Large-scale land acquisition and its effects on the water balance in investor and host countries

This study examines the validity of the assumption that international large-scale land acquisition (LSLA) is motivated by the desire to secure control over water resources, which is commonly referred to as ‘water grabbing’. This assumption was repeatedly expressed in recent years, ascribing the said motivation to the Gulf States in particular. However, it must be considered of hypothetical nature, as the few global studies conducted so far focused primarily on the effects of LSLA on host countries or on trade in virtual water. In this study, we analyse the effects of 475 intended or concluded land deals recorded in the Land Matrix database on the water balance in both host and investor countries. We also examine how these effects relate to water stress and how they contribute to global trade in virtual water. The analysis shows that implementation of the LSLAs in our sample would result in global water savings based on virtual water trade. At the level of individual LSLA host countries, however, water use intensity would increase, particularly in 15 sub-Saharan states. From an investor country perspective, the analysis reveals that countries often suspected of using LSLA to relieve pressure on their domestic water resources—such as China, India, and all Gulf States except Saudi Arabia—invest in agricultural activities abroad that are less water-intensive compared to their average domestic crop production. Conversely, large investor countries such as the United States, Saudi Arabia, Singapore, and Japan are disproportionately externalizing crop water consumption through their international land investments. Statistical analyses also show that host countries with abundant water resources are not per se favoured targets of LSLA. Indeed, further analysis reveals that land investments originating in water-stressed countries have only a weak tendency to target areas with a smaller water risk.

Grabbing or investment? On judging large-scale land acquisitions

Although analyses of large-scale land acquisitions (LSLA) often contain an explicit or implicit normative judgment about such projects, they rarely deduce such judgment from a nuanced balancing of pros and cons. This paper uses assessments about a well-researched LSLA in Sierra Leone to show that a utilitarian approach tends to lead to the conclusion that positive effects prevail, whereas deontological approaches lead to an emphasis on negative aspects. LSLA are probably the most radical land-use change in the history of humankind. This process of radical transformation poses a challenge for balanced evaluations. Thus, we line out a framework that focuses on the options of local residents but sets boundaries of acceptability through the core contents of human rights. In addition, systemic implications of a project need to be regarded.

Large-scale dust jets in the coma of 67P/Churyumov-Gerasimenko as seen by the OSIRIS instrument onboard Rosetta

Context. During the most recent perihelion passage in 2009 of comet 67P/Churyumov-Gerasimenko (67P), ground-based observations showed an anisotropic dust coma where jet-like features were detected at similar to 1.3 AU from the Sun. The current perihelion passage is exceptional as the Rosetta spacecraft is monitoring the nucleus activity since March 2014, when a clear dust coma was already surrounding the nucleus at 4.3 AU from the Sun. Subsequently, the OSIRIS camera also witnessed an outburst in activity between April 27 and 30, and since mid-July, the dust coma at rh similar to 3.7-3.6 AU preperihelion is clearly non-isotropic, pointing to the existence of dust jet-like features. Aims. We aim to ascertain on the nucleus surface the origin of the dust jet-like features detected as early as in mid-July 2014. This will help to establish how the localized comet nucleus activity compares with that seen in previous apparitions and will also help following its evolution as the comet approaches its perihelion, at which phase most of the jets were detected from ground-based observations. Determining these areas also allows locating them in regions on the nucleus with spectroscopic or geomorphological distinct characteristics. Methods. Three series of dust images of comet 67P obtained with the Wide Angle Camera (WAC) of the OSIRIS instrument onboard the Rosetta spacecraft were processed with different enhancement techniques. This was made to clearly show the existence of jet-like features in the dust coma, whose appearance toward the observer changed as a result of the rotation of the comet nucleus and of the changing observing geometry from the spacecraft. The position angles of these features in the coma together with information on the observing geometry, nucleus shape, and rotation, allowed us to determine the most likely locations on the nucleus surface where the jets originate from. Results. Geometrical tracing of jet sources indicates that the activity of the nucleus of 67P gave rise during July and August 2014 to large-scale jet-like features from the Hapi, Hathor, Anuket, and Aten regions, confirming that active regions may be present on the nucleus localized at 60. northern latitude as deduced from previous comet apparitions. There are also hints that large-scale jets observed from the ground are possibly composed, at their place of origin on the nucleus surface, of numerous small-scale features.

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

Dissolved organic matter molecular composition and concentrations from a large scale mesocosm study KOSMOS 2013 Kristineberg) on ocean acidification

Marine dissolved organic matter (DOM) represents one of the largest active carbon reservoirs on Earth. Changes in pool size or composition could have major impacts on the global carbon cycle. Ocean acidification is a potential driver for these changes because it influences marine primary production and heterotrophic respiration. Here we show that ocean acidification as expected for a 'business-as-usual' emission scenario in the year 2100 (900 µatm) does not affect the DOM pool with respect to its size and molecular composition. We applied ultrahigh-resolution mass spectrometry to monitor the production and turnover of 7,360 distinct molecular DOM features in an unprecedented long-term mesocosm study in a Swedish Fjord, covering a full cycle of marine production. DOM concentration and molecular composition did not differ significantly between present-day and year 2100 CO2 levels. Our findings are likely applicable to other coastal and productive marine ecosystems in general.

Wave height (regular and irregular waves) reduction in 2m water depth over a 40-m-long salt marsh test section in a large scale laboratory flume

Coastal communities around the world face increasing risk from flooding as a result of rising sea level, increasing storminess, and land subsidence. Salt marshes can act as natural buffer zones, providing protection from waves during storms. However, the effectiveness of marshes in protecting the coastline during extreme events when water levels and waves are highest is poorly understood. Here, we experimentally assess wave dissipation under storm surge conditions in a 300-m-long wave flume that contains a transplanted section of natural salt marsh. We find that the presence of marsh vegetation causes considerable wave attenuation, even when water levels and waves are high. From a comparison with experiments without vegetation, we estimate that up to 60% of observed wave reduction is attributed to vegetation. We also find that although waves progressively flatten and break vegetation stems and thereby reduce dissipation, the marsh substrate remained remarkably stable and resistant to surface erosion under all conditions.The effectiveness of storm wave dissipation and the resilience of tidal marshes even at extreme conditions suggest that salt marsh ecosystems can be a valuable component of coastal protection schemes.

Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model

The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

An Experimental Platform for large-scale research facing FI-IoT scenarios

Providing experimental facilities for the Internet of Things (IoT) world is of paramount importance to materialise the Future Internet (FI) vision. The level of maturity achieved at the networking level in Sensor and Actuator networks (SAN) justifies the increasing demand on the research community to shift IoT testbed facilities from the network to the service and information management areas. In this paper we present an Experimental Platform fulfilling these needs by: integrating heterogeneous SAN infrastructures in a homogeneous way; providing mechanisms to handle information, and facilitating the development of experimental services. It has already been used to deploy applications in three different field trials: smart metering, smart places and environmental monitoring and it will be one of the components over which the SmartSantander project, that targets a large-scale IoT experimental facility, will rely on

A big data platform for large scale event processing

To date, big data applications have focused on the store-and-process paradigm. In this paper we describe an initiative to deal with big data applications for continuous streams of events. In many emerging applications, the volume of data being streamed is so large that the traditional ‘store-then-process’ paradigm is either not suitable or too inefficient. Moreover, soft-real time requirements might severely limit the engineering solutions. Many scenarios fit this description. In network security for cloud data centres, for instance, very high volumes of IP packets and events from sensors at firewalls, network switches and routers and servers need to be analyzed and should detect attacks in minimal time, in order to limit the effect of the malicious activity over the IT infrastructure. Similarly, in the fraud department of a credit card company, payment requests should be processed online and need to be processed as quickly as possible in order to provide meaningful results in real-time. An ideal system would detect fraud during the authorization process that lasts hundreds of milliseconds and deny the payment authorization, minimizing the damage to the user and the credit card company.

A non-perturbative Kolmogorov turbulence approach to the cosmic web structure

The Kolmogorov approach to turbulence is applied to the Burgers turbulence in the stochastic adhesion model of large-scale structure formation. As the perturbative approach to this model is unreliable, here a new, non-perturbative approach, based on a suitable formulation of Kolmogorov's scaling laws, is proposed. This approach suggests that the power-law exponent of the matter density two-point correlation function is in the range 1–1.33, but it also suggests that the adhesion model neglects important aspects of the gravitational dynamics.