The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechanisms are unknown. Here, a novel application of a method for predicting disease occurrence that combines machine learning and statistics is used to identify the key spatial scales that define the relationship between zoonotic malaria cases and environmental change. Using data from satellite imagery, a case-control study, and a cross-sectional survey, predictive models of household-level occurrence of P. knowlesi were fitted with 16 variables summarized at 11 spatial scales simultaneously. The method identified a strong and well-defined peak of predictive influence of the proportion of cleared land within 1 km of households on P. knowlesi occurrence. Aspect (1 and 2 km), slope (0.5 km) and canopy regrowth (0.5 km) were important at small scales. By contrast, fragmentation of deforested areas influenced P. knowlesi occurrence probability most strongly at large scales (4 and 5 km). The identification of these spatial scales narrows the field of plausible mechanisms that connect land use change and P. knowlesi, allowing for the refinement of disease occurrence predictions and the design of spatially-targeted interventions.
Leaf samples of tropical trees, i.e. Dryobalanops lanceolata (Kapur paji), Dipterocarpaceae and Macaranga spp. (Mahang), Euphorbiaceae were analyzed for 21 chemical elements. The pioneer Macaranga spp. exhibited higher concentrations for the majority of elements compared to the emergent species of Dryobalanops lanceolata, which was attributed to the higher physiological activity of the fast growing pioneer species compared to emergent trees. Lead showed rather high concentrations in several samples from the Bakam re-forestation site. This is suggested to be caused by emissions through brick manufacturing and related activities in the vicinity. A comparison of Dryobalanops lanceolata samples collected in 1993, 1995 and 1997 in the Lambir Hills National Park revealed that certain heavy metals, i.e. Co, Cu, Mn, Ni, Pb and Ti showed higher values in 1997 compared to the previous years, which could indicate an atmospheric input from the haze caused by the extensive forest fires raging in Borneo and other parts of Southeast Asia.
Much of the forest remaining in South East Asia has been selectively logged. The processes promoting species coexistence may be the key to the recovery and maintenance of diversity in these forests. One such process is the Janzen-Connell mechanism, where specialized natural enemies such as seed predators maintain diversity by inhibiting regeneration near conspecifics. In Neotropical forests, anthropogenic disturbance can disrupt the Janzen-Connell mechanism, but similar data are unavailable for South East Asia. We investigated the effects of conspecific density (two spatial scales) and distance from fruiting trees on seed and seedling survival of the canopy tree Parashorea malaanonan in unlogged and logged forests in Sabah, Malaysia. The production of mature seeds was higher in unlogged forest, perhaps because high adult densities facilitate pollination or satiate pre-dispersal predators. In both forest types, post-dispersal survival was reduced by small-scale (1 m(2)) conspecific density, but not by proximity to the nearest fruiting tree. Large-scale conspecific density (seeds per fruiting tree) reduced predation, probably by satiating predators. Higher seed production in unlogged forest, in combination with slightly higher survival, meant that recruitment was almost entirely limited to unlogged forest. Thus, while logging might not affect the Janzen-Connell mechanism at this site, it may influence the recruitment of particular species.
This paper assesses the Environmental Kuznets curve based on quantile behavior of the relationship between economic growth, forest area, agriculture production, renewable energy, and environmental degradation. The current literature generally used a single indicator to address environmental issues; however single indicator neither measures overall environmental conditions nor does specify that the environment issue is generally diminishing. Our study is the first one that used ecological footprint (EF) as an indicator to test environmental Kuznets curve (EKC) hypothesis for Pakistan by employing recent approach of quantile autoregressive distributed lag (QARDL) initiated by Cho et al. (J Econ 188(1):281-300, 2015). The result of this study validates the EKC hypothesis for Pakistan and shows quantile-dependent relationship, and in that case, using the conventional methods may somewhat lead to biased results. Moreover, the rejection of the null hypothesis of parameter constancy is also confirmed by Wald test. In the long run, the findings of renewable energy consumption and forest area show significant negative effects on ecological footprints, which indicates that by increasing renewable energy usage and forest area, ecological footprints can be minimized. Interestingly, the short-term effects of agricultural production findings on EF show statistically negative results. This illustrates that EF can also be reduced in the agriculture sector by adopting environment-friendly technologies. In order to create efficient policies for environment deterioration, the empirical findings of the current analysis can be used as a guideline for policy implications.
Sustainable forest management (SFM) practices have started in 1999 in Turkey. A set of criteria and indicators, composed by the General Directorate of Forestry (GDF) on the basis of the criteria and indicators defined in the Pan-European and Near Eastern Processes, was enquired via a survey to serve this purpose. GDF tested the sustainability under the following titles: Situation of forest resources, biodiversity, health and vitality, production capacity and functions, protective functions and environmental and socio-economic functions. There were problems in identification and definition of SFM criteria and indicators. Biological diversity indicators has been selected, described and developed in this study. At this phase, the survey was completed upon receiving the views of the scientists interested in different dimensions of this topic as well as the views of other interest groups affiliated with forestry. As a result, there were 13 indicators that may be used as the basis of a regional or forest management unit level for the purpose of protecting, developing and maintaining biodiversity. Furthermore, these indicators are instruments, which may easily be used by relevant decision-makers in the management of forest resources in a more effective and productive manner.
Agricultural expansion and deforestation are spatial processes of land transformation that impact on landscape pattern. In peninsular Malaysia, the conversion of forested areas into two major cash crops--rubber and oil palm plantations--has been identified as driving significant environmental change. To date, there has been insufficient literature studying the link between changes in landscape patterns and land-related development policies. Therefore, this paper examines: (i) the links between development policies and changes in land use/land cover and landscape pattern and (ii) the significance and implications of these links for future development policies. The objective is to generate insights on the changing process of land use/land cover and landscape pattern as a functional response to development policies and their consequences for environmental conditions. Over the last century, the development of cash crops has changed the country from one dominated by natural landscapes to one dominated by agricultural landscapes. But the last decade of the century saw urbanization beginning to impact significantly. This process aligned with the establishment of various development policies, from land development for agriculture between the mid 1950s and the 1970s to an emphasis on manufacturing from the 1980s onward. Based on a case study in Selangor, peninsular Malaysia, a model of landscape pattern change is presented. It contains three stages according to the relative importance of rubber (first stage: 1900--1950s), oil palm (second stage: 1960s--1970s), and urban (third stage: 1980s--1990s) development that influenced landscape fragmentation and heterogeneity. The environmental consequences of this change have been depicted through loss of biodiversity, geohazard incidences, and the spread of vector-borne diseases. The spatial ecological information can be useful to development policy formulation, allowing diagnosis of the country's "health" and sustainability. The final section outlines the usefulness of landscape analysis in the policy-making process to prevent further fragmentation of the landscape and forest loss in Malaysia in the face of rapid economic development.
Genetically modified organisms (GMO) are increased remarkably from year to year and the estimated global area cultivated with genetically modified (GM) crops reached 125 million hectares in year 2008. However, insect resistance maize based on Bacillus thuringienses (Bt) is of the most cultivated GM crop in worldwide. Bacillus thuringiensis (Bt) is an aerobic, gram-positive bacterium that synthesize one or more Cry protein that are toxic to various types crop and forestry insects pests. To date, several cry genes have been introduced into GM plant to combat with various type of insect. Worldwide commercialization of GM crops has raised the customers’ concern about the Biosafety issues, and thus, many countries have implemented the labeling legislations for GM food and their derivatives. In this study, we introduced the quantitative analysis method based on the recombinant plasmid DNA as calibrators that can be used to determine the percentage of GMO content in various types of food and feed samples. Therefore, we have reported 7.5% (6/80) of the samples were contained StarLink maize and 1.25% (1/80) samples were contained Bt176 maize. Additionally, the percentage of GM content in each positive sample were further determined with the developed quantitative method. The percentage of the StarLink corns that present in the positive samples were varies from 0.09% to 2.53% and Bt176 corn that present in the positive sample was 16.90%. The present study demonstrated that the recombinant plasmid DNA that used in quantitative real-time method as good alternative quantitative analysis of GM content.