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Forest biomass quantification is highly crucial for the maintenance of global carbon cycle. Hence, the accurate estimation of tree parameters is of utmost requirement nowadays. The hypothesis of this research is to formulate a volumetric equation which will be focussed on the structure of the tree and not the species. To serve this purpose, 13 plots were scanned in the Barkot forest range of Uttarakhand, India, and the plots were scanned using Terrestrial Laser Scanner (TLS). The tree attribute such as radius of the stem and tree height were estimated using Random Sample Consensus (RANSAC) algorithm and line primitive vector, respectively. The correlation was established using multiple linear regression using the TLS derived tree parameters and field estimated tree parameters. The R2 obtained for field estimated biomass is 0.91 with radius and 0.73 with the tree height. The radius of the stem and tree height were used for the calculation of volume of all the trees and the R2 value obtained for field estimated volume and TLS derived volume is 0.95. Then the stem volume of the trees were calculated based on the new volume equation. The statistical analysis was done, and ANOVA test was performed indicating high F value (25.4) which shows that the regression model is significant. The predicted biomass correlation coefficient (R2 = 0.97) was obtained. It represents the significance of the model for the estimation of volume and biomass is high. The equation can be implemented in any forest type irrespective of the forest structure. [ABSTRACT FROM AUTHOR]

The photosynthesis governs productivity and health of the forests. Traditionally, remote sensing derived reflectance measures have been used to assess forest phenology, productivity and stress. The chlorophyll pigments absorb solar radiation, and emit fluorescence in far red region of electromagnetic spectrum. Chlorophyll fluorescence directly relates to the photosynthetic activity of the plants. Measurement of chlorophyll fluorescence from space has recently been achieved in the form of Sun-Induced Fluorescence (SIF). But SIF response have been found variable with respect to variation in vegetation type, hence, there is a need to study SIF response of tropical forests of India considering their wide extent, contribution to national carbon cycle and climate resilience. In this study, intra- and inter-annual GOME-2 and OCO-2 SIF responses of contrasting Indian tropical forest types viz., dry deciduous (Betul, Madhya Pradesh), moist deciduous (Kalahandi, Orissa) and wet evergreen forests (Uttara Kannada, Karnataka) has been investigated with respect to rainfall, NDVI and GPP trends. The results show that dry, moist and wet forests of India have differences in photosynthetic activity at intra- and inter-annual scale. GOME-2 SIF observations were more variables than OCO-2 SIF, particularly during green-up and senescence phase. SIF explained higher seasonality for dry deciduous followed by moist deciduous and wet evergreen. Annually integrated SIF (proxy of GPP) was in order: wet evergreen > moist deciduous > dry deciduous. [ABSTRACT FROM AUTHOR]

Recently, numerous frameworks and tools are being developed for enhancing access to data and services with a standardized view to communicate the advances in open information sharing. Another emerging field of data exploration is encountered in the coordination, examination and perception of bioresource data and are prompting corresponding new innovations. The bioresource information team aims to develop standards for nationwide data exchange by the establishment of a catalog service to locate and access biological data and information from across the country and information tool for decision makers. With the growth of open data sharing initiatives, the sharing of data among different and myriad sources has increased significantly, but major challenge lies in addressing the issues of interoperability during exchange and use since the data sources are heterogeneous and the data being organization specific is prepared with different (organization) specific data standards and platforms. This paper presents the model based on the study of different metadata standards and to develop a recommended standard for biodiversity information to support interoperability among heterogeneous databases under the umbrella of Indian Bioresource Information Network (IBIN) portal. The paper presents the mapping of different data standards into the IBIN standard for sharing species data in the form of distributed and interoperable web services to set the stage for interoperability. [ABSTRACT FROM AUTHOR]

The study explores the use of multiple criteria decision techniques in predicting spatial niche of Brown oak (also known as Kharsu oak, Quercus semecarpifolia Sm.) formation in midaltitude (2,400-3,500 meter amsl) Kumaun Himalaya. Predictive models using various climatic and topographical factors influencing Brown oak's growth and survival were developed to define its current ecological niche. Analytical Hierarchical Process (AHP) method involving Saaty's pair-wise comparison was performed to rank the explanatory powers of each compared variable. Variables were suitably weighted using fuzzy factor standardization scheme to reflect their relative importance in defining species niche. An optimum indicator was then chosen for deriving a site suitability map of brown oak. This study establishes the role of aspect in the current distribution of the species along with known influence of altitude. Future niches of oak has been tracked in the projected climate change scenario of +1°C and +2°C rise in temperature and 20 mm in precipitation. The results show that on predicted +1°C and +2°C increase in temperature, present habitat of brown oak distribution may be reduced by 40 per cent and 76 per cent respectively. [ABSTRACT FROM AUTHOR]

Present study deals with the vegetation type mapping, structure and composition analysis of the tropical forests, spread over 1,294 km area in South Andaman Islands. Seventeen vegetation classes spreading over 89.92% forested area of the islands were mapped with the overall accuracy of 88.89%. Evergreen, semi-evergreen and mangrove forests were reasonably well distributed forests, while moist deciduous and littoral evergreen were narrowly restricted. The stocking was quite variable across the forest types. 60.04% of forested area was under medium to high canopy density. Secondary and degraded forest types were mapped. Information on floristic composition, structure and diversity of various forest types were obtained from 84 field sample plots. An inventory of 423 species of plants from 101 families included 155 trees, 84 shrubs, 150 herbs and 84 climbers. Tree density and mean basal area ranged from 517 to 900 stems ha and 36.15 to 53.58 m ha respectively. Evergreen forests accounted for highest diversity followed almost equally by semi-evergreen and moist deciduous forests. [ABSTRACT FROM AUTHOR]

Increasing concern for biodiversity conservation at species level resulted in the development of cost effective tools for getting information at larger scale. Modeling distribution of species using remote sensing and geographic information has already proved its potentials to get such information with less effort. Pittosporum eriocarpum Royle is an endemic and threatened tree species of Uttarakhand, yet till now its regional distribution is poorly known. This study using geospatial modelling tools indentified several localities of potential occurrence of this species in the Mussoorie hills and Doon valley, and also provides information on its habitat specificity. The main objective of the study is to predict the suitable habitats for endangered plant species in Himalayan region using logistic regression model where availability of sufficient data on species presenceabsence is a major limitation for larger areas. [ABSTRACT FROM AUTHOR]