EFFECTS OF LAND-USE CHANGE ON THE PROPERTIES OF TOP SOIL OF DECIDUOUS SAL FOREST IN BANGLADESH

This study examined the effects of land use change on the physico-chemical properties of top soil in the deciduous Sal forest of Bangladesh. Relatively less disturbed Sal (Shorea robusta Roxb. Ex Gaertn.) forest stands and the nearby stands those were converted into Acacia (Acacia auriculiformis Benth.) plantation and pineapple (Ananus comosus (L.) Merr.) cultivation were selected to examine the effects of land use change on soil properties. For each land use type, soil samples were collected from 4 locations, 50m distant from each other, as replicates. Soil samples were collected at 0-5, 5-10, and 10-15 cm depths. Soil moisture content, conductivity, pH organic C, total N and total P were determined as soil properties. Leaf litter of Sal, Acacia and pineapple was incubation for 90 and 180 days in independent identical soil in order to examine the effects of plant species through leaf litter on the soil chemical nutrient (N and P) status. Data showed that soil moisture content, conductivity and pH were significantly affected by land use but not by depth. However, soil organic C was affected by both land-use type (P< 0.02) and soil depth (P< 0.003), although no significant interactions appeared between these two factors. Soil total N and P did not differ between land use types but by depth and, N and P contents decreased with the increase of depth. Rates of nutrients (N and P) released from Sal, Acacia and pineapple did not differ significantly among them during incubation. Results of the present study reveal that properties of the top soil of the Madhupur Sal forest are different in their responses to the varying land uses. The findings of this study are thus relevant for the sustainable management of the deciduous Sal forest ecosystems

Distinguishing Posed and Spontaneous Smiles by Facial Dynamics

Smile is one of the key elements in identifying emotions and present state of mind of an individual. In this work, we propose a cluster of approaches to classify posed and spontaneous smiles using deep convolutional neural network (CNN) face features, local phase quantization (LPQ), dense optical flow and histogram of gradient (HOG). Eulerian Video Magnification (EVM) is used for micro-expression smile amplification along with three normalization procedures for distinguishing posed and spontaneous smiles. Although the deep CNN face model is trained with large number of face images, HOG features outperforms this model for overall face smile classification task. Using EVM to amplify micro-expressions did not have a significant impact on classification accuracy, while the normalizing facial features improved classification accuracy. Unlike many manual or semi-automatic methodologies, our approach aims to automatically classify all smiles into either `spontaneous' or `posed' categories, by using support vector machines (SVM). Experimental results on large UvA-NEMO smile database show promising results as compared to other relevant methods.Comment: 16 pages, 8 figures, ACCV 2016, Second Workshop on Spontaneous Facial Behavior Analysi

Flushing History as a Hydrogeological Control on the Regional Distribution of Arsenic in Shallow Groundwater of the Bengal Basin

Whereas serious health consequences of widespread consumption of groundwater elevated in As have been documented in several South Asian countries, the mechanisms responsible for As mobilization in reducing aquifers remain poorly understood. We document here a previously unrecognized and consistent relationship between dissolved As concentrations in reducing groundwater and the phosphate-mobilizable As content of aquifer sediment for a set of precisely depth-matched samples from across Bangladesh. The relationship holds across nearly 3 orders of magnitude in As concentrations and suggests that regional as well as local patterns of dissolved As in shallow groundwater are set by the solid phase according to a remarkably constant ratio of ∼250 μg/L dissolved As per 1 mg/kg P-mobilizable As. We use this relationship in a simple model of groundwater recharge to propose that the distribution of groundwater As in shallow aquifers of the Bengal Basin could primarily reflect the different flushing histories of sand formations deposited in the region over the past several thousand years

A new estimate of carbon for Bangladesh forest ecosystems with their spatial distribution and REDD+ implications

In tropical developing countries, reducing emissions from deforestation and forest degradation (REDD+) is becoming an important mechanism for conserving forests and protecting biodiversity. A key prerequisite for any successful REDD+ project, however, is obtaining baseline estimates of carbon in forest ecosystems. Using available published data, we provide here a new and more reliable estimate of carbon in Bangladesh forest ecosystems, along with their geo-spatial distribution. Our study reveals great variability in carbon density in different forests and higher carbon stock in the mangrove ecosystems, followed by in hill forests and in inland Sal (Shorea robusta) forests in the country. Due to its coverage, degraded nature, and diverse stakeholder engagement, the hill forests of Bangladesh can be used to obtain maximum REDD+ benefits. Further research on carbon and biodiversity in under-represented forest ecosystems using a commonly accepted protocol is essential for the establishment of successful REDD+ projects and for the protection of the country’s degraded forests and for addressing declining levels of biodiversity