Intrinsic contributions of polar amino acid residues toward thermal stability of an ABC–ATPase of mesophilic origin

The nucleotide-binding subunit of phosphate-specific transporter (PstB) from mesophilic bacterium, Mycobacterium tuberculosis, is a unique ATP-binding cassette (ABC) ATPase because of its unusual ability to hydrolyze ATP at high temperature. In an attempt to define the basis of thermostability, we took a theoretical approach and compared amino acid composition of this protein to that of other PstBs from available bacterial genomes. Interestingly, based on the content of polar amino acids, this protein clustered with the thermophiles

Evaluating landscape capacity to provide spatially explicit valued ecosystem services for sustainable coastal resource management

Ecosystem Services (ESs) are the direct and indirect benefits and opportunities that human obtained from the ecosystem. This study evaluated landscape capacity of providing multiple key ESs in a tropical coastal ecosystem (Sundarbans Biodiversity Region (SBR)India). Multiple supervised machine learning algorithms were utilized to classify the regions into several landscape zones. The provisioning capacities of ESs for each landscape type were derived separately from an expert opinion survey and the remote sensing based methods, and the association of the outcomes between these two approaches was evaluated using the Pearson correlation coefficient test. A total of nine ESs were selected to quantify their economic values for several reference years. The benefit transfer and equivalent value coefficient approaches were used to aggregate the economic values for each ES. Research results indicated that the water bodies are the most important landscape units in the SBR region. This ecosystem has the highest relevant capacity to provide the necessary regulatory, supporting, provisioning, and cultural ESs. Water regulation (WR), waste treatment (WT), aesthetic, recreation, and cultural (ARC), and climate regulation (CR) are the main ESs of the SBR. These services are immensely important not only for upgrading the livelihood status of coastal communities but also for the climatic and environmental suitability of the Kolkata urban region. The correlation results between the remote sensing and expert-based capacity estimates have suggested that the proposed remote sensing approach could be an alternative to evaluate the landscape capacity of providing multiple ESs in any given ecosystem. Except for the mangrove region, a very high (>0.7) correlation was observed between the model and expert-derived capacity values. The outcome of this study could be an important reference to the land administrators, planners, decision makers for adopting suitable land resource management plans for sustainable uses of natural resources in coastal region.</p

Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem

Most of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the last few decades, primarily due to increasing human dominance in the natural environment. Identification and categorization of factors that affect the provision of ESs from global to local scales are challenging. This study makes an effort to identify the key driving factors and examine their effects on different ESs in the Sundarbans region, India. We carry out the analysis following five successive steps: (1) quantifying biophysical and economic values of ESs using three valuation approaches; (2) identifying six major driving forces on ESs; (3) categorizing principal data components with dimensionality reduction; (4) constructing multivariate regression models with variance partitioning; (5) implementing six spatial regression models to examine the causal effects of natural and anthropogenic forcings on ESs. Results show that climatic factors, biophysical factors, and environmental stressors significantly affect the ESs. Among the six driving factors, climate factors are highly associated with the ESs variation and explain the maximum model variances (R2 = 0.75–0.81). Socioeconomic (R2 = 0.44–0.66) and development (R2 = 27–0.44) factors have weak to moderate effects on the ESs. Furthermore, the joint effects of the driving factors are much higher than their individual effects. Among the six spatial regression models, Geographical Weighted Regression (GWR) performs the most accurately and explains the maximum model variances. The proposed hybrid valuation method aggregates biophysical and economic estimates of ESs and addresses methodological biases existing in the valuation process. The presented framework can be generalized and applied to other ecosystems at different scales. The outcome of this study could be a reference for decision-makers, planners, land administrators in formulating a suitable action plan and adopting relevant management practices to improve the overall socio-ecological status of the region.</p

Identification of Conservation Priority Zones Using Spatially Explicit Valued Ecosystem Services : A Case from the Indian Sundarbans

Demarcation of conservation priority zones (CPZs) using spatially explicit models is the new challenge in ecosystem services (ESs) research. This study identifies the CPZs of the Indian Sundarbans by integrating 2 different approaches, that is, ESs and ecosystem health (EH). Five successive steps were followed to conduct the analysis: First, the ESs were estimated using biophysical and economic methods and a hybrid method (that combines biophysical and economic methods); second, the vigor–organization–resilience (VOR) model was used for estimating EH; third, the risk characterization value (RCV) of ESs was measured using the function of EH and ESs; fourth, Pearson correlation test was performed to analyze the interaction between ESs and EH components; and fifth, the CPZs were defined by considering 7 relevant components: ecosystem vigor, ecosystem organization, ecosystem resilience, RCV, EH, ESs, and the correlation between EH and ESs. Among the major ecoregions of the Sundarbans, the highest ESs value in economic terms is provided by the mangrove ecosystem (US$19 144.9 million per year). The highest conservation priority score was projected for the Gosaba block, which is dominated by dense mangrove forests. The estimated CPZs were found to be highly consistent with the existing biodiversity zonations. The outcome of this study could be a reference for environmentalists, land administrators, researchers, and decision makers to design relevant policies to protect the high values of the Sundarbans ecosystem. Integr Environ Assess Manag 2020;16:773–787

Examining the effects of forest fire on terrestrial carbon emission and ecosystem production in India using remote sensing approaches

Remote sensing techniques are effectively used for measuring the overall loss of terrestrial ecosystem productivity and biodiversity due to forest fires. The current research focuses on assessing the impacts of forest fires on terrestrial ecosystem productivity in India during 2003–2017. Spatiotemporal changes of satellite remote sensing derived burn indices were estimated for both fire and normal years to analyze the association between forest fires and ecosystem productivity. Two Light Use Efficiency (LUE) models were used to quantify the terrestrial Net Primary Productivity (NPP) of the forest ecosystem using the open-source and freely available remotely sensed data. A novel approach (delta NPP/delta burn indices) is developed to quantify the effects of forest fires on terrestrial carbon emission and ecosystem production. During 2003–2017, the forest fire intensity was found to be very high (>2000) across the eastern Himalayan hilly region, which is mostly covered by dense forest and thereby highly susceptible to wildfires. Scattered patches of intense forest fires were also detected in the lower Himalayan and central Indian states. The spatial correlation between the burn indices and NPP were mainly negative (−0.01 to −0.89) for the fire-prone states as compared to the other neighbouring regions. Additionally, the linear approximation between the burn indices and NPP showed a positive relation (0.01 to 0.63), suggesting a moderate to high impact of the forest fires on the ecosystem production and terrestrial carbon emission. The present approach has the potential to quantify the loss of ecosystem productivity due to forest fires.</p

Examining the effects of green revolution led agricultural expansion on net ecosystem service values in India using multiple valuation approaches

Ecosystem Services (ESs) are bundles of natural processes and functions that are essential for human well-being, subsistence, and livelihoods. The ‘Green Revolution’ (GR) has substantial impact on the agricultural landscape and ESs in India. However, the effects of GR on ESs have not been adequately documented and analyzed. This leads to the main hypothesis of this work – ‘the incremental trend of ESs in India is mainly prompted by GR led agricultural innovations that took place during 1960 - 1970’. The analysis was carried out through five successive steps. First, the spatiotemporal Ecosystem Service Values (ESVs) in Billion US$ for 1985, 1995, and 2005 were estimated using several value transfer approaches. Second, the sensitivity and elasticity of different ESs to land conversion were carried out using coefficient of sensitivity and coefficient of elasticity. Third, the Geographically Weighted Regression model was performed using five explanatory factors, i.e., total crop area, crop production, crop yield, net irrigated area, and cropping intensity, to explore the cumulative and individual effects of these driving factors on ESVs. Fourth, Multi-Layer Perceptron based Artificial Neural Network was employed to estimate the normalized importance of these explanatory factors. Fifth, simple and multiple linear regression modeling was done to assess the linear associations between the driving factors and the ESs. During the observation periods, cropland, forestland and water bodies contributed to 80%–90% of ESVs, followed by grassland, mangrove, wetland and urban built-up. In all three evaluation years, the highest estimated ESVs among the nine ES categories was provided by water regulation, followed by soil formation and soil-water retention, biodiversity maintenance, waste treatment, climate regulation, and greenhouse gas regulation. Among the five explanatory factors, total crop area, crop production, and net irrigated area showed strong positive associations with ESVs, while cropping intensity exhibited a negative association. Therefore, the study reveals a strong association between GR led agricultural expansion and ESVs in India. This study suggests that there should be an urgent need for formulation of rigorous ecosystem management strategies and policies to preserve ecological integrity and flow of uninterrupted ESs and to sustain human well-being