Spatial distribution of forest aboveground biomass estimated from remote sensing and forest inventory data in New England, USA.

Abstract We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867 teragram (1012, dry weight) in 2001, with a mean AGB density of 120 Mg/ha (Standard deviation = 54 Mg/ha) ranging from 15 to 240 Mg/ha within a 95% percentile. The majority of regional AGB density was in the range of 80 to 160 Mg/ha (58.2%). High AGB densities were observed along the Appalachian Mountains from northwestern Connecticut to the Green Mountains in Vermont and White Mountains in New Hampshire, while low AGB densities were concentrated in the Downeast area of Maine (ME) and the Cape Cod area of Massachusetts (MA). At the state level, the averaged difference in mean AGB densities between simulated and FIA (as reference) was -2.0% ranging from 0% to -4.2% with a standard error of 3.2%. Within the 95% confidence interval the differences between FIA and simulated AGB densities ranged from 0 to 6% (absolute value). Our study may provide useful information for regional fuel-loading estimates

Carbon changes in conterminous US forests associated with growth and major disturbances.

Abstract We estimated forest area and carbon changes in the conterminous United States using a remote sensing based land cover change map, forest fire data from the Monitoring Trends in Burn Severity program, and forest growth and harvest data from the USDA Forest Service, Forest Inventory and Analysis Program. Natural and human-associated disturbances reduced the forest ecosystems\u27 carbon sink by 36% from 1992 to 2001, compared to that without disturbances in the 48 states. Among the three identified disturbances, forest-related land cover change contributed 33% of the total effect in reducing the forest carbon potential sink, while harvests and fires accounted for 63% and 4% of the total effect, respectively. The nation\u27s forests sequestered 1.6 ± 0.1Pg (1015 petagram) carbon during the period, or 0.18PgCyr-1, with substantial regional variation. The southern region of the United States was a small net carbon source whereas the greater Pacific Northwest region was a strong net sink. Results of the approach fit reasonably well at an aggregate level with other related estimates of the current forest US greenhouse gas inventory, suggesting that further research using this approach is warranted

Carbon benefits from protected areas in the conterminous United States

Background: Conversion of forests to other land cover or land use releases the carbon stored in the forests and reduces carbon sequestration potential of the land. The rate of forest conversion could be reduced by establishing protected areas for biological diversity and other conservation goals. The purpose of this study is to quantify the efficiency and potential of forest land protection for mitigating GHG emissions. Results: The analysis of related national-level datasets shows that during the period of 1992–2001 net forest losses in protected areas were small as compared to those in unprotected areas: -0.74% and −4.07%, respectively. If forest loss rates in protected and unprotected area had been similar, then forest losses in the protected forestlands would be larger by 870 km2/yr forests, that corresponds to release of 7 Tg C/yr (1 Tg=1012 g). Conversely, and continuing to assume no leakage effects or interactions of prices and harvest levels, about 1,200 km2/yr forests could have remained forest during the period of 1992–2001 if net area loss rate in the forestland outside protected areas was reduced by 20%. Not counting carbon in harvested wood products, this is equivalent to reducing fossil-fuel based carbon emissions by 10 Tg C/yr during this period. The South and West had much higher potentials to mitigate GHG emission from reducing loss rates in unprotected forests than that of North region. Spatially, rates of forest loss were higher across the coastal states in the southeastern US than would be expected from their population change, while interior states in the northern US experienced less forest area loss than would have been expected given their demographic characteristics. Conclusions: The estimated carbon benefit from the reduced forest loss based on current protected areas is 7 Tg C/yr, equivalent to the average carbon benefit per year for a previously proposed ten-year $110 million per year tree planting program scenario in the US. If there had been a program that could have reduced forest area loss by 20% in unprotected forestlands during 1992–2001, collectively the benefits from reduced forest loss would be equal to 9.4% of current net forest ecosystem carbon sequestration in the conterminous US

A daily soil temperature model based on air temperature and precipitation for continental applications

Soil temperature is a necessary component for estimating below-ground processes for continental and global carbon budgets; however, there are an insufficient number of climatic stations monitoring soil temperature. We used an 11-day running average of daily mean air temperature to estimate daily mean soil temperature at a depth of 10 cm using linear regression. This model was tested using data from 6 climate regions across the United States. Frequency analyses for 17 of 19 data sets showed that the number of days which were within a +/-3.5 degree C range centered on the measured soil temperature varied from 77 to 96%. The values of R2 between observed and final predicted soil temperatures ranged from 0.85 to 0.96 with standard errors from 1.5 to 2.9 degrees C for all 19 simulations. Changes of soil temperature under snow cover were smaller than those without snow cover. Soil temperature under vegetation cover was also simulated assuming the rate of soil warming under vegetation cover would be reduced with increasing leaf area index according to the Beer-Lambert Law. Annual soil respiration can be estimated from the predicted soil temperature with reasonable accuracy. Daily soil temperature may be predicted from daily air temperature once regional equations have been established, because weather stations in the United States can be generalized into a few regions and sites within each region may use the same equation

Edge effects in fragmented landscapes: A generic model for delineating area of edge influences (D-AEI)

We developed a generic model for delineating area of edge influences D-AEI for quantifying edge effects within a landscape by combining remote sensing, geographic information systems (GIS), moving window (3 x 3), and computer programming techniques. Our model provided a more realistic assessment of edge effects than those based on traditional methods. Unique characteristics of the D-AEI model included: (1) preservation of the spatial characteristics of the landscape structure; (2) incorporation of the most critical parameters controlling edge effects, such as edge orientation, edge contrast, prevailing direction of edge effects, decay value, and interior approximation; and (3) ability to quantify edge effects for various variables at multiple scales. The model is flexible so that the users can define key parameters and generate ecologically relevant output based on environmental and spatial characteristics of the study area and the study purpose. Our results demonstrated that: (a) edge effects were not symmetrically distributed in all directions around clearcuts; (b) AEI was not necessarily continuous around patches; and (c) boundary dynamics and multiple edge effects were clearly reflected across the landscape. Results from this research are important for current and future resource assessments, biological conservation and wildlife habitat management, biodiversity studies of flora and fauna, microclimatic research, future studies on edges and their importance in landscape design and analysis. The model has potential for broader applications in other research areas where human and natural disturbances are evident, at multiple scales from watershed, forest management district, to region. (C) 2000 Elsevier Science B.V

Forest biomass estimated from MODIS and FIA data in the Lake States: MN, WI and MI, USA.

Abstract This study linked the Moderate Resolution Imaging Spectrometer and USDA Forest Service, Forest Inventory and Analysis (FIA) data through empirical models established using high-resolution Landsat Enhanced Thematic Mapper Plus observations to estimate aboveground biomass (AGB) in three Lake States in the north-central USA. While means obtained from larger sample sizes in FIA datasets can be used as reference numbers over large scales, remote sensing (RS)-based observations have the ability to reflect spatial variation of properties of interest within a given area. Thus, combining two national on-going datasets may improve our ability to accurately estimate ecological properties across large scales. Using standard and consistent data sources can reduce uncertainty and provide more comparable results at both temporal and spatial dimensions. We estimated total forest AGB in the region was 1479 Tg (1012 g, dry weight) in 2001 with mean AGB value of 95 mg ha-1 ranging from 4 to 411 mg ha-1 (within 95 per cent percentiles). Mixed forests featured 66 per cent of the total AGB while deciduous and evergreen forests contained 32 and 2 per cent of the total AGB, respectively, at 1-km pixel resolution. Spatially, AGB values increased from north-west to south-east in general. The RS-based estimates indicated a greater range in AGB variations than the FIA data. Deciduous forests were more variable (both in absolute and relative terms) than evergreen forests. The standard deviation of AGB for deciduous forests was 137 mg ha-1, or a coefficient of variation of 92 per cent, that for evergreen forests was 24 mg ha-1, or a coefficient of variation of 37 per cent

Identifying grain-size dependent errors on global forest area estimates and carbon studies.

Abstract Satellite-derived coarse-resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse-resolution maps (e.g., 1 km) inevitably differ from a corresponding fine-resolution map (such as a 30-m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our ability to quantify bias and uncertainty, and provide more accurate estimates of forest area and associated carbon stocks and fluxes. We simulated that global forest area estimated from a 1-km land-cover map (the most practical and finest resolution currently used for global applications) was 947,573 km2 less than that of its corresponding 30-m map (excluding Antarctic and Greenland). This amount of forest could produce 0.57 ± 0.01 petagrams of carbon per year (PgC/yr) as NPP or 0.11 ± 0.002 PgC/yr as NEP equivalent to 4% of the 2.9 PgC/yr missing carbon sink in the 1990s. The most significant underestimation of forest area was in the temperate zone (the more uncertain region regarding the missing carbon sink ) while a relatively small overestimation occurred in the tropic zone as the grain size of satellite-derived land-cover maps increases from 30 m to 1 km

Satellite detection of land-use change and effects on regional forest aboveground biomass estimates.

Abstract We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha-1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data and land-cover map (University of Maryland) from Advanced Very High Resolution Radiometer (AVHRR) and 2001 products from Moderate Resolution Imaging Spectroradiometer (MODIS) at 1-km resolution for the region; and 30-m resolution land-cover maps from the National Land Cover Data (NLCD) for a subarea to conduct nine simulations to address our questions. Sensitivity analysis showed that (1) AVHRR data tended to underestimate AGB density by 11%, on average, compared to that estimated using MODIS data; (2) regional mean AGB density increased slightly from 124 (1992) to 126 Mg·ha-1 (2001) by 1.6%; (3) a substantial decrease in total forest AGB across the region was detected, from 2,507 (1992) to 1,961 Tg (2001), an annual rate of -2.4%; and (4) in the subarea, while NLCD-based estimates suggested a 26% decrease in total AGB from 1992 to 2001, AVHRR/MODIS-based estimates indicated a 36% increase. The major source of uncertainty in change detection of total forest AGB over large areas was due to area differences from using land-cover maps produced by different sources. Scaling up 30-m land-cover map to 1-km resolution caused a mean difference of 8% (in absolute value) in forest area estimates at the county-level ranging from 0 to 17% within a 95% confidence interval

Assessing net carbon sequestration on urban and community forests of northern New England, USA.

Abstract Urban and community forests play an important role in the overall carbon budget of the USA. Accurately quantifying carbon sequestration by these forests can provide insight for strategic planning to mitigate greenhouse gas effects on climate change. This study provides a new methodology to estimate net forest carbon sequestration (FCS) in urban and community lands of northern New England using ground based forest growth rates, housing density data, satellite derived land cover and tree canopy cover maps at the county level. We estimated that the region\u27s urban and community forests sequestered 603,200. tC/yr ($38.7. million/yr value), contributing 8.2% of regional net forest ecosystem carbon sequestration. The contributions at the state level varied from 2.3% in Vermont to 16.6% in New Hampshire with substantial variation at the county level up to 73.3%. Spatially, contribution rates from urban and community forests at the county level were much higher and concentrated in southeast portion of NH and southwest portion of ME along the coast, and decreased toward inland areas. Our estimated net FCS compared reasonably with gross FCS in the region reported by a previous study. On average, the net FCS was 34.2% lower (varying from 41.9% lower in Vermont to 28.1% lower in Maine) than the corresponding gross FCS mainly because of a lower regional average net growth rate used in this study, compared to the national average gross carbon sequestration rate used in the previous study