A multi-criteria evaluation method for sturgeon farming site selection in the southern coasts of the Caspian Sea

Aquaculture ◽  
2019 ◽  
Vol 513 ◽  
pp. 734416 ◽  
Author(s):  
Saeid Esmaeilpour-Poodeh ◽  
Rasoul Ghorbani ◽  
Seyed Abbas Hosseini ◽  
Abdolrassoul Salmanmahiny ◽  
Hassan Rezaei ◽  
...  
2021 ◽  
Vol 13 (5) ◽  
pp. 2672
Author(s):  
Elham Haghshenas ◽  
Mehdi Gholamalifard ◽  
Nemat Mahmoudi ◽  
Tiit Kutser

Fish consumption is on the increase due to the increase in growth of the global population. Therefore, taking advantage of new methods such as marine aquaculture can be a reliable source for the production of fish in the world. It is necessary to allocate suitable sites from environmental, economic, and social points of view in the decision-making process. In this study, in order to specify suitable areas for marine aquaculture by the Ordered Weighted Averaging (OWA) methodology in the Caspian Sea (Iran), efforts were made to incorporate the concept of risk into the GIS-based analysis. By using the OWA-based method, a model was provided which can generate marine aquaculture maps with various pessimistic or optimistic strategies. Eighteen modeling criteria (14 factors and 4 constraints) were considered to determine the appropriate areas for marine aquaculture. This was done in 6 scenarios using multi-criteria evaluation (MCE) and ordered weighted average (OWA) methodologies. The results of the sensitivity analysis showed that most of the parameters affecting the marine aquaculture location in the region were as follows: Social-Economic, Water Quality, and Physical–Environmental parameters. In addition, based on Cramer’s V coefficient values for each parameter, bathymetry and distance from the coastline with the most effective and maximum temperature had the least impact on site selection of marine aquaculture. Finally, the final aggregated suitability image (FASI) of weighted linear combination (WLC) scenario was compared with existing sites for cage culture on the southern part of the Caspian Sea and the ROC (Relative Operating Characteristics) value turned out to be equal to 0.69. Although the existing sites (9 farms) were almost compatible with the results of the study, their locations can be transferred to more favorable areas with less risk and the mapping risk level can be controlled and low- or high-risk sites for marine aquaculture could be determined by using the OWA method.


Author(s):  
Edward Vladimirovich Nikitin

Shallow coastal waters of the Volga river is a flooded feeding area for fish juveniles of nonmigratory fish species. There takes place annual downstream migration of fluvial anadromous fish species from spawning grounds of the Volga river to the Northern Caspian Sea. The most important factors determining the number and qualitative characteristics of fry fishes are the level of the Caspian Sea (currently having a tendency to the lowering), hydrological and thermal regimes of the Volga river. Researches were carried out in definite periods of time. In the summer-autumn period of 2012 fry fishes were presented by 19 species (13 of them were commercial species), which belonged to 9 families. The article gives data on all the commercial fish species. In the first decade of July the maximum number of fry fish was registered in the western part of the Volga outfall offshore - in box 247 (19.86 mln specimens/km2), in the eastern part - in box 142 (20.4 mln specimens/km2). The most populous were roach, red-eye, silver bream and bream; size-weight characteristics were better in the areas remoted from the Volga delta. In the third decade of July the quantitative indicators of fry fish on these areas decreased, size-weight characteristics greatly increased. In the second decade of October in the western part of the seaside there were registered increased pre-wintering concentrations of fish juveniles, their qualitative indicators increased, which is evidence to favorable feeding conditions in 2012.


2020 ◽  
Vol 324 (2) ◽  
pp. 262-272
Author(s):  
I.V. Doronin ◽  
T.N. Dujsebayeva ◽  
K.M. Akhmedenov ◽  
A.G. Bakiev ◽  
K.N. Plakhov

The article specifies the type locality of the Steppe Ribbon Racer. The holotype Coluber (Taphrometopon) lineolatus Brandt, 1838 is stored in the reptile collection of the Zoological Institute of the Russian Academy of Sciences (ZISP No 2042). Literature sources provide different information about the type locality. A mistake has been made in the title of the work with the original species description: the western coast of the sea was indicated instead of the eastern one. The place of capture was indicated as “M. Caspium” (Caspian Sea) on the label and in the reptile inventory book of the Zoological Museum of the Academy of Sciences. The specimen was sent to the museum by G.S. Karelin. The “1842” indicated on the labels and in the inventory book cannot be the year of capture of the type specimen, just as the “1837” indicated by A.M. Nikolsky. In 1837, Karelin was in Saint Petersburg and in 1842 in Siberia. Most likely, 1837 is the year when the collection arrived at the Museum, and 1842 is the year when the information about the specimen was recorded in the inventory book (catalog) of the Zoological Museum of the Academy of Sciences. In our opinion, the holotype was caught in 1932. From Karelin’s travel notes of the expedition to the Caspian Sea in 1832, follows that the snake was recorded in two regions adjacent to the eastern coast of the Caspian Sea – Ungoza Mountain (“Mangyshlak Mountains”) and site of the Western Chink of Ustyurt between Zhamanairakty and Kyzyltas Mountains (inclusive) on the northeast coast of Kaydak Sor (“Misty Mountains”). In our article, Karelin’s route to the northeastern coast of the Caspian Sea in 1832 and photographs of these localities are given. The type locality of Psammophis lineolatus (Brandt, 1838) should be restricted to the Mangystau Region of the Kazakhstan: Ungoza Mountain south of Sarytash Gulf, Mangystau (Mangyshlak) Penninsula (44°26´ N, 51°12´ E).


Author(s):  
Nepomenko Leonid ◽  
◽  
Popova Natalia ◽  
Zubanov Stepan ◽  
Ostrovskaya Elena ◽  
...  

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