Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data

West African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources of the region, for instance, reduced freshwater availability. Assessing and predicting large-scale total water storage (TWS) variations are necessary for West Africa, due to its environmental, social, and economical impacts. Hydrological models, however, may perform poorly over West Africa due to data scarcity. This study describes a new statistical, data-driven approach for predicting West African TWS changes from (past) gravity data obtained from the gravity recovery and climate experiment (GRACE), and (concurrent) rainfall data from the tropical rainfall measuring mission (TRMM) and sea surface temperature (SST) data over the Atlantic, Pacific, and Indian Oceans. The proposed method, therefore, capitalizes on the availability of remotely sensed observations for predicting monthly TWS, a quantity which is hard to observe in the field but important for measuring regional energy balance, as well as for agricultural, and water resource management.Major teleconnections within these data sets were identified using independent component analysis and linked via low-degree autoregressive models to build a predictive framework. After a learning phase of 72 months, our approach predicted TWS from rainfall and SST data alone that fitted to the observed GRACE-TWS better than that from a global hydrological model. Our results indicated a fit of 79 % and 67 % for the first-year prediction of the two dominant annual and inter-annual modes of TWS variations. This fit reduces to 62 % and 57 % for the second year of projection. The proposed approach, therefore, represents strong potential to predict the TWS over West Africa up to 2 years. It also has the potential to bridge the present GRACE data gaps of 1 month about each 162days as well as a—hopefully—limited gap between GRACE and the GRACE follow-on mission over West Africa. The method presented could also be used to generate a near real-time GRACE forecast over the regions that exhibit strong teleconnections

Markov Chain Monte Carlo and the Application to Geodetic Time Series Analysis

The time evolution of geophysical phenomena can be characterised by stochastic time series. The stochastic nature of the signal stems from the geophysical phenomena involved and any noise, which may be due to, e.g., un-modelled effects or measurement errors. Until the 1990's, it was usually assumed that white noise could fully characterise this noise. However, this was demonstrated to be not the case and it was proven that this assumption leads to underestimated uncertainties of the geophysical parameters inferred from the geodetic time series. Therefore, in order to fully quantify all the uncertainties as robustly as possible, it is imperative to estimate not only the deterministic but also the stochastic parameters of the time series. In this regard, the Markov Chain Monte Carlo (MCMC) method can provide a sample of the distribution function of all parameters, including those regarding the noise, e.g., spectral index and amplitudes. After presenting the MCMC method and its implementation in our MCMC software we apply it to synthetic and real time series and perform a cross-evaluation using Maximum Likelihood Estimation (MLE) as implemented in the CATS software. Several examples as to how the MCMC method performs as a parameter estimation method for geodetic time series are given in this chapter. These include the applications to GPS position time series, superconducting gravity time series and monthly mean sea level (MSL) records, which all show very different stochastic properties. The impact of the estimated parameter uncertainties on sub-sequentially derived products is briefly demonstrated for the case of plate motion models. Finally, the MCMC results for weekly downsampled versions of the benchmark synthetic GNSS time series as provided in Chapter 2 are presented separately in an appendix

Biodiversity and structure of spider communities along a metal pollution gradient

The objective of the study was to determine whether long-term metal pollution affects communities of epigeal spiders (Aranea), studied at three taxonomic levels: species, genera, and families. Biodiversity was defined by three indices: the Hierarchical Richness Index (HRI), Margalef index (DM) and Pielou evenness index (J). In different ways the indices describe taxa richness and the distribution of individuals among taxa. The dominance pattern of the communities was described with four measures: number of dominant species at a site, percentage of dominant species at a site, average dominant species abundance at a site, and the share of the most numerous species (Alopecosa cuneata) at a site. Spiders were collected along a metal pollution gradient in southern Poland, extending ca. 33 km from zinc and lead smelter to an uncontaminated area. The zinc concentration in soil was used as the pollution index.The study revealed a significant effect of metal pollution on spider biodiversity as described by HRI for species (p = 0.039), genera (p = 0.0041) and families (p = 0.0147), and by DM for genera (p = 0.0259) and families (p = 0.0028). HRI correlated negatively with pollution level, while DM correlated positively. This means that although broadly described HRI diversity decreased with increasing pollution level, species richness increased with increasing contamination. Mesophilic meadows were generally richer. Pielou (J) did not show any significant correlations. There were a few evidences for the intermediate disturbance hypothesis: certain indices reached their highest values at moderate pollution levels rather than at the cleanest or most polluted sites

A review of studies performed to assess metal uptake by earthworms

Earthworms perform a number of essential functions in soil; the impacts of metals on earthworms are often investigated. In this review we consider the range of earthworm species, types of soil and forms of metal for which metal uptake and accumulation have been studied, the design of these experiments and the quantitative relationships that have been derived to predict earthworm metal body burden. We conclude that there is a need for more studies on earthworm species other than Eisenia fetida in order to apply the large existing database on this earthworm to other, soil dwelling species. To aid comparisons between studies agreement is needed on standard protocols that define exposure and deputation periods and the parameters, such as soil solution composition, soil chemical and physical properties to be measured. It is recommended that more field or terrestrial model ecosystem studies using real contaminated soil rather than metal-amended artificial soils are performed. (c) 2006 Elsevier Ltd. All rights reserved

Effects of metals on life cycle parameters of the earthworm Eisenia fetida exposed to field-contaminated, metal-polluted soils

Two control and eight field-contaminated, metal-polluted soils were inoculated with Eisenia fetida (Savigny, 1826). Three, 7, 14, 21, 28 and 42 days after inoculation, earthworm survival, body weight, cocoon production and hatching rate were measured. Seventeen metals were analysed in E.fetida tissue, bulk soil and soil solution. Soil organic carbon content, texture, pH and cation exchange capacity were also measured. Cocoon production and hatching rate were more sensitive to adverse conditions than survival or weight change. Soil properties other than metal concentration impacted toxicity. The most toxic soils were organic-poor (1-10 g C kg(-1)), sandy soils (c. 74% sand), with intermediate metal concentrations (e.g. 7150-13, 100 mg Ph kg(-1), 2970-53,400 mg Zn kg(-1)). Significant relationships between soil properties and the life cycle parameters were determined. The best coefficients of correlation were generally found for texture, pH, Ag, Cd, Mg, Pb, Tl, and Zn both singularly and in multivariate regressions. Studies that use metal-amended artificial soils are not useful to predict toxicity of field multi-contaminated soils. (c) 2007 Elsevier Ltd. All rights reserved

Uptake kinetics of metals by the earthworm Eisenia fetida exposed to field-contaminated soils

It is well known that earthworms can accumulate metals. However, most accumulation studies focus on Cd-, Cu-, Pb- or Zn-amended soils, additionally few studies consider accumulation kinetics. Here we model the accumulation kinetics of 18 elements by Eisenia fetida, exposed to 8 metal-contaminated and 2 uncontaminated soils. Tissue metal concentration was determined after 3, 7,14, 21, 28 and 42 days. Metal elimination rate was important in determining time to reach steady-state tissue metal concentration. Uptake flux to elimination rate ratios showed less variation and lower values for essential than for non-essential metals. In theory kinetic rate constants are dependent only on species and metal. Therefore it should be possible to predict steady-state tissue metal concentrations on the basis of very few measurements using the rate constants. However, our experiments show that it is difficult to extrapolate the accumulation kinetic constants derived using one soil to another. (C) 2009 Elsevier Ltd. All rights reserved

Carbon quality as a control on decomposition in tropical forests

International audienc

Carbon quality as a control on decomposition in tropical forests

International audienc

Comparison of tropospheric delays from Raman lidar, radiosondes, GPS and DORIS during the MANITOUL experiment

International audienceWater vapor measurements from a Raman lidar developed conjointly by IGN and LATMOS/CNRS are used for documenting water vapor heterogeneities in the lower troposphere and correcting geodetic radio-signal propagation delays in clear sky conditions. This instrument has both capabilities for realizing zenith pointing and slant pointing measurements. During fall 2009, the system was deployed in Toulouse (France) in collaboration with Météo-France, IPGP, CNRS and CNES for an experiment devoted to investigate the impact of water vapor heterogeneities on the propagation of DORIS and GPS signals and subsequent position estimates. During this experiment the lidar was operated for the first time in a slant pointing mode realizing sky maps of slant wet delays which will be used for correcting GPS observations. A second pointing mode was used to track DORIS satellites (Envisat, SPOT4 and SPOT5) for assessing slant wet delays retrieved from DORIS geodetic solutions. The first results from this campaign show a good agreement between both geodetic techniques for zenith wet delay retrieval. The agreement between geodetic techniques, lidar, and radiosoundings are rather good as well, despite a bias remains. Lidar slant pointing measurements are intended to be compared to GPS and DORIS slant retrievals and then used for correcting the GPS data. They are expected to improve the positioning accuracy, especially the vertical component

Collembolan biodiversity in Mediterranean urban parks : impact of history, urbanization, management and soil characteristics

Urban parks provide esthetic and recreational services and improve the quality of life in cities. Sometimes considered as biodiversity hot-spots in cities, they are subjected to different management practices which may affect soil biological quality. This is the first study - performed in urban parks of Naples (southern Italy) - aiming to evaluate the effects of park history (age, previous land use of the area and soil origin), urbanization (sealed surface density of park neighborhood), current management (land cover type and litter presence/absence) or soil physico-chemical properties on collembolan communities diversity, as indicators of soil biological quality. Our results showed that the maintenance of specific land cover types and the presence of a litter layer were crucial factors in favoring high collembolan richness in urban parks, likely by ensuring adequate trophic resources and spatial niches. In addition, park age, urban density and previous land use of areas may be involved in shaping collembolan communities. Indeed, the most diverse and structured communities inhabit soils of the oldest urban park, with the lowest surrounding urban density and mild land use change