Lithuania

Gudžinskas, Liutauras; Bekišas, Tomas

doi:10.1007/978-3-030-40858-9_8

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…A oristic approach was used to prepare the national CWR checklist as described by Maxted et al (2013). The checklist of the ora of Lithuania was compiled by using the following sources: Dictionary of Plant Names (Jankevičienė 1998), Vascular Plants of Lithuania (Gudžinskas 1999), Flora of the Baltic Countries (Laasimer et al 1993;Kuusk et al 1996;Kuusk et al 2003), Orchids (Orchidaceae) of Lithuania (Gudžinskas, Ryla 2006), Red Data Book of Lithuania (Rašomavičius 2021), and the Euro + Med PlantBase (Euro + Med 2006+). The taxonomic harmonization was carried out by referring to the International Plant Name Index (IPNI 2023) and Plants of the World online (POWO 2024).…”

Section: National Cwr Checklistmentioning

confidence: 99%

Enhancing in Situ Conservation of Crop Wild Relatives for Food and Agriculture in Lithuania

Labokas,

Lisajevičius,

Uogintas

et al. 2024

Preprint

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The crop and CWR checklist of Lithuania was created containing 2,630 taxa. The checklist comprises 1,384 native taxa including archaeophytes and 1,246 neophytes. In total, 699 taxa (26.6%) could be quite strictly defined as of food or forage use. A list of 144 CWR priority species with 135 native species and archaeophytes and 9 naturalized species was generated. In total, 53 genera of food and forage species belonging to 15 families are represented by the priority CWR. Two approaches for CWR genetic reserve selection have been employed in this study: (1) CWR-targeted evaluation of preselected sites, including Natura 2000 sites, national protected areas, and other effective area-based conservation measures (OECMs), such as ancient hillfort sites and ecological protection zones of water bodies; and (2) analysis of large georeferenced plant databases. Forty-five potential genetic reserve sites have been selected by the first approach covering 83 species or 57.6% of the national CWR priority list. With the second approach, the in situ CWR National Inventory database has been created by combining data from the Database of EU habitat mapping in Lithuania (BIGIS), Herbarium Database of the Nature Research Centre (BILAS), Lithuanian Vegetation Database (EU-LT-001), and Global Biodiversity Information Facility (GBIF). Hotspot analysis of CWR species richness and number of observations suggested that higher CWR diversity is more likely to be found in protected areas. However, Shannon diversity and Shannon equitability indices showed that the areas outside of the protected areas are also suitable for CWR genetic reserve establishment.

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Section: National Cwr Checklistmentioning

confidence: 99%

Enhancing in Situ Conservation of Crop Wild Relatives for Food and Agriculture in Lithuania

Labokas,

Lisajevičius,

Uogintas

et al. 2024

Preprint

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“…Projection cover-abundance was estimated visually using the Braun-Blanquet cover-abundance scale (Braun-Blanquet 1964), and then in subsequent analyses, it was transformed into percentage cover according to recommendations of Otto Wildi (2013). Nomenclature follows Jankeviciene (1998) and Gudžinskas (1999).…”

Section: Samplingmentioning

confidence: 99%

Changes of ground vegetation after shelter wood cuttings in pine forests, the hemiboreal zone, Lithuania

Marozas

Sasnauskienė

2021

BALT FOR

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Sustainable forestry plays an important role in applying forest management measures. In many forests, management is oriented towards closer natural forest processes. Silvicultural systems that retain some part of the trees in the stand, such as shelter wood cuttings have been introduced. The aim of the study was to evaluate the early changes of ground vegetation after shelter wood cuttings in sites of different soil fertility gradient in pine dominated stands on sandy soils in the European hemiboreal zone. The Scots pine stands in which first step of shelter wood cuttings was applied were investigated. The stands were selected in fresh (normal humidity) sites according to soil fertility gradient: very poor, poor and medium fertility soils. All mosses, lichens, herbaceous vegetation and dwarf shrubs were recorded, and projection cover was estimated in June - August. Ellenberg’s indicator figures were used to evaluate site conditions. In shelter wood cuttings (5-6-year-old) the number of species was higher in medium fertile sites than in very poor sites. After shelter wood cuttings the abundance of herbaceous species increased in all sites, while the abundance of mosses and lichens decreased. Within the first year after shelter wood cuttings, the abundance of Ericaceae species decreased, and abundance of Rosaceae and Poaceae species increased. Average Ellenberg’s indicator values showed that site conditions changed after shelter wood cuttings. The changes were more intensive in medium fertile sites than in poor sites. After shelter wood cuttings the richness and abundance of ground vegetation changed. The intensity of change differed in sites of certain soil fertility and was caused by alteration of site conditions, which were more homogenous in sites of the certain fertility in uncut stands than in cuttings. Key words: herbs, mosses, non-clear cuttings, vegetation

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