Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 486996
Title A novel protocol for assessment of aboveground biomass in rangeland environments
Author(s) Mundava, C.; Schut, A.G.T.; Helmholtz, P.; Stovold, R.G.H.; Donald, G.; Lamb, D.W.
Source The Rangeland Journal 37 (2015)2. - ISSN 1036-9872 - p. 157 - 167.
Department(s) Plant Production Systems
Publication type Refereed Article in a scientific journal
Publication year 2015
Keyword(s) rising-plate-meter - dry tropical savanna - standing crop - herbage mass - grazing strategies - pasture biomass - vegetation - grassland - yield - management
Abstract Current methods to measure aboveground biomass (AGB) do not deliver adequate results in relation to the extent and spatial variability that characterise rangelands. An optimised protocol for the assessment ofAGBis presented that enables calibration and validation of remote-sensing imagery or plant growth models at suitable scales. The protocol combines a limited number of destructive samples with non-destructive measurements including normalised difference vegetation index (NDVI), canopy height and visual scores of AGB. A total of 19 sites were sampled four times during two growing seasons. Fresh and dry matter weights of dead and green components ofAGBwere recorded. Similarity of responses allowed grouping into Open plains sites dominated by annual grasses, Bunch grass sites dominated by perennial grasses and Spinifex (Triodia spp.) sites. Relationships between non-destructive measurements and AGB were evaluated with a simple linear regression per vegetation type. Multiple regression models were first used to identify outliers and then cross-validated using a 'Leave-One-Out' and 'Leave-Site-Out' (LSO) approach on datasets including and excluding the identified outliers. Combining all non-destructive measurements into one single regression model per vegetation type provided strong relationships for all seasons for total and green AGB (adjusted R2 values of 0.65-0.90) for datasets excluding outliers. The model provided accurate assessments of total AGB in heterogeneous environments for Bunch grass and Spinifex sites (LSO-Q2 values of 0.70-0.88), whereas assessment of green AGB was accurate for all vegetation types (LSO-Q2 values of 0.62-0.84). The protocol described can be applied at a range of scales while considerably reducing sampling time
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