...
首页> 外文期刊>Environmental Modeling & Assessment >Using Data on Social Influence and Collective Action for Parameterizing a Geographically-Explicit Agent-Based Model for the Diffusion of Soil Conservation Efforts
【24h】

Using Data on Social Influence and Collective Action for Parameterizing a Geographically-Explicit Agent-Based Model for the Diffusion of Soil Conservation Efforts

机译:使用社会影响力和集体行动数据对基于地理的,基于代理的基于模型的水土保持努力扩散进行参数化

获取原文
获取原文并翻译 | 示例
           

摘要

Social influence affects individual decision-making on soil conservation. Understanding the emergent diffusion of collective conservation effort is relevant to natural resource management at the river basin level. This study focuses on the effect of subjective norms and collective action on the diffusion of Soil Conservation Effort (SCE) in the Lake Naivasha basin (Kenya) for the period 1965-2010. A geographically-explicit Agent-Based Model (ABM) version of the CONSUMAT model was developed: the CONSERVAT model. In our model, we have represented heterogeneity in the physical environment and in the social network using empirical data. To parameterize the model, physical data, and social data from a household survey (n=307) were used. Model simulation results show that it is possible to reproduce empirical spatiotemporal diffusion patterns of SCE levels which are quite sensitive to the way in which social survey data are used to initialize the model. Overall, this study demonstrates (i) that social survey data can effectively be used for parameterization of a geographically-explicit ABM, and (ii) that empirical knowledge on natural environment characteristics and social phenomena can be used to build an agent-based model at the river basin level. This study is an important first step towards including subjective norms for evaluating the effectiveness of alternative policy strategies for natural resource management.
机译:社会影响会影响土壤保护的个人决策。了解集体保护活动的迅速扩散与流域一级的自然资源管理有关。这项研究集中于主观规范和集体行动对奈瓦沙湖盆地(肯尼亚)在1965-2010年期间水土保持努力(SCE)扩散的影响。开发了CONSUMAT模型的基于地理位置的基于代理的模型(ABM)版本:CONSERVAT模型。在我们的模型中,我们使用经验数据表示了物理环境和社交网络中的异质性。为了参数化该模型,使用了来自家庭调查(n = 307)的物理数据和社会数据。模型仿真结果表明,有可能重现SCE级别的经验时空扩散模式,这对使用社会调查数据初始化模型的方式非常敏感。总的来说,这项研究表明(i)社会调查数据可以有效地用于地理上明确的反导系统的参数化;(ii)关于自然环境特征和社会现象的经验知识可以用于建立基于主体的模型。流域水平。这项研究是朝着纳入主观规范以评估自然资源管理替代政策策略的有效性迈出的重要第一步。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号