Is the GBIF appropriate for use as input in models of predicting species distributions? Study from the Czech Republic

Nature Conservation Research, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Questions concerning species diversity have attracted ecologists and biogeographers for over a century, mainly because the of life on Earth is in rapid decline, which expected to continue future. One most important current database distribution data Global Biodiversity Information Facility (GBIF), contains more than 2 billion occurrences all organisms, this number continuously increasing with addition new by combining other applications. Such also exist several national databases, are unfortunately often not freely available included GBIF. We suspected that mostly professionally maintained governmental organisations, may be comprehensive GBIF, centrally organised therefore databases give accurate predictions To test our assumptions, we compared: (i) amount Czech called Nálezová databáze ochrany přírody (NDOP, Discovery nature protection) GBIF after its restriction Republic, (ii) overlap distributions based these two databases. used family Orchidaceae as model group. found that: there significantly larger records per studied region (Czech Republic) NDOP, compared Maxent orchid NDOP overlapping great degree Bearing mind results, suggest if only one studied, must use one. If should containing locations (usually some local ones, like NDOP), using implies significance distributions.

Language: Английский

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Completeness of Digital Accessible Knowledge of plants across Africa and priorities for future data discovery

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 3, 2025

Digital Accessible Knowledge (DAK) is of utmost importance for biodiversity conservation. The Global Biodiversity Information Facility (GBIF, www.gbif.org) a mega data infrastructure with more than two billion and hundred million occurrence records as ¹⁷ January 2023. It by far the largest initiative assembling sharing DAK to support scientific research, conservation, sustainable development. We decided analyze plant published at GBIF site scale Africa highlight contribution continent thereby underline quality issues gaps across taxonomic groups geographic space. therefore downloaded on 17th 2023 from Plantae kingdom Africa. They are available https://doi.org/10.15468/dl.p2n6um. achieved treatment analysis using R, several packages related functions. Although home rich many hotspots, global (61,176,994 2023) still incredibly low (2.69%). Furthermore, there large disparities between African countries, South contributing alone 50% continent. (9,116,401 records) accounted 14.90% continent; this underlines huge groups. noted important loss during process cleaning clearly underlining limited indeed, fitness purpose in completeness were only 50.94% total initially downloaded. Efforts check before publication needed countries. Magnoliopsida was dominant class highest number (71.07%) species (68.36%), followed Liliopsida, 22.80% 19.06% species. In space, also quite West Africa, Southern East Madagascar. Accessibility roads protected areas (> 10,000 Km²) limiting factors multidimensional identified study should be priority addressed future collections

Language: Английский

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Mobilisation of Data From Natural History Collections Can Increase the Quality and Coverage of Biodiversity Information

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(4)

Published: April 1, 2025

ABSTRACT The surge of biodiversity data availability in recent decades has allowed researchers to ask questions on previously unthinkable scales, but knowledge gaps still remain. In this study, we aim quantify potential gains insect the Global Biodiversity Information Facility (GBIF) through further digitisation natural history collections, assess what degree would fill biases spatial and environmental record coverage, deepen understanding bias with regard climate rarity. Using mainland Afrotropical records for Catharsius Hope, 1837 (Coleoptera: Scarabaeidae), compared inventory completeness GBIF a dataset which combined these from taxonomic revision. We analysed how improved reduced regional distribution occurrence using an approach that identifies well‐surveyed units 100 × 100km as well emerging techniques classify rarity climates. found number cells could be calculated, coverage types by ‘well‐sampled’ cells, increased threefold when set set. Improvements sampling Central Western Africa were particularly striking, rare climates was similarly improved, not single well‐sampled cell alone occurred rarest types. These findings support existing literature suggests are pervasive, especially insects tropics, so, is yet ready serve standalone source all taxa. However, show collections hold necessary information many gaps, their should priority.

Language: Английский

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Conserving Amazonian vascular epiphytes: evaluating protected areas and unveiling biodiversity through comprehensive species inventories

Biodiversity and Conservation, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

Language: Английский

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Completeness of Digital Accessible Knowledge of plants across Africa and priorities for future data discovery

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Digital Accessible Knowledge (DAK) is of utmost importance for biodiversity conservation. The Global Biodiversity Information Facility (GBIF, www.gbif.org) a mega data infrastructure with more than three billion and seventy millions (3,070,000,000) occurrence records as ⁰⁴ March 2025. It by far the largest initiative assembling sharing DAK to support scientific research, conservation, sustainable development. We decided analyze plant published at GBIF site scale Africa highlight contribution continent thereby underline quality issues gaps across taxonomic groups geographic space. therefore downloaded on 17th January 2023 from Plantae kingdom Africa. They are available https://doi.org/10.15468/dl.p2n6um. achieved treatment analysis using R, several packages related functions. Although home rich many hotspots, global (61,176,994 2023) still incredibly low (2.69%). Furthermore, there large disparities between African countries, South contributing alone 50% continent. (9,116,401 records) accounted 14.90% continent; this underlines huge groups. noted important loss during process cleaning clearly underlining limited indeed, fitness purpose in completeness were only 50.94% total initially downloaded. Efforts check before publication needed countries. Magnoliopsida was dominant class highest number (71.07%) species (68.36%), followed Liliopsida, 22.80% 19.06% species. In space, also quite West Africa, Southern East Madagascar. order account non-normality distribution data, robust correlation methods well mean comparison used. From results, accessibility rivers roads protected areas limiting factors multidimensional identified study should be priority addressed future collections

Language: Английский

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Completeness of digitally accessible knowledge of plants across Africa and priorities for future data discovery

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Digital accessible knowledge (DAK) is of utmost importance for biodiversity conservation. The Global Biodiversity Information Facility (GBIF, www.gbif.org) a mega data infrastructure with more than three billion and seventy million (3,070,000,000) occurrence records as ⁰⁴ March 2025. It by far the largest initiative assembling sharing DAK to support scientific research, conservation, sustainable development. We analyzed plant published at GBIF site in Africa highlight contribution continent thereby quality issues gaps across taxonomic groups geographic space. therefore downloaded from 17th January 2023 Plantae kingdom Africa. They are available https://doi.org/10.15468/dl.p2n6um. achieved treatment analysis via R, several packages related functions. Although home rich many hotspots, global (61,176,994 2023) still extremely low (2.69%). Furthermore, there large disparities between African countries, South contributing 50% continent’s alone. (9,116,401 records) accounted 14.90% continent; this underlines enormous groups. noted important loss during process cleaning, clearly underlining limited indeed, fitness completeness was only 50.94% total initially downloaded. Efforts checks before publication needed countries. Magnoliopsida dominant class highest number (71.07%) species (68.36%), followed Liliopsida, 22.80% 19.06% species. In space, also quite greater West Africa, Southern East Madagascar. To account non-normal distribution data, robust correlation methods mean comparison were used. According results, accessibility rivers roads well protected areas limiting factors continent. multidimensional identified study cleaning should be prioritized future collection

Language: Английский

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Habitat selection by an extraordinary savannah raptor: environmental factors driving abundance of the Secretarybird Sagittarius serpentarius in the Serengeti National Park (Tanzania)

Bird Study, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: April 30, 2025

Language: Английский

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Big data, big problems? How to circumvent problems in biodiversity mapping and ensure meaningful results

Ecography, Journal Year: 2024, Volume and Issue: 2024(8)

Published: May 30, 2024

Our knowledge of biodiversity hinges on sufficient data, reliable methods, and realistic models. Without an accurate assessment species distributions, we cannot effectively target stem loss. Species range maps are the foundation such efforts, but countless studies have failed to account for most basic assumptions mapping practices, undermining credibility their results potentially misleading hindering conservation management efforts. Here, use examples from recent literature broader community highlight substantial shortfalls in current practices consequences both analyses management. We detail how different decisions data filtering impact outcomes analysis provide practical recommendations steps more analysis, whilst understanding limits what available will reliably allow methods appropriate. Whilst perfect not possible many taxa given limited biases, ensuring within reasonable inherent is crucial ensure appropriate use. By embracing enacting best can accuracy improved comparability going forward, ultimately enhancing our ability facilitate protection natural world.

Language: Английский

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Capability of big data to capture threatened vertebrate diversity in protected areas

Conservation Biology, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Abstract Protected areas (PAs) are an essential tool for conservation amid the global biodiversity crisis. Optimizing PAs to represent species at risk of extinction is crucial. Vertebrate representation in assessed using distribution databases from International Union Conservation Nature (IUCN) and Global Biodiversity Information Facility (GBIF). Evaluating addressing discrepancies biases these data sources vital effective strategies. Our objective was gain insights into potential constraints (e.g., differences biases) repositories objectively depict diversity threatened vertebrates system PAs. We richness (SR) as reported by IUCN GBIF globally then compared how biased this information with reports independent a subset Both showed substantial SR ( t = −62.35, p ≤ 0.001), but varied among regions vertebrate groups. When results were assessments, overestimated 575% on average underestimated 63% average, again variable indicate need improve analyses representativeness such that robust unbiased assessments PA effectiveness can be conducted. The scientific community decision makers should consider regional taxonomic disparities when distributional assessment. Overall, supplementing could lead more reliable analyses. Additional efforts acquire comprehensive distributions support decisions clearly needed.

Language: Английский

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Projected impacts of climate change on ecosystem services provided by terrestrial mammals in Brazil

Ecosystem Services, Journal Year: 2024, Volume and Issue: 71, P. 101687 - 101687

Published: Dec. 7, 2024

Language: Английский

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