Effects of different soil management practices on soil mechanic resistance and seed depth placement in a maize crop in Alentejo, Portugal Mediterranean region.

No tillage, minimum tillage and conventional tillage practices are commonly used in maize crops in Alentejo, affecting soil physic conditions and determining seeders performance. Seeders distribution can be evaluated in the longitudinal and vertical planes. Vertical plane is specified by seeding depth (Karayel et al., 2008). If, in one hand seeding depth uniformity is a goal for all crop establishment , in the other hand, seeders furrow openers depth control is never constant depending on soil conditions. Seed depth uniformity affects crop emergence, Liu et al. (2004) showed an higher correlation between crop productivity and emergence uniformity than with longitudinal plants distribution. Neto et al. (2007) evaluating seed depth placement by measuring maize mesocotyl length under no tillage conditions in 38 farms concluded that 20% of coefficient of variation suggests the need of improvement seeders depth control mechanisms. The objective of this study was to evaluate casual relationships and create spatial variability maps between soil mechanic resistance and vertical distribution under three different soil practices to improve seed depth uniformity.

Amphibian Hotspots and Conservation Priorities in Eastern Cuba Identified by Species Distribution Modeling

The high rate of amphibian endemism and the severe habitat modification in the Caribbean islands make them an ideal place to test if the current protected areas network might protect this group. In this study, we model distribution and map species richness of the 40 amphibian species from eastern Cuba with the objectives of identify hotspots, detect gaps in species representation in protected areas, and select additional areas to fill these gaps. We used two modeling methods, Maxent and Habitat Suitability Models, to reach a consensus distribution map for each species, then calculate species richness by combining specific models and finally performed gap analyses for species and hotspots. Our results showed that the models were robust enough to predict species distributions and that most of the amphibian hotspots were represented in reserves, but 50 percent of the species were incompletely covered and Eleutherodactylus rivularis was totally uncovered by the protected areas. We identified 1441 additional km2 (9.9% of the study area) that could be added to the current protected areas, allowing the representation of every species and all hotspots. Our results are relevant for the conservation planning in other Caribbean islands, since studies like this could contribute to fill the gaps in the existing protected areas and to design a future network. Both cases would benefit from modeling amphibian species distribution using available data, even if they are incomplete, rather than relying only in the protection of known or suspected hotspots.

A software tool for accurate assessment of costs and CO2 emissions in wood transport using OpenStreetMap©

Costs and environmental impacts are key elements in forest logistics and they must be integrated in forest decision-making. The evaluation of transportation fuel costs and carbon emissions depend on spatial and non-spatial data but in many cases the former type of data are dicult to obtain. On the other hand, the availability of software tools to evaluate transportation fuel consumption as well as costs and emissions of carbon dioxide is limited. We developed a software tool that combines two empirically validated models of truck transportation using Digital Elevation Model (DEM) data and an open spatial data tool, specically OpenStreetMap©. The tool generates tabular data and spatial outputs (maps) with information regarding fuel consumption, cost and CO2 emissions for four types of trucks. It also generates maps of the distribution of transport performance indicators (relation between beeline and real road distances). These outputs can be easily included in forest decision-making support systems. Finally, in this work we applied the tool in a particular case of forest logistics in north-eastern Portugal

Factores determinantes de la variabilidad espacial de anchoveta peruana (Engraulis ringens) en el Pacífico Sudoriental

Los modelos de nicho ecológico permiten estudiar el efecto del ambiente sobre la distribución de las especies, relacionando datos de su distribución con información ambiental. El objetivo del presente estudio fue estimar el nicho ecológico y describir la variabilidad en la distribución espacial de la anchoveta (Engraulis ringens) mediante el uso de modelos estadísticos de nicho ecológico. Se trabajó con dos enfoques de análisis: por stocks (norte, centro y sur) en el Pacífico Sudoriental (PSO) y por estadios de desarrollo (pre-reclutas, reclutas y adultos) en la costa peruana. El modelo de nicho ecológico utilizó modelos aditivos generalizados, estimaciones georeferenciadas de presencia y ausencia de anchoveta e información de cuatro variables ambientales (temperatura superficial del mar, salinidad superficial del mar, concentración de clorofila a superficial y la profundidad de la oxiclina) entre los a˜nos 1985 y 2008. Se encontró que no existen diferencias en los nichos ecológicos de los tres stocks de anchoveta siendo los modelos que utilizaron la información de la anchoveta en todo el PSO los que lograron modelar el nicho de manera correcta. Respecto al análisis por estadios, se evidenció que cada estadio de desarrollo tiene distintas tolerancias a las variables ambientales consideradas en este trabajo, siendo los nichos de estadios menos desarrollados los que estuvieron incluidos dentro de los estadios más desarrollados. Se recomienda realizar estudios separados para cada estadio de desarrollo, lo cual permita comprender mejor las relaciones ecológicas encontradas en los resultados del nicho ecológico. Además se recomienda realizar simulaciones con modelos de nicho que incluyan más variables ambientales, las cuales puedan mejorar los mapas de distribución espacial de la anchoveta para los dos enfoques de análisis.

Shell preservation of Limacina inflata in surface sediments of the Central and South Atlantic

Over 300 surface sediment samples from the Central and South Atlantic Ocean and the Caribbean Sea were investigated for the preservation state of the aragonitic test of Limacina inflata. Results are displayed in spatial distribution maps and are plotted against cross-sections of vertical water mass configurations, illustrating the relationship between preservation state, saturation state of the overlying waters, and overall water mass distribution. The microscopic investigation of L. inflata (adults) yielded the Limacina dissolution index (LDX), and revealed three regional dissolution patterns. In the western Atlantic Ocean, sedimentary preservation states correspond to saturation states in the overlying waters. Poor preservation is found within intermediate water masses of southern origin (i.e. Antarctic intermediate water (AAIW), upper circumpolar water (UCDW)), which are distinctly aragonite-corrosive, whereas good preservation is observed within the surface waters above and within the upper North Atlantic deep water (UNADW) beneath the AAIW. In the eastern Atlantic Ocean, in particular along the African continental margin, the LDX fails in most cases (i.e. less than 10 tests of L. inflata per sample were found). This is most probably due to extensive "metabolic" aragonite dissolution at the sediment-water interface combined with a reduced abundance of L. inflata in the surface waters. In the Caribbean Sea, a more complex preservation pattern is observed because of the interaction between different water masses, which invade the Caribbean basins through several channels, and varying input of bank-derived fine aragonite and magnesian calcite material. The solubility of aragonite increases with increasing pressure, but aragonite dissolution in the sediments does not simply increase with water depth. Worse preservation is found in intermediate water depths following an S-shaped curve. As a result, two aragonite lysoclines are observed, one above the other. In four depth transects, we show that the western Atlantic and Caribbean LDX records resemble surficial calcium carbonate data and delta13C and carbonate ion concentration profiles in the water column. Moreover, preservation of L. inflata within AAIW and UCDW improves significantly to the north, whereas carbonate corrosiveness diminishes due to increased mixing of AAIW and UNADW. The close relationship between LDX values and aragonite contents in the sediments shows much promise for the quantification of the aragonite loss under the influence of different water masses. LDX failure and uncertainties may be attributed to (1) aragonite dissolution due to bottom water corrosiveness, (2) aragonite dissolution due to additional CO2 release into the bottom water by the degradation of organic matter based on an enhanced supply of organic matter into the sediment, (3) variations in the distribution of L. inflata and hence a lack of supply into the sediment, (4) dilution of the sediments and hence a lack of tests of L. inflata, or (5) redeposition of sediment particles.

Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR)

Interferometric synthetic aperture radar (InSAR) techniques can successfully detect phase variations related to the water level changes in wetlands and produce spatially detailed high-resolution maps of water level changes. Despite the vast details, the usefulness of the wetland InSAR observations is rather limited, because hydrologists and water resources managers need information on absolute water level values and not on relative water level changes. We present an InSAR technique called Small Temporal Baseline Subset (STBAS) for monitoring absolute water level time series using radar interferograms acquired successively over wetlands. The method uses stage (water level) observation for calibrating the relative InSAR observations and tying them to the stage's vertical datum. We tested the STBAS technique with two-year long Radarsat-1 data acquired during 2006–2008 over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). The InSAR-derived water level data were calibrated using 13 stage stations located in the study area to generate 28 successive high spatial resolution maps (50 m pixel resolution) of absolute water levels. We evaluate the quality of the STBAS technique using a root mean square error (RMSE) criterion of the difference between InSAR observations and stage measurements. The average RMSE is 6.6 cm, which provides an uncertainty estimation of the STBAS technique to monitor absolute water levels. About half of the uncertainties are attributed to the accuracy of the InSAR technique to detect relative water levels. The other half reflects uncertainties derived from tying the relative levels to the stage stations' datum.

Compréhension des différences de distribution spatiale des anchois et de leurs œufs

La campagne PELGAS participe à la gestion du stock d’anchois du Golfe de Gascogne, en réalisant une évaluation directe à la mer de la biomasse d’anchois. Pour déterminer la biomasse totale, des appareils acoustiques envoyant des ultra-sons dans l’eau pour détecter les bancs de poisson sont utilisés. Ensuite des pêches sont effectuées sur les zones détectées pour déterminer la composition des bancs (espèces, poids, longueurs…). En parallèle, les oeufs d’anchois sont comptés. A partir des données récoltées de 2000 à 2015, j’ai pu réaliser des cartes de distribution spatiale des anchois et de leurs oeufs, ainsi que des analyses statistiques afin de comprendre les différences de distribution entre les deux. Il s’avère que les oeufs sont plus au large que les anchois, ce qui est dû à une question de poids moyen et de fécondité. Les anchois les plus gros seraient plus féconds et se localisent plus au large, d’où la répartition des oeufs plus éloignées des côtes que la biomasse totale d’anchois. La fécondité et le poids des anchois font parties des paramètres qui ont une influence sur la distribution des oeufs.

The role of environmental factors in the spatial distribution of Japanese encephalitis in mainland China

Japanese encephalitis (JE) is the most common cause of viral encephalitis and an important public health concern in the Asia-Pacific region, particularly in China where 50% of global cases are notified. To explore the association between environmental factors and human JE cases and identify the high risk areas for JE transmission in China, we used annual notified data on JE cases at the center of administrative township and environmental variables with a pixel resolution of 1 km×1 km from 2005 to 2011 to construct models using ecological niche modeling (ENM) approaches based on maximum entropy. These models were then validated by overlaying reported human JE case localities from 2006 to 2012 onto each prediction map. ENMs had good discriminatory ability with the area under the curve (AUC) of the receiver operating curve (ROC) of 0.82-0.91, and low extrinsic omission rate of 5.44-7.42%. Resulting maps showed JE being presented extensively throughout southwestern and central China, with local spatial variations in probability influenced by minimum temperatures, human population density, mean temperatures, and elevation, with contribution of 17.94%-38.37%, 15.47%-21.82%, 3.86%-21.22%, and 12.05%-16.02%, respectively. Approximately 60% of JE cases occurred in predicted high risk areas, which covered less than 6% of areas in mainland China. Our findings will help inform optimal geographical allocation of the limited resources available for JE prevention and control in China, find hidden high-risk areas, and increase the effectiveness of public health interventions against JE transmission.

Constructing abstract maps from spatial descriptions for goal-directed exploration

This paper describes ongoing work on a system using spatial descriptions to construct abstract maps that can be used for goal-directed exploration in an unfamiliar office environment. Abstract maps contain membership, connectivity, and spatial layout information extracted from symbolic spatial information. In goal-directed exploration, the robot would then link this information with observed symbolic information and its grounded world representation. We demonstrate the ability of the system to extract and represent membership, connectivity, and spatial layout information from spatial descriptions of an office environment. In the planned study, the robot will navigate to the goal location using the abstract map to inform the best direction to explore in.

Landslide Susceptible Locations in Western Ghats: Prediction through openModeller

Many shallow landslides are triggered by heavy rainfall on hill slopes resulting in enormous casualties and huge economic losses in mountainous regions. Hill slope failure usually occurs as soil resistance deteriorates in the presence of the acting stress developed due to a number of reasons such as increased soil moisture content, change in land use causing slope instability, etc. Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration and information related to land surface susceptibility. Terrain analysis applications using spatial data such as aspect, slope, flow direction, compound topographic index, etc. along with information derived from remotely sensed data such as land cover / land use maps permit us to quantify and characterise the physical processes governing the landslide occurrence phenomenon. In this work, the probable landslide prone areas are predicted using two different algorithms – GARP (Genetic Algorithm for Rule-set Prediction) and Support Vector Machine (SVM) in a free and open source software package - openModeller. Several environmental layers such as aspect, digital elevation data, flow accumulation, flow direction, slope, land cover, compound topographic index, and precipitation data were used in modelling. A comparison of the simulated outputs, validated by overlaying the actual landslide occurrence points showed 92% accuracy with GARP and 96% accuracy with SVM in predicting landslide prone areas considering precipitation in the wettest month whereas 91% and 94% accuracy were obtained from GARP and SVM considering precipitation in the wettest quarter of the year.

Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii

The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.

Digital elevation models and GIS for watershed modelling and flood prediction-A case study of Accra Ghana

Geographical Information Systems (GIS) and Digital Elevation Models (DEM) can be used to perform many geospatial and hydrological modelling including drainage and watershed delineation, flood prediction and physical development studies of urban and rural settlements. This paper explores the use of contour data and planimetric features extracted from topographic maps to derive digital elevation models (DEMs) for watershed delineation and flood impact analysis (for emergency preparedness) of part of Accra, Ghana in a GIS environment. In the study two categories of DEMs were developed with 5 m contour and planimetric topographic data; bare earth DEM and built environment DEM. These derived DEMs were used as terrain inputs for performing spatial analysis and obtaining derivative products. The generated DEMs were used to delineate drainage patterns and watershed of the study area using ArcGIS desktop and its ArcHydro extension tool from Environmental Systems Research Institute (ESRI). A vector-based approach was used to derive inundation areas at various flood levels. The DEM of built-up areas was used as inputs for determining properties which will be inundated in a flood event and subsequently generating flood inundation maps. The resulting inundation maps show that about 80% areas which have perennially experienced extensive flooding in the city falls within the predicted flood extent. This approach can therefore provide a simplified means of predicting the extent of inundation during flood events for emergency action especially in less developed economies where sophisticated technologies and expertise are hard to come by. © 2009 Springer Netherlands.

Digital Elevation Models and GIS for watershed modelling and flood prediction - A case study of Accra Ghana

Geographical Information Systems (GIS) and Digital Elevation Models (DEM) can be used to perform many geospatial and hydrological modelling including drainage and watershed delineation, flood prediction and physical development studies of urban and rural settlements. This paper explores the use of contour data and planimetric features extracted from topographic maps to derive digital elevation models (DEMs) for watershed delineation and flood impact analysis (for emergency preparedness) of part of Accra, Ghana in a GIS environment. In the study two categories of DEMs were developed with 5 m contour and planimetric topographic data; bare earth DEM and built environment DEM. These derived DEMs were used as terrain inputs for performing spatial analysis and obtaining derivative products. The generated DEMs were used to delineate drainage patterns and watershed of the study area using ArcGIS desktop and its ArcHydro extension tool from Environmental Systems Research Institute (ESRI). A vector-based approach was used to derive inundation areas at various flood levels. The DEM of built-up areas was used as inputs for determining properties which will be inundated in a flood event and subsequently generating flood inundation maps. The resulting inundation maps show that about 80% areas which have perennially experienced extensive flooding in the city falls within the predicted flood extent. This approach can therefore provide a simplified means of predicting the extent of inundation during flood events for emergency action especially in less developed economies where sophisticated technologies and expertise are hard to come by. © Springer Science + Business Media B.V. 2009.

SpaciMS: spatial and temporal operando resolution of reactions within catalytic monoliths

Monolithic catalysts are widely used as structured catalysts, especially in the abatement of pollutants. Probing what happens inside these monoliths during operation is, therefore, vital for modelling and prediction of the catalyst behavior. SpaciMS is a spatially resolved capillary-inlet mass spectroscopy system allowing for the generation of spatially resolved maps of the reactions within monoliths. In this study SpaciMS results combined with 3D CFD modelling demonstrate that SpaciMS is a highly sensitive and minimally invasive technique that can provide reaction maps as well as catalytic temporal behavior. Herein we illustrate this by examining kinetic oscillations during a CO oxidation reaction over a Pt/Rh on alumina catalyst supported on a cordierite monolith. These oscillations were only observed within the monolith by SpaciMS between 30 and 90% CO conversion. Equivalent experiments performed in a plug-flow reactor using this catalyst in a crushed form over a similar range of reaction conditions did not display any oscillations demonstrating the importance of intra monolith analysis. This work demonstrates that the SpaciMS offers an accurate and comprehensive picture of structured catalysts under operation.