Advanced

Primary production of Inner Mongolia, China, between 1982 and 1999 estimated by a satellite data-driven light use efficiency model

Brogaard, Sara LU ; Runnström, Micael LU and Seaquist, Jonathan LU (2005) In Global and Planetary Change 45(4). p.313-332
Abstract
Declining biological production as a part of an ongoing land degradation process is considered a severe environmental problem in the dry northern and northwestern regions of China. The aim of this study is to develop and adapt a satellite data-driven gross primary production model called Lund University light use efficiency model (LULUE) to temperate conditions in order to map gross primary production (GPP) for the Grasslands of Inner Mongolia Autonomous Region (IMAR), China, from 1982 to 1999. The water stress factor included in the original model has been complemented with two temperature stress factors. In addition, algorithms that allocate the proportions of C3/C4 photosynthetic pathways used by plants and that compute... (More)
Declining biological production as a part of an ongoing land degradation process is considered a severe environmental problem in the dry northern and northwestern regions of China. The aim of this study is to develop and adapt a satellite data-driven gross primary production model called Lund University light use efficiency model (LULUE) to temperate conditions in order to map gross primary production (GPP) for the Grasslands of Inner Mongolia Autonomous Region (IMAR), China, from 1982 to 1999. The water stress factor included in the original model has been complemented with two temperature stress factors. In addition, algorithms that allocate the proportions of C3/C4 photosynthetic pathways used by plants and that compute temperature-based C3 maximum efficiency values have been incorporated in the model. The applied light use efficiency (LUE) model is using time series of the Normalized Difference Vegetation Index (NDVI), CLouds from AVHRR (CLAVR) from the 8-km resolution NOAA Pathfinder Land Data Set (PAL). Quasi-daily rainfall and monthly minimum and maximum temperatures, together with soil texture information, are used to compute water limitations to plant growth. The model treats bare soil evaporation and actual transpiration separately, a refinement that is more biophysically realistic, and leads to enhanced precision in our water stress term, especially across vegetation gradients. Based on ground measurements of net primary production (NPP) at one site, the LULUE reproduces the variability of primary production better than CENTURY or NDVI alone. Mean annual GPP between 1982 and 1999 range from about 100 g/m(2) in desert regions in the west to about 4000 g/m(2) in the northeast of IMAR, and the coefficient of variation for GPP is highest near the margins of the deserts in the west where rainfall is erratic. Linear trends fitted through the 18-year time series reveal that the western regions have encountered no change, while a large area in the center of the IMAR shows marked increases in GPP. In the northeast, negative trends in GPP are noted and coincide with rainfall trends. Though the high inter-annual variability in primary production undermines the identification of significant trends, we could not isolate any general decline in grassland primary production. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Inner, Mongolia, NDVI, light use efficiency (LUE), grassland, primary production, China
in
Global and Planetary Change
volume
45
issue
4
pages
313 - 332
publisher
Elsevier
external identifiers
  • wos:000228343500004
  • scopus:14844286518
ISSN
1872-6364
DOI
10.1016/j.gloplacha.2004.09.012
language
English
LU publication?
yes
id
89d9c335-1469-453e-b2b5-71a5b70249fd (old id 246507)
date added to LUP
2007-08-22 08:36:32
date last changed
2017-11-12 03:31:37
@article{89d9c335-1469-453e-b2b5-71a5b70249fd,
  abstract     = {Declining biological production as a part of an ongoing land degradation process is considered a severe environmental problem in the dry northern and northwestern regions of China. The aim of this study is to develop and adapt a satellite data-driven gross primary production model called Lund University light use efficiency model (LULUE) to temperate conditions in order to map gross primary production (GPP) for the Grasslands of Inner Mongolia Autonomous Region (IMAR), China, from 1982 to 1999. The water stress factor included in the original model has been complemented with two temperature stress factors. In addition, algorithms that allocate the proportions of C3/C4 photosynthetic pathways used by plants and that compute temperature-based C3 maximum efficiency values have been incorporated in the model. The applied light use efficiency (LUE) model is using time series of the Normalized Difference Vegetation Index (NDVI), CLouds from AVHRR (CLAVR) from the 8-km resolution NOAA Pathfinder Land Data Set (PAL). Quasi-daily rainfall and monthly minimum and maximum temperatures, together with soil texture information, are used to compute water limitations to plant growth. The model treats bare soil evaporation and actual transpiration separately, a refinement that is more biophysically realistic, and leads to enhanced precision in our water stress term, especially across vegetation gradients. Based on ground measurements of net primary production (NPP) at one site, the LULUE reproduces the variability of primary production better than CENTURY or NDVI alone. Mean annual GPP between 1982 and 1999 range from about 100 g/m(2) in desert regions in the west to about 4000 g/m(2) in the northeast of IMAR, and the coefficient of variation for GPP is highest near the margins of the deserts in the west where rainfall is erratic. Linear trends fitted through the 18-year time series reveal that the western regions have encountered no change, while a large area in the center of the IMAR shows marked increases in GPP. In the northeast, negative trends in GPP are noted and coincide with rainfall trends. Though the high inter-annual variability in primary production undermines the identification of significant trends, we could not isolate any general decline in grassland primary production.},
  author       = {Brogaard, Sara and Runnström, Micael and Seaquist, Jonathan},
  issn         = {1872-6364},
  keyword      = {Inner,Mongolia,NDVI,light use efficiency (LUE),grassland,primary production,China},
  language     = {eng},
  number       = {4},
  pages        = {313--332},
  publisher    = {Elsevier},
  series       = {Global and Planetary Change},
  title        = {Primary production of Inner Mongolia, China, between 1982 and 1999 estimated by a satellite data-driven light use efficiency model},
  url          = {http://dx.doi.org/10.1016/j.gloplacha.2004.09.012},
  volume       = {45},
  year         = {2005},
}