Bhitarkanika Research Articles

Community-based Ecotourism in Protected Areas towards Inclusive Development-An Evidence of Bhitarkanika Wildlife Sanctuary of India

Community-based ecotourism (CBET) is one of the tourism segments used to protect the natural environment by the host communities in many countries; however, empirical studies involving active involvement, understanding, and level of satisfaction of the community and tourists in various ecotourism projects are still scarce in the context of developing countries. Thus, this study empirically examines the potential of community-based ecotourism in and around the Bhitarkanika Wildlife Sanctuary (BKWS) from the perspectives of the community and tourists in Odisha, India. Primary data were collected through a structured questionnaire prepared based on an expert view. In this study, both descriptive and exploratory research designs were considered the most appropriate. A total of 470 respondents participated in this study. Cronbach’s α was used to ensure reliability and validity of the instrument used for the survey. Data analysis was performed using SPSS 23.0. Collected data were tested for outliers using stem and leaf chart analysis, and all data were normally distributed for further analysis. Finally, a clear picture of the study was drawn based on the analysis and interpretation. The ANOVA (F-test) results demonstrated that community-based ecotourism was quite significant for inclusive development and conservation practices, as supported by all five statistically significant explanatory factors. The one-way ANOVA test for Hypothesis 1 found that community-based eco-tourism can be leveraged as a unique selling point (USP) to boost tourism in Odisha. Furthermore, one-way ANOVA was used to test the second hypothesis, which demonstrated that community-based ecotourism raises awareness within the local population about the importance of protecting Odisha's tourism resources. Similarly, the t-test results demonstrated that tourists and communities do not differ significantly in terms of satisfaction with event settings, art and craft, performance, infrastructure, guide services, and information. The findings of the study revealed that CBET was a major tool for promoting Odisha Tourism and creating awareness among the local community for the conservation of protected areas to embrace sustainability. Practical implications have been suggested for policy improvement in Odisha Tourism.

Ecotourism in Bhitarkanika Wildlife Sanctuary, India: assessment of participation, economic benefits and conservation goals

ABSTRACT Ecotourism is a special category of tourism that links livelihood and conservation. However, the efficacy of ecotourism in conservation and the promotion of the livelihood system of local people in and around the protected area needs in-depth investigation. The paper has used a mixed-method approach to examine the factors that affect the participation of residents in ecotourism-related businesses, assess the economic impact of ecotourism, and analyse the impact of participation on the preservation of natural resources in Bhitarkanika Wildlife Sanctuary, Odisha, India. Using social exchange theory as the base, the study finds that land availability of the family, age between 20 and 35, graduation and above education, and earning members as a proportion of total members are the factors affecting households’ incidence of participation in ecotourism significantly. Ecotourism participation has positively influenced the asset holdings such as owning lighta, fans, and televisions as well as housing ownership, types of housing, sanitary condition and fuel wood used by the participants. The empirical results show that participation and economic benefits are reflected in the lesser dependency of the participants on the sanctuary. Proper strategies need to be designed for an inclusive ecotourism approach in BKWS, one which is economically beneficial and environmentally sustainable.

Unveiling the hidden treasures: the vital contributions of Bhitarkanika mangrove in supporting local communities

Mangroves are salt-resistant vegetation that inhibit the muddy intertidal region of tropical and sub-tropical countries. Bhitarkanika Mangrove Sanctuary is one of the hotspots of Odisha state due to its wide range of biodiversity. Mangroves are always integral to the coastal livelihood by providing goods and services to the communities. The importance of mangroves gets neglected by sideling its provision of valuable resources and protection services against cyclones and storms. The present article studied the benefits provided by the Bhitarkanika Mangroves forests to the local communities and focuses on the sustainable conservation of resources for the future. Evidence-based suggestions are suitable for achieving the sustainability of local communities by adopting conservation measures.

Interspecific variations in leaf litter decomposition and nutrient release from tropical mangroves

Efficient nutrient cycling through decomposition of leaf litter often regulates the high productivity and subsequent carbon sequestration of mangrove ecosystems along the land-ocean boundary. To understand the characteristics and the potentials of mangrove leaf litter in supplying organic carbon and nutrients to the coastal waters, four major mangrove species (A. officinalis, R. mucronata, H. littoralis and S. apetala) of Bhitarkanika mangrove forest, Odisha, India, were examined in controlled environmental conditions. Half-life time (t0.5), estimated for decomposition of those mangrove leaf litter materials ranged from 18 to 52 days. During the incubation experiment, organic carbon from mangrove leaf litter was released primarily through physical processes and was available for heterotrophic respiration. Among the four species, leaf litter of S. apetala with the lowest initial C/N ratios, released organic carbon with low molecular weight (labile substances) that has a relatively higher potential to support the aquatic food web. On the contrary, leaf litter of R. mucronata released organic material with relatively higher molecular weight (humic substances, higher aromaticity), which revealed its superior non-labile characteristics in this unique environment. The mean total heterotrophic bacterial (THB) population in the incubation was around nine-fold higher than the control. THB population growth and Chromophoric Dissolved Organic Matter (CDOM) spectral data further suggested the rapid release of highly labile and recalcitrant carbon from S. apetala and R. mucronata (between 7th and 21st day of incubation), respectively. The mean litter fall from the Bhitarkanika mangrove forest was estimated to be 11.32 ± 1.57 Mg ha−1 y−1 and its corresponding carbon content was 5.43 ± 0.75 Mg C ha−1. The study revealed the role of leaf litter leachates as an important food source to microbial communities in the adjacent coastal waters, in addition to a potential carbon sequesterer through long-term burial in mangrove soil and export to the deep sea.

A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest

Mangroves are well-recognized for their very high carbon sequestration potential. However, studies on their role in global carbon cycling and climate change are hindered due to lack of operational methodologies to model and map their biophysical properties. This study establishes a robust methodological protocol for aboveground biomass (AGB) estimation using i) field measurements, ii) a generic (in the absence of species-specific) allometric equation, iii) multi-sensor/polarization SAR data and derived variables thereof, and iv) machine learning models; that demonstrated high prediction accuracy (R2 = 0.93) and low uncertainty (mean ≤ 3% and median ≤ 1.5%) for a mangrove forest. Following stratified random sampling and on-field accessibility criteria, we laid out 314 elementary sampling points of 0.04 ha each at Bhitarkanika wildlife sanctuary (BWS), India and measured circumference at breast height (CBH) and canopy tree height for 18 species. The estimated AGB range of a generic allometric equation was 9–474 Mg/ha for BWS, with a major representation of 9–347 Mg/ha. We utilized Sentinel-1 and ALOS-2/PALSAR-2 and derived their variables for AGB prediction. Compared to single sensor-based model, we observed higher prediction accuracy for combined sensor data (R2 = 0.63, 0.87, 0.93; RMSE = 66.75, 39.95, 28.35 Mg/ha; MAE = 52.63, 24.21, 19.55 Mg/ha; and Bias = 3.42, 0.22, 2.15 Mg/ha for C, L and C & L bands respectively using a Generalized Additive Model (GAM) over Random Forest (RF), Gradient Boosting Machines (GBM) and Support Vector Regression (SVR). The higher uncertainty pixels represented seasonal grassland and scrubs in the swampy areas and along the fringes of the creeks that experience diurnal tidal fluctuations. This robust methodology can be replicated for AGB estimates in other mangrove ecosystems to meet the operational carbon accounting requirements of various entities.

Ecotourism a solution or deception for conservation: a case of Bhitarkanika Wildlife Sanctuary, Odisha, India

PurposeThe quest for alternative approaches to tourism has introduced ecotourism. However, in many instances, ecotourism becomes “green washing” process where revenue generation becomes prominent and protection of environmental assets is kept aside. The present article attempts to examine the impact of ecotourism policy on conservation in Bhitarkanika Wildlife Sanctuary (BKWS), Odisha, India.Design/methodology/approachUsing social exchange theory (SET), the article examines whether ecotourism reduces the dependency of the local communities on natural resources and also the impact of ecotourism on conservation of biodiversity in BKWS.FindingsThe study using a mixed method approach finds that ecotourism in BKWS is able to provide economic benefits to the villagers. The economic benefits from diversified employment opportunities are able to motivate locals to conserve biodiversity. However, the socio-cultural impact is hardly experienced by the villagers.Research limitations/implicationsBy examining the linkage of conservation with community development in a diverse society like India, the paper finds the linkage of conservation with development. The paper has also widened the existing ecotourism literature of India and Odisha. The study adopted SET so as to get a comprehensive understanding at the ground level, forming the basis for future research and further conceptual development.Practical implicationsThe results of the study will help policy makers to develop an effective conservation strategy by integrating tourism, conservation and sustainable development of the locals so as to make ecotourism a successful approach in BKWS.Originality/valueFor a growing ecotourism site like BKWS, the current study is the first to assess impact of ecotourism on conservation and local people.

Distribution and dynamics of particulate organic matter in Indian mangroves during dry period.

The distribution and possible sources of particulate organic carbon (POC) and particulate nitrogen (PN) in seven mangroves ecosystems along the east and west coast of India were examined, to understand their contribution to coastal biogeochemistry. Suspended particulate matter (SPM) concentration in mangrove waters were about ~ 1.6-fold higher in west coast (Gulf of Kachchh (GOK), Mandovi-Zuari (MA-ZU) and Karwar-Kumta (KR-KU)], whereas the mean POC content in SPM along east coast [Sundarbans (SUN), Bhitarkanika (BHK), Coringa (COR) and Pichavaram-Muthupet (PI-MU)] was nearly two times higher than the west coast (1.97 ± 0.91% and 1.06 ± 0.29%), respectively. The results indicated that the influence of the land-based contaminants on the water quality parameters (dissolved oxygen, pH, salinity, nutrients and chlorophyll-a, etc.), which primarily regulated the distribution and transformation of organic carbon in these mangrove waters. Among the studied systems, an extremely high DOC/POC ratio (5.72 ± 1.64) with low pH and DO in COR waters clearly indicated the labile nature of the organic matter influenced by anthropogenic stress. Strong correlation between POC and PN indicated a similar origin in particulate organic matter. The ratios of POC/PN and POC/Chl-a showed significant spatial variation ranging from 5.5 to 18.7 and 126 to 1057, respectively. The results indicated that significant fraction of in-situ primary production contributed to particulate organic matter (POM) pool in all Indian mangrove waters except the GOK and the SUN waters, where sediment resuspension and mangrove derived organic matter were the dominant POM sources.

Symbolic regression-based allometric model development of a mangrove forest LAI using structural variables and digital hemispherical photography

The leaf area index (LAI) serves as a proxy to understand the dynamics of plant productivity, energy balance, and gas exchange. Cost-effective and accurate estimation of LAI is essential for under-assessed carbon-rich tropical forests, e.g., mangroves. Here, we developed allometric equations to estimate LAI using a combination of non-destructive, optical measurements through digital hemispherical photographs (DHP), and genetic programming-based Symbolic Regression (SR). We used three structural variables: diameter at breast height (DBH), tree density (TD), and canopy height (Ht) for a mangrove forest in the BhitarKanika Wildlife Sanctuary (BWS), located along the Eastern coast of India. Triplet combination using SR provided the best equation (R2 = 0.51) than any singlet or duplet combination of the variables, and even it was better than Partial Least Square (PLS) based regression (R2 = 0.42). To the best of our knowledge, the current study is the maiden attempt to develop an allometric model to estimate LAI for a mangrove ecosystem in India. In-situ measurements of structural variables such as DBH, Ht, and TD can be used for LAI estimates, as shown here. LAI estimates using cost-effective methods would greatly enhance our understanding of the spatial and temporal dynamics of mangrove ecosystems.

Quantitative Ecological Study of Rhizophoraceae Mangroves of Bhitarkanika Wildlife Sanctuary Regions of Odisha Coast, India

Quantitative Ecological Study of Rhizophoraceae Mangroves of Bhitarkanika Wildlife Sanctuary Regions of Odisha Coast, India

Interspecific variations in mangrove stem biomass: A potential storehouse of sequestered carbon

Variations in stem biomass and carbon density in 12 mangrove species were studied to understand the potential of carbon storage in the live biomass of Bhitarkanika mangrove ecosystems, South-East Coast of India. The results highlighted significant inter-species variations (p<0.01; ANOVA) in the stem wood density and carbon content and could be attributed to the spatial variations in soil fertility, adaptation, freshwater supply, genus identity as well as properties of the fibre lumen and wall. Among the studied species, Avicennia officinalis showed the highest carbon density and Corg/Ntot ratios followed by Heritiera fomes. Further, the higher carbon sequestration capacity of these two mangrove species was confirmed through Principal Component Analysis (PCA). Corg, Corg/Ntot and cellulose/protein ratio were strongly associated with the wood density of the studied mangrove species. Mangrove stem diameter (at breast height; DBH), wood density and tree height were used to estimate the above-ground biomass of all the species, which showed remarkably higher biomass for Avicennia officinalis. Possible adaptation of these species under extreme environmental conditions in addition to variations in vessel wall thickness caused by differential carbon fixation and storage in the form of biomass could explain the variability in elemental properties of mangrove stem wood. Heritiera littoralis and Kandelia candel with relatively higher lignin to cellulose content showed greater potentials to sustain biotic and abiotic stresses and indicated higher carbon sequestration as recalcitrant biomass. The lowest carbon density and highest ratio of cellulose/lignin in the Sonneratia apetala and Sonneratia caseolaris species indicated faster plant growth compared to the other studied species. FTIR analysis evidenced that the increase in the 1728–1733 cm −1 band height assigned to cellulose and decrease in the 1517–1519 cm −1 band height assigned to lignin.

Species-Level Classification and Mapping of a Mangrove Forest Using Random Forest—Utilisation of AVIRIS-NG and Sentinel Data

Although studies on species-level classification and mapping using multisource data and machine learning approaches are plenty, the use of data with ideal placement of central wavelength and bandwidth at appropriate spatial resolution, for the classification of mangrove species is underreported. The species composition of a mangrove forest has been estimated utilising the red-edge spectral bands and chlorophyll absorption information from AVIRIS-NG and Sentinel-2 data. In this study, three dominant species, Heritiera fomes, Excoecaria agallocha and Avicennia officinalis, have been classified using the random forest (RF) model for a mangrove forest in Bhitarkanika Wildlife Sanctuary, India. Various combinations of reflectance/backscatter bands and vegetation indices derived from Sentinel-2, AVIRIS-NG, and Sentinel-1 were used for species-level discrimination and mapping. The RF model showed maximum accuracy using Sentinel-2, followed by the AVIRIS-NG, in discriminating three dominant species and two mixed compositions. This study indicates the potential of Sentinel-2 data for discriminating various mangrove species owing to the appropriate placement of central wavelength and bandwidth in Sentinel-2 at ≥10 m spatial resolution. The variable importance plots proved that species-level classification could be attempted using red edge and chlorophyll absorption information. This study has wider applicability in other mangrove forests around the world.

Multiple values of Bhitarkanika mangroves for human well-being: synthesis of contemporary scientific knowledge for mainstreaming ecosystem services in policy planning

Bhitarkanika National Park and Mahanadi Delta are the most biologically diverse mangrove patches of India. Due to inadequate representation of the value of the mangroves in decision-making, mangroves of Bhitarkanika and Mahanadi delta have undergone a rapid decline in the last fifty years. Thus, there is a growing need to assess the ecosystem services and multiple values of mangrove ecosystems in the region, and to identify the various anthropogenic and environmental drivers acting upon them. In this paper, we conducted a bibliometric analysis, followed by a synthesis of contemporary knowledge to understand the diverse ecosystem services of the Bhitarkanika mangroves and the existing data gaps for the protection and sustainable management of mangroves. It was observed that Bhitarkanika mangroves primarily serve as a buffer to coastal storms, tsunamis and cyclones, and they also contribute immense provisioning, and cultural ecosystem services for human well-being. The present review provides a comprehensive database projecting important ecosystem services and multiple values (including carbon sink potential, pollinator benefits and protection from storm surges) of Bhitarkanika mangrove forests. We found that there is a significant pressure on the mangroves of Bhitarkanika due to increasing aquaculture, environmental pollution, industrialization, storm surges and frequent cyclones. The present study helps to understand the urgent need of protecting the existing mangroves and to devise a coastal zone policy framework and strengthening participatory approaches for preservation of dense and intact mangroves of Bhitarkanika and Mahanadi delta.

Aquatic and edaphic determinants influencing carbon storage in a salt marsh grass, Porteresia coarctata, of the Bhitarkanika wildlife sanctuary and the Mahanadi estuary

In the present study, investigation was carried out in the Bhitarkanika and Mahanadi mangrove ecosystems during 2017–18 and 2018–19 on biomass and carbon of Porteresia coarctata, a salt marsh grass species of the Poaceae family. Water parameters such as temperature, pH, and salinity were measured along with soil parameters such as pH, electrical conductivity, bulk density, organic carbon, and soil texture, which were measured simultaneously. Growth pattern in terms of increase in biomass and carbon (in Mg ha−1) over the study period in Bhitarkanika was 1.03 ± 0.49 and 0.48 ± 0.22 and that of Mahanadi was 0.62 ± 0.17 and 0.29 ± 0.09, respectively. The correlation coefficient was computed for biomass and carbon of P. coarctata where salinity, soil bulk density, and soil organic carbon played a major role in governing the distribution of species. MANOVA results computed for both Bhitarkanika and Mahanadi showed significant difference between stations for both biomass and carbon of P. coarctata. However, other parameters of water and soil exhibited very weak relationship. Allometric models computed with AGB and AGC as dependent variables and physico-chemical variables as independent variables have revealed that salinity and OC are the major driving factors for growth and development as well as carbon storage potential of the species.

Aboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data - The superiority of deep learning over a semi-empirical model

The availability of advanced Machine Learning algorithms has made the estimation process of biophysical parameters more efficient. However, the efficiency of those methods seldom compared with the efficiency of already established semi-empirical procedures. Aboveground biomass (AGB) of mangrove forests is a crucial biophysical parameter as it is positively correlated to the carbon stocks and fluxes. The free availability of Sentinel-1 C-band SAR data and machine learning algorithms hold promises in estimating AGB of tropical mangrove forests. We reported high AGB (70 t/ha to 666 t/ha) using 185 field quadrats of 0.04ha each from Bhitarkanika Wildlife Sanctuary, located on the eastern Indian coast that could be attributed to species composition. The AGB maps generated using Interferometric Water Cloud Model (IWCM) and Deep Learning models were different from each other as they rely on different variables. IWCM was more dependent, especially on ground and vegetation components of coherence, while canopy height acted as the most crucial variable in the Deep Learning model. However, the negligible variations in Deep Learning-based AGB maps can be attributed to interpreting the importance of coherence and VH backscatter. Due to low canopy penetration power of C-band SAR, high temporal decorrelation resulting from longer time gap between interferometric image pairs, and high spatial heterogeneity of mangrove forests, IWCM found as an unsuitable method for AGB estimation. Interestingly, a Deep Learning algorithm could translate the exact relationship between predictor variables and mangrove AGB in Bhitarkanika Wildlife Sanctuary. The AGB estimation studies in mangrove forests using Sentinel data should focus more on using machine learning algorithms like Deep Learning rather than semi-empirical models.

Community Empowerment and Conservation Through Ecotourism: A Case of Bhitarkanika Wildlife Sanctuary, Odisha, India

Ecotourism is a type of sustainable tourism that aims at conservation of the environment through maintaining a balance between conservation and empowerment of local residents. However, for developing countries like India, proper implementation of ecotourism is questionable. The present study has selected Bhitarkanika Wildlife Sanctuary (BKWS), Odisha, India, which is the second largest mangrove ecosystem in India. An attempt is made to examine how far ecotourism has been successful in empowering the locals socially, culturally, and psychologically through their involvement in different organizations and its implications in achieving the conservation goals. Both primary and secondary data were used in the study. The study uses a variety of econometric techniques and case studies for finding the results. The study finds that with the creation of employment opportunities locals also have been made aware for participation in community development programs, including ecodevelopment clubs and self-help groups. However, these organizations have failed to empower the communities. Although some positive attitudes have come in discussions, the results mostly indicate that ecotourism certainly has not met the principles of empowerment. Organizational participation has therefore not been successful for the reduction of dependence on natural resources in Bhitarkanika. The support of the locals is highly essential for successful conservation policy. Thus, proper strategies need to be designed for an inclusive ecotourism approach in BKWS and beyond, one that is socially effective, psychologically and politically empowered, culturally progressive, and environmentally sustainable.

Human-crocodile conflict and attitude of local communities toward crocodile conservation in Bhitarkanika Wildlife Sanctuary, Odisha, India

Where conservation programs aimed at rebuilding depleted populations of saltwater crocodiles (Crocodylus porosus) have been successful, incentives for local people to support ongoing conservation action have been undermined by increasing rates of human-crocodile conflict (HCC), involving fatal and non-fatal attacks on people and livestock. In this study we report on HCC within the 672 km2 Bhitarkanika Wildlife Sanctuary (BWS), Odisha, India. Forest Department contain records of 51 attacks on people and 57 on cattle over 21 years (1996–2016). Human attacks were both fatal (45%) and non-fatal (55%), and were highest in the monsoon season (63%) and summer (23%) and lowest in the post-monsoon (10%) and winter (4%). The activities of people attacked were: domestic chores and crossing rivers (32%), defecating (24%), Bathing (22%), fishing (10%), paddy cultivation (8%) and grazing cattle (4%). Attacks on males (70%) were more common than on females (30%). No attacks on young children (0-10 years-of-age) were reported, and the most common age of victims was 40–50 yr (29%) and 20–30 yr (26%). Semi-structured interviews with the main household earning member in villages on the periphery of BWS (n = 57), revealed there was no notable influence of age, gender, and education on the perception and attitude of the local community but people who were affected negatively from the conflict tended to be negative toward the conservation of saltwater crocodiles. The findings of this research aim to serve the planning of mitigation strategies for future human crocodile conflicts in Bhitarkanika Wildlife Sanctuary.

Community structure, taxonomic diversity and spatio-temporal variation of sediment and water bacteria in Bhitarkanika mangrove ecosystem, India

Bacterial diversity of Bhitarkanika mangrove was studied by both the culture-dependent and culture-independent methods. The variation of culture-dependent bacterial population with respect to different physico-chemical parameters was also observed seasonally (summer and monsoon) from five stations—Dangmal, Ekakula, Gupti, Habalikhati and Kalibhanjadiha. Overall, culture-dependent total heterotrophic bacteria varied from 2.16 ± 0.5 to 168.25 ± 1.73 × 103 cfu/g in sediment and 1.53 ± 0.915 to 38.33 ± 0.108 × 103 cfu/ml in water. Major regulatory factors for bacterial abundance of water were nitrate phosphate, conductivity, dissolved oxygen in different seasons while no such clear influence was observed on sediment bacterial abundance. Culture-dependent study revealed that Bacilli, Gammaproteobacteria and Betaproteobacteria were dominant bacterial classes. Culture-independent study revealed that the operational taxonomic unit varied from 5077 to 21,207 in sediment and 14,213 to 17,501 in water. Majority of the bacterial community were found to be under the class Gammaproteobacteria followed by Alphaproteobacteria and Bacilli. In sediment, highest and lowest species richness as well as evenness was recorded at Dangmal and Ekakula, respectively, while in water, both the parameters were more or less similar in all the sampling sites. Maximum species diversity was observed at Dangmal sediment (Shannon diversity index: 10.43) and Habalikhati water (Shannon diversity index: 7.45). Principal Coordinate Analysis (PCoA) revealed that Ekakula, Kalibhanjadiha and Gupti, Habalikhati sediment had similar species composition in culture-dependent and independent analysis, respectively. Dangmal sediment had the unique species composition, whereas bacterial species composition in water varied greatly within different sites in both the cases. This study depicts the highly rich bacterial diversity of Bhitarkanika.

Canopy Height Estimation Using Sentinel Series Images through Machine Learning Models in a Mangrove Forest

Canopy height serves as a good indicator of forest carbon content. Remote sensing-based direct estimations of canopy height are usually based on Light Detection and Ranging (LiDAR) or Synthetic Aperture Radar (SAR) interferometric data. LiDAR data is scarcely available for the Indian tropics, while Interferometric SAR data from commercial satellites are costly. High temporal decorrelation makes freely available Sentinel-1 interferometric data mostly unsuitable for tropical forests. Alternatively, other remote sensing and biophysical parameters have shown good correlation with forest canopy height. The study objective was to establish and validate a methodology by which forest canopy height can be estimated from SAR and optical remote sensing data using machine learning models i.e., Random Forest (RF) and Symbolic Regression (SR). Here, we analysed the potential of Sentinel-1 interferometric coherence and Sentinel-2 biophysical parameters to propose a new method for estimating canopy height in the study site of the Bhitarkanika wildlife sanctuary, which has mangrove forests. The results showed that interferometric coherence, and biophysical variables (Leaf Area Index (LAI) and Fraction of Vegetation Cover (FVC)) have reasonable correlation with canopy height. The RF model showed a Root Mean Squared Error (RMSE) of 1.57 m and R2 value of 0.60 between observed and predicted canopy heights; whereas, the SR model through genetic programming demonstrated better RMSE and R2 values of 1.48 and 0.62 m, respectively. The SR also established an interpretable model, which is not possible via any other machine learning algorithms. The FVC was found to be an essential variable for predicting forest canopy height. The canopy height maps correlated with ICESat-2 estimated canopy height, albeit modestly. The study demonstrated the effectiveness of Sentinel series data and the machine learning models in predicting canopy height. Therefore, in the absence of commercial and rare data sources, the methodology demonstrated here offers a plausible alternative for forest canopy height estimation.

Use of Hyperion for Mangrove Forest Carbon Stock Assessment in Bhitarkanika Forest Reserve: A Contribution Towards Blue Carbon Initiative

Mangrove forest coastal ecosystems contain significant amount of carbon stocks and contribute to approximately 15% of the total carbon sequestered in ocean sediments. The present study aims at exploring the ability of Earth Observation EO-1 Hyperion hyperspectral sensor in estimating aboveground carbon stocks in mangrove forests. Bhitarkanika mangrove forest has been used as case study, where field measurements of the biomass and carbon were acquired simultaneously with the satellite data. The spatial distribution of most dominant mangrove species was identified using the Spectral Angle Mapper (SAM) classifier, which was implemented using the spectral profiles extracted from the hyperspectral data. SAM performed well, identifying the total area that each of the major species covers (overall kappa = 0.81). From the hyperspectral images, the NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) were applied to assess the carbon stocks of the various species using machine learning (Linear, Polynomial, Logarithmic, Radial Basis Function (RBF), and Sigmoidal Function) models. NDVI and EVI is generated using covariance matrix based band selection algorithm. All the five machine learning models were tested between the carbon measured in the field sampling and the carbon estimated by the vegetation indices NDVI and EVI was satisfactory (Pearson correlation coefficient, R, of 86.98% for EVI and of 84.1% for NDVI), with the RBF model showing the best results in comparison to other models. As such, the aboveground carbon stocks for species-wise mangrove for the study area was estimated. Our study findings confirm that hyperspectral images such as those from Hyperion can be used to perform species-wise mangrove analysis and assess the carbon stocks with satisfactory accuracy.

Insect Flower Visitors and their Role in Mangrove Pollination: A Study from East Coast of India

Insects play a critical role in bringing successful pollination in angiosperms. Mangrove pollination is a poorly studied aspect from scientific community. This particular work investigated the insect visitors and other prospective of mangrove flowers. Twenty two species (i.e., 17 true and 5 mangrove associates) from Bhitarkanika Wildlife Sanctuary and Devi estuary of Odisha state (East coast of India) were selected; plants were pre-marked and visiting insects were recorded starting from 07.00 am to 13.00 pm during the flowering period of each species. Fifty three species of insects which belongs to seven orders, twenty five families and forty four genera were recorded. The highest, i.e., 14 sp. of insects had been recorded from Aegiceras corniculatum which is a small tree and riverine mangrove. Among insects, bees were found as the most common flower visitors (in 82% mangroves) and particularly “honey bee”, i.e., Apis dorsata visited to sixteen mangrove species (i.e., 73% mangroves). Bees, particularly Honeybee (A. dorsata), sweet bee (Lasioglossum sp.) and carpenter bee (Xylocopa pubescens) were actively engaged in pollen dispersal. Resident time and visitation rate supported that bees with highest visitation rate and low resident time were powerful candidates in bringing mangrove pollination. Wasps, beetles and butterflies act more to be foraging species. Facilitation of bee management and particularly supporting apiculture will help to increase pollination successes of rare and threatened mangroves at regional and global level.