Cited by 110Fire effects on ecosystemsLand Use and Ecosystem ServicesImpact of Light on Environment and Health

Relationships between Human Population Density and Burned Area at Continental and Global Scales

Open access
Bistinas, Ioannis, Oom, Duarte, Sá, Ana C. L., Harrison, Sandy P., Prentice, I. Colin, Pereira, José M. C.·2013·PLoS ONE

Abstract

We explore the large spatial variation in the relationship between population density and burned area, using continental-scale Geographically Weighted Regression (GWR) based on 13 years of satellite-derived burned area maps from the global fire emissions database (GFED) and the human population density from the gridded population of the world (GPW 2005). Significant relationships are observed over 51.5% of the global land area, and the area affected varies from continent to continent: population density has a significant impact on fire over most of Asia and Africa but is important in explaining fire over < 22% of Europe and Australia. Increasing population density is associated with both increased and decreased in fire. The nature of the relationship depends on land-use: increasing population density is associated with increased burned are in rangelands but with decreased burned area in croplands. Overall, the relationship between population density and burned area is non-monotonic: burned area initially increases with population density and then decreases when population density exceeds a threshold. These thresholds vary regionally. Our study contributes to improved understanding of how human activities relate to burned area, and should contribute to a better estimate of atmospheric emissions from biomass burning.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0081188

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In the modern period, the link between people and fire seems strongest at middle levels of development, with fires becoming less likely beyond certain population density, urbanization, or fossil fuel dependence.

    “The human–fire connection in the modern era appears strongest at intermediate levels of development, as fires become less likely in the landscape beyond a certain population density, level of urbanization, or dependence on fossil fuels (11, 13, 24).”
  • Geographic variation in regional and continental-scale fire activity in the US is strongly associated with proxies for human-caused changes such as population density, road density, and land-use and development patterns.

    “Geographic variability in regional and continental-scale fire activity in the United States is strongly tied to proxies for these human-caused changes, including population and road density, and different land-use and development patterns (10–15).”
  • The anthropogenic influence on fire activity is well known but still a matter of debate, as the nature of this influence is complicated.

    “The anthropogenic influence (AI) on fire activity is well known, but is still a matter of debate, as the nature of this influence is complicated [33-35].”
  • Relationships between fire and global population patterns have been identified.

    “Relationships between fire and global population patterns have been identified [16–18]”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 14

  1. [2]Johnson E (1996) Fire and Vegetation Dynamics: Studies from the North American Boreal Forest. Cambridge University Press Cambridge.
  2. [3]Pyne SJ, Andrews PL, Laven RD (1996) Introduction to wildland fire. New York, John Wiley and Sons p. 769.
  3. [6]IPCC (2007) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [ Solomon S Qin D Manning M Chen Z Marquis M Cambridge University Press, Cambridge, UK and New York, NY, USA.
  4. [7]Sanderson EW, Jaiteh M, Levy MA, Redford KH, Wannebo AV et al. (2002) The Human Footprint and the Last of the Wild. BioScience, 52(10): 891- 904.
  5. [9]Guyette RP, Muzika RM, Dey DC (2002) Dynamics of an anthropogenic fire regime. Ecosystems 5: 472- 486. doi: 10.1007/s10021-002-0115-7. · DOI
  6. [19]Brunsdon CA, Fotheringham AS, Charlton ME (1998) Geographically weighted regression–modelling spatial non-stationarity. Stat 47(3): 431– 443.
  7. [20]Fotheringham S, Brunsdon C, Charlton M (2002) Geographically Weighted Regression: the analysis of spatially varying relationships. John Wiley & Sons, UK.
  8. [21]Openshaw S, Taylor PJ (1981) The modifiable areal unit problem. in: Quantitative geography: a British View, (eds) N. Wrigley and R.J. Bennett, (Routledge and Kegan Paul: London), p. 60-70
  9. [23]Byrne G, Charlton M, Fotheringham S (2009) Multiple dependent hypothesis tests in geographically weighted regression. In: Lees BG Laffan SW 10th International conference on geocomputation. UNSW, Sydney November-December
  10. [27]Koenker R (2005) Quantile Regression. Cambridge University Press Cambridge. UK.
  11. [29]Chiu GS (2003) Bent cable Regression for Assesing Abruptness of Change. PhD Thesis, University of British Columbia: Canada.
  12. [30]Cade SB, Noon BR (2003) A gentle introduction to quantile regression for ecologists. Front Ecol Environment 1(8): 412- 420. Available online at: doi:10.1890/1540-9295(2003)001[0412:AGITQR]2.0.CO; 2 · DOI
  13. [37]Gralewicz NJ, Nelson TA, Wulder MA (2011) Spatial and temporal patterns of wildfire ignitions in Canada from 1980 to 2006. International Journal of Wildland Fire 21(3): 230- 242.
  14. [41]Page Le Y, van der Werf GR, Morton DC, Pereira JMC (2010) Modelling fire-driven deforestation potential in Amazonia under current and projected climate conditions. Journal of Geophysical Research 115: 11

Cited by

Sorted by citations

Authors
Bistinas, I., Oom, D., Sá, A. C. L., Harrison, S. P., Prentice, I. C., & Pereira, J. M. C.
Affiliations
  • University of Lisbon (PT)
  • University of Reading (GB)
  • Imperial College London (GB)
Corresponding author
Prentice, I. Colin
Venue
PLoS ONE
Published
2013-12-16
Volume
8
Issue
12
Pages
e81188
ISSN
1932-6203 (ISSN-L)
OpenAlex
W2018994427
Cited by
110
References
30
Citations by year
2026: 8 · 2025: 9 · 2024: 6 · 2023: 18 · 2022: 12 · 2021: 11 · 2020: 8 · 2019: 7 · 2018: 8 · 2017: 7 · 2016: 7 · 2015: 5 · 2014: 4
FWCI
4.07
Type
journal article
Language
en
Open access
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • CentAUR (University of Reading) (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Spiral (Imperial College London) (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
  • Physical Sciences › Environmental Science › Global and Planetary Change › Impact of Light on Environment and Health
Keywords
population density, burned area, fire emissions, biomass burning, land use, rangeland, cropland, non-monotonic relationship, population thresholds, Global Fire Emissions Database, spatial heterogeneity
MeSH terms
Climate, Fires, Humans, Population Density, Ecosystem, Biomass

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review