572 research outputs found
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Knowledge, attitudes and practices (KAP) towards rabies and free-roaming dogs (FRD) in Shirsuphal village in western India: A community based cross-sectional study
Full text linkThe lack of awareness about dog-bite related rabies in the rural population of developing countries, including India, is a major impediment to controlling the incidence of disease in humans. A survey of 127 rural residents was undertaken in Shirsuphal village in western India using a structured questionnaire to assess the influence of demographic and pet/livestock owning characteristics on the knowledge, attitudes and practices of the respondents
towards rabies and free roaming dogs (FRD). Multivariable logistic regression models were constructed and the knowledge of the rural residents of Shirsuphal village was found to be significantly influenced by family size (OR 2.1, 95%CI 1.0–4.6, p = 0.04) and poultry ownership
(OR 2.3, 95%CI 1.1–4.9, p = 0.03), while their attitudes towards FRD was significantly influenced by age of the respondents (OR 2.6, 95% CI 1.2–5.8) and ownership of cattle/ buffalo (OR 2.2, 95% CI 1.1–5.5). Although the knowledge score about rabies was high, a comprehensive understanding of the disease was lacking. Concerted efforts to widen the knowledge about rabies and promote healthier practices towards FRD are recommended
Evaluation of the performance of SAR and SAR-optical fused dataset for crop discrimination
Full text linkCrop discrimination and acreage play a vital role in interpreting the cropping pattern, statistics of the produce and market value of each product. Sultan Battery is an area where a large amount of irrigated and rainfed paddy crops are grown along with Rubber, Arecanut and Coconut. In addition, the northern region of Sultan Battery is covered with evergreen and deciduous forest. In this study, the main objective is to evaluate the performance of optical and Synthetic Aperture Radar (SAR)-optical hybrid fusion imageries for crop discrimination in Sultan Bathery Taluk of Wayanad district in Kerala. Seven land use classes such as paddy, rubber, coconut, deciduous forest, evergreen forest, water bodies and others land use (e.g., built-up, barren etc.) were selected based on literature review and local land use classification policy. Both Sentinel-2A (optical) and sentinel-1A (SAR) satellite imageries of 2017 for Kharif season were used for classification using three machine learning classifiers such as Support Vector Machine (SVM), Random Forest (RF) and Classification and Regression Trees (CART). Further, the performance of these techniques was also compared in order to select the best classifier. In addition, spectral indices and textural matrices (NDVI, GLCM) were extracted from the image and best features were selected using the sequential feature selection approach. Thus, 10-fold cross-validation was employed for parameter tuning of such classifiers to select best hyperparameters to improve the classification accuracy. Finally, best features, best hyperparameters were used for final classification and accuracy assessment. The results show that SVM outperforms the RF and CART and similarly, Optical+SAR datasets outperforms the optical and SAR satellite imageries. This study is very supportive for the earth observation scientists to support promising guideline to the agricultural scientist, policy-makers and local government for sustainable agriculture practice
Contesting renewable energy in the global south: A case-study of local opposition to a wind power project in the Western Ghats of India
No full textInfluenced by global concerns around climate change mitigation, reduction in carbon emissions and energy security, countries are increasingly focussing on increasing the share of renewable energy. Various national and provincial level authorities are aggressively promoting renewable energy expansion, resulting in new geographies of renewable energy. The expansion of renewable energy, particularly large-scale projects, is contingent upon access to natural resources. However, areas that have high natural resource endowment for renewable energy, often have other overlapping uses of natural resources, including livelihoods and biodiversity. And renewable energy projects located in these areas compete with these other multiple uses of natural resources, often leading to unintended consequences. This study employs ethnographic methods to analyse the case of local opposition to a 113 MW wind power project, located in the Western Ghats of India. India, an emerging economy, is the fourth largest producer of wind energy worldwide and is expanding the share of renewable energy through national as well as provincial level policies. The Western Ghats are a designated UNESCO world heritage site for their exceptional biodiversity and the wind power project conflicted with natural resource-based livelihoods of indigenous populations and threatened their subsistence agricultural practices along with posing a threat to the ecology of the landscape. As a result, local activists protested against the wind power project and this contestation was animated and influenced by a variety of public, civic and private actors and institutions across scale. This paper uses insights from political ecology and energy geography to shed light on the interaction between these multiple actors and how this interaction mediated the contestations around renewable energy. It focuses on the micropolitics of this contestation to highlight the social and political processes that underpin the transition to sustainable energy. It sheds light on local struggles and contestations around renewable energy projects in conjunction with national and global commitments and shows how contestations around renewable energy in the Global South are distinct from the largely prevalent NIMBY approaches in the developed countries. This study contributes to global debates around governing renewable energy, particularly in developing countries
Assessing the transferability of machine learning algorithms using cloud computing and earth observation datasets for agricultural land use/cover mapping
Full text linkMapping of agricultural land use/cover was initiated since the past several decades for land use planning, change detection analysis, crop yield monitoring etc. using earth observation datasets and traditional parametric classifiers. Recently, machine learning, cloud
computing, Google Earth Engine (GEE) and open source earth observation datasets widely used for fast, cost-efficient and precise agricultural land use/cover mapping and change detection analysis. Main objective of this study was to assess the transferability of the machine learning algorithms for land use/cover mapping using cloud computing and open source earth observation datasets. In this study, the Landsat TM (L5, L8) of 2018, 2009 and 1998 were selected and median reflectance of spectral bands in Kharif and Rabi season were used for the classification. In addition, three important machine learning algorithms such as Support Vector Machine with Radial Basis Function (SVM-RBF), Random forest (RF) and Classification and Regression Tree (CART) were selected to evaluate the performance in transferability for agricultural land use classification using GEE. Seven land use/cover classes such as built-up, cropland, fallow land, vegetation etc. were selected based on literature review and local land use classification scheme. In this classification, several strategies were employed such as feature extraction, feature selection, parameter tuning, sensitivity analysis on size of training samples, transferability analysis to assess the performance of the selected machine learning algorithms for land use/cover classification. The result shows that SVM-RBF outperforms the RF and CART for both spatial and temporal transferability analysis. This result is very helpful for agriculture and remote sensing scientist to suggest
promising guideline to land use planner and policy-makers for efficient land use mapping, change detection analysis, land use planning and natural resource management
Unpacking the ‘canine conundrum’
No full textAt the end of the Indian epic, the Mahabharata, the victorious Pandava king Yudhisthir and his brothers renounce worldly pleasures and make their final pilgrimage to the Himalayas. Throughout this arduous journey, they are accompanied by a stray dog. Eventually, only the king and the dog survive. At this point, Indra, the god of heaven appears and invites the king to board his chariot, but without the faithful dog, as it is
considered unworthy of entering heaven. In some sense, this dual identity of the dog mirrors that of Cerberus, the hound of Hades. In Hesiod’s description, Cerberus is friendly and welcoming to the dying, but if they attempt to return to the world of the living, the murderous nature of Cerberus is unleashed (Wasik & Murphy, 2012)
Development of microsatellite markers for the resin-yielding, non-timber forest product species Boswellia serrata (Burseraceae)
Full text linkPREMISE OF THE STUDY: Boswellia serrata (Burseraceae) is an economically important aromatic,gum-resin–yielding, non-timber forest tree species. Microsatellite markers were developed for B. serrata for the first time to study genetic diversity and population structure.
METHODS AND RESULTS: A magnetic bead enrichment method was used to develop 16 microsatellite markers, of which 11 were polymorphic. The number of alleles per locus in
the 60 individuals studied ranged from three to 10, and the levels of observed and expected heterozygosity ranged from 0.50 to 0.90 and 0.666 to 0.861, respectively. The primers successfully amplified in the congeneric species B. ovalifoliolata.
CONCLUSIONS: These microsatellite markers can be used to study the genetic variation and population structure of B. serrata and to provide crucial information on population and ecological issues for management and conservation of the species
Bush encroachment influences nocturnal rodent community and behaviour in a semi-arid grassland in Gujarat, India
No full textBush encroachment is one of the major threats to grasslands globally. The increased cover due to bush encroachment can strongly influence the behaviour of animals adapted to a more open habitat. In this study, we
explored the effects of bush encroachment on the foraging behaviour of nocturnal rodents the semi-arid Banni
grasslands of western India, once one of India's largest tropical grassland habitats. We quantified foraging behaviour using the giving-up density (GUD) framework, across two sites that differed in the extent of bush encroachment.
Rodents in the site with high bush encroachment (the dense site) exhibited higher foraging costs (higher GUD) in early summer compared to the site with low bush encroachment (the sparse site). Rodents in the dense site also had lower activity. The dense site supported higher richness and relative abundance of generalist rodents than the sparse site. Our results suggest that bush encroachment may be associated with higher foraging
costs for nocturnal rodents and result in a change in species composition of rodents. Given the ecosystem engineering services performed by native grassland species, these results can have negative implications for
grassland restoration
Development and characterization of microsatellite markers for Phyllanthus emblica Linn., important nontimber forest product species
Full text linkPhyllanthus emblica and P. indofischeri, commonly known as the Indian gooseberry, are important nontimber forest
product (NTFP) species widely distributed across the Indian subcontinent. The fruits of these species are rich in vitamin C and are used in the preparation of a number of herbal medicines for treating a wide range of disorders. Due to the increased demand, they have been harvested extensively and form a major source of income for the forest-dwelling communities living in southern
India. There are limited studies to understand the impact of harvesting on the genetic structure of these species. In this study, 15 polymorphic microsatellite markers have been developed for P. emblica and were characterized by screening 20 individuals each of P.emblica and P. indofischeri. The number of alleles per locus ranged 2–9 for P. emblica and 2–11 for P. indofischeri. The observed and expected heterozygosity of P. emblica ranged 0–1 and 0.401–0.825, respectively. Similarly, the observed and expected heterozygosity of P. indofischeri ranged 0.5–1 and 0.366–0.842, respectively. Cross-amplification of the designed primers was assessed with seven related
Phyllanthus species. The microsatellite markers developed can be used for studying the population genetic structure, gene flow and genetic diversity of P. emblica and P. indofischeri
Knowledge, attitudes and practices towards dog-bite related rabies in para-medical staff at rural primary health centres in Baramati, western India
Full text linkThe lack of awareness regarding rabies amongst rural primary care health staff and their adverse practices towards the management of dog-bite wounds is a major contributor to the high incidence of rabies infection and subsequent human mortality in India. A Knowledge,
Attitudes and Practices survey was carried out involving 54 nursing and non-nursing staff working in 18 rural Primary Health centres and sub-centres around Baramati town of Pune district in Western India. Multivariable logistic regression models were constructed to assess
factors that influenced knowledge of rabies and practices towards management of dog-bite related wounds. The more experienced and better-educated workers were found to have a good awareness of rabies (OR 3.4, 95%CI 1.0–12.1) and good practices towards dog-bite wound management (OR 5.6, 95%CI 1.2–27.0). Surprisingly, non-nursing staff were significantly more knowledgeable about rabies (OR 3.5, 95%CI 1.0–12.3), but their practices towards dog-bite wound management were inadequate (OR 0.18, 95%CI 0.04–0.8) compared to the nursing staff. It is recommended that a mandatory training module for primary
care health staff be developed and implemented to improve their knowledge regarding rabies and management of dog-bite wounds to reduce the incidence of human rabies in
rural India
New policy directions for global pond conservation
Full text linkDespite the existence of well-established international environmental and nature conservation policies (e.g., the Ramsar Convention and Convention on Biological Diversity)
ponds are largely missing from national and international legislation and policy frameworks. Ponds are among the most biodiverse and ecologically important freshwater
habitats, and their value lies not only in individual ponds, but more importantly, in networks of ponds (pondscapes). Ponds make an important contribution to society through the ecosystem services they provide, with effective conservation of pondscapes essential to ensuring that these services are maintained. Implementation of current pond conservation through individual site designations does not function at
the landscape scale, where ponds contribute most to biodiversity. Conservation and management of pondscapes should complement current national and international
nature conservation and water policy/legislation, as pondscapes can provide species protection in landscapes where large-scale traditional conservation areas cannot be established (e.g., urban or agricultural landscapes). We propose practical steps for the effective incorporation or enhancement of ponds within five policy areas: through open water sustainable urban drainage systems in urban planning, increased incentives
in agrienvironment schemes, curriculum inclusion in education, emphasis on ecological scale in mitigation measures following anthropogenic developments, and
the inclusion of pondscapes in conservation policy