Spatially Explicit Analysis of Metal Transfer to Biota: Influence of Soil Contamination and Landscape

PLoS ONE, Published 31 May 2011

Clémentine Fritsch, Michaël Cœurdassier, Patrick Giraudoux, Francis Raoul, Francis Douay, Dominique Rieffel, Annette de Vaufleury, and Renaud Scheifler

“Concepts and developments for a new field in ecotoxicology, referred to as “landscape ecotoxicology,” were proposed in the 1990s; however, to date, few studies have been developed in this emergent field. In fact, there is a strong interest in developing this area, both for renewing the concepts and tools used in ecotoxicology as well as for responding to practical issues, such as risk assessment. The aim of this study was to investigate the spatial heterogeneity of metal bioaccumulation in animals in order to identify the role of spatially explicit factors, such as landscape as well as total and extractable metal concentrations in soils.

Iso-concentration lines of predicted total Cd, Pb and Zn concentrations in topsoils from Metaleurop-impacted area.

Iso-concentration lines of predicted total Cd, Pb and Zn concentrations in topsoils from Metaleurop-impacted area.

“Over a smelter-impacted area, we studied the accumulation of trace metals (TMs: Cd, Pb and Zn) in invertebrates (the grove snail Cepaea sp and the glass snail Oxychilus draparnaudi) and vertebrates (the bank vole Myodes glareolus and the greater white-toothed shrew Crocidura russula). Total and CaCl2-extractable concentrations of TMs were measured in soils from woody patches where the animals were captured. TM concentrations in animals exhibited a high spatial heterogeneity. They increased with soil pollution and were better explained by total rather than CaCl2-extractable TM concentrations, except in Cepaea sp. TM levels in animals and their variations along the pollution gradient were modulated by the landscape, and this influence was species and metal specific. Median soil metal concentrations (predicted by universal kriging) were calculated in buffers of increasing size and were related to bioaccumulation. The spatial scale at which TM concentrations in animals and soils showed the strongest correlations varied between metals, species and landscapes. The potential underlying mechanisms of landscape influence (community functioning, behaviour, etc.) are discussed. Present results highlight the need for the further development of landscape ecotoxicology and multi-scale approaches, which would enhance our understanding of pollutant transfer and effects in ecosystems.”

Risk Analysis of Rainstorm Waterlogging on Residences in Shanghai based on Scenario Simulation

Natural HazardsNatural Hazards, Published Online 02 March 2012

Yong Shi

“Due to special geographical location and climate, the waterlogging has always been one of the most serious hazards in Shanghai. Residences in the inner city are prone to be damaged by waterlogging hazards. This paper describes the risk analysis of rainstorm waterlogging on residences in Shanghai. First, a rainstorm scenario of 50-year return period was simulated with the rainstorm simulation model from Shanghai Flood Risk Information Center. Each residence was ranked according to its degree of exposure indicated by the inundation depth of that residence, and an exposure analysis model was then built. It is found from the exposure analysis that residences in the sub-districts like Linfen Road, Pengpu Village, Gonghe New Village, Hongqiao Road, Xianxia Road, Xinhua Road, and Zhenru Town are at high-exposure level. Whereas residences in other sub-districts like Gaojing Town, Siping Road, Huaihai Road, Yuyuan, Waitan, Caojiadu, Nanjing East Road, etc. are at low-exposure level. Second, given the characteristics of residences in waterlogging, the vulnerability of residences was expressed as the proportion of old-style residences to total residences. The results show that residences in Yuyuan, Xiaodongmen, Waitan, Nanjing East Road, Laoximen, Zhapu Road, North Station, and Tilanqiao are the most vulnerable ones, while there is no vulnerability in Fenglin Road, Kongjiang Road, Liangcheng New Village, Quyang Road, Siping Road, and Xianxia Road due to the absence of old-style residences. Finally, a model has been built from a systematic perspective and then waterlogging risk analysis was quantified by multiplying the exposure value with vulnerability value of residences. The results reveal that Laoximen, Tilanqiao, Dinghai Road, North Station, Tianping Road, Hongmei Road, Hunan Road, and Xiaodongmen are at high-risk level. The systemic risk model is a simple tool that can be used to assess the relative risk of waterlogging in different regions and the results of risk analysis are applicable to prevention and mitigation of waterlogging for Shanghai Municipal Government.”

A Spatial Cluster Analysis of Tractor Overturns in Kentucky from 1960 to 2002

PLoS ONE, Published 24 January 2012

Daniel M. Saman, Henry P. Cole, Agricola Odoi, Melvin L. Myers, Daniel I. Carey, and Susan C. Westneat

“Background: Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns.

Spatial Empirical Bayes' (SEB) smoothed tractor overturn rates in Kentucky, 1960–2002.

Spatial Empirical Bayes' (SEB) smoothed tractor overturn rates in Kentucky, 1960–2002.

“Methods: A spatial statistical analysis using Kulldorff’s spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns.

“Results: The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001).

“Conclusions: This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky.”

Spatial Analysis of Land Cover Determinants of Malaria Incidence in the Ashanti Region, Ghana

PLoS ONEPLoS ONE 6(3), Published 23 March 2011

Anne Caroline Krefis, Norbert Georg Schwarz, Bernard Nkrumah, Samuel Acquah, Wibke Loag, Jens Oldeland, Nimako Sarpong, Yaw Adu-Sarkodie, Ulrich Ranft, and Jürgen May

“Malaria belongs to the infectious diseases with the highest morbidity and mortality worldwide. As a vector-borne disease malaria distribution is strongly influenced by environmental factors. The aim of this study was to investigate the association between malaria risk and different land cover classes by using high-resolution multispectral Ikonos images and Poisson regression analyses. The association of malaria incidence with land cover around 12 villages in the Ashanti Region, Ghana, was assessed in 1,988 children <15 years of age. The median malaria incidence was 85.7 per 1,000 inhabitants and year (range 28.4–272.7). Swampy areas and banana/plantain production in the proximity of villages were strong predictors of a high malaria incidence. An increase of 10% of swampy area coverage in the 2 km radius around a village led to a 43% higher incidence (relative risk [RR] = 1.43, p<0.001). Each 10% increase of area with banana/plantain production around a village tripled the risk for malaria (RR = 3.25, p<0.001). An increase in forested area of 10% was associated with a 47% decrease of malaria incidence (RR = 0.53, p = 0.029).

Supervised maximum likelihood classification map

Supervised maximum likelihood classification map (combined NDVI image, the texture bands, and the four spectral bands).

“Distinct cultivation in the proximity of homesteads was associated with childhood malaria in a rural area in Ghana. The analyses demonstrate the usefulness of satellite images for the prediction of malaria endemicity. Thus, planning and monitoring of malaria control measures should be assisted by models based on geographic information systems.”

Methods for Studying the Ecological Physiology of Feeding in Free-Ranging Howlers (Alouatta palliata) at La Pacifica, Costa Rica

International Journal of PrimatologyInternational Journal of Primatology, Published Online 02 March 2012

Christopher J. Vinyard, Kenneth E. Glander, Mark F. Teaford, Cynthia L. Thompson, Max Deffenbaugh and Susan H. Williams

“We lack a general understanding of how primates perform physiologically during feeding to cope with the challenges of their natural environments. We here discuss several methods for studying the ecological physiology of feeding in mantled howlers (Alouatta palliata) at La Pacifica, Costa Rica. Our initial physiological effort focuses on recording electromyographic activity (EMG) from the jaw muscles in free-ranging howlers while they feed in their natural forest habitat. We integrate these EMG data with measurements of food material properties, dental wear rates, as well as spatial analyses of resource use and food distribution. Future work will focus on incorporating physiological measures of bone deformation, i.e., bone strain; temperatures; food nutritional data; and hormonal analyses. Collectively, these efforts will help us to better understand the challenges that howlers face in their environment and the physiological mechanisms they employ during feeding. Our initial efforts provide a proof of concept demonstrating the methodological feasibility of studying the physiology of feeding in free-ranging primates. Although howlers offer certain advantages to in vivo field research, many of the approaches described here can be applied to other primates in natural habitats. By collecting physiological data simultaneously with ecological and behavioral data, we will promote a more synthetic understanding of primate feeding and its evolutionary history.”

Spatial Analysis of Terrain in Virtual Reality

IEEE VR Workshop 2012

Rolf Westerteiger, Andreas Gerndt, Bernd Hamann, and Hans Hagen

“We extend an existing Virtual Reality terrain visualization framework to support spatial analysis tasks for geoscientific purposes. Interactive measurement of height profiles is used as an example application to demonstrate the efficacy of the approach. In this application, virtual reality technology enables superior perception of profile line localization with respect to terrain features.”

Fault network on Mars next to Valles Marineris

Fault network on Mars next to Valles Marineris

Knowledge-based Classification of Remote Sensing Data for the Estimation of Below- and Above-ground Organic Carbon Stocks in Riparian Forests

Wetlands Ecology and ManagementWetlands Ecology and Management, Published Online 02 March 2012

L. Suchenwirth, M. Förster, A. Cierjacks, F. Lang, and B. Kleinschmit

“Floodplain forests play a crucial role in the storage of organic carbon (Corg). However, modeling of carbon stocks in these dynamic ecosystems remains inherently difficult. Here, we present the spatial estimation of Corg stocks in riparian woody vegetation and soils (to a depth of 1 m) in a Central European floodplain using very high spatial resolution remote sensing data and auxiliary geodata. The research area is the Danube Floodplain National Park in Austria, one of the last remaining wetlands with near-natural vegetation in Central Europe. Different vegetation types within the floodplain show distinct capacities to store Corg. We used remote sensing to distinguish the following vegetation types: meadow, reed bed and hardwood, softwood, and cottonwood forests. Spectral and knowledge-based classification was performed with object-based image analysis. Additional knowledge rules included distances to the river, object area, and slope information. Five different classification schemes based on spectral values and additional knowledge rules were compared and validated. Validation data for the classification accuracy were derived from forest inventories and topographical maps. Overall accuracy for vegetation types was higher for a combination of spectral- and knowledge-based classification than for spectral values alone. While water, reed beds and meadows were clearly detectable, it remained challenging to distinguish the different forest types. The total carbon storage of soils and vegetation was quantified using a Monte Carlo simulation for all classified vegetation types, and the spatial distribution was mapped. The average storage of the study site is 428.9 Mg C ha−1. Despite certain difficulties in vegetation classification this method allows an indirect estimation of Corg stocks in Central European floodplains.”

Temporal Analysis of Soil and Water Assessment Tool (SWAT) Performance based on Remotely Sensed Precipitation Products

Hydrological ProcessesHydrological Processes, Accepted for Publication

Kenneth J. Tobin and Marvin E. Bennett

“No study has systematically evaluated streamflow modeling between monthly and daily timescales. This study examines streamflow from seven watersheds across the United States where five different precipitation products were used as primary input into the Soil and Water Assessment Tool to generate simulated streamflow. Timescales examined include monthly, dekad (10 day), pentad (5 day), triad (3 day), and daily. The seven basins studied are the San Pedro (Arizona); Cimarron (north-central Oklahoma); mid-Nueces (south Texas); mid-Rio Grande (south Texas and northern Mexico), Yocano (northern Mississippi); Alapaha (south Georgia); and mid-St. Francis (eastern Arkansas). The precipitation products used to drive simulations include rain gauge, NWS Multisensor Precipitation Estimator, Tropical Rainfall Measurement Mission, Multi-Satellite (TRMM) Precipitation Analysis, TRMM 3B42-V6, and Climate Prediction Center Morphing Method (CMORPH). Understanding how streamflow varies at sub-monthly timescales is important because there are a host of hydrological applications such a flood forecast guidance and reservoir inflow forecasts that reside in a temporal domain between monthly and daily timescales. The major finding of this study is the quantification of a strong positive correlation between performance metrics and time step at which model performance deteriorates. Better performing simulations, with higher Nash-Sutcliffe values of 0.80 and above can support modeling at finer timescales to at least daily and perhaps beyond into the sub-daily realm. These findings are significant in that they clearly document the ability of SWAT to support modeling at sub-monthly time steps, which is beyond the capability for which SWAT was initially designed.”

Niche Models Tell Half the Story: Spatial Context and Life-history Traits Influence Species Responses to Global Change

Journal of BiogeographyJournal of Biogeography, published online 01 March 2012

Rebecca M. Swab, Helen M. Regan, David A. Keith, Tracey J. Regan and Mark K. J. Ooi

“Aim: While niche models are typically used to assess the vulnerability of species to climate change, they have been criticized for their limited assessment of threats other than climate change. We attempt to evaluate this limitation by combining niche models with life-history models to investigate the relative influence of climate change and a range of fire regimes on the viability of a long-lived plant population. Specifically, we investigate whether range shift due to climate change is a greater threat to an obligate seeding fire-prone shrub than altered fire frequency and how these two threatening processes might interact.

“Location: Australian sclerophyll woodland and heathland.

“Methods: The study species is Leucopogon setiger, an obligate seeding fire-prone shrub. A spatially explicit stochastic matrix model was constructed for this species and linked with a dynamic niche model and fire risk functions representing a suite of average fire return intervals. We compared scenarios with a variety of hypothetical patches, a patch framework based upon current habitat suitability and one with dynamic habitat suitability based on climate change scenarios A1FI and A2.

“Results: Leucopogon setiger was found to be sensitive to fire frequency, with shorter intervals reducing expected minimum abundances (EMAs). Spatial decoupling of fires across the landscape reduced the vulnerability of the species to shortened fire frequencies. Shifting habitat, while reducing EMAs, was less of a threat to the species than frequent fire.

“Main conclusions: Altered fire regime, in particular more frequent fires relative to the historical regime, was predicted to be a strong threat to this species, which may reflect a vulnerability of obligate seeders in general. Range shifts induced by climate change were a secondary threat when habitat reductions were predicted. Incorporating life-history traits into habitat suitability models by linking species distribution models with population models allowed for the population-level evaluation of multiple stressors that affect population dynamics and habitat, ultimately providing a greater understanding of the impacts of global change than would be gained by niche models alone. Further investigations of this type could elucidate how particular bioecological factors can affect certain types of species under global change.”

Studying Relationships between Environment and Malaria Incidence in Camopi (French Guiana) through the Objective Selection of Buffer-based Landscape Characterisations

International Journal of Health GeographicsInternational Journal of Health Geographics, 2011, Volume 10, Number 1

Aurélia Stefani, Emmanuel Roux, Jean-Marie Fotsing, and Bernard Carme

“Background: Malaria remains a major health problem in French Guiana, with a mean of 3800 cases each year. A previous study in Camopi, an Amerindian village on the Oyapock River, highlighted the major contribution of environmental features to the incidence of malaria attacks. We propose a method for the objective selection of the best multivariate peridomestic landscape characterisation that maximises the chances of identifying relationships between environmental features and malaria incidence, statistically significant and meaningful from an epidemiological point of view.

“Methods: A land-cover map, the hydrological network and the geolocalised inhabited houses were used to characterise the peridomestic landscape in eleven discoid buffers with radii of 50, 100, 200, 300, 400, 500, 600, 700, 800, 900 and 1000 metres. Buffer-based landscape characterisations were first compared in terms of their capacity to discriminate between sites within the geographic space and of their effective multidimensionality in variable space. The Akaike information criterion (AIC) was then used to select the landscape model best explaining the incidences of P. vivax and P. falciparum malaria. Finally, we calculated Pearson correlation coefficients for the relationships between environmental variables and malaria incidence, by species, for the more relevant buffers.

“Results: The optimal buffers for environmental characterisation had radii of 100 m around houses for P. vivax and 400 m around houses for P. falciparum. The incidence of P. falciparum malaria seemed to be more strongly linked to environmental features than that of P. vivax malaria, within these buffers. The incidence of P. falciparum malaria in children was strongly correlated with proportions of bare soil (r = -0.69), land under high vegetation (r = 0.68) and primary forest (r = 0.54), landscape division (r = 0.48) and the number of inhabited houses (r = -0.60). The incidence of P. vivax malaria was associated only with landscape division (r = 0.49).

“Conclusions: The proposed methodology provides a simple and general framework for objective characterisation of the landscape to account for field observations. The use of this method enabled us to identify different optimal observation horizons around houses, depending on the Plasmodium species considered, and to demonstrate significant correlations between environmental features and the incidence of malaria.”