1.2 参与方法评估和文件编制的资源人员和机构的联系方式

有助于对方法进行记录/评估的项目名称（如相关）

Book project: Making sense of research for sustainable land management (GLUES)

1.3 关于使用通过WOCAT记录的数据的条件

（现场）数据是什么时候汇编的？:

11/12/2015

编制者和关键资源人员接受有关使用通过WOCAT记录数据的条件。:

是

2.1 该方法的简要说明

Assessment of the probability and effectiveness of management options or innovations to describe cause-effect-relationships and to make recommendations for action on sustainable land management in the Itaparica region in Northeast Brazil.

2.2 该方法的详细说明

该方法的详细说明:

The study focus was on the determinants behind the adoption of innovations developed under a scientific project. The specific innovation analysed was intended to benefit both the environment and local smallholder farmers: namely cultivating a multi-purpose, low-growing, to the prevailing harsh semiarid environment well-adapted tree species (Spondias tuberosa L. – so called umbuzeiro). The assessment method was selected as it allows the combination of qualitative and quantitative data, and can be applied even in data-scarce situations. Moreover, it allows downscaling from a broad overview to small-scale management.

Knowledge is collected from different disciplines to support decision-making through the inter- and transdisciplinary approaches of constellation analysis and Bayesian networks. A Bayesian Network (BN) is a probabilistic graphical model that represents a set of variables (elements, nodes) and their conditional dependencies. There are three input components to a Bayesian Network: (a) a set of elements representing factors relevant to a particular environmental system or problem, (b) the links between these elements, and (c) the conditional probability tables (CPTs) behind each node (element) used to calculate the state of the node. Collected data and ratings are arranged in a hierarchical Bayesian Network model in Netica software (Netica 5.12 - freeware up to 15 nodes).

The creation of a Bayesian Network model is as follows: the objectives and necessary interventions for the innovation process aimed at sustainable management are characterized, with scientists arranging a conceptual diagram, including the mapping of elements. States of the nodes are determined through study of the literature and expert consultation (by scientists, stakeholders and experts on related topics). In a final step, a sensitivity analysis is performed on the Bayesian Network to highlight crucial nodes with the highest influence on objectives in order to derive actions to be recommended.

Stakeholder participation is the core process of designing Bayesian Networks. In pre-consultations stakeholders help identifying major influencing factors and relationships. Assessments are compiled in interview sessions enabling the states of the nodes to be quantified later. In this case study, the stakeholders were farmers, farmer-supporting institutions, and expert in soils, vegetation and crops.

2.3 该方法的照片

2.5 采用该方法的国家/地区/地点

2.6 该方法的开始和终止日期

2.8 该方法的主要目的/目标

The principle of Bayesian Network modelling is the integration of multiple issues and system components, where information from different sources can be integrated, while also handling missing data and uncertainty. The outcome may be recommendations that support local management decision-making. As the method is strong in transdisciplinary knowledge integration, it has the potential to become one of the core methods in environmental management.

2.9 推动或妨碍实施本办法所适用的技术的条件

3.1 该方法涉及的利益相关者及其职责

3.2 当地土地使用者/当地社区参与该方法的不同阶段

	当地土地使用者/当地社区的参与	指定参与人员并描述活动
启动/动机	被动	Interviews
计划	无
实施	互动	Interviews
监测/评估	互动	Interviews

3.3 流程图（如可用）

3.4 有关SLM技术选择的决策

是否就技术的选择做出了决定？:

• The approach was initiated by scientists.

解释:

The approach can be applied to SLM technologies, but also can be employed for other purposes. In our data-scarce case, the method was very helpful as able to deal with different data sources and types.

明确做出决策的依据:

• 研究结果

4.1 能力建设/培训

是否为土地使用者/其他利益相关者提供培训？:

是

明确受训人员:

• 土地使用者
• 现场工作人员/顾问

培训形式:

• 农民对农民
• 示范区域

培训形式:

• workshops

涵盖的主题:

Detecting decisive factors for an ideal scenario of implementation being adopted by land users. For the participants it was interesting to participate in preparing a joint view of their action space - this is generally known in its parts though not with its major interconnections and complexity. Participants especially acknowledged this value added for them.

4.2 咨询服务

土地使用者有权使用咨询服务吗？:

否

4.3 机构强化（组织发展）

是否通过这种方法建立或加强了机构？:

• 是，非常

具体说明机构的强化或建立程度:

• 本地

说明机构、角色和职责、成员等。:

Decisive factors for the adoption of innovations were identified, including favoring cultivation techniques for Umbuzeiro agriculture (e.g. soil additives).

具体说明支持类型:

• 能力建设/培训

4.4 监测和评估

监测和评估是该方法的一部分吗？:

是

若是，该文件是否用于监测和评估？:

否

4.5 研究

研究是该方法的一部分吗?

是

明确话题:

• 社会学
• 经济/市场营销
• 生态学
• 技术

提供进一步的细节，并指出是谁做的研究:

Research on the situation of local action and governance was a major driver for the workshops. University project members prepared and held the workshops, while also did extended interpretation and integration of results across a number of different workshops.

5.1 该方法中SLM组成部分的年度预算

如果不知道准确的年度预算，请给出一个范围:

• < 2,000

注释（例如主要的资助来源/主要捐助者）:

German Federal Ministry of Education and Research (BMBF) 100%

5.2 为土地使用者提供财政/物质支援

土地使用者是否获得实施该技术的财政/物质支持？:

否

5.3 对特定投入的补贴（包括劳动力）

• 无

如果土地使用者的劳动力是一项重要的投入，那么是不是:

• 自愿

5.4 信用

是否根据SLM活动的方法给予信用值？:

否

5.5 其它激励或手段

是否有其他激励措施或工具用于促进SLM技术的实施？:

否

6.1 方法的影响

6.2 土地使用者实施SLM的主要动机

6.3 方法活动的可持续性

土地使用者能否维持通过该方法实施的措施（无外部支持的情况下）？:

• 是

若是，请说明如何维持:

Lessons learnt (especially on most favorable soil additive mixture) improve effectiveness of potential Umbuzeiro cultivation. Stakeholder pool of BN-creation comprises business networking opportunities for land users.

6.4 该方法的长处/优点

编制者或其他关键资源人员认为的长处/优势/机会
The combination of input variables from any given background is possible.
Via Bayesian networks changes to the modelled system can be tested prospectively. The space and potential effects of management options can be shown to decision makers.
Combining Bayesian networks with Constellation Analysis allows easy determination of major nodes of the model and supports the process of decision-making for sustainable land management activities; methods proved to be very transdisciplinary.

6.5 该方法的弱点/缺点以及克服它们的方法

编制者或其他关键资源人员认为的弱点/缺点/风险	如何克服它们？
The statistical component of the Bayesian network approach can be hard to grasp for less educated or near-illiterate stakeholder groups.	Percentages of probability estimations can be translated to a graphical equivalent (e.g. gradual scale of emoticons).

7.1 方法/信息来源

7.2 参考可用出版物

标题、作者、年份、ISBN:

Rodorff V., Steinmetz L., Siegmund-Schultze M., Köppel J. (2015) Using Bayesian networks to depict favouring frame conditions for sustainable land management: Umbuzeiro-tree planting by smallholders in Brazil

可以从哪里获得?成本如何?

Session: Methods, tools and impact applications. Tropentag ‘Management of land use systems for enhanced food security - conflicts, controversies and resolutions’, September 16 – 18, 2015, Humboldt-Universität zu Berlin, Berlin, Germany

7.3 链接到网络上可用的相关信息

标题/说明:

Innovate project information

URL:

http://www.innovate.tu-berlin.de/v_menue/subprojects/sp7_decision_support_approach_and_project_coordination/sp7_rm1_decision_support_approach/parameter/en/