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  • 1
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    Half-century evidence from western Canada shows forest dynamics are primarily driven by competition followed by climate (2015)
    National Academy of Sciences
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    Publication Date: 2015-03-16
    Description: Tree mortality, growth, and recruitment are essential components of forest dynamics and resiliency, for which there is great concern as climate change progresses at high latitudes. Tree mortality has been observed to increase over the past decades in many regions, but the causes of this increase are not well understood, and we know even less about long-term changes in growth and recruitment rates. Using a dataset of long-term (1958–2009) observations on 1,680 permanent sample plots from undisturbed natural forests in western Canada, we found that tree demographic rates have changed markedly over the last five decades. We observed a widespread, significant increase in tree mortality, a significant decrease in tree growth, and a similar but weaker trend of decreasing recruitment. However, these changes varied widely across tree size, forest age, ecozones, and species. We found that competition was the primary factor causing the long-term changes in tree mortality, growth, and recruitment. Regional climate had a weaker yet still significant effect on tree mortality, but little effect on tree growth and recruitment. This finding suggests that internal community-level processes—more so than external climatic factors—are driving forest dynamics.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 2
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    Assessing the goodness of fit of forest models estimated by nonlinear mixed-model methods (2009)
    Canadian Science Publishing
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    Publication Date: 2009-12-01
    Description: In this study we examined various measures, including the concordance correlation (CC) coefficient, for determining the goodness of fit of forest models estimated by nonlinear mixed-model (NLMM) methods. Based on the volume–age data for black spruce, we analyzed the use of CC and other traditional goodness-of-fit measures such as coefficient of determination (R2), mean bias, percent bias, root mean square error, and graphic techniques on both the population and subject-specific levels within the NLMM framework. We also examined the relationship between goodness-of-fit measures and the number of observations per subject. We found that the standard overall goodness-of-fit measures commonly reported on combined data from different subjects were generally insufficient in determining the goodness of fitted models. We recommend that CC and other selected goodness-of-fit measures be calculated for individual subjects, and that the frequency distributions of the calculated values be examined and used as the principal criteria for determining the goodness of fit of forest models estimated by NLMM methods and for comparing alternative models and covariance structures. We also emphasized the importance of using pertinent graphic techniques to assess the appropriateness of NLMMs, especially at the subject-specific level, wherein lies the main interest of NLMMs.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 3
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    Climate-sensitive height–age models for top height trees in natural and reclaimed oil sands stands in Alberta, Canada (2019)
    Canadian Science Publishing
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    Publication Date: 2019-11-21
    Description: Climate-sensitive height–age models were developed for top height trees of trembling aspen (Populus tremuloides Michx.), jack pine (Pinus banksiana Lamb.), and white spruce (Picea glauca (Moench) Voss) in natural and reclaimed oil sands stands. We used stem analysis data collected from the Athabasca oil sands region in northern Alberta, Canada, and climate data generated by the ClimateWNA model. Height–age trajectories differed between top height trees in natural and reclaimed stands for jack pine and white spruce, but not for trembling aspen. At a given age, white spruce top height trees were taller and jack pine top height trees were shorter in reclaimed stands than those in natural stands, suggesting that it is easier to achieve similar forest productivity for oil sands sites reclaimed with white spruce stands than for sites reclaimed with jack pine stands. The principal climate variables were growing season (May to September) precipitation averaged over the previous 10 years for trembling aspen and jack pine and summer (June to August) precipitation averaged over the previous 10 years for white spruce. These variables had positive effects on the height–age trajectories.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 4
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    An age-independent individual tree height prediction model for boreal spruce–aspen stands in Alberta (1994)
    Canadian Science Publishing
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    Publication Date: 1994-07-01
    Description: This study presents an individual tree height prediction model for white spruce (Piceaglauca (Moench) Voss) and trembling aspen (Populustremuloides Michx.) grown in boreal mixed-species stands in Alberta. The model is based on a three-parameter Chapman–Richards function fitted to data from 164 permanent sample plots using the parameter prediction method. It is age independent and expresses tree height as a function of tree diameter, tree basal area, stand density, species composition, site productivity, and stand average diameter. This height-prediction model was fitted by weighted nonlinear regression for spruce and unweighted nonlinear regression for aspen. Almost all estimates of parameters were significant at α = 0.05 and model R2-values were high (0.9192 for white spruce and 0.9087 for aspen). No consistent underestimate or overestimate of tree heights was evident in plots of studentized residuals against predicted heights. The model was also tested on an independent data set representing the population on which the model was to be used. Results showed that the average prediction biases were not significant at α = 0.05 for either species, indicating that the model appropriately described the data and performed well when predictions were made.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 5
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    A multilevel individual tree basal area increment model for aspen in boreal mixedwood stands (2009)
    Canadian Science Publishing
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    Publication Date: 2009-11-01
    Description: Based on a multilevel nonlinear mixed model approach, a basal area increment model was developed for individual aspen ( Populus tremuloides Michx.) trees growing in boreal mixedwood stands in Alberta. Various stand and tree characteristics were evaluated for their contributions to model improvement. Total stand basal area, basal area of larger trees, and the ratio of target tree height to maximum stand height were found to be significant predictors. When random effects were modeled at the plot level alone, correlations among normalized residuals remained significant. These correlations were successfully removed when random effects were modeled at both plot and tree levels. The predictive abilities of two alternative models were evaluated at the population, plot, and tree levels. At the tree level, a tree measured at the first growth period was used for estimating random parameters, and basal area increments of that tree in future growth periods were subsequently predicted. At the plot level, one to five trees in each plot at each growth period were used to estimate random parameters. Basal area increments of the remaining trees in the same plot at the same growth period were subsequently predicted. The final model provided accurate predictions at all three levels.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 6
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    Evaluation of population-averaged and subject-specific approaches for modeling the dominant or codominant height of lodgepole pine trees (2009)
    Canadian Science Publishing
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    Publication Date: 2009-06-01
    Description: Population-averaged (PA) and subject-specific (SS) approaches for modeling the height of dominant or codominant lodgepole pine ( Pinus contorta Dougl. ex Loud.) trees were evaluated using six candidate models derived from the Chapman–Richards and logistic functions. The true PA response obtained from separate fits of the models was compared with the typical mean (TM) response computed using only the fixed-effects parameters of the mixed-effects models. Results showed that the TM response had higher prediction errors than the PA response, suggesting that a true PA response and not the TM response is needed to reflect the overall mean response of the model. The SS approach produced improved height predictions relative to the PA approach when evaluated using independent validation data. In addition, the logistic performed better than the Chapman–Richards function, regardless of whether the SS or PA approach was applied. Among the candidate models, the logistic function with the inclusion of site index gave the most accurate predictions. Three scenarios of calibrating the mixed-effects models on the validation data set were compared. The SS predictions obtained using only one premeasured observation per subject were poorer than those using all observations, but they were still generally better than PA predictions.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 7
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    Modeling percent stocking changes for lodgepole pine stands in Alberta (2008)
    Canadian Science Publishing
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    Publication Date: 2008-05-01
    Description: A percent stocking change model was developed for lodgepole pine ( Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) in Alberta based on spatially mapped permanent sample plot data. Percent stocking was defined as the percentage of 10 m2 subplots occupied by at least one tree with a minimum height of 1.3 m. The difference equation technique was employed to fit the model. Three model forms were examined and the logistic function was chosen as the final model. Site index was found to be a significant predictor and incorporated into the model. Analyses revealed that the model had correlated, but homoskedastic errors and the correlated errors were modeled by spherical covariance structure using NLINMIX macro in SAS. A percent stocking index, defined as the percent stocking at 50 years total age, was introduced and derived from the developed model. The percent stocking model had both forward and backward projection capabilities. It was demonstrated, both on model fitting and validation data, that the model adequately portrayed the percent stocking dynamics of lodgepole pine stands in Alberta. The model also provided an important basis for creating linkages between reforestation survey results and future yield, which is crucial for sustainable forest management.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 8
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    An evaluation of diagnostic tests and their roles in validating forest biometric models (2004)
    Canadian Science Publishing
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    Publication Date: 2004-03-01
    Description: Model validation is an important part of model development. It is performed to increase the credibility and gain sufficient confidence about a model. This paper evaluated the usefulness of 10 statistical tests, five parametric and five nonparametric, in validating forest biometric models. The five parametric tests are the paired t test, the Χ2 test, the separate t test, the simultaneous F test, and the novel test. The five nonparametric tests are the Brown-Mood test, the KolmogorovSmirnov test, the modified KolmogorovSmirnov test, the sign test, and the Wilcoxon signed-rank test. Nine benchmark data sets were selected to evaluate the behavior of these tests in model validation; three were collected from Alberta and six were published elsewhere. It was shown that the usefulness of statistical tests in model validation is very limited. None of the tests seems to be generic enough to work well across a wide range of models and data. Each model passed one or more tests, but not all of them. Because of this, caution should be exercised when choosing a statistical test or several tests together to try to validate a model. It is important to reduce and remove any potential personal bias in selecting a favorite test, which can influence the outcome of the results.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 9
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    Comparison of nonlinear height–diameter functions for major Alberta tree species (1992)
    Canadian Science Publishing
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    Publication Date: 1992-09-01
    Description: Twenty nonlinear height–diameter functions were fitted and evaluated for major Alberta species based on a data set consisting of 13 489 felled trees for 16 different species. All functions were fitted using weighted nonlinear least squares regression (wi = 1/DBHi) because of the problem of unequal error variance. The examination and comparison of the weighted mean squared errors, the asymptotic t-statistics for the parameters, and the plots of studentized residuals against the predicted height show that many concave and sigmoidal functions can be used to describe the height–diameter relationships. The sigmoidal functions such as the Weibull-type function, the modified logistic function, the Chapman–Richards function, and the Schnute function generally gave the most satisfactory results.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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  • 10
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    Incorporating correlated error structures into mixed forest growth models: prediction and inference implications (2010)
    Canadian Science Publishing
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    Publication Date: 2010-05-01
    Description: Three nonlinear mixed models with and without incorporating a function to model the serial correlation were compared with regard to their predictive abilities. Results showed that accounting for the serial correlation using the spatial power (SP(POW)) or Toeplitz (TOEP(X)) functions resulted in a large reduction in serial correlation and improved the fit of the models. The improved model fits, however, did not unanimously translate into improved model predictions when evaluated under different scenarios. In many cases, the models with the simple independent and identically distributed structure outperformed the models with the SP(POW) or TOEP(X) structure in terms of the models’ predictive ability. We also examined the effect of adjusting predictions based on the prediction theorem within the nonlinear mixed modeling framework. It was shown that, in general, the adjusted predictions had lower errors than those without adjustment, but the differences were small in many cases. The adjustment with three prior measurements was better in predictions than the adjustment with only one or two prior measurements for the models with the TOEP(X) structure, but not for SP(POW). A theoretical derivation was developed to prove the insensitivity of the models with the SP(POW) structure to the number of prior measurements. The implications of accounting for serial correlation on model inference and model predictions were discussed.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Canadian Science Publishing
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