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Aerial Photo: P. velutina cover derived from June 1996 color-infrared digital ortho-photographs and classified with Maximum Likelihood supervised classification algorithm
 

Summary:  Aerial Photo: P. velutina cover derived from June 1996 color-infrared digital ortho-
photographs and classified with Maximum Likelihood supervised classification algorithm
(ERDAS Imagine); CA algorithm (Fig. 1B) applied.
NOTE: Results from 13 of the 24 sampled plots summarized below

The extent to which changes in the size and abundance of woody plants on Southwestern rangelands
affect ecosystem processes is not well known.
Assessing the impacts of changes in velvet mesquite (Prosopis velutina) abundance on the C, N, and
H2O cycles and land surface-atmosphere interactions requires quantitative knowledge of plant biomass.
Direct measurements and complete inventories of woody plant biomass on a landscape scale are not
practical; hence indirect, non-destructive population sampling approaches are required.
Algorithms estimating mesquite biomass were developed by measuring basal diameter, canopy
dimensions and height and then destructively harvesting 31 P. velutina trees across a size gradient.
These allometric relationships were then used in conjunction with field surveys and aerial photos to
ascertain the extent to which estimates of mesquite biomass might vary with typical sampling
approaches.
ESTIMATING Prosopis velutina ABOVEGROUND BIOMASS:
C. McMurtry1, S. Archer1, M. McClaran1, D. Browning1, and H. Throop2 ; 1School of Natural Resources, University of Arizona, Tucson, AZ 85721; 2Biology Dept., New Mexico State University, Las Cruces, NM 88003
Aboveground biomass of individual P. velutina plants can be reliably / accurately
predicted from diverse and easily measured, non-destructive metrics.

  

Source: Archer, Steven R. - Savanna/Woodland Ecology Lab., School of Natural Resources and the Environment, University of Arizona

 

Collections: Environmental Sciences and Ecology