Quantifying the environmental limits to fire spread in grassy ecosystems

Anabelle W. Cardoso, Sally Archibald, William J. Bond, Corli Coetsee, Matthew Forrest, Navashni Govendere, David Lehmann, Loïc Makaga, Nokukhanya Mpanza, Josué Edzang Ndong, Aurélie Flore Koumba Pambo, Tercia Strydom, David Tilman, Peter D. Wragg, A. Carla Staver

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Modeling fire spread as an infection process is intuitive: An ignition lights a patch of fuel, which infects its neighbor, and so on. Infection models produce nonlinear thresholds, whereby fire spreads only when fuel connectivity and infection probability are sufficiently high. These thresholds are fundamental both to managing fire and to theoretical models of fire spread, whereas applied fire models more often apply quasiempirical approaches. Here, we resolve this tension by quantifying thresholds in fire spread locally, using field data from individual fires (n = 1,131) in grassy ecosystems across a precipitation gradient (496 to 1,442 mm mean annual precipitation) and evaluating how these scaled regionally (across 533 sites) and across time (1989 to 2012 and 2016 to 2018) using data from Kruger National Park in South Africa. An infection model captured observed patterns in individual fire spread better than competing models. The proportion of the landscape that burned was well described by measurements of grass biomass, fuel moisture, and vapor pressure deficit. Regionally, averaging across variability resulted in quasi-linear patterns. Altogether, results suggest that models aiming to capture fire responses to global change should incorporate nonlinear fire spread thresholds but that linear approximations may sufficiently capture medium-term trends under a stationary climate.

Original languageEnglish (US)
Article numbere2110364119
JournalProceedings of the National Academy of Sciences of the United States of America
Volume119
Issue number26
DOIs
StatePublished - Jun 28 2022

Bibliographical note

Funding Information:
This work was funded by a grant from the NSF (Principal Investigator: A.C.S.; NSF-MSB 1802453). Assistance in the field was provided by M. M. Nappo, the scientific field team, and Ecoguards at Lope National Park, Gabon; by E. Masango, S. Mukhumo, H. Mangena, the Kruger Scientific Services burning team, and the game guards at Kruger National Park, South Africa; and by T. Mielke and the controlled burn team at Cedar Creek Ecosystem Science Reserve, East Bethel, MN. We are appreciative of the two anonymous reviewers and journal editor whose thoughtful feedback helped us improve the manuscript.

Funding Information:
ACKNOWLEDGMENTS. This work was funded by a grant from the NSF (Principal Investigator: A.C.S.; NSF-MSB 1802453). Assistance in the field was provided by M. M. Nappo, the scientific field team, and Ecoguards at Lopé National Park, Gabon; by E. Masango, S. Mukhumo, H. Mangena, the Kruger Scientific Services burning team, and the game guards at Kruger National Park, South Africa; and by T. Mielke and the controlled burn team at Cedar Creek Ecosystem Science Reserve, East Bethel, MN. We are appreciative of the two anonymous reviewers and journal editor whose thoughtful feedback helped us improve the manuscript.

Publisher Copyright:
Copyright © 2022 the Author(s).

Keywords

  • fire model
  • fire thresholds
  • fuel moisture
  • infection model
  • percolation

PubMed: MeSH publication types

  • Journal Article
  • Research Support, U.S. Gov't, Non-P.H.S.

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