Opportunities for forest finance under the International climate change regime

The international climate change regime has the potential to increase revenue available for forest restoration projects in Commonwealth nations. There are three mechanisms which could be used to fund forest projects aimed at forest conservation, forest restoration and sustainable forest management. The first forest funding opportunity arises under the clean development mechanism, a flexibility mechanism of the Kyoto Protocol. The clean development mechanism allows Annex I parties (industrialised nations) to invest in emission reduction activities in non-Annex 1 (developing countries) and the establishment of forest sinks is an eligible clean development mechanism activity. Secondly, parties to the Kyoto Protocol are able to include sustainable forest management activities in their national carbon accounting. The international rules concerning this are called the Land-Use, Land-Use Change and Forestry Guidelines. Thirdly, it is anticipated that at the upcoming Copenhagen negotiations that a Reduced Emissions from Deforestation and Degradation (REDD) instrument will be created. This will provide a direct funding mechanism for those developing countries with tropical forests. Payments made under a REDD arrangement will be based upon the developing country with tropical forest cover agreeing to protect and conserve a designated forest estate. These three funding options available under the international climate change regime demonstrate that there is potential for forest finance within the regime. These opportunities are however hindered by a number of technical and policy barriers which prevent the ability of the regime to significantly increase funding for forest projects. There are two types of carbon markets, compliance carbon markets (Kyoto based) and voluntary carbon markets. Voluntary carbon markets are more flexible then compliance markets and as such offer potential to increase revenue available for sustainable forest projects.

Australia and Forest Carbon Partnerships : Indigenous Land Rights

One of the ways in which indigenous communities seek justice is through the formal recognition of their sovereign rights to land. Such recognition allows indigenous groups to maintain a physical and spiritual connection with their land and continue customary management of their land. Indigenous groups world over face significant hurdles in getting their customary rights to land recognized by legal systems. One of the main difficulties for indigenous groups in claiming customary land rights is the existence of a range of conflicting legal entitlements attaching to the land in question. In Australia, similar to New Zealand and Canada legal recognition to customary land is recognized through a grant of native title rights or through the establishment of land use agreement. In other jurisdictions such as Indonesia and Papua New Guinea a form of customary land title has been preserved and is recognized by the legal system. The implementation of REDD+ and other forms of forest carbon investment activities compounds the already complex arrangements surrounding legal recognition of customary land rights. Free, prior and informed consent of indigenous groups is essential for forest carbon investment on customary land. The attainment of such consent in practice remains challenging due to the number of conflicting interests often associated with forested land. This paper examines Australia’s experience in recongising indigenous land rights under its International Forest Carbon Initiative and under its domestic Carbon Credits (Carbon Farming Initiative) Act (Australia) 2011. Australia’s International Forest Carbon initiative has a budget of $273 million dollars. In 2008 the governments of Australia and Indonesia signed the Indonesia-Australia Forest Carbon Partnership Agreement. This paper will examine the indigenous land tenure and justice lessons learned from the implementation of the Kalimantan Forest and Climate Partnership (KFCP). The KFCP is $30 million dollar project taking place over 120,000 hectares of degraded and forested peatland in Central Kalimantan, Indonesia. The KFCP project site contains seven villages of the Dayak Ngdu indigenous people. In 2011 Australia established a domestic Forest Carbon Initiative, which seeks to provide new economic opportunities for farmers, forest growers and indigenous landholders while helping the environmental by reducing carbon pollution. This paper will explore the manner in which indigenous people are able to participate within these scheme noting the limits and opportunities in deriving co-benefits for indigenous people in Australia under this scheme.

The effects of deep cracks on the rain-induced instability of slopes : A case study

Rainfall can disrupt the balance of natural soil slope. This imbalance will be accelerated by existence of cracks in soil slope, which lead to decreasing shear strength and increasing hydraulic conductivity of the soil slope. Some research works have been conducted on the effects of surface-cracks on slope stability. However, the influence of deep-cracks is yet to be investigated. Limited availability of deep crack data due to the lack of effective sub-soil investigation methods could be one of the obstacles. To emphasize the effects of deep cracks in soil slope on its rain-induced instability, a natural soil slope in Indonesia that failed in 31st October 2010 due to heavy rainfall was analyzed for stability with and without deep cracks in the slope. The slope stability analysis was conducted using SLOPE/W coupling with the results of transient seepage analysis (SEEP/W) that simulate the pore-water pressure development in the slope during the rainfall. The results of Electrical Resistivity Tomography (ERT) survey, bore-hole tests and geometrical survey conducted on the slope before its failure were used to identify the soil layers’ stratification including deep cracks, the properties of different soil layers, and geometrical parameters of the slope for the analysis. The results showed that it is vital to consider the existence of deep crack in soil slopes in analysing their instability induced by rainfalls.

Effects of slope inclination on the rain-induced instability of embankment slopes

Rainfall has been identified as one of the main causes for embankment failures in areas where high annual rainfall is experienced. The inclination of the embankment slope is important for its stability during rainfall. In this study, instrumented model embankments were subjected to artificial rainfalls to investigate the effects of the slope inclination on their stability. The results of the study suggested that when the slope inclination is greater than the friction angle of the soil, the failure is initiated by the loss of soil suction and when it is smaller than the friction angle of the soil, the failure is initiated by the positive pore water pressure developed at the toe of the slope. Further, slopes become more susceptible to sudden collapse during rainfall as the slope angle increases.

Wetlands, climate zones and Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia, but the linkages of the wetlands and climate zones with BFV transmission remain unclear. We aimed to examine the relationship between the wetlands, climate zones and BFV risk in Queensland, Australia. Data on the wetlands, climate zones, population and BFV cases for the period 1992 to 2008 were obtained from relevant government agencies. BFV risk was grouped as low-, medium- and high-level based on BFV incidence percentiles. The buffer zones around each BFV case were made using 1, 5, 10, 15, 20, 25 and 50 km distances. We performed a discriminant analysis to determine the differences between wetland classes and BFV risk within each climate zone. The discriminant analyses show that saline 1, riverine and saline tidal influence were the most significant contributors to BFV risk in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. These models had classification accuracies of 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV risk varies with wetland class and climate zone. The discriminant analysis is a useful tool to quantify the links between wetlands, climate zones and BFV risk.

Cryptic diversity and evolutionary relationships among Australian closed-forest Melomys (Rodentia: Muridae) and related Australo-Papuan mosaic-tailed rats

This thesis investigates patterns of evolution in a group of native Australo-Papuan rodents. Past climatic change and associated sea level fluctuations, and fragmentation of wet forests in eastern Australia has facilitated rapid radiation, diversification and speciation in this group. This study adds to our understanding of the evolution of Australia’s rainforest fauna and describes the evolutionary relationships of a new genus of Australian rodent.

A method for predicting rain-induced instability of an individual slope

Awareness to avoid losses and casualties due to rain-induced landslide is increasing in regions that routinely experience heavy rainfall. Improvements in early warning systems against rain-induced landslide such as prediction modelling using rainfall records, is urgently needed in vulnerable regions. The existing warning systems have been applied using stability chart development and real-time displacement measurement on slope surfaces. However, there are still some drawbacks such as: ignorance of rain-induced instability mechanism, mislead prediction due to the probabilistic prediction and short time for evacuation. In this research, a real-time predictive method was proposed to alleviate the drawbacks mentioned above. A case-study soil slope in Indonesia that failed in 2010 during rainfall was used to verify the proposed predictive method. Using the results from the field and laboratory characterizations, numerical analyses can be applied to develop a model of unsaturated residual soils slope with deep cracks and subject to rainwater infiltration. Real-time rainfall measurement in the slope and the prediction of future rainfall are needed. By coupling transient seepage and stability analysis, the variation of safety factor of the slope with time were provided as a basis to develop method for the real-time prediction of the rain-induced instability of slopes. This study shows the proposed prediction method has the potential to be used in an early warning system against landslide hazard, since the FOS value and the timing of the end-result of the prediction can be provided before the actual failure of the case study slope.

Impact of rain on daily bus ridership : a Brisbane case study

Weather is one of the most significant elements affecting transit ridership on a daily basis. Until now, there has been limited focus in the literature investigating this issue. Adverse weather conditions impact travellers in choosing travel mode and route, travel schedule, and trip making itself. This paper explores the relationship between adverse weather and transit ridership by analysing the correlation between daily bus ridership and daily precipitation for a three-year period from 2010 to 2012. It is observed from the analysis that wet weather has varying impacts on daily bus ridership. Overall, rainfall negatively affects the daily bus ridership in this region. Morning peak-hours and weekend ridership were found more sensitive to rain than entire day’s ridership and weekdays. The study also found a negative correlation between the morning-peak precipitation level and the daily bus ridership, which suggests that a small amount of morning peak-hours rain reduces a significant amount bus ridership for the whole day. The analysis also confirms that summer rain has the most significant effect on ridership compared with the other three seasons. The study findings will contribute to enhancing the fundamental understanding of traveller behaviours, particularly mode choice behaviour under adverse weather conditions.

Forecasting the future risk of Barmah Forest Virus disease under climate change scenarios in Queensland, Australia

BACKGROUND Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. METHODS/PRINCIPAL FINDINGS We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. CONCLUSIONS/SIGNIFICANCE We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

Spatially-explicit modelling of grassland classes - an improved method of integrating a climate-based classification model with interpolated climate surfaces

Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.

Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score

Catchment and riparian degradation has resulted in declining ecosystem health of streams worldwide. With restoration a priority in many regions, there is an increasing interest in the scale at which land use influences stream ecosystem health. Our goal was to use a substantial data set collected as part of a monitoring program (the Southeast Queensland, Australia, Ecological Health Monitoring Program data set, collected at 116 sites over six years) to identify the spatial scale of land use, or the combination of spatial scales, that most strongly influences overall ecosystem health. In addition, we aimed to determine whether the most influential scale differed for different aspects of ecosystem health. We used linear-mixed models and a Bayesian model-averaging approach to generate models for the overall aggregated ecosystem health score and for each of the five component indicators (fish, macroinvertebrates, water quality, nutrients, and ecosystem processes) that make up the score. Dense forest close to the survey site, mid-dense forest in the hydrologically active nearstream areas of the catchment, urbanization in the riparian buffer, and tree cover at the reach scale were all significant in explaining ecosystem health, suggesting an overriding influence of forest cover, particularly close to the stream. Season and antecedent rainfall were also important explanatory variables, with some land-use variables showing significant seasonal interactions. There were also differential influences of land use for each of the component indicators. Our approach is useful given that restoring general ecosystem health is the focus of many stream restoration projects; it allowed us to predict the scale and catchment position of restoration that would result in the greatest improvement of ecosystem health in the regions streams and rivers. The models we generated suggested that good ecosystem health can be maintained in catchments where 80% of hydrologically active areas in close proximity to the stream have mid-dense forest cover and moderate health can be obtained with 60% cover.

'Not a Local Win': Rural Australian perceptions of the sustainable impacts of forest plantations

Australian forestry plantations have doubled in the past 15 years, with rural communities harbouring a diverse range of positive and negative of economic, environmental and social impacts – the so-called triple bottom line (TBL). Utilising two Australian rural communities in Eden/Gippsland and Tasmania as qualitative case studies, this research explores how 23 non-forestry affiliated rural residents perceived and experienced the TBL economic, environmental and social impacts of plantation forestry. Residents criticised the economic plantation forestry benefits because of lengthy periods of inactivity and limited local employment, explaining that their community was reliant on the industry yet the promised economic benefits had never fully materialised. There was a sense the industry ‘plant and walk away.’ Residents were concerned about the environment impact on water quality, water tables and fire hazards, although they praised plantation forestry for carbon sequestering, eradicating erosion and water run-off. Negative social impacts were described, specifically how the land-use change from farming to forestry had significantly reduced the local population, employment and need for services. Natural resource management and communication strategies are offered, derived from non-forestry affiliated rural resident perspectives on how best to ensure sustainable forest development in their community.

Detection of rain in acoustic recordings of the environment

Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

Spatial analysis of risk factors for transmission of the Barmah forest virus in Queensland, Australia

Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia but few data are available on the risk factors. We assessed the impact of spatial climatic, socioeconomic and ecological factors on the transmission of BFV disease in Queensland, Australia, using spatial regression. All our analyses indicate that spatial lag models provide a superior fit to the data compared to spatial error and ordinary least square models. The residuals of the spatial lag models were found to be uncorrelated, indicating that the models adequately account for spatial and temporal autocorrelation. Our results revealed that minimum temperature, distance from coast and low tide were negatively and rainfall was positively associated with BFV disease in coastal areas, whereas minimum temperature and high tide were negatively and rainfall was positively associated with BFV disease (all P-value.

Emerging methods in using GIS to analyse Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is an emerging mosquito-borne disease in Australia. We aimed to outline some recent methods in using GIS for the analysis of BFV disease in Queensland, Australia. A large database of geocoded BFV cases has been established in conjunction with population data. The database has been used in recently published studies conducted by the authors to determine spatio-temporal BFV disease hotspots and spatial patterns using spatial autocorrelation and semi-variogram analysis in conjunction with the development of interpolated BFV disease standardised incidence maps. This paper briefly outlines spatial analysis methodologies using GIS tools used in those studies. This paper summarises methods and results from previous studies by the authors, and presents a GIS methodology to be used in future spatial analytical studies in attempt to enhance the understanding of BFV disease in Queensland. The methodology developed is useful in improving the analysis of BFV disease data and will enhance the understanding of the BFV disease distribution in Queensland, Australia.