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Wind power production is uncertain. The imbalance between committed and delivered energy in pool markets leads to the increase of system costs, which must be incurred by defaulting producers, thereby decreasing their revenues. To avoid this situation, wind producers can submit their bids together with hydro resources. Then the mismatches between the predicted and supplied wind power can be used by hydro producers, turbining or pumping such differences when convenient. This study formulates the problem of hydro-wind production optimization in operation contexts of pool market. The problem is solved for a simple three-reservoir cascade case to discuss optimization results. The results show a depreciation in optimal revenues from hydro power when wind forecasting is uncertain. The depreciation is caused by an asymmetry in optimal revenues from positive and negative wind power mismatches. The problem of neutralizing the effect of forecasting uncertainty is subsequently formulated and solved for the three-reservoir case. The results are discussed to conclude the impacts of uncertainty on joint bidding in pool market contexts.

Short-Term Load Forecasting is critical for reliable power system operation, and the search for enhanced methodologies has been a constant field of investigation, particularly in an increasingly competitive environment where the market operator and its participants need to better inform their decisions. Hence, it is important to continue advancing in terms of forecasting accuracy and consistency. This paper presents a new deep learning-based ensemble methodology for 24 h ahead load forecasting, where an automatic framework is proposed to select the best Box-Jenkins models (ARIMA Forecasters), from a wide-range of combinations. The method is distinct in its parameters but more importantly in considering different batches of historical (training) data, thus benefiting from prediction models focused on recent and longer load trends. Afterwards, these accurate predictions, mainly the linear components of the load time-series, are fed to the ensemble Deep Forward Neural Network. This flexible type of network architecture not only functions as a combiner but also receives additional historical and auxiliary data to further its generalization capabilities. Numerical testing using New England market data validated the proposed ensemble approach with diverse base forecasters, achieving promising results in comparison with other state-of-the-art methods.

Highlights • Ambient temperatures were up to 42% higher in clearcut stands than native forest. • Abundance of C. chilensis is concentrated near the edge and high in native forest. • Ambient temperature and month are the most influential predictor of the abundance. • Ambient temperature surpasses physiological performance of C. chilensis. Abstract The intensive management of tree plantations has replaced and fragmented native forests worldwide. A direct consequence of this activity is the creation of new edges, which generate changes in microclimatic conditions in the adjacent forest as well as in the neighboring clearcut stands left over after harvesting by clearcut logging. Thus, newly created anthropogenic thermal gradients could influence ectothermic responses regarding abundance and physiology of native species in fragmented landscapes. Interestingly, the consequences of these changes have not been studied in insects. To test the effects of the anthropogenic thermal gradient on the abundance and physiology of ectothermic species, we chose the fragmented Maulino forest and the ground-dwelling beetle Ceroglossus chilensis (Coleoptera: Carabidae) as our biological model, working with seven fragments of native forest surrounded by active and clearcut pine plantation stands. We measured temperature variables and beetle abundance in different months using transects perpendicular to the edge and used general linear modelling to explain abundance with temperature. In addition, we assessed the preferential body temperatures (T b) and Rollover Speed (RoS) of C. chilensis at five different temperatures in controlled conditions to explain field abundance. We found that mean ambient temperatures were up to 42% higher in clearcut stands than in native forest fragments during summer. However, ambient temperatures in autumn were similar between native forest fragments and clearcut stands. The abundance of C. chilensis , is concentrated near the edge in the native forest (between 2 and 10 m to interior of native forest), regardless of month sampled. The abundance of C. chilensis was higher at the edge than inside native forest interiors or clearcut stands, regardless of the month. Ambient temperature surpasses preferential body temperature (14–15.99 °C) and physiological performance of C. chilensis (15 °C), particularly during summer. Ceroglossus chilensis abundance at the edge of clearcut stands could be favored by understory structural complexity in understory vegetation, creating suitable microclimatic conditions and increasing abundance of prey resource. In essence, we found that the higher temperatures found near the edge inside forest interiors might enable individuals of C. chilensis to display thermoregulatory behavior by concentrating activity at these particular regions, resulting in increased abundances and more concentrated occurrences, helping to explain the edge-biased distribution. Thus, we offer evidence that physiological performance might be a key functional trait to explain abundance of ectothermic species in fragmented forest landscapes. We submit to decision makers linked to the forestry industry, that managing the understory of young tree plantations and increasing the structural complexity at remnant forest edges to cushion high temperatures in clearcut stands would enable more effective conservation planning of thermosensitive ectotherms in disturbed forest landscapes. [ABSTRACT FROM AUTHOR]

Fungi execute many ecosystem functions and are thus expected to contribute substantially to ecosystem stability along environmental gradients. Here, we aimed to describe the fungal communities along a vegetation gradient found in Amazonian cangas using ITS2 metabarcoding. Rupestrian canga vegetation covers ironstone outcrops from the Carajás National Forest and the Campos Ferruginosos National Park of the Eastern Amazon. We detected 3574 operational taxonomic unit sequences dominated by the phyla Ascomycota , Basidiomycota , and Glomeromycota. The taxonomic and functional groups differed among periodically inundated grasslands (GR), typical scrublands (SB), Vellozia scrublands (VL), and woodlands (WD). Saprotrophic fungi were the most abundant, occurring primarily in WD, while stress-tolerant lineages and functional groups were dominant in environments with less soil. Our results provide new insights into the fungal ecology on ironstone outcrops and shed light on the importance of these organisms in enabling growth of vegetation cover, promoting species coexistence and increasing degrees of plant diversity in these harsh environments. • Metabarcoding reveals high fungal diversity in Amazonian ironstone outcrops. • Dothideomycetes and Agaricomycetes predominate in soils from canga ecosystems. • Fungal communities differ among canga formations. • Canga ecosystems harbor many fungi tolerant to extreme conditions. • The high number of unidentified OTUs highlights the need for further research. [ABSTRACT FROM AUTHOR]

Land use change can reduce the wealth and wellbeing of a nation by modifying its biodiversity. We used value transfer methodology to estimate changes in the value of ecosystem services provided by natural ecosystems in El Salvador, a country particularly impacted by natural disasters. Ecosystem services (1998–2011) provided annually only by natural ecosystems declined by 2.6%, and are equal to 44% of El Salvador’s GDP in 2011. Changes in services provided by tropical forests account for 90% of those losses, followed by 9% for coastal wetlands. However, sensitivity analysis of changes per biome revealed that changes for coastal wetlands are much more elastic than for tropical forests, emphasizing the severity that further losses in coastal wetlands may incur. Forests reduce soil erosion and landslides while coastal wetlands reduce hurricane damages. Focusing conservation efforts towards these ecosystems could reduce the occurrence of natural disasters, but their services should be complemented by those generated in the agricultural matrix during forest and mangrove resurgence. [ABSTRACT FROM AUTHOR]