A new species of Raorchestes (Amphibia: Anura: Rhacophoridae) from mid-elevation evergreen forests of the southern Western Ghats, India

A new species of the shrub frog genus Raorchestes Biju, Souche, Dubois, Dutta and Bossuyt is described as Raorchestes kakachi sp. nov. from Agastyamalai hill region in the southern Western Ghats, India. The small sized Raorchestes (male: 24.7–25.8 mm, n = 3 and female: 24.3–34.1 mm, n = 3) is distinguished from all other known congeners by the following suite of characters. Snout oval in dorsal view; tympanum indistinct; head wider than long; moderate webbing in feet; colour on dorsum varying from ivory to brown, blotches of dark brown on flanks, brown mottling on throat reducing towards vent; inner and outer surface of thigh, inner surface of shank and inner surface of tarsus with a distinct dark brown horizontal band which extends upto first three toes on upper surface. A detailed description, advertisement call features, ecology, natural history notes and comparison with closely related species are provided for the new species.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

Decentralised carbon footprint analysis for opting climate change mitigation strategies in India

Carbon footprint (CF) refers to the total amount of carbon dioxide and its equivalents emitted due to various anthropogenic activities. Carbon emission and sequestration inventories have been reviewed sector-wise for all federal states in India to identify the sectors and regions responsible for carbon imbalances. This would help in implementing appropriate climate change mitigation and management strategies at disaggregated levels. Major sectors of carbon emissions in India are through electricity generation, transport, domestic energy consumption, industries and agriculture. A majority of carbon storage occurs in forest biomass and soil. This paper focuses on the statewise carbon emissions (CO2. CO and CH4), using region specific emission factors and statewise carbon sequestration capacity. The estimate shows that CO2, CO and CH4 emissions from India are 965.9, 22.5 and 16.9 Tg per year, respectively. Electricity generation contributes 35.5% of total CO2 emission, which is followed by the contribution from transport. Vehicular transport exclusively contributes 25.5% of total emission. The analysis shows that Maharashtra emits higher CO2, followed by Andhra Pradesh, Uttar Pradesh, Gujarat, Tamil Nadu and West Bengal. The carbon status, which is the ratio of annual carbon storage against carbon emission, for each federal state is computed. This shows that small states and union territories (UT) like Arunachal Pradesh, Mizoram and Andaman and Nicobar Islands, where carbon sequestration is higher due to good vegetation cover, have carbon status > 1. Annually, 7.35% of total carbon emissions get stored either in forest biomass or soil, out of which 34% is in Arunachal Pradesh, Madhya Pradesh, Chhattisgarh and Orissa. (C) 2012 Elsevier Ltd. All rights reserved.

Prediction of Shallow Landslide prone regions in Undulating Terrains

Genetic Algorithm for Rule-set Prediction (GARP) and Support Vector Machine (SVM) with free and open source software (FOSS) - Open Modeller were used to model the probable landslide occurrence points. Environmental layers such as aspect, digital elevation, flow accumulation, flow direction, slope, land cover, compound topographic index and precipitation have been used in modeling. Simulated output of these techniques is validated with the actual landslide occurrence points, which showed 92% (GARP) and 96% (SVM) accuracy considering precipitation in the wettest month and 91% and 94% accuracy considering precipitation in the wettest quarter of the year.

Modeling the effect of transmission errors on TCP controlled transfers over infrastructure 802.11 wireless LANs

There have been several studies on the performance of TCP controlled transfers over an infrastructure IEEE 802.11 WLAN, assuming perfect channel conditions. In this paper, we develop an analytical model for the throughput of TCP controlled file transfers over the IEEE 802.11 DCF with different packet error probabilities for the stations, accounting for the effect of packet drops on the TCP window. Our analysis proceeds by combining two models: one is an extension of the usual TCP-over-DCF model for an infrastructure WLAN, where the throughput of a station depends on the probability that the head-of-the-line packet at the Access Point belongs to that station; the second is a model for the TCP window process for connections with different drop probabilities. Iterative calculations between these models yields the head-of-the-line probabilities, and then, performance measures such as the throughputs and packet failure probabilities can be derived. We find that, due to MAC layer retransmissions, packet losses are rare even with high channel error probabilities and the stations obtain fair throughputs even when some of them have packet error probabilities as high as 0.1 or 0.2. For some restricted settings we are also able to model tail-drop loss at the AP. Although involving many approximations, the model captures the system behavior quite accurately, as compared with simulations.

Random forest algorithm with derived geographical layers for improved classification of remote sensing data

Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.

Water treatment potential in relation to phytoplankton dynamics in tropical sewage-fed urban water bodies

Urban water bodies frequently receive untreated sewage and water levels in such water bodies are maintained by daily inputs of sewage. They function as “variable-zone” anaerobic-aerobic lagoons suffering several macrophyte, biotic and abiotic stresses. We have studied two such lakes in Bangalore (Bellandur-360 ha and Varthur-220 ha) to understand whether such an occurrence could be made beneficial (maintaining water levels as well as treatment). Such hypertrophic water body receives sewage at 180-250mg/L and is discharged at 25-80mg/L COD/BOD in different seasons. In an earlier study we reported macrophyte altering the purification function of the water body. In this paper we studied the impact of phytoplankton dynamics and macrophyte cover on the functions such as organic load removal. Algal community analysis, algal biomass, macrophyte cover, water quality, nutrient status was studied seasonally during 2009-2010. Oxygen deficiency and sometimes anoxia, recorded from surface samples resulted in high quantities of NH4+-N (30-40mg/L) and phosphate (0.5-4mg/L)-characteristics of anoxic hypertrophic urban lakes. The productiveness favoured high phytoplanktonic community characterized by small cells (<10μm; Chlorella sp. - highest numbers). The lake could be clearly demarcated into an initial anaerobic zone (40% area), a facultative zone (20%) and an aerobic zone (40%) based on redox values and GIS/bathymetry. During summer the lake is covered by floating macrophytes converting the lake into an anoxic/anaerobic water pool subduing the water purification function as well as aesthetics. When macrophytes are controlled such sewage fed water bodies can be used for treating urban wastewater while also maintaining water sustainability in these semi-arid ecosystems. This paper reports the community dynamics of phytoplankton, their function and competition with macrophytes.

Algal biofuel from urban wastewater in India: Scope and challenges

Rapidly depleting stocks of fossil fuels and increasing greenhouse gas (GHG) emissions have necessitated the exploration of cost effective sustainable energy sources focussing on biofuels through algae. Abundant wastewaters generated in urban localities every day provide the nourishment to nurture algae for biofuel generation. The present communication focuses on the lipid prospects of algae grown in wastewater systems. Euglena sp., Spirogyra sp. and Phormidium sp. were collected from selected locations of sewage fed urban lakes and sewage treatment plants of Bangalore and Mysore. The total lipid content of Euglena sp. was higher (24.6%) compared to Spirogyra sp. (18.4%) followed by Phormidium sp. (8.8%) and their annual lipid yield potential was 6.52, 1.94 and 2.856 t/ha/year, respectively. These species showed higher content of fatty acids (palmitate, stearate followed by oleic and linoleic acids) with the desirable biofuel properties. (C) 2013 Elsevier Ltd. All rights reserved.

Robustness of early warning signals of regime shifts in time-delayed ecological models

Various ecological and other complex dynamical systems may exhibit abrupt regime shifts or critical transitions, wherein they reorganize from one stable state to another over relatively short time scales. Because of potential losses to ecosystem services, forecasting such unexpected shifts would be valuable. Using mathematical models of regime shifts, ecologists have proposed various early warning signals of imminent shifts. However, their generality and applicability to real ecosystems remain unclear because these mathematical models are considered too simplistic. Here, we investigate the robustness of recently proposed early warning signals of regime shifts in two well-studied ecological models, but with the inclusion of time-delayed processes. We find that the average variance may either increase or decrease prior to a regime shift and, thus, may not be a robust leading indicator in time-delayed ecological systems. In contrast, changing average skewness, increasing autocorrelation at short time lags, and reddening power spectra of time series of the ecological state variable all show trends consistent with those of models with no time delays. Our results provide insights into the robustness of early warning signals of regime shifts in a broader class of ecological systems.

Treatment efficacy of algae-based sewage treatment plants

Lagoons have been traditionally used in India for decentralized treatment of domestic sewage. These are cost effective as they depend mainly on natural processes without any external energy inputs. This study focuses on the treatment efficiency of algae-based sewage treatment plant (STP) of 67.65 million liters per day (MLD) capacity considering the characteristics of domestic wastewater (sewage) and functioning of the treatment plant, while attempting to understand the role of algae in the treatment. STP performance was assessed by diurnal as well as periodic investigations of key water quality parameters and algal biota. STP with a residence time of 14.3 days perform moderately, which is evident from the removal of total chemical oxygen demand (COD) (60 %), filterable COD (50 %), total biochemical oxygen demand (BOD) (82 %), and filterable BOD (70 %) as sewage travels from the inlet to the outlet. Furthermore, nitrogen content showed sharp variations with total Kjeldahl nitrogen (TKN) removal of 36 %; ammonium N (NH4-N) removal efficiency of 18 %, nitrate (NO3-N) removal efficiency of 22 %, and nitrite (NO2-N) removal efficiency of 57.8 %. The predominant algae are euglenoides (in facultative lagoons) and chlorophycean members (maturation ponds). The drastic decrease of particulates and suspended matter highlights heterotrophy of euglenoides in removing particulates.

A Cooperative ARQ Scheme for Infrastructure WLANs

We propose a Cooperative Opportunistic Automatic Repeat ReQuest (CoARQ) scheme to solve the HOL-blocking problem in infrastructure IEEE 802.11 WLANs. HOL blocking occurs when the head-of-the-line packet at the Access Point (AP) queue blocks the transmission of packets to other destinations resulting in severe throughput degradation. When the AP transmits a packet to a mobile station (STA), some of the nodes in the vicinity can overhear this packet transmission successfully. If the original transmission by the AP is unsuccessful, our CoARQ scheme chooses the station. STA or AP) with the best channel to the intended receiver as a relay and the chosen relay forwards the AP's packet to the receiver. This way, our scheme removes the bottleneck at the AP, thereby providing significant improvements in the throughput of the AP. We analyse the performance of our scheme in an infrastructure WLAN under a TCP controlled file download scenario and our analytical results are further validated by extensive simulations.

Assimilation of endmember variability in spectral for urban land cover extraction mixture analysis

Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

Delineating Ecological Boundaries of Hanuman Langur Species Complex in Peninsular India Using MaxEnt Modeling Approach

Hanuman langur is one of the widely distributed and extensively studied non-human diurnal primates in India. Until recently it was believed to be a single species - Semnopithecus entellus. Recent molecular and morphological studies suggest that the Hanuman langurs consists of at least three species S. entellus, S. hypoleucos and S. priam. Furthermore, morphological studies suggested that both S. hypoleucos and S. priam have at least three subspecies in each. We explored the use of ecological niche modeling (ENM) to confirm the validity of these seven taxa and an additional taxon S. johnii belonging to the same genus. MaxEnt modeling tool was used with 19 bioclimatic, 12 vegetation and 6 hydrological environmental layers. We reduced total environmental variables to 14 layers after testing for collinearity and an independent test for model prediction was done using ENMTools. A total of 196 non-overlapping data points from primary and secondary sources were used as inputs for ENM. Results showed eight distinct ecological boundaries, corroborating the eight taxa mentioned above thereby confirming validity of these eight taxa. The study, for the first time provided ecological variables that determined the ecological requirements and distribution of members of the Hanuman langur species complex in the Indian peninsula.