard Space Flight Center (US)
- University of Reading (GB)
- Senckenberg Biodiversity and Climate Research Centre (DE)
- Deltares (NL)
- Universidad de Alcalá (ES)
- University of California, Irvine (US)
- Max Planck Institute for Chemistry (DE)
- Chinese Academy of Sciences (CN)
- Environment and Climate Change Canada (CA)
- University of Exeter (GB)
- Laboratoire des Sciences du Climat et de l'Environnement (FR)
- Karlsruhe Institute of Technology (DE)
- Corresponding author
- Forkel, Matthias
- ORCID
- Venue
- Biogeosciences
- Publisher
- Copernicus GmbH
- Published
- 2019-01-11
- Volume
- 16
- Issue
- 1
- Pages
- 57-76
- ISSN
- 1726-4170 (ISSN-L)
- 1726-4189
- OpenAlex
- W2908971356
- Cited by
- 184
- References
- 117
- Citations by year
- 2026: 18 · 2025: 19 · 2024: 22 · 2023: 17 · 2022: 26 · 2021: 57 · 2020: 14 · 2019: 11
- FWCI
- 13.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Biogeosciences (publishedVersion, cc-by)
- CentAUR (University of Reading) (acceptedVersion, other-oa)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- Repository KITopen (Karlsruhe Institute of Technology) (submittedVersion, cc-by)
- HAL (submittedVersion, cc-by)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion, other-oa)
- reposiTUm (TU Wien) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- Biogeosciences (European Geosciences Union) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- reposiTUm (TU Wien) (submittedVersion)
- KITopen (cc-by)
- Funders
- Gordon and Betty Moore Foundation (GBMF3269)
- European Space Agency
- Technische Universität Wien
- Technische Universität Wien Bibliothek
- H2020 European Research Council (694481)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Keywords
- burned area, dynamic global vegetation models, model evaluation, random forest, climate drivers of fire, leaf area index, plant productivity, woody litter, human population density, fire-prone ecosystems, global change
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