Parent – environmental interactions shape acoustic signatures in tree swallows: a cross-fostering experiment.

Acoustic signatures are common components of avian vocalizations and are important for the recognition of individuals and groups. The proximate mechanisms by which these signatures develop are poorly understood, however. The development of acoustic signatures in nestling birds is of particular interest, because high rates of extra-pair paternity or egg dumping can cause nestlings to be unrelated to at least one of the adults that are caring for them. In such cases, nestlings might conceal their genetic origins, by developing acoustic signatures through environmental rather than genetic mechanisms. In a cross-fostering experiment with tree swallows Tachycineta bicolor, we investigated whether brood signatures of nestlings that were about to fledge were attributable to their genetic/maternal origins or to their rearing environment. We found that the calls of cross-fostered nestlings did not vary based on their genetic/maternal origin, but did show some variation based on their rearing environment. Control nestlings that were not swapped, however, showed stronger brood signatures than either experimental group, suggesting that acoustic signatures develop through an interaction between rearing environment and genetic/maternal effects.

Longitudinal Study of Tree Swallows

Tree swallows (Tachycineta bicolor) are the most widely distributed of the Tachycineta species, extending from northern Alaska and Canada to the southern United States. They are semi-colonial, secondary cavity nesters, primarily aerial insectivores, and migratory throughout most of their range. Tree swallows are a widely used model organism for avian ecologists and environmental physiologists because their life history lends itself to longterm study. They can be readily and repeatedly trapped at nests, and losses to nest predators are low. Adults return to previous breeding sites with high fidelity, so individuals marked during or after their first reproductive season can be reliably captured in subsequent years, and return rate to the breeding area can be used as an index of survival. Swallows using nest boxes are extraordinarily resistant to the disturbance of handling, allowing repeated captures to obtain measurements, blood samples, etc., both within and between breeding seasons.

How does nest box temperature affect nestling growth rate and breeding success in a parrot?

Climate change is predicted to affect many species by reducing range, habitat suitability and breeding success. Cavity-nesting species, already threatened by deforestation and declining natural hollows, may be particularly at risk because they are limited in nest-site location, and climatic alterations may further reduce usability of natural cavities. It is therefore essential to determine how cavity-users may be affected. We recorded internal nest box temperatures and modelled the relationships of four temperature parameters (relating to mean temperature, variability in temperature, low temperature extremes and high temperature extremes) with breeding success and nestling growth in an Australian cavity-nesting parrot, the Crimson Rosella (Platycercus elegans). We found that less extreme low temperatures resulted in heavier nestlings; however, higher mean temperatures tended to result in lighter nestlings. Greater temperature variability tended to reduce fledging success; however, no temperature variables had a clear effect on clutch size or hatching success. Our findings indicate that there may be a complex relationship between nestling growth and temperature, and although less extreme cold temperatures may benefit nestlings, continued increases in mean temperature and variability may have negative consequences.

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.