Forecasting invasions: resource use by mussels informs invasion patterns along the South African coast

Invasive species are often more able to rapidly and efficiently utilise resources than natives, and comparing per capita resource use at different resource densities among invaders and trophically analogous natives could allow for reliable predictions of invasiveness. In South Africa, invasion by the Mediterranean mussel Mytilus galloprovincialis has transformed wave-exposed shores, negatively affecting native mussel species. Currently, South Africa is experiencing a second mussel invasion with the recent detection of the South American Semimytilus algosus. We tested per capita uptake of an algal resource by invading M. galloprovincialis, S. algosus, and the native Aulacomya atra at different algal concentrations and temperatures, representing the west and south coasts of South Africa, to examine whether their per capita resource use could be a predictor of their spread and subsequent invasiveness. Regardless of temperature, M. galloprovincialis was the most efficient consumer, significantly reducing algal cells compared to the other species when the resource was presented in both low and high starting densities. Furthermore, these findings aligned with a greater biomass of M. galloprovincialis on the shore in comparison with the other species. Resource use by the new invader S. algosus was dependent on the density of resource and, although this species was efficient at low algal concentrations at cooler temperatures, this pattern broke down at higher algal densities. This was once more reflected in lower biomass in surveys of this species along the cool west coast. We therefore forecast that S. algosus will be become established along the south coast; however, we also predict that M. galloprovincialis will maintain dominance on these shores.

The Baltic Dry Index: cyclicalities, forecasting and hedging strategies

The cyclical properties of the Baltic Dry Index (BDI) and their implications for forecasting performance are investigated. We find that changes in the BDI can lead to permanent shocks to trade of major exporting economies. In our forecasting exercise, we show that commodities and trigonometric regression can lead to improved predictions and then use our forecasting results to perform an investment exercise and to show how they can be used for improved risk management in the freight sector.

Hydrological and photochemical influence on dynamics of estuarine bacteria

Os estuários são ecossistemas complexos, onde os processos físicos, químicos e biológicos estão intimamente ligados. A dinâmica bacteriana num estuário reflete a interação e a elevada variação temporal e espacial desses processos. Este trabalho teve como objetivo elucidar as interações entre os processos físicos, fotoquímicos e microbiológicos no sistema estuarino da Ria de Aveiro (Portugal). Para tal, foi realizada uma abordagem inicial no campo, durante a qual as comunidades bacterianas na coluna de água foram caracterizadas em termos de abundância e atividade ao longo de 2 anos. O estudo foi realizado em dois locais distintos, escolhidos por tipificarem as características marinhas e salobras do estuário. Estes locais possuem diferentes hidrodinâmicas, influências fluviais e, quantidade e composição de matéria orgânica. Numa perspectiva mecanicista, foram realizadas simulações laboratoriais no sentido de elucidar a resposta das bactérias à matéria orgânica foto-transformada. As comunidades bacterianas no estuário adaptam-se a diferentes regimes de água doce, desenvolvendo padrões de abundância e atividade distintos nas zonas marinha e salobra. Os elevados caudais dos rios induzem estratificação vertical na zona marinha, promovendo o fluxo de fitoplâncton do mar para o estuário, do bacterioplâncton do estuário para o mar, e estimulam a importação de bactérias aderentes a partículas na zona salobra. O transporte advectivo e os processos de ressuspensão contribuem para aumentar 3 vezes o número de bactérias aderentes a partículas durante os períodos de intensas descargas fluviais. Adicionalmente, a atividade bacteriana no estuário é controlada pela concentração de azoto inerente à variações de água doce. O fornecimento de azoto em associação com a fonte dos substratos bacterianos induzem alterações significativas na produtividade. O padrão de variação vertical de comunidades bacterianas foi distinto nas duas zonas do estuário. Na zona marinha, as bactérias na microcamada superficial (SML) apresentaram taxas de hidrólise mais elevadas, mas menores taxas de incorporação de monómeros e produção de biomassa que na água subjacente (UW), enquanto na zona salobra, as taxas de hidrólise e incorporação foram similares nos dois compartimentos, mas a produtividade foi significativamente mais elevada na SML. Apesar da abundância bacteriana ter sido semelhante na SML e UW, a fração de células aderentes a partículas foi significativamente maior na SML (2-3 vezes), em ambas as zonas do estuário. A integração dos resultados microbiológicos com as variáveis ambientais e hidrológicos mostraram que fortes correntes na zona marinha promovem a mistura vertical, inibindo o estabelecimento de uma comunidade bacteriana na SML distinta da UW. Em contraste, na zona de água salobra, a menor velocidades das correntes fornece as condições adequadas ao aumento da atividade bacteriana na SML. Características específicas do local, tais como a hidrodinâmica e as fontes e composição da matéria orgânica, conduzem também a diferentes graus de enriquecimento superficial de matéria orgânica e inorgânica, influenciando a sua transformação. Em geral, o ambiente da SML estuarina favorece a hidrólise de polímeros, mas inibe a utilização de monómeros, comparativamente com água subjacente. No entanto, as diferenças entre as duas comunidades tendem a atenuar-se com o aumento da atividade heterotrófica na zona salobra. A matéria orgânica dissolvida cromófora (CDOM) das duas zonas do estuário possui diferentes características espectrais, com maior aromaticidade e peso molecular médio (HMW) na zona de água salobra, em comparação com a zona marinha. Nesta zona, a abundância bacteriana correlacionou-se com a350 e a254, sugerindo uma contribuição indireta das bactéria para HMW CDOM. A irradiação do DOM resultou numa diminuição dos valores de a254 e a350, e, em um aumento do declive S275-295 e dos rácios E2:E3 (a250/a365) e SR. No entanto, a extensão de transformações foto-induzidas e as respostas microbianas são dependentes das características iniciais CDOM, inferidas a partir das suas propriedades ópticas. A dinâmica estuarina influencia claramente as atividades heterotróficas e a distribuição dos microorganismos na coluna de água. A entrada de água doce influencia a dinâmica e os principais reguladores das comunidades bacterianas no estuário. Os processos fotoquímicos e microbianos produzem alterações nas propriedades ópticas da CDOM e a combinação desses processos determina o resultado global e o destino da CDOM nos sistemas estuarinos com influência na produtividade nas áreas costeiras adjacente.

Understanding and modelling hydrological and soil erosion processes in burnt forest catchments

Forest fires implications in overland flow and soil erosion have been researched for several years. Therefore, is widely known that fires enhance hydrological and geomorphological activity worldwide as also in Mediterranean areas. Soil burn severity has been widely used to describe the impacts of fire on soils, and has being recognized as a decisive factor controlling post-fire erosion rates. However, there is no unique definition of the term and the relationship between soil burn severity and post-fire hydrological and erosion response has not yet been fully established. Few studies have assessed post-fire erosion over multiple years, and the authors are aware of none which assess runoff. Small amount of studies concerning pre-fire management practices were also found. In the case of soil erosion models, the Revised Universal Soil Loss Equation (RUSLE) and the revised Morgan–Morgan–Finney (MMF) are well-known models, but not much information is available as regards their suitability in predicting post-fire soil erosion in forest soils. The lack of information is even more pronounced as regards post-fire rehabilitation treatments. The aim of the thesis was to perform an extensive research under the post fire hydrologic and erosive response subject. By understanding the effect of burn severity in ecosystems and its implications regarding post fire hydrological and erosive responses worldwide. Test the effect of different pre-fire land management practices (unplowed, downslope plowed and contour plowed) and time-since-fire, in the post fire hydrological and erosive response, between the two most common land uses in Portugal (pine and eucalypt). Assess the performance of two widely-known erosion models (RUSLE and Revised MMF), to predict soil erosion rates during first year following two wildfires of distinctive burn severity. Furthermore, to apply these two models considering different post-fire rehabilitation treatments in an area severely affected by fire. Improve model estimations of post-fire runoff and erosion rates in two different land uses (pine and eucalypt) using the revised MMF. To assess these improvements by comparing estimations and measurements of runoff and erosion, in two recently burned sites, as also with their post fire rehabilitation treatments. Model modifications involved: (1) focusing on intra-annual changes in parameters to incorporate seasonal differences in runoff and erosion; and (2) inclusion of soil water repellency in runoff predictions. Additionally, validate these improvements with the application of the model to other pine and eucalypt sites in Central Portugal. The review and meta-analysis showed that fire occurrence had a significant effect on the hydrological and erosive response. However, this effect was only significantly higher with increasing soil burn severity for inter-rill erosion, and not for runoff. This study furthermore highlighted the incoherencies between existing burn severity classifications, and proposed an unambiguous classification. In the case of the erosion plots with natural rainfall, land use factor affected annual runoff while land management affected both annual runoff and erosion amounts significantly. Time-since-fire had an important effect in erosion amounts among unplowed sites, while for eucalypt sites time affected both annual runoff and erosion amounts. At all studied sites runoff coefficients increase over the four years of monitoring. In the other hand, sediment concentration in the runoff, recorded a decrease during the same period. Reasons for divergence from the classic post-fire recovery model were also explored. Short fire recurrence intervals and forest management practices are viewed as the main reasons for the observed severe and continuing soil degradation. The revised MMF model presented reasonable accuracy in the predictions while the RUSLE clearly overestimated the observed erosion rates. After improvements: the revised model was able to predict first-year post-fire plot-scale runoff and erosion rates for both forest types, these predictions were improved both by the seasonal changes in the model parameters; and by considering the effect of soil water repellency on the runoff, individual seasonal predictions were considered accurate, and the inclusion of the soil water repellency in the model also improved the model at this base. The revised MMF model proved capable of providing a simple set of criteria for management decisions about runoff and erosion mitigation measures in burned areas. The erosion predictions at the validation sites attested both to the robustness of the model and of the calibration parameters, suggesting a potential wider application.

Hydrological modelling of Maranhão and Pracana Basins, a first approach

Modelling the hydrology of hydrographic basins has shown itself as a useful tool in environment management. The hydrological models can be used for multiple purposes: estimate runoff from sequences of rainfall, access stream water quality, quantify the diffuse pollution that reaches water masses such as estuaries, rivers and lakes, etc. This study has as final objective to simulate and analyse the flow, sediment transport and water quality as a function of landuse and soil type in the basins of Maranhão and Pracana. The modelling system used is SWAT, Soil Water Assessment Tool. In this first phase of the study the hydrodynamic calibration of the model was performed using measurements of average daily flows in five stations. The model compares well with the measurements; the annual average flows are similar and the majority of the measured flow peaks coincide with the model peaks.

SETAR nonlinearity, nonstationarity and forecasting

Tese de dout., Métodos Quantitativos Aplicados à Economia e à Gestão, Faculdade de Economia, Universidade do Algarve, 2008

Spatial variability of macroinvertebrate assemblages and the influence of hydrological and environmental variables along the Sigi River, Tanzania-East Africa

The study of investigating the spatial and temporal variability of macroinvertebrate and their relation to hydrology, hydraulic and environmental factors was done along the Sigi River during two sampling periods in the dry (March) and wet (May) periods of 2012. The river was demarcated based on slope ranges and five river zones were identified as mountains streams (MS), upper foothills (UF), lower foothills (LF), rejuvenated foothills (REJ) and mature lower river (MR). Samples of macroinvertebrate were collected from the five river zones and measurements of hydrological (discharge), hydraulics (Depth, velocity and Froude number) and Environmental (pH, Temperature, substrate, conductivity) parameters were done in each zone. In characterizing the macroinvertebrate assemblages along the Sigi River diversity indices (number of taxa, total abundances, Margalef richness index and ShannonWiener index) were calculated and the most representative species for the spatial and temporal variation were identified. Melanoides and Afronurous showed differences in abundance in two samplings periods while Cleopatra, Potamonautes, Ephemerythus, Neoperla, Caenis, Ceratogomphus and Cheumatopsyche showed significant difference among the river zones. Spearman rank correlation and Distance Linear Model (DistLM) used to revealed physical factors governing the macroinvertebrate assemblages distribution. The study demonstrated that the variation of physical factors like discharge, temperature, conductivity and pH have an important role in the spatial distribution of macroinvertebrate assemblages along the river and the life cycle of macroinvertebrate (Afronurus) is important in determining the temporal variability.

Catchment influences on the hydrological flows to lake terra alta (Linhares, ES, Brazil) and ecohydrology perspectives

Dissertação de mestrado, Ecohidrologia, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Application of WRF-Chem to Forecasting PM10 Concentration over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains using the GFS meteorological data and the TNO MACC II emissions. Forecasts, with 48h lead time, were run for a winter and summer period 2014. WRF-Chem in general captures the variability in observed PM10 concentrations, but underestimates some peak concentrations during winter-time. The peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. Such episodes lead to increased combustion in residential heating, where hard coal is the main fuel in Poland. This suggests that a key to improvement in the model performance for the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Chem.

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150forecasting model, which was accurate (correlation between observed and predicted values varied from rs=0.57 to rs=0.68).

Forecasting overseas visitors into the United Kingdom using continuous time and autoregressive fractional integrated moving average models with discrete data

This paper applies Gaussian estimation methods to continuous time models for modelling overseas visitors into the UK. The use of continuous time modelling is widely used in economics and finance but not in tourism forecasting. Using monthly data for 1986–2010, various continuous time models are estimated and compared to autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models. Dynamic forecasts are obtained over different periods. The empirical results show that the ARIMA model performs very well, but that the constant elasticity of variance (CEV) continuous time model has the lowest root mean squared error (RMSE) over a short period.

Volatility and VaR Forecasting in the Madrid Stock Exchange

This paper provides an empirical study to assess the forecasting performance of a wide range of models for predicting volatility and VaR in the Madrid Stock Exchange. The models performance was measured by using different loss functions and criteria. The results show that FIAPARCH processes capture and forecast more accurately the dynamics of IBEX-35 returns volatility. It is also observed that assuming a heavy-tailed distribution does not improve models ability for predicting volatility. However, when the aim is forecasting VaR, we find evidence of that the Student’s t FIAPARCH outperforms the models it nests the lower the target quantile.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.