Uncertainty analysis of the productivity of cattle populations in tropical drylands
Uncertainty analysis of the productivity of cattle populations in tropical drylands
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DOI：
10.1017/s175173111500124x
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发表时间：
2015-11-01
期刊：
影响因子：
3.6
通讯作者：
Lesnoff, M.
中科院分区：
文献类型：
--
作者：
Lesnoff, M.
本文对西非和中非旱地传统农业系统中牛群的生产力进行了不确定性分析。该研究的重点是根据畜群生长模型估算的动物数量（RN）和肉类重量（RW）生产率，并将其与基于粮农组织统计数据库的估算进行比较。不确定性分析包含以下两个步骤：不确定性传播和全局敏感性分析。该分析基于当前最先进的知识和一组有关牛群表现的可用数据。计算使用蒙特卡罗模拟来估计 RN 和 RW 的 95% 置信区间 (CI)，并使用标准化回归系数方法来估计输入变量对输出方差的贡献。平均 RN 率估计为 0.127 动物/动物年，95% CI 为 (0.091, 0.163)，平均 RW 率估计为 11.7 kg/动物年，95% CI 为 (8.8, 14.7)，对应于平均值周围的相对变化分别约为 +/- 29% 和 +/- 25%。对 RN 方差影响最大的输入变量（几乎占输出方差的 76%）是产犊率、成年雌性死亡率和种群中雌性比例（由牛群中雄性摄入量的模式决定）。对 RW 方差影响最大的输入变量与 RN 的输入变量加上成体活重相同。本文估计的 CI 范围表明，应谨慎考虑基于文献数据或专家对牛群表现的估计的生产率。未来应基于考虑时间和空间变化的黄金标准牛群监测协议进行研究工作，以减少对这些范围贡献最大的输入变量的知识差距。
This article presents an uncertainty analysis of the productivity of cattle herds in traditional farming systems of West and Central African drylands. The study focused on productivity rates in animal numbers (RN) and meat weights (RW) estimated from a herd growth model, which were compared with FAOSTAT-based estimates. The uncertainty analysis contained the following two steps: uncertainty propagation and a global sensitivity analysis. The analysis was based on a state-of-the-art of the current knowledge and a set of available data on the herd performances. The calculations used Monte Carlo simulations to estimate the 95% confidence intervals (CI) of RN and RW and the standardized regression coefficients method to estimate the contribution of the input variables to the outputs variances. The mean rate RN was estimated to 0.127 animal/animal-year with a 95% CI of (0.091, 0.163) and the mean rate RW to 11.7 kg/animal-year with a 95% CI of (8.8, 14.7), corresponding to relative variation around the mean of about +/- 29% and +/- 25%, respectively. The input variables that contributed most to the variance of RN (almost 76% of the output variance) were the calving rate, the adult female mortality rate and the female proportion in the population (determined by the pattern of the male offtake in the herds). The input variables that contributed most to the variance of RW were the same as those for RN plus the adult live weights. The CI ranges that were estimated in this article indicate that productivity rates based on literature data or expert estimations of the herd performances should be considered with caution. Research efforts based on gold-standard herd monitoring protocols accounting for temporal and spatial variations should be undertaken in future to decrease the knowledge gaps on the input variables that contribute most to these ranges.