The modelled occurrence of non-thermal plasma in the ionospheric F-region and the possible consequences for ion outflows into the magnetosphere

A global, time-dependent, three-dimensional, coupled ionosphere-thermosphere model is used to predict the spatial distribution of non-thermal plasma in the F-layer. It is shown that, even for steady-state conditions with Kp as low as 3, the difference between the ion and neutral velocities often exceeds the neutral thermal speed by a factor, D', which can be as large as 4. Theoretically, highly non-Maxwellian, and probably toroidal, ion velocity distributions are expected when D' exceeds about 1.5. The lack of response of the neutral winds to sunward ion drifts in the dawn sector of the auroral oval cause this to be the region most likely to contain toroidal distributions. The maximum in D' is found in the throat region of the convection pattern, where the strong neutral winds of the afternoon sector meet the eastward ion flows of the morning sector. These predictions are of interest, not only to radar scientists searching for non-thermal ionospheric plasma, but also as one possible explanation of the initial heating and upward flows of ions in the cleft ion fountain and nightside auroral oval, both of which are a major source of plasma for the magnetosphere.

Bacterial motility confers fitness advantage in the presence of phages

Dispersal provides the opportunity to escape harm and colonize new patches, enabling populations to expand and persist. However, the benefits of dispersal associated with escaping harm will be dependent on the structure of the environment and the likelihood of escape. Here, we empirically investigate how the spatial distribution of a parasite influences the evolution of host dispersal. Bacteriophages are a strong and common threat for bacteria in natural environments and offer a good system with which to explore parasite-mediated selection on host dispersal. We used two transposon mutants of the opportunistic bacteria, Pseudomonas aeruginosa, which varied in their motility (a disperser and a nondisperser), and the lytic bacteriophage ФKZ. The phage was distributed either in the central point of colony inoculation only, thus offering an escape route for the dispersing bacteria; or, present throughout the agar, where benefits of dispersal might be lost. Surprisingly, we found dispersal to be equally advantageous under both phage conditions relative to when phages were absent. A general explanation is that dispersal decreased the spatial structuring of host population, reducing opportunities for parasite transmission, but other more idiosyncratic mechanisms may also have contributed. This study highlights the crucial role the parasites can play on the evolution of dispersal and, more specifically, that bacteriophages, which are ubiquitous, are likely to select for bacterial motility.

A land cover map of Latin America and the Caribbean in the framework of the SERENA project

Land cover maps at different resolutions and mapping extents contribute to modeling and support decision making processes. Because land cover affects and is affected by climate change, it is listed among the 13 terrestrial essential climate variables. This paper describes the generation of a land cover map for Latin America and the Caribbean (LAC) for the year 2008. It was developed in the framework of the project Latin American Network for Monitoring and Studying of Natural Resources (SERENA), which has been developed within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLaTIF). The SERENA land cover map for LAC integrates: 1) the local expertise of SERENA network members to generate the training and validation data, 2) a methodology for land cover mapping based on decision trees using MODIS time series, and 3) class membership estimates to account for pixel heterogeneity issues. The discrete SERENA land cover product, derived from class memberships, yields an overall accuracy of 84% and includes an additional layer representing the estimated per-pixel confidence. The study demonstrates in detail the use of class memberships to better estimate the area of scarce classes with a scattered spatial distribution. The land cover map is already available as a printed wall map and will be released in digital format in the near future. The SERENA land cover map was produced with a legend and classification strategy similar to that used by the North American Land Change Monitoring System (NALCMS) to generate a land cover map of the North American continent, that will allow to combine both maps to generate consistent data across America facilitating continental monitoring and modeling

Probabilistic skill in ensemble seasonal forecasts

Simulation models are widely employed to make probability forecasts of future conditions on seasonal to annual lead times. Added value in such forecasts is reflected in the information they add, either to purely empirical statistical models or to simpler simulation models. An evaluation of seasonal probability forecasts from the Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction (DEMETER) and ENSEMBLES multi-model ensemble experiments is presented. Two particular regions are considered: Nino3.4 in the Pacific and the Main Development Region in the Atlantic; these regions were chosen before any spatial distribution of skill was examined. The ENSEMBLES models are found to have skill against the climatological distribution on seasonal time-scales. For models in ENSEMBLES that have a clearly defined predecessor model in DEMETER, the improvement from DEMETER to ENSEMBLES is discussed. Due to the long lead times of the forecasts and the evolution of observation technology, the forecast-outcome archive for seasonal forecast evaluation is small; arguably, evaluation data for seasonal forecasting will always be precious. Issues of information contamination from in-sample evaluation are discussed and impacts (both positive and negative) of variations in cross-validation protocol are demonstrated. Other difficulties due to the small forecast-outcome archive are identified. The claim that the multi-model ensemble provides a ‘better’ probability forecast than the best single model is examined and challenged. Significant forecast information beyond the climatological distribution is also demonstrated in a persistence probability forecast. The ENSEMBLES probability forecasts add significantly more information to empirical probability forecasts on seasonal time-scales than on decadal scales. Current operational forecasts might be enhanced by melding information from both simulation models and empirical models. Simulation models based on physical principles are sometimes expected, in principle, to outperform empirical models; direct comparison of their forecast skill provides information on progress toward that goal.

Quantifying sources of inter-model diversity in the cloud albedo effect

There is large diversity in simulated aerosol forcing among models that participated in the fifth Coupled Model Intercomparison Project (CMIP5), particularly related to aerosol interactions with clouds. Here we use the reported model data and fitted aerosol-cloud relations to separate the main sources of inter-model diversity in the magnitude of the cloud albedo effect. There is large diversity in the global load and spatial distribution of sulfate aerosol, as well as in global-mean cloud-top effective radius. The use of different parameterizations of aerosol-cloud interactions makes the largest contribution to diversity in modeled radiative forcing (up to -39%, +48% about the mean estimate). Uncertainty in pre-industrial sulfate load also makes a substantial contribution (-15%, +61% about the mean estimate), with smaller contributions from inter-model differences in the historical change in sulfate load and in mean cloud fraction.

The greening of Arabia: multiple opportunities for human occupation of the Arabian peninsula during the Late Pleistocene inferred from an ensemble of climate model simulations

Climate models are potentially useful tools for addressing human dispersals and demographic change. The Arabian Peninsula is becoming increasingly significant in the story of human dispersals out of Africa during the Late Pleistocene. Although characterised largely by arid environments today, emerging climate records indicate that the peninsula was wetter many times in the past, suggesting that the region may have been inhabited considerably more than hitherto thought. Explaining the origins and spatial distribution of increased rainfall is challenging because palaeoenvironmental research in the region is in an early developmental stage. We address environmental oscillations by assembling and analysing an ensemble of five global climate models (CCSM3, COSMOS, HadCM3, KCM, and NorESM). We focus on precipitation, as the variable is key for the development of lakes, rivers and savannas. The climate models generated here were compared with published palaeoenvironmental data such as palaeolakes, speleothems and alluvial fan records as a means of validation. All five models showed, to varying degrees, that the Arabia Peninsula was significantly wetter than today during the Last Interglacial (130 ka and 126/125 ka timeslices), and that the main source of increased rainfall was from the North African summer monsoon rather than the Indian Ocean monsoon or from Mediterranean climate patterns. Where available, 104 ka (MIS 5c), 56 ka (early MIS 3) and 21 ka (LGM) timeslices showed rainfall was present but not as extensive as during the Last Interglacial. The results favour the hypothesis that humans potentially moved out of Africa and into Arabia on multiple occasions during pluvial phases of the Late Pleistocene.

Sea level extremes at the coasts of China

Hourly sea level records from 1954 to 2012 at 20 tide gauges at and adjacent to the Chinese coasts are used to analyze extremes in sea level and in tidal residual. Tides and tropical cyclones determine the spatial distribution of sea level maxima. Tidal residual maxima are predominantly determined by tropical cyclones. The 50 year return level is found to be sensitive to the number of extreme events used in the estimation. This is caused by the small number of tropical cyclone events happening each year which lead to other local storm events included thus significantly affecting the estimates. Significant increase in sea level extremes is found with trends in the range between 2.0 and 14.1 mm yr−1. The trends are primarily driven by changes in median sea level but also linked with increases in tidal amplitudes at three stations. Tropical cyclones cause significant interannual variations in the extremes. The interannual variability in the sea level extremes is also influenced by the changes in median sea level at the north and by the 18.6 year nodal cycle at the South China Sea. Neither of PDO and ENSO is found to be an indicator of changes in the size of extremes, but ENSO appears to regulate the number of tropical cyclones that reach the Chinese coasts. Global mean atmospheric temperature appears to be a good descriptor of the interannual variability of tidal residual extremes induced by tropical cyclones but the trend in global temperature is inconsistent with the lack of trend in the residuals.

Sensitivity of terrestrial precipitation trends to the structural evolution of sea surface temperatures

Pronounced intermodel differences in the projected response of land surface precipitation (LSP) to future anthropogenic forcing remain in the Coupled Model Intercomparison Project Phase 5 model integrations. A large fraction of the intermodel spread in projected LSP trends is demonstrated here to be associated with systematic differences in simulated sea surface temperature (SST) trends, especially the representation of changes in (i) the interhemispheric SST gradient and (ii) the tropical Pacific SSTs. By contrast, intermodel differences in global mean SST, representative of differing global climate sensitivities, exert limited systematic influence on LSP patterns. These results highlight the importance to regional terrestrial precipitation changes of properly simulating the spatial distribution of large-scale, remote changes as reflected in the SST response to increasing greenhouse gases. Moreover, they provide guidance regarding which region-specific precipitation projections may be potentially better constrained for use in climate change impact assessments.

A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links

Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.

An ASIFT-based local registration method for satellite imagery

Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs) are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT) was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC) algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion). Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM) algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE) and better distribution of feature points.

A new governance perspective on port–hinterland relationships: the Port Hinterland Impact (PHI) matrix

We develop a new governance perspective on port–hinterland linkages and related port impacts. Many stakeholders in a port’s hinterland now demand tangible economic benefits from port activities, as a precondition for supporting port expansion and infrastructural investments. We use a governance lens to assess this farsighted contracting challenge. We find that most contemporary economic impact assessments of port investment projects pay scant attention to the contractual relationship challenges in port-hinterland relationships. In contrast, we focus explicitly on the spatial distribution of such impacts and the related contractual relationship issues facing port authorities or port users and their stakeholders in the port hinterland. We introduce a new concept, the Port Hinterland Impact (PHI) matrix, which focuses explicitly on the spatial distribution of port impacts and related contractual relationship challenges. The PHI matrix offers insight into port impacts using two dimensions: logistics dedicatedness, as an expression of Williamsonian asset specificity in the sphere of logistics contractual relationships, and geographic reach, with a longer reach typically reflecting the need for more complex contacting to overcome ‘distance’ challenges with external stakeholders. We use the PHI matrix in our empirical, governance-based analysis of contractual relationships between the port authorities in Antwerp and Zeebrugge, and their respective stakeholders.

Sampling and analyzing metals in soils for archaeological prospection: a critique

This paper presents a critique of current methods of sampling and analyzing soils for metals in archaeological prospection. Commonly used methodologies in soil science are shown to be suitable for archaeological investigations, with a concomitant improvement in their resolution. Understanding the soil-fraction location, concentration range, and spatial distribution of autochthonous (native) soil metals is shown to be a vital precursor to archaeological-site investigations, as this is the background upon which anthropogenic deposition takes place. Nested sampling is suggested as the most cost-effective method of investigating the spatial variability in the autochthonous metal concentrations. The use of the appropriate soil horizon (or sampling depth) and point sampling are critical in the preparation of a sampling regime. Simultaneous extraction is proposed as the most efficient method of identifying the location and eventual fate of autochthonous and anthropogenic metals, respectively.

Ungulate behavioral responses to the heterogeneous road-network of a touristic protected area in Africa

Understanding how wildlife responds to road and traffic is essential for effective conservation. Yet, not many studies have evaluated how roads influence wildlife in protected areas, particularly within the large iconic African National Parks where tourism is mainly based on sightings from motorized vehicles with the consequent development and intense use of roads. To reduce this knowledge gap, we studied the behavioral response and local spatial distribution of impala Aepyceros melampus along the heterogeneous (with variation in road surface type and traffic intensity) road-network of Kruger National Park (KNP, South Africa). We surveyed different types of roads (paved and unpaved) recording the occurrence of flight responses among sighted impala and describing their local spatial distribution (in relation to the roads). We observed relatively few flight responses (19.5% of 118 observations), suggesting impalas could be partly habituated to vehicles in KNP. In addition, impala local distribution is apparently unaffected by unpaved roads, yet animals seem to avoid the close proximity of paved roads. Overall, our results suggest a negative, albeit small, effect of traffic intensity, and of presence of pavement on roads on the behavior of impala at KNP. Future studies would be necessary to understand how roads influence other species, but our results show that even within a protected area that has been well-visited for a long time, wildlife can still be affected by roads and traffic. This result has ecological (e.g., changes in spatial distribution of fauna) and management implications (e.g., challenges of facilitating wildlife sightings while minimizing disturbance) for protected areas where touristic activities are largely based on driving.

Which intrinsic traits predict vulnerability to extinction depends on the actual threatening processes

Understanding what makes some species more vulnerable to extinction than others is an important challenge for conservation. Many comparative analyses have addressed this issue exploring how intrinsic and extrinsic traits associate with general estimates of vulnerability. However, these general estimates do not consider the actual threats that drive species to extinction and hence, are more difficult to translate into effective management. We provide an updated description of the types and spatial distribution of threats that affect mammals globally using data from the IUCN for 5941 species of mammals. Using these data we explore the links between intrinsic species traits and specific threats in order to identify key intrinsic features associated with particular drivers of extinction. We find that families formed by small-size habitat specialists are more likely to be threatened by habitat-modifying processes; whereas, families formed by larger mammals with small litter sizes are more likely to be threatened by processes that directly affect survival. These results highlight the importance of considering the actual threatening process in comparative studies. We also discuss the need to standardize and rank threat importance in global assessments such as the IUCN Red List to improve our ability to understand what makes some species more vulnerable to extinction than others.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.