The research contained in this thesis was completed by the candidate while in the Discipline of Environmental Science, School of Agricultural, Earth and Environmental Sciences of the College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa, is based. The content of this work has not been submitted in any form to another university and, except where the work of others is acknowledged in the text, the results reported are due to investigations by the candidate.
PLAGIARISM
PUBLICATIONS
46 Figure 4.3 - The distribution of DMOSS in the eThekwini Metro, used to perform the corridor analysis. 47 Figure 4.4 - The distribution of land uses within the eThekwini Metro, used to conduct the corridor analysis.
INTRODUCTION
- Rationale for the research
- Aim
- Objectives
- Study site
- Outline of thesis structure
The KZN SS is found both inside and outside the eThekwini Metropolitan area (Figure 1.1). The existing patches of KZN SS cover approximately two percent of the eThekwini Metropolitan area.
LITERATURE REVIEW
Habitat fragmentation
- Landscape connectivity
- Measures of landscape connectivity
- Analytical tools to quantify habitat fragmentation and connectivity
A useful feature of Fragstats is that it does not limit the scale of the landscape under investigation. As a result, not only does this software allow the spatial structure of the landscape (structural connectivity) to be included in the analysis, but it takes care of the dispersal distances of species and their interaction with the physical structure of the landscape (functional connectivity) as well (Tischendorf and Fahrig, 2000, Theobald, 2006; Saura and Torne, 2009).
Corridor design
- Types of corridors
- The different roles of corridors
- The structure of corridors
- Do the benefits of corridors outweigh their limitations?
- Tools for corridor design
Environmental corridors arise as a result of the interaction of vegetation with a natural resource, such as a geological formation (Linehan et al, 1995; Jordan et al, 2003; Townsend and Levey, 2005; Zehao et al, 2014). It is important to note that corridors will affect different species differently depending on the intended function of the corridor.
Conclusion
This is due to their ability to only provide forecasts for connectivity between a single source and a single destination (LaRue and Nielsen, 2008). A comprehensive landscape context analysis was carried out in Chapter 3, which helped to overcome some of the limitations of a least-cost-path analysis. A Least Cost Path was chosen due to its ability to account for multiple variables and as such helped derive the least expensive route for a landscape corridor to complete (Chapter 4).
ASSESSING HOW HABITAT FRAGMENTATION AND LOW
Introduction
It is entirely distributed within the sub-escarpment of KwaZulu-Natal Province (KZN). To our knowledge, no studies have been conducted to assess the current level of fragmentation and connectivity of the KZN SS vegetation type landscape. Due to this lack of information, the study aimed to quantify the level of habitat fragmentation of the KZN SS using measures of structural and functional connectivity.
This chapter is about quantifying overall habitat fragmentation within and outside the eThekwini metropolitan area.
Materials and methods
- Data acquisition and pre-processing
- Quantifying habitat fragmentation
- Analysis
- Determining the connectivity of different fragments
- Quantifying overall landscape connectivity
Thus, it not only takes into account the spatial configuration of the landscape (structural connectivity), but also includes the distribution distances of species and their interaction with the physical structure of the landscape (functional connectivity) in the analysis (Tischendorf and Fahrig, 2000; Theobald, 2006). . Therefore, the required inputs for the software are the spatial structure of the landscape and the distribution distance of the species under study. Data set 2 focused on patches that occurred outside the eThekwini metro, and data set 3 looked at the entire stretch of the KZN SS.
Two indices of connectivity were used to determine the extent of overall landscape connectivity of the KZN SS, namely; number of components and IIC.
Results
- The degree of habitat fragmentation
- Determining connectivity
Most of the KZN SS is located outside the eThekwini metro, which explains the large number of components in datasets 2 and 3 (Figure 3.1), which have more than 1200 components compared to datasets 1, 4 and 5. (Figures 3.1 and 3.2), which have less than 200 components. The slight difference between data sets 4 and 5 in Figure 3.2 shows that the inclusion of patches, regardless of their ecological status, has no significant effect on the degree of fragmentation. Dataset 5 (Figure 3.3), which considered degraded patches, showed a much higher degree of connectivity.
Patches 'A' and 'B', located in the Metro, are considered the most important in terms of connectivity (Figure 3.5A and 3.6A).
Discussion
- Understanding the implications of habitat fragmentation
- Dealing with the effects of connectivity
- Are landscape corridors the solution to the problem faced?
- The quantification of habitat fragmentation
The overall results of the analysis of the connectivity between patches of KZN SS showed that the level of connectivity is very low and therefore species persistence is threatened. The results gathered from the broad-scale data indicate that patches 'A' and 'B' (Figure 3.5A . & 3.6A) are crucial in relation to the connectivity of the KZN SS. The method used also helped to determine important criteria, such as the patches' individual contribution to the connectivity of the landscape (McGarigal and Cushman, 2002).
The fine-scale data showed a more appropriate description of the current state of the KZN SS.
Conclusion
In addition, the detailed data also included patches of KZN SS that were completely excluded from the broader data. The fine scale data is better to use, not only because it is a more recent data set and therefore gives a more adequate representation of what the KZN SS looks like, but the smaller scale of the fine scale adds to its level of accuracy which can be seen in the large scale data which does not showing large patches of KZN SS. The positive uses of this method for quantifying habitat fragmentation far outweigh any negative consequences.
As a result, this method of quantitative measurement of habitat fragmentation can be seen as a more applicable and simpler means to carry out this process.
DESIGNING LANDSCAPE CORRIDORS TO IMPROVE
Introduction
The grassland biome has become one of the most devastated biomes due to habitat loss and fragmentation (Tarboton, 1997). Ensuring landscape connectivity is crucial for conserving biodiversity and species survival in the region. One of the main limitations is the design of landscape corridors for a specific focal species (Simberloff, 1998; LaRue and Nielsen, 2008; Doko et al, 2011).
The aim of this chapter is to design appropriate regional corridors within the eThekwini metropolitan area to improve the connectivity levels of the KZN SS.
Materials and methods
- Data acquisition and pre-processing
- Delineating corridors
- The tool used to design the landscape corridor
- The analysis conducted
Here, the landscape corridors will be considered successful if they manage to consist of: more than 50% of the KZN SS (taking into account the small percentage of KZN SS present in the eThekwini Metropolitan area), 50% of the DMOSS ( taking into account the percentage of DMOSS in the eThekwini metro), less than 10% of urban areas (taking into account the large percentage of urban areas located within the eThekwini metro). Least cost analysis is one of the most widely used tools for corridor design and development (Store and Kangas, 2001; Adriaensen et al, 2003; Rouget et al, 2006). A comprehensive analysis of the state of connectivity levels of the KZN SS within the eThekwini Metro was carried out in Chapter 3.
This allowed Least Cost Path Analysis to be used to assist in the design and development of the KZN SS landscape corridors within the eThekwini Metro.
Results
Landscape corridors can be seen in Figure 4.4 and control corridors can be seen highlighted in Appendix B (Figure B3). Furthermore, less than 10% of the corridor consists of urban areas (Figure 4.8), after examining Figure B2B (see Appendix B) it is evident that there is no continuous extension of urban areas within. Similar to Corridor 1, the 20% of KZN SS present within Corridor 2 consists of moderately to highly connected patches (Figure 4.9).
Furthermore, the corridor has less than 5% of urban areas (Figure 4.9) which are sparsely distributed along the corridor (see Appendix B, Figure B2B).
Discussion
- Have the landscape corridors succeeded?
- Evaluation of methodology
- Urban green space planning
DMOSS can be seen as eThekwini's greenbelt or greenway, although it is not designed in the same way as a traditional greenbelt. The loss of Sydney's green belt is a prime example of the failure to implement a green belt. Eventually, the green belt had to be removed due to the unforeseen numbers of immigration to the city and the subsequent need for housing (Freestone, 1992).
In contrast, Adelaide's green belt is an initiative that has worked to limit the spread of urban development (Buxton and Goodman, 2003).
Conclusions
Urban green spaces should strive for an integrative approach to achieve a sustainable environment (Shah and Haq, 2011). Only one aspect of a sustainable environment, biodiversity and nature conservation, was considered in the corridors designed in the study. The corridors for the study were designed with the sole purpose of improving the level of connectivity within the eThekwini metro and thereby ensuring species persistence (Shah and Haq, 2011).
The integration of all these aspects will allow corridors to not only meet the needs of urban biodiversity conservation, but also contribute to ecosystem services such as recreational regions (Shah and Haq, 2011).
CONCLUSIONS AND RECOMMENDATIONS FOR FURTHER
Major research findings
- Quantifying the degree of habitat fragmentation of the KZN SS and determining the
- Comparing the effectiveness of fine-scale vs broad-scale data in quantifying habitat
- Designing landscape corridors to facilitate movement of species indigenous to the
- Assessing the actual importance of the protected areas network and the Durban
There were some associated challenges such as the lack of clear and distinct boundaries available for KZN SS distribution. The biggest challenge in relation to this goal was the lack of clear distinct boundaries of the KZN SS. The main limitation of this objective was the lack of data on individual species that would confirm the effectiveness and functionality of the proposed landscape corridors.
DMOSS has a key corridor role in conserving biodiversity in the urban areas of eThekwini Metro.
Implications for the management and conservation of the KwaZulu-Natal Sandstone
Important conservation regions are located within DMOSS, highlighting its importance in conserving biodiversity in the eThekwini Metropolitan Region. DMOSS was used as a means of ensuring that biodiversity concerns could inform the development planning and assessment process (Roberts et al, 2011). It can be implemented through restoration efforts such as clearing alien plants and fire control through an ecosystem work project.
The Bartlett Estate is a good example where the council has purchased private property and is currently converting it into a nature reserve to ensure the protection of pristine stretches of KZN SS.
Concluding Remarks
Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylavanica (Orthoptera) metapopulation. Comparison and development of new graph-based landscape connectivity indices: towards prioritizing habitat patches and corridors for conservation. Design of landscape corridors to improve connectivity levels of the KwaZulu-Natal Sandstone Acid Field within the eThekwini Metropolitan.
Figure B1 - Distribution of A) KwaZulu-Natal Sandstone Sourveld and B) DMOSS along Provincial Corridors 1 and 2.
