Temporal variability of forest communities: empirical estimates of population change in 4000 tree species

Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

Return levels of hydrologic droughts under climate change

Developments in the statistical extreme value theory, which allow non-stationary modeling of changes in the frequency and severity of extremes, are explored to analyze changes in return levels of droughts for the Colorado River. The transient future return levels (conditional quantiles) derived from regional drought projections using appropriate extreme value models, are compared with those from observed naturalized streamflows. The time of detection is computed as the time at which significant differences exist between the observed and future extreme drought levels, accounting for the uncertainties in their estimates. Projections from multiple climate model-scenario combinations are considered; no uniform pattern of changes in drought quantiles is observed across all the projections. While some projections indicate shifting to another stationary regime, for many projections which are found to be non-stationary, detection of change in tail quantiles of droughts occurs within the 21st century with no unanimity in the time of detection. Earlier detection is observed in droughts levels of higher probability of exceedance. (C) 2014 Elsevier Ltd. All rights reserved.

Assessing ``inherent vulnerability'' of forests: a methodological approach and a case study from Western Ghats, India

The objective of this study is to present a methodological approach to assess the inherent vulnerability of forests and apply it to a case study. Addressing inherent vulnerability, resulting from current stresses, is a necessary step for building resilience to long-term climate change. The proposed approach includes use of analytical framework that enables selection of vulnerability criteria and indicators systematically, application of pairwise comparison method (PCM) for assigning weights, and synthesis of a composite vulnerability index. This methodological approach has been applied at local scale to Aduvalli Protected Forest in Western Ghats in South India, where a vulnerability index value of 0.248 is estimated. Results of the case study indicate that `preponderance of invasive species' and forest dependence of community are the major sources of vulnerability at present for Aduvalli Protected Forest. Adoption of this methodology can assist in development of forest management plans to enhance adaptability of Aduvalli PF to current as well as future stresses, including climate change. This methodological approach can be applied across forest-types after appropriate changes to criteria and indicators and their weights, to estimate the inherent vulnerability to enable development of adaptation strategy.

Real-time maximum a-posteriori image reconstruction for fluorescence microscopy

Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Mycobacterium tuberculosis Inhibits RAB7 Recruitment to Selectively Modulate Autophagy Flux in Macrophages

Here we report a novel regulatory mechanism for autophagy-mediated degradation of Mycobacterium tuberculosis (Mtb) and specific strategy exploited by the virulent Mtb to evade it. We show while both avirulent (H37Ra) and virulent (H37Rv) mycobacteria could readily localize to autophagosomes, their maturation into autolysosomes (flux) was significantly inhibited by the latter strain. The inhibition of autophagy flux by the virulent strain was highly selective, as it did not perturb the basal autophagy flux in the macrophages. Selective inhibition of flux of Mtb-containing autophagosomes required virulence regulators PhoP and ESAT-6. We show that the maturation of Mtb-containing autophagosomes into autolysosomes required recruitment of the late endosome marker RAB7, forming the intermediate compartment amphisomes. Virulent Mtb selectively evaded their targeting to the amphisomes. Thus we report a crosstalk between autophagy and phagosome maturation pathway and highlight the adaptability of Mtb, manifested by selective regulation of autophagy flux.

Delineation of homogeneous hydrometeorological regions using wavelet-based global fuzzy cluster analysis

Identification of homogeneous hydrometeorological regions (HMRs) is necessary for various applications. Such regions are delineated by various approaches considering rainfall and temperature as two key variables. In conventional approaches, formation of regions is based on principal components (PCs)/statistics/indices determined from time series of the key variables at monthly and seasonal scales. An issue with use of PCs for regionalization is that they have to be extracted from contemporaneous records of hydrometeorological variables. Therefore, delineated regions may not be effective when the available records are limited over contemporaneous time period. A drawback associated with the use of statistics/indices is that they do not provide effective representation of the key variables when the records exhibit non-stationarity. Consequently, the resulting regions may not be effective for the desired purpose. To address these issues, a new approach is proposed in this article. The approach considers information extracted from wavelet transformations of the observed multivariate hydrometeorological time series as the basis for regionalization by global fuzzy c-means clustering procedure. The approach can account for dynamic variability in the time series and its non-stationarity (if any). Effectiveness of the proposed approach in forming HMRs is demonstrated by application to India, as there are no prior attempts to form such regions over the country. Drought severity-area-frequency (SAF) curves are constructed corresponding to each of the newly formed regions for the use in regional drought analysis, by considering standardized precipitation evapotranspiration index (SPEI) as the drought indicator.

Nitrogen-assisted electroless assembling of 3D nanodendrites consisting of Pd and N-doped carbon nanoparticles as bifunctional catalysts

We report a facile synthesis of three-dimensional (3D) nanodendrites of Pd nanoparticles (NPs) and nitrogen-doped carbon NPs (N-CNPs) by electroless deposition of Pd2+ ions. N-CNPs being an electron-enriched material act as a reducing agent. Moreover, the availability of a variety of nitrogen species in N-CNPs promotes the open arm structure as well as stabilizes the oriented 3D assembly of primary Pd NPs. The dendrites exhibit superior catalytic activity for methanol (0.5 M) oxidation in alkaline media (1 M NaOH) which is ascribed to the large electrochemical active surface area and the enhanced mass activity with repeated use. Further mass activity improvement has been realized after acid-treatment of dendrites which is attributed to the increment in the -OH group. The dendrites show higher mass activity (J(f) similar to 653 A g(-1)) in comparison with a commercial Pt-carbon/Pd-carbon (Pt-C/Pd-C) catalyst (J(f) similar to 46 and 163 A g(-1), respectively), better operational stability, superior CO tolerance with I-f/I-b (similar to 3.7) over a commercial Pt-C/Pd-C catalyst (I-f/I-b similar to 1.6 and 1.75, respectively) and may serve as a promising alternative to commercial Pt-C catalysts for anode application in alkaline fuel cells. To ensure the adaptability of our 3D-nanodendrites for other catalytic activities, we studied 4-nitrophenol reduction at room temperature. The 3D-nanodendrites show excellent catalytic activity toward 4-nitrophenol reduction, as well.