Traditional vegetation knowledge of the Hortobágy salt steppe (Hungary): a neglected source of information for vegetation science and conservation

IF 0.8 4区 生物学 Q4 ECOLOGY Phytocoenologia Pub Date : 2013-11-01 DOI:10.1127/0340-269X/2013/0043-0561
Z. Molnár
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引用次数: 12

Abstract

Traditional vegetation knowledge of herders was studied in the Hortobagy steppe. In this paper (1) the habitat types/vegetation types herders distinguish, (2) the names they use for these folk habitats, (3) the botanical equivalents of folk habitats, and (4) the herders' description of the main vegetation types distinguished by phytosociologists are presented. Ecological anthropological methods such as participant observation, interviews, free listings were used for eliciting herders' knowledge. There were 2239 records of habitat names and features, and 1432 records of the knowledge of habitat requirements of plant species collected from 78 herders. Herders distinguished 47–66 habitat types using 185 names. Many categories were more or less equivalent to the level of plant association, and some described mosaics of habitats. Herders divided the steppe into three large habitat groups: wet habitats (lapos in Hungarian, 16–21 habitat categories), saline habitats (called szik, szikes, 11–16 categories), and habitats found on chernozem soils (called partos, telek, 8-13 categories). Another 10-14 categories were used by them to name habitats in arable areas and settlements. Herders distinguished and described habitats based on their productivity, salinity, wetness, dominant species, relative elevation on the steppe habitat gradient, surface geomorphology, land-use, density of vegetation, and passabilty. We will argue that traditional herders' knowledge can provide new information for scientists, e.g.on local vegetation dynamics and history. Understanding herders' vegetation knowledge, motivations and constraints in herding could also contribute to the improvement of nature conservation management e.g.by making communication between herders and scientists/conservationists more concrete, and perhaps by providing better targets for conservationists and environmental managers. Traditional vegetation knowledge is a neglected part of European culture, and it is fading quickly. An effective collection and understanding of this deep vegetation knowledge can best and most effectively be accomplished by scientists with experience in botany.
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Hortobágy盐草原的传统植被知识(匈牙利):植被科学和保护的一个被忽视的信息来源
对霍尔特巴吉草原牧民的传统植被知识进行了研究。本文介绍了牧民区分的生境类型/植被类型,牧民对这些民间生境的命名,牧民对民间生境的植物等效性,牧民对植物社会学家区分的主要植被类型的描述。采用参与式观察法、访谈法、免费清单法等生态人类学方法对牧民的知识进行梳理。共收集78名牧民的生境名称和特征记录2239条,植物物种生境要求知识记录1432条。牧民用185个名字区分了47-66种栖息地类型。许多分类或多或少相当于植物关联的水平,有些描述了生境的马赛克。牧民将草原划分为3大生境群:湿生境(匈牙利语lapos, 16-21生境类别)、盐生境(称为szik, szikes, 11-16生境类别)和黑土生境(称为partos, telek, 8-13生境类别)。他们还使用另外10-14个类别来命名耕地和定居点的栖息地。牧民根据其生产力、盐度、湿度、优势物种、草原生境梯度的相对海拔、地表地貌、土地利用、植被密度和可通过性来区分和描述栖息地。我们将认为,传统牧民的知识可以为科学家提供新的信息,例如当地植被动态和历史。了解牧民在放牧中的植被知识、动机和制约因素也有助于改善自然保护管理,例如,通过使牧民与科学家/保护主义者之间的沟通更加具体,或者通过为保护主义者和环境管理者提供更好的目标。传统的植被知识是欧洲文化中被忽视的一部分,它正在迅速消失。具有植物学经验的科学家可以最好和最有效地收集和理解这些深刻的植被知识。
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来源期刊
Phytocoenologia
Phytocoenologia 生物-植物科学
CiteScore
2.60
自引率
0.00%
发文量
7
审稿时长
>12 weeks
期刊介绍: Phytocoenologia is an international, peer-reviewed journal of plant community ecology. It is devoted to vegetation survey and classification at any organizational and spatial scale and without restriction to certain methodological approaches. The journal publishes original papers that develop new vegetation typologies as well as applied studies that use such typologies, for example, in vegetation mapping, ecosystem modelling, nature conservation, land use management or monitoring. Particularly encouraged are methodological studies that design and compare tools for vegetation classification and mapping, such as algorithms, databases and nomenclatural principles. Papers dealing with conceptual and theoretical bases of vegetation survey and classification are also welcome. While large-scale studies are preferred, regional studies will be considered when filling important knowledge gaps or presenting new methods.
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