Fog deposition is a notable component of the water budget of herbaceous-shrub ecosystems on the central and southern coastal regions of California. This paper presents an analysis of fog water deposition rates and meteorological controls in Big Sur, California. Mesh-screen fog collectors were installed the Brazil Ranch weather station sites to measure fog water during the summer seasons of 2010 and 2011. Fog deposition occurred during 73% of days recorded in 2010 and 87% of days recorded in 2011. The daily average deposition rate was 2.29 L/m<sup>2</sup> in 2010 and 3.86 L/m<sup>2</sup> in 2011. The meteorological variables which had the greatest influence on prediction of fog deposition were wind speed, wind direction, and the dew-point depression (difference between air temperature and dew point). Based on these results, we hypothesize that high rates of summer fog deposition help sustain the productivity of California coastal vegetation through periods of low rainfall
Satellite remote sensing was combined with the NASA-CASA (Carnegie Ames Stanford Approach) carbon cycle simulation model to evaluate the impact of the 2010 drought (July through September) throughout tropical South America. Results indicated that net primary production in Amazon forest areas declined by an average of 7% in 2010 compared to 2008. This represented a loss of vegetation CO 2 uptake and potential Amazon rainforest growth of nearly 0.5 Pg C in 2010. The largest overall decline in ecosystem carbon gains by land cover type was predicted for closed broadleaf forest areas of the Amazon river basin, including a large fraction of regularly flooded forest areas. Model results support the hypothesis that soil and dead wood carbon decomposition fluxes of CO 2 to the atmosphere were elevated during the drought period of 2010 in periodically flooded forest areas, compared to those for forests outside the main river floodplains.
The CASA (Carnegie-Ames-Stanford) ecosystem model based on satellite greenness observations has been used to estimate monthly carbon fluxes in terrestrial ecosystems from 2000 to 2009. The CASA model was driven by NASA Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation cover properties and large-scale (1-km resolution) disturbance events detected in biweekly time series data. This modeling framework has been implemented to estimate historical as well as current monthly patterns in plant carbon fixation, living biomass increments, and long-term decay of woody (slash) pools before, during, and after land cover disturbance events. Results showed that CASA model predictions closely followed the seasonal timing of Ameriflux tower measurements. At a global level, predicting net ecosystem production (NEP) flux for atmospheric CO<sub>2</sub> from 2000 through 2005 showed a roughly balanced terrestrial biosphere carbon cycle. Beginning in 2006, global NEP fluxes became increasingly imbalanced, starting from -0.9 Pg C yr<sup>-1</sup> to the largest negative (total net terrestrial source) flux of -2.2 Pg C yr<sup>-1</sup> in 2009. In addition, the global sum of CO<sub>2</sub> emissions from forest disturbance and biomass burning for 2009 was predicted at 0.51 Pg C yr<sup>-1</sup>. These results demonstrate the potential to monitor and validate terrestrial carbon fluxes using NASA satellite data as inputs to ecosystem models
BackgroundThe objective of this study was to demonstrate a new, cost-effective method to define the sustainable amounts of harvested wood products in Southeast Asian countries case studies, while avoiding degradation (net loss) of total wood carbon stocks. Satellite remote sensing from the MODIS sensor was used in the CASA (Carnegie Ames Stanford Approach) carbon cycle model to map forest production for the Southeast Asia region from 2000 to 2010. These CASA model results have been designed to be spatially detailed enough to support carbon cycle assessments in different wooded land cover classes, e.g., open woodlands, wetlands, and forest areas.ResultsThe country with the highest average forest net primary production (NPP greater than 950 g C m-2 yr-1) over the period was the Philippines, followed by Malaysia and Indonesia. Myanmar and Vietnam had the lowest average forest NPP among the region’s countries at less than 815 g C m-2 yr-1. Case studies from throughout the Southeast Asia region for the maximum harvested wood products amount that could be sustainably extracted per year were generated using the CASA model NPP predictions.ConclusionsThe method of using CASA model’s estimated annual change in forest carbon on a yearly basis can conservatively define the upper limit for the amount of harvested wood products that can be removed and still avoid degradation (net loss) of the total wood carbon stock over that same time period.
In this study, we present results from the CASA (Carnegie-Ames-Stanford Approach) model to estimate net primary production (NPP) in grasslands under different management (ranching versus unmanaged) on the Central Coast of California. The latest model version called CASA Express has been designed to estimate monthly patterns in carbon fixation and plant biomass production using moderate spatial resolution (30 m to 250 m) satellite image data of surface vegetation characteristics. Landsat imagery with 30 m resolution was adjusted by contemporaneous Moderate Resolution Imaging Spectroradiometer (MODIS) data to calibrate the model based on previous CASA research. Results showed annual NPP predictions of between 300 - 450 grams C per square meter for coastal rangeland sites. Irrigation increased the predicted NPP carbon flux of grazed lands by 59 grams C per square meter annually compared to unmanaged grasslands. Low intensity grazing activity appeared to promote higher grass regrowth until June, compared to the ungrazed grassland sites. These modeling methods were shown to be successful in capturing the differing seasonal growing cycles of rangeland forage production across the area of individual ranch properties
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