Changes in timber haul emissions in the context of shifting forest management and infrastructure

<p>Abstract</p> <p>Background</p> <p>Although significant amounts of carbon may be stored in harvested wood products, the extraction of that carbon from the forest generally entails combustion of fossil fuels. The transport of timber from the forest to primary milling facilities may in particular create emissions that reduce the net sequestration value of product carbon storage. However, attempts to quantify the effects of transport on the net effects of forest management typically use relatively sparse survey data to determine transportation emission factors. We developed an approach for systematically determining transport emissions using: 1) -remotely sensed maps to estimate the spatial distribution of harvests, and 2) - industry data to determine landscape-level harvest volumes as well as the location and processing totals of individual mills. These data support spatial network analysis that can produce estimates of fossil carbon released in timber transport.</p> <p>Results</p> <p>Transport-related emissions, evaluated as a fraction of transported wood carbon at 4 points in time on a landscape in western Montana (USA), rose from 0.5% in 1988 to 1.7% in 2004 as local mills closed and spatial patterns of harvest shifted due to decreased logging on federal lands.</p> <p>Conclusion</p> <p>The apparent sensitivity of transport emissions to harvest and infrastructure patterns suggests that timber haul is a dynamic component of forest carbon management that bears further study both across regions and over time. The monitoring approach used here, which draws only from widely available monitoring data, could readily be adapted to provide current and historical estimates of transport emissions in a consistent way across large areas.</p

Satellite-based terrestrial production efficiency modeling

Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research

Plant growth enhancement by elevated CO2 eliminated by joint water and nitrogen limitation

http://www.nature.com/ngeo/Rising atmospheric CO2 concentrations can fertilize plant growth. The resulting increased plant uptake of CO2 could, in turn, slow increases in atmospheric CO2 levels and associated climate warming. CO2 fertilization e ects may be enhanced when water availability is low, because elevated CO2 also leads to improved plant water-use e ciency. However, CO2 fertilization e ects may be weaker when plant growth is limited by nutrient availability. How variation in soil nutrients and water may act together to influence CO2 fertilization is unresolved. Here we report plant biomass levels from a five-year, open-air experiment in a perennial grassland under two contrasting levels of atmospheric CO2, soil nitrogen and summer rainfall, respectively. We find that the presence of a CO2 fertilization e ect depends on the amount of available nitrogen and water. Specifically, elevated CO2 levels led to an increase in plant biomass of more than 33% when summer rainfall, nitrogen supply, or both were at the higher levels (ambient for rainfall and elevated for soil nitrogen). But elevated CO2 concentrations did not increase plant biomass when both rainfall and nitrogen were at their lower level. We conclude that given widespread, simultaneous limitation by water and nutrients, large stimulation of biomass by rising atmospheric CO2 concentrations may not be ubiquitous

A new approach for developing comprehensive agricultural drought index using satellite-derived biophysical parameters and factor analysis method

The accurate assessment of drought and its monitoring is highly depending on the selection of appropriate indices. Despite the availability of countless drought indices, due to variability in environmental properties, a single universally drought index has not been presented yet. In this study, a new approach for developing comprehensive agricultural drought index from satellite-derived biophysical parameters is presented. Therefore, the potential of satellite-derived biophysical parameters for improved understanding of the water status of pistachio (Pistachio vera L.) crop grown in a semiarid area is evaluated. Exploratory factor analysis with principal component extraction method is performed to select the most in?uential parameters from seven biophysical parameters including surface temperature (Ts), surface albedo (a), leaf area index (LAI), soil heat ?ux (Go), soil-adjusted vegetation index (SAVI), normalized difference vegetation index (NDVI), and net radiation (Rn). Ts and Gowere found as the most effective parameters by this method. However, Ts, LAI, a, and SAVI that accounts for 99.6 % of the total variance of seven inputs were selected to model a new biophysical water stress index (BPWSI). The values of BPWSI were stretched independently and compared with the range of actual evapotranspiration estimated through well-known METRIC (mapping evapotranspiration at high resolution with internal calibration) energy balance model. The results showed that BPWSI can be ef?ciently used for the prediction of the pistachio water status (RMSE of 0.52, 0.31, and 0.48 mm/day on three image dates of April 28, July 17, and August 2, 2010). The study con?rmed that crop water status is accounted by several satellite-based biophysical parameters rather than single parameter

Estimating Terrestrial Primary Productivity by Combining Remote Sensing and Ecosystem Simulation

Beginning in 1972 with the launch of Landsat 1, estimation of terrestrial plant production has been one of the most important applications attempted of satellite remote sensing. Initial interest focused on the prediction of regional crop yields, such as wheat (Erickson, 1984). However, changing goals, hardware capabilities, and theory have produced a steady evolution in the approaches taken to calculate net primary production (NPP) of large areas. Interest has also expanded to calculating primary production of natural vegetation. The much wider array of topography, climate, canopy geometry, and life-cycle dynamics exhibited by natural vegetation make computation of primary production much more challenging than the rather controlled, organized field conditions of a crop