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Relevant bibliographies by topics / European Floristic Cartographic Grid

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Journal articles

Academic literature on the topic 'European Floristic Cartographic Grid'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "European Floristic Cartographic Grid"

1

Fariselli, Riccardo, Maria Speranza, and Michele Aleffi. "Bryological flora of the regional historic Park of Monte Sole (Emilia-Romagna, Italy)." Italian Botanist 3 (June 7, 2017): 99–108. https://doi.org/10.3897/ib.3.12663.

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This article presents the results of a study on the bryological flora of the historic Park of Monte Sole, in the Bologna Apennines (Emilia-Romagna region). A total of 129 taxa were identified, including 9 new findings for the region. The study makes use of the regional cartographic grid, a methodology already used in the description of the vascular flora of the region, applied here for the first time to the bryological flora. If used in future studies, this method will allow a standardization of our knowledge on the distribution of the bryological flora in the region.

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2

Fariselli, Riccardo, Maria Speranza, and Michele Aleffi. "Bryological flora of the regional historic Park of Monte Sole (Emilia-Romagna, Italy)." Italian Botanist 3 (June 7, 2017): 99–108. https://doi.org/10.3897/italianbotanist.3.12663.

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This article presents the results of a study on the bryological flora of the historic Park of Monte Sole, in the Bologna Apennines (Emilia-Romagna region). A total of 129 taxa were identified, including 9 new findings for the region. The study makes use of the regional cartographic grid, a methodology already used in the description of the vascular flora of the region, applied here for the first time to the bryological flora. If used in future studies, this method will allow a standardization of our knowledge on the distribution of the bryological flora in the region.

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3

Wootton, Lara M., Florian C. Boucher, Julien Renaud, et al. "The Limited Legacy of Post-Glacial Recolonization in the Floristic Patterns of the European Alps." Systematic Botany 50, no. 1 (2025): 83–98. https://doi.org/10.1600/036364425x17466502618876.

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Abstract— Past glacial periods were highly disruptive to plant species distributions in mid-latitude mountain belts, such as the European Alps, and drove many species to survive in peripheral or nunatak refugia. Progressive glacial retreat during the late Pleistocene and Holocene is thought to have triggered a mass recolonization event in the European Alps. Here, we asked whether this recolonization event has left a spatial legacy in the floristic patterns of the extant Alpine flora, and if so, how strongly this determines floristic patterns in comparison to present-day landscape and climatic

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4

Budzhak, Vasyl, and Olena Miskova. "Grid map of Seymskiy Regional Landscape Park." Biolohichni systemy 12, no. 2 (2020): 245–50. http://dx.doi.org/10.31861/biosystems2020.02.245.

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Modern approaches to the use of grid mapping in studies of biodiversity at the level of distinct countries and local territories are described. Information on the territory of Seymskiy Regional Landscape Park as a significant element of the National Ecological Network, the Emerald Network in Ukraine and the regional ecological network, and on its functional zoning is given. The cartographic basis of the territory of Seymskiy Regional Landscape Park is created via MapInfo program. When designing the grid map of the park, the experience of developing grid maps for Cheremosh National Nature Park,

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5

Shcherbakov, Andrey, Marina Kazakova, Nadezhda Lyubeznova, Anastasia Pastushenko, and Alexey Seregin. "A grid-based database on vascular plant distribution in the Meshchersky National Park, Ryazan Oblast, Russia." Biodiversity Data Journal 9 (November 1, 2021): e75892. https://doi.org/10.3897/BDJ.9.e75892.

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Ryazan Oblast, situated in the central part of European Russia, has a long tradition of biodiversity research. Large distributional, ecological and phenological data on various taxonomic groups are available from this territory, mainly in the form of paper publications items, undigitised museum collections and archival sources. The purpose of this dataset is to deliver floristic materials, collected by the authors in the Meshchera Lowlands in the form of GBIF-mediated electronic data, to a wider audience. The dataset covers wild tracheophytes (native species, naturalised aliens and casuals) of

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6

Liakos, Leonidas, and Panos Panagos. "Challenges in the Geo-Processing of Big Soil Spatial Data." Land 11, no. 12 (2022): 2287. http://dx.doi.org/10.3390/land11122287.

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This study addressed a critical resource—soil—through the prism of processing big data at the continental scale. Rapid progress in technology and remote sensing has majorly improved data processing on extensive spatial and temporal scales. Here, the manuscript presents the results of a systematic effort to geo-process and analyze soil-relevant data. In addition, the main highlights include the difficulties associated with using data infrastructures, managing big geospatial data, decentralizing operations through remote access, mass processing, and automating the data-processing workflow using

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7

Karamysheva, Z. V., V. N. Khramtsov, and E. A. Volkova. "N. I. Kuznetsov’s scientific heritage in vegetation mapping (to the 100th anniversary of the Geobotany Department of the Komarov Botanical Institute)." Geobotanical mapping, no. 2021 (2021): 3–19. http://dx.doi.org/10.31111/geobotmap/2021.3.

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The development of vegetation mapping as a research branch in geobotany and botanical geography is connected with the history of the Geobotany Department of the Komarov Botanical Institute. The 100th anniversary of the Department will be celebrated in 2022. Nikolai Ivanovich Kuznetsov — a world-renowned scientist, who had great scientific and organizational experience — was assigned to lead the new department in 1922. In connection with the requests of the practice, the main task of the Department of Geobotany was the development of geobotanical cartography. Despite the difficult period for th

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8

Justić, Marta, Marija Bučar, Petra Vizec, Ana Vukres, Vedran Šegota, and Nina Vuković. "The diversity and distribution of flora of the island of Zlarin (Northern Dalmatia)." Natura Croatica 30, no. 2 (2021): 435–66. http://dx.doi.org/10.20302/nc.2021.30.29.

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The flora of the island of Zlarin was studied in 2019 and mapped using the Central European grid (MTB fields), the area studied consisting of nine MTB 1/64 fields. Altogether 576 vascular plant taxa (532 species and 44 subspecies) were identified, out of which there were 126 newly recorded, 450 previously recorded and confirmed, while 153 taxa from previous authors were not confirmed. In total, 730 taxa are currently recorded on the island of Zlarin. Among these, 580 taxa are indigenous, 147 cultivated and 23 listed as invasive in Croatia. Cultivated and adventitious plants were not included i

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9

ОГУРЕЕВА, Г. Н., та М. В. БОЧАРНИКОВ. "КАРТОГРАФИЧЕСКОЕ ОБЕСПЕЧЕНИЕ РАБОТ ПО ИЗУЧЕНИЮ БОТАНИЧЕСКОГО РАЗНООБРАЗИЯ". География и природные ресурсы 45, № 3 (2024): 164–74. https://doi.org/10.15372/gipr20240316.

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Освещены проблемы инвентаризации, оценки и мониторинга биоразнообразия на основе картографирования как развивающегося самостоятельного направления исследований, позволяющего проводить пространственный анализ биоты с использованием широкого спектра тематических карт. Рассмотрены примеры выявления разнообразия биоты, которое проводится с помощью картографического метода на четырех основных уровнях: видовое богатство конкретных (локальных) флор, фитоценотическое (видовое богатство и разнообразие сообществ растительных формаций), определенных природных комплексов (ландшафтное биоразнообразие) и эк

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10

Michalak, Michał P., Lesław Teper, Florian Wellmann, et al. "Clustering has a meaning: optimization of angular similarity to detect 3D geometric anomalies in geological terrains." Solid Earth 13, no. 11 (2022): 1697–720. http://dx.doi.org/10.5194/se-13-1697-2022.

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Abstract. The geological potential of sparse subsurface data is not being fully exploited since the available workflows are not specifically designed to detect and interpret 3D geometric anomalies hidden in the data. We develop a new unsupervised machine learning framework to cluster and analyze the spatial distribution of orientations sampled throughout a geological interface. Our method employs Delaunay triangulation and clustering with the squared Euclidean distance to cluster local unit orientations, which results in minimization of the within-cluster cosine distance. We performed the clus

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