Spatial and radiometric fidelity of airborne multispectral imagery in the context of land-cover change analyses

The goal was to quantitatively estimate and compare the fidelity of images acquired with a digital imaging system (ADAR 5500) and generated through scanning of color infrared aerial photographs (SCIRAP) using image-based metrics. Images were collected nearly simultaneously in two repetitive flights to generate multi-temporal datasets. Spatial fidelity of ADAR was lower than that of SCIRAP images. Radiometric noise was higher for SCIRAP than for ADAR images, even though noise from misregistration effects was lower. These results suggest that with careful control of film scanning, the overall fidelity of SCIRAP imagery can be comparable to that of digital multispectral camera data. Therefore, SCIRAP images can likely be used in conjunction with digital metric camera imagery in long-term landcover change analyses.

The diffusion of grassroots innovations for sustainability in Italy and Great Britain: an exploratory spatial data analysis

Little research so far has been devoted to understanding the diffusion of grassroots innovation for sustainability across space. This paper explores and compares the spatial diffusion of two networks of grassroots innovations, the Transition Towns Network (TTN) and Gruppi di Acquisto Solidale (Solidarity Purchasing Groups – GAS), in Great Britain and Italy. Spatio-temporal diffusion data were mined from available datasets, and patterns of diffusion were uncovered through an exploratory data analysis. The analysis shows that GAS and TTN diffusion in Italy and Great Britain is spatially structured, and that the spatial structure has changed over time. TTN has diffused differently in Great Britain and Italy, while GAS and TTN have diffused similarly in central Italy. The uneven diffusion of these grassroots networks on the one hand challenges current narratives on the momentum of grassroots innovations, but on the other highlights important issues in the geography of grassroots innovations for sustainability, such as cross-movement transfers and collaborations, institutional thickness, and interplay of different proximities in grassroots innovation diffusion.

Spatial patterns and environmental constraints on ecosystem services at a catchment scale

Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1x1 km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness.

Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Quantitative measurements in 3-dimensional datasets of mouse lymph nodes resolve organ-wide functional dependencies

Deep tissue imaging has become state of the art in biology, but now the problem is to quantify spatial information in a global, organ-wide context. Although access to the raw data is no longer a limitation, the computational tools to extract biologically useful information out of these large data sets is still catching up. In many cases, to understand the mechanism behind a biological process, where molecules or cells interact with each other, it is mandatory to know their mutual positions. We illustrate this principle here with the immune system. Although the general functions of lymph nodes as immune sentinels are well described, many cellular and molecular details governing the interactions of lymphocytes and dendritic cells remain unclear to date and prevent an in-depth mechanistic understanding of the immune system. We imaged ex vivo lymph nodes isolated from both wild-type and transgenic mice lacking key factors for dendritic cell positioning and used software written in MATLAB to determine the spatial distances between the dendritic cells and the internal high endothelial vascular network. This allowed us to quantify the spatial localization of the dendritic cells in the lymph node, which is a critical parameter determining the effectiveness of an adaptive immune response.

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.

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.