The investigation of edge effects within ragmented forest islands in Short Hills Provincial Park

It has been well documented, within the field of landscape ecology, that terrestrial fragmentation contributes to increased heterogeneity at the landscape level. It has also been observed that elevated areas of edge habitat occur within fragmented landscapes. Spatial and temporal edge effects were investigated in four areas designated as Nature Reserve Zones within Short Hills Provincial Park, near St. Catharines, Ontario. Random sampling along exposed edges was performed on trees and saplings, at 5 and 25 ill edge depths, using the point-centred quarter method. Diameter at breast height (dbh) and distance from point measurements were used to establish relative density, dominance, frequency and importance value. One-way analyses of variance were used on dbh measurements of tree species and Chi-Square contingency tables were used on size class distributions of saplings species to determine significant differences between 5 and 25 metres. Qualitative comparisons of importance values were also used to determine differences between 5 and 25 metres as well as between trees and saplings. These statistical and qualitative comparisons suggest that a significant overall spatial edge effect is currently exhibited by fragmented wooded islands within the park. The major species of the park, Acersaccharuln, may be exhibiting a temporal edge effect. The heterogeneous nature of the park may be of importance in understanding this area as a complex, ecological system. It is possible that the remaining forest tracts of the park have been affected, and continue to be affected by previous disturbances. Based on these findings, recommendations are made to the Ontario Ministry of Natural Resources concerning the management of Short Hills Provincial Park in accordance with their 1990 proposed Management Plan.

Assessing the Reproducibility of Clustering of Molecular Dynamics Conformations on Self-Organizing Maps

The goal of most clustering algorithms is to find the optimal number of clusters (i.e. fewest number of clusters). However, analysis of molecular conformations of biological macromolecules obtained from computer simulations may benefit from a larger array of clusters. The Self-Organizing Map (SOM) clustering method has the advantage of generating large numbers of clusters, but often gives ambiguous results. In this work, SOMs have been shown to be reproducible when the same conformational dataset is independently clustered multiple times (~100), with the help of the Cramérs V-index (C_v). The ability of C_v to determine which SOMs are reproduced is generalizable across different SOM source codes. The conformational ensembles produced from MD (molecular dynamics) and REMD (replica exchange molecular dynamics) simulations of the penta peptide Met-enkephalin (MET) and the 34 amino acid protein human Parathyroid Hormone (hPTH) were used to evaluate SOM reproducibility. The training length for the SOM has a huge impact on the reproducibility. Analysis of MET conformational data definitively determined that toroidal SOMs cluster data better than bordered maps due to the fact that toroidal maps do not have an edge effect. For the source code from MATLAB, it was determined that the learning rate function should be LINEAR with an initial learning rate factor of 0.05 and the SOM should be trained by a sequential algorithm. The trained SOMs can be used as a supervised classification for another dataset. The toroidal 10×10 hexagonal SOMs produced from the MATLAB program for hPTH conformational data produced three sets of reproducible clusters (27%, 15%, and 13% of 100 independent runs) which find similar partitionings to those of smaller 6×6 SOMs. The χ^2 values produced as part of the C_v calculation were used to locate clusters with identical conformational memberships on independently trained SOMs, even those with different dimensions. The χ^2 values could relate the different SOM partitionings to each other.