Suppr超能文献

论生物多样性模型、预测与情景的伦理学

On the Ethics of Biodiversity Models, Forecasts and Scenarios.

作者信息

Mazzega Pierre

机构信息

UMR5563 GET Geosciences Environment Toulouse, CNRS / University of Toulouse, Toulouse, France.

Affiliate Researcher, Strathclyde Center for Environmental Law and Governance, University of Strathclyde, Glasgow, UK.

出版信息

Asian Bioeth Rev. 2018 Nov 16;10(4):295-312. doi: 10.1007/s41649-018-0069-5. eCollection 2018 Dec.

Abstract

The development of numerical models to produce realistic prospective scenarios for the evolution of biological diversity is essential. Only integrative impact assessment models are able to take into account the diverse and complex interactions embedded in social-ecological systems. The knowledge used is objective, the procedure of their integration is rigorous and the data massive. Nevertheless, the technical choices (model ontology, treatment of scales and uncertainty, data choice and pre-processing, technique of representation, etc.) made at each stage of the development of models and scenarios are mostly circumstantial, depending on both the skills of modellers on a project and the means available to them. In the end, the scenarios selected and the way they are simulated limit the futures explored, and the options offered to decision makers and stakeholders to act. The ethical implications of these circumstantial choices are generally not documented, explained or even perceived by modellers. Applied ethics propose a coherent set of principles to guide a critical reflection on the social and environmental consequences of integrative modelling and simulation of biodiversity scenarios. Such reflection should be incorporated into the actual modelling process, in a broad participatory framework, and foster effective moral involvement of modellers, policy-makers and stakeholders, in preference to the application of fixed ethical rules.

摘要

开发数值模型以生成生物多样性演化的现实前瞻性情景至关重要。只有综合影响评估模型能够考虑到社会生态系统中嵌入的多样且复杂的相互作用。所使用的知识是客观的,其整合过程是严谨的,数据量也很大。然而,在模型和情景开发的每个阶段所做的技术选择(模型本体、尺度和不确定性处理、数据选择与预处理、表示技术等)大多是视具体情况而定的,这既取决于项目中建模人员的技能,也取决于他们可利用的资源。最终,所选的情景及其模拟方式限制了所探索的未来,以及提供给决策者和利益相关者采取行动的选项。建模人员通常不会记录、解释甚至意识到这些视具体情况而定的选择所带来的伦理影响。应用伦理学提出了一套连贯的原则,以指导对生物多样性情景综合建模与模拟的社会和环境后果进行批判性反思。这种反思应在广泛的参与性框架内纳入实际建模过程,并促进建模人员、政策制定者和利益相关者进行有效的道德参与,而不是应用固定的伦理规则。

相似文献

1
On the Ethics of Biodiversity Models, Forecasts and Scenarios.论生物多样性模型、预测与情景的伦理学
Asian Bioeth Rev. 2018 Nov 16;10(4):295-312. doi: 10.1007/s41649-018-0069-5. eCollection 2018 Dec.
2
Risk management frameworks for human health and environmental risks.人类健康与环境风险的风险管理框架。
J Toxicol Environ Health B Crit Rev. 2003 Nov-Dec;6(6):569-720. doi: 10.1080/10937400390208608.
6
The future of Cochrane Neonatal.考克兰新生儿协作网的未来。
Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12.
7

本文引用的文献

1
Using the Value of Information to improve conservation decision making.利用信息价值改进保护决策。
Biol Rev Camb Philos Soc. 2019 Apr;94(2):629-647. doi: 10.1111/brv.12471. Epub 2018 Oct 2.
3
Big data need big theory too.大数据也需要大理论。
Philos Trans A Math Phys Eng Sci. 2016 Nov 13;374(2080). doi: 10.1098/rsta.2016.0153.
5
Deep learning.深度学习。
Nature. 2015 May 28;521(7553):436-44. doi: 10.1038/nature14539.
6
Deep learning in neural networks: an overview.神经网络中的深度学习:综述。
Neural Netw. 2015 Jan;61:85-117. doi: 10.1016/j.neunet.2014.09.003. Epub 2014 Oct 13.
9
Scenarios for global biodiversity in the 21st century.21 世纪全球生物多样性设想。
Science. 2010 Dec 10;330(6010):1496-501. doi: 10.1126/science.1196624. Epub 2010 Oct 26.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验