A Statistical Approach for Predicting Grassland Degradation in Disturbance-Driven LandscapesReport as inadecuate

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Maintaininga land base that supports safe and realistic training operations is asignificant challenge for military land managers which can be informed byfrequent monitoring of land condition in relation to management practices. Thisstudy explores the relationship between fire and trends in tallgrass prairievegetation at military and non-military sites in the Kansas Flint Hills. Theresponse variable was the long-term linear trend 2001-2010 of surfacegreenness measured by MODIS NDVI using BFAST time series trend analysis.Explanatory variables included fire regime frequency and seasonality andspatial strata based on existing management unit boundaries. Severalnon-spatial generalized linear models GLM were computed to explain trends byfire regime and-or stratification. Spatialized versions of the GLMs were alsoconstructed. For non-spatial models at the military site, fire regime explainedlittle 4% of the observed surface greenness trend compared to strata alone7% - 26%. The non-spatial and spatial models for the non-military siteperformed better for each explanatory variable and combination tested with fireregime. Existing stratifications contained much of the spatial structure in modelresiduals. Fire had only a marginal effect on surface greenness trends at themilitary site despite the use of burning as a grassland management tool.Interestingly, fire explained more of the trend at the non-military site andmodels including strata improved explanatory power. Analysis of spatial modelpredictors based on management unit stratification suggested ways to reduce thenumber of strata while achieving similar performance and may benefit managersof other public areas lacking sound data regarding land usage.


Fire Regime, Spatial Statistics, GLM Model, Grassland, Remote Sensing

Cite this paper

Jacquin, A. , Goulard, M. , Hutchinson, J. , Devienne, T. and Hutchinson, S. 2016 A Statistical Approach for Predicting Grassland Degradation in Disturbance-Driven Landscapes. Journal of Environmental Protection, 7, 912-925. doi: 10.4236-jep.2016.76081.

Author: Anne Jacquin1, Michel Goulard2, J. M. Shawn Hutchinson3, Thomas Devienne1, Stacy L. Hutchinson4

Source: http://www.scirp.org/


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