Grassland with tradition: sampling across several scientific disciplines

Author:

Janišová MonikaORCID,Iuga Anamaria,Ivașcu Cosmin Marius,Magnes Martin

Abstract

The traditional, low-input use of grassland in Central and Eastern Europe has provided high-quality food, clothing and manure for millennia. As an outcome of sustainable low-intensity agriculture, some rural areas have globally significant species richness. Traditional farming is still well preserved in several regions of the Carpathian Mountains. This is a unique opportunity to use the wisdom of our ancestors to keep grassland biodiversity for our descendants. We present a sampling methodology to survey traditionally managed grassland ecosystems holistically, including abiotic, biological and cultural phenomena, and reflect thus the multidimensionality of traditional farming. Our main objective was to reveal the connection between particular management practices and precisely measured plot plant diversity. Our motivation was to identify traditional farming approaches that result in both high biodiversity and sustainable grassland utilization in particular region, and confirm their impact also using statistical tests. The multitaxon vegetation sampling at seven spatial scales combined with soil analyses, detailed land-use information derived from interviews with the land parcel owners, satellite pictures and historical materials provide potentially valuable data for several scientific disciplines including syntaxonomy, plant ecology, environmental anthropology and ethnology. Examples of grassland management practices based on traditional ecological knowledge can serve as an inspiration for developing modern biodiversity conservation strategies applicable for rural regions. The database Grassland with Tradition is registered in Global Index of Vegetation-Plot Databases (GIVD) with the identifier ID EU-00-032. To date it contains data from 31 study sites in 7 countries (Austria, Czech Republic, Slovakia, Hungary, Poland, Romania, Ukraine). Syntaxonomic reference: Mucina et al. (2016).

Publisher

Pensoft Publishers

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