Ecological data in Darwin Core: the case of earthworm surveys

Shashkov, Maxim; Ivanova, Natalia V.; Wieczorek, John

doi:10.3897/bdj.9.e71292

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…Currently, most of the datasets in GBIF are occurrence-based and describe point records of species. In contrast, the contribution of sampling-event datasets remains very low, about 3% of all published datasets ( Ivanova and Shashkov 2021 , Shashkov et al 2021 ). Sampling-event datasets can contain more zeros than non-zeros for the multi-species communities since only a tiny part of the regional species pool may be present in each specific sample.…”

Section: Introductionmentioning

confidence: 94%

Diversity and abundance of soil macroinvertebrates along a contamination gradient in the Central Urals, Russia

Воробейчик¹,

Nesterkov²,

Ермаков³

et al. 2022

BDJ

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Since the late 1980s, long-term monitoring of terrestrial ecosystems in metal-contaminated areas near the Middle Ural Copper Smelter has been carried out in the Central Urals. As a part of these monitoring programmes, the data on species diversity, community composition and abundance of soil macroinvertebrates continue to be gathered. The dataset (available from the GBIF network at https://www.gbif.org/dataset/61e92984-382b-4158-be6b-e391c7ed5a64) includes a 2004 census for soil macroinvertebrates of spruce-fir forests along a pollution gradient in the Central Urals. The dataset describes soil macrofauna’s abundance (the number of individuals per sample, i.e. the density) and community structure (list of supraspecific taxa, list of species for most abundant taxa and supraspecific taxa or species abundance). Seventeen sampling plots differed in the levels of toxic metal (Cu, Zn, Pb, Cd and Fe) soil contamination from air emissions of the Middle Ural Copper Smelter (heavily polluted, moderately polluted and unpolluted areas). The dataset consists of 340 sampling events (= samples corresponding to upper and lower layers of the 170 soil monoliths) and 64658 rows (2907 and 61751 for non-zero and zero density of taxa, respectively). Arachnida (Araneae and Opiliones), Carabidae (imagoes), Elateridae (larvae), Chilopoda, Diplopoda, Gastropoda, Staphylinidae (imagoes) and Lumbricidae were identified to species level. In contrast, Mermithida, Enchytraeidae, Lepidoptera larvae, Diptera larvae, Hemiptera, Hymenoptera and some other insects were identified to family or order levels. In total, 8430 individuals of soil macroinvertebrates were collected in two soil layers (organic and organic-mineral horizons), including 1046 Arachnida (spiders and harvestmen), 45 Carabidae, 300 Elateridae, 529 Myriapoda, 741 Gastropoda, 437 Staphylinidae, 623 Lumbricidae and 4709 other invertebrates. The presence-absence data on each taxon are provided for each sampling event. An overwhelming majority of such absences can be interpreted as “pseudo-absences” at the scale of sampling plots or study sites. The dataset contains information helpful for long-term ecotoxicological monitoring of forest ecosystems and contributes to studying soil macrofauna diversity in the Urals.

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Section: Introductionmentioning

confidence: 94%

Diversity and abundance of soil macroinvertebrates along a contamination gradient in the Central Urals, Russia

Воробейчик¹,

Nesterkov²,

Ермаков³

et al. 2022

BDJ

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“…Нами создана и поддерживается инфраструктура для хранения и публикации национальных данных о биоразнообразии, объединяющая в настоящее время данные более 60-ти российских организаций [10,11]. Совместно с зарубежными коллегами проанализированы возможности и ограничения основного стандарта GBIF Darwin Core для представления экологических учетов: предложено дополнение спецификации, добавление терминов, разработана новая схема представления данных комплексных учетов почвенных беспозвоночных [12]. В составе международных коллективов выполнена стандартизация и публикация в GBIF объединенного массива данных Летописей природы 55 российских заповедников [13].…”

Section: ) экоинформатика и анализ массивов объединенных данныхunclassified

The IMPB RAS is 50 years old. Laboratory of Computational Ecology: achievements and prospects

Ханина¹,

Ivanova²,

Shashkov³

et al. 2022

Proceedings of the International Conference "Mathematical Biology and Bioinformatics"

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математических проблем биологии РАН -филиал Института прикладной математики им. М.В. Келдыша РАН 2 Институт глобального климата и экологии имени академика Ю.А. Израэля 3 Центр по проблемам экологии и продуктивности лесов РАН 4 Институт физико-химических и биологических проблем почвоведения РАНобособленное подразделение ФИЦ НЦБИ РАН

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Earthworm occurrence dataset extracted from Russian-language literature

Shashkov,

Ivanova,

Ermolov

2024

BDJ

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Earthworms are one of the most important components of temperate ecosystems and groups of soil animals globally, but data on their distribution around the world are still incomplete and uneven. Northern Eurasia is a region for which available data on earthworm distribution is extremely poor. At the same time, generations of Soviet and Russian researchers have performed extensive research and accumulated a large amount of data on the distribution of earthworms in this vast region. Most of this information was published in Russian, not digitised and, therefore, hardly accessible to researchers. Our dataset fills this gap and provides occurrence data extracted from 159 literature sources in Russian published between 1868 and 2022. The dataset contains 5,304 occurrences of 109 species and 14 subspecies. The collected data cover the territory of 27 countries. The dataset extends the data available through GBIF.org on earthworm distribution in Russia, Belarus, and Ukraine. For Transcaucasia and Central Asia countries, our resource has become the main GBIF source on earthworm diversity distribution. On a global scale, our dataset contributes to filling gaps in biodiversity, which facilitates more accurate estimates of the response of biodiversity to global climate change as well as the spreading of invasive species.

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Ecological data in Darwin Core: the case of earthworm surveys

Cited by 3 publications

References 23 publications

Diversity and abundance of soil macroinvertebrates along a contamination gradient in the Central Urals, Russia

Diversity and abundance of soil macroinvertebrates along a contamination gradient in the Central Urals, Russia

The IMPB RAS is 50 years old. Laboratory of Computational Ecology: achievements and prospects

Earthworm occurrence dataset extracted from Russian-language literature

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