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Forecasting and Assessing the Large-Scale and Long-Term Impacts of Global Environmental Change on Terrestrial Ecosystems in the United States and China

  • Hanqin Tian
  • Xiaofeng Xu
  • Chi Zhang
  • Wei Ren
  • Guangsheng Chen
  • Mingliang Liu
  • Dengsheng Lu
  • Shufen Pan

Abstract

The Earth’s terrestrial ecosystems have experienced a complex set of global changes, occurring on large spatial-temporal scales and interactively affecting individual organisms and ecological systems, most of which are not amenable to direct experimentation. To understand, predict, and assess the large-scale and long-term impacts of global changes on the Earth’s terrestrial ecosystems, we need such a new approach for extrapolating the growth of plants, animals, or ecosystems into the future when climate, CO2, and other factors may be different, and extrapolating individual plant or site studies onto a regional or global scale. In this chapter, we present such a newly developed approach called the Regional Integration System for Earth’s ecosystem (RISE), which builds upon improved knowledge of the fundamental mechanisms of ecological systems, and supported by rapidly developing technology from high-speed computer systems to high-resolution remote sensing sources with global coverage. Then we apply the RISE to address our common understanding of perhaps the most important issue facing humankind in the twenty-first century, our disruption of the global carbon cycle. We use two case studies to illustrate the overall merits and applications of the RISE in terrestrial ecosystem research. In the first case study, the RISE has been used to predict and assess the impacts of global change on net primary productivity and ecosystem carbon storage in southeastern U.S. under current climatic conditions and future climate scenarios. In the second case study, we have used the RISE to assess changes in ecosystem carbon storage and fluxes induced by multiple environmental stresses including climate variability/change, land-use and land-cover change, elevated carbon dioxide, and air pollution in China.

Keywords

Carbon Storage Gross Primary Production Advance Very High Resolution Radiometer Advance Very High Resolution Radiometer Terrestrial Ecosystem Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations:

AVHRR

Advanced Very High Resolution Radiometer

CLC

Scenario combined Climate, Land Use, and CO2 effects

CLM

Climate Change only

DGVM

Dynamic Global Vegetation Model

DLEM

Dynamic Land Ecosystem Model

ETM

Enhanced Thematic Mapper

fPAR

Fraction of Photosynthetically Active Radiation

GCM

General Circulation Model

GEOMOD

Geographical Modeling

GIS

Geographic Information System

GISS

Goddard Institute for Space Studies

GPP

Gross Primary Production

IPCC

Intergovernmental Panel on Climate Change

LAI

Leaf Area Index

LUCC

Land Use Cover and Change

LULC

Land Use and/or Land Cover

MATCH

Multi-scale Atmospheric Transport and Chemistry

MIT IGSM

Massachusetts Institute of Technology’s Integrated Global System Model

MODIS

Moderate-resolution Imaging Spectroradiometer

NARR

North American Regional Reanalysis

NCE

Net Carbon Exchange

NCEP

National Center for Environmental Prediction

NEP

Net Ecosystem Production

NPP

Net Primary Production

NOAH

NCEP, Oregon State University, Air Force, and Hydrologic Research Lab

OCLC

Scenario combined O3, Climate, Land Use, and CO2 effects

PFT

Plant Functional Type

RCM

Regional Climate Model

RegEM

Regional Ecosystem Model

RISE

Regional Integration System for Earth’s ecosystem

SEUS

Southeastern U.S.

SOC

Soil Organic Carbon

TEM

Terrestrial Ecosystem Model

TOTEC

Total Terrestrial Carbon Storage

Notes

Acknowledgment

This research has been supported by NASA Interdisciplinary Science Program (NNG04GM39C), NASA Land Use and Land Cover change Program, DOE NICCR Program, US EPA 2004-STAR-L1 (RD-83227601) and AAES Program. We thank Drs. Yuhang Wang, Tao Zeng, and L. Ruby Leung for providing the regional climate data of the southeastern U.S., Dr. Felzer for providing the troposheric ozone data set for China, and Drs. Martha K. Nungesser and ShiLi Miao for providing valuable comments.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Hanqin Tian
    • 1
  • Xiaofeng Xu
  • Chi Zhang
  • Wei Ren
  • Guangsheng Chen
  • Mingliang Liu
  • Dengsheng Lu
  • Shufen Pan
  1. 1.Ecosystem Science and Regional Analysis LaboratorySchool of Forestry and Wildlife Sciences, Auburn UniversityUSA

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