PG Thesis
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Item Comparative assessment of the spatial distribution and edaphic attributes of mangroves in Perumba and Puthuvype regions(Department of Forest Resource Management, College of Forestry, Vellanikkara, 2024-01-25) Rohan, M S.Mangroves are characterized by salt-tolerant vegetation thriving in tropical and subtropical coastlines. It provides critical ecological services and a source of livelihood for coastal communities. Globally, these crucial ecosystems are currently under threat due to the over-exploitation of natural resources. The mangroves in the state of Kerala have witnessed a drastic reduction in the area from seven hundred sq. km to a mere nine sq. km over the last five decades. Developmental activities and anthropogenic disturbances in the coastal areas are the major threats to these sensitive ecosystems. The knowledge of the extent of disturbance, the changes brought by the anthropogenic activities and their effect on the mangrove vegetation are the prerequisites for the sustainable management of these ecosystems. In this context, the present research work studied the extent of change in mangrove areas, variation in vegetation structures, soil and water properties among two contrasting regions namely, the Perumba river region with low and the Puthuvype region with high human disturbances. The Land Use Land Cover (LULC) classification for the current year has shown almost same percentage of mangroves to the total area in both the studied regions. In the present study, we used the three most widely used machine learning algorithms for the classification process. Among the machine learning algorithms studied, the Gradient Tree Boost (GTB) algorithm with a combination of Sentinel 1, 2 datasets and few spectral indices shown exemplary performance (88 % accuracy) in classifying mangrove areas. Change detection analysis showed a positive trend in mangrove cover in Perumba region (7.03 % increase) and contrarily a negative trend (66.51 % decrease) in the Puthuvype region during the study period (2013 - 2023). Phytosociological analysis figured out seven species belonging to four families in both Perumba and Puthuvype regions. The only difference in the species composition between the two regions is that Kandelia candel was found only in Perumba region, while it was replaced by Bruguiera gymnorhiza in the Puthuvype region. The common species present among these two regions were Avicennia officinalis, Bruguiera cylindrical, Excocaria agallocha, Rhizophora apiculate and Rhizophora mucronata. The Perumba region exhibits higher vegetation diversity indices when compared to the Puthuvype region. Perumba region exhibited higher seedling, tree, and sapling density, indicating a healthier mangrove ecosystem. In both regions, the majority of trees belong to the girth xii class of 20-30 cm. Further, Important Value Index (IVI) identified Avicennia officinalis as a dominant species followed by Rhizhophora mucronata in both the regions. Soil analysis showed a significant variation for chemical properties between the regions studied. Electrical conductivity, soil organic carbon, available nitrogen, available potassium, sodium, magnesium, lead, and chromium levels were recorded higher values in the Perumba region. Meanwhile, available phosphorus content was found higher in the Puthuvype region. In addition, biological properties viz, actinomycetes, bacteria, and fungi populations were higher in the Perumba region. Moreover, water analyses also revealed a maximum electrical conductivity, salinity and turbidity in the Perumba region. Altogether, the study showed a declining mangrove population in the Puthuvype region due to significant changes in the mangrove ecosystem brought by the intense anthropogenic interventions in the mangrove ecosystem, necessitating immediate action for the restoration of this fragile ecosystem.Item Biomass estimation of mumbai mangroves using optical and microwave satellite remote sensing(College of climate change and environmental science, Vellanikkara, 2023-12-07) Ashitha Venu,M.; Gnanappazham, LIn a changing climate condition, the ability to effectively quantify biomass becomes increasingly important in the context of climate change mitigation and adaptation strategies. This study is an attempt to estimate biomass of Mumbai mangroves and Bhitarkanika mangroves using Optical remote sensing and microwave remote sensing. For this study the ground data along with ORNL DAAC biomass data is used to form a model to compare the performance of both remote sensing platforms in estimating the biomass. In order to find these selected parameters were derived for Sentinel-1 and Sentinel-2 data. A total of 14 parameters were derived from them. For these parameters the relation with biomass was analyzed using linear regression, multiple linear regression, and stepwise regression. The analysis was done separately for the Sentinel-1 and Sentinel-2 parameters to compare their performance. From the linear regression, Normalised Difference Vegetation Index (NDVI) parameter derived from Sentinel-2 and Polarimetric Radar Vegetation Index (PRVI) parameter from Sentinel-1 showed relatively better relationship with biomass when compared to other parameters chosen. The Multiple linear regression indicates that the Sentinel-2 parameters are explaining the biomass variance better than the Sentinel-1 parameters. And the result implies that the Sentinel-1 parameters show poor relationship to explain variance in biomass of mangroves. The biomass map for both regions was generated based on the R2 value of stepwise regression. A comparative analysis was conducted for the Sentinel-1 and Sentinel-2 dataset by creating scatterplot between the parameters derived from them. Also analyzed the difference in them for both mangroves and other vegetation. For mangroves, EVI (Enhanced Vegetation Index) and PRVI (Polarimetric Radar Vegetation Index) have relatively strong relationships with biomass. Whereas for other vegetation, CMVI (Combined Mangrove vegetation Index) and DOP (Degree of Polarization) show similarly strong associations with biomass. Keywords: Mangroves, NDVI, PRVI, EVI, CMVI, ORNL DAACItem Modelling and prediction of the impact of climate change on blue carbon ecosystem services provided by tropical mangroves , east coast of India(College of Climate Change and Environmental Science,Vellanikkara, 2023-11-30) Sreelekshmi, M; Mangrove deforestation by land use conversions is the greatest threat to the conservation of coastal ecosystem. Here, the aim of this study is to predict the changes in mangrove regulatory services in Bapatla district Andhra Pradesh. Also estimate the carbon stock of planted and natural mangroves in the study area. Core of this study is Modelling and evaluation of spatial-temporal changes in blue carbon stocks and net sequestration potential in mangrove forests in Bapatla Landscape Andhra Pradesh, from 1993 to 2050. InVEST Coastal Blue Carbon model, which quantifies the potential carbon sequesteredin the study area based on changes in the land use and land cover. Also estimate the economic value of coastal blue carbon in Bapatla mangroves by analysing the changes in carbon storage that have taken place over 57 years. Field studies reveals that carbonstock in soil and biomass were high in natural mangroves as compared to planted mangroves. There is an increased trend in carbon stocks and net sequestration of mangroves. Over all net carbon sequestration was approximately 1.42 Mt C over a period from 1993 to 2050. The future projection by InVEST model reveals that there was a net increase on the carbon sequestration (0.83 Mt C from 2022) as a business-as- usual scenario. The monetary value of CBCS was subject to gains of between US$ 300000 and 1550000 per year, and losses of between US$ 40000 and 206666 per year, according to recent estimates by social cost of carbon (SCC). In spite of loss of mangrove vegetation over Krishna delta due to coastal erosion, deforestation, decline and aquaculture encroachments, several mangrove- restoration projects taken up during 1991–2008 led to an overall increase in its area. This study only considers about the regulatory services provided by mangroves. This finding can support the development of public policies for mangrove conservationand restoration actions to mitigate climate impact. Key words : Coastal blue carbon, Land use/Land cover, Mangrove, InVEST modelMangrove deforestation by land use conversions is the greatest threat to the conservation of coastal ecosystem. Here, the aim of this study is to predict the changes in mangrove regulatory services in Bapatla district Andhra Pradesh. Also estimate the carbon stock of planted and natural mangroves in the study area. Core of this study is Modelling and evaluation of spatial-temporal changes in blue carbon stocks and net sequestration potential in mangrove forests in Bapatla Landscape Andhra Pradesh, from 1993 to 2050. InVEST Coastal Blue Carbon model, which quantifies the potential carbon sequesteredin the study area based on changes in the land use and land cover. Also estimate the economic value of coastal blue carbon in Bapatla mangroves by analysing the changes in carbon storage that have taken place over 57 years. Field studies reveals that carbonstock in soil and biomass were high in natural mangroves as compared to planted mangroves. There is an increased trend in carbon stocks and net sequestration of mangroves. Over all net carbon sequestration was approximately 1.42 Mt C over a period from 1993 to 2050. The future projection by InVEST model reveals that there was a net increase on the carbon sequestration (0.83 Mt C from 2022) as a business-as- usual scenario. The monetary value of CBCS was subject to gains of between US$ 300000 and 1550000 per year, and losses of between US$ 40000 and 206666 per year, according to recent estimates by social cost of carbon (SCC). In spite of loss of mangrove vegetation over Krishna delta due to coastal erosion, deforestation, decline and aquaculture encroachments, several mangrove- restoration projects taken up during 1991–2008 led to an overall increase in its area. This study only considers about the regulatory services provided by mangroves. This finding can support the development of public policies for mangrove conservationand restoration actions to mitigate climate impact. Key words : Coastal blue carbon, Land use/Land cover, Mangrove, InVEST modelItem Spatial variation of carbon stocks and its turnover in the mangrove systems of Kerala(College of Climate Change and Environmental Science ,Vellanikkara, 2023-12-07) Aryadevi, J S.; Sandeep, SA study of 625 individuals from six mangrove species in Kerala found that A. marina dominates the mangrove forest, accounting for 38% of the tree count. Other species include A. officinalis, R. mucronata, B. cylindrica, R. apiculata, and S. alba. The northern zone has the highest diversity value and lowest Simpson index value. The total AGB of six mangrove species in Kerala is 1852.42 t ha-1, with the northern zone having the highest biomass at 827.73 t ha-1. R. mucronata has the highest AGB in the northern zone, followed by A. marina in the southern zone. Avicennia species dominate over half of the basal area. The study also found that soil bulk density increased with soil depth, with the lowest value in the northern zone and the highest in the southern zone. The pH levels in mangrove habitats vary, with the central zone having the highest pH (7.62). Organic carbon content varies among soil profiles, with the top soil in the central zone having the highest organic C level (2.05%). Estimated total organic C stock is 434±60.99 t ha-1, with the north zone having the largest deposit (181.96±16.14 t ha-1). The amount recorded in the southern zone is the lowest (111.93±18.06 t ha-1). Future predictions show that, temperature and rainfall significantly impact mangrove growth and productivity in Kerala over a 27-year period. Temperature rises by 0.74°C and rainfall increases by 13.63%, with temperature having the greatest influence in DNDC modelling. From 2022 to 2050, SOC is expected to increase at a rate of 0.3 to 1% per year, with an increase of 0.4% from 2022 to 2030 and 0.25% from 2030 to 2040 and 2040 to 2050. Temperature and precipitation positively correlate with SOC, with higher temperatures and rainfall increasing soil carbon mineralization and lowering SCS. Tree C in mangroves is experiencing a 0.2% decline annually, with no effect from RCP 4.5. The study shows a decline in GPP from 2022-2050, due to increased atmospheric CO2 concentrations. The trend towards reducing tree respiration is increasing, with a 0.04% increase expected between 2040-2050. Climate change is predicted to positively impact SCS by 2050, but its severity is concerning, as rising temperatures and precipitation pose risks to mangrove ecosystems' future. Key words: Mangrove, SOC, DNDC modellingItem Weed dynamics in acid saline pokkali ecosystem(Department of Agronomy, College of Horticulture, Vellanikkara, 2018) Jeen Shaji; Deepa ThomasPokkali is a unique and sustainable rice farming system in coastal saline soils of Kerala, where rice - prawn rotational system is the traditional system followed. Pokkali system though unique in the world, is vanishing due to many practical problems and socio - economic constraints. The weed flora of Pokkali rice fields is different from that of other rice ecosystems. Weeds survive and dominate in Pokkali ecosystem by developing morphological and anatomical adaptive mechanisms. Aquatic and semi aquatic weeds occur during the crop season and get dried up and decay in the off-season (high saline phase). Hence no weed management practices are taken up during the period of crop production. With time, deviations in soil fertility status and variations in many other climatic factors like mean rainfall and number of rainy days have been observed. As a result, the weed spectrum has also undergone changes. However, not many studies have been conducted on the weed spectrum or contributing factors to weed shifts in Pokkali areas. The present study entitled “Weed dynamics in acid saline Pokkali ecosystem” was conducted in three parts. The first part was survey in the five major Pokkali growing areas in Ernakulum and Alappuzha districts viz., Paravur, Palluruthy, Vypin, Kalamassery and Pattanakad blocks. Two panchayaths from each block were selected for surveying. The predominant weeds reported in the Pokkali ecosystem were Diplachne fusca and Eleocharis dulcis. A total of 36 weeds were identified from Pokkali ecosystem during low saline phase and that included the weed flora in the actual rice fields, bunds and water channels. The newly reported weeds of the ecosystem include Rhizophora mangle, Hygroryza aristata, Hydrilla verticillata, Najas graminea, Fuirena umbellata, Schoenoplectus lateriflorus, Hygrophila schulli, Cleome burmanii, Ipomoea sp., Digitaria sanguinalis, Lindernia sp., Sesbania sp., Pennisetum clandestinum, Cyperus exaltatus, C. javanicus, Achrostichum aureum, and Exoecaria agallocha. Echinochloa cruss-galli, a dominant weed reported in earlier weed surveys has now confined to a very few locations only and the frequency has now reduced from 80 per cent to 12.5 per cent When weeds in the field alone were considered, Vypin block was found to have highest species richness (S) and diversity index (H). Similarity coefficients between the blocks indicated that Pattanakad and Kalamassery blocks were highly similar, followed by Vypin and Paravur blocks. When total weeds in the ecosystem were considered, Palluruthy block was seen to have highest species richness and diversity indices. The second part was a pot culture study of three predominant weeds found during the survey. Experimental design was CRD with three dominant weeds at two salinity levels. Presence of micro-hairs and higher K+ / Na+ ratio were the tolerance mechanisms observed in D. fusca. For E. dulcis and S. zeylanica, higher K+ / Na+ ratio and presence of more aerenchymatous voids were observed. The third part was the field study to assess the extent of crop loss due to weed infestation in Pokkali system. Factorial RBD was the experimental design used with two rice varieties (Vyttila -6 and Chettivirippu) and three weed management practices (unweeded control, weeding at 20 DAT and weed free condition) as the two factors. From the biometric characters recorded it was observed that the plant height and tiller number per m2 were found significantly higher in weed free conditions. Yield attributes like panicles per m2 and grains per panicle were also found significantly higher in weed free plot. Grain yield in weed free treatment had 19 per cent yield advantage over the unweeded control check. However the increase in yield of weed free treatment over single weeding was only 4 per cent. The highest benefit - cost ratio was recorded in weed free treatments of both varieties. However, the ratio of single weeded treatment was found comparable with the weed free treatment. Thus, it can be concluded that a single weeding at 20 DAT is an inevitable practice which can be recommended to farmers for better returns