Allometry and size structure of trees in two ancient snow forests in coastal British Columbia

2008 ◽  
Vol 38 (2) ◽  
pp. 278-288 ◽  
Author(s):  
Roberta Parish ◽  
Gordon D. Nigh ◽  
Joseph A. Antos
Keyword(s):  
Size Structure ◽  
Model Development ◽  
Tree Height ◽  
Tsuga Heterophylla ◽  
Diameter Ratio ◽  
Data Set ◽  
Crown Length ◽  
Shade Tolerant Species ◽  
Height Change ◽  
Ancient Forests

Shade-tolerant trees that start in the understory but ultimately reach the canopy persist through different microhabitat conditions during their ontogeny. We evaluate how the height to diameter ratio and the crown ratio (crown length/tree height) change during development and differ among four coniferous species ( Abies amabilis (Dougl. ex Loud.) Dougl. ex J. Forbes, Chamaecyparis nootkatensis (D. Don) Spach, Tsuga mertensiana (Bong.) Carrière, and Tsuga heterophylla (Ref.) Sarg.) in ancient forests. At two sites, we measured diameter, height, and height to the base of live crown for trees ≥4.0 cm diameter at breast height in four 0.25 ha plots. For each species, we constructed models of height based on diameter and crown length using part of the data for model development and part as the test data set. Models predicting tree height were effective for all species, and adding crown length considerably improved the prediction over diameter alone. The height to diameter ratio increased until the subcanopy and then decreased for two shade-tolerant species (A. amabilis and T. heterophylla) but decreased linearly throughout ontogeny for C. nootkatensis. Crown ratio increased as trees became larger except for C. nootkatensis, where the reverse occurred. Differences in allometric relationship among species reflect patterns of crown development and also suggest different approaches to a common structural constraint in these forests: heavy snow loads.

Reconstruction of Tertiary Metasequoia forests. I. Test of a method for biomass determination based on stem dimensions

Paleobiology ◽  
2003 ◽  
Vol 29 (2) ◽  
pp. 256-270 ◽  
Author(s):  
Christopher J. Williams ◽  
Arthur H. Johnson ◽  
Ben A. LePage ◽  
David R. Vann ◽  
Karen D. Taylor
Keyword(s):  
Forest Ecology ◽  
Tree Height ◽  
Data Set ◽  
Chamaecyparis Thyoides ◽  
Biomass Structure ◽  
History Of ◽  
Biomass Determination ◽  
Canopy Depth ◽  
Ancient Forests

Accurate reconstruction of the biomass, structure, and productivity of ancient forests from their fossilized remnants remains an interesting challenge in paleoecology. In well-preserved Tertiary fossil Metasequoia forests of Canada's Arctic, in situ stumps and fragments of stems, treetops, and branches contain substantial information about tree dimensions that can be used to determine tree height, stand biomass, and other characteristics such as canopy depth and structure, and the history of stand development. To validate a method for reconstructing the biomass of the Eocene floodplain Metasequoia forests of Axel Heiberg Island, we measured stump diameters and spacing, and stem, branch, and treetop characteristics in living Metasequoia glyptostroboides and Chamaecyparis thyoides stands in ways that simulate the limited measurements that can be made in well-preserved fossil forests in Canada and probably elsewhere. We used those limited measurements to estimate tree height and volume, branch and foliar dry weights, and tree biomass. The estimates derived from the limited data set are usually within 15% of the estimates derived from the methods currently used in forest ecology for determining those metrics in modern forests. Under appropriate conditions, the biomass of ancient forests can be estimated with reasonable confidence.

scholarly journals Height growth and vertical development of an old-growth Pseudotsuga-Tsuga forest in southwestern Washington State, U.S.A.

2000 ◽  
Vol 30 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Hiroaki Ishii ◽  
Joel H Reynolds ◽  
E David Ford ◽  
David C Shaw
Keyword(s):  
Future Development ◽  
Growth Rates ◽  
Forest Canopy ◽  
Size Structure ◽  
Tree Height ◽  
Tsuga Heterophylla ◽  
Height Growth ◽  
Washington State ◽  
Thuja Plicata ◽  
Old Growth

A detailed analysis of diameter-height relationships was applied to an old-growth Pseudotsuga menziesii (Mirb.) Franco var. menziesii - Tsuga heterophylla (Raf.) Sarg. forest in southwestern Washington State, U.S.A., to predict future development of vertical stratification among tree species. Differences among species in relative abundance and size structure resulted in diameter-height regressions of varying certainty and stability. Damage and shading had negative impacts on predicted heights and estimates of maximum attainable height (Hmax) in all species. However, species varied as to the main causes and size dependency of damage in relation to tree height. Current height-growth rates of the upper canopy species declined with increasing tree height, reaching minimum values near the predicted Hmax. The future development of the forest canopy would involve a slow invasion of the upper canopy by Tsuga heterophylla and Thuja plicata Donn ex D. Don, as P. menziesii are near their maximum attainable height, and Abies amabilis Dougl. ex Forbes and Taxus brevifolia Nutt. are restricted to the middle to lower canopy. However, if current height-growth rates continue, P. menziesii should maintain its dominant status in the upper canopy for at least another century.

scholarly journals A Comprehensive Set of Impact Data for Common Aerospace Metals

2017 ◽  
Vol 12 (6) ◽  
Author(s):  
M. R. W. Brake ◽  
P. L. Reu ◽  
D. S. Aragon
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Model Development ◽  
Coefficient Of Restitution ◽  
Image Correlation ◽  
Plastic Behavior ◽  
Data Set ◽  
Force Resolution ◽  
Impact Data ◽  
The Impact

The results of two sets of impact experiments are reported within. To assist with model development using the impact data reported, the materials are mechanically characterized using a series of standard experiments. The first set of impact data comes from a series of coefficient of restitution (COR) experiments, in which a 2 m long pendulum is used to study “in-context” measurements of the coefficient of restitution for eight different materials (6061-T6 aluminum, phosphor bronze alloy 510, Hiperco, nitronic 60A, stainless steel 304, titanium, copper, and annealed copper). The coefficient of restitution is measured via two different techniques: digital image correlation (DIC) and laser Doppler vibrometry (LDV). Due to the strong agreement of the two different methods, only results from the digital image correlation are reported. The coefficient of restitution experiments are in context as the scales of the geometry and impact velocities are representative of common features in the motivating application for this research. Finally, a series of compliance measurements are detailed for the same set of materials. The compliance measurements are conducted using both nano-indentation and micro-indentation machines, providing sub-nm displacement resolution and μN force resolution. Good agreement is seen for load levels spanned by both machines. As the transition from elastic to plastic behavior occurs at contact displacements on the order of 30 nm, this data set provides a unique insight into the transitionary region.

scholarly journals Using Model Performance to Assess the Representativeness of Data for Model Development and Calibration in Financial Institutions

Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 204
Author(s):  
Chamay Kruger ◽  
Willem Daniel Schutte ◽  
Tanja Verster
Keyword(s):  
Case Studies ◽  
Model Development ◽  
Model Performance ◽  
Data Set ◽  
Pooled Data ◽  
External Data ◽  
First Case ◽  
Multivariate Prediction ◽  
Credit Data

This paper proposes a methodology that utilises model performance as a metric to assess the representativeness of external or pooled data when it is used by banks in regulatory model development and calibration. There is currently no formal methodology to assess representativeness. The paper provides a review of existing regulatory literature on the requirements of assessing representativeness and emphasises that both qualitative and quantitative aspects need to be considered. We present a novel methodology and apply it to two case studies. We compared our methodology with the Multivariate Prediction Accuracy Index. The first case study investigates whether a pooled data source from Global Credit Data (GCD) is representative when considering the enrichment of internal data with pooled data in the development of a regulatory loss given default (LGD) model. The second case study differs from the first by illustrating which other countries in the pooled data set could be representative when enriching internal data during the development of a LGD model. Using these case studies as examples, our proposed methodology provides users with a generalised framework to identify subsets of the external data that are representative of their Country’s or bank’s data, making the results general and universally applicable.

scholarly journals Keep it simple - A case study of model development in the context of the Dynamic Stocks and Flows (DSF) task

2010 ◽  
Vol 2 (2) ◽  
pp. 38-51 ◽  
Author(s):  
Marc Halbrügge
Keyword(s):  
Goodness Of Fit ◽  
Model Development ◽  
Cognitive Model ◽  
Training Data ◽  
Sequence Matching ◽  
Data Set ◽  
Depth Analysis ◽  
Stocks And Flows ◽  
Matching Techniques

Keep it simple - A case study of model development in the context of the Dynamic Stocks and Flows (DSF) taskThis paper describes the creation of a cognitive model submitted to the ‘Dynamic Stocks and Flows’ (DSF) modeling challenge. This challenge aims at comparing computational cognitive models for human behavior during an open ended control task. Participants in the modeling competition were provided with a simulation environment and training data for benchmarking their models while the actual specification of the competition task was withheld. To meet this challenge, the cognitive model described here was designed and optimized for generalizability. Only two simple assumptions about human problem solving were used to explain the empirical findings of the training data. In-depth analysis of the data set prior to the development of the model led to the dismissal of correlations or other parametric statistics as goodness-of-fit indicators. A new statistical measurement based on rank orders and sequence matching techniques is being proposed instead. This measurement, when being applied to the human sample, also identifies clusters of subjects that use different strategies for the task. The acceptability of the fits achieved by the model is verified using permutation tests.

scholarly journals Crown structure of Picea omorika trees in the plantation

2012 ◽  
Vol 64 (2) ◽  
pp. 605-611 ◽  
Author(s):  
M. Krstic ◽  
N. Stavretovic ◽  
V. Isajev ◽  
I. Bjelanovic
Keyword(s):  
Tree Height ◽  
Tree Crown ◽  
Crown Length ◽  
Crown Structure ◽  
Parabolic Function ◽  
Picea Omorika ◽  
Serbian Spruce ◽  
The Relationship ◽  
Total Tree ◽  
Stand Conditions

The study was carried out in Serbian spruce (Picea omorika Panc/Purkyn?) plantations in the western Serbia. The paper presents results of the analysis of crown development. The following elements were analyzed: total tree height, height of the crown base, absolute and relative crown length, maximal crown diameter, coefficient of crown spreading and degree of crown girth. We discuss approaches to the modeling of tree crown growth and development, growing under favorable environmental and stand conditions, without anomalies in development. In order to establish the relationship between analyzed factors, regression analyses were applied. Data fitting was by the analytic method, by the implementation of Prodan?s functions of growth, linear and parabolic function. Received models can be used for the simulation of various growth and developing processes in forest.

scholarly journals Classification of Clinically Significant Prostate Cancer on Multi-Parametric MRI: A Validation Study Comparing Deep Learning and Radiomics

Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 12
Author(s):  
Jose M. Castillo T. ◽  
Muhammad Arif ◽  
Martijn P. A. Starmans ◽  
Wiro J. Niessen ◽  
Chris H. Bangma ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Deep Learning ◽  
Characteristic Curve ◽  
Model Development ◽  
Learning Model ◽  
Multiparametric Mri ◽  
Data Sets ◽  
Data Set ◽  
Test Sets ◽  
Deep Learning Model

The computer-aided analysis of prostate multiparametric MRI (mpMRI) could improve significant-prostate-cancer (PCa) detection. Various deep-learning- and radiomics-based methods for significant-PCa segmentation or classification have been reported in the literature. To be able to assess the generalizability of the performance of these methods, using various external data sets is crucial. While both deep-learning and radiomics approaches have been compared based on the same data set of one center, the comparison of the performances of both approaches on various data sets from different centers and different scanners is lacking. The goal of this study was to compare the performance of a deep-learning model with the performance of a radiomics model for the significant-PCa diagnosis of the cohorts of various patients. We included the data from two consecutive patient cohorts from our own center (n = 371 patients), and two external sets of which one was a publicly available patient cohort (n = 195 patients) and the other contained data from patients from two hospitals (n = 79 patients). Using multiparametric MRI (mpMRI), the radiologist tumor delineations and pathology reports were collected for all patients. During training, one of our patient cohorts (n = 271 patients) was used for both the deep-learning- and radiomics-model development, and the three remaining cohorts (n = 374 patients) were kept as unseen test sets. The performances of the models were assessed in terms of their area under the receiver-operating-characteristic curve (AUC). Whereas the internal cross-validation showed a higher AUC for the deep-learning approach, the radiomics model obtained AUCs of 0.88, 0.91 and 0.65 on the independent test sets compared to AUCs of 0.70, 0.73 and 0.44 for the deep-learning model. Our radiomics model that was based on delineated regions resulted in a more accurate tool for significant-PCa classification in the three unseen test sets when compared to a fully automated deep-learning model.

scholarly journals Tree crown size as a measure of tree biosocial position in 135-year-old oak (Quercus L.) stand

2016 ◽  
Vol 58 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Katarzyna Kaźmierczak ◽  
Bogna Zawieja
Keyword(s):  
Principal Component ◽  
Tree Height ◽  
Projection Area ◽  
Tree Crown ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Crown Length ◽  
Pca Method ◽  
Crown Projection Area

AbstractThe paper presents an attempt to apply measurable traits of a tree – crown projection area, crown length, diameter at breast height and tree height for classification of 135-year-old oak (QuercusL.) trees into Kraft classes. Statistical multivariate analysis was applied to reach the aim. Empirical material was collected on sample plot area of 0.75 ha, located in 135-year-old oak stand. Analysis of dimensional traits of oaks from 135-year-old stand allows quite certain classification of trees into three groups: pre-dominant, dominant and co-dominant and dominated ones. This seems to be quite promising, providing a tool for the approximation of the biosocial position of tree with no need for assessment in forest. Applied analyses do not allow distinguishing trees belonging to II and III Kraft classes. Unless the eye-estimation-based classification is completed, principal component analysis (PCA) method provided simple, provisional solution for grouping trees from 135-year-old stand into three over-mentioned groups. Discriminant analysis gives more precise results compared with PCA. In the analysed stand, the most important traits for the evaluation of biosocial position were diameter at breast height, crown projection area and height.

Modeling individual tree height to diameter ratio for Norway spruce and European beech in Czech Republic

Trees ◽  
2016 ◽  
Vol 30 (6) ◽  
pp. 1969-1982 ◽  
Author(s):  
Ram P. Sharma ◽  
Zdeněk Vacek ◽  
Stanislav Vacek
Keyword(s):  
Czech Republic ◽  
Norway Spruce ◽  
Tree Height ◽  
European Beech ◽  
Diameter Ratio ◽  
Individual Tree

Robustness of Parametric and Nonparametric Fitting Procedures of Tree-Stem Taper with Alternative Definitions for Validation Data

2020 ◽  
Vol 118 (6) ◽  
pp. 576-583
Author(s):  
Sheng-I Yang ◽  
Harold E Burkhart
Keyword(s):  
Loblolly Pine ◽  
Model Development ◽  
Data Partitioning ◽  
Parametric Models ◽  
Validation Data ◽  
Data Set ◽  
Stem Taper ◽  
Computationally Intensive ◽  
Tree Stem ◽  
Selection Of

Abstract This study aims to evaluate the robustness of parametric and nonparametric procedures using alternative definitions of validation data for loblolly pine. Specifically, four data division strategies were implemented: random selection of one-third of the trees in the data set, selection of the smallest one-third of the trees by diameter at breast height (DBH), selection of the middle third of the trees by DBH, and selection of the largest third of the trees by DBH. Results indicate that tree taper was predicted reasonably well by both procedures when the smallest, medium-sized, or randomly selected trees were withheld for validation. However, when the largest trees were withheld for validation, diameters predicted by the nonparametric random forest algorithm were considerably less accurate than those predicted by the parametric models, especially for diameters near the tree top. When extrapolation is anticipated, a carefully designed data-partitioning strategy should provide some protection against poor results for given prediction objectives. Study Implications Parametric tree-stem taper models have been widely applied in forestry. Recently, nonparametric methods with computationally intensive algorithms were proposed for estimating tree taper, but reliability of the methods has not been explicitly examined. In practice, models are commonly applied to predict unknown populations, which may vary from the observations used in model development. This study provides insights for natural resource and forest managers to select appropriate validation procedures when developing models for predicting tree-stem taper and examining robustness of parametric and nonparametric fitting of tree-stem taper under varying levels of interpolation/extrapolation from fitting to validation of data.

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