关于利用初始监测数据交流恢复潜力和局限性

Q2 Social Sciences
S. Lyon, M. Diblasio, Ellen Creveling
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引用次数: 1

摘要

在修复项目的初步阶段,我们往往没有多少成功的证据可以向利益相关者展示。然而,提出最初的监测数据可以围绕恢复的早期进展进行有影响力的科学交流和利益相关者的参与。我们使用Paulins Kill流域的再造林监测来强调在设计监测方案和提供初始监测数据时预先考虑利益相关者沟通的价值。首先,出现了四项可概括的建议,以帮助指导从业者在常见的环境沟通技术和平台中考虑初始数据:(1)口头陈述:考虑围绕初始监测数据的长期数据;(2)对在线数据库:隔离不应改变的因素,以评估初始监测置信度;(3)制图平台:在初始监测数据中关注差异而不是震级;(4)实地考察:利用初始监测本身直接与利益相关者接触。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On using initial monitoring data to communicate restoration potentials and limitations
Abstract We often have little evidence of success to take to stakeholders in the preliminary stages of restoration projects. However, presenting initial monitoring data can allow for impactful science communication and stakeholder engagement around the early progress of restoration. We use reforestation monitoring in the Paulins Kill watershed to highlight the value associated with considering stakeholder communication upfront when designing monitoring schemes and presenting initial monitoring data. Primarily, four generalizable recommendations emerge to help guide practitioners considering initial data within common environmental communication techniques and platforms: (1) for oral presentations: consider long-term data for context around initial monitoring data; (2) for online databases: isolate factors that should not change to assess initial monitoring confidence; (3) for mapping platforms: focus on differences rather than magnitudes in initial monitoring data; (4) for field trips: use the initial monitoring itself to directly engage stakeholders.
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
15
期刊介绍: Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome.
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