Erratum: Climate and human influences on global biomass burning over the past two millennia

Marlon, Jennifer R.; Bartlein, Patrick J.; Carcaillet, Christopher; Gavin, Daniel G.; Harrison, Sandy P.; Higuera, Philip E.; Joos, Fortunat; Power, Mitchell J.; Prentice, I. C.

doi:10.1038/ngeo468

Cited by 34 publications

(29 citation statements)

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“…Our study together with others show the prevalence of positive fire-vegetation feedbacks in communities dominated by taxa that did not evolve with a high fire frequency (McWethy et al, 2010;Perry et al, 2012). These systems are, in the context of climatic changes and anthropogenic increases in ignition, prone to suffer rapid landscape transformations (Bowman et al, 2011;Kitzberger et al, 2016;Marlon et al, 2009;McWethy et al, 2013;Miller et al, 2005;Veblen & Lorenz, 1988). Neglecting the effect of humans in enhancing firevegetation feedbacks can have catastrophic effects on fire regimes and cause irreversible changes in landscapes.…”

Section: Discussionsupporting

confidence: 55%

Changes in vegetation structure and fuel characteristics along post‐fire succession promote alternative stable states and positive fire–vegetation feedbacks

Tiribelli

Kitzberger

Morales

2018

J Vegetation Science

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Aims Structural and compositional changes along post‐fire succession modify plant community proneness to burn (flammability). The dominant regeneration strategies and life forms, and their interactions along post‐fire succession, modulate these changes by affecting density, amount and connectivity of fuels. Depending on how flammability evolves during post‐fire succession it may feed back negatively, neutrally or positively into fire probability and behaviour. Negative fire–vegetation feedbacks arise when communities increase flammability as stands age, while positive feedbacks occur where early stages have higher flammability than later stages. We characterized changes in vegetation structure and fuel characteristics with time since fire in sites where either resprouters maintained dominance (shrublands), or where colonizer trees reached the sites and dominate later post‐fire stages (forests). Location Northwestern Patagonia, Argentina. Methods We measured vegetation structure and characterized fine fuels with the intercept pole method in stands of different post‐fire age in 18 shrublands (range 1–115 years) and 18 forests (range 7–216 years). Results In shrublands fuel amount quickly recovered after fire to a relatively constant value and fine fuel density remained high. Conversely, in forests, fuel amount rapidly increased during early post‐fire stages (when resprouting shrubs dominate the community), peaked at c. 30–50 years (related to the co‐existence of resprouters and young trees) and decreased to a relatively constant value (when tall trees dominate the community and suppress resprouters). Moreover, forest fuel density decreased with time. These changes in fuel characteristics were largely linked to changes in vegetation structure, which in turn were modulated by the dominant regeneration strategies and life forms. Conclusions Our results provide evidence of a positive fire–vegetation feedback for the community dominated by colonizer trees, while the community dominated by resprouter shrubs showed a neutral feedback. Given the co‐existence of flammable shrublands bordering fire‐sensitive forests and their low tree regeneration rates, we argue that forest communities are especially sensitive to changes in fire frequency and severity driven by global change. Anthropogenic or climate‐driven changes in ignitions are threatening these landscapes, which may undergo potentially rapid transformations, as seen in other temperate ecosystems.

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Section: Discussionsupporting

confidence: 55%

Changes in vegetation structure and fuel characteristics along post‐fire succession promote alternative stable states and positive fire–vegetation feedbacks

Tiribelli

Kitzberger

Morales

2018

J Vegetation Science

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“…For example, it is shown that the mean sea level over the South China Sea has a rise rate of 11.3 mm/yr during 1993-2000 and a fall rate of 11.8 mm/yr during -2005[Cheng and Qi, 2007. For the northeast coast of the United States, a collection of model projections have shown a rapid SLR in the next century, and the rise could have a greater effect on the heavily populated coastal regions than estimated previously [Yin et al, 2009]. A recent review has concluded that improving estimates of the spatial variability in future sea level changes should be an important research target in coming years [Milne et al, 2009].…”

Section: Introductionmentioning

confidence: 94%

“…[4] Ocean models have been the primary tools in quantifying sea level changes and project the 21st century sea level rise as well as estimate ocean heat content [Wunsch et al, 2007;Yin et al, 2009;Gregory et al, 2004]. However, most of these ocean models are designed to conserve volume rather than mass [e.g., Haidvogel and Beckmann, 1999].…”

Section: Introductionmentioning

confidence: 99%

Deep ocean warming assessed from altimeters, Gravity Recovery and Climate Experiment, in situ measurements, and a non-Boussinesq ocean general circulation model

Song

Colberg

2011

J. Geophys. Res.

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[1] Observational surveys have shown significant oceanic bottom water warming, but they are too spatially and temporally sporadic to quantify the deep ocean contribution to the present-day sea level rise (SLR). In this study, altimetry sea surface height (SSH), Gravity Recovery and Climate Experiment (GRACE) ocean mass, and in situ upper ocean (0-700 m) steric height have been assessed for their seasonal variability and trend maps. It is shown that neither the global mean nor the regional trends of altimetry SLR can be explained by the upper ocean steric height plus the GRACE ocean mass. A non-Boussinesq ocean general circulation model (OGCM), allowing the sea level to rise as a direct response to the heat added into the ocean, is then used to diagnose the deep ocean steric height. Constrained by sea surface temperature data and the top of atmosphere (TOA) radiation measurements, the model reproduces the observed upper ocean heat content well. Combining the modeled deep ocean steric height with observational upper ocean data gives the full depth steric height. Adding a GRACE-estimated mass trend, the data-model combination explains not only the altimetry global mean SLR but also its regional trends fairly well. The deep ocean warming is mostly prevalent in the Atlantic and Indian oceans, and along the Antarctic Circumpolar Current, suggesting a strong relation to the oceanic circulation and dynamics. Its comparison with available bottom water measurements shows reasonably good agreement, indicating that deep ocean warming below 700 m might have contributed 1.1 mm/yr to the global mean SLR or one-third of the altimeter-observed rate of 3.11 ± 0.6 mm/yr over 1993-2008. Citation: Song, Y. T., and F. Colberg (2011), Deep ocean warming assessed from altimeters, Gravity Recovery and Climate Experiment, in situ measurements, and a non-Boussinesq ocean general circulation model,

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“…Database (e.g., Daniau et al, 2012;Marlon et al, 2016;Power et al, 2008;Vannière et al, 2016;Marlon et al, 2008) have focused on grassland systems. In part, this is due to the difficulties in identifying which sites should be considered "grassland" given that they can be defined in many ways and their spatial distributions vary through time.…”

Section: Global Charcoal Database and Grassland Biomesmentioning

confidence: 99%

Global fire history of grassland biomes

Leys

Marlon

Umbanhowar

et al. 2018

Ecology and Evolution

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Grasslands are globally extensive; they exist in many different climates, at high and low elevations, on nutrient‐rich and nutrient‐poor soils. Grassland distributions today are closely linked to human activities, herbivores, and fire, but many have been converted to urban areas, forests, or agriculture fields. Roughly 80% of fires globally occur in grasslands each year, making fire a critical process in grassland dynamics. Yet, little is known about the long‐term history of fire in grasslands. Here, we analyze sedimentary archives to reconstruct grassland fire histories during the Holocene. Given that grassland locations change over time, we compare several charcoal‐based fire reconstructions based on alternative classification schemes: (a) sites from modern grassland locations; (b) sites that were likely grasslands during the mid‐Holocene; and (c) sites based on author‐derived classifications. We also compare fire histories from grassland sites, forested sites, and all sites globally over the past 12,000 years. Forested versus grassland sites show different trends: grassland burning increased from the early to mid‐Holocene, reaching a maximum about 8000–6000 years ago, and subsequently declined, reaching a minimum around 4000 years ago. In contrast, biomass burning in forests increased during the Holocene until about 2000 years ago. Continental grassland fire history reconstructions show opposing Holocene trends in North versus South America, whereas grassland burning in Australia was highly variable in the early Holocene and much more stable after the mid‐Holocene. The sharp differences in continental as well as forest versus grassland Holocene fire history trajectories have important implications for our understanding of global biomass burning and its emissions, the global carbon cycle, biodiversity, conservation, and land management.

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Erratum: Climate and human influences on global biomass burning over the past two millennia

Abstract: In this Article, the y axis label of Fig. 4d was incorrect; it should have read 'Population (10 6)'. This has been corrected in the HTML and PDF versions.

Cited by 34 publications

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Changes in vegetation structure and fuel characteristics along post‐fire succession promote alternative stable states and positive fire–vegetation feedbacks

Changes in vegetation structure and fuel characteristics along post‐fire succession promote alternative stable states and positive fire–vegetation feedbacks

Deep ocean warming assessed from altimeters, Gravity Recovery and Climate Experiment, in situ measurements, and a non-Boussinesq ocean general circulation model

Global fire history of grassland biomes

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