Stand Density Control Diagrams for Scots pine and Austrian black pine plantations in Bulgaria

Stankova, T.; Shibuya, Masato

doi:10.1007/s11056-007-9043-x

Cited by 24 publications

(24 citation statements)

References 19 publications

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“…However, the advent of the structural SDMD which incorporates a diameter distribution sub-model has been useful in solving a broad array of forest management problems (e.g., designing thinning prescriptions, evaluating wildlife habitat potential, estimating carbon storage potential, assessing the attainment of biologic diversity objectives (Newton et al , 2005Newton 2009)). The present investigation on the diameter structure of Austrian black pine plantations in Bulgaria was preceded by elaboration of a dynamic SDMD (Stankova and Shibuya 2007), which was further verified and proven to be better than the whole stand yield tables (Stankova and Zlatanov 2007). Thus, the incorporation of the diameter distribution model into the framework of the SDMD would significantly improve its modeling applicability by not only characterizing the present, but also by predicting the future horizontal structure.…”

Section: Discussionmentioning

confidence: 63%

Modeling diameter distribution of Austrian black pine (Pinus nigra Arn.) plantations: a comparison of the Weibull frequency distribution function and percentile-based projection methods

Stankova

Zlatanov

2010

Eur J Forest Res

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The main purpose of the present investigation is to examine and compare three methods for diameter distribution modeling in terms of their fitness to predict from stand level variables the diameter distributions of even-aged Austrian black pine (Pinus nigra Arn.) plantations in Bulgaria. The percentile-based projection method involving empirical probability density function based on 12 percentiles was the first method tested. A new modified approach based on the first method was proposed as the second alternative. The third method was the 2-parameter Weibull functional model in which parameters were recovered from the first and the second raw moments and the second central moment of the empirical distributions. The KolmogorovSmirnov test was applied to compare the experimental distributions with the predicted ones, and estimation of the error indices was employed to evaluate the total absolute deviation of the predicted numbers from the actual ones by diameter class. The two-parameter Weibull function proved superior to the examined alternative percentile-based projection methods and the newly proposed percentile method, without a driver percentile showed improved precision compared to the classical percentile method (with a driver percentile). The parameters of the Weibull frequency distribution function can be easily recovered from the stand quadratic mean diameter. Consequently, this diameter distribution model could be incorporated as a sub-model for stand horizontal structure characterization within the Stand Density Management Diagram modeling framework.

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Section: Discussionmentioning

confidence: 63%

Modeling diameter distribution of Austrian black pine (Pinus nigra Arn.) plantations: a comparison of the Weibull frequency distribution function and percentile-based projection methods

Stankova

Zlatanov

2010

Eur J Forest Res

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“…These data were available from the current and the archived forest management plans of the local forest management units. The plot dominant height was estimated from the experimental mean plot height by the relationship established by Stankova et al (2006). Data obtained before and after the thinning of the treated plots were considered as distinct time series thus yielding 98 data series from 79 plots.…”

Section: Data Set and Data Assessmentmentioning

confidence: 99%

A dynamic whole-stand growth model, derived from allometric relationships

Stankova¹

2016

Silva Fenn.

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A dynamic whole-stand growth model, derived from allometric relationships Stankova T.V. (2016). A dynamic whole-stand growth model, derived from allometric relationships. Silva Fennica vol. 50 no. 1 article id 1406. 21 p. Highlights• A dynamic whole-stand model was derived from simple allometries and biological rationale.• The state-space modelling approach was applied, suggesting several novelties to overcome scarcity of longitudinal data.• The model consists of a three-dimensional state vector, defined by dominant stand height, stand density and mean stem volume, and three transition functions.• It was tested with data from Scots pine plantations. AbstractGrowth and yield tables are constrained by a standard production regime and the stand-level dynamic models are an attractive alternative for the even-aged monospecific stands. The objective of this study is to derive a parsimonious and biologically sound whole-stand dynamic growth model and to validate its consistency and relevance for prediction of stand growth and yield. The state-space modelling approach was employed, introducing several novelties in comparison with its current usage. The model consists of a three-dimensional state vector, defined by dominant stand height, number of trees per hectare and mean stem volume, and three transition functions. A site index model was incorporated for height growth projection and transition functions for stand density and mean stem volume with respect to dominant height increase were derived from simple allometries and biological rationale. The model was examined with data from 79 permanent sample plots in Scots pine plantations. Nonlinear Seemingly Unrelated Regression was used to account for cross-equation correlations, and the Base-Height-Invariant dummy variable method was employed to estimate dynamic-form equations. Model consistency was validated in terms of accuracy of predictions and applicability to both thinned and unthinned stands. The new dynamic growth model is a parsimonious biometric whole-stand model that simulates the expected stand development for a broad spectrum of potential management alternatives and can be incorporated in a computer program for further use. It may be especially useful for application when a scarcity of longitudinal data prevents the use of more complicated modelling approaches.

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“…The data records for Scots pine plantations were obtained from permanent sample plots (of size 150-2000 m 2 , measured 2-4 times since the 1970s) used to develop growth and yield tables for Scots pine plantations (Krastanov et al 1980), experimental plots in Scots pine plantations against erosion (Marinov 2008) and permanent sample plots established for inventory purposes. We estimated the plot dominant height of this data set from the experimental mean plot height, using a previously established linear relationship (Stankova et al 2006).…”

Section: Data Setsmentioning

confidence: 99%

Derivation and analysis of new stand‐level mortality models based on existing growth equations

Stankova

Diéguez-Aranda

2014

Ecological Research

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Considering that, the temporal trend in stocking, expressed as number of trees per unit area, is the opposite of that of growth, and that both trajectories are sigmoidal, we derived a temporal trajectory of density decrease by reversing the temporal trend of a generalized growth function. We derived and analysed twelve stand‐level mortality models by using four data sets from monospecific even‐aged stands. Stand dominant height rather than stand age was incorporated as an indicator of the growth stage and a careful examination of the models conformity with the essential logical properties of the stand‐level survival models was conducted. We first tested the models adequacy and general predictive performance by fitting them to parameterization data sets and subsequently assessing them with validation data. The regression equations were re‐fitted afterwards over the total data sets to make use of all available information in the final parameter estimates. Nine model formulations were successfully fitted and four of them were the most adequate in describing stand density decrease with dominant height growth. The site‐specific effect was incorporated in the newly derived models through the predictor variable and the stand‐specific starting density was accounted for through a specific model parameter. These new dominant height‐dependent mortality equations can be considered for inclusion in the framework of stand‐level growth models as transition functions.

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Stand Density Control Diagrams for Scots pine and Austrian black pine plantations in Bulgaria

Cited by 24 publications

References 19 publications

Modeling diameter distribution of Austrian black pine (Pinus nigra Arn.) plantations: a comparison of the Weibull frequency distribution function and percentile-based projection methods

Modeling diameter distribution of Austrian black pine (Pinus nigra Arn.) plantations: a comparison of the Weibull frequency distribution function and percentile-based projection methods

A dynamic whole-stand growth model, derived from allometric relationships

Derivation and analysis of new stand‐level mortality models based on existing growth equations

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