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Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.
Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment.
To support scientifically sound water management in dryland environments a modelling system has been developed for the quantitative assessment of water and sediment fluxes in catchments, transport in the river system, and retention in reservoirs. The spatial scale of interest is the mesoscale because this is the scale most relevant for management of water and land resources.
This modelling system comprises process-oriented hydrological components tailored for dryland characteristics coupled with components comprising hillslope erosion, sediment transport and reservoir deposition processes. The spatial discretization is hierarchically designed according to a multi-scale concept to account for particular relevant process scales. The non-linear and partly intermittent run-off generation and sediment dynamics are dealt with by accounting for connectivity phenomena at the intersections of landscape compartments. The modelling system has been developed by means of data from nested research catchments in NE-Spain and in NE-Brazil.
In the semi-arid NE of Brazil sediment retention along the topography is the main process for sediment retention at all scales, i.e. the sediment delivery is transport limited. This kind of deposition retains roughly 50 to 60 % of eroded sediment, maintaining a similar deposition proportion in all spatial scales investigated. On the other hand, the sediment retained in reservoirs is clearly related to the scale, increasing with catchment area. With increasing area, there are more reservoirs, increasing the possibility of deposition. Furthermore, the area increase also promotes an increase in flow volume, favouring the construction of larger reservoirs, which generally overflow less frequently and retain higher sediment fractions. The second example comprises a highly dynamic Mediterranean catchment in NE-Spain with nested sub-catchments and reveals the full dynamics of hydrological, erosion and deposition features. The run-off modelling performed well with only some overestimation during low-flow periods due to the neglect of water losses along the river. The simulated peaks in sediment flux are reproduced well, while low-flow sediment transport is less well captured, due to the disregard of sediment remobilization in the riverbed during low flow.
This combined observation and modelling study deepened the understanding of hydro-sedimentological systems characterized by flashy run-off generation and by erosion and sediment transport pulses through the different landscape compartments. The connectivity between the different landscape compartments plays a very relevant role, regarding both the total mass of water and sediment transport and the transport time through the catchment.
Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.
A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará’s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.
A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará’s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.
The epicardium, the outer mesothelial layer enclosing the myocardium, plays key roles in heart development and regeneration. During embryogenesis, the epicardium arises from the proepicardium (PE), a cell cluster that appears in the dorsal pericardium (DP) close to the venous pole of the heart. Little is known about how the PE emerges from the pericardial mesothelium. Using a zebrafish model and a combination of genetic tools, pharmacological agents and quantitative in vivo imaging, we reveal that a coordinated collective movement of DP cells drives PE formation. We found that Bmp signaling and the actomyosin cytoskeleton promote constriction of the DP, which enables PE cells to extrude apically. We provide evidence that cell extrusion, which has been described in the elimination of unfit cells from epithelia and the emergence of hematopoietic stem cells, is also a mechanism for PE cells to exit an organized mesothelium and fulfil their developmental fate to form a new tissue layer, the epicardium.
Climate science is highly interdisciplinary by nature, so understanding interactions between Earth processes inherently warrants the use of analytical software that can operate across the disciplines of Earth science. Toward this end, we present the Climate Data Toolbox for MATLAB, which contains more than 100 functions that span the major climate-related disciplines of Earth science. The toolbox enables streamlined, entirely scriptable workflows that are intuitive to write and easy to share. Included are functions to evaluate uncertainty, perform matrix operations, calculate climate indices, and generate common data displays. Documentation is presented pedagogically, with thorough explanations of how each function works and tutorials showing how the toolbox can be used to replicate results of published studies. As a well-tested, well-documented platform for interdisciplinary collaborations, the Climate Data Toolbox for MATLAB aims to reduce time spent writing low-level code, let researchers focus on physics rather than coding and encourage more efficacious code sharing. Plain Language Summary This article describes a collection of computer code that has recently been released to help scientists analyze many types of Earth science data. The code in this toolbox makes it easy to investigate things like global warming, El Nino, or other major climate-related processes such as how winds affect ocean circulation. Although the toolbox was designed to be used by expert climate scientists, its instruction manual is well written, and beginners may be able to learn a great deal about coding and Earth science, simply by following along with the provided examples. The toolbox is intended to help scientists save time, help them ensure their analysis is accurate, and make it easy for other scientists to repeat the results of previous studies.
Explaning change in flood hazard in the Mekong river : the hypothesis of nonstationary variance
(2013)
Intransitive competition is widespread in plant communities and maintains their species richness
(2015)
Intransitive competition networks, those in which there is no single best competitor, may ensure species coexistence. However, their frequency and importance in maintaining diversity in real-world ecosystems remain unclear. We used two large data sets from drylands and agricultural grasslands to assess: (1) the generality of intransitive competition, (2) intransitivity-richness relationships and (3) effects of two major drivers of biodiversity loss (aridity and land-use intensification) on intransitivity and species richness. Intransitive competition occurred in >65% of sites and was associated with higher species richness. Intransitivity increased with aridity, partly buffering its negative effects on diversity, but was decreased by intensive land use, enhancing its negative effects on diversity. These contrasting responses likely arise because intransitivity is promoted by temporal heterogeneity, which is enhanced by aridity but may decline with land-use intensity. We show that intransitivity is widespread in nature and increases diversity, but it can be lost with environmental homogenisation.