Landscape Ecology

, Volume 26, Issue 2, pp 211–224 | Cite as

Spatial and temporal heterogeneity of agricultural fires in the central United States in relation to land cover and land use

  • Mirela G. Tulbure
  • Michael C. Wimberly
  • David P. Roy
  • Geoffrey M. Henebry
Research Article

Abstract

Agricultural burning is an important land use practice in the central U.S. but has received little attention in the literature, whereas most of the focus has been on wildfires in forested areas. Given the effects that agricultural burning can have on biodiversity and emissions of greenhouse gasses, there is a need to quantify the spatial and temporal patterns of fire in agricultural landscapes of the central U.S. Three years (2006–2008) of the MODIS 1 km daily active fire product generated from the MODIS Terra and Aqua satellite data were used. The 2007 Cropland Data Layer developed by the U.S. Department of Agriculture was used to examine fire distribution by land cover/land use (LCLU) type. Global ordinary least square (OLS) models and local geographically weighted regression (GWR) analyses were used to explore spatial variability in relationships between fire detection density and LCLU classes. The monthly total number of fire detections peaked in April and the density of fire detections (number of fires/km2/3 years) was generally higher in areas dominated by agriculture than areas dominated by forest. Fire seasonality varied among areas dominated by different types of agriculture and land use. The effects of LCLU classes on fire detection density varied spatially, with grassland being the primary correlate of fire detection density in eastern Kansas; whereas wheat cropping was important in central Kansas, northeast North Dakota, and northwest Minnesota.

Keywords

Agricultural burning Active fires Biodiversity Emissions Patterns of fire detections Cloud cover Local spatial analysis Fire detections 

Notes

Acknowledgments

This research was supported in part by a NASA EPSCoR project entitled Land cover dynamics, regional hydrometeorology, and the vulnerability of rain-fed agriculture to climate change under scenarios of extensive cultivation of biofuel feedstocks (NNX07AT61A) and by the US Department of Energy through the Sun Grant Initiative’s Regional Biomass Feedstock Partnership. We thank Dr. Luigi Boschetti for help with MODIS data processing. We thank two anonymous reviewers for helpful comments on an earlier draft.

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Mirela G. Tulbure
    • 1
  • Michael C. Wimberly
    • 1
  • David P. Roy
    • 1
  • Geoffrey M. Henebry
    • 1
  1. 1.Geographic Information Science Center of ExcellenceSouth Dakota State UniversityBrookingsUSA

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