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.

Relationships between major ownerships, forest aboveground biomass distributions, and landscape dynamics in the New England region of USA.

This study utilizes remote sensing derived forest aboveground biomass (AGB) estimates and ownership information obtained from the Protected Areas Database (PAD), combining landscape analyses and GIS techniques to demonstrate how different ownerships (public, regulated private, and other private) relate to the spatial distribution of AGB in New England states of the USA. "Regulated private" lands were dominated by lands in Maine covered by a Land Use Regulatory Commission. The AGB means between all pairs of the identified ownership categories were significantly different (P < 0.05). Mean AGB observed in public lands (156 Mg/ha) was 43% higher than that in regulated private lands (109 Mg/ha), or 30% higher than that of private lands as a whole. Seventy-seven percent of the regional forests (or about 9,300 km(2)) with AGB >200 Mg/ha were located outside the area designated in the PAD and concentrated in western MA, southern VT, southwestern NH, and northwestern CT. While relatively unfragmented and high-AGB forests (>200 Mg/ha) accounted for about 8% of total forested land, they were unevenly proportioned among the three major ownership groups across the region: 19.6% of the public land, 0.8% of the regulated private land, and 11.0% of the other private land. Mean disturbance rates (in absolute value) between 1992 and 2001 were 16, 66, and 19 percent, respectively, on public, regulated private, and other private land. This indicates that management practices from different ownerships have a strong impact on dynamic changes of landscape structures and AGB distributions. Our results may provide insight information for policy makers on issues regarding forest carbon management, conservation biology, and biodiversity studies at regional level.

Global potential net primary production predicted from vegetation class, precipitation, and temperature.

Net primary production (NPP), the difference between CO2 fixed by photosynthesis and CO2 lost to autotrophic respiration, is one of the most important components of the carbon cycle. Our goal was to develop a simple regression model to estimate global NPP using climate and land cover data. Approximately 5600 global data points with observed mean annual NPP, land cover class, precipitation, and temperature were compiled. Precipitation was better correlated with NPP than temperature, and it explained much more of the variability in mean annual NPP for grass- or shrub-dominated systems (r2 = 0.68) than for tree-dominated systems (r2 = 0.39). For a given precipitation level, tree-dominated systems had significantly higher NPP (approximately 100-150 g C m(-2) yr(-1)) than non-tree-dominated systems. Consequently, previous empirical models developed to predict NPP based on precipitation and temperature (e.g., the Miami model) tended to overestimate NPP for non-tree-dominated systems. Our new model developed at the National Center for Ecological Analysis and Synthesis (the NCEAS model) predicts NPP for tree-dominated systems based on precipitation and temperature; but for non-tree-dominated systems NPP is solely a function of precipitation because including a temperature function increased model error for these systems. Lower NPP in non-tree-dominated systems is likely related to decreased water and nutrient use efficiency and higher nutrient loss rates from more frequent fire disturbances. Late 20th century aboveground and total NPP for global potential native vegetation using the NCEAS model are estimated to be approximately 28 Pg and approximately 46 Pg C/yr, respectively. The NCEAS model estimated an approximately 13% increase in global total NPP for potential vegetation from 1901 to 2000 based on changing precipitation and temperature patterns.

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

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.