Constructing Causal Understanding in Complex Systems: Epistemic Strategies Used by Ecosystem Scientists
Constructing Causal Understanding in Complex Systems: Epistemic Strategies Used by Ecosystem Scientists
复制标题
在复杂系统中构建因果理解：生态系统科学家使用的认知策略
DOI：
10.1093/biosci/biz053
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发表时间：
2019
期刊：
影响因子：
10.1
通讯作者：
Tina A. Grotzer
中科院分区：
文献类型：
--
作者：
A. Kamarainen;Tina A. Grotzer
从相关到因果的解释涉及到任何学科的认识论假设。当现象涉及多种原因、时间滞后、反馈回路或阈值时，就像生态系统科学中的情况一样，它提出了特别的挑战。虽然还原论的方法可能有助于解释的努力，在生态系统科学的调查需要一个系统的角度来看。了解生态系统科学家如何得出因果关系的解释--重要的是，他们确实做到了--对于公众理解科学至关重要。对10位生态系统科学家的采访揭示了生态系统科学家研究复杂系统的策略和思维习惯。科学家们描述了在相关尺度上进行实验的挑战以及在回应中采用的认知策略。这些主题包括使用多种方法构建一系列证据，通过统计和基于过程的模型整合结果，测量和描述可变性，在上下文中进行实验，跨层次思考，考虑可概括性的限制，以及练习认知流畅性。我们讨论了对K-20教育的影响。
Moving from a correlational to a causal account involves epistemological assumptions in any discipline. It presents particular challenges when phenomena involve multiple causes, time lags, feedback loops, or thresholds, as is the case in ecosystem science. Although reductionist approaches may contribute to explanatory efforts, investigation in ecosystems science requires a systems perspective. Understanding how ecosystem scientists arrive at causal accounts—and importantly, that they do—is critical to public understanding of science. Interviews with ten ecosystem scientists revealed the strategies and habits of mind that ecosystem scientists bring to examining complex systems. The scientists described challenges in conducting experiments at relevant scales and the epistemic strategies employed in response. The themes included constructing a body of evidence using multiple approaches, integrating results through statistical and process-based models, measuring and describing variability, conducting experiments in context, thinking across levels, considering the limits to generalizability, and exercising epistemic fluency. We discuss implications for K–20 education.