Estimation of gross primary production over burned black spruce forests in interior Alaska using MODIS data
Abstract
Black spruce forests, which are distributed widely in Alaska and Canada, have been reported to be sinks of carbon dioxide (CO2) under the current climate. However, an increasing trend of wildfire occurrence, and its magnitude, in interior Alaska, may alter the future CO2 budget in regional scale. The goal of this study is to estimate the gross primary production (GPP) in burned area using the light-use efficiency model with MODerate resolution Imaging Spectroradiometer (MODIS) data. Accuracy of GPP estimation was improved by explicitly treating burned area with a new parameterization of light-use efficiency and fraction of absorbed photosynthetically active radiation (FPAR). To parameterize the model, we started a CO2flux observation at a burned black spruce site (65°07N, 147°26W) in interior Alaska in 2008. At this site, a severe wildfire occurred in late June 2004, and almost all vegetation were burned. The vegetation is recovering and saplings of deciduous tree are currently starting to dominate. In order to parameterize the light-use efficiency for burned area, we observed absorption of photosynthetically active radiation (PAR) along with the CO2flux. The obtained maximum light-use efficiency gradually increased over 2009-2011 with the vegetation recovery. In calculating spatial distribution of GPP with satellite data, we estimated PAR distribution using a model developed by Nishida (2006, SOLA). FPAR and the maximum light-use efficiency were estimated from the relationships with satellite NDVI data. A comparison with GPP calculated using MOD15, total GPP can be over estimated by 7% if the burned areas are not considered. This overestimation will lead to a significant error in regional GPP estimation in severe fire years.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFM.B23F0514O
- Keywords:
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- 9350 GEOGRAPHIC LOCATION / North America;
- 4337 NATURAL HAZARDS / Remote sensing and disasters