Assessment of a Mediterranean shallow lentic ecosystem (Lake Pamvotis, Greece) using benthic community diversity: Response to environmental parameters

Macroinvertebrates play a key role in freshwater lentic and lotic ecosystems. The macroinvertebrate benthic community of a shallow Mediterranean lake (Lake Pamvotis, NW Greece) was studied. The benthic assemblage was sampled monthly at five sites during a period of 1 year (Apr. 1998–Mar. 1999). In addition hypolimnetic water quality variables were monitored over the same period at each site.

The aim of the study was (a) to describe the intra-annual and spatial variability in benthic communities, (b) to relate possible community changes to environmental conditions and (c) to evaluate the responses of the lake's ecological status on community indices.

The benthic fauna of Lake Pamvotis was found to be very limited with a total of 10 species belonging to five taxonomic groups. The oligochaete community comprised 80% of the total benthic fauna with Potamothrix bavaricus as a new record for the Lake Pamvotis and Potamothrix hammoniensis, being the dominant benthic species represented more than 61% of the total benthic fauna. Chironomus plumosus was the most abundant chironomid species contributing with about 6% of the total benthic fauna, and Chaoborus flavicans with 19% was the important dipteran. Almost all benthic species showed the same intra-annual seasonal pattern, with peak population densities during spring and early summer except P. hammoniensis which predominated during the whole sampling period. Dissolved oxygen and temperature seemed to be the main environmental factors affecting community indices.

Benthic communities are affected by human disturbances in Lake Pamvotis shifting their composition to more tolerant taxa, reflecting also the eutrophic to hypertophic character of the lake.     

Applications of hybrid genetic algorithms in seismic tomography

Almost all earth sciences inverse problems are nonlinear and involve a large number of unknown parameters, making the application of analytical inversion methods quite restrictive. In practice, most analytical methods are local in nature and rely on a linearized form of the problem equations, adopting an iterative procedure which typically employs partial derivatives in order to optimize the starting (initial) model by minimizing a misfit (penalty) function. Unfortunately, especially for highly non-linear cases, the final model strongly depends on the initial model, hence it is prone to solution-entrapment in local minima of the misfit function, while the derivative calculation is often computationally inefficient and creates instabilities when numerical approximations are used. An alternative is to employ global techniques which do not rely on partial derivatives, are independent of the misfit form and are computationally robust. Such methods employ pseudo-randomly generated models (sampling an appropriately selected section of the model space) which are assessed in terms of their data-fit. A typical example is the class of methods known as genetic algorithms (GA), which achieves the aforementioned approximation through model representation and manipulations, and has attracted the attention of the earth sciences community during the last decade, with several applications already presented for several geophysical problems.In this paper, we examine the efficiency of the combination of the typical regularized least-squares and genetic methods for a typical seismic tomography problem. The proposed approach combines a local (LOM) and a global (GOM) optimization method, in an attempt to overcome the limitations of each individual approach, such as local minima and slow convergence, respectively. The potential of both optimization methods is tested and compared, both independently and jointly, using the several test models and synthetic refraction travel-time date sets that employ the same experimental geometry, wavelength and geometrical characteristics of the model anomalies. Moreover, real data from a crosswell tomographic project for the subsurface mapping of an ancient wall foundation are used for testing the efficiency of the proposed algorithm. The results show that the combined use of both methods can exploit the benefits of each approach, leading to improved final models and producing realistic velocity models, without significantly increasing the required computation time.     

Earthquake precursory signatures in electromagnetic radiation measurements in terms of day-to-day fractal spectral exponent variation: analysis of the eastern Aegean 13/04/2017–20/07/2017 seismic activity

The recent seismic activity in the eastern Aegean Sea, foregrounded by two major (M_L?=?6.1 and M_L?=?6.2) earthquakes occurring near Lesvos and Kos islands, respectively, is investigated in this work. Electromagnetic radiation measurements across different frequency bands and antenna orientations from a monitoring station in Agia Paraskevi, Lesvos Island, are analysed in order to reveal earthquake precursory signatures hidden in the electromagnetic data sequence. A straightforward, data-driven approach is employed in which day-to-day variations of the fractal characteristics of the measurements are adaptively monitored via a fractal spectral exponent similarity measure. The evolution of the fractal day-to-day variation in a 99-day period, which includes the two major earthquakes, shows a sustained, sudden increase lasting 1 to 4 days before every earthquake cluster of M_L?=?4.0 and above. Most importantly, this day-to-day variation subsides shortly after and remains relatively low during the absence of earthquakes, thus alleviating the emergence of false alarms.