MSc

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.