Ontario Forest Research Institute

About: Ontario Forest Research Institute is a facility organization based out in Sault Ste. Marie, Ontario, Canada. It is known for research contribution in the topics: Black spruce & Forest management. The organization has 82 authors who have published 162 publications receiving 7411 citations.

Changes in Forest Biomass Carbon Storage in China Between 1949 and 1998

Abstract: The location and mechanisms responsible for the carbon sink in northern mid-latitude lands are uncertain. Here, we used an improved estimation method of forest biomass and a 50-year national forest resource inventory in China to estimate changes in the storage of living biomass between 1949 and 1998. Our results suggest that Chinese forests released about 0.68 petagram of carbon between 1949 and 1980, for an annual emission rate of 0.022 petagram of carbon. Carbon storage increased significantly after the late 1970s from 4.38 to 4.75 petagram of carbon by 1998, for a mean accumulation rate of 0.021 petagram of carbon per year, mainly due to forest expansion and regrowth. Since the mid-1970s, planted forests (afforestation and reforestation) have sequestered 0.45 petagram of carbon, and their average carbon density increased from 15.3 to 31.1 megagrams per hectare, while natural forests have lost an additional 0.14 petagram of carbon, suggesting that carbon sequestration through forest management practices addressed in the Kyoto Protocol could help offset industrial carbon dioxide emissions.

Forest bioenergy or forest carbon? Assessing trade-offs in greenhouse gas mitigation with wood-based fuels.

Abstract: The potential of forest-based bioenergy to reduce greenhouse gas (GHG) emissions when displacing fossil-based energy must be balanced with forest carbon implications related to biomass harvest. We integrate life cycle assessment (LCA) and forest carbon analysis to assess total GHG emissions of forest bioenergy over time. Application of the method to case studies of wood pellet and ethanol production from forest biomass reveals a substantial reduction in forest carbon due to bioenergy production. For all cases, harvest-related forest carbon reductions and associated GHG emissions initially exceed avoided fossil fuel-related emissions, temporarily increasing overall emissions. In the long term, electricity generation from pellets reduces overall emissions relative to coal, although forest carbon losses delay net GHG mitigation by 16−38 years, depending on biomass source (harvest residues/standing trees). Ethanol produced from standing trees increases overall emissions throughout 100 years of continuous prod...

Interannual Variability in Net Primary Production and Precipitation

Abstract: Knapp and Smith (1) suggested that interannual variability in aboveground net primary production (ANPP) is not related to fluctuations in precipitation, based on analysis of data from 11 Long-Term Ecological Research sites across North America. This finding, if applicable to other regions, is crucial to climate change research, because it may necessitate revisions of projections of ecosystem responses to climate change (2, 3). To examine the relationship between variability in net primary production (NPP) and precipitation at a broad scale, a longterm normalized difference vegetation index (NDVI) data set derived from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA), coupled with a historical climate data set, should constitute a useful and powerful data source, because NDVI data are strongly correlated with terrestrial NPP and are frequently used as NPP predictors (4, 5). We used an annual mean NDVI data set over China to quantify temporal NPP variability relative to precipitation variation, and used coefficient of variation (CV) to express the magnitude of interannual variability in NDVI and precipitation. We then calculated CVs of these two variables for each pixel, with a resolution of 0.1° latitude by 0.1° longitude, for five biome groups across China—forest, grassland, desert, alpine vegetation, and cropland (6 )—using 1982 to 1999 NDVI and precipitation data compiled in China (7 ). We assumed that interannual variability in NDVI or NPP was related to temporal variability in precipitation if the correlation between CVs for NDVI or NPP and precipitation were identified as statistically significant. The CV value of NDVI for these five biome groups showed a large spatial variation, with a mean CV of 8.3% for the forest biome group, 10.4% for grasslands, 24.6% for desert areas, 12.7% for alpine vegetation, and 9.3 % for cropland. The largest variation occurred in the desert bi