Madingley Model

The Madingley model is a ‘next-generation’ model of ecosystems and biodiversity. It aims to help inform decision-makers about the impacts of their choices on biodiversity and ecosystem services, and on trajectories of biodiversity change under different scenarios of human development.

ecosystemsbiodiversityecosystem services
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contributed at 2019-07-17

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English {{currentDetailLanguage}} English

Quoted from: https://madingley.github.io/index.html

The scientific community has spent decades developing models of the atmosphere and climate so that we can project the consequences of anthropogenic climate change. But there is no equivalent for life on land and in the sea. Madingley was developed with exactly this long-term vision in mind: to develop a model of ecosystems and biodiversity on land and sea that would follow on from the successes of climate models and use the fundamental principles of how animals and plants interact to project the global consequences of human impacts.

The Madingley model is an entirely new approach to modelling ecosystems and biodiversity. It is different from existing models as it includes both marine and terrestrial ecosystems, and marine and terrestrial human pressures – fisheries, agriculture, and climate change, for example. It is global in scope but can be applied regionally or nationally, and allows for unpredictable behaviour to emerge – meaning that food webs can shift and ecosystems can radically alter. It is published and described in the scientific peer-reviewed literature, and is open for anyone to use and modify.

Madingley is global in scope and includes both terrestrial and marine habitats, as well as the ability to track the fate and ecological interactions of every individual in the model. It spans organisms ranging in size from plankton to whales, and aphids to elephants. The model is undergoing continual development and refinement.

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How to Cite

Madingley community (2019). Madingley Model, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/3057f341-1cb0-46ba-abae-5d3bf752fc34
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Initial contribute: 2019-07-17

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