In:
Global Ecology and Biogeography, Wiley, Vol. 14, No. 3 ( 2005-05), p. 271-292
Abstract:
Aim Extrapolation of tower CO 2 fluxes will be greatly facilitated if robust relationships between flux components and remotely sensed factors are established. Long‐term measurements at five Northern Great Plains locations were used to obtain relationships between CO 2 fluxes and photosynthetically active radiation ( Q ), other on‐site factors, and Normalized Difference Vegetation Index ( NDVI ) from the SPOT VEGETATION data set. Location CO 2 flux data from the following stations and years were analysed: Lethbridge, Alberta 1998–2001; Fort Peck, MT 2000, 2002; Miles City, MT 2000–01; Mandan, ND 1999–2001; and Cheyenne, WY 1997–98. Results Analyses based on light‐response functions allowed partitioning net CO 2 flux ( F ) into gross primary productivity ( P g ) and ecosystem respiration ( R e ). Weekly averages of daytime respiration, γ day , estimated from light responses were closely correlated with weekly averages of measured night‐time respiration, γ night ( R 2 0.64 to 0.95). Daytime respiration tended to be higher than night‐time respiration, and regressions of γ day on γ night for all sites were different from 1 : 1 relationships. Over 13 site‐years, gross primary production varied from 459 to 2491 g CO 2 m −2 year −1 , ecosystem respiration from 996 to 1881 g CO 2 m −2 year −1 , and net ecosystem exchange from −537 (source) to +610 g CO 2 m −2 year −1 (sink). Maximum daily ecological light‐use efficiencies, ɛ d , max = P g /Q , were in the range 0.014 to 0.032 mol CO 2 (mol incident quanta) −1 . Main conclusions Ten‐day average P g was significantly more highly correlated with NDVI than 10‐day average daytime flux, P d ( R 2 = 0.46 to 0.77 for P g ‐NDVI and 0.05 to 0.58 for P d ‐NDVI relationships). Ten‐day average R e was also positively correlated with NDVI , with R 2 values from 0.57 to 0.77. Patterns of the relationships of P g and R e with NDVI and other factors indicate possibilities for establishing multivariate functions allowing scaling‐up local fluxes to larger areas using GIS data, temporal NDVI, and other factors.
Type of Medium:
Online Resource
ISSN:
1466-822X
,
1466-8238
DOI:
10.1111/geb.2005.14.issue-3
DOI:
10.1111/j.1466-822X.2005.00151.x
Language:
English
Publisher:
Wiley
Publication Date:
2005
detail.hit.zdb_id:
1479787-2
detail.hit.zdb_id:
2021283-5
SSG:
12
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