Combined effects of elevated [CO2] and high temperature on leaf mineral balance in Coffea spp. plants

Modelling studies predicted that climate change will have strong impacts on the coffee crop, although no information on the effective impact of elevated CO₂ on this plant exists. Here, we aim at providing a first glimpse on the effect of the combined impact of enhanced [CO₂] and high temperature on the leaf mineral content and balance on this important tropical crop. Potted plants from two genotypes of Coffea arabica (cv. Icatu and IPR 108) and one from C. canephora (cv. Conilon Clone 153) were grown under 380 or 700 μL CO₂ L^?1 air, for 1 year, after which were exposed to an stepwise increase in temperature from 25/20 °C (day/night) up to 42/34 °C, over 8 weeks. Leaf macro???(N, P, K, Ca, Mg, S) and micronutrients (B, Cu, Fe, Mn, Zn) concentrations were analyzed at 25/20 °C (control), 31/25 °C, 37/30 °C and 42/34 °C. At the control temperature, the 700 μL L^?1 grown plants showed a moderate dilution effect (between 7 % and 25 %) in CL 153 (for N, Mg, Ca, Fe) and Icatu (for N, K and Fe), but not in IPR 108 (except for Fe) when compared to the 380 μL L^?1 plants. For temperatures higher than control most nutrients tended to increase, frequently presenting maximal contents at 42/34 °C (or 37/30 °C), although the relation between [CO₂] treatments did not appreciably change. Such increases offset the few dilution effects observed under high growth [CO₂] at 25/20 °C. No clear species responses were found considering [CO₂] and temperature impacts, although IPR 108 seemed less sensitive to [CO₂]. Despite the changes promoted by [CO₂] and heat, the large majority of mineral ratios were kept within a range considered adequate, suggesting that this plant can maintain mineral balances in a context of climate changes and global warming.     

Downscaling projections of climate change in Sao Tome and Principe Islands,Africa

Sao Tome and Principe is a small insular African country extremely vulnerable to rising sea levels and impacts such as inundation, shore line change, and salt water intrusion into underground aquifers. Projections of climate change have considered coarse model resolutions. The objective of this work is to dynamically downscale the global model projections to 4-km resolution and to assess the climate change in the Sao Tome and Principe islands. The global climate projections are provided by the Canadian Earth System Model under two Representative Concentration Pathways greenhouse gas scenarios, RCP4.5 and RCP8.5. The downscaling is produced by the Eta regional climate model. The baseline period is taken between 1971 and 2000, and the future climate period is taken between 2041 and 2070. The 2-m temperature simulations show good agreement with station data. The model simulates temperature more accurately than precipitation. The precipitation simulations systematically show underestimation and delay of the rainy and the dry seasons by about 1 month, a feature inherited from the global climate model. In the middle of the 21st century, projections show the strongest warming in the elevated parts of the Sao Tome Island, especially in February under RCP8.5. Warmer nights and warmer days become more frequent in the islands when compared with those in the present. While under RCP4.5, precipitation increases in the islands; under RCP8.5, it decreases everywhere in both islands. Heavy precipitation rates should increase, especially in the south-southwestern parts of the Sao Tome islands. Detailed spatial variability of the temperature and precipitation changes in the islands can only be revealed at very high spatial model resolution. Implications for the potential energy production from two major river basins are assessed in this work.     

Lateglacial and early Holocene palaeoclimatic reconstruction based on glacier fluctuations and equilibrium‐line altitudes at northern Folgefonna,Hardanger, western Norway

Northern Folgefonna (c. 23 km²), is a nearly circular maritime ice cap located on the Folgefonna Peninsula in Hardanger, western Norway. By combining the position of marginal moraines with AMS radiocarbon dated glacier‐meltwater induced sediments in proglacial lakes draining northern Folgefonna, a continuous high‐resolution record of variations in glacier size and equilibrium‐line altitudes (ELAs) during the Lateglacial and early Holocene has been obtained. After the termination of the Younger Dryas (c. 11 500 cal. yr BP), a short‐lived (100–150 years) climatically induced glacier readvance termed the ‘Jondal Event 1’ occurred within the ‘Preboreal Oscillation’ (PBO) c. 11 100 cal. yr BP. Bracketed to 10 550–10 450 cal. yr BP, a second glacier readvance is named the ‘Jondal Event 2’. A third readvance occurred about 10 000 cal. yr BP and corresponds with the ‘Erdalen Event 1’ recorded at Jostedalsbreen. An exponential relationship between mean solid winter precipitation and ablation‐season temperature at the ELA of Norwegian glaciers is used to reconstruct former variations in winter precipitation based on the corresponding ELA and an independent proxy for summer temperature. Compared to the present, the Younger Dryas was much colder and drier, the ‘Jondal Event 1’/PBO was colder and somewhat drier, and the ‘Jondal Event 2’ was much wetter. The ‘Erdalen Event 1’ started as rather dry and terminated as somewhat wetter. Variations in glacier magnitude/ELAs and corresponding palaeoclimatic reconstructions at northern Folgefonna suggest that low‐altitude cirque glaciers (lowest altitude of marginal moraines 290 m) in the area existed for the last time during the Younger Dryas. These low‐altitude cirque glaciers of suggested Younger Dryas age do not fit into the previous reconstructions of the Younger Dryas ice sheet in Hardanger. Copyright © 2005 John Wiley & Sons, Ltd.     

The Iguaraçu H5 chondrite: a fall from Paraná State,Brazil

Abstract— The Iguaraçu meteorite, a single stone of 1200 g, fell in Paraná State, Brazil in October 1977. It is classified as an H5 ordinary chondrite with olivine of composition Fa 18.7.     

Cirque glacier activity in arctic Norway during the last deglaciation

Numerous cirques of the Lofoten–Vesterålen archipelago in northern Norway have distinct moraine sequences that previously have been assigned to the Allerød-Younger Dryas ( 13,400 to 11,700 yr BP) interval, constraining the regional distribution of the equilibrium-line altitude (ELA) of cirque and valley glaciers. Here we present evidence from a once glacier-fed lake on southern Andøya that contests this view. Analyses of radiocarbon dated lacustrine sediments including rock magnetic parameters, grain size, organic matter, dry bulk density and visual interpretation suggest that no glacier was present in the low-lying cirque during the Younger Dryas-Allerød. The initiation of the glacial retreat commenced with the onset of the Bølling warming ( 14,700 yr BP) and was completed by the onset of Allerød Interstade ( 13,400 yr BP). The reconstructed glacier stages of the investigated cirque coincide with a cool and dry period from  17,500 to 14,700 yr BP and a somewhat larger Last Glacial Maximum (LGM) advance possibly occurring between  21,050 and 19,100 yr BP.     

National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data

China is one of the countries where landslides caused the most fatalities in the last decades.The threat that landslide disasters pose to people might even be greater in the future,due to climate change and the increasing urbanization of mountainous areas.A reliable national-scale rainfall induced landslide suscep-tibility model is therefore of great relevance in order to identify regions more and less prone to landslid-ing as well as to develop suitable risk mitigating strategies.However,relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area.The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China.In this context,it is aimed to explore the benefit of mixed effects mod-elling to counterbalance associated bias propagations.Six influencing factors including lithology,slope,soil moisture index,mean annual precipitation,land use and geological environment regions were selected based on an initial exploratory data analysis.Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information:Set 1(disregards the presence of incomplete landslide information),Set 2(excludes factors related to the incompleteness of landslide data),Set 3(accounts for factors related to the incompleteness via random effects).The vari-able sets were then introduced in a generalized additive model(GAM:Set 1 and Set 2)and a generalized additive mixed effect model(GAMM:Set 3)to establish three national-scale statistical landslide suscep-tibility models:models 1,2 and 3.The models were evaluated using the area under the receiver operating characteristics curve(AUROC)given by spatially explicit and non-spatial cross-validation.The spatial pre-diction pattern produced by the models were also investigated.The results show that the landslide inven-tory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models.The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9.However,although Model 1 reached the highest AUROCs within non-spatial cross-validation(median of 0.9),it was not associated with the most plausible representation of landslide susceptibility.The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias.The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility.However,a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data(e.g.,the Kuenlun Mountains in the northern Tibetan Plateau).The non-linear mixed-effects model(Model 3)reduced the impact of these biases best by introducing bias-describing variables as random effects.Among the three models,Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive perfor-mance(median AUROC of spatial cross validation 0.84)compared to the other two models(median AUROCs of 0.81 and 0.79,respectively).We conclude that ignoring landslide inventory-based incomplete-ness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.     

Daily streamflow forecasting using a wavelet transform and artificial neural network hybrid models

Abstract

New wavelet and artificial neural network (WA) hybrid models are proposed for daily streamflow forecasting at 1, 3, 5 and 7 days ahead, based on the low-frequency components of the original signal (approximations). The results show that the proposed hybrid models give significantly better results than the classical artificial neural network (ANN) model for all tested situations. For short-term (1-day ahead) forecasts, information on higher-frequency signal components was essential to ensure good model performance. However, for forecasting more days ahead, lower-frequency components are needed as input to the proposed hybrid models. The WA models also proved to be effective for eliminating the lags often seen in daily streamflow forecasts obtained by classical ANN models. 

Editor D. Koutsoyiannis; Associate editor L. See

Citation Santos, C.A.G. and Silva, G.B.L., 2013. Daily streamflow forecasting using a wavelet transform and artificial neural network hybrid models. Hydrological Sciences Journal, 59 (2), 312–324.     

New method for estimating reference evapotranspiration and comparison with alternative methods in a fruit-producing hub in the semi-arid region of Brazil

Theoretical and Applied Climatology - Analysing alternative methods for estimating reference evapotranspiration (ET0) is essential for improving the management of water resources, especially where...     

Evaluation of the chemical stability of a landfilled primary lead smelting slag

A primary lead smelter operating in Santo Amaro, Bahia, Brazil, from 1960 to 1993 generated a large amount of slag that was landfilled close to the former smelter and used in roads and houses as a construction material. To evaluate the stability of the slag classical leaching procedures (TCLP, SWEP and SPLP) were applied. In addition, samples of the slag were placed in contact with HCl, HNO₃, HOAc and NaOH solutions for about 24 h at room temperature to simulate acidic and alkaline environments over a wide pH range. In the acidic environment Ca, Fe and Si are strongly solubilized, and Pb and Zn solubilization was significant only below pH 3. The lead slag was also in contact with purified water for a period of 30 days. The results show that Ca and Si were solubilized and Pb, Fe, and Zn were not detected in the solution. The solubilization kinetics are second order processes for both Ca and Si. The initial solubilization rate for Ca and Si are 4.6 and 0.6 mg/L/day, respectively. The main implication of these results is that the major potentially toxic elements of the lead slag landfilled at Santo Amaro were stabilized for a short contact time with pure water and for alkaline and acidic solutions to a pH of about 3 and the groundwater and the surface water contamination found at Santo Amaro smelter region cannot be directly attributed to the landfilled lead slag.     

Multifractal IDW interpolation and fractal filtering method in environmental studies: an application on regional stream sediments of (Italy), Campania region

In recent years environmental geochemical mapping has assumed an increasing relevance and separation of background values to evaluate pollution is, probably, even more critical than the separation between background and anomalies in mineral prospecting studies. The recognition of background values assumes particular relevance as a function of national environmental legislation, which fixes intervention limits for some elements, such as the harmful ones (e.g. As, Cd, Hg, Pb). In this paper a recently developed multifractal IDW interpolation method and a fractal filtering technique are applied to separate natural background and anthropogenic values for the compilation of environmental geochemical mapping from stream sediment samples of Campania region (Italy), where no mineralization occurs. To discuss the application of these recently developed techniques the elements Pb and U were selected because they show two completely different situations, the high Pb values being mostly of anthropogenic origin and high U values being mostly of geogenic origin. The new fractal filtering method works well in both extreme situations.