Search results for: gallery forest

Authors: Bhenjamin Jordan L. Ona

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Weather modification is an act of altering weather systems that catches interest on scientific studies. Cloud seeding is a common form of weather alteration. On the same principle, tropical cyclone mitigation experiment follows the methods of cloud seeding with intensity to account for. This study will present the effects of aerosol to tropical cyclone cloud microphysics and intensity. The framework of Weather Research and Forecasting (WRF) model incorporated with Thompson aerosol-aware scheme is the prime host to support the aerosol-cloud microphysics calculations of cloud condensation nuclei (CCN) ingested into the tropical cyclones before making landfall over the Philippine coast. The coupled microphysical and radiative effects of aerosols will be analyzed using numerical data conditions of Tropical Storm Ketsana (2009), Tropical Storm Washi (2011), and Typhoon Haiyan (2013) associated with varying CCN number concentrations per simulation per typhoon: clean maritime, polluted, and very polluted having 300 cm-3, 1000 cm-3, and 2000 cm-3 aerosol number initial concentrations, respectively. Aerosol species like sulphates, sea salts, black carbon, and organic carbon will be used as cloud nuclei and mineral dust as ice nuclei (IN). To make the study as realistic as possible, investigation during the biomass burning due to forest fire in Indonesia starting October 2015 as Typhoons Mujigae/Kabayan and Koppu/Lando had been seeded with aerosol emissions mainly comprises with black carbon and organic carbon, will be considered. Emission data that will be used is from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). The physical mechanism/s of intensification or deintensification of tropical cyclones will be determined after the seeding experiment analyses.

Keywords: aerosol, CCN, IN, tropical cylone

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

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The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

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Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

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Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

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Authors: Hachaichi Mohamed Nour El-Islem, Baouni Tahar

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Environmental sustainability rather than a trans-disciplinary and a scientific issue, is the main problem that characterizes all modern cities nowadays. In developing countries, this concern is expressed in a plethora of critical urban ills: traffic congestion, air pollution, noise, urban decay, increase in energy consumption and CO₂ emissions which blemish cities’ landscape and might threaten citizens’ health and welfare. As in the same manner as developing world cities, the rapid growth of Algiers’ human population and increasing in city scale phenomena lead eventually to increase in daily trips, energy consumption and CO₂ emissions. In addition, the lack of proper and sustainable planning of the city’s infrastructure is one of the most relevant issues from which Algiers suffers. The aim of this contribution is to estimate the carbon deficit of the City of Algiers, Algeria, using the Ecological Footprint Model (carbon footprint). In order to achieve this goal, the amount of CO₂ from fuel combustion has been calculated and aggregated into five sectors (agriculture, industry, residential, tertiary and transportation); as well, Algiers’ biocapacity (CO₂ uptake land) has been calculated to determine the ecological overshoot. This study shows that Algiers’ transport system is not sustainable and is generating more than 50% of Algiers total carbon footprint which cannot be sequestered by the local forest land. The aim of this research is to show that the Carbon Footprint Assessment might be a relevant indicator to design sustainable strategies/policies striving to reduce CO₂ by setting in motion the energy consumption in the transportation sector and reducing the use of fossil fuels as the main energy input.

Keywords: biocapacity, carbon footprint, ecological footprint assessment, energy consumption

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Authors: Fatemeh Parhizkar, Mojtaba Yamani, Abdolla Behboodi, Masoomeh Hashemi

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The mangrove forests are natural and valuable gifts that exist in some parts of the world, including Iran. Regarding the threats faced by these forests and the declining area of them all over the world, as well as in Iran, it is very necessary to manage and monitor them. The current study aimed to investigate the changes in mangrove forests and the relationship between these changes and the marine hydrodynamics and coastal morphology in the area between qeshm island and the west coast of the Hormozgan province (i.e. the coastline between Mehran river and Bandar-e Pol port) in the 49-year period. After preprocessing and classifying satellite images using the SVM, MLC, and ANN classifiers and evaluating the accuracy of the maps, the SVM approach with the highest accuracy (the Kappa coefficient of 0.97 and overall accuracy of 98) was selected for preparing the classification map of all images. The results indicate that from 1972 to 1987, the area of these forests have had experienced a declining trend, and in the next years, their expansion was initiated. These forests include the mangrove forests of Khurkhuran wetland, Muriz Deraz Estuary, Haft Baram Estuary, the mangrove forest in the south of the Laft Port, and the mangrove forests between the Tabl Pier, Maleki Village, and Gevarzin Village. The marine hydrodynamic and geomorphological characteristics of the region, such as average intertidal zone, sediment data, the freshwater inlet of Mehran river, wave stability and calmness, topography and slope, as well as mangrove conservation projects make the further expansion of mangrove forests in this area possible. By providing significant and up-to-date information on the development and decline of mangrove forests in different parts of the coast, this study can significantly contribute to taking measures for the conservation and restoration of mangrove forests.

Keywords: mangrove forests, marine hydrodynamics, coastal morphology, west of strait of Hormuz, Iran

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Authors: B. Niez, B. Moulia, J. Dlouha, E. Badel

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Trees adjust their development to the environmental conditions they experience. Storms events of last decades showed that acclimation of trees to mechanical stresses due to wind is a very important process that allows the trees to sustain for long years. In the future, trees will experience new wind patterns, namely, more often strong winds and fewer daily moderate winds. Moreover, these patterns will go along with drought periods that may interact with the capacity of trees to adjust their growth to mechanical stresses due to wind. It is necessary to understand the mechanisms of wood functional acclimations to environmental conditions in order to predict their behaviour and in order to give foresters and breeders the relevant tools to adapt their forest management. This work aims to study how trees adjust the mechanical and hydraulic functions of their wood to environmental stresses and how this acclimation may be beneficial for the tree to resist to future stresses. In this work, young poplars were grown under controlled climatic conditions that include permanent environmental stress (daily mechanical stress of the stem by bending and/or hydric stress). Then, the properties of wood formed under these stressed conditions were characterized. First, hydraulic conductivity and sensibility to cavitation were measured at the tissue level in order to evaluate the changes in water transport capacity. Secondly, bending tests and Charpy impact tests were carried out at the millimetric scale to locally measure mechanical parameters such as elastic modulus, elastic limit or rupture energy. These experimental data allow evaluating the impacts of mechanical and water stress on the wood material. At the stem level, they will be merged in an integrative model in order to evaluate the beneficial aspect of wood acclimation for trees.

Keywords: acclimation, environmental stresses, hydraulics, mechanics, wood

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Authors: Chukwuebuka Vincent Azuka, Chidimma Peace Odoh

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Changes in agricultural practices and land use influence the storage and release of soil organic carbon and soil structural dynamics. To investigate this in Nsukka, southeastern Nigeria, soil samples were collected at 0-10 cm, 10-20 cm and 20-30 cm from three locations; Ovoko (OV), Obukpa (OB) and University of Nigeria, Nsukka (UNN) and three land use types; cultivated land (CL), forest land (FL) and grassland (GL)). Data were subjected to analysis of variance (ANOVA) using SPSS. Also, correlations between organic carbon stock, structural stability indices and other soil properties were established. The result showed that Ksat was significantly (p < 0.05) influenced by location with mean values of 68 cmhr⁻¹,121.63 cmhr⁻¹, 8.42 cmhr⁻¹ in OV, OB and UNN respectively. The MWD and aggregate stability (AS) were significantly (p < 0.05) influenced by land use and depth. The mean values of MWD are 0.85 (CL), 1.35 (FL) and 1.45 (GL), and 1.66 at 0-10 cm, 1.08 at 10-20 cm and 0.88 mm at 20-30 cm. The mean values of AS are; 27.66% (CL), 46.39% (FL) and 49.81% (GL), and 53.96% at 0-10cm, 40.22% at 10-20cm and 29.57% at 20-30cm. Clay flocculation (CFI) and dispersion indices (CDI) differed significantly (p < 0.05) among the land use. Soil pH differed significantly (p < 0.05) across the land use and locations with mean values ranging from 3.90-6.14. Soil organic carbon (SOC) significantly (p < 0.05) differed across locations and depths. SOC decreases as depth increases depth with mean values of 15.6 gkg⁻¹, 10.1 gkg⁻¹, and 8.6 gkg⁻¹ at 0-10 cm, 10-20 cm, and 20-30 cm respectively. SOC in the three land use was 8.8 g kg-1, 15.2 gkg⁻¹ and 10.4 gkg⁻¹ at CL, FL, and GL respectively. The highest aggregate-associated carbon was recorded in 0.5 mm across the land use and depth except in cultivated land and at 20-30 cm which recorded their highest SOC at 1mm. SOC stock, total nitrogen (TN) and CEC were significantly (p < 0.05) different across the locations with highest values of 23.43 t/ha, 0.07g/kg and 14.27 Cmol/kg respectively recorded in UNN. SOC stock was significantly (p < 0.05) influenced by depth as follows; 0-10>10-20>20-30 cm. TN was low with mean values ranging from 0.03-0.07 across the locations, land use and depths. The mean values of CEC ranged from 9.96-14.27 Cmol kg⁻¹ across the locations and land use. SOC stock showed correlation with silt, coarse sand, N and CEC (r = 0.40*, -0.39*, -0.65** and 0.64** respectively. AS showed correlation with BD, Ksat, pH in water and KCl, and SOC (r = -0.42*, 0.54**, -0.44*, -0.45* and 0.49** respectively. Thus, land use and location play a significant role in sustainable management of soil resources.

Keywords: agricultural practices, structural dynamics, sequestration, soil resources, management

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Authors: Abdullah Al-Mamun, Md. Nuruzzaman, Md. Noor Salleh, Muhammad Abu Eusuf, Ahmad Jalal Khan Chowdhury, Mohd. Zaki M. Amin, Norlida Mohd. Dom

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Identification of pollution sources and determination of pollution loads from all areas are very important for sustainable rehabilitation of any contaminated river. Pusu is a small river which, flows through the main campus of International Islamic University Malaysia (IIUM) at Gombak. Poor aesthetics of the river, which is flowing through the entrance of the campus, gives negative impression to the local and international visitors. As such, this study is being conducted to find ways to rehabilitate the river in a sustainable manner. The point and non-point pollution sources of the river basin are identified. Upper part of the 12.6 km2 river basin is covered with secondary forest. However, it is the lower-middle reaches of the river basin which is being cleared for residential development and source of high sediment load. Flow and concentrations of the common pollutants, important for a healthy river, such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solids (SS), Turbidity, pH, Ammoniacal Nitrogen (AN), Total Nitrogen (TN) and Total Phosphorus (TP) are determined. Annual pollution loading to the river was calculated based on the primary and secondary data. Concentrations of SS were high during the rainy day due to contribution from the non-point sources. There are 7 ponds along the river system within the campus, which are severely affected by high sediment load from the land clearing activities. On the other hand, concentrations of other pollutants were high during the non-rainy days. The main sources of point pollution are the hostels, cafeterias, sewage treatment plants located in the campus. Therefore, both pollution sources need to be controlled in order to rehabilitate the river in a sustainable manner.

Keywords: river pollution, rehabilitation, point pollution source, non-point pollution sources, pollution loading

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Authors: Andrew Kanzunguze, Lusayo Mwabumba, Jason K. Gilbertson, Dominic B. Gondwe, George Z. Nxumayo

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Knowledge about the spatio-temporal distribution of invasive plants in protected areas provides a base from which hypotheses explaining proliferation of plant invasions can be made alongside development of relevant invasive plant monitoring programs. The aim of this study was to investigate the spatio-temporal distribution of bracken fern on the grassland plateau of Nyika National Park over the past 30 years (1986-2016) as well as to determine the current extent of the invasion. Remote sensing, machine learning, and statistical modelling techniques (object-based image analysis, image classification and linear regression analysis) in geographical information systems were used to determine both the spatial and temporal distribution of bracken fern in the study area. Results have revealed that bracken fern has been increasing coverage on the Nyika plateau at an estimated annual rate of 87.3 hectares since 1986. This translates to an estimated net increase of 2,573.1 hectares, which was recorded from 1,788.1 hectares (1986) to 4,361.9 hectares (2016). As of 2017 bracken fern covered 20,940.7 hectares, approximately 14.3% of the entire grassland plateau. Additionally, it was observed that the fern was distributed most densely around Chelinda camp (on the central plateau) as well as in forest verges and roadsides across the plateau. Based on these results it is recommended that Ecological Niche Modelling approaches be employed to (i) isolate the most important factors influencing bracken fern proliferation as well as (ii) identify and prioritize areas requiring immediate control interventions so as to minimize bracken fern proliferation in Nyika National Park.

Keywords: bracken fern, image classification, Landsat-8, Nyika National Park, spatio-temporal distribution

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Authors: Meimei Shi

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Objectives: The identification of endangered species, especially simultaneous detection of multiple species in complex samples, plays a critical role in alleged wildlife crime incidents and prevents illegal trade. This study was to develop a multi-locus DNA metabarcoding method for endangered animal species identification. Methods: Several pairs of universal primers were designed according to the mitochondria conserved gene regions. Experimental mixtures were artificially prepared by mixing well-defined species, including endangered species, e.g., forest musk, bear, tiger, pangolin, and sika deer. The artificial samples were prepared with 1-16 well-characterized species at 1% to 100% DNA concentrations. After multiplex-PCR amplification and parameter modification, the amplified products were analyzed by capillary electrophoresis and used for NGS library preparation. The DNA metabarcoding was carried out based on Illumina MiSeq amplicon sequencing. The data was processed with quality trimming, reads filtering, and OTU clustering; representative sequences were blasted using BLASTn. Results: According to the parameter modification and multiplex-PCR amplification results, five primer sets targeting COI, Cytb, 12S, and 16S, respectively, were selected as the NGS library amplification primer panel. High-throughput sequencing data analysis showed that the established multi-locus DNA metabarcoding method was sensitive and could accurately identify all species in artificial mixtures, including endangered animal species Moschus berezovskii, Ursus thibetanus, Panthera tigris, Manis pentadactyla, Cervus nippon at 1% (DNA concentration). In conclusion, the established species identification method provides technical support for customs and forensic scientists to prevent the illegal trade of endangered animals and their products.

Keywords: DNA metabarcoding, endangered animal species, mitochondria nucleic acid, multi-locus

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Authors: Fikre Belay Tekulu

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This thesis presents the socio-economic and environmental impacts of urban sprawl in the case of Adigrat city, Tigray Region, Ethiopia. The main objective of this research is to assess major causes, trends and socio-economic and environmental impacts of the urban sprawl of Adigrat city. The study employed both quantitative and qualitative methods as questionnaires, interviews and observation used for data collection. Simple random sampling has been used to select the participants. The land use and land cover change for agricultural land and forest and grassland resource analysis is done with the aid of GIS. Urban sprawl is mainly caused by the rapid population growth, increase in the living and property cost in the core of the city, land demand and land speculation and the growth of transport and an increase in income of people and demand of more living space. The study indicates 15726.24 hectares (515.49 per cent) of new land added to the city jurisdiction from its adjacent Gantafeshum Wereda between 1986 and 2018. The population of Adigrat city increased by 9.045 per cent per year, while the city expanded 16.01 per cent per annum and the LCR was 0.0233 hectares per person between 1986 and 2018.Built-up area increased by 35.27 per cent per annum, while agricultural land, forests and grassland cover decreased by 1.68 per cent and 1.26 per cent per annum respectively in the last thirty three years. This rapid growth of urban sprawl brought social-economic and environmental change in the city that has been observed by the city residents. Therefore, the city administration should need strong, integrated, effective and efficient work, with its neighbor rural area and also done timely preparation, implementation, supervision, and evaluation of the structural plan of the city to bring out sustainable development of the city.

Keywords: cause, , trends, urban sprawl, land use land cover, GIS

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Authors: Aleksandar M. Radojković, Jovana M. Ćirković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

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In many parts of the world, various Phytophthora species pose a serious threat to forests and crops. With the rapidly growing international trade in plants and the ongoing impacts of climate change, the harmful effects of plant pathogens of the genus Phytophthora are increasing, damaging the biodiversity and sustainability of forest ecosystems. This genus is one of the most destructive plant pathogens, causing the majority of fine root (66%) and collar rot diseases (90%) of woody plant species worldwide. Eco-friendly biopesticides, based on plant-derived products, such as essential oils (EOs), are one of the promising solutions to this problem. In this study, among three different EOs investigated (Chamaecyparis lawsoniana (A. Murr.) Parl., Thuja plicata Donn ex D.Don and Juniperus communis L.), western red cedar (Thuja plicata) essential oil almost completely inhibited the growth of three Phytophthora species (P. plurivora Jung and Burgess, P. quercina Jung, and P. ×cambivora (Petri) Buisman) during seven days of exposure for the EO concentrations of 0.1% and 0.5% (v/v). To prolong the inhibiting effect, Thuja plicata EO was encapsulated into a biopolymer matrix consisting of a chitosan-gelatin mixture to form a water-in-oil emulsion. This approach allowed the prolonged effect of the essential oil by its slow release from the biopolymer matrix and protection of the active components from atmospheric influences. Thus, it was demonstrated that encapsulated Thuja plicata EO consisting of sustainable bioproducts is efficient in controlling of Phytophthora species and can be considered a means of protection in natural and semi-natural ecosystems.

Keywords: emulsions, essential oils, phytophthora, thuja plicata

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Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

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This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

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Authors: Melis Inalpulat, Levent Genc

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In the present study, an attempt was made to state the Land Use Land Cover (LULC) transformation over three decades around the urban regions of Balıkesir, Bursa, and Çanakkale provincial centers (PCs) in Turkey. Landsat imageries acquired in 1984, 1999 and 2014 were used to determine the LULC change. Images were classified using the supervised classification technique and five main LULC classes were considered including forest (F), agricultural land (A), residential area (urban) - bare soil (R-B), water surface (W), and other (O). Change detection analyses were conducted for 1984-1999 and 1999-2014, and the results were evaluated. Conversions of LULC types to R-B class were investigated. In addition, population changes (1985-2014) were assessed depending on census data, the relations between population and the urban areas were stated, and future populations and urban area needs were forecasted for 2030. The results of LULC analysis indicated that urban areas, which are covered under R-B class, were expanded in all PCs. During 1984-1999 R-B class within Balıkesir, Bursa and Çanakkale PCs were found to have increased by 7.1%, 8.4%, and 2.9%, respectively. The trend continued in the 1999-2014 term and the increment percentages reached to 15.7%, 15.5%, and 10.2% at the end of 30-year period (1984-2014). Furthermore, since A class in all provinces was found to be the principal contributor for the R-B class, urban sprawl lead to the loss of agricultural lands. Moreover, the areas of R-B classes were highly correlated with population within all PCs (R²>0.992). Depending on this situation, both future populations and R-B class areas were forecasted. The estimated values of increase in the R-B class areas for Balıkesir, Bursa, and Çanakkale PCs were 1,586 ha, 7,999 ha and 854 ha, respectively. Due to this fact, the forecasted values for 2,030 are 7,838 ha, 27,866, and 2,486 ha for Balıkesir, Bursa, and Çanakkale, and thus, 7.7%, 8.2%, and 9.7% more R-B class areas are expected to locate in PCs in respect to the same order.

Keywords: landsat, LULC change, population, urban sprawl

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Maher J. Tadros

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This research was conducted to study the effect of different salinity concentrations on the plant water relation and forage quality on two multipurpose forest trees species seedlings Leucaena leucocephala (Lam.) de wit and Acacia saligna (Labill.). Five different salinity concentrations mixture between sodium chloride and calcium chloride (v/v, 1:1) were applied. The control (Distilled Water), 2000, 4000, 6000, and 8000 ppm were used to water the seedlings for 3 months. The research results presented showed a marked variation among the two species in response to salinity. The Leucaena was able to withstand the highest level of salinity compared to Acacia all over the studied parameters except in the relative water content. Although all the morphological characteristics studied for the two species showed a marked decrease under the different salinity concentrations, except the shoot/root ratio that showed a trend of increase. The water stress measure the leaf water potential was more negative with as the relative water content increase under that saline conditions compared to the control. The forage quality represented by the crude protein and nitrogen content were low at 6000 ppm compared to the 8000 ppm in L. Leucocephala that increased compared that level in A. saligna. Also the results showed that growing both Leucaena and Acacia provide a good source of forage when that grow under saline condition which will be of great benefits to the agricultural sector especially in the arid and semiarid areas were these species can provide forage with high quality forage all year around when grown under irrigation with saline. This research recommended such species to be utilized and grown for forages under saline conditions.

Keywords: plant water relations, growth performance, salinity stress, protein content, forage quality, multipurpose trees

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Authors: K. K. Bolarinwa, A. F. O. Ayinde, B. B. Abiona, O. Oyekunle

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Conflict and HIV/AIDS infection have had a profound impact on the Sub-Saharan African societies, individually and collectively. Nigeria has been experiencing several violent conflicts in many communities across the geographical spread of the country. These conflicts which often lead to loss of lives, properties and loss of livelihoods are mainly felt by women in terms of increased responsibility towards affected family members with attendant decrease in livelihood options. Despite these, conflict issues have not really received enough focal attention by Nigerian academics. It is against this backdrop that this study was undertaken to describe the respondents, the most prevalent conflict repercussions and most prevalent STDs, in conflict areas. Data were collected using interview schedule to elicit a response from 122 respondents in Southwest Nigeria, through a multi-stage sampling technique involving stratification of respondents into violent conflict areas (VCA) and non-violent conflict areas (NVCA). The data collected were analysed using descriptive statistics and correlation analysis. Results revealed that majority (86.5% and 70.5 %) of the respondents were in the age bracket of 10-39 years in both the VCA and NVCA respectively; 35.5% and 40.2% of the respondents were literate in VCA and NVCA, respectively while 76.5% and 55.8% of the respondents were in the lower income groups in VCA and NVCA, respectively. HIV/AIDS and gonorrhoea were the more predominant (75.2% and 55.6% respectively) STDs in the VCA as against 33.2% and 38.3% respectively in the NVCA. Further, significant (p<0.05) correlation existed between conflict incidence and spread of HIV/AIDS, rape and torture, maltreatment of women as well as sexual harassment; in both VCA and NVCA among others. The study concluded that conflict situations in the study area aggravated incidence of HIV/AIDS and made the women more vulnerable to inhuman treatments such as rape, torture and harassment with attendant reduction in sources of livelihoods. The study recommended among others that sensitisation on control and preventive measures of HIV/AID and other sexually transmitted diseases should be included in programme designed to mitigate against conflicts in the study areas.

Keywords: conflict, gender dimension, HIV/AIDS epidemiology, Nigeria

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Authors: Kevin Soubly, Kaysara Khatun

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This study applies the existing Middle-Out Perspective (MOP) as a complementing analytical alternative to the customary dichotomous options of top-down vs. bottom-up strategies of international development and commons governance. It expands the framework by applying it to a new context of land management and environmental change, enabling fresh understandings of decision making around land use. Using a case study approach in Central Kalimantan, Indonesia among a village of indigenous Dayak, this study explores influences from both internal and external middle actors, utilizing qualitative empirical evidence and incorporating responses across 25 village households and 11 key stakeholders. Applying the factors of 'agency' and 'capacity' specific to the MOP, this study demonstrates middle actors’ unique capabilities and criticality to change due to their influence across various levels of decision-making. Study results indicate that middle actors play a large role, both passively and actively, both directly and indirectly, across various levels of decision-making, perception-shaping, and commons governance. In addition, the prominence of novel 'passive' middle actors, such as the internet, can provide communities themselves with a level of agency beyond that provided by other middle actors such as NGOs and palm oil industry entities – which often operate at the behest of the 'top' or out of self-interest. Further, the study posits that existing development and decision-making frameworks may misidentify the 'bottom' as the 'middle,' raising questions about traditional development and livelihood discourse, strategies, and support, from agricultural production to forest management. In conclusion, this study provides recommendations including that current policy preconceptions be reevaluated to engage middle actors in locally-adapted, integrative manners in order to improve governance and rural development efforts more broadly.

Keywords: environmental management, governance, Indonesia, land use, middle actors, middle-out perspective

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Anima Ashraf

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Over the past few decades biodiversity has become the issue of global concern for its rapid reduction worldwide. Bangladesh is no exception. The country is exceptionally endowed with a vast variety of flora and fauna, but due to tremendous population pressure, rural poverty and unemployment it has been decreased alarmingly. Since, both biodiversity and sustainable development are the part of human life in modern era and both work together to make our life safer and comfortable therefore balance should be kept in development and biodiversity conservation and priority should be given to alternative and sustainable development paths. This paper is based on study of two projects undertaken by Arannayk Foundation jointly with its local NGO partners. The aim was to understand previous, current and future scenarios for the hilly biodiversity of Khagrachari in the Chittagong Hill Tracts (CHT) of Bangladesh. It is also observed how alternative income generating activities (AIGA) improve livelihood of the tribal inhabitants of the area, decrease their dependency on forest resources and also aid conservation activities. Intensive field visits were made and interviews were conducted with key informants to see the progress and achievements of local NGOs working with the tribal community for the past seven years to restore the denuded hills of Khagrachari. The paper also covers the impacts and interventions of the projects and the methods used to aid conservation activities. Raising awareness among the villagers has reduced extraction of forests resources by 47% and granting funds and access to microcredit to adopt AIGAs have increased their average annual income by 25%. Finally, the paper concludes that effective community-based conservation practices are fundamental to ensure biodiversity conservation in the Chittagong Hill Tracts. In order to conserve biodiversity and restore the forests of CHT, livelihood development of the villagers has to be considered as the main component of the projects undertaken by all NGOs and the Government.

Keywords: biodiversity, conservation, forests, livelihood

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Authors: Peifang Hsieh

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The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

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Authors: Shaista Maseeh

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English Literature from the beginning itself has had psychological, social and environment concerns. Virgil, Shakespeare, John Milton, William Wordsworth to the most current Robert Hass have shown and proved their environmental and ecological interests as well as distress related to its loss. Pastoral literature is also one such genre that links literature with environment. Thanks to the contemporary literary theories that they successfully are relating Literature formally to the subjects other than written text. One of such literary theory is 'Ecocriticism.' It stands under the umbrella of the Economics term, Sustainable Development,' or it can also be understood as an ecological extension of it. Ecocriticism helps the reader to study the dynamic relation between literature and our degrading environment. It draws attention towards the ravaged condition of nature and animals, that how nature is exploited by human beings for their own benefit leaving nature at a repairable loss. For instance, deforestation is reducing the size of forest every year, injuring permanently flora, fauna and also the habitat of animals. This paper will study the ecological and environmental concerns in the latest novel by Pakistani British writer Kamila Shamsie, A God in every Stone (2014). The book is not only a literary masterpiece in elegant prose, but also a novel posing a lot of questions about 'nature and environment' in general and 'animals' in particular. It gives the glimpses of the interesting history of Temple of Zeus in Greece and Ancient Caria, and covers many episodes of history the Indian freedom struggle. In course of novel's narrative Kamila Shamsie poses disturbing question about environmental abuse, about how human beings are more 'beasts' than so call beasts, poor animals. She also glorifies the simplicity of past. The novel has enough instances to prove Shamsie's positive stand on saving the earth that is being more abused than used by human beings. This paper will provide an ecocritical approach to study A God in Every Stone (2014).

Keywords: animals, ecocriticism, environment, nature

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Authors: Essam A. Makky, Chan Cai Wen, Muna Jalal, Mashitah M. Yusoff

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Termites are considered as important pests that could cause severe wood damage and economic losses in urban, agriculture and forest of Malaysia. The ability of termites to degrade cellulose depends on association of gut cellulolytic microflora or better known as mutual symbionts. With the idea of disrupting the mutual symbiotic association, better pest control practices can be attained. This study is aimed to isolate cellulolytic bacteria from the gut of termites and carry out antibacterial studies for the termite. Confirmation of cellulase activity is done by qualitative and quantitative methods. Impacts of antibiotics and their combinations, as well as heavy metals and disinfectants, are conducted by using disc diffusion method. Effective antibacterial agents are then subjected for termite treatment to study the effectiveness of the agents as termiticides. 24 cellulolytic bacteria are isolated, purified and screened from the gut of termites. All isolates were identified as Gram-negative with either rod or cocci in shape. For antibacterial studies result, isolates were found to be 100% sensitive to 4 antibiotics (rifampicin, tetracycline, gentamycin, and neomycin), 2 heavy metals (cadmium and mercury) and 3 disinfectants (lactic acid, formalin, and hydrogen peroxide). 22 out of 36 antibiotic combinations showed synergistic effect while 15 antibiotic combinations showed an antagonistic effect on isolates. The 2 heavy metals and 3 disinfectants that showed 100% effectiveness, as well as 22 antibiotic combinations, that showed synergistic effect were used for termite control. Among the 27 selected antibacterial agents, 12 of them were found to be effective to kill all the termites within 1 to 6 days. Mercury, lactic acid, formalin and hydrogen peroxide were found to be the most effective termiticides in which all termites were killed within 1 day only. These effective antibacterial agents possess a great potential to be a new application to control the termite pest species in the future.

Keywords: antibacterial, cellulase, termicide, termites

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Authors: Andrew Kanzunguze, Sopani Sichinga, Paston Simkoko, George Nxumayo, Cosmas, V. B. Dambo

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Early detection of plant invasions is a necessary prerequisite for effective invasive plant management in protected areas. This study was conducted to determine the distribution and abundance of alien invasive trees in Nyika National Park (NNP). Data on species' presence and abundance were collected from belt transects (n=31) in a 100 square kilometer area on the central plateau. The data were tested for normality using the Shapiro-Wilk test; Mann-Whitney test was carried out to compare frequencies and abundances between the species, and geographical information systems were used for spatial analyses. Results revealed that Black Wattle (Acacia mearnsii), Mexican Pine (Pinus patula) and Himalayan Raspberry (Rubus ellipticus) were the main alien invasive trees on the plateau. A. mearnsii was localized in the areas where it was first introduced, whereas P. patula and R. ellipticus were spread out beyond original points of introduction. R. ellipticus occurred as dense, extensive (up to 50 meters) thickets on the margins of forest patches and pine stands, whilst P. patula trees were frequent in the valleys, occurring most densely (up to 39 stems per 100 square meters) south-west of Chelinda camp on the central plateau with high variation in tree heights. Additionally, there were no significant differences in abundance between R. ellipticus (48) and P. patula (48) in the study area (p > 0.05) It was concluded that R. ellipticus and P. patula require more attention as compared to A. mearnsii. Howbeit, further studies into the invasion ecology of both P. patula and R. ellipticus on the Nyika plateau are highly recommended so as to assess the threat posed by the species on biodiversity, and recommend appropriate conservation measures in the national park.

Keywords: alien-invasive trees, Himalayan raspberry, Nyika National Park, Mexican pine

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Authors: Marlene Yu Lilin Wätzold, Wisnu Harto Adiwijoyo, Meike Wollni

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Land-use conversion from tropical forests to cash crop production in the form of monocultures has drastic consequences for biodiversity. Meanwhile, high dependence on cash crop production is often associated with a decrease in other food crop production, thereby affecting household dietary diversity. Additionally, deforestation rates have been found to reduce households’ dietary diversity, as forests often offer various food sources. Agroforestry systems are seen as a potential solution to improve local biodiversity as well as provide a range of provisioning ecosystem services, such as timber and other food crops. While a number of studies have analyzed the effects of agroforestry on biodiversity, as well as household livelihood indicators, little is understood between potential trade-offs or synergies between the two. This interdisciplinary study aims to fill this gap by assessing cacao agroforestry’s role in enhancing local bird diversity, as well as farm household dietary diversity. Additionally, we will take a landscape perspective and investigate in what ways the landscape composition, such as the proximity to forests and forest patches, are able to contribute to the local bird diversity, as well as households’ dietary diversity. Our study will take place in two agro-ecological zones in Ghana, based on household surveys of 500 cacao farm households. Using a subsample of 120 cacao plots, we will assess the degree of shade tree diversity and density using drone flights and a computer vision tree detection algorithm. Bird density and diversity will be assessed using sound recordings that will be kept in the cacao plots for 24 hours. Landscape compositions will be assessed via remote sensing images. The results of our study are of high importance as they will allow us to understand the effects of agroforestry and landscape composition in improving simultaneous ecosystem services.

Keywords: agroforestry, biodiversity, landscape composition, nutrition

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Authors: John Gichimu Mbaka, Jan Helmrich Martin von Baumbach, Celia Somlai, Denis Köpfer, Andreas Maeck, Andreas Lorke, Ralf Schäfer

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Leaf litter decomposition is an important process providing energy to biotic communities. Additionally, methane gas (CH4) has been identified as an important alternative source of carbon and energy in some freshwater food webs.Flow regulation and dams can strongly alter freshwater ecosystems, but little is known about the effect of small impoundments on leaf litter decomposition and methane derived carbon in streams. In this study, we tested the effect of small water storage impoundments on leaf litter decomposition rates and methane derived carbon. Leaf litter decomposition rates were assessed by comparing treatment sites located close to nine impoundments (Rheinland Pfalz state, Germany) and reference sites located far away from the impoundments.CH4 concentrations were measured in eleven impoundments and correlated with the δ13C values of two subfamilies of chironomid larvae (i.e. Chironomini and Tanypodinae). Leaf litter break down rates were significantly lower in study sites located immediately above the impoundments, especially associated with a reduction in the abundance of shredders. Chironomini larvae had the lower mean δ13C values (‒29.2 to ‒25.5 ‰), than Tanypodinae larvae (‒26.9 to ‒25.3 ‰).No significant relationships were established between CH4 concentrations and δ13C values of chironomids (p> 0.05).Mean δ13C values of chironomid larvae (mean: ‒26.8‰, range: ‒ 29.2‰ to ‒ 25.3‰) were similar to those of sedimentary organic matter (SOM) (mean: ‒28.4‰, range: ‒ 29.3‰ to ‒ 27.1‰) and tree leaf litter (mean: ‒29.8 ‰, range: ‒ 30.5‰ to ‒ 29.1‰). In conclusion, this study demonstrates that small impoundments may have a negative effect on leaf litter decomposition in forest streams and that CH4 has limited influence on the benthic food web in stream impoundments.

Keywords: river functioning, chironomids, Alder tree, stable isotopes, methane oxidation, shredder

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Authors: Ambika Prasad Gupta, Harshit Sosan Lakra

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Food security is an important issue that has been widely discussed in literature. However, there is a lack of research on the specific food security challenges faced by tribal communities. Tribal food security refers to the ability of indigenous or tribal communities to consistently access and afford an adequate and nutritious supply of food. These communities often have unique cultural, social, and economic contexts that can impact their food security. The study aims to assess the food security status of all thirty-two major tribes, including Particularly Vulnerable Tribal Groups (PVTG) people living in various blocks of Jharkhand State. The methodology of this study focuses on measuring the food security index of indigenous people by developing and redefining a new Tribal Food Security Index (TFSI) as per the indigenous community-level indicators identified by the Global Food Security Index and other indicators relevant to food security. Affordability, availability, quality and safety, and natural resources were the dimensions used to calculate the overall Tribal Food Security Index. A survey was conducted for primary data collection of tribes and PVTGs at the household level in various districts of Jharkhand with a considerable tribal population. The result shows that due to the transition from rural to urban areas, there is a considerable change in TFSI and a decrease in forest dependency of tribal communities. Socioeconomic factors like occupation and household size had a significant correlation with TFSI. Tribal households living in forests have a higher food security index than tribal households residing in urban transition areas. The study also shows that alternative methodology adopted to measure specific community-level food security creates high significant impact than using commonly used indices.

Keywords: indigenous people, tribal food security, particularly vulnerable tribal groups, Jharkhand

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Authors: S. K. Dewangan, K. R. Sahu, S. Soni

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Unemployment is today’s basic socio-economic problem eroding national income and living standards, aggravating national development and poverty alleviation. The farmers are encouraged to take up non-agriculture practices which are integrated with Sericulture. Sericulture is one of the primary occupations for livelihood of poor people in tribal area. Most of tribal are involved in Sericulture. Tasar, Eri are the main forest-based cultivation. Among these sericultures is the major crop adopted by the Tribal’s and practiced in respective areas. Out of the 6, 38,588 villages in India, sericultures are practiced in about 69000 villages providing employment to about 7.85 million people. Sericulture is providing livelihood for 9, 47,631 families. India continues to be the second largest producer of silk in the World. Among the four varieties of silk produced, as in 2012-13, Mulberry accounts for 18,715 MT, Eri 3116 MT, Tasar 1729 MT and Muga 119MT of the total raw silk production in the country. Sericulture with its unique features plays an important role in upgrading the socio-economic conditions of the rural folk and with employment opportunities to the educated rural youth and women. In view of the importance of sericulture enterprise for the biodiversity conservation as well as its cultural bondage, the paper tries to enlighten and discuss the significance of sericulture and strategies to be taken for the employment generation in Indian sericulture industry. The present paper explores the possible employment opportunities derived from problem analysis and strategies to be adopted aiming at revolutionary biodiversity conservation in the study area. The paper highlights the sericulture is a way for biodiversity conservation, employment generation in Raigarh district, their utilization and needs as they act as a tool for socio-economic change for tribal. The study concludes with some suggestions to improve the feasibility of sericulture in long term.

Keywords: bio-diversity, employment, sericulture, tribal, income, socio-economic

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Authors: Aswandi Anas Husin, Cut Rizlani Kholibrina

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Harvesting camphor resin has been carried out since the beginning of civilization on the west coast of Sumatra. Oil or crystals that containing borneol are harvested from the camphor tree (Dryobalanops aromatica). Non-timber forest products are utilized for the manufacture of fragrances, antiseptics, anti-inflammatory, analgesic as well as effective for the treatment of blocked arteries. Based on exploration on the west coast of Sumatra, these endemic tree species were found remaining growing in groups on small spots in the lowlands to the hills. Some populations are found at an altitude of 700 meters above sea level in Kadabuhan, Jongkong and Sultan Daulat in Subulussalam district, Singkohor and Lake Paris in Aceh Singkil district, and Sirandorung and Manduamas in the north of Barus, Central Tapanuli district. These multi-purpose tree species was also identified as being able to adapt to the Singkil Peat Swamp. The decline in tree population has a direct impact on reducing their productivity. Conventionally, the crystals are harvested by cutting and splitting the stem into wooden blocks. In this way about 1.5-2.5 kg of crystals are obtained with various qualities. Camphor retrieval can also be done by making a notch on a standing tree trunk and collecting liquid resin (ombil) that is removed from the injured resin channel. Twigs and leaves also contain borneol. The aromatic content in this section opens opportunities for the supply of borneol through the distillation process. Vegetative propagation technology is needed to overcome the limitations of available seeds. This breeding strategy for vulnerable species starts with gathering genetic material from various provenances which are then used to support the provision of basic populations, breeding populations, multiplication populations and production populations for extensive development of camphor tree plantations

Keywords: camphor, conservation, natural borneol, productivity, vulnerable species

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