967 resultados para Forest surveys
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Mode of access: Internet.
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"October 1993"--P. [1].
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"August 1938."
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"Computations in charge of P.R. Wheeler."
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"December 1940."
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Contribution from Forest Service.
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"Urban forest effects model."
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"December 2006"--T.p. verso.
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"April 2004."
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Estimates of potential and actual C sequestration require areal information about various types of management activities. Forest surveys, land use data, and agricultural statistics contribute information enabling calculation of the impacts of current and historical land management on C sequestration in biomass (in forests) or in soil (in agricultural systems). Unfortunately little information exists on the distribution of various management activities that can impact soil C content in grassland systems. Limited information of this type restricts our ability to carry out bottom-up estimates of the current C balance of grasslands or to assess the potential for grasslands to act as C sinks with changes in management. Here we review currently available information about grassland management, how that information could be related to information about the impacts of management on soil C stocks, information that may be available in the future, and needs that remain to be filled before in-depth assessments may be carried out. We also evaluate constraints induced by variability in information sources within and between countries. It is readily apparent that activity data for grassland management is collected less frequently and on a coarser scale than data for forest or agricultural inventories and that grassland activity data cannot be directly translated into IPCC-type factors as is done for IPCC inventories of agricultural soils. However, those management data that are available can serve to delineate broad-scale differences in management activities within regions in which soil C is likely to change in response to changes in management. This, coupled with the distinct possibility of more intensive surveys planned in the future, may enable more accurate assessments of grassland C dynamics with higher resolution both spatially and in the number management activities.
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1. The relationship between species richness and ecosystem function, as measured by productivity or biomass, is of long-standing theoretical and practical interest in ecology. This is especially true for forests, which represent a majority of global biomass, productivity and biodiversity. 2. Here, we conduct an analysis of relationships between tree species richness, biomass and productivity in 25 forest plots of area 8-50ha from across the world. The data were collected using standardized protocols, obviating the need to correct for methodological differences that plague many studies on this topic. 3. We found that at very small spatial grains (0.04ha) species richness was generally positively related to productivity and biomass within plots, with a doubling of species richness corresponding to an average 48% increase in productivity and 53% increase in biomass. At larger spatial grains (0.25ha, 1ha), results were mixed, with negative relationships becoming more common. The results were qualitatively similar but much weaker when we controlled for stem density: at the 0.04ha spatial grain, a doubling of species richness corresponded to a 5% increase in productivity and 7% increase in biomass. Productivity and biomass were themselves almost always positively related at all spatial grains. 4. Synthesis. This is the first cross-site study of the effect of tree species richness on forest biomass and productivity that systematically varies spatial grain within a controlled methodology. The scale-dependent results are consistent with theoretical models in which sampling effects and niche complementarity dominate at small scales, while environmental gradients drive patterns at large scales. Our study shows that the relationship of tree species richness with biomass and productivity changes qualitatively when moving from scales typical of forest surveys (0.04ha) to slightly larger scales (0.25 and 1ha). This needs to be recognized in forest conservation policy and management.
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Issued originally as Forestry circular no. 1.
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"Funds for this publication were provided by the Illinois Forestry Development Council, Illinois Department of Natural Resources, Division of Forest Resources, and by the Dept. of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign"--T.p. verso.
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Mode of access: Internet.
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Forest health surveillance (FHS) of hardwood plantations commenced in Queensland in 1997 as plantations expanded following a state government planting initiative arising from the national 2020 forest policy vision. The estate was initially characterised by a large number of small plantations (10-50 ha), although this has changed more recently with the concentration of larger plantations in the central coast and South Burnett regions. Due to the disparate nature of the resource, drive- and walkthrough surveys of subsets of plantations have been undertaken in preference to aerial surveys. FHS has been effective in detecting a number of new hardwood pests in Queensland including erinose mites (Rhombacus and Acalox spp.), western white gum plate galler (Ophelimus sp.), Creiis psyllid and bronzing bug (Thaumastocoris sp.), in evaluating their potential impact and assisting in focussing future research efforts. Since 2003 there has been an increased emphasis on training operational staff to take a greater role in identifying and reporting on forest health issues. This has increased their awareness of forest health issues, but their limited time to specifically survey and report on pests and diseases, and high rates of staff turnover, necessitate frequent ongoing training. Consequently, common and widespread problems such as quambalaria shoot blight (Quambalaria pitereka), chrysomelid leaf beetles (mainly Paropsis atomaria) and erinose mites may be under-reported or not reported, and absence data may often not be recorded at all. Comment is made on the future directions that FHS may take in hardwood plantations in Queensland.