It is widely known that the world is losing biodiversity and primarily it is thought to be caused by anthropogenic activities. Many of these activities have been identified. However, we still lack a clear understanding of the causal relationships between human activities and the pressures they place on the environment and biodiversity. We need to know how ecosystems and individual species respond to changes in human activities and therefore how best to moderate our actions and reduce the rate of loss of biodiversity. One of the ways to detect these changes is to use indicators of ecosystem conditions. Indicators are statistics following changes in a particular factor usually over time. These indicators are used to summarise a complex set of data, and are seen as being representative of the wider situation in that field. So it can be assumed that if that particular factor is declining or improving, then the situation in general is also declining or improving. They are used to check the status and trends of biodiversity by both the public and policy makers. Indicators are also used to assess national performance and can be used to identify the actions required at the policy level. In this manner, they provide an important link between policy-makers and scientists collecting the data. The current thesis investigates the possibility of using bird species as indicators of biodiversity for better management of natural terrestrial ecosystems, by identifying their habitats according to various environmental factors. The study is established by drawing upon three main scientific areas: ecology, geographical information system (GIS), and statistical modelling. The Mornington Peninsula and Western Port Biosphere Reserve (MPWPBR) (Victoria, Australia) was chosen for the study area because of the combination of suburban and natural environments that made it optimum for this type of study. Once the study area was defined, the necessary data for the research were obtained from various sources. Birds Australia provided data on recorded observation of 271 bird species within the study area. Based on the nature of this study, seven species were selected for the study. The criteria for this selection are discussed in Chapter 3. Most literature state that the primary determinant for bird abundance is vegetation and land cover. Because of this, Ecological Vegetation Class (EVC) layer was used to determine which type(s) of vegetation have the greatest impact on habitat selection. Each species showed a relationship to a number of v vegetation types. These EVCs were combined to produce vegetation patches, and were considered as potentially suitable habitats of corresponding bird species. For each of the species, these habitat patches were analysed for the different aspects of patch characteristics (such as the level of patchiness, connectivity, size, shape, weighted distance between patches, etc.) by using the Landscape Context Tool (a GIS add-on). This process assisted the understanding of the importance of patch quality in habitat selection among different bird species by analysing the location of bird observation sites relative to habitat patches. In this way, the association between bird presence and the conditions of a habitat patch was identified by performing a discriminant function analysis. To investigate the probability of a species presence according to different environmental factors, a model of species distribution was created. Binary logistic regression was used to indicate the level of effect of each variable. The model was then successfully validated in the field. To define the indicators of environmental factors, it was essential to separate bird species based on their dependency on one or more of the studied variables. For this purpose, One-Way ANOVA was used. This analysis showed that some bird species can be considered as indicators of urban areas, while others could be good indicators of wellpreserved large forests. Finally, it must be mentioned that the type and quality of the datasets are crucial to this type of study, because some species have a higher degree of sensitivity to certain types of vegetation or land cover. Therefore, the vegetation data must be produced as detailed as possible. At the same time, the species data needs to be collected based on the presence and absence (versus presence-only) of the birds.
| Identifer | oai:union.ndltd.org:ADTP/210054 |
| Date | January 2006 |
| Creators | Alizadeh Shabani, Afshin, afshin.alizadeh@rmit.edu.au |
| Publisher | RMIT University. Mathematical and Geospatial Sciences |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://www.rmit.edu.au/help/disclaimer, Copyright Afshin Alizadeh Shabani |
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