2001
DOI: 10.1006/jare.2000.0678
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Spatial heterogeneity in Chihuahuan Desert vegetation: implications for sampling methods in semi-arid ecosystems

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Cited by 94 publications
(101 citation statements)
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“…Then, we performed linear regression analysis between green vegetation cover and green aboveground biomass for grasses, and green cover and green leaves for shrubs. Our biomass-cover regressions gave comparable estimates of ANPP to those from the LTER-IBP exclosure, a grassland with similar characteristics to our study site where ANPP was calculated using a different method (Huenneke et al 2001 2 ¼ 0.88, cover ranged between 0.08 and 0.75). These equations were used to estimate black grama ANPP and mesquite leaf productivity in our experimental plots.…”
Section: Response Variablessupporting
confidence: 61%
“…Then, we performed linear regression analysis between green vegetation cover and green aboveground biomass for grasses, and green cover and green leaves for shrubs. Our biomass-cover regressions gave comparable estimates of ANPP to those from the LTER-IBP exclosure, a grassland with similar characteristics to our study site where ANPP was calculated using a different method (Huenneke et al 2001 2 ¼ 0.88, cover ranged between 0.08 and 0.75). These equations were used to estimate black grama ANPP and mesquite leaf productivity in our experimental plots.…”
Section: Response Variablessupporting
confidence: 61%
“…We note that additional terms to the calibration accounting for variations in lattice water, soil organic carbon, and vegetation have been proposed (Zreda et al, 2012;Bogena et al, 2013;McJannet et al, 2014;Coopersmith et al, 2014). However, given the relatively small amount of biomass (∼ 2.5 kg m −2 at SRER; Huang et al, 2007; ∼ 0.5 kg m −2 at JER, Huenneke et al, 2001), low soil organic carbon (4.2 mg C g −1 soil at SRER; 2.7 mg C g −1 soil at JER; Throop et al, 2011), and low clay percent (5.2 % at SRER; 4.9 % at JER; Anderson, 2013), and thus low lattice water amounts (Greacen, 1981), we have neglected these terms in the analysis. Figure 2 presents the horizontal aggregation scale of the CRNS method in comparison to the watershed boundaries and to the EC footprints obtained for summer 2013 (Anderson, 2013).…”
Section: Cosmic-ray Neutron Sensing Methods For Soil Moisture Estimationmentioning
confidence: 96%
“…Within each grid, percent cover was estimated for six categories: bare soil, litter, grass, creosote, yucca, and other shrubs. Percent cover could be greater than 100%, owing to overlapping canopy cover of shrubs (Huenneke et al 2001).…”
Section: Data Collectionmentioning
confidence: 99%