Species Richness-Environment Relationships of European Arthropods at Two Spatial Grains: Habitats and Countries

We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

Spatial and temporal analysis of land cover and landscape structure change in Zagros Forests

The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

Public Commons for Geospatial Data: A Conceptual Model

A wide variety of spatial data collection efforts are ongoing throughout local, state and federal agencies, private firms and non-profit organizations. Each effort is established for a different purpose but organizations and individuals often collect and maintain the same or similar information. The United States federal government has undertaken many initiatives such as the National Spatial Data Infrastructure, the National Map and Geospatial One-Stop to reduce duplicative spatial data collection and promote the coordinated use, sharing, and dissemination of spatial data nationwide. A key premise in most of these initiatives is that no national government will be able to gather and maintain more than a small percentage of the geographic data that users want and desire. Thus, national initiatives depend typically on the cooperation of those already gathering spatial data and those using GIs to meet specific needs to help construct and maintain these spatial data infrastructures and geo-libraries for their nations (Onsrud 2001). Some of the impediments to widespread spatial data sharing are well known from directly asking GIs data producers why they are not currently involved in creating datasets that are of common or compatible formats, documenting their datasets in a standardized metadata format or making their datasets more readily available to others through Data Clearinghouses or geo-libraries. The research described in this thesis addresses the impediments to wide-scale spatial data sharing faced by GIs data producers and explores a new conceptual data-sharing approach, the Public Commons for Geospatial Data, that supports user-friendly metadata creation, open access licenses, archival services and documentation of parent lineage of the contributors and value- adders of digital spatial data sets.

Geo-referenced photo-mosaics of the Menez Gwen Hydrothermal Vent (Mid-Atlantic Ridge)

The Menez Gwen hydrothermal vents, located on the flanks of a small young volcanic structure in the axial valley of the Menez Gwen seamount, are the shallowest known vent systems on the Mid-Atlantic Ridge that host chemosynthetic communities. Although visited several times by research cruises, very few images have been published of the active sites, and their spatial dimensions and morphologies remain difficult to comprehend. We visited the vents on the eastern flank of the small Menez Gwen volcano during cruises with RV Poseidon (POS402, 2010) and RV Meteor (M82/3, 2010), and used new bathymetry and imagery data to provide first detailed information on the extents, surface morphologies, spatial patterns of the hydrothermal discharge and the distribution of dominant megafauna of five active sites. The investigated sites were mostly covered by soft sediments and abundant white precipitates, and bordered by basaltic pillows. The hydrothermally-influenced areas of the sites ranged from 59 to 200 m**2. Geo-referenced photomosaics and video data revealed that the symbiotic mussel Bathymodiolus azoricus was the dominant species and present at all sites. Using literature data on average body sizes and biomasses of Menez Gwen B. azoricus, we estimated that the B. azoricus populations inhabiting the eastern flank sites of the small volcano range between 28,640 and 50,120 individuals with a total biomass of 50 to 380 kg wet weight. Based on modeled rates of chemical consumption by the symbionts, the annual methane and sulfide consumption by B. azoricus could reach 1760 mol CH4 yr**-1 and 11,060 mol H2S yr**-1. We propose that the chemical consumption by B. azoricus over at the Menez Gwen sites is low compared to the natural release of methane and sulfide via venting fluids.

Two historical maps from nineteenth-century Palestine, with links to digitized maps in shapefile format

Reconstructing past landscapes from historical maps requires quantifying the accuracy and completeness of these sources. The accuracy and completeness of two historical maps of the same period covering the same area in Israel were examined: the 1:63,360 British Palestine Exploration Fund map (1871-1877) and the 1:100,000 French Levés en Galilée (LG) map (1870). These maps cover the mountainous area of the Galilee (northern Israel), a region with significant natural and topographical diversity, and a long history of human presence. Land-cover features from both maps, as well as the contours drawn on the LG map, were digitized. The overall correspondence between land-cover features shown on both maps was 59% and we found that the geo-referencing method employed (transformation type and source of control points) did not significantly affect these correspondence measures. Both maps show that in the 1870s, 35% of the Galilee was covered by Mediterranean maquis, with less than 8% of the area used for permanent agricultural cropland (e.g., plantations). This article presents how the reliability of the maps was assessed by using two spatial historical sources, and how land-cover classes that were mapped with lower certainty and completeness are identified. Some of the causes that led to observed differences between the maps, including mapping scale, time of year, and the interests of the surveyors, are also identified.

Acoustic multi-frequency indicator of four major groups on a spatial grid in the Bay of Biscay

The first data set contains the mean and cofficient of variation (standard deviation divided by mean) of a multi-frequency indicator I derived from ER60 acoustic information collected at five frequencies (18, 38, 70, 120, and 200 kHz) in the Bay of Biscay in May of the years 2006, 2008, 2009 and 2010 (Pelgas surveys). The multi-frequency indicator was first calculated per voxel (20 m long × 5 m deep sampling unit) and then averaged on a spatial grid (approx. 20 nm × 20 nm) for five 5-m depth layers in the surface waters (10-15m, 15-20m, 20-25m, 25-30m below sea surface); there are missing values in particular in the shallowest layer. The second data set provides for each grid cell and depth layer the proportion of voxels for which the multi-frequency indicator I was indicative of a certain group of organisms. For this the following interpretation was used: I < 0.39 swim bladder fish or large gas bubbles, I = 0.39-0.58 small resonant bubbles present in gas bearing organisms such as larval fish and phytoplankton, I = 0.7-0.8 fluidlike zooplankton such as copepods and euphausiids, and I > 0.8 mackerel. These proportions can be interpreted as a relative abundance index for each of the four organism groups.

Spatial compartmentalization of free radical formation and mitochondrial heterogeneity in bivalve gills revealed by live-imaging techniques, supplementary material

Live-imaging techniques (LIT) utilize target-specific fluorescent dyes to visualize biochemical processes using confocal and multiphoton scanning microscopy, which are increasingly employed as non-invasive approach to physiological in-vivo and ex-vivo studies. Here we report application of LIT to bivalve gills for ex-vivo analysis of gill physiology and mapping of reactive oxygen (ROS) and nitrogen (RNS) species formation in the living tissue. Our results indicate that H2O2, HOO. and ONOO- radicals (assessed through C-H2DFFDA staining) are mainly formed within the blood sinus of the filaments and are likely to be produced by hemocytes as defense against invading pathogens. The oxidative damage in these areas is controlled by enhanced CAT (catalase) activities recorded within the filaments. The outermost areas of the ciliated epithelial cells composing the filaments, concentrated the highest mitochondrial densities (MTK Deep Red 633 staining) and the most acidic pH values (as observed with ageladine-a). These mitochondria have low (depolarized) membrane potentials (D psi m) (JC-1 staining), suggesting that the high amounts of ATP required for ciliary beating may be in part produced by non-mitochondrial mechanisms, such as the enzymatic activity of an ATP-regenerating kinase. Nitric oxide (NO, DAF-2DA staining) produced in the region of the peripheral mitochondria may have an effect on mitochondrial electron transport and possibly cause the low membrane potential. High DAF-2DA staining was moreover observed in the muscle cells composing the wall of the blood vessels where NO may be involved in regulating blood vessel diameter. On the ventral bend of the gills, subepithelial mucus glands (SMG) contain large mucous vacuoles showing higher fluorescence intensities for O2.- (DHE staining) than the rest of the tissue. Given the antimicrobial properties of superoxide, release of O2.- into the mucus may help to avoid the development of microbial biofilms on the gill surface. However, cells of the ventral bends are paying a price for this antimicrobial protection, since they show significantly higher oxidative damage, according to the antioxidant enzyme activities and the carbonyl levels, than the rest of the gill tissue. This study provides the first evidence that one single epithelial cell may contain mitochondria with significantly different membrane potentials. Furthermore, we provide new insight into ROS and RNS formation in ex-vivo gill tissues which opens new perspectives for unraveling the different ecophysiological roles of ROS and RNS in multifunctional organs such as gills.

Spatial and seasonal distribution of Thaumarchaeota in the water column and sediment of the southern North Sea

We have examined the spatial and seasonal distribution of Thaumarchaeota in the water column and sediment of the southern North Sea using the specific intact polar lipid (IPL) hexose, phosphohexose (HPH) crenarchaeol, as well as thaumarchaeotal 16S rRNA gene abundances and expression. In the water column, a higher abundance of Thaumarchaeota was observed in the winter season than in the summer, which is in agreement with previous studies, but this was not the case in the sediment where Thaumarchaeota were most abundant in spring and summer. This observation corresponds well with the idea that ammonia availability is a key factor in thaumarchaeotal niche determination. In the surface waters of the southern North Sea, we observed a spatial variability in HPH crenarchaeol, thaumarchaeotal 16S rRNA gene abundance and transcriptional activity that corresponded well with the different water masses present. In bottom waters, a clear differentiation based on water masses was not observed; instead, we suggest that observed differences in thaumarchaeotal abundance with depth may be related to resuspension from the sediment. This could be due to suspension of benthic Thaumarchaeota to the water column or due to delivery of e.g. resuspended sediment or ammonium to the water column, which could be utilized by pelagic Thaumarchaeota. This study has shown that the seasonality of Thaumarchaeota in water and sediment is different and highlights the importance of water masses, currents and sedimentary processes in determining the spatial abundance of Thaumarchaeota in the southern North Sea.

Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

Spatial distribution of isotopic compositions of Globigerina bulloides and Neogloboquadrina pachyderma (dex.) and the faunal assemblages of planktic foraminifera in surface sediment samples along the Chilean continental slope between 23°S and 44°S

We report on the spatial distribution of isotopic compositions of the two planktic foraminifera species Globigerina bulloides and Neogloboquadrina pachyderma (dex.), and the faunal assemblages of planktic foraminifera in 91 surface sediment samples along the Chilean continental slope between 23°S and 44°S. Both d13C and d18O data of N. pachyderma (dex.) show little variability in the study area. North of 39°S, the isotopic values of N. pachyderma (dex.) are heavier than those of G. bulloides, whereas south of 39°S, this relation inverses. This is indicative for a change from a well-mixed, deep thermocline caused by coastal upwelling north of 39°S to well-stratified water masses in a non-upwelling environment south of 39°S. In addition, the faunal composition of planktic foraminifera marks this change by transition from an upwelling assemblage north of 39°S to a high-nutrient-non-upwelling assemblage south of 39°S, which is characterized by decreased contributions of upwelling indicators such as G. bulloides, N. pachyderma (sin.), and Globigerinita glutinata. In general, we can conclude that food and light rather than temperature are the primary control of the planktic foraminiferal assemblage between 23°S and 44°S off Chile. Our data point to higher marine productivity at upwelling centers north of 25°S and at 30-33°S. South of 39°S, significant supply of nutrients by fluvial input most likely boosts the productivity.

Temporal and spatial LGM variability of biomarker records in the Arctic Ocean

Using the sea ice proxy IP25 and phytoplankton-derived biomarkers (brassicasterol and dinosterol) Arctic sea-ice conditions were reconstructed for Marine Isotope Stage (MIS) 3 to 1 in sediment cores from the north of Barents Sea continental margin across the Central Arctic to the Southern Mendeleev Ridge. Our results suggest more extensive sea-ice cover than present-day during MIS 3, increasing sea-ice growth during MIS 2 and decreased sea-ice cover during the last deglacial. The summer ice edge sustained north of the Barents Sea even during extremely cold (i.e., Last Glacial Maximum (LGM)) as well as warm periods (i.e., Bølling-Allerød). During the LGM, the western Svalbard margin and the northern Barents Sea margin areas were characterized by high concentrations of both IP25 and phytoplankton biomarkers, interpreted as a productive ice-edge situation, caused by the inflow of warm Atlantic Water. In contrast, the LGM high Arctic proper (north of 84°N) was covered by thick permanent sea ice throughout the year with rare break up, indicated by zero or near-zero biomarker concentrations. The spring/summer sea-ice margin significantly extended southwards to the southern Lomonosov Ridge and Mendeleev Ridge during the LGM. Our proxy reconstructions are very consistent with published model results based on the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM).

Map4rdf - Faceted Browser for Geospatial Datasets

Recently we have seen a large increase in the amount of geospatial data that is being published using RDF and Linked Data principles. Eorts such as the W3C Geo XG, and most recently the GeoSPARQL initiative are providing the necessary vocabularies to pub- lish this kind of information on the Web of Data. In this context it is necessary to develop applications that consume and take advantage of these geospatial datasets. In this paper we present map4rdf, a faceted browsing tool for exploring and visualizing RDF datasets enhanced with geospatial information.

Spatial Estimation of Sub-Hour Global Horizontal Irradiance Based on Official Observations and Remote Sensors.

This study was motivated by the need to improve densification of Global Horizontal Irradiance (GHI) observations, increasing the number of surface weather stations that observe it, using sensors with a sub-hour periodicity and examining the methods of spatial GHI estimation (by interpolation) with that periodicity in other locations. The aim of the present research project is to analyze the goodness of 15-minute GHI spatial estimations for five methods in the territory of Spain (three geo-statistical interpolation methods, one deterministic method and the HelioSat2 method, which is based on satellite images). The research concludes that, when the work area has adequate station density, the best method for estimating GHI every 15 min is Regression Kriging interpolation using GHI estimated from satellite images as one of the input variables. On the contrary, when station density is low, the best method is estimating GHI directly from satellite images. A comparison between the GHI observed by volunteer stations and the estimation model applied concludes that 67% of the volunteer stations analyzed present values within the margin of error (average of +-2 standard deviations).