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Preface: Emerging trends in aquatic ecology II
No full textWe are proud to present this Special Issue of Hydrobiologia, which celebrates the publication of the 800th Volume of the journal
Historic nitrogen deposition determines future climate change effects on nitrogen retention in temperate forests
No full textNitrogen (N) cycle processes in terrestrial ecosystems are highly sensitive to temperature and soil moisture variations. Thus, future climate change may affect the degree to which N deposited from the atmosphere will be retained in forest ecosystems. We evaluated the effect of future changes in climate and N deposition on ecosystem N cycling using the model LandscapeDNDC forced with historical data from eight long-term forest ecosystem monitoring stations in Austria and downscaled future N deposition and climate scenarios. With every 1 ?C of warming, annual N uptake in biomass increased by +0.03 to +0.54 kg N ha?\u271, total soil organic matter (SOM) increased annually by +0.003 to +0.08 kg N ha?\u271, and mean annual N leaching was between ?\u270.09 and ?\u272.03 kg N ha?\u271 lower. The magnitude of N deposition in the years from 1990 to 2010 was by far the most important determinant of the response of nitrogen cycling to future warming, including statistically significant relationships with humus N content and N leaching. We conclude that climate change will likely increase ecosystem N retention in temperate forest ecosystems, and even more so at forest sites with high past N deposition
Climate impacts on global hot spots of marine biodiversity.
No full textHuman activities drive environmental changes at scales that could potentially cause ecosystem collapses in the marine environment. We combined information on marine biodiversity with spatial assessments of the impacts of climate change to identify the key areas to prioritize for the conservation of global marine biodiversity. This process identified six marine regions of exceptional biodiversity based on global distributions of 1729 species of fish, 124 marine mammals, and 330 seabirds. Overall, these hot spots of marine biodiversity coincide with areas most severely affected by global warming. In particular, these marine biodiversity hot spots have undergone local to regional increasing water temperatures, slowing current circulation, and decreasing primary productivity. Furthermore, when we overlapped these hot spots with available industrial fishery data, albeit coarser than our estimates of climate impacts, they suggest a worrying coincidence whereby the world\u27s richest areas for marine biodiversity are also those areas mostly affected by both climate change and industrial fishing. In light of these findings, we offer an adaptable framework for determining local to regional areas of special concern for the conservation of marine biodiversity. This has exposed the need for finer-scaled fishery data to assist in the management of global fisheries if the accumulative, but potentially preventable, effect of fishing on climate change impacts is to be minimized within areas prioritized for marine biodiversity conservation
Fish fauna of the deep subalpine lakes: present status and trends
No full textNot availableLarge and deep subalpine lakes represent an important resource for biodiversity and ecosystem services such as tourism, water supply for agriculture, drinking and power production, and fishery. In Italy, they constitute more than 80% of the total lacustrine volume and are located in one of the most populated and industrialised areas in Europe which contains approximately 16 million inhabitants. Subalpine lakes have been under significant pressure since the first decades of the XX century. Cultural eutrophication and chemical pollution of industrial origin have impacted or are still impacting lakes and their catchments. Additionally, hydromorphological pressures such as dam construction and water abstraction for agriculture, drinking water and power production have significantly affected lake tributaries and outlets, with further cascading effects on lacustrine biological communities, including fish. Recently, climate change has added to this array of adverse effects on the physical, chemical and biological environments of subalpine lakes and their catchments. Finally, the spread of non-native species in these habitats has recently become significant concern in relation to biodiversity conservation
Variability of ant community composition in cork oak woodlands across the Mediterranean region: implications for forest management
No full textWe evaluated the potential use of ants as a powerful tool for environmental monitoring, together with the applicability of the functional group approach as an alternative method for studying ant communities in cork oak woodlands. Variations in ant community composition, diversity and functional groups were studied in two cork oak forested sites across the Mediterranean region. Ants were sampled using pitfall traps placed along linear transects at 12 sites located in the main cork districts of Italy and Morocco (Gallura in Sardinia, and Ma?mora, east of Rabat). A total of 13.501 specimens were collected, belonging to 38 species (five shared species). A distinct separation in the NMDS plots between Gallura and Ma?mora ant assemblages was clearly visible. Ant species composition was widely different between the two districts and significant differences were detected within the Gallura district at the species level. Opportunist species were well represented in Gallura (about 27% of average Bray-Curtis similarity) as well as cryptic species (over 23%). In the Ma?mora forest, generalized Myrmicinae, hot climate specialists and opportunists contributed equally to the average similarity (together about 53%). Multi-scale ant diversity showed that the true turnover was higher in Gallura than in Ma?mora. These findings support the idea that the functional group approach, rather than species diversity per se, could be considered as a valuable tool to detect the response of the ant community to environmental changes in Mediterranean cork oak woodlands. Using ants as bioindicators could help not only in detecting early warning signs of habitat disturbance, but also in defining a useful management strategy to increase the resilience of agroforestry systems under future global change scenarios
Invasive species in inland waters: from early detection to innovative management approaches
No full textInvasive alien species are one of the major threats to biodiversity and the functioning of ecosystems (Vitousek et al. 1997; Garcia-Berthou et al. 2005), having serious consequences for the ecological status of inland water
On the interest of the spectral bands in the automatic selection of high quality MODIS data through spatial pattern identification.
No full textMODIS (MODerate resolution Imaging Spectroradiometer) daily surface reflectance data is distributed with one of the most complete quality ancillary data sets. Such amount of quality information is essential for automatically selecting the highest quality MODIS daily images, for example using geostatistical analysis of the image spatial pattern. However, the success of this automatic selection certainly could depend on the spectral information of each MODIS band. This work studies the influence of MODIS spectral bands on the automatic identification of high quality daily images by analyzing their variogram and aiming at the identification of the most suitable spectral band (or band combination) for the spatial characterization of a given geographical region. The analysis tests the influence of each of the reflectance bands of the 2009 MOD09GA Daily Surface Reflectance product and the first component of its Principal Component Analysis over an area of 32 000 km2 , Catalonia (northeast of the Iberian Peninsula). Specifically, the combination of quality data and the variogram analysis allows the detection of different anomalies by the correspondence between the variability among the pixels and the fitted variogram parameters: nugget, sill and range. The variogram analysis is reaffirmed as an extremely useful approach for the automatic selection of high quality images while highlighting the need of high computational techniques for such huge processing. Finally, it reveals that is crucial to select the appropriate spectral band in order to, not only optimize, but substantially improve the automatic selection of remote sensing images using geostatistical analysis based on variogram tools
Positive symplectic integrators for predator-prey dynamics
No full textWe propose novel positive numerical integrators for approximating predator-prey models. The schemes are based on suitable symplectic procedures applied to the dynamical system written in terms of the log transformation of the original variables. Even if this approach is not new when dealing with Hamiltonian systems, it is of particular interest in population dynamics since the positivity of the approximation is ensured without any restriction on the temporal step size. When applied to separable ?-systems, the resulting schemes are proved to be explicit, positive, Poisson maps. The approach is generalized to predator-prey dynamics which do not exhibit an ?-system structure and successively to reaction-diffusion equations describing spatially extended dynamics. A classical polynomial Krylov approximation for the diffusive term joint with the proposed schemes for the reaction, allows us to propose numerical schemes which are explicit when applied to well established ecological models for predator-prey dynamics. Numerical simulations show that the considered approach provides results which outperform the numerical approximations found in recent literature
Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models
No full textThe estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow-climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized. This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR), and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs), participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX) and in the Fifth Coupled Model Intercomparison Project (CMIP5) respectively. We evaluate their reliability in reproducing the main drivers of snow processes - near-surface air temperature and precipitation - against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections. The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around the ensemble mean. We find that GCMs at spatial resolutions equal to or finer than 1.25? longitude are in closer agreement with the ensemble mean of satellite and reanalysis products in terms of root mean square error and standard deviation than lower-resolution GCMs. The set of regional climate models from the EURO-CORDEX ensemble provides estimates of snow water equivalent at 0.11? resolution that are locally much larger than those indicated by the gridded data sets, and only in a few cases are these differences smoothed out when snow water equivalent is spatially averaged over the entire Alpine domain. ERA-Interim-driven RCM simulations show an annual snow cycle that is comparable in amplitude to those provided by the reference data sets, while GCM-driven RCMs present a large positive bias. RCMs and higher-resolution GCM simulations are used to provide an estimate of the snow reduction expected by the mid-21st century (RCP 8.5 scenario) compared to the historical climatology, with the main purpose of highlighting the limits of our current knowledge and the need for developing more reliable snow simulations