G. Rapalee | Geology Reports

USGS2001

Moss and lichen cover mapping at local and regional scales in the boreal forest ecosystem of central Canada

Mosses and lichens are important components of boreal landscapes [Vitt et al., 1994; Bubier et al., 1997]. They affect plant productivity and belowground carbon sequestration and alter the surface runoff and energy balance. We report the use of multiresolution satellite data to map moss and lichens over the BOREAS region at a 10 m, 30 m, and 1 km scales. Our moss and lichen classification at the 10 m scale is based on ground observations of associations among soil drainage classes, overstory composition, and cover type among four broad classes of ground cover (feather, sphagnum, and brown mosses and lichens). For our 30 m map, we used field observations of ground cover-overstory associations to map mosses and lichens in the BOREAS southern study area (SSA). To scale up to a 1 km (AVHRR) moss map of the BOREAS region, we used the TM SSA mosaics plus regional field data to identify AVHRR overstory-ground cover associations. We found that: 1) ground cover, overstory composition and density are highly correlated, permitting inference of moss and lichen cover from satellite-based land cover classifications; 2) our 1 km moss map reveals that mosses dominate the boreal landscape of central Canada, thereby a significant factor for water, energy, and carbon modeling; 3) TM and AVHRR moss cover maps are comparable; 4) satellite data resolution is important; particularly in detecting the smaller wetland features, lakes, and upland jack pine sites; and 5) distinct regional patterns of moss and lichen cover correspond to latitudinal and elevational gradients. Copyright 2001 by the American Geophysical Union.

Journal of Geophysical Research D: Atmospheres↗

USGS1998

On the influence of biomass burning on the seasonal CO2 signal as observed at monitoring stations

We investigated the role of biomass burning in simulating the seasonal signal in both prognostic and diagnostic analyses. The prognostic analysis involved the High-Resolution Biosphere Model, a prognostic terrestrial biosphere model, and the coupled vegetation fire module, which together produce a prognostic data set of biomass burning. The diagnostic analysis involved the Simple Diagnostic Biosphere Model (SDBM) and the Hao and Liu [1994] diagnostic data set of biomass burning, which have been scaled to global 2 and 4 Pg C yr −1 , respectively. The monthly carbon exchange fields between the atmosphere and the biosphere with a spatial resolution of 0.5° × 0.5°, the seasonal atmosphere-ocean exchange fields, and the emissions from fossil fuels have been coupled to the three-dimensional atmospheric transport model TM2. We have chosen eight monitoring stations of the National Oceanic and Atmospheric Administration network to compare the predicted seasonal atmospheric CO 2 signals with those deduced from atmosphere-biosphere carbon exchange fluxes without any contribution from biomass burning. The prognostic analysis and the diagnostic analysis with global burning emissions of 4 Pg C yr −1 agree with respect to the change in the amplitude of the seasonal CO 2 concentration introduced through biomass burning. We find that the seasonal CO 2 signal at stations in higher northern latitudes (north of 30°N) is marginally influenced by biomass burning. For stations in tropical regions an increase in the CO 2 amplitude of more than 1 ppmv (up to 50% with respect to the observed trough to peak amplitude) has been calculated. Biomass burning at stations farther south accounts for an increase in the CO 2 amplitude of up to 59% (0.6 ppmv). A change in the phase of the seasonal CO 2 signal at tropical and southern stations has been shown to be strongly influenced by the onset of biomass burning in southern tropical Africa and America. Comparing simulated and observed seasonal CO 2 signals, we find higher discrepancies at southern tropical stations if biomass burning emissions are included. This is caused by the additional increase in the amplitude in the prognostic analysis and a phase shift in a diagnostic analysis. In contrast, at the northern tropical stations biomass burning tends to improve the estimates of the seasonal CO 2 signal in the prognostic analysis because of strengthening of the amplitude. Since the SDBM predicts the seasonal CO 2 signal reasonably well for the northern hemisphere tropical stations, no general improvement of the fit occurs if biomass burning emissions are considered.

Global Biogeochemical Cycles↗