15 resultados para Chinese Vegetation

em Indian Institute of Science - Bangalore - Índia


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A permanent 2 ha (200 m x 100 m) plot was established for long-term monitoring of plant diversity and dynamics in a tropical dry deciduous forest of Bhadra Wildlife Sanctuary, Karnataka, southern India. Enumeration of all woody plants >= 1 cm DBH (diameter at breast height) yielded a total of 1766 individuals that belonged to 46 species, 37 genera and 24 families. Combretaceae was the most abundant family in the forest with a family importance value of 68.3. Plant density varied from 20 - 90 individuals with an average 35 individuals/quadrat (20 m x 20 m). Randia dumetorum, with 466 individuals (representing 26.7 % of the total density 2 ha(-1)) with species importance value of 36.25, was the dominant species in the plot. The total basal area of the plot was 18.09 m(2) ha(-1) with a mean of 0.72 m(2) quadrat(-1). The highest basal area of the plot was contributed by Combretaceae (12.93 m(2) 2 ha(-1)) at family level and Terminalia tomentosa (5.58 m(2) 2 ha(-1)) at species level. The lowest diameter class (1-10 cm) had the highest density (1054 individuals 2 ha(-1)), but basal area was highest in the 80 - 90 cm diameter class (5.03m(2) 2 ha(-1)). Most of the species exhibited random or aggregated distribution over the plot. This study provides a baseline information on the dry forests of Bhadra Wildlife Sanctuary.

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Vegetated coastal ecosystems provide goods and services to billions of people. In the aftermath of a series of recent natural disasters, including the Indian Ocean Tsunami, Hurricane Katrina and Cyclone Nargis, coastal vegetation has been widely promoted for the purpose of reducing the impact of large storm surges and tsunami. In this paper, we review the use of coastal vegetation as a "bioshield" against these extreme events. Our objective is to alter bioshield policy and reduce the long-term negative consequences for biodiversity and human capital. We begin with an overview of the scientific literature, in particular focusing on studies published since the Indian Ocean Tsunami in 2004 and discuss the science of wave attenuation by vegetation. We then explore case studies from the Indian subcontinent and evaluate the detrimental impacts bioshield plantations can have upon native ecosystems, drawing a distinction between coastal restoration and the introduction of exotic species in inappropriate locations. Finally, we place bioshield policies into a political context, and outline a new direction for coastal vegetation policy and research.

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Vegetated coastal ecosystems provide goods and services to billions of people.In the aftermath of a series of recent natural disasters, including the Indian Ocean Tsunami, Hurricane Katrina and Cyclone Nargis, coastal vegetation has been widely promoted for the purpose of reducing the impact of large storm surges and tsunami. In this paper, we review the use of coastal vegetation as a ``bioshield'' against these extreme events. Our objective is to alter bioshield policy and reduce the long-term negative consequences for biodiversity and human capital. We begin with an overview of the scientific literature, in particular focusing on studies published since the Indian Ocean Tsunami in 2004 and discuss the science of wave attenuation by vegetation. We then explore case studies from the Indian subcontinent and evaluate the detrimental impacts bioshield plantations can have upon native ecosystems, drawing a distinction between coastal restoration and the introduction of exotic species in inappropriate locations. Finally, we place bioshield policies into a political context, and outline a new direction for coastal vegetation policy and research.

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We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.

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As part of an international network of large plots to study tropical vegetation dynamics on a long-term basis, a 50-hectare permanent plot was set up during 1988-89 in the deciduous forests of Mudumalai, southern India. Within this plot 25,929 living woody plants (71 species) above 1 cm DBH (diameter at breast height) were identified, measured, tagged and mapped. Species abundances corresponded to the characteristic log-normal distribution. The four most abundant species (Kydia calycina, Lagerstroemia microcarpa, Terminalia crenulata and Helicteres isora) constituted nearly 56% of total stems, while seven species were represented by only one individual each in the plot. Variance/mean ratios of density showed most species to have clumped distributions. The population declined overall by 14% during the first two years, largely due to elephant and fire-mediated damage to Kydia calycina and Helicteres isora. In this article we discuss the need for large plots to study vegetation dynamics.

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1. Recovery of rainforest bird community structure and composition, in relation to forest succession after slash-and-burn shifting cultivation or jhum was studied in Mizoram, north-east India. Replicate fallow sites abandoned after shifting cultivation 1, 5, 10, 25 and approximate to 100 years ago, were compared with primary evergreen and semi-evergreen forest using transect and quadrat sampling. 2. Vegetation variables such as woody plant species richness, tree density and vertical stratification increased with fallow age in a rapid. nun-linear, asymptotic manner. Principal components analysis of vegetation variables summarized 92.8% of the variation into two axes: PC1 reflecting forest development and woody plant succession (variables such as tree density, woody plant species richness), and PC2 depicting bamboo density, which increased from 1 to 25 years and declined thereafter. 3. Bird species richness, abundance and diversity, increased rapidly and asymptotically during succession paralleling vegetation recovery as shown by positive correlations with fallow age and PC1 scores of sites. Bamboo density reflected by PC2 had a negative effect on bird species richness and abundance. 4. The bird community similarity (Morisita index) of sites with primary forest also increased asymptotically with fallow age indicating sequential species turnover during succession. Bird community similarity of sites with primary forest (or between sites) was positively correlated with both physiognomic and floristic similarities with primary forest (or between sites). 5. The number of bird species in guilds associated with forest development and woody plants (canopy insectivores, frugivores: bark feeders) was correlated with PCI scores of the sites. Species in other guilds (e. g. granivores, understorey insectivores) appeared to dominate during early and mid-succession. 6. The non-linear relationships imply that fallow periods less than a threshold of 25 years for birds, and about 50-75 years for woody plants, are likely to cause substantial community alteration. 7. As 5-10-year rotation periods or jhum cycles prevail in many parts of north-east India. there is a need to protect and conserve tracts of late-successional and primary forest.

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Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years, and natural forests have declined.

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Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

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This study in Western Ghats, India, investigates the relation between nesting sites of ants and a single remotely sensed variable: the Normalised Difference Vegetation Index (NDVI). We carried out sampling in 60 plots each measuring 30 x 30 m and recorded nest sites of 13 ant species. We found that NDVI values at the nesting sites varied considerably between individual species and also between the six functional groups the ants belong to. The functional groups Cryptic Species, Tropical Climate Specialists and Specialist Predators were present in regions with high NDVI whereas Hot Climate Specialists and Opportunists were found in sites with low NDVI. As expected we found that low NDVI values were associated with scrub jungles and high NDVI values with evergreen forests. Interestingly, we found that Pachycondyla rufipes, an ant species found only in deciduous and evergreen forests, established nests only in sites with low NDVI (range = 0.015 - 0.1779). Our results show that these low NDVI values in deciduous and evergreen forests correspond to canopy gaps in otherwise closed deciduous and evergreen forests. Subsequent fieldwork confirmed the observed high prevalence of P. rufipes in these NDVI-constrained areas. We discuss the value of using NDVI for the remote detection and distinction of ant nest sites.

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A terrestrial biosphere model with dynamic vegetation capability, Integrated Biosphere Simulator (IBIS2), coupled to the NCAR Community Atmosphere Model (CAM2) is used to investigate the multiple climate-forest equilibrium states of the climate system. A 1000-year control simulation and another 1000-year land cover change simulation that consisted of global deforestation for 100 years followed by re-growth of forests for the subsequent 900 years were performed. After several centuries of interactive climate-vegetation dynamics, the land cover change simulation converged to essentially the same climate state as the control simulation. However, the climate system takes about a millennium to reach the control forest state. In the absence of deep ocean feedbacks in our model, the millennial time scale for converging to the original climate state is dictated by long time scales of the vegetation dynamics in the northern high latitudes. Our idealized modeling study suggests that the equilibrium state reached after complete global deforestation followed by re-growth of forests is unlikely to be distinguishable from the control climate. The real world, however, could have multiple climate-forest states since our modeling study is unlikely to have represented all the essential ecological processes (e. g. altered fire regimes, seed sources and seedling establishment dynamics) for the reestablishment of major biomes.

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We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

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The proportion of chemical elements passing through vegetation prior to being exported in a stream was quantified for a forested tropical watershed(Mule Hole, South India) using an extensive hydrological and geochemical monitoring at several scales. First, a solute annual mass balance was established at the scale of the soil-plant profile for assessing the contribution of canopy interaction and litter decay to the solute fluxes of soil inputs (overland flow) and soil outputs (pore water flow as seepages). Second, based on the respective contributions of overland flow and seepages to the stream flow as estimated by a hydrological lumped model, we assigned the proportion of chemical elements in the stream that transited through the vegetation at both flood event (End Member Mixing Analysis) and seasonal scales. At the scale of the 1D soil-plant profile, leaching from the canopy constituted the main source of K above the ground surface. Litter decay was the main source of Si, whereas alkalinity, Ca and Mg originated in the same proportions from both sources. The contribution of vegetation was negligible for Na. Within the soil, all elements but Na were removed from the pore water in proportions varying from 20% for Cl to 95% for K: The soil output fluxes corresponded to a residual fraction of the infiltration fluxes. The behavior of K, Cl, Ca and Mg in the soil-plant profile can be explained by internal cycling, as their soil output fluxes were similar to the atmospheric inputs. Na was released from soils as a result of Na-plagioclase weathering and accompanied by additional release of Si. Concentration of soil pore water by evapotranspiration might limit the chemical weathering in the soil. Overall, the solute K, Ca, Mg, alkalinity and Si fluxes associated with the vegetation turnover within the small experimental watershed represented 10-15 times the solute fluxes exported by the stream, of which 83-97% transited through the vegetation. One important finding is that alkalinity and Si fluxes at the outlet were not linked to the ``current weathering'' of silicates in this watershed. These results highlight the dual effect of the vegetation cover on the solute fluxes exported from the watershed: On one hand the runoff was limited by evapotranspiration and represented only 10% of the annual rainfall, while on the other hand, 80-90% of the overall solute flux exported by the stream transited through the vegetation. The approach combining geochemical monitoring and accurate knowledge of the watershed hydrological budget provided detailed understanding of several effects of vegetation on stream fluxes: (1) evapotranspiration (limiting), (2) vertical transfer through vegetation from vadose zone to ground surface (enhancing) and (3) redistribution by throughfalls and litter decay. It provides a good basis for calibrating geochemical models and more precisely assessing the role of vegetation on soil processes. (C) 2014 Elsevier Ltd. All rights reserved.

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Despite high vulnerability, the impact of climate change on Himalayan ecosystem has not been properly investigated, primarily due to the inadequacy of observed data and the complex topography. In this study, we mapped the current vegetation distribution in Kashmir Himalayas from NOAA AVHRR and projected it under A1B SRES, RCP-4.5 and RCP-8.5 climate scenarios using the vegetation dynamics model-IBIS at a spatial resolution of 0.5A degrees. The distribution of vegetation under the changing climate was simulated for the 21st century. Climate change projections from the PRECIS experiment using the HADRM3 model, for the Kashmir region, were validated using the observed climate data from two observatories. Both the observed as well as the projected climate data showed statistically significant trends. IBIS was validated for Kashmir Himalayas by comparing the simulated vegetation distribution with the observed distribution. The baseline simulated scenario of vegetation (1960-1990), showed 87.15 % agreement with the observed vegetation distribution, thereby increasing the credibility of the projected vegetation distribution under the changing climate over the region. According to the model projections, grasslands and tropical deciduous forests in the region would be severely affected while as savannah, shrubland, temperate evergreen broadleaf forest, boreal evergreen forest and mixed forest types would colonize the area currently under the cold desert/rock/ice land cover types. The model predicted that a substantial area of land, presently under the permanent snow and ice cover, would disappear by the end of the century which might severely impact stream flows, agriculture productivity and biodiversity in the region.

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In the present paper, we present the structure and composition of tropical evergreen and deciduous forests in the Western Ghats monitored under a long-term programme involving Indian Institute of Science, Earthwatch and volunteer investigators from HSBC. Currently, there is limited evidence on the status and dynamics of tropical forests in the context of human disturbance and climate change. Observations made in this study show that the `more disturbed' evergreen and one of the deciduous plots have low species diversity compared to the less-disturbed forests. There are also variations in the size class structure in the more and `less disturbed' forests of all the locations. The variation is particularly noticeable in the DBH size class 10 - 15 cm category. When biomass stock estimates are considered, there was no significant difference between evergreen and deciduous forests. The difference in biomass stocks between `less disturbed' and `more disturbed' forests within a forest type is also low. Thus, the biomass and carbon stock has not been impacted despite the dependence of communities on the forests. Periodic and long-term monitoring of the status and dynamics of the forests is necessary in the context of potential increased human pressure and climate change. There is, therefore, a need to inform the communities of the impact of extraction and its effect on regeneration so as to motivate them to adopt what may be termed as ``adaptive resource management'', so as to sustain the flow of forest products.

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The non-availability of high-spatial-resolution thermal data from satellites on a consistent basis led to the development of different models for sharpening coarse-spatial-resolution thermal data. Thermal sharpening models that are based on the relationship between land-surface temperature (LST) and a vegetation index (VI) such as the normalized difference vegetation index (NDVI) or fraction vegetation cover (FVC) have gained much attention due to their simplicity, physical basis, and operational capability. However, there are hardly any studies in the literature examining comprehensively various VIs apart from NDVI and FVC, which may be better suited for thermal sharpening over agricultural and natural landscapes. The aim of this study is to compare the relative performance of five different VIs, namely NDVI, FVC, the normalized difference water index (NDWI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI), for thermal sharpening using the DisTrad thermal sharpening model over agricultural and natural landscapes in India. Multi-temporal LST data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors obtained over two different agro-climatic grids in India were disaggregated from 960 m to 120 m spatial resolution. The sharpened LST was compared with the reference LST estimated from the Landsat data at 120 m spatial resolution. In addition to this, MODIS LST was disaggregated from 960 m to 480 m and compared with ground measurements at five sites in India. It was found that NDVI and FVC performed better only under wet conditions, whereas under drier conditions, the performance of NDWI was superior to other indices and produced accurate results. SAVI and MSAVI always produced poorer results compared with NDVI/FVC and NDWI for wet and dry cases, respectively.