预测(人工智能)
适应(眼睛)
动作(物理)
弹性(材料科学)
转化式学习
代理(哲学)
心理弹性
适应能力
过程(计算)
环境资源管理
功能(生物学)
气候变化
计算机科学
社会学
生态学
心理学
经济
社会心理学
人工智能
热力学
生物
操作系统
物理
进化生物学
社会科学
神经科学
教育学
量子力学
作者
Donald R. Nelson,W. Neil Adger,Katrina Brown
标识
DOI:10.1146/annurev.energy.32.051807.090348
摘要
Adaptation is a process of deliberate change in anticipation of or in reaction to external stimuli and stress. The dominant research tradition on adaptation to environmental change primarily takes an actor-centered view, focusing on the agency of social actors to respond to specific environmental stimuli and emphasizing the reduction of vulnerabilities. The resilience approach is systems orientated, takes a more dynamic view, and sees adaptive capacity as a core feature of resilient social-ecological systems. The two approaches converge in identifying necessary components of adaptation. We argue that resilience provides a useful framework to analyze adaptation processes and to identify appropriate policy responses. We distinguish between incremental adjustments and transformative action and demonstrate that the sources of resilience for taking adaptive action are common across scales. These are the inherent system characteristics that absorb perturbations without losing function, networks and social capital that allow autonomous action, and resources that promote institutional learning.
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