The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform

João P. De Maçaneiro - One of the best experts on this subject based on the ideXlab platform.

  • generic and specific stem volume models for three subtropical Forest Types in southern brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    K volume models, calibrated on large datasets in tropical and subtropical Forests, are rare. & Aims This study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare speciesspecific and generic models.

  • Generic and specific stem volume models for three subtropical Forest Types in southern Brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    Key messageWe adjusted generic models for species-rich Forest Types and specific models for 15 species. Regression assumptions, lack of fitness and goodness of fit and comparison between models were assessed analytically. Generic models produced estimates not less reliable than species-specific models. Logarithmic models presented the best results of adjustment and evenness of residual variance.ContextAssessment of dendrometric variables is important to obtain accurate estimates of stand attributes as biomass and carbon stock estimates. Some of them, as tree height and stem volume, are difficult and expensive to measure; volume models, calibrated on large datasets in tropical and subtropical Forests, are rare.AimsThis study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare species-specific and generic models.MethodsData from 418 sample plots were used to adjust generic models for Forest Types and specific models for 15 species. Regression assumptions, modelling efficiency, lack of fitness, goodness of fit and comparison between species-specific and generic models were assessed by analytical methods.ResultsLogarithmic models presented the best results of adjustment and evenness of residual variance. Lack of fit F test showed acceptable adjust quality for nearly all species-specific and generic models; R2adj* and modelling efficiency measure presented values close to 1 for all fitted models; model identity F test showed differences between specific and generic models in some cases.ConclusionSince regression assumptions were satisfied and because of their quality of fit, the fitted models compose useful tools for predicting total stem volume (with bark) for Forest remnants in southern Brazil. Stratification of datasets by Forest type for model fitting showed to be necessary, but, commonly, generic models for Forest Types produced estimates not less reliable than species-specific models.

Alexander C. Vibrans - One of the best experts on this subject based on the ideXlab platform.

  • generic and specific stem volume models for three subtropical Forest Types in southern brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    K volume models, calibrated on large datasets in tropical and subtropical Forests, are rare. & Aims This study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare speciesspecific and generic models.

  • Generic and specific stem volume models for three subtropical Forest Types in southern Brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    Key messageWe adjusted generic models for species-rich Forest Types and specific models for 15 species. Regression assumptions, lack of fitness and goodness of fit and comparison between models were assessed analytically. Generic models produced estimates not less reliable than species-specific models. Logarithmic models presented the best results of adjustment and evenness of residual variance.ContextAssessment of dendrometric variables is important to obtain accurate estimates of stand attributes as biomass and carbon stock estimates. Some of them, as tree height and stem volume, are difficult and expensive to measure; volume models, calibrated on large datasets in tropical and subtropical Forests, are rare.AimsThis study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare species-specific and generic models.MethodsData from 418 sample plots were used to adjust generic models for Forest Types and specific models for 15 species. Regression assumptions, modelling efficiency, lack of fitness, goodness of fit and comparison between species-specific and generic models were assessed by analytical methods.ResultsLogarithmic models presented the best results of adjustment and evenness of residual variance. Lack of fit F test showed acceptable adjust quality for nearly all species-specific and generic models; R2adj* and modelling efficiency measure presented values close to 1 for all fitted models; model identity F test showed differences between specific and generic models in some cases.ConclusionSince regression assumptions were satisfied and because of their quality of fit, the fitted models compose useful tools for predicting total stem volume (with bark) for Forest remnants in southern Brazil. Stratification of datasets by Forest type for model fitting showed to be necessary, but, commonly, generic models for Forest Types produced estimates not less reliable than species-specific models.

Paolo Moser - One of the best experts on this subject based on the ideXlab platform.

  • generic and specific stem volume models for three subtropical Forest Types in southern brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    K volume models, calibrated on large datasets in tropical and subtropical Forests, are rare. & Aims This study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare speciesspecific and generic models.

  • Generic and specific stem volume models for three subtropical Forest Types in southern Brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    Key messageWe adjusted generic models for species-rich Forest Types and specific models for 15 species. Regression assumptions, lack of fitness and goodness of fit and comparison between models were assessed analytically. Generic models produced estimates not less reliable than species-specific models. Logarithmic models presented the best results of adjustment and evenness of residual variance.ContextAssessment of dendrometric variables is important to obtain accurate estimates of stand attributes as biomass and carbon stock estimates. Some of them, as tree height and stem volume, are difficult and expensive to measure; volume models, calibrated on large datasets in tropical and subtropical Forests, are rare.AimsThis study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare species-specific and generic models.MethodsData from 418 sample plots were used to adjust generic models for Forest Types and specific models for 15 species. Regression assumptions, modelling efficiency, lack of fitness, goodness of fit and comparison between species-specific and generic models were assessed by analytical methods.ResultsLogarithmic models presented the best results of adjustment and evenness of residual variance. Lack of fit F test showed acceptable adjust quality for nearly all species-specific and generic models; R2adj* and modelling efficiency measure presented values close to 1 for all fitted models; model identity F test showed differences between specific and generic models in some cases.ConclusionSince regression assumptions were satisfied and because of their quality of fit, the fitted models compose useful tools for predicting total stem volume (with bark) for Forest remnants in southern Brazil. Stratification of datasets by Forest type for model fitting showed to be necessary, but, commonly, generic models for Forest Types produced estimates not less reliable than species-specific models.

Laio Z. Oliveira - One of the best experts on this subject based on the ideXlab platform.

  • generic and specific stem volume models for three subtropical Forest Types in southern brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    K volume models, calibrated on large datasets in tropical and subtropical Forests, are rare. & Aims This study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare speciesspecific and generic models.

  • Generic and specific stem volume models for three subtropical Forest Types in southern Brazil
    Annals of Forest Science, 2015
    Co-Authors: Alexander C. Vibrans, Paolo Moser, Laio Z. Oliveira, João P. De Maçaneiro
    Abstract:

    Key messageWe adjusted generic models for species-rich Forest Types and specific models for 15 species. Regression assumptions, lack of fitness and goodness of fit and comparison between models were assessed analytically. Generic models produced estimates not less reliable than species-specific models. Logarithmic models presented the best results of adjustment and evenness of residual variance.ContextAssessment of dendrometric variables is important to obtain accurate estimates of stand attributes as biomass and carbon stock estimates. Some of them, as tree height and stem volume, are difficult and expensive to measure; volume models, calibrated on large datasets in tropical and subtropical Forests, are rare.AimsThis study aimed to construct stem volume models for native tree species in three Forest Types in southern Brazil, to select models with best fitness, to assess agreement between measured and predicted datasets and to compare species-specific and generic models.MethodsData from 418 sample plots were used to adjust generic models for Forest Types and specific models for 15 species. Regression assumptions, modelling efficiency, lack of fitness, goodness of fit and comparison between species-specific and generic models were assessed by analytical methods.ResultsLogarithmic models presented the best results of adjustment and evenness of residual variance. Lack of fit F test showed acceptable adjust quality for nearly all species-specific and generic models; R2adj* and modelling efficiency measure presented values close to 1 for all fitted models; model identity F test showed differences between specific and generic models in some cases.ConclusionSince regression assumptions were satisfied and because of their quality of fit, the fitted models compose useful tools for predicting total stem volume (with bark) for Forest remnants in southern Brazil. Stratification of datasets by Forest type for model fitting showed to be necessary, but, commonly, generic models for Forest Types produced estimates not less reliable than species-specific models.

Michael A Jenkins - One of the best experts on this subject based on the ideXlab platform.

  • relationship between cornus florida l and calcium mineralization in two southern appalachian Forest Types
    Forest Ecology and Management, 2007
    Co-Authors: Eric J Holzmueller, Shibu Jose, Michael A Jenkins
    Abstract:

    Abstract Cornus florida L. has long been hypothesized to increase calcium (Ca) mineralization in eastern Forests because of its high foliar Ca concentration, quick foliar decomposition rate, and abundance. This hypothesis, however, has not been proven. We sampled 68 10 m × 10 m plots in two Forest Types, cove hardwood and oak hardwood, to quantify the influence of C. florida density on initial exchangeable Ca and Ca mineralization in the mineral soil and Forest floor. C. florida density was classified into three levels in each Forest type (zero = 0 stems ha −1 , low = 200–300 stems ha −1 , and high ≥600 stems ha −1 ). We found significantly greater levels of initial exchangeable Ca in high density plots than in low density plots in both Forest Types in both the Forest floor and mineral soil ( P C. florida plots (cove hardwood, high density 3.3 g Ca kg −1  year −1 versus zero density 0.6 g Ca kg −1  year −1 , P  = 0.04 and oak hardwood, high density 2.4 g Ca kg −1  year −1 versus zero density 1.1 g Ca kg −1  year −1 , P  = 0.09). These results indicate that the loss of C. florida due to dogwood anthracnose has altered the Ca cycle and may negatively affect the health of eastern hardwood Forests.