Abstract
In this rapidly changing world, improving the capacity to forecast future dynamics of ecological systems and their services is essential for better stewardship of the earth system. This chapter introduces ecological forecasting, the next frontier of research in ecology. Using weather forecasting as an analog, this chapter discusses four elements for ecological forecasting. The four elements are: predictability of the land carbon cycle; observations to constrain forecasting; data assimilation to integrate data with models; and a workflow system to automate ecological forecasting. This chapter also describes applications of an ecological forecasting system to a warming and CO2 experiment in northern Minnesota and a precipitation mean and variance experiment in New Mexico.
Original language | English (US) |
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Title of host publication | Land Carbon Cycle Modeling |
Subtitle of host publication | Matrix Approach, Data Assimilation, Ecological Forecasting, and Machine Learning, Second Edition |
Publisher | CRC Press |
Pages | 187-191 |
Number of pages | 5 |
ISBN (Electronic) | 9781040026298 |
ISBN (Print) | 9781032698496 |
DOIs | |
State | Published - Jan 1 2024 |
Externally published | Yes |
ASJC Scopus subject areas
- General Business, Management and Accounting
- General Agricultural and Biological Sciences
- General Earth and Planetary Sciences
- General Environmental Science
- General Engineering