ID: 66735
Title: IISc_EIACP: Environmental Information, Awareness,Capacity Building and Livelihood Programme (EIACP)
Author: T.V. Ramachandra
Editor: T.V. Ramachandra
Year: 2026
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: IISc_EIACP: Environmental Information, Awareness,Capacity Building and Livelihood Programme (EIACP) Pg no 1-43
Subject: IISc_EIACP: Environmental Information, Awareness,Capacity Building and Livelihood Programme (EIACP)
Keywords: None
Abstract: IISc_EIACP: Environmental Information, Awareness,
Capacity Building and Livelihood Programme (EIACP)
Thematic Programme Centre on Western Ghats Biodiversity and Ecology
Location: T E 15 New Biology building
Literature cited 1:
Literature cited 2:
ID: 66734
Title: Sustainable Biohydrogen Production From Agricultural Residues Potential, Processes, and Environmental Impact
Author: TV Ramachandra and Niyam Dave
Editor: T.V. Ramachandra
Year: 2024
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Sustainable Biohydrogen
Production From Agricultural Residues
Potential, Processes, and Environmental
Impact Pg no 1-4
Subject: Sustainable Biohydrogen Production From Agricultural Residues Potential, Processes, and Environmental Impact
Keywords: None
Abstract: Burgeoning demand for conventional
energy and associated environmental
impacts, coupled with the dwindling
fossil fuel stocks, has led to exploration
for sustainable energy alternatives
like solar, wind, biofuels, etc. India has
witnessed significant economic growth
with enhanced reliance on fossil fuels
during the 1990s due to globalization.
However, escalating fossil fuel import
dependence and escalating greenhouse
gas footprint have necessitated an
exploration of viable energy alternatives.
Location: T E 15 New Biology building
Literature cited 1: Ahlström, J. M., 2021. Renewable
Hydrogen Production from
Biomass, Bioenergy Position Pap.
Reports, pp. 1–25, 2021, https://
www.etipbioenergy.eu/images/
Renewable_Hydrogen_Production_
from_Biomass.
Wang J and Yin, Y, 2021.Clostridium
species for fermentative hydrogen
production: An overview,” Int.
J. Hydrogen Energy, vol. 46, no.
70, pp. 34599–34625, 2021, doi:
10.1016/j.ijhydene.2021.08.052.
Literature cited 2: Abdeshahian P, Najeeb Kaid Nasser
Al-Shorgani, Noura K.M. Salih,
Hafiza Shukor, Abudukeremu
Kadier, Aidil Abdul Hamid,
Mohd Sahaid Kalil, 2014. The
production of biohydrogen by a
novel strain Clostridium sp. YM1
in dark fermentation process, Int.
J. Hydrogen Energy, vol. 39, no.
24, pp. 12524–12531, 2014, doi:
10.1016/j.ijhydene.2014.05.081.
Meena H. N., Singh S. K., Meena
M. S., Narayan R., and Sen B.,
2022. Crop residue: waste or
wealth?, Tech. Bull., pp. 1–30,
http://krishi.icar.gov.in/jspui/
handle/123456789/71699
ID: 66733
Title: Soil environmental health linkages with the landscape structure in Raichur district, Karnataka, India
Author: T. V. Ramachandra and Paras Negi
Editor: None
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Soil environmental health linkages
with the landscape structure in Raichur district, Karnataka, India Pg no. 1-25
Subject: Soil environmental health linkages with the landscape structure in Raichur district, Karnataka, India
Keywords: None
Abstract: Appraisal of land use (LU) dynamics through time-series remote sensing data offers
valuable insights into the extent and condition of a landscape, which is essential
for the sustainable management of natural resources. Integrated spatial analyses
of LU with social, ecological, hydrological, bio-geo-climatic, and environmental
variables would aid in the prioritization of natural resources-rich regions (NRRRs).
The current study assesses the LU changes in an agrarian district using temporal
remote sensing data through a supervised machine learning technique- Random
Forest (RF) in the Google Earth Engine platform (GEE) with access to a multi-petabyte
catalog of satellite imagery and geospatial datasets, enabling efficient processing
and analysis. Paddy cultivation spatial extent has increased from 0.74% (1973) to
18.41% (2024), with the increase in the extent of water bodies due to the Krishna and
Tungabhadra Rivers. The simulated LU using Cellular Automata reveals that the area
under agriculture will decrease to 1159.33 sq. km, and a significant increase in road
network and industrial area is expected by 2038. The consequence of LU changes
on soil health, evident from declining nutrients, necessitates the identification of
natural resources-rich regions (NRRRs) for formulating effective policies for prudent
management of natural resources to achieve sustainable development goals (SDGs
especially SDG 1, 2, 6, 11, 12, 13, and 15) by exploring all feasible dimensions and
analyzing the patterns and dynamics across various interdisciplinary themes such as
social, hydrological, ecological and bio-geo-climatic. The study reveals that 15% of
the total geographical area of the district is rich in natural resources (NRRR 1 and 2),
which requires prudent management to sustain natural resources.
Location: T E 15 New Biology building
Literature cited 1: Forman RT. Some general principles of landscape and regional ecology. Landscape Ecol. 1995;10(3):133–42. https://doi.or
g/10.1007/BF00133027.
2. Pan D, Domon G, De Blois S, Bouchard A. Temporal (1958–1993) and spatial patterns of land use changes in Haut-SaintLaurent
(Quebec,
Canada)
and their relation
to
landscape physical
attributes.
Landscape Ecol.
1999;14:35–52. https://doi.o
rg/10.1023/A:1008022028804.
Literature cited 2: Bharath S, Rajan KS, Ramachandra TV. Land surface temperature responses to land use land cover dynamics. Geoinfor
Geostat Overview. 2013;54:50–78.
Foody GM. Remote sensing of tropical forest environments: towards the monitoring of environmental resources for
sustainable development. Int J Remote Sens. 2003;24(20):4035–46. https://doi.org/10.1080/0143116031000103853.
ID: 66732
Title: Land Surface Temperature Responses to Landscape Structure Dynamics in Trans-Gangetic Plain Region
Author: T V Ramachandra , Rajesh Singh Rana and Bharath H Aithal
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Land Surface Temperature Responses to Landscape Structure Dynamics in Trans-Gangetic Plain Region Pg no. 1-17
Subject: Land Surface Temperature Responses to Landscape Structure Dynamics in Trans-Gangetic Plain Region
Keywords: Landscape Dynamics, Land Surface Temperature, Machine Learning, Random Forest Classifier.
Abstract: Global patterns of Land Use and Land Cover (LULC) have undergone signif icant changes due to the
continuous conversion of natural landscapes into settings controlled by humans. The primary drivers for
converting natural landscapes (vegetation, water bodies, open space, etc.) into artif icial ones are
unplanned developmental activities leading to land degradation and deforestation with rapid
urbanization, intense agriculture, inf rastructural development, etc. The surface properties of the Earth
are signif icantly altered by anthropogenic activities, with a reduction in the porous surfaces and an
increase in paved surfaces, which alters the capacity of a landscape to percolate water, retain moisture,
retain thermal heat, evapotranspiration rates, albedo, etc., resulting in the changes in the local and
regional climate patterns. The current study investigates the interplay of land use changes with land
surface temperature (LST) in the trans-Gangetic Plain agroclimatic zone region of India. Temporal
land use analyses for 2001 to 2022, using MODIS remote sensing data, classif ied through machine
learning non-parametric supervised classif ier Random Forest (RF) suitable for heterogeneous
landscapes reveal that agriculture is the dominant land use class and rapid expansion of paved surfaces
(built-up etc.) in Land surface temperature (LST) computed for 2001 to 2022, reveals increasing LST
with the expansion of paved surfaces and negatively correlated with the higher NDVI (corresponding to
the vegetation cover).
Location: T E 15 New Biology building
Literature cited 1: Adams, L. W. (1994). Urban wildlife habitats: a landscape
perspective (3). U of Minnesota Press.
Amini Parsa, V., Yavari, A., & Nejadi, A. (2016). Spatiotemporal
analysis
of
land
use/land
cover
pattern
changes
in
Arasbaran Biosphere Reserve: Iran. Modeling earth
systems and environment, 2, 1-13.
Literature cited 2: Buya, S., Chuangchang, P., & Owusu, B. A. (2022).
Analysis of land surface temperature with land use and
land cover and elevation f rom NASA MODIS satellite
data: a case study of Bali, Indonesia. Environmental
Monitoring and Assessment, 194(8), 566.
Edan, M. H., Maarouf, R. M., & Hasson, J. (2021).
Predicting the impacts of land use/land cover change on
land surface temperature using remote sensing approach
in Al Kut, Iraq. Physics and Chemistry of the Earth, Parts
A/B/C, 123, 103012.
ID: 66731
Title: Biomonitoring of urban lakes through microalgae
Author: Asulabha K.S. , Sincy V. , Jaishanker R. and Ramachandra T.V
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Biomonitoring of urban lakes through microalgae Pg no.
Subject: Biomonitoring of urban lakes through microalgae
Keywords: None
Abstract: Biomonitoring entails monitoring the quality of an ecosystem through representative biota, which responds
to environmental changes through alterations in morphological, physiological, biochemical, molecular,
and genetic traits. The sustained inflow of untreated wastewater due to point and non-point sources has
been putting significant strain on aquatic ecosystems, leading to a decline in aquatic biodiversity, the loss
of vital habitats for sensitive biota, and consequent erosion in ecosystem services. Microalgae constitute the
primary producers in aquatic ecosystems and serve as pollution indicators as they respond to changes in
water quality. This necessitates an understanding of microalgae dynamics in relation to environmental
factors for prudent management of aquatic resources. The study examines microalgal composition and
water quality in Sankey and Mathikere lakes, Bangalore, revealing pollution from untreated wastewater in
Mathikere Lake, which exhibits high physicochemical parameters. The microalgae composition in both
lakes varied in response to the water quality and across seasons. Multivariate analyses through nonparametric
canonical correspondence analysis (CCA) demonstrate linkages between microalgal composition
and
water quality parameters in both lakes. Nutrient enrichment leading to eutrophic conditions with the
profuse
growth of invasive exotic macrophytes has declined microalgal diversity, suggesting immediate
interventions
to mitigate pollutants to improve the chemical integrity of waterbodies.
Location: T E 15 New Biology building
Literature cited 1: Algae Base. 2021. Available at: https://
www.algaebase.org/
Amaro, H.M., Sousa, J.F., Salgado, E.M., Pires, J.C. and
Nunes, O.C. 2023. Microalgal systems, a green solution
for wastewater conventional pollutants removal,
disinfection, and reduction of antibiotic resistance
genes prevalence? Applied
Sciences.
13(7):
4266
Literature cited 2: APHA, 2012. Standard Methods for the Examination of Water
and Wastewater, 22nd ed. American Public Health
Association/American Water Works Association/
Water Environment Federation: Washington, DC,
USA
Asulabha, K.S., Jaishanker, R., Sincy, V. and Ramachandra,
T.V. 2022. Diversity of phytoplankton in lakes of
Bangalore, Karnataka, India, p. 147-178. In:
Shashikanth Majige (Edited), Biodiversity Challenges:
A Way Forward, Daya Publishing House, New Delhi,
India
ID: 66730
Title: Geoinformatics‑based prioritisation of natural resources rich regions at disaggregated levels for sustainable management
Author: T. V. Ramachandra , Paras Negi
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Geoinformatics‑based prioritisation of natural resources rich regions
at disaggregated levels for sustainable management Pg no. 1-27
Subject: Geoinformatics‑based prioritisation of natural resources rich regions at disaggregated levels for sustainable management
Keywords: LULC change · Supervised learning · Machine learning · Random Forest · CA-Markov · Natural Resource Rich Regions (NRRRs)
Abstract: Natural Resource Rich Regions (NRRRs) are ecologically and economically vital regions that support the livelihood of
people through the sustained ecosystem process involving interaction among biotic and abiotic elements. Identifying
NRRRs, considering spatially ecological, geo-climatic, biological, and social dimensions, would help in conservation
planning and prudent management of natural resources as per the Biodiversity Act 2002, Government of India. Changes
in the landscape structure would lead to alterations in the composition and health of these regions with irreversible
changes in the ecosystem process, impacting the sustenance of natural resources. Landscape dynamics is assessed by
classifying temporal remote sensing data using the supervised machine learning (ML) technique based on the Random
Forest (RF) algorithm. Additionally, predicting likely land use changes in ecologically fragile areas would help formulate
appropriate location-speciic mitigation measures. Modeling likely land uses through the simulation of long-term spatial
variations of complex patterns has been done through the CA–Markov model. Prioritization of NRRRs at disaggregated
levels highlights that 12% of the total geographical area of the district is under NRRR 1 and NRRR 2, 54% of the total
geographical area under NRRR 3, and the rest of the region under NRRR 4. The current study emphasizes the need for
robust decision support systems to aid in efective policy formulation for conserving and restoring natural resources.
Clinical trial number: Not applicable.
Location: T E 15 New Biology building
Literature cited 1: Forman RT. Some general principles of landscape and regional ecology. Landsc Ecol. 1995;10(3):133–42. https://doi.org/10.1007/BF001
33027.
Ramachandra TV, Setturu B, Bhatta V. Landscape ecological modeling to identify ecologically signiicant regions in Tumkur district,
Karnataka. Phys Sci Rev. 2022. https://doi.org/10.1515/psr-2022-0154.
Literature cited 2: Matlhodi B, Kenabatho PK, Parida BP, Maphanyane JG. Evaluating land use and land cover change in the Gaborone dam catchment,
Botswana, from 1984–2015 using GIS and remote sensing. Sustainability. 2019;11(19):5174. https://doi.org/10.3390/su11195174.
Spruce J, Bolten J, Mohammed IN, Srinivasan R, Lakshmi V. Mapping land use land cover change in the Lower Mekong Basin from 1997
to 2010. Front Environ Sci. 2020;8:21. https://doi.org/10.3390/rs10121910.
ID: 66729
Title: Sustainable Management of Natural Resources at Disaggregated Levels with Insights from Landscape Dynamics
Author: T V Ramachandra , Paras Negi , Tulika Mondal , Bharath Setturu
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Sustainable Management of Natural Resources at Disaggregated Levels with
Insights from Landscape Dynamics Pg no 1-27
Subject: Sustainable Management of Natural Resources at Disaggregated Levels with Insights from Landscape Dynamics
Keywords: Natural Resource Rich Regions (NRRRs); arid regions, Land Use Land Cover (LULC); Machine Learning (ML); Random Forest (RF); landscape modelling.
Abstract: The burgeoning population, coupled with the resource demand and alterations in the climatic regime, have
been posing serious challenges for the sustenance of natural resources. Natural Resource Rich Regions
(NRRRs) are areas endowed with abundant natural resources, which maintain ecological balance and economic
activities.
Location: T E 15 New Biology building
Literature cited 1: Adugna, T., Xu, W., & Fan, J. (2022). Comparison of random forest and support vector machine classifiers for regional
land cover mapping using coarse resolution FY-3C images. Remote Sensing, 14(3), 574. doi: 10.3390/rs14030574
Ahmadi, K., Kalantar, B., Saeidi, V., Harandi, E. K., Janizadeh, S., & Ueda, N. (2020). Comparison of machine learning
methods for mapping the stand characteristics of temperate forests using multi-spectral sentinel-2 data. Remote
Sensing, 12(18), 3019. doi: 10.3390/rs12183019
Literature cited 2: Ali, K., & Johnson, B. A. (2022). Land-Use and Land-Cover Classification in Semi-arid Areas from Medium-Resolution
Remote-Sensing Imagery: A Deep Learning Approach. Sensors, 22(22), 8750. doi: 10.3390/s22228750
Ashok, A., Rani, H. P., & Jayakumar, K. V. (2021). Monitoring of dynamic wetland changes using NDVI and NDWI
based landsat imagery. Remote Sensing Applications: Society and Environment, 23, 100547. doi:
10.1016/j.rsase.2021.100547
ID: 66728
Title: Prioritization of natural resources rich regions (NRRZ) based on ecosystem (biotic and abiotic) extent and conditions
Author: T. V. Ramachandra · Bharath Setturu
Editor: T.V. Ramachandra
Year: 2026
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Prioritization of natural resources rich regions (NRRZ) based
on ecosystem (biotic and abiotic) extent and conditions Pg no. 1-36
Subject: Prioritization of natural resources rich regions (NRRZ) based on ecosystem (biotic and abiotic) extent and conditions
Keywords: Biodiversity · Ecosystem · Ecologically sensitive · Forest fragmentation · Karnataka state
Abstract: Ecosystems are distinct biological entities characterized by a range of functions. The integrity
of
the ecosystem
is
vital for
sustaining ecosystem
goods
and services
to
support
people’s
livelihood. Maintaining
ecosystem
integrity
requires
ecosystem
approaches
in
managing
natural
resources considering dynamics
due
to natural variabilities
and
anthropogenic
activities.
Sustainable
developmental
planning
focuses
on
the
efficient
and
innovative
use of regional resources, with an improved understanding of social and environmental
interactions.
The
comprehensive knowledge
of
a region’s
ecological
sensitivity/fragility
is
quintessential for evolving conservation strategies. Ecosystems’
ecological sensitivity
refers
to ecosystem stability,
persistence, resilience, and
recovery properties to overcome
environmental
disasters,
which are likely to affect natural landscapes’ character adversely.
The ecologically sensitive regions are natural resources-rich zones (NRRZ) endowed with
distinct biological elements with geological, physical, and chemical characteristics. Spatial
integration of geo-climatic, ecological, environmental, and social variables helps delineate
NRRZ for prudent management of natural resources through ecological and conservation
planning as per the Biodiversity Act, 2002, Government of India. NRRZ delineation has
been done at disaggregated levels (9 km x 9 km grids) considering ecological, bio-geoclimatic,
social, and environmental aspects compiled from field and published literature,
and prioritization of NRRZ (as NRRZ 1 to 4) has been done through aggregated weightage
metric
score (of chosen variables per
grid). The
novelty of
the current study is the
prioritization
of
NRRZ at disaggregated
levels
(grids
of 5’
x 5’
or 9
km
x 9
km,
equivalent
to
a
grid
in
1:50000
topographic
map
of
the
Survey
of
India)
and
also
the
decentralized
governance
unit-
Panchayat through
the integration of
diverse multi-dimensional bio-geoclimatic,
environmental
and social factors. The
strength of NRRZ is the replicability for
prudent
management
of
natural resources
and real-world conservation
governance.
32%
of
the state’s
geographical area
was
depicted as
a high-resource region
under
NRRZ 1 and
2,
which needs to be conserved with stringent regulations.
Prioritizing
regions
as NRRZ
by
integrating spatial data (land cover) with location-based attribute
information would
strengthen
regional
decision-making.
Location: T E 15 New Biology building
Literature cited 1: Anoop, P., & Suryaprakash, S. (2008). Estimating the option value of Ashtamudi Estuary in South India: A
contingent valuation approach. In 2008 International Congress, August 26-29, 2008, Ghent, Belgium
43607. European Association of Agricultural Economists. https://doi.org/10.22004/ag.econ.43607
Aragão, L., Adami, M., & Arai, E. (2017). Land use and land cover change analysis using NRZ mapping in
the Amazon rainforest. Remote Sensing of Environment, 198, 213–225.
Literature cited 2: Araya, A., Keesstra, S. D., & Stroosnijder, L. (2010). A new agro-climatic classification for crop suitability
zoning in Northern semi-arid Ethiopia. Agricultural and Forest Meteorology, 150(7–8), 1057–1064.
Barbier, E. B., Hacker, S. D., Kennedy, C., Koch, E. W., Stier, A. C., & Silliman, B. R. (2011). The value of
estuarine and coastal ecosystem services. Ecological Monographs, 81(2), 169–193.
ID: 66727
Title: Urban heat island linkages with the landscape morphology
Author: T. V. Ramachandra , Rajesh Singh Rana , S. Vinay & Bharath H. Aithal
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Urban heat island linkages with the
landscape morphology Pg no 1-16
Subject: Urban heat island linkages with the landscape morphology
Keywords: Landscape dynamics, Land surface temperature (LST), Urban heat island (UHI), Spatial interrelationship, Urban thermal field variance index (UTFVI)
Abstract: The landscape consists of a mosaic of interacting ecosystem elements, which maintain stability and
aid in sustaining crucial services. Unplanned developmental activities leading to the transition of
pervious surfaces into impervious/paved surfaces have significant implications for the urban climate,
mainly through the phenomenon of urban heat islands (UHIs). Changes in landscape integrity
could be quantified through land use (land cover) assessment and urban heat island effect through
spatial computation of land surface temperature (LST). The current research uses multi-resolution
remote sensing data to evaluate UHIs with landscape dynamics and assess the complex spatial
interrelationships in heterogeneous urban landscapes at micro-levels. The composition of pervious and
impervious surfaces at the micro-level plays a pivotal role in regulating thermal comfort. Landscape
configuration at microlevels, predominantly barren (C1 class) and urban (C2 class) areas, constitute
hotspots with higher temperatures. UHI was mapped through the urban hotspot and Urban thermal
field variance index (UTFVI) analysis. Urban hotspot analysis shows the 15.41 km
2
area in the city has
a very high temperature. The study provides vital data-driven insights into the complex relationship
between urban land use and LST at the micro-level that supports the decision-makers, stakeholders,
and public officials in policymaking.
Location: T E 15 New Biology building
Literature cited 1: Mallik, R. et al. Spatio-temporal analysis of environmental criticality: Planned versus unplanned urbanization. In IOP Conference
Series: Earth and Environmental Science 1164 (1), 012014 https://doi.org/10.1088/1755-1315/1164/1/012014 (IOP Publishing,
2023).
Ramachandra, T. V., Aithal, B. H. & Sanna, D. D. Insights to urban dynamics through landscape Spatial pattern analysis. Int. J. Appl.
Earth Obs. Geoinf. 18, 329–343. https://doi.org/10.1016/j.jag.2012.03.005 (2012).
Literature cited 2: Gupta, N. & Aithal, B. H. Urban land surface temperature forecasting: a data-driven approach using regression and neural network
models. Geocarto Int. 39 (1), 2299145. https://doi.org/10.1080/10106049.2023.2299145 (2024).
UN DESA. 2018 Revision of world urbanization prospects. (accessed 5 March 2025); https://population.un.org/wup/Publications
/Files/WUP2018-Report.pdf
ID: 66726
Title: Insights into the linkages of forest structure dynamics with ecosystem services
Author: T. V. Ramachandra , Paras Negi , Tulika Mondal & Syed Ashfaq Ahmed
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Insights into the linkages of forest structure dynamics with ecosystem services, Pg no. 1-21
Subject: Insights into the linkages of forest structure dynamics with ecosystem services
Keywords: Land use, Land cover, Land use change prediction, Agent-based modeling, Carbon sequestration, InVEST model, Ecosystem services, Ecologically sensitive regions (ESR), Western Ghats
Abstract: Large-scale land cover changes leading to land degradation and deforestation in fragile ecosystems
such as the Western Ghats have impaired ecosystem services, evident from the conversion of
perennial water bodies to seasonal, which necessitates an understanding of forest structure dynamics
with ecosystem services to evolve appropriate location-specific mitigation measures to arrest land
degradation. The current study evaluates the extent and condition of forest ecosystems in Goa of the
Central Western Ghats, a biodiversity hotspot. Land use dynamics is assessed through a supervised
hierarchical classifier based on the Random Forest Machine Learning Algorithm, revealing that
total forest cover declined by 3.75% during the post-1990s due to market forces associated with
globalization. Likely land uses predicated through the CA-Markov-based Analytic Hierarchy Process
(AHP) highlight a decline in evergreen forest cover of 10.98%. The carbon sequestration potential of
forests in Goa assessed through the InVEST model highlights the storage of 56,131.16 Gg of carbon,
which accounts for 373.47 billion INR (4.49 billion USD). The total ecosystem supply value (TESV) for
forest ecosystems was computed by aggregating the provisioning, regulating, and cultural services,
which accounts for 481.76 billion INR per year. TESV helps in accounting for the degradation cost
of ecosystems towards the development of green GDP (Gross Domestic Product). Prioritization of
Ecologically Sensitive Regions (ESR) considering bio-geo-climatic, ecological, and social characteristics
at disaggregated levels reveals that 54.41% of the region is highly sensitive (ESR1 and ESR2). The
outcome of the research offers invaluable insights for the formulation of strategic natural resource
management approaches.
Location: T E 15 New Biology building
Literature cited 1: Mooney, H. et al. Biodiversity, climate change, and ecosystem services. Curr. Opin. Environ. Sustain. 1 (1), 46–54. https://doi.org
/10.1016/j.cosust.2009.07.006 (2009).
2. Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity.
Ecol. Lett. 15 (4), 365–377. https://doi.org/10.1111/j.1461-0248.2011.01736.x (2012).
Literature cited 2: Muluneh, M. G. Impact of climate change on biodiversity and food security: a global perspective—a review Article. Agric. Food
Secur. 10 (1), 1–25. https://doi.org/10.1186/s40066-021-00318-5 (2021).
4. Prakash, S. Impact of climate change on aquatic ecosystem and its biodiversity: an overview. Int. J. Biol. Innovations. 3, 2. https://
doi.org/10.46505/IJBI.2021.3210 (2021).
ID: 66725
Title: Sahyadri E-NEWS 2025-26
Author: None
Editor: T.V. Ramachandra
Year: 2026
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Sahyadri E-NEWS 2025-26 , ETR 221, SCR 148 , Pg no 1-117
Subject: Sahyadri E-NEWS 2025-26
Keywords: None
Abstract: Ecology and natural history are thoroughly tangled with an organism's geographic distribution and spatial arrangement. Throughout the nineteenth century, attempts were made to characterize the distribution patterns by considering microclimatic factors like precipitation and temperature. In order to gain a comprehensive understanding of ecosystems, it is essential to delve into the complexities not only at levels below that of an ecosystem, such as individual organisms, but also at levels above it over a geographic space. This includes examining landscapes, ecoregions or biomes and extending to a global perspective. Such an approach is crucial for grasping ecosystems' detailed structure and functioning. The inadequate availability of historical and current information regarding the status and distribution of biotic diversity worldwide presents significant obstacles in comprehending global shifts in biodiversity. The current issue (Sahyadri E News, Issue LXL) offers a comprehensive overview of the biodiversity richness in Karnataka through documentation of the spatial distribution of species diversity within various genera.
Location: T E 15 New Biology building
Literature cited 1:
Literature cited 2:
ID: 66724
Title: Ecological Insights of Sharavathi River Basin, Central Western Ghats, Uttara Kannada and Shivamogga districts, Karnataka
Author: T V Ramachandra M D Subash Chandran Tulika Mondal Bharath Setturu Vinay S Bharath H Aithal
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Ecological Insights of Sharavathi river basin, Central Western Ghats, Uttara Kannada and Shivamogga districts, Karnataka, ETR 213, SCR 141, 2025
Subject: Ecological Insights of Sharavathi river basin, Central Western Ghats, Uttara Kannada and Shivamogga districts, Karnataka
Keywords: None
Abstract: The National Environment Policy (2006) defined the Eco-Sensitive Zones “as areas/zones with identified
environmental resources having incomparable values which require special attention for their conservation”
because of its landscape, wildlife, biodiversity, historical and natural values.
Location: T E 15 New Biology building
Literature cited 1: Ramachandra, T. V., Bharath, Setturu, Subash Chandran, M. D., & Joshi, N. V. (2018). Salient ecological sensitive
regions of central Western Ghats, India. Earth Systems and Environment, 2, 15-34. DOI: 10.1007/s41748-018-0040-
3
Ramachandra, T. V., Bharath, Setturu, & Aithal, Bharath H. (2020). Insights of forest dynamics for the regional
ecological fragility assessment. Journal of the Indian Society of Remote Sensing, 48(8), 1169-1189. DOI:
10.1007/s12524-020-01146-z
Literature cited 2: Ramachandra, T. V., Vinay, S., Bharath, Setturu, Subash Chandran, M. D., & Aithal, Bharath H. (2020). Insights
into riverscape dynamics with the hydrological, ecological and social dimensions for water sustenance. Current
Science, 118(9), 1379-1393. DOI: 10.18520/cs/v118/i9/1379-1393
Ramachandra, T. V., & Vinay, S. (2023). Ecohydrological Footprint and Climate Trends in Lotic Ecosystems of
Central Western Ghats. Water, 15(18), 3169. DOI: 10.3390/w15183169
ID: 66723
Title: Ecological Insights of Northern Karnataka River basins, Central Western Ghats, Karnataka and Goa
Author: TV Ramachandra Tulika Mondal Paras Negi
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Ecological Insights of Northern Karnataka River basins,
Central Western Ghats, Karnataka and Goa,ETR 214, SCR 142, Pg no. 1-23
Subject: Ecological Insights of Northern Karnataka River basins, Central Western Ghats, Karnataka and Goa
Keywords: None
Abstract: The National Environment Policy (2006) defined the Eco-Sensitive Zones “as areas/zones with
identified environmental resources having incomparable values which require special attention
for their conservation” because of its landscape, wildlife, biodiversity, historical and natural
values.
Location: T E 15 New Biology building
Literature cited 1: Ramachandra, T. V., Bharath Setturu, Vinay S., Chandran, M. S., Baghel, A., & Aithal, Bharath H.
(2024). Ecologically sensitive regions in the Western Ghats, a biodiversity hotspot. Indian
Forester, 149, 1105-1121. DOI: 10.36808/if/2023/v149i11/169382
Literature cited 2: Ramachandra, T. V., Bharath, Setturu, Subash Chandran, M. D., & Joshi, N. V. (2018). Salient
ecological sensitive regions of central Western Ghats, India. Earth Systems and Environment, 2, 1534.
DOI:
10.1007/s41748-018-0040-3
Ramachandra, T. V., & Setturu, B. (2023). Ecologically sensitive regions in Belgaum district,
Karnataka, Central Western Ghats. Journal of Environmental Biology, 44(1), 11-26.
ID: 66722
Title: Non-commercial fuel consumption in the domestic sector across agro-climatic zones in Karnataka, India
Author: TV Ramachandra Sara Kunnath
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference: Non-commercial fuel consumption in the domestic sector across agro-climatic zones in Karnataka, India ,ETR 215, SCR 143, Pg no. 1-46
Subject: Non-commercial fuel consumption in the domestic sector across agro-climatic zones in Karnataka, India
Keywords: None
Abstract: Energy plays a pivotal role in the socio-economic development of a region as it plays a crucial
role in improving human welfare, while raising living standards. The demand of energy
requirement is directly proportional to the developmental activities coupled with the
population. Across the world a billion people still lack access to electricity and about 3 billion
rely on traditional fuels such as fuelwood, charcoal and animal waste for cooking and heating
(UNEP- 2020). About 80% of India’s energy needs are met by three fuels coal, oil and biomass
(IPNG 2021-22, IEA 2021). India is home to more than 240 million households out of which
about 100 million households rely on traditional fuels such as firewood, coal, dung cakes etc.
as a primary source of cooking fuel (WLPGA, 2020, Ministry of Petroleum and Natural Gas).
Location: T E 15 New Biology building
Literature cited 1: Ali, J., & Benjaminsen, T. A. (2004). Fuelwood, timber and deforestation in the Himalayas:
The case of Basho Valley, Baltistan Region, Pakistan. Mountain Research and Development,
24(4), 312-318.
Arnold, M., & Persson, R. (2003). Reassessing the fuelwood situation in developing countries.
International Forestry Review, 5(4), 379-383.
Literature cited 2: Carlos, M. R., & Khang, D. B. (2008). Characterization of biomass energy projects in
Southeast Asia. Biomass and Bioenergy, 32(2008), 525-532.
Choudhuri, P., & Desai, S. (2020). Gender inequalities and household fuel choice in India.
Journal of Cleaner Production, 265.
ID: 66721
Title: Natural Capital Accounting and Valuation of Ecosystem Services in R K Mission campus, Shivanahalli, Bangalore Urban district, India
Author: Ramachandra T.V., Bhuwan Chandra Arya, Swami Vishnumayananda and Murali S
Editor: T.V. Ramachandra
Year: 2025
Publisher: Energy &Wetlands Research Group
Source: ENVIS, CES & EWRG, CES
Reference:
Subject: Natural Capital Accounting and Valuation of Ecosystem Services in R K Mission campus, Shivanahalli, Bangalore Urban district, India
Keywords: None
Abstract: Ecosystem services are the contributions of ecosystems to the benefits that are used in economic and other
human activities. Further, ecosystem services encompass all forms of interaction between ecosystems and people,
including both in situ and remote interactions. The supply of an ecosystem service is associated with an
ecosystem structure or process, or a combination of ecosystem structures and processes that reflect the biological,
chemical, and physical interactions among ecosystem components.
Location: T E 15 New Biology building
Literature cited 1:
Literature cited 2: