Systems mapping of drivers
Causal loop diagrams and system maps built with experts show the feedbacks linking drivers, revealing leverage points and the places where small changes could cascade.
GRF · Foresight Nexus
Complex 系统 and agent-based modelling help foresight explain why change is often nonlinear: feedbacks, thresholds and interactions among many actors produce surprises that trend extrapolation misses. In this field the models are tools for exploring possibility and 系统性风险, not for predicting outcomes.
Complex 系统 and agent-based modelling study systems whose behaviour emerges from interactions among many components. They help explain nonlinear dynamics, tipping points and collective behaviour. In foresight and risk management and 系统性风险, complex systems approaches explore how interacting risks can produce sudden, systemic shifts. They support stress testing of policies against emergent behaviour. The canonical description is on STEM Commons.
Causal loop diagrams and system maps built with experts show the feedbacks linking drivers, revealing leverage points and the places where small changes could cascade.
Agent-based models represent households, firms or states with simple behavioural rules to explore how trust, migration or technology adoption could tip under different conditions.
Time series are examined for rising variance, rising autocorrelation and slower recovery that can precede a 临界点, with the method’s tendency to false alarms stated beside any signal.
Flood water, population density and active fires over the Arctic, from NASA GIBS. Each layer carries its own date.
交互式地图需要JavaScript;图层列表和来源见下文。
图层 3
本页面的危害与暴露
键盘操作,地图获得焦点时
按住 Ctrl 或 ⌘ 并滚动以缩放
最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。
北极地区的危害与风险暴露。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
图层与日期
Datasets and records used by complex 系统 and agent-based modelling on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Expert-elicited causal maps | Structure of system models | 估算 |
| Survey and census microdata | Agent behaviour and heterogeneity | 已发布统计 |
| Observational time series | Calibration and transition indicators | 观测 |
| Trade and financial network data | Interdependence and contagion channels | 已报告 |
团队遵循该方法时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。
Foresight · Complex systems in foresight · Run R-2561
| 前瞻负责人 | adapts after 3 losses | 0.9 | survey, labelled |
| Scanning network member | adapts after 2 losses | 0.2 | survey, labelled |
| 情景作者 | adapts after 4 losses | 0.4 | survey, labelled |
Models are evaluated by matching multiple stylised facts and patterns at different scales. Sensitivity and robustness analysis test dependence on assumptions.
| 核查 | 如何开展 |
|---|---|
| Pattern-oriented validation | Models are checked against several observed patterns at different scales, not a single one |
| Sensitivity and robustness | Results are tested across parameter ranges and alternative behavioural rules |
| Model plurality | Conclusions are compared across alternative model structures before they inform a scenario |
Many plausible models can reproduce the same patterns. Calibration and validation data are often limited.
三类文书与基线并列比较,各有其滞后和采纳速度,在你设定的覆盖率和遵守率下运行;效应量是教学数值,应以证据替换。情景:关于未来的明示假设,不是预测。本页地图显示的是北极;模型本身不限于某一地点。
控制措施
读数
| 年份 | 基线 | 监管 | 经济激励 | 信息与能力 |
|---|---|---|---|---|
| 0 | 100.0 | 99.5 | 98.8 | 99.1 |
| 1 | 102.0 | 101.2 | 100.1 | 99.8 |
| 2 | 104.0 | 102.5 | 101.1 | 99.9 |
| 3 | 106.1 | 103.5 | 101.6 | 100.0 |
| 4 | 108.2 | 103.7 | 101.8 | 100.7 |
| 5 | 110.4 | 103.2 | 101.7 | 102.1 |
| 6 | 112.6 | 102.0 | 101.6 | 103.9 |
| 7 | 114.9 | 100.4 | 101.6 | 105.9 |
| 8 | 117.2 | 99.2 | 102.1 | 108.0 |
| 9 | 119.5 | 98.6 | 102.9 | 110.1 |
| 10 | 121.9 | 98.9 | 104.2 | 112.3 |
| 11 | 124.3 | 99.7 | 105.7 | 114.5 |
| 12 | 126.8 | 101.1 | 107.4 | 116.8 |
| 13 | 129.4 | 102.7 | 109.4 | 119.2 |
| 14 | 131.9 | 104.5 | 111.4 | 121.6 |
| 15 | 134.6 | 106.5 | 113.5 | 124.0 |
| 16 | 137.3 | 108.5 | 115.7 | 126.5 |
| 17 | 140.0 | 110.7 | 118.0 | 129.0 |
| 18 | 142.8 | 112.9 | 120.4 | 131.6 |
| 19 | 145.7 | 115.1 | 122.8 | 134.2 |
| 20 | 148.6 | 117.4 | 125.2 | 136.9 |
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
贯穿六大支柱,由 Nexus Consortium 牵头
一项文书从授权到评估所经历的步骤,每一步都标明负责运行的支柱,以及仍由当局作出的决定。这是带有明示说明性数值的教学模型,不是预测。本页地图显示的是北极;模型本身不限于某一地点。
贯穿六大支柱,由 Nexus Consortium 牵头
Assembled from the Nexus Standards area profile 子孙后代与长期风险: the hazards it names, the 系统 and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. To model a place of your own choosing, open the full System Builder.
灾害
系统与耦合
控制措施
NS-0 章程与原则NS-9 情境 UNI(部署、实例、计划实例)NS-10 政策和条款(机器可读的义务:定义、约束、评估和执行)NS-11 验证与监测(证据、证明、零信任符合性观测)NS-13 标准制定流程(公开提案、审查、版本管理、采纳)NRS-U12 宇宙 platform profile: Foresight NexusNRS-H26 危害类别:土地与湿地退化(NHS-1 eco.land)NRS-H92 危害类别:老化与退化的基础设施(NHS-1 infra.ageing)NRS-P4 前瞻、地平线扫描与战略NRS-H11 危害类别:沿海与海平面危害(NHS-1 water.coastal)NRS-H31 危害类别:持久性和生物累积性物质(NHS-1 poll.persistent)观测
示例地理范围
政策制定者、外交官或发展机构所使用的文书、授权、行为方和问责安排,并注明设定它们的协定。结构遵循所列框架。所绘制的任何状态或进展均为说明性,并非记录。
The kinds of instrument available on complex systems in foresight, by level of government and cooperation.
| 工具类型 | 地方 | 国家 | 区域 | 全球 |
|---|---|---|---|---|
| 监管型 | 分区、建筑规范 | 法律、标准、许可 | 统一规则 | 公约与条约 |
| 经济 | 地方税费、拨款 | 预算项目、税收、保险计划 | 风险池,区域基金 | 融资机制 |
| 信息 | 地方预警 | 披露、预警、统计 | 数据共享安排 | 全球监测与报告 |
| 制度型 | 地方委员会 | 牵头机构,协调理事会 | 区域机构与秘书处 | 多边授权 |
| 合作型 | 社区协议 | 伙伴关系契约 | 谅解备忘录与联合计划 | 协定与共同承诺 |
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
切勿发送个人数据、敏感基础设施细节或您无权分享的任何内容。贡献在使用前会经过审查;发送贡献不赋予署名权或编辑权,赞助也绝不能换取研究结论。
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