Anthropic effects on the fish community of Ribeirão Claro, Rio Claro, SP, Brazil

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

滑坡泥石流信息遥感获取与空间预测

On the issue of geological hazard evaluation（GHE）, taking remote sensing and GIS systems as experimental environment, assisting with some programming development, this thesis combines multi-knowledges of geo-hazard mechanism, statistic learning, remote sensing (RS), high-spectral recognition, spatial analysis, digital photogrammetry as well as mineralogy, and selects geo-hazard samples from Hong Kong and Three Parallel River region as experimental data, to study two kinds of core questions of GHE, geo-hazard information acquiring and evaluation model. In the aspect of landslide information acquiring by RS, three detailed topics are presented, image enhance for visual interpretation, automatic recognition of landslide as well as quantitative mineral mapping. As to the evaluation model, the latest and powerful data mining method, support vector machine (SVM), is introduced to GHE field, and a serious of comparing experiments are carried out to verify its feasibility and efficiency. Furthermore, this paper proposes a method to forecast the distribution of landslides if rainfall in future is known baseing on historical rainfall and corresponding landslide susceptibility map. The details are as following: (a) Remote sensing image enhancing methods for geo-hazard visual interpretation. The effect of visual interpretation is determined by RS data and image enhancing method, for which the most effective and regular technique is image merge between high-spatial image and multi-spectral image, but there are few researches concerning the merging methods of geo-hazard recognition. By the comparing experimental of six mainstream merging methods and combination of different remote sensing data source, this thesis presents merits of each method ,and qualitatively analyzes the effect of spatial resolution, spectral resolution and time phase on merging image. (b) Automatic recognition of shallow landslide by RS image. The inventory of landslide is the base of landslide forecast and landslide study. If persistent collecting of landslide events, updating the geo-hazard inventory in time, and promoting prediction model incessantly, the accuracy of forecast would be boosted step by step. RS technique is a feasible method to obtain landslide information, which is determined by the feature of geo-hazard distribution. An automatic hierarchical approach is proposed to identify shallow landslides in vegetable region by the combination of multi-spectral RS imagery and DEM derivatives, and the experiment is also drilled to inspect its efficiency. (c) Hazard-causing factors obtaining. Accurate environmental factors are the key to analyze and predict the risk of regional geological hazard. As to predict huge debris flow, the main challenge is still to determine the startup material and its volume in debris flow source region. Exerting the merits of various RS technique, this thesis presents the methods to obtain two important hazard-causing factors, DEM and alteration mineral, and through spatial analysis, finds the relationship between hydrothermal clay alteration minerals and geo-hazards in the arid-hot valleys of Three Parallel Rivers region. (d) Applying support vector machine (SVM) to landslide susceptibility mapping. Introduce the latest and powerful statistical learning theory, SVM, to RGHE. SVM that proved an efficient statistic learning method can deal with two-class and one-class samples, with feature avoiding produce ‘pseudo’ samples. 55 years historical samples in a natural terrain of Hong Kong are used to assess this method, whose susceptibility maps obtained by one-class SVM and two-class SVM are compared to that obtained by logistic regression method. It can conclude that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping. (e) Predicting the distribution of rainfall-induced landslides by time-series analysis. Rainfall is the most dominating factor to bring in landslides. More than 90% losing and casualty by landslides is introduced by rainfall, so predicting landslide sites under certain rainfall is an important geological evaluating issue. With full considering the contribution of stable factors (landslide susceptibility map) and dynamic factors (rainfall), the time-series linear regression analysis between rainfall and landslide risk mapis presented, and experiments based on true samples prove that this method is perfect in natural region of Hong Kong. The following 4 practicable or original findings are obtained: 1) The RS ways to enhance geo-hazards image, automatic recognize shallow landslides, obtain DEM and mineral are studied, and the detailed operating steps are given through examples. The conclusion is practical strongly. 2) The explorative researching about relationship between geo-hazards and alteration mineral in arid-hot valley of Jinshajiang river is presented. Based on standard USGS mineral spectrum, the distribution of hydrothermal alteration mineral is mapped by SAM method. Through statistic analysis between debris flows and hazard-causing factors, the strong correlation between debris flows and clay minerals is found and validated. 3) Applying SVM theory (especially one-class SVM theory) to the landslide susceptibility mapping and system evaluation for its performance is also carried out, which proves that advantages of SVM in this field. 4) Establishing time-serial prediction method for rainfall induced landslide distribution. In a natural study area, the distribution of landslides induced by a storm is predicted successfully under a real maximum 24h rainfall based on the regression between 4 historical storms and corresponding landslides.

Immune factors and fatty acid composition in human milk from river/lake, coastal and inland regions of China

Breast milk fatty acid composition may be affected by maternal diet during gestation and lactation. The influence of dietary and breast milk fatty acids on breast milk immune factors is poorly defined. We determined the fatty acid composition and immune factor concentrations of breast milk from women residing in river & lake, coastal, and inland regions of China, which differ in their consumption of lean fish and oily fish. Breast milk samples were collected on days 3 to 5 (colostrum), 14 and 28 post-partum and analysed for soluble CD14 (sCD14), transforming growth factor (TGF)-β1, TGF-β2, secretory immunoglobulin A (sIgA) and fatty acids. The fatty acid composition of breast milk differed between regions and with time post-partum. The concentrations of all four immune factors in breast milk decreased over time, with sCD14, sIgA and TGF-β1 being highest in colostrum in the river & lake region. Breast milk DHA and arachidonic acid (AA) were positively associated, and γ-linolenic acid and EPA negatively associated, with the concentrations of each of the four immune factors. In conclusion, breast milk fatty acids and immune factors differ between regions in China characterised by different patterns of fish consumption and change during the course of lactation. A higher breast milk DHA and AA concentration is associated with higher concentrations of immune factors in breast milk, suggesting a role for these fatty acids in promoting gastrointestinal and immune maturation of the infant.

Can sand slugs in rivers deliver conservation benefits? The biodiversity value of tributary junction plug wetlands in the Glenelg River, Australia

Restoration works are carried out to alleviate human impacts and improve habitats within ecosystems. However, human impacts may also create new (anthropogenic) habitat for species to exploit.A dilemma arises when proposed restoration works would remove anthropogenic habitat and the assemblages it supports. Sediment input into the Glenelg River has formed tributary junction plug wetlands at confluences. Sand slug removal is proposed as part of river rehabilitation, but would also drain plug wetlands. We sampled four plug wetland, four river run and three river pool sites to determine whether plug wetlands influence water quality and add to the biodiversity of macroinvertebrates in the Glenelg River.Water quality and macroinvertebrate diversity were similar in plug wetlands, river runs and river pools.Assemblages were distinct among all sites, regardless of type, so there was no characteristic ‘plug-wetland fauna’. Therefore, although removal of plug wetlands would not cause a dramatic loss of invertebrate biodiversity, it would destroy anthropogenic habitat that supports a similar range of species to natural habitats in a river subject to multiple degrading processes. Gains from rehabilitation should be weighed against the value of anthropogenic habitat and the extent of similar habitat lost elsewhere in the ecosystem.

Preliminary qualitative analysis on mtDNA in Astyanax fasciatus populations Cuvier, 1819 (Teleostei; Characidae) indicate population distinctiveness

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

Shipping costs: a rising challenge to the region's competitive development

This issue of the FAL Bulletin examines the impact of shipping costs on the exports of five Latin American and Caribbean countries by analysing the difference between the unit value of goods at the port of origin and at the port of destination, in three of the region's main external markets.

A paisagem cultural do Sítio Arqueológico Piracanjuba, Piraju, SP

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

A paisagem cultural do Sítio Arqueológico Piracanjuba, Piraju, SP

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

Organic carbon and total nitrogen stocks in soils of the Lena River Delta

The Lena River Delta, which is the largest delta in the Arctic, extends over an area of 32 000 km**2 and likely holds more than half of the entire soil organic carbon (SOC) mass stored in the seven major deltas in the northern permafrost regions. The geomorphic units of the Lena River Delta which were formed by true deltaic sedimentation processes are a Holocene river terrace and the active floodplains. Their mean SOC stocks for the upper 1 m of soils were estimated at 29 kg/m**2 ± 10 kg/m**2 and at 14 kg/m**2 ± 7 kg/m**2, respectively. For the depth of 1 m, the total SOC pool of the Holocene river terrace was estimated at 121 Tg ± 43 Tg, and the SOC pool of the active floodplains was estimated at 120 Tg ± 66 Tg. The mass of SOC stored within the observed seasonally thawed active layer was estimated at about 127 Tg assuming an average maximum active layer depth of 50 cm. The SOC mass which is stored in the perennially frozen ground at the increment 50-100 cm soil depth, which is currently excluded from intense biogeochemical exchange with the atmosphere, was estimated at 113 Tg. The mean nitrogen (N) stocks for the upper 1 m of soils were estimated at 1.2 kg/m**2 ± 0.4 kg/m**2 for the Holocene river terrace and at 0.9 kg/m**2 ± 0.4 kg/m**2 for the active floodplain levels, respectively. For the depth of 1 m, the total N pool of the river terrace was estimated at 4.8 Tg ± 1.5 Tg, and the total N pool of the floodplains was estimated at 7.7 Tg ± 3.6 Tg. Considering the projections for deepening of the seasonally thawed active layer up to 120 cm in the Lena River Delta region within the 21st century, these large carbon and nitrogen stocks could become increasingly available for decomposition and mineralization processes.

Phytoplankton abundance measured on water samples from rivers of the Lena Delta in 2010

The Lena Delta in Northern Siberia is one of the largest river deltas in the world. During peak discharge, after the ice melt in spring, it delivers between 60-8000 m**3/s of water and sediment into the Arctic Ocean. The Lena Delta and the Laptev Sea coast also constitute a continuous permafrost region. Ongoing climate change, which is particularly pronounced in the Arctic, is leading to increased rates of permafrost thaw. This has already profoundly altered the discharge rates of the Lena River. But the chemistry of the river waters which are discharged into the coastal Laptev Sea have also been hypothesized to undergo considerable compositional changes, e.g. by increasing concentrations of inorganic nutrients such as dissolved organic carbon (DOC) and methane. These physical and chemical changes will also affect the composition of the phytoplankton communities. However, before potential consequences of climate change for coastal arctic phytoplankton communities can be judged, the inherent status of the diversity and food web interactions within the delta have to be established. In 2010, as part of the AWI Lena Delta programme, the phyto- and microzooplankton community in three river channels of the delta (Trofimov, Bykov and Olenek) as well as four coastal transects were investigated to capture the typical river phytoplankton communities and the transitional zone of brackish/marine conditions. Most CTD profiles from 23 coastal stations showed very strong stratification. The only exception to this was a small, shallow and mixed area running from the outflow of Bykov channel in a northerly direction parallel to the shore. Of the five stations in this area, three had a salinity of close to zero. Two further stations had salinities of around 2 and 5 throughout the water column. In the remaining transects, on the other hand, salinities varied between 5 and 30 with depth. Phytoplankton counts from the outflow from the Lena were dominated by diatoms (Aulacoseira species) cyanobacteria (Aphanizomenon, Pseudanabaena) and chlorophytes. In contrast, in the stratified stations the plankton was mostly dominated by dinoflagellates, ciliates and nanoflagellates, with only an insignificant diatom component from the genera Chaetoceros and Thalassiosira (brackish as opposed to freshwater species). Ciliate abundance was significantly coupled with the abundance of total flagellates. A pronounced partitioning in the phytoplankton community was also discernible with depth, with a different community composition and abundance above and below the thermocline in the stratified sites. This work is a first analysis of the phytoplankton community structure in the region where Lena River discharge enters the Laptev Sea.

Composition of zooplankton assemblages along the Zagyva River

The species composition, longitudinal distribution and seasonal dynamics of zooplankton were studied in the Zagyva River, Hungary. A total of 108 taxa was recorded from which 61 were new for the river. Rotatoria was the most abundant group, microcrustaceans were less important, only nauplii and copepodites were represented in similar individual numbers. Frequent species included Anuraeopsis fissa, Pompholyx spp., Keratella cochlearis, Brachionus angularis, Bdelloida sp., Bosmina longirostris. Dominance of cosmopolitan species was observed both in the river and its reservoir, and species characteristic of eutrophic waters were of major importance in the latter. There was a downstream decrease in zooplankton densities, which was explained by modified conditions. The relatively large number of individuals in autumn months, and the characteristic large number of individuals in the upper section contrasted general findings of potamoplankton dynamics. On the basis of the species abundance matrix, three river sections can be distinguished (upper, middle, lower section). Due to waste water discharges - received from the Tarján Stream - we found extremely high number of individuals and the lowest diversity at the sampling site Nagybátony (148 rkm).

Ambiguity Acceptance Testing : A Comparison of the Ratio Test and Difference Test

Integer ambiguity resolution is an indispensable procedure for all high precision GNSS applications. The correctness of the estimated integer ambiguities is the key to achieving highly reliable positioning, but the solution cannot be validated with classical hypothesis testing methods. The integer aperture estimation theory unifies all existing ambiguity validation tests and provides a new prospective to review existing methods, which enables us to have a better understanding on the ambiguity validation problem. This contribution analyses two simple but efficient ambiguity validation test methods, ratio test and difference test, from three aspects: acceptance region, probability basis and numerical results. The major contribution of this paper can be summarized as: (1) The ratio test acceptance region is overlap of ellipsoids while the difference test acceptance region is overlap of half-spaces. (2) The probability basis of these two popular tests is firstly analyzed. The difference test is an approximation to optimal integer aperture, while the ratio test follows an exponential relationship in probability. (3) The limitations of the two tests are firstly identified. The two tests may under-evaluate the failure risk if the model is not strong enough or the float ambiguities fall in particular region. (4) Extensive numerical results are used to compare the performance of these two tests. The simulation results show the ratio test outperforms the difference test in some models while difference test performs better in other models. Particularly in the medium baseline kinematic model, the difference tests outperforms the ratio test, the superiority is independent on frequency number, observation noise, satellite geometry, while it depends on success rate and failure rate tolerance. Smaller failure rate leads to larger performance discrepancy.

Rainfall and streamflow response to El Niño Southern Oscillation: a case study in a semiarid catchment, Australia.

This paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0-3 month lead time, compared to rainfall distribution.