The relationship between stem-form, stand-closure and site -conditions : the influence of environmental conditions on tree allometry and forest structure in west-central Alberta

Changes in the configuration of a tree stern result insignificant differences in its total volume and in the proportion of that volume that is merchantable timber. Tree allometry, as represented by stem-fo~, is the result of the vertical force of gravity and the horizontal force of wind. The effect of wind force is demonstrated in the relationship between stem-form, standclosure and site-conditions. An increase in wind force on the individual tree due to a decrease in stand density should produce a more tapered tree. The density of the stand is determined by the conditions that the trees are growing under. The ability of the tree to respond to increased wind force may also be a function of these conditions . This stem-form/stand-closure/site-conditions relationship was examined using a pre-existing database from westcentral Alberta. This database consisted of environmental, vegetation, soils and timber data covering a wide range of sites. There were 653 sample trees with 82 variables that formed the basis of the analysis. There were eight tree species consisting of Pinus contorta, Picea mariana, Picea engelmannii x glauca, Abies lasiocarpa, Larix laricina, Populus tremuloides, Betula papyrifera and Populus balsamifera plus a comprehensive all-species data set. As the actual conformation of the stern is very individual, stem-fo~was represented by the diameter at breast height to total height r~tio. The four stand-closure variables, crown closure, total basal area, total volume and total number of stems were reduced to total basal area and total number of stems utilizing a bivariate correlation matrix by species. Site-conditions were subdivided into macro, meso and micro variables and reduced in number 3 using cross-tabulations, bivariate correlation and principal components analysis as screening tools. The stem-fo~/stand-closure relationship was examined using bivariate correlation coefficients for stem-fo~ with total number of stems and stem-fo~ with total basal area. The stem-fo~/site-conditions and the stand-closure/site- conditions relationships were examined using multiple correlation coefficients. The stem-form/stand-closure/site-conditions relationship was examined using multiple correlation coefficients in separate analyses for both total number of stems and total basal area. An increase in stand-closure produced a decrease in stem-form for both total number of stems and total basal area for most species. There was a significant relationship between stem-form and site-conditions and between stand-closure and site-conditions for both total number of stems and total basal area for most species. There was a significant relationship between the stemform and site-conditions, including the stand-closure, for most species; total number of stems was involved independently of the site-conditions in the prediction of stem-form and total basal area was not. Larix laricina and Betula papyrifera were the exceptions to the trends observed with most species. The influence of both stand-closure (total number of stems in particular) and site-conditions (elevation in particular) suggest that forest management practices should include these- ecological parameters in determining appropriate restocking levels.

Allometric equations for estimating tree biomass in restored mixed-species Atlantic Forest stands

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

K-tree : large scale document clustering

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

How is a fruit tree like you? Using artistic metaphors to explore and develop emotional competence in children

Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

Document clustering with K-tree

This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Random Indexing K-tree

Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

Thai word segmentation with hidden Markov Model and decision tree

The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

Tree of knowledge memorial

This article discusses the design of a memorial space of the Tree of Knowledge, located in Oak Street, Barcaldine, Queensland designed by Brian Hooper Architect and M3 Architecture. Features of the design include the dead tree trunk underneath pieces of timber hanging down to show the original size of the tree in the 1890s and the root ball visible under a glass floor.

Clustering with random indexing K-tree and XML structure

This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.