Eliciting experts' tacit models for the interpretation of soil information, an example from the evaluation of potential benefits from conservation agriculture
Eliciting experts' tacit models for the interpretation of soil information, an example from the evaluation of potential benefits from conservation agriculture
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引出专家解读土壤信息的隐性模型——以保护性农业潜在效益评估为例
DOI：
10.1016/j.geoderma.2020.114545
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发表时间：
2020
期刊：
影响因子：
6.1
通讯作者：
Chabala L
中科院分区：
文献类型：
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作者：
Chabala L
我们研究了一个程序，以引出专家对环境因素意见的隐性模型，这些环境因素影响南部非洲采用保护性农业（CA）实践所带来的预期绝对产量效益。该程序基于专家对特定情景或“状态”下采用 CA 后作物产量预期改善的评估，“状态”是通过赞比亚特定农业生态区 (AEZ) 的标准土壤剖面描述捕获的一组特定土壤条件。包括土壤科学家、农学家、农业经济学家和其他环境科学家在内的混合科学家小组在经验丰富的高级研究人员的协助下，向三个州的每个州提供了多个子集，并要求根据 CA 下的预期产量改进对每个子集中的州进行排名。这些科学家群体可以分为两组。每组由两组组成，每组内各组之间的排名一致性比随机排名时的预期要大。对于两组群体，可以根据土壤特性以及 AEZ 之间的对比对排名进行建模。这些模型揭示了两组截然不同的概念假设。一组人普遍预计，在水最有可能受到限制且土壤碳状况较差的地区，保护性农业的绝对产量将得到更大的提高。相比之下，另一组则期望在水不太可能受到限制的情况下取得更大的改进。这些截然不同的观点与当前的讨论有关，即作为“气候智能”种植战略推广的保护性农业在作物生产已经具有挑战性的条件下是否对小农生产者具有足够的吸引力，以及是否应考虑在水资源供应本身不是常见限制的地区的潜在效益。得出的模型可以直接转化为待测试的竞争假设，也许可以在不同优先发展区对比土壤上进行保护性农业实践的农场试验中。该方法基于对排名过程进行建模，对于征求有关复杂土壤、作物和环境系统的专家意见可能更具有普遍意义。
We examined a procedure to elicit the tacit models underlying expert opinions on environmental factors that affect the absolute yield benefits expected from the adoption of conservation agriculture (CA) practices in southern Africa. The procedure is based on expert evaluation of the expected improvement in crop yield on adoption of CA in a particular scenario or ‘state’, a state being a specified set of soil conditions captured by a standard soil profile description from a specified agroecological zone (AEZ) of Zambia. Mixed groups of scientists including soil scientists, agronomists, agricultural economists and other environmental scientists, facilitated by experienced senior researchers, were presented with multiple subsets each of three states, and asked to rank the states in each subset with respect to expected yield improvement under CA. The groups of scientists could be divided into two sets. Each set comprised two groups, and the agreement on ranking between groups within each set was larger than would be expected if the ranking were done at random. For both sets of groups the ranking could be modelled with respect to properties of the soil, and the contrast between AEZ. The models revealed two contrasting groups of conceptual assumptions. One group broadly expected larger absolute yield improvements from conservation agriculture in settings where water is most likely to be limiting and the carbon status of the soil is poor. By contrast, the other group expected larger improvements where water was less likely to be limiting. These contrasting views are relevant to current discussions as to whether conservation agriculture, which is promoted as a ‘climate smart’ strategy for cropping, is sufficiently attractive for smallholder producers in conditions where crop production is already challenging, and whether the potential benefits in areas where water availability is not of itself a common limitation should be considered. The elicited models could be translated directly into competing hypotheses to be tested, perhaps in on-farm trials of conservation agriculture practices over contrasting soils in the different AEZ. The method, based on modelling the ranking process, could be of more general interest for the elicitation of expert opinion about complex soil, crop and environmental systems.