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Journal of the Australian Rangeland Society
RESEARCH ARTICLE (Open Access)

An online system for calculating and delivering long-term carrying capacity information for Queensland grazing properties. Part 2: modelling and outputs

B. Zhang A D , G. Fraser A , J. Carter B , G. Stone A , S. Irvine A , G. Whish C , J. Willcocks A and G. McKeon A
+ Author Affiliations
- Author Affiliations

A Grazing Land Systems, Queensland Department of Environment and Science, Brisbane, Queensland 4001, Australia.

B Remote Sensing Centre, Queensland Department of Environment and Science, Brisbane, Queensland 4001, Australia.

C Animal Science, Queensland Department of Agriculture and Fisheries, Brisbane, Queensland 4001, Australia.

D Corresponding author: Email: baisen.zhang@qld.gov.au

The Rangeland Journal 43(3) 159-172 https://doi.org/10.1071/RJ20088
Submitted: 3 September 2020  Accepted: 17 September 2021   Published: 26 October 2021

Journal Compilation © Australian Rangeland Society 2021 Open Access CC BY-NC-ND

Abstract

A combination of field data and models have been used to estimate long-term carrying capacity (LTCC) of domestic livestock in Queensland grazing lands. These methods have been synthesised and coupled with recent developments in science and information technology to provide a fully-automated approach of modelling LTCC through the FORAGE online system. In this study, the GRASP model was used to simulate pasture growth with parameter sets and safe pasture utilisation rates defined for 225 land types across Queensland. Distance to water points was used to assess the accessibility of pastures to livestock. Spatial analysis classified the property into unique areas based on paddock, land type and distance to water points, which estimated pasture growth, pasture utilisation and accessibility at a sub-paddock scale. Thirteen foliage projective cover (FPC) classes were used in modelling the pasture system to deal with the non-linear relationship between tree and grass interactions. As ‘proof of concept’, remotely-sensed individual-date green ground cover data were used to optimise the GRASP model parameters to improve the model performance, and a Monte Carlo analysis provided uncertainty estimates for model outcomes. The framework provides an efficient and standardised method for estimating LTCC. To test the system, LTCCs from 43 ‘benchmark’ properties were compared with simulated LTCCs, and 65% of the modelled LTCCs were within ± 25% of the benchmark LTCCs. Due to uncertainties in model inputs at the property scale and in model simulation, the modelled LTCC should be used as a starting point for further refinement of actual property LTCC.

Keywords: adult equivalent, domestic livestock carrying capacity, land condition, optimisation, safe utilisation.


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