Climatic change controls productivity variation in global grasslands.

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2-71.2% during 1982-2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms

How inefficient are small-scale rice farmers in eastern India really?: Examining the effects of microtopography on technical efficiency estimates

We focus on the impact of failing to control for differences in land types defined along toposequence on estimates of farm technical efficiency for small-scale rice farms in eastern India. In contrast with the existing literature, we find that those farms may be considerably more technically efficient than they appear from more aggregated analysis without such control. Farms planted with modern rice varieties are technically efficient. Furthermore, farms planted with traditional rice varieties operate close to the production frontier on less productive lands (upland and mid-upland), but significant technical inefficiency exists on more productive lands (medium land and lowland).

Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using dynamical community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.Comment: 8 pages, 6 figures, accepted for publication in Chao

Analysis of aggregated tick returns: evidence for anomalous diffusion

In order to investigate the origin of large price fluctuations, we analyze stock price changes of ten frequently traded NASDAQ stocks in the year 2002. Though the influence of the trading frequency on the aggregate return in a certain time interval is important, it cannot alone explain the heavy tailed distribution of stock price changes. For this reason, we analyze intervals with a fixed number of trades in order to eliminate the influence of the trading frequency and investigate the relevance of other factors for the aggregate return. We show that in tick time the price follows a discrete diffusion process with a variable step width while the difference between the number of steps in positive and negative direction in an interval is Gaussian distributed. The step width is given by the return due to a single trade and is long-term correlated in tick time. Hence, its mean value can well characterize an interval of many trades and turns out to be an important determinant for large aggregate returns. We also present a statistical model reproducing the cumulative distribution of aggregate returns. For an accurate agreement with the empirical distribution, we also take into account asymmetries of the step widths in different directions together with crosscorrelations between these asymmetries and the mean step width as well as the signs of the steps.Comment: 9 pages, 10 figures, typos correcte

Tuning Structure and Rheology of Silica-Latex Nanocomposites with the Molecular Weight of Matrix Chains: A Coupled SAXS-TEM-Simulation Approach

The structure of silica-latex nanocomposites of three matrix chain masses (20, 50, and 160 kg/mol of poly(ethyl methacrylate)) are studied using a SAXS/TEM approach, coupled via Monte Carlo simulations of scattering of fully polydisperse silica nanoparticle aggregates. At low silica concentrations (1 vol. %), the impact of the matrix chain mass on the structure is quantified in terms of the aggregation number distribution function, highest mass leading to individual dispersion, whereas the lower masses favor the formation of small aggregates. Both simulations for SAXS and TEM give compatible aggregate compacities around 10 vol. %, indicating that the construction algorithm for aggregates is realistic. Our results on structure are rationalized in terms of the critical collision time between nanoparticles due to diffusion in viscous matrices. At higher concentrations, aggregates overlap and form a percolated network, with a smaller and lighter mesh in the presence of high mass polymers. The linear rheology is investigated with oscillatory shear experiments. It shows a feature related to the silica structure at low frequencies, the amplitude of which can be described by two power laws separated by the percolation threshold of aggregates