scholarly journals The Habitat Classification of mammals in Korea based on the National Ecosystem Survey

2017 ◽  
Vol 26 (2) ◽  
pp. 160-170
Author(s):  
Hwajin Lee ◽  
Jeongwook Ha ◽  
Jinyeol Cha ◽  
Junghyo Lee ◽  
Heenam Yoon ◽  
...  
2019 ◽  
Vol 143 (5-6) ◽  
pp. 264-264
Author(s):  
Ivana Plišo Vusić ◽  
Irena Šapić ◽  
Joso Vukelić

Habitat type 91E0 in Croatia extends to approximately 80,000 ha. It contains 16 types according to the National habitat classification of Croatia (NHC). They are based on phytosociological principles and are aligned with the level of association. They are: E.1. Riparian alluvial willow forests (Salicion albae Soó 1930), poplar (Populion albae Br.-Bl. 1931) and white alder forests (Alnion incanae Pawl. in Pawl. et al. 1928) Riparian alluvial willow and poplar forests (Salicion albae, Populion albae) E.1.1.1. – Salicetum albae-fragilis Soó (1930) 1958 E.1.1.2. – Salicetum albae Isller 1926 E.1.1.3. – Salici-Populetum nigrae (R. Tx. 1931) Meyer Drees 1936 E.1.2.1. – Populetum albae (Br.-Bl.) Tchou 1947 E.1.2.2. – Populetum nigro-albae Slavnić 1952 Alluvial white alder forests (Alnion incanae) E.1.3.1. – Equiseto hyemali-Alnetum incanae M. Moor 1958 E.1.3.2. – Lamio orvalae-Alnetum incanae Dakskobler 2010 E.2. Floodplain forests of pedunculate oak, black alder and narrow-leaved ash (Alnion glutinosae Malcuit 1929, Alnion incanae) Swamp and floodplain forests of black alder narrow-leaved ash (Alnion glutinosae) E.2.1.4. – Frangulo-Alnetum glutinosae Rauš (1971) 1973 E.2.1.6. – Carici elongatae-Alnetum glutinosae W. Koch 1926 ex Tx. 1931 E.2.1.7. – Leucojo-Fraxinetum angustifoliae Glavač 1959 E.2.1.9. – Carici acutiformis-Alnetum glutinosae Scamoni 1935 Alluvial and wetland forests of black alder, elms, narrow-leaved and common ash (Alnion incanae) E.2.1.1. – Fraxino angustifoliae-Ulmetum laevis Slavnić 1952 E.2.1.2. – Carici remotae-Fraxinetum excelsioris W. Koch 1926 ex Faber 1936 E.2.1.3. – Carici brizoidis-Alnetum glutinosae Horvat 1938 E.2.1.5. – Pruno-Fraxinetum angustifoliae Glavač 1960 E.2.1.8. – Stellario nemorum-Alnetum glutinosae Lohmayer 1957 The article contains a description, area of distribution in Croatia, and diagnostic indicators for each type. For each type related types are listed, the corresponding code according to EUNIS-classification, and literature in which is described in more detail. This article has practical importance because it helps in the identification and mapping of forest habitat types, and these tasks are currently being implemented in the Croatian forestry.


2014 ◽  
Vol 6 (3) ◽  
pp. 2154-2175 ◽  
Author(s):  
Richard Zavalas ◽  
Daniel Ierodiaconou ◽  
David Ryan ◽  
Alex Rattray ◽  
Jacquomo Monk

2018 ◽  
Author(s):  
Valérie Cypihot ◽  
Philippe Archambault ◽  
Kimberly L Howland

Coastal habitats provide unique conditions allowing a specific diversity of species to establish. However, in the Canadian Arctic, it may experience a growing number of impacts such as oil spills and aquatic invasive species. Effective, low-cost sampling methods are then required to obtain baseline data on Arctic species. In this context, the eSPACE project developed a classification of habitats by videography using substrate and geomorphology. To verify the relationships between this habitat classification and the biological and functional composition, coastal benthic communities and associated habitats were characterized in Churchill, Manitoba. Differences between biological composition and functional traits of each habitat were found which allow for direct information on the relative biological importance of sampled habitats and help validate the classification of habitats.


2008 ◽  
Vol 18 (02) ◽  
pp. 337-348 ◽  
Author(s):  
VIDYA MANIAN ◽  
MIGUEL VELEZ-REYES

This paper presents a novel wavelet and support vector machine (SVM) based method for hyperspectral image classification. A 1-D wavelet transform is applied to the pixel spectra, followed by feature extraction and SVM classification. Contrary to the traditional method of using pixel spectra with SVM classifier, our approach not only reduces the dimension of the input pixel feature vector but also improves the classification accuracy. Texture energy features computed in the spectral dimension are mapped using polynomial kernels and used for training the SVM classifier. Results with AVIRIS and other hyperspectral images for land cover and benthic habitat classification are presented. The accuracy of the method with limited training sets and computational burden is assessed.


2018 ◽  
Author(s):  
Valérie Cypihot ◽  
Philippe Archambault ◽  
Kimberly L Howland

Coastal habitats provide unique conditions allowing a specific diversity of species to establish. However, in the Canadian Arctic, it may experience a growing number of impacts such as oil spills and aquatic invasive species. Effective, low-cost sampling methods are then required to obtain baseline data on Arctic species. In this context, the eSPACE project developed a classification of habitats by videography using substrate and geomorphology. To verify the relationships between this habitat classification and the biological and functional composition, coastal benthic communities and associated habitats were characterized in Churchill, Manitoba. Differences between biological composition and functional traits of each habitat were found which allow for direct information on the relative biological importance of sampled habitats and help validate the classification of habitats.


2021 ◽  
pp. 150-161
Author(s):  
V. B. Golub

The rapid rate of decline in the Earth’s biodiversity under the influence of direct and indirect anthropogenic pressure makes it necessary to develop the scientific foundations for its conservation at all levels of life. Ecologists have come to understand that the best way to ensure the conservation of populations of organisms and their communities is to preserve the environment in which they live. The countries of the European Community, where special programs have been developed since mid 1980s, have shown the greatest activity in preserving environmental conditions. Currently, the «European Union Nature Information System» (EUNIS) has become the most popular among such programs. Habitat is a central concept in EUNIS. For the purposes of EUNIS, habitat is defined asa place where plants or animals normally live, characterized primarily by its physical features (topography, plant or animal physiognomy, soil characteristics, climate, water quality etc.) and secondarily by the species of plants and animals that live there (Davies et al., 2004). Most often, habitat is considered to be synonym of the term biotope. The EUNIS biotope classification would correspond to the ecosystem classification if heterotrophic components were largely present in it. However, at present, these organisms, are not used for classification of terrestrial ecosystems. The latter (especially benthos) are important in the characterization of marine habitat types. The author does not deny the extreme importance of the EUNIS habitat classification for ecological science and solving problems of nature conservation. He is only sure that the concept of habitat classification began to be developed in the Soviet Union as early as 1920–1930th in the papers by L. G. Ramenskiy who in 1927 published the definition of habitat type: The type of habitat or natural area is determined by a combination of climate conditions, relief, irrigation, and the nature of the soil and subsoil. The same type can be covered by a meadow, or a forest, or plowed up, etc.: these are its transitional states (in virgin untouched nature, each type is inhabited by a completely definite combination of plants - steppe, forest, meadow, etc.). Afterwards L. G. Ramenskiy began to use the term land type instead of habitat type. In the 1930s, by the land type he meant an ecosystem unit in which plant community would exist without human influence. The land type in nature is represented by a set of various modifications that arise, as a rule, under man pressure. Modifications can transform into each other and revert to the original state of the type. Later, such plant community was called potential vegetation (Tüxen, 1956). In 1932–1935, L. G. Ramenskiy supervised the inventory of natural forage lands in the USSR, which used this concept of land type (Golub, 2015). The inventory of natural forage lands in the USSR resulted in their hierarchical classification: 19 classes and 43 subclasses were established. The exact number of distinguished types was not calculated, according to L. G. Ramenskiy rough assessment, there were more than thousand. In most cases, the potential vegetation of the types could not be identified. Proceedings of this inventory were not published. However, the L. G. Ramenskiy former post-graduate student N. V. Kuksin, who took part in the inventory in Ukraine, wrote the book about the forage type lands in this republic of the USSR (Kuksin, 1935). The typology of hayfields and pastures presented in that book is very similar to the habitat classification developed on the principles of the EUNIS system (Kuzemko et al., 2018). By the late 1940s, L. G. Ramenskiy had concluded that modern science was unable to establish potential vegetation for many habitat types. Therefore, he recommended calling the land type what he previously attributed to modifications. For practical reasons and for the sake of brevity, it is advisable to also call types the main groups of modifications of land types (forest, meadow, arable) (Ramenskiy, 1950, p. 489). As a result, his understanding of land type became the same as later habitat was interpreted in the EUNIS system. The typology by L. G. Ramenskiy lands and the classification of EUNIS habitats have the same essence and basis, but different groups of human society proposed them: the first exploits land resources, the second tries to protect them. Based on L. G. Ramenskiy typology, recommendations are made on the use of biotopes with the purpose to obtain sustainable maximum economic production. Based on the classification of the EUNIS system, recommendations are drawn up for the protection of plant and animal populations, as well as their community’s characteristic of a given biotope. The land typology by L. G. Ramenskiy could well be deployed towards the protection of biotopes, if there was a demand from society for such use. So keen interest in nature conservation, as now, did not exist in the course of the L. G. Ramenskiy lifetime. At present, the EUNIS biotope classification has begun to be used on the territory of the former USSR, while the land typology by L. G. Ramenskiy has been forgotten. There are two reasons for this phenomenon: 1) isolationism of Soviet science, which separated domestic scientists from their colleagues in the West; 2) L. G. Ramenskiy ideas were too ahead of time, their depth, essence and importance became understandable to biologists only few decades later. The paper shows that the formation of L. G. Ramenskiy views concerning the typology of habitats could been influenced by the ideas of the Russian forest scientist A. A. Krudener.


2017 ◽  
Author(s):  
Fabian Souisa ◽  
Marvin Mario Makailipessy

This study aimed to determine mapped of the substrate (habitat) of the bottom shallow waters at Tayando District, Tual City with Landsat 8 imagery satellite. We used transformation blue and green bands with depth invariant index algorithm Y = ln Band 1 + (ki/kj) ln Band 2 on mapped the basic characteristics of the bottom shallow water. The classification of the imagery transformation by using shallow marine water habitat classification scheme based on color pallet and the result showed there were five classes on bottom substrate at Tayando District, those were sand, sand mixed coral, dead coral, coral reefs and seagrass.


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