969 resultados para Forest site quality


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The relationship between site characteristics and understorey vegetation composition was analysed with quantitative methods, especially from the viewpoint of site quality estimation. Theoretical models were applied to an empirical data set collected from the upland forests of southern Finland comprising 104 sites dominated by Scots pine (Pinus sylvestris L.), and 165 sites dominated by Norway spruce (Picea abies (L.) Karsten). Site index H100 was used as an independent measure of site quality. A new model for the estimation of site quality at sites with a known understorey vegetation composition was introduced. It is based on the application of Bayes' theorem to the density function of site quality within the study area combined with the species-specific presence-absence response curves. The resulting posterior probability density function may be used for calculating an estimate for the site variable. Using this method, a jackknife estimate of site index H100 was calculated separately for pine- and spruce-dominated sites. The results indicated that the cross-validation root mean squared error (RMSEcv) of the estimates improved from 2.98 m down to 2.34 m relative to the "null" model (standard deviation of the sample distribution) in pine-dominated forests. In spruce-dominated forests RMSEcv decreased from 3.94 m down to 3.16 m. In order to assess these results, four other estimation methods based on understorey vegetation composition were applied to the same data set. The results showed that none of the methods was clearly superior to the others. In pine-dominated forests, RMSEcv varied between 2.34 and 2.47 m, and the corresponding range for spruce-dominated forests was from 3.13 to 3.57 m.

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This paper develops a dynamic model for cost-effective selection of sites for restoring biodiversity when habitat quality develops over time and is uncertain. A safety-first decision criterion is used for ensuring a minimum level of habitats, and this is formulated in a chance-constrained programming framework. The theoretical results show; (i) inclusion of quality growth reduces overall cost for achieving a future biodiversity target from relatively early establishment of habitats, but (ii) consideration of uncertainty in growth increases total cost and delays establishment, and (iii) cost-effective trading of habitat requires exchange rate between sites that varies over time. An empirical application to the red listed umbrella species - white-backed woodpecker - shows that the total cost of achieving habitat targets specified in the Swedish recovery plan is doubled if the target is to be achieved with high reliability, and that equilibrating price on a habitat trading market differs considerably between different quality growth combinations. © 2013 Elsevier GmbH.

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There is growing evidence that organo-nitrogen compounds may constitute a significant fraction of the aerosol nitrogen (N) budget. However, very little is known about the abundance and origin of this aerosol fraction. In this study, the concentration of organic nitrogen (ON) and major inorganic ions in PM2.5 aerosol were measured at the Duke Forest Research Facility near Chapel Hill, NC, during January and June of 2007. A novel on-line instrument was used, which is based on the Steam Jet Aerosol Collector (SJAC) coupled to an on-line total carbon/total nitrogen analyzer and two on-line ion chromatographs. The concentration of ON was determined by tracking the difference in concentrations of total nitrogen and of inorganic nitrogen (determined as the sum of N-ammonium and N-nitrate). The time resolution of the instrument was 30 min with a detection limit for major aerosol components of ∼0.1 mu;gm-3. Nitrogen in organic compounds contributed ∼33% on average to the total nitrogen concentration in PM2.5, illustrating the importance of this aerosol component. Absolute concentrations of ON, however, were relatively low (lt;1.0 mu;gm-3) with an average of 0.16 mu;gm-3. The absolute and relative contribution of ON to the total aerosol nitrogen budget was practically the same in January and June. In January, the concentration of ON tended to be higher during the night and early morning, while in June it tended to be higher during the late afternoon and evening. Back-trajectories and correlation with wind direction indicate that higher concentrations of ON occur in air masses originating over the continental US, while marine air masses are characterized by lower ON concentrations. The data presented in this study suggests that ON has a variety of sources, which are very difficult to quantify without information on chemical composition of this important aerosol fraction.

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Background: Organizational features can affect how staff view their quality of work life. Determining staff perceptions about quality of work life is an important consideration for employers interested in improving employee job satisfaction. The purpose of this study was to identify organization specific predictors of job satisfaction within a health care system that consisted of six independent health care organizations.

Methods: 5,486 full, part and causal time (non-physician) staff on active payroll within six organizations (2 community hospitals, 1 community hospital/long-term care facility, 1 long-term care facility, 1 tertiary care/community health centre, and 1 visiting nursing agency) located in five communities in Central West Ontario, Canada were asked to complete a 65-item quality of work life survey. The self-administered questionnaires collected staff perceptions of: co-worker and supervisor support; teamwork and communication; job demands and decision authority; organization characteristics; patient/resident care; compensation and benefits; staff training and development; and impressions of the organization. Socio-demographic data were also collected.

Results: Depending on the organization, between 15 and 30 (of the 40 potential predictor) variables were found to be statistically associated with job satisfaction (univariate analyses). Logistic regression analyses identified the best predictors of job satisfaction and these are presented for each of the six organizations and for all organizations combined.

Conclusions: The findings indicate that job satisfaction is a multidimensional construct and although there appear to be some commonalities across organizations, some predictors of job satisfaction appear to be organization and context specific.

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Aerosol physical and chemical properties were measured in a forest site in central Amazonia (Cuieiras reservation, 2.61S; 60.21W) during the dry season of 2004 (Aug-Oct). Aerosol light scattering and absorption, mass concentration, elemental composition and size distributions were measured at three tower levels (Ground: 2 m; Canopy: 28 m, and Top: 40 m). For the first time, simultaneous eddy covariance fluxes of fine mode particles and volatile organic compounds (VOC) were measured above the Amazonian forest canopy. Aerosol fluxes were measured by eddy covariance using a Condensation Particle Counter (CPC) and a sonic anemometer. VOC fluxes were measured by disjunct eddy covariance using a Proton Transfer Reaction Mass Spectrometer (PTR-MS). At nighttime, a strong vertical gradient of phosphorus and potassium in the aerosol coarse mode was observed, with higher concentrations at Ground level. This suggests a source of primary biogenic particles below the canopy. Equivalent black carbon measurements indicate the presence of light-absorbing aerosols from biogenic origin. Aerosol number size distributions typically consisted of superimposed Aitken (76 nm) and accumulation modes (144 nm), without clear events of new particle formation. Isoprene and monoterpene fluxes reached respectively 7.4 and 0.82 mg m(-2) s(-1) around noon. An average fine particle flux of 0.05 +/- 0.10 10(6) m(-2) s(-1) was calculated, denoting an equilibrium between emission and deposition fluxes of fine mode particles at daytime. No significant correlations were found between VOC and fine mode aerosol concentrations or fluxes. (C) 2009 Elsevier Ltd. All rights reserved.

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O gênero Gochnatia é comumente encontrado em diferentes fitofisionomias do Cerrado do Estado de São Paulo, crescendo desde ambientes mais abertos até áreas florestais mais fechadas. Aqui foram comparadas a anatomia foliar e alguns parâmetros ecofisiológicos de duas espécies do gênero Gochnatia, uma arbustiva (Gochnatia barrosii Cabrera) e a outra arbórea (Gochnatia polymorpha (Less.) Cabrera), ambas ocorrendo em área de cerradão na Estação Ecológica de Assis, SP. Encontraram-se diferenças estruturais qualitativas entre as espécies, com G. barrosii apresentando folhas anfiestomáticas, com epiderme unisseriada e G. polymorpha apresentando folhas hipoestomáticas, com epiderme múltipla ou hipoderme, na face adaxial. Além disso, as folhas de G. barrosii apresentaram menores valores para a espessura dos tecidos (com exceção da epiderme na face abaxial) e da folha em relação a G. polymorpha. Foram observadas diferenças na assimilação de CO2 tanto em base de área quanto de massa seca foliar, além de diferenças na área foliar específica, sendo esta maior em G. barrosii. Apesar das folhas de G. barrosii possuírem estrutura bem menos escleromorfa do que as folhas de G. polymorpha, não foram encontradas diferenças na eficiência do uso de água. Os resultados sugerem que espécies de formas distintas de crescimento de um mesmo gênero possuem características foliares diferenciadas para lidar com as variações ambientais a que são submetidas.

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Detailed environmental land characterization is essential for technical and financial planning, for both the scientific point of view and technological application. This work aimed at the physiographic and pedological characterization and eucalyptus productivity mapping at Itatinga Forest Sciences Experimental Station (southeastern Brazil), using geographic information systems in order to identify possible cause-effect relationships between forest productivity and soil attributes. The digital cartographic dataset was structured as follows: as primary source of data, aerial photograph and field survey were used and, as a secondary source, topographical, geological and land use occupation maps were used. For mapping wood productivity at age six (MAI6, Mean Annual Increment), inventory data of permanent plots (same species, provenance and age) were used, which were obtained from Eucalyptus grandis plantations. Using simple linear correlation and backward stepwise multiple regression analysis, the dependent variable (MAI) was related with physical and chemical characteristics of the soils. Two standards of contour curves were identified, one with close curves, narrow and surrounding the drainage network, in the steeper and lower altitude areas; the other, with spaced contour lines, in the areas of higher altitude and with plane relief. Six types of soils were characterized as being highly related to the physiographic patterns of the area: loamy sandy to sandy clayey Typic Hapludox (LVAd, 47.5%), clayey Rhodic Hapludox (LVd1, 33.4%), sandy clay Rhodic Hapludox (LVd2, 6%), clayey Rhodic Hapludox (LVdf, 9.1%), Entisols (G, 3.4%) and Fluvents soil (RY, 0.6%). There were large variations in wood productivity in the Eucalyptus grandis plantations, characterized in six classes, ranging from 26 to 52 m(3) ha(-1) yr(-1). These productivity changes were strictly related to soil mapping units. Through multiple regression analysis, we found that clay and organic matter contents were the attributes which most strongly explained the productivity differences.

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"PMS 830"--Cover, v. 1; "PMS 831"--Cover, v. 2; "PMS 832"--Cover, v. 3; "PMS 833"--Cover, v. 4; "PMS 835"--Cover, v. 6; "PMS 838"--Cover, v. 6a; "PMS 839"--Cover. v. 7; "PMS 840"--Cover, v. 8.

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Shipping list no.: 90-262-P.

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"Supersedes U.S. Department of Agriculture Tech. Bull. No. 168 of same title."

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This review highlights the considerable variation found in wood properties impacting timber stiffness and stability such as wood density, spiral grain and microfibril angle. Variation with age, site quality and environment, as well as amongst species, hybrids and genetic stock is reported and opportunities for product-focused wood quality improvement are identified.

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The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

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Decomposition was studied in a reciprocal litter transplant experiment to examine the effects of forest type, litter quality and their interaction on leaf decomposition in four tropical forests in south-east Brazil. Litterbags were used to measure decomposition of leaves of one tree species from each forest type: Calophyllum brasiliense from restinga forest; Guapira opposita from Atlantic forest; Esenbeckia leiocarpa from semi-deciduous forest; and Copaifera langsdorffii from cerradao. Decomposition rates in rain forests (Atlantic and restinga) were twice as fast as those in seasonal forests (semi-deciduous and cerradao), suggesting that intensity and distribution of precipitation are important predictors of decomposition rates at regional scales. Decomposition rates varied by species, in the following order: E. leiocarpa > C. langsdorffii > G. opposita > C. brasiliense. However, there was no correlation between decomposition rates and chemical litter quality parameters: C:N, C:P, lignin concentration and lignin:N. The interaction between forest type and litter quality was positive mainly because C. langsdorffii decomposed faster than expected in its native forest. This is a potential indication of a decomposer`s adaptation to specific substrates in a tropical forest. These findings suggest that besides climate, interactions between decomposers and plants might play an essential role in decomposition processes and it must be better understood.