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An assessment of grazing management options for Mediterranean grasslands using Noy-Meir's model of system dynamics parameterized from a long-term field trial
Year:
2018
Source of publication :
Journal of Agricultural Science
Authors :
Henkin, Zalmen
;
.
Perevolotsky, Avi
;
.
Seligman, No’am G.
;
.
Ungar, Eugene David
;
.
Volume :
156
Co-Authors:
Facilitators :
From page:
1205
To page:
1215
(
Total pages:
11
)
Abstract:

Noy-Meir's simple but insightful model of grazing-system dynamics was used to draw broader inferences from empirical data generated by a 17-year field trial with beef cattle grazing a Mediterranean grassland in northern Israel. After calibration of its parameters against the field results, the model predictions were tested against an independent set of data obtained from the study site; they were within acceptable deviations from the inherently noisy field data. The calibrated model was used to analyse the effects of changes to two key grazing-management factors - stocking density and early-season grazing deferment - on biomass dynamics and forage consumption. The simulated results were used to calculate forage deficits and supplementary feed requirements for optimum herd performance during the growth ('green') season and throughout the year. The results revealed a critical stocking density of 0.7 Animal Units (AU)/ha, above which early-season deferment reduced the amount of supplementary feed required to maintain the optimum production of the herd. Optimum stocking is higher when the grassland is used mainly in the highly nutritious green season. Responses of the strongly seasonal Mediterranean grassland to the interaction between stocking density and early-season grazing deferment were expressed by a calibrated model, in terms that determine the efficiency of forage supplementation of the herd during the green season and throughout the year. © 2019 Cambridge University Press.

Note:
Related Files :
beef cows
feed deficit
Grazing deferment
herbage biomass
model calibration
model validation
stocking density
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More details
DOI :
10.1017/S0021859619000157
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
40021
Last updated date:
02/03/2022 17:27
Creation date:
15/04/2019 10:23
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An assessment of grazing management options for Mediterranean grasslands using Noy-Meir's model of system dynamics parameterized from a long-term field trial
156
An assessment of grazing management options for Mediterranean grasslands using Noy-Meir's model of system dynamics parameterized from a long-term field trial

Noy-Meir's simple but insightful model of grazing-system dynamics was used to draw broader inferences from empirical data generated by a 17-year field trial with beef cattle grazing a Mediterranean grassland in northern Israel. After calibration of its parameters against the field results, the model predictions were tested against an independent set of data obtained from the study site; they were within acceptable deviations from the inherently noisy field data. The calibrated model was used to analyse the effects of changes to two key grazing-management factors - stocking density and early-season grazing deferment - on biomass dynamics and forage consumption. The simulated results were used to calculate forage deficits and supplementary feed requirements for optimum herd performance during the growth ('green') season and throughout the year. The results revealed a critical stocking density of 0.7 Animal Units (AU)/ha, above which early-season deferment reduced the amount of supplementary feed required to maintain the optimum production of the herd. Optimum stocking is higher when the grassland is used mainly in the highly nutritious green season. Responses of the strongly seasonal Mediterranean grassland to the interaction between stocking density and early-season grazing deferment were expressed by a calibrated model, in terms that determine the efficiency of forage supplementation of the herd during the green season and throughout the year. © 2019 Cambridge University Press.

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