Skip to Main content Skip to Navigation
Journal articles

A statistical approach for predicting grassland degradation in disturbance-driven landscapes

Abstract : Maintaining a land base that supports safe and realistic training operations is a significant challenge for military land managers which can be informed by frequent monitoring of land condition in relation to management practices. This study explores the relationship between fire and trends in tallgrass prairie vegetation at military and non -military sites in the Kansas Flint Hills. The response variable was the longterm linear trend (2001-2010) of surface greenness measured by MODIS NDVI using BFAST time series trend analysis. Explanatory variables included fire regime (frequency and seasonality) and spatial strata based on existing management unit boundaries. Several non-spatial generalized linear models (GLM) were computed to explain trends by fire regime and/or stratification. Spatialized versions of the GLMs were also constructed. For non-spatial models at the military site, fire regime explained little (4%) of the observed surface greenness trend compared to strata alone (7% - 26%). The non-spatial and spatial models for the non -military site performed better for each explanatory variable and combination tested with fire regime. Existing stratifications contained much of the spatial structure in model residuals. Fire had only a marginal effect on surface greenness trends at the military site despite the use of burning as a grassland management tool. Interestingly, fire explained more of the trend at the nonmilitary site and models including strata improved explanatory power. Analysis of spatial model predictors based on management unit stratification suggested ways to reduce the number of strata while achieving similar performance and may benefit managers of other public areas lacking sound data regarding land usage.
Complete list of metadatas

Cited literature [38 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01509642
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Tuesday, April 18, 2017 - 12:08:47 PM
Last modification on : Wednesday, August 12, 2020 - 8:30:21 AM
Long-term archiving on: : Wednesday, July 19, 2017 - 3:03:02 PM

File

17611_Jacquin.pdf
Publisher files allowed on an open archive

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Collections

Citation

Anne Jacquin, Michel Goulard, J. M. Shawn Hutchinson, Thomas Devienne, Stacy L. Hutchinson. A statistical approach for predicting grassland degradation in disturbance-driven landscapes. Journal of Environmental Protection, Scientific Research Publishing, 2016, vol. 7 (n° 6), pp. 912-925. ⟨10.4236/jep.2016.76081⟩. ⟨hal-01509642⟩

Share

Metrics

Record views

337

Files downloads

654