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J Environ Manage ; 81(4): 315-22, 2006 Dec.
Article in English | MEDLINE | ID: mdl-16549228

ABSTRACT

Sustainable use of military training lands requires understanding and prediction of the effects of military vehicles on vegetation. We examined the initial impacts of an 8-wheeled, light armored vehicle (LAV) on grassland vegetation at Fort Lewis, Washington. The LAV drove replicate spiral paths at two starting velocities, 10.3 and 5.1 m s(-1). The disturbed width (width of ground impacted by the tires) increased as turning radius decreased, but was unaffected by vehicle velocity. An inverse-exponential model predicted disturbed width (r(2)=0.68) at all turning radii for both velocities combined. In low-velocity spirals, and for straight tracking (turning radius>40 m) and moderate turns (radius 20-40 m) in high-velocity spirals, all vegetation damage was imprint (plants flattened by wheels). During sharp (radius <20 m), high-velocity turns, most or all of the disturbed width was scraped free of surface vegetation and soil, which was piled to the outside of each tire track. Total plant cover (all species) was not affected by track curvature in low-velocity spirals, but decreased in the order straight tracking>moderate turns>sharp turns in high-velocity spirals. In low-velocity spirals, post-tracking cover of several plant growth forms (non-native species, perennial species, sod-forming grasses) was similar to pre-tracking cover, but in high-velocity spirals, post-tracking cover of these growth forms decreased in the order straight > or =moderate=sharp. Cover of native species and forbs decreased more in high- than in low-velocity spirals, but was unaffected by curvature. Pre- and post-tracking cover of annual species, bunchgrasses, and shrubs was < or =3%. The most severe vegetation damage caused by operation of wheeled LAVs on grasslands is associated with sharp, high-velocity turns.


Subject(s)
Ecosystem , Military Science/instrumentation , Models, Theoretical , Motor Vehicles , Poaceae/growth & development , Analysis of Variance , Conservation of Natural Resources , Regression Analysis , Washington
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