Tanzania's Eastern Arc Mountains form part of the Eastern Afromontane Biodiversity Hotspots, listed among the global World Wide Fund for Nature's (WWF) priority ecoregions. The overall objective of this study was to quantify fragmentation, examine its impact on tree species diversity, abundance and biomass, and to identify management interventions in the Eastern Arc Mountains of Tanzania.
Plagiarism
Publications and manuscripts
General overview
This not only affects habitat structure, but also makes it a challenge for species survival (Platts et al., 2008). To date, the topic of landscape-human interactions, species distribution and interactions is a poorly understood topic in the tropics (Turner et al., 2003).
The potential of remote sensing in conservation of the Eastern Arc Mountains
Remotely sensed datasets are also valuable for maximizing multi-temporal monitoring efforts (Wiens et al., 2009). In general, remotely sensed datasets, unlike field-based techniques, are valuable in monitoring areas that would otherwise be expensive and time-consuming (Wiens et al., 2009).
Study goal and objectives
A conceptual framework was built with the aim of establishing relationships between fragmentation and impacts on vegetation in the Eastern Arc Mountains. The framework used played an important role in identifying problems, the complexities associated with conservation and possible solutions in the applied case studies.
Study area
- Location and climate
- Biological significance
- Study site selection
Selection of case studies was based on a detailed synthesis of literature review conducted in the region, which showed a lack of knowledge about challenges of habitat modification and fragmentation (Green et al., 2013b; Newmark, 1998; Platts, 2012; Shirk et al., 2014). This forest block is considered vulnerable to fragmentation, which affects biodiversity conservation in the region (Burgess et al., 2007a; Burgess et al., 2002).
Thesis structure
In addition, the importance of integrating relatively fine resolution data in the conservation and management of complex forest blocks in the Eastern Arc Mountains is discussed. Research reflections and future recommendations in the management of the Eastern Arc Mountains are presented.
Introduction
Ecosystems in the Morogoro region, Tanzania contribute to global climate regulation through large carbon sinks (Burgess et al., 2007; Swetnam et al., 2011). An increase in anthropogenic disturbances poses a significant threat to their long-term conservation (Hall et al., 2009; Hall, 2009; Newmark, 1998).
Study area
Kitulanghalo Forest is part of Miombo, which covers 90% of the total forested ecosystem in Tanzania (Mugasha et al., 2013). They are dominated by Brachystegia, Isoberlinia and Julbernardia species, Pterocarpus angolensis, Afzelia quanzesis and Albizia (Munishi et al., 2010).
Materials and methods
- Image pre-processing
- Image classification
- Modelling habitat fragmentation
- Secondary data
Patch area (MN) Refers to the sum, over all patches in the landscape, of the corresponding patch metric values, divided by the total number of patches in (ha). Useful for calculating the proportional abundance for each of the patch types across the landscape.
Results
- Classification and accuracy assessment
- Change detection
- Quantifying the magnitude of change
- Fragmentation patterns
- Mann-Whitney results
- Games Howell test results for perimeter area relationship
- Population trends in the region
Woodlands and grasslands had the highest PARA compared to less dense and dense forests (Table 2.4). Spatial analyzes indicated a greater probability of dispersal in forests and less dense forest habitats.
Discussion
- Spatial and temporal patterns in Morogoro region
- Potential driving forces and conservation impacts
The patchy type of fragmentation is driven by economic and demographic reasons (Green et al., 2013a). Furthermore, a decline in woodland can be attributed to timber harvesting for commercial purposes in Kitulanghalo Forest (Theilade et al., 2007).
Conclusions
Impacts of forest fragmentation on species abundance and diversity in the Eastern Arc Mountains of Tanzania. Effect of forest fragmentation on tree species abundance and diversity in the Eastern Arc Mountains of Tanzania.
Introduction
Despite their global importance, the region remains highly vulnerable to anthropogenic impacts (Bjørndalen, 1992; Burgess et al., 2002). To date, this topic remains unexplored in natural fragmenting ecosystems of the Morogoro region, Tanzania (Hall et al., 2009). Currently, the topic of how landscape modification and species interactions are not well explored (Turner et al., 2003).
Materials and methods
- Study area
- Field data collection
- Image acquisition and pre-processing
- Soil chemical analysis
The status of the habitat in Uluguru forest blocks was categorized into two classes; fragmented and intact (82 data points were used). ATCOR is useful in computing the ground reflectance image for the reflective spectral bands and emissivity images for the thermal bands. The spectrometer was then used to extract reflectance values for each of the elements (N, P, K, ph, C) which were then taken for wet chemistry analysis.
Data analysis
- Image classification
- Modelling fragmentation
- Statistical analyses
GARP is basically an algorithm that helps in identifying the best ecological niche for species occurrence or survival. Jack Knife tests were used to determine the significance of the variables used to run the model (Saatchi et al., 2008). This test is built into the GARP model which is important to test the importance of each of the environmental variables used.
Results
- Estimating tree species abundance
- Impacts of forest fragmentation on patch area and soil health
- Impacts of forest fragmentation on species abundance and soil health
- GARP model AUC KAPPA results
- Species diversity
Syzygium cordatum Hochst.ex C.Krauss was the most dominant tree species, representing 18% of all measured trees (Figure 3.4). The model was performed with a high accuracy of the total area under the curve (AUC) of 0.89, indicating a good model fit. High species diversity dominated the pristine areas in the central area of the Uluguru Forest (Figure 3.5A), while low species diversity was prevalent in the fragmented areas (Figure 3).
Discussion
- Fragmentation impacts on species abundance and soil health conditions
- Impacts of fragmentation on species diversity
- Conservation implications
This could be related to the rich biodiversity resources in the high terrain areas in the Ulugurus (Swetnam et al., 2011). The intensification of agricultural systems and settlements represents a key threat to the abundance and survival of species in the Ulugurus (Burgess et al., 2007b). Most likely, the existence of the species could become irreplaceable in the long term if the trend continues (Rondinini et al., 2006).
Conclusions
This is beneficial in establishing farming systems and therefore attractive to subsistence farmers in Tanzania (Burgess et al., 2007a). These ecosystems are valuable social and ecological assets as they contain large carbon storage capacity (Howell et al., 2006). Due to variability in topo-edaphic characteristics, studies have shown that biomass in tropical forests varies across landscapes (Schulp et al., 2008).
Materials and methods
- Study area
- Biomass estimation based on field allometric equations
- Soil analysis and topographic variables
- Image acquisition and pre-processing
However, to our knowledge, none of these studies have investigated the integration of topo-edaphic and remotely sensed variables for predicting forest above ground biomass. In the current study, we hypothesized that complementing topoedaphic factors with remotely sensed variables could provide a better assessment when estimating aboveground forest biomass in a heterogeneous tropical landscape. The existing allometric model of Chave et al., 2005 was then used to estimate aboveground biomass.
Data analysis
However, the PLSR model may perform poorly if a high number of components are included in the model (Mevik and Wehrens, 2007). A number of components that resulted in the first minimum RMSE error were selected. The use of twenty-nine spectral vegetation indices (Table 4.1) for the estimation of aboveground biomass in the study area was also tested.
Results
- Species and trends in above ground forest biomass contribution
When only eight topo-edaphic variables were used, i.e. (DEM, slope, Shannon, N, P, K, ph, C), the PLSR model showed only 44% of the variability in above-ground forest biomass. On the other hand, a PLSR model with a total of 29 vegetation indices and the 8 topo-edaphic factors explained 60% of the above-ground variability of the forest biomass. Using eight topo-edaphic factors, (B) using 29 vegetation indices, and (C) using 29 vegetation indices plus the eight topo-edaphic factors based on 115 samples.
Discussions
- Use of vegetation indices on above ground biomass estimation
- Effects of edaphic factors on above ground biomass estimation
- Comparing biomass estimates with previous studies
- Management implications
This finding is consistent with other study findings that show the effect of topo-edaphic factors on aboveground biomass productivity (Colgan et al., 2012). Other studies considered only dbh, while others considered both dbh and height (Mugasha et al., 2013). Regular biomass assessment studies are considered a prerequisite in effectively quantifying carbon stocks and fluxes (Ketterings et al., 2001).
Conclusions
It is envisaged that the present results provide information on the current biomass status, but also inform decision makers on the need to carry out regular conservation monitoring frameworks in Morogoro region. Using remotely sensed data and empirical data from 335 households, a model was developed to understand how different ecological and socioeconomic factors affected ecosystem vulnerability in the region. From a social point of view, low income level (54.62%) and limited knowledge about environmental conservation (18.51%) are considered important catalysts that increase ecosystem vulnerability.
Introduction
Vulnerability has been directly related to sensitivity to change, degree of exposure, and ability to cope (Kasperson et al., 2005; Gallopín 2006). Vulnerability is widely used in various fields, including climate studies (Antwi-Agyei et al., 2012) and social system (Adger, 2006). Gaps in knowledge and the best ways to link science and policy can hinder effective management interventions (Giliba et al., 2011).
Materials and methods
- Study area
- Field data collection
A lack of region-specific policy and management guidelines is one of the leading factors limiting conservation and management efforts, especially in sub-Saharan Africa, where there are multiple drivers of change (Dolisca et al. , 2006; Giliba et al., 2011). . This is attributed to an increase in settlements and agricultural activities in the region. 96 activities in the region, perceptions on changes in forest cover over the last twenty years, and appropriate strategies for managing vulnerable landscapes.
Data analysis
Results
- Forest cover change - an indicator of ecosystem vulnerability
- Ecosystem vulnerability as perceived by respondents
- Socio-economic factors influencing ecosystem vulnerability
- Management interventions
- Population trend statistics in the region
Duncan's post-hoc tests were used to assess significant differences (p≤ 0.05) within and between group means. Duncan's post hoc test showed statistical significance within and between group differences in different villages (Figure 5.3). The results of Duncan's post-test showed statistical significance within and between group differences in different villages (Figure 5.4).
Discussion
- Natural ecosystem vulnerability in Morogoro region
- Emerging factors
The extent of deforestation in most forests in Tanzania makes conservation very challenging (Kidegheho et al., 2013). For example, sustainable livelihood options hold more promise relative to better livelihood options (Lopa et al., 2012). To an extent, local communities in the region lack confidence in their national governments regarding policy planning and management (Sanga et al., 2013).
Conclusions and recommendations
A relatively good percentage of respondents in the region (24.2%) indicated the need for long-term reforestation programs. Despite the challenges associated with managing vulnerable ecosystems, our results present a window for positive change by pointing to the need to strengthen livelihood diversification needs and effective institutional frameworks. It is of utmost importance that the management of vulnerable landscapes integrate policy guidelines aligned with effective institutional and livelihood diversification frameworks.
Introduction
The 112 spectrum (690-730 nm), which characterizes some of the newer generation sensors, offers great potential for distinguishing between diverse and stressed vegetation types (see Figure 6.1) (Eitel et al., 2011). To date, the use of remotely sensed data in ecological applications in Tanzania remains limited (Platts, 2012). This is explained in the discussion section with reference to preservation of the eastern arch blocks.
Effectiveness of remotely-sensed data in the study
- Analysis of vegetation fragmentation
- An analysis of impacts on vegetation species
- The potential utility of remote sensing in biomass estimation
- Analyzing potential threats and opportunities
Little research in the Eastern Arc Mountains has used remote sensing data and other biophysical variables to understand patterns of species diversity and threats in each of the forest blocks (Platts et al., 2008). This may be due to the fact that altitude determines the abundance of species in the Uluguru mountain ecosystem. The red edge band has the potential to detect chlorophyll concentration in the visible region of the spectrum; which allows the use of different vegetation indices in the prediction of aboveground biomass.
Discussions
In addition, research work in the field of biomass estimation also confirms the need to incorporate remote sensing techniques to support biodiversity conservation initiatives. The need to assess the conservation and management policies that have/have not been implemented is one aspect that stood out strongly from the management perspective of this study. Therefore, conservationists and other natural resource professionals must establish other options for local communities living near natural areas.
Conclusions and future research opportunities
A study of habitat fragmentation in southeastern Brazil using remote sensing and geographic information systems (GIS). Potential Effects of Agricultural Expansion and Climate Change on Soil Erosion in the Eastern Arc Mountains of Kenya. 142 forest fragmentation on tree species abundance and diversity in Tanzania's Eastern Arc Mountains.
