| 来源类型 | Conference or Workshop Item (Poster) |
| 规范类型 | 其他 |
| Using natural selection and optimization for smarter vegetation models - challenges and opportunities. | |
| Franklin O; Han W; Dieckmann U; Cramer W; Brännström Å; Pietsch S; Rovenskaya E; Prentice IC | |
| 发表日期 | 2017 |
| 出处 | European Geosciences Union (EGU) General Assembly 2017, 23–28 April 2017, Vienna, Austria |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | Dynamic global vegetation models (DGVMs) are now indispensable for understanding the biosphere and for estimating the capacity of ecosystems to provide services. The models are continuously developed to include an increasing number of processes and to utilize the growing amounts of observed data becoming available. However, while the versatility of the models is increasing as new processes and variables are added, their accuracy suffers from the accumulation of uncertainty, especially in the absence of overarching principles controlling their concerted behaviour. We have initiated a collaborative working group to address this problem based on a ‘missing law’ – adaptation and optimization principles rooted in natural selection. Even though this ‘missing law’ constrains relationships between traits, and therefore can vastly reduce the number of uncertain parameters in ecosystem models, it has rarely been applied to DGVMs. |
| 主题 | Advanced Systems Analysis (ASA) ; Evolution and Ecology (EEP) ; Ecosystems Services and Management (ESM) ; Exploratory and Special projects (ESP) |
| URL | http://pure.iiasa.ac.at/id/eprint/14576/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/132793 |
| 推荐引用方式 GB/T 7714 | Franklin O,Han W,Dieckmann U,et al. Using natural selection and optimization for smarter vegetation models - challenges and opportunities.. 2017. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Dynamic%20vegetation（3378KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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