Marine phenology and its response to climate change -Winter School on Impact of Climate Change on Indian Marine Fisheries held at CMFRI, Cochin 18.1.2008 to 7.2.2008

Phenology is defined as the study of the timing of recurring biological phases, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species. In other words it is the study of plant and animal life cycle events, which are triggered by environmental changes, especially temperature. The word “phenology” is derived from the Greek Phainomai, which means “to appear” or “come into view”, and indicates that phenology has been principally concerned with the dates of first occurrence of natural events in their annual cycle

Marine pollution

Pollution is a big problem that has impact on all of the planet's ecosystems, including the oceans. Economic developement has been most active In coastal zones, putting enormous pressure on coastal ecosystems. Marine pollution has Increased throughout the world, mainly due to direct discharges from rivers, increased surface run-off and drainage from expanding port areas, oil spills and other contaminants from shipping and domestic and industrial effluent. Most of the world's wastes-some 20 billion tonnes of it a year-end up in the sea, often without any preliminary processing

Marine pollution monitoring using mussels

Pollution is a major problem that has negative effects on all of the planet’s ecosystems, including the oceans. In many parts of the region, economic development has been most active in coastal zones, putting enormous pressures on coastal ecosystems. Coastal and marine water pollution has increased throughout the world, mainly due to direct discharges from rivers, increased surface rim-off and drainage from expanding port areas, oil spil sand other contaminants from shipping, and domestic and industrial effluent

Estimation of secondary production & benthos- Winter School on Towards Ecosystem Based Management of Marine Fisheries – Building Mass Balance Trophic and Simulation Models

Marine organisms can be categorized as benthic, planktonic or nektonic depending on their physical habitat and their mode of motility. Planktonic organisms are those that live suspended in the water column and that are sufficiently small and/or slow so as to be incapable of directed swimming. Thus, their distribution is considered to be controlled by physical processes, such as water currents and turbulent mixing. In addition, plankton can be divided further based on their nutritional modality. Autotrophic phytoplankton depends on light and chlorophyll to fix carbon dioxide into organic molecules, whereas heterotrophic zooplankton ultimately depends on the phytoplankton for their dissolved or particulate foodstuffs

Climate change related marine ecosystem regime shifts and their impact on fisheries -Winter School on Impact of Climate Change on Indian Marine Fisheries held at CMFRI, Cochin 18.1.2008 to 7.2.2008

Global changes affect the biotic and abiotic elements that influence the numbers and distribution of fish species. It is now understood that marine ecosystems change on a variety of time scales, from seasonal to centennial and longer. Atmospheric and climate-related processes force many of these time scales, and therefore it is well understood by marine scientists that climate variability is a strong driver of changes in fish populations and in fisheries

Primer software and its application in marine biodiversity studies. In: Winter School on Impact of Climate Change on Indian Marine Fisheries held at CMFRI, Cochin 18.1.2008 to 7.2.2008

The PRIMER (Plymouth Routines In Multivariate Ecological Research) software was developed by Dr. Bob Clarke and Dr. Ray Gorley of Plymouth Marine Laboratory, UK (Clarke and Warwick, 1994). This software can perform analysis of ecological data entered in spreadsheets. It can be used for calculating various univariate biodiversity measures such as Margalef’s index, Shannon-Weiner index, Brillouin’s index, Simpson diversity index etc. The latest version of the software (PRIMER 6) consists of a wide range of univariate, graphical and multivariate routines for analysing the species/samples abundance (or biomass) matrices that arise in biological monitoring of environmental impact and more fundamental studies in community ecology, together with associated physico-chemical data. The methods make few, if any, assumptions about the form of the data (‘non-metric’ ordination and permutation tests are fundamental to the approach) and concentrate on approaches that are straightforward to understand and explain

Lie Symmetry Analysis of the Black-Scholes-Merton Model for European Options with Stochastic Volatility

We perform a classification of the Lie point symmetries for the Black--Scholes--Merton Model for European options with stochastic volatility, $\sigma$, in which the last is defined by a stochastic differential equation with an Orstein--Uhlenbeck term. In this model, the value of the option is given by a linear (1 + 2) evolution partial differential equation in which the price of the option depends upon two independent variables, the value of the underlying asset, $S$, and a new variable, $y$. We find that for arbitrary functional form of the volatility, $\sigma(y)$, the (1 + 2) evolution equation always admits two Lie point symmetries in addition to the automatic linear symmetry and the infinite number of solution symmetries. However, when $\sigma(y)=\sigma_{0}$ and as the price of the option depends upon the second Brownian motion in which the volatility is defined, the (1 + 2) evolution is not reduced to the Black--Scholes--Merton Equation, the model admits five Lie point symmetries in addition to the linear symmetry and the infinite number of solution symmetries. We apply the zeroth-order invariants of the Lie symmetries and we reduce the (1 + 2) evolution equation to a linear second-order ordinary differential equation. Finally, we study two models of special interest, the Heston model and the Stein--Stein model.Comment: Published version, 14pages, 4 figure

Multi-frequency scatter broadening evolution of pulsars - I

We present multi-wavelength scatter broadening observations of 47 pulsars, made with the Giant Metre-wave Radio Telescope (GMRT), Ooty Radio Telescope (ORT) and Long Wavelength Array (LWA). The GMRT observations have been made in the phased array mode at 148, 234, and 610 MHz and the ORT observations at 327 MHz. The LWA data sets have been obtained from the LWA pulsar data archive. The broadening of each pulsar as a function of observing frequency provides the frequency scaling index, $\alpha$. The estimations of $\alpha$ have been obtained for 39 pulsars, which include entirely new estimates for 31 pulsars. This study increases the total sample of pulsars available with $\alpha$ estimates by $\sim$50\%. The overall distribution of $\alpha$ with the dispersion measure (DM) of pulsar shows interesting variations, which are consistent with the earlier studies. However, for a given value of DM a range of $\alpha$ values are observed, indicating the characteristic turbulence along each line of sight. For each pulsar, the estimated level of turbulence, $C^{2}_{n_e}$, has also been compared with $\alpha$ and DM. Additionally, we compare the distribution of $\alpha$ with the theoretically predicated model to infer the general characteristics of the ionized interstellar medium (ISM). Nearly 65\% of the pulsars show a flatter index (i.e., $\alpha < 4.4$) than that is expected from the Kolmogorov turbulence model. Moreover, the group of pulsars having flatter index is typically associated with an enhanced value of $C^{2}_{n_e}$ than those with steeper index.Comment: 13 pages, 4 figures, 3 tables. Accepted for publication in Ap