A model of the grazing of hill vegetation by sheep in the UK. I. The prediction of vegetation biomass

Armstrong, Helen M., Gordon, Iain J., Grant, Sheila A., Hutchings, Nicholas J., Milne, John A., and Sibbald, Alan R. (1997) A model of the grazing of hill vegetation by sheep in the UK. I. The prediction of vegetation biomass. Journal of Applied Ecology, 34 (1). pp. 166-185.

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1. A computer model is described which predicts monthly growth, senescence, litterfall and standing biomass of ungrazed herbage in seven dwarf shrub-dominated and five grass-dominated vegetation types commonly found in the hill areas of the UK.

2. Using published data, the annual and monthly dry matter (DM) production of each vegetation type is predicted at sea level for the temperature zone in which the relevant data were collected. These estimates are then adjusted to take account of the effects of altitude and temperature zone on the production of all vegetation types and the effects of fertilizer rate, likely levels of soil nitrogen, summer rainfall and available soil water capacity on reseeded grassland. Empirically derived rules predict senescence and litterfall and, together with predicted DM production, are used to determine standing biomass in each month. The model also predicts the mean undisturbed sward surface height (sward height) of the grass vegetation types.

3. The sensitivity of the model to variations in inputs is described and the reliability of the relationships used in the model an discussed. Despite the limited availability of data suitable for model development, the model predicts DM production to lie between 1 and 11% of the measured values for the few remaining sites with appropriate data.

4. The most significant gaps in knowledge are identified and suggestions are made as to how the model might be further developed and tested.

Item ID: 42619
Item Type: Article (Research - C1)
ISSN: 1365-2664
Keywords: Calluna, empirical model, indigenous grassland, plant growth, plant senescence
Funders: Scottish Office of the Agriculture, Environment and Fisheries Department (SOAEFD)
Projects and Grants: SOAEFD Increased Flexibility Fund Grant
Date Deposited: 10 Feb 2016 07:43
FoR Codes: 05 ENVIRONMENTAL SCIENCES > 0501 Ecological Applications > 050199 Ecological Applications not elsewhere classified @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 100%
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