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Journal of the Australian Rangeland Society
RESEARCH ARTICLE

Application of a livestock weight model to the 2009–2010 winter disaster in Mongolia

Kaoru Tachiiri A D , Hiroshi Komiyama B , Yuki Morinaga C and Masato Shinoda B
+ Author Affiliations
- Author Affiliations

A Japan Agency for Marine-Earth Science and Technology; 3173-25 Showamachi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan.

B Nagoya University; Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan.

C Meiji University; 1-9-1 Eifuku, Suginami-ku, Tokyo 168-8555, Japan.

D Corresponding author. Email: tachiiri@jamstec.go.jp

The Rangeland Journal 39(3) 263-277 https://doi.org/10.1071/RJ16113
Submitted: 17 October 2016  Accepted: 8 April 2017   Published: 13 June 2017

Abstract

Mongolia has historically experienced winter disasters (called dzud in Mongolian), which seriously damage the livestock sector. To reduce this damage, it is necessary to foresee the risk in advance. To do so, we applied a process-based livestock weight model based on the balance of energy intake and energy loss, each of which is calculated from environmental conditions. The spatial unit of the model is the province (aimag), and biomass amount derived from remote sensing and climatic data extracted from existing datasets were used as environmental conditions. We ran the model with parameters for sheep and validated the output using data of dzud in 2009–2010 and of the prior and subsequent years, comparing modelled sheep weight with spatial and temporal variation of observed sheep mortality. The model represented the basic feature of observed seasonal sheep weight change, and output smaller weights during 2009–2010, corresponding to the historic dzud of that period. A statistically significant (at 1% level) negative correlation was found between modelled weight and observed mortality. Determining the anomaly from the provincial average for 3 years further improved consistency. The model still has significant residuals, but is expected to contribute to dzud risk assessment by incorporating the effect of short-term, extreme climatic events (e.g. storms) and social factors.

Additional keywords: biomass, energy balance, energy consumption, energy intake, mortality, sheep.


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