• Energy Research
• Closed Access close
• 15. Life on land close
• IT close
• NO close

Climate change has become an important issue for scientific community, for its numerous impacts, especially on agriculture and environment. To shed light on this phenomenon, long data-sets of meteorological data as well as temperature and rainfall extreme events are needed, since they are important climate variability indicators. In a small semi-agricultural catchment of the Italian Apennines, drained by the Centonara Stream, weather data have been monitored for 30 years (1986–2015). Here, their trend was identified with Mann–Kendall test, and the temperature and precipitation extremes were characterized by means of specific indices. Data were analyzed at event, daily, seasonal, and annual bases. In addition, to understand implications of rainfall patterns on catchment hydrological response, a total of 388 rainfall–streamflow events (recorded during 1994–2009) were analyzed. Results showed a significant increase of temperature (minimum (Tn), mean (Tm), and maximum (Tx)), both at annual and seasonal base, except for Winter, with an annual mean increase of 0.08, 0.09, and 0.13 °C year−1 for Tn, Tm, and Tx, respectively. Annual rainfall data showed a positive trend for the number of wet days, but not in the quantity. In Winter, the rainfall amount and the number of wet days increased. The annual number of rainfall extreme events (P > 20.2 mm and D > 18.3 h) significantly increased, especially in spring and autumn. The rainfall–streamflow relationship suggested that the flow response of the Centonara Stream depends mainly on the rainfall amount. So, since the number of extreme events (P > 20.2 mm) is increasing in spring and autumn, an increase of events with high streamflow in these seasons may occur.

AbstractIn this manuscript we reply to the issues raised by G. Bagheri and C. Bonadonna in their comment 2019JB017697. We reiterate our definition of particle Reynolds number, which is appropriate for our data set of experimental measurements, and we show that the poor performance of Bagheri and Bonadonna (2016, https://doi.org/10.1016/j.powtec.2016.06.015) model discussed in Dioguardi et al. (2018, https://doi.org/10.1002/2017JB014926) was mainly due to the typos in the equations presented in their original manuscript. We believe that the iterative methodology for calculating the drag coefficient is not strictly necessary for our data set. In this reply, however, we also include results of the intercomparison study among different drag models using the iterative methodology. Results show that the performance of the different drag models considered in the intercomparison study is not significantly affected by the employed methodology (direct vs. iterative) and that, regardless the employed methodology and unlike what has been stated in the comment 2019JB017697, our model has the best performance in reproducing the experimentally measured terminal velocities.

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.

Solar radiation incident on the Earth’s surface is a determining factor of climate on Earth, hence having a proper solar radiation database is crucial in understanding climate processes in the Earth’s atmosphere. Solar radiation data may be used in the development of insolation maps, analysis of crop growth and in the simulation of solar systems. Unfortunately, measured solar radiation data may not be available in locations where it is most needed. An alternative to obtaining observed data is to estimate it using an appropriate solar radiation model. The purpose of this study is to assess the performance of thirteen global solar radiation empirical formulations, in Kampala, Uganda, located in an African Equatorial region. The best performing formulations were determined using the ranking method. The mean bias error, root mean square error and t-statistic value were calculated and utilized in the ranking process. Results have shown that the formulation: \({\bar H}/{\bar H }_0 = a + b({\bar S}/{\bar S} _0 ) + c( {\bar S } /{\bar S} _0)^2\) is ranked the highest and therefore is the recommended empirical equation for the estimation of the monthly mean global solar irradiation in Kampala, Uganda and in other African Equatorial locations with similar climate and terrain.

Coral reefs in the tropical Pacific region are exposed to a range of anthropogenic local pressures. Climate change is exacerbating local impacts, causing unprecedented declines in coral reef habitats and bringing negative socio-economic consequences to Pacific communities who depend heavily on coral reefs for food, income and livelihoods. Continued increases in greenhouse gas emissions will drive future climate change, which will accelerate coral reef degradation. Traditional systems of resource governance in Pacific island nations provide a foundation to address local pressures and build reef resilience to climate change. Management and adaptation options should build on the regional diversity of governance systems and traditional knowledge to support community-based initiatives and cross-sectoral cooperation to address local pressures and minimize climate change impacts. Such an inclusive approach will offer enhanced opportunities to develop and implement transformative adaptation solutions, particularly in remote and regional areas where centralized management does not extend.

Enrichment of activity sludge allowed to select a suitable microbial mixed culture able to grow on crude glycerol as the only carbon source, using a very simple synthetic medium without any extra nutrient supplements. Following to statistical optimisation, the selected pool was able to effectively convert crude glycerol into H2 and ethanol, both at a near¬stoichiometric yield. Subsequently, upscale tests were performed to validate the statistical model, and fed¬batch tests, in non¬sterile conditions, led to a three¬fold increase of ethanol production, thus reaching 26g/L, while producing up to 9L of H2. These results were obtained without the use of vitamin¬ and trace element solution, tryptone or yeast extract. Based on these findings it seems feasible to totally exclude the use of any synthetic medium for glycerol fermentation, through the co ¬fermentation with other waste/residual (organic) compounds, i.e. proteins and carbohydrates derived from the microalgae. In this way it might be possible to link 3rd generation biodiesel with H2 and ethanol production, while avoiding the competition with food feedstock and agricultural land use. Moreover, the valorisation of crude glycerol (converted into high¬ value products) might contribute to enhance the economic viability of microalgae feedstock and biofuels, which are, at the moment, still too costly to be commercialized. Proceedings of the 20th European Biomass Conference and Exhibition, 18-22 June 2012, Milan, Italy, pp. 713-716

Seagrass systems of the Western Pacific region are biodiverse habitats, providing vital services to ecosystems and humans over a vast geographic range. SeagrassNet is a worldwide monitoring program that collects data on seagrass habitats, including the ten locations across the Western Pacific reported here where change at various scales was rapidly detected. Three sites remote from human influence were stable. Seagrasses declined largely due to increased nutrient loading (4 sites) and increased sedimentation (3 sites), the two most common stressors of seagrass worldwide. Two sites experienced near-total loss from of excess sedimentation, followed by partial recovery once sedimentation was reduced. Species shifts were observed at every site with recovering sites colonized by pioneer species. Regulation of watersheds is essential if marine protected areas are to preserve seagrass meadows. Seagrasses in the Western Pacific experience stress due to human impacts despite the vastness of the ocean area and low development pressures.

The aim of this work was to highlight the main ecological predictors driving invertebrate distribution in eight glacier-fed streams in the Southern Alps. Thirty-five sites belonging to four stream types were sampled monthly during the ablation season of one, two or three years between 1996 and 2014. Taxa from glacial (kryal and glacio-rhithral) and non-glacial (kreno-rhithral and lake outlet) sites were separated by canonical correspondence analysis (CCA) along a glacial influence gradient and a hydrological-altitudinal gradient. High glacial influence was associated mainly with low maximum water temperature (Tmax), high Glacial Index (calculated as a function of glacier area and distance from the glacier), and the abundance of Diamesa species (D. steinboecki, D. goetghebueri, D. zernyi, and D. latitarsis). Change-point analysis and Threshold Indicator Taxa Analysis confirmed the CCA results in identifying these Diamesa species as the taxa with the strongest preference for high percent glacier cover in the catchment (change point~30%) and low Tmax (change point~6°C). Temporal changes in community structure were highlighted in seven sites fed by glaciers under different retreat rates. Where the rate was faster and the remaining glacier smaller (≪1km2), the most cold-stenothermal kryal inhabitant, D. steinboecki, almost disappeared or survived only as brachypterous populations, whereas other Diamesinae (Pseudokiefferiella parva), Orthocladiinae (e.g. Eukiefferiella, Orthocladius), Limoniidae, Baetidae, Nemouridae, and non-insect taxa (e.g. Oligochaeta, Hydracarina) became more abundant. Upstream migration was observed in Diamesa spp. which conquered new stream reaches left free by the retreating glacier, and euriecious taxa which colonized reaches with ameliorated environmental conditions, no longer the exclusive habitat of Diamesa spp. Co-occurrence of stochastic and deterministic assembly processes seem to drive spatio-temporal changes in these invertebrate communities. Long-term ecological studies on the adaptive biology of kryal species will be useful to predict the fate of Alpine biodiversity.

AbstractThe classic 10‐year population cycle of snowshoe hares (Lepus americanus,Erxleben 1777) and Canada lynx (Lynx canadensis, Kerr 1792) in the boreal forests ofNorth America has drawn much attention from both population and community ecologists worldwide; however, the ecological mechanisms driving the 10‐year cyclic dynamic pattern are not fully revealed yet. In this study, by the use of historic fur harvest data, we constructed a series of generalized additive models to study the effects of density dependence, predation, and climate (both global climate indices ofNorth Atlantic Oscillation index (NAO),Southern Oscillation index (SOI) and northern hemispheric temperature (NHT) and local weather data including temperature, rainfall, and snow). We identified several key pathways from global and local climate to lynx with various time lags: rainfall shows a negative, and snow shows a positive effect on lynx;NHTandNAOnegatively affect lynx through their positive effect on rainfall and negative effect on snow;SOIpositively affects lynx through its negative effect on rainfall. Direct or delayed density dependency effects, the prey effect of hare on lynx and a 2‐year delayed negative effect of lynx on hare (defined as asymmetric predation) were found. The simulated population dynamics is well fitted to the observed long‐term fluctuations of hare and lynx populations. Through simulation, we find density dependency and asymmetric predation, only producing damped oscillation, are necessary but not sufficient factors in causing the observed 10‐year cycles; while extrinsic climate factors are important in producing and modifying the sustained cycles. Two recent population declines of lynx (1940–1955 and after 1980) were likely caused by ongoing climate warming indirectly. Our results provide an alternative explanation to the mechanism of the 10‐year cycles, and there is a need for further investigation on links between disappearance of population cycles and global warming in hare–lynx system.