The persistent multi-dimensional biases of biodiversity digital accessible knowledge of birds in China

Huang, Xiande; Lin, Congtian; Ji, Liqiang

doi:10.1007/s10531-020-02024-3

Cited by 13 publications

(10 citation statements)

References 68 publications

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“…The observational dataset included the bird checklist data compiled from observational data, including digitalized specimen and bird-watching data, i.e., bird occurrence data. The data were obtained from three main sources, which represent the digital accessible knowledge of birds in China: (1) the Global Biodiversity Information Facility (GBIF, https://www.gbif.org, GBIF, 2018), with the majority of these records coming from eBird and specimen; (2) the BirdReport, 1 and (3) three sub-platforms of the National Specimen Information Infrastructure (NSII, http://www.nsii.org.cn; Huang et al, 2020). The bird checklist data for each data source were also compiled for further analyses.…”

Section: Bird Lists and Plant Richnessmentioning

confidence: 99%

“…In addition, biodiversity informatics is booming in China, and a large amount of publicly accessible observational data being generated. For instance, the National Species Information Infrastructure (NSII, http://www.nsii.org.cn) is the main source of digitalized specimen data in China at present (Huang et al, 2020). In recent years, citizen science has become popular in China, and many citizen science projects are continuously producing data, which has been used in many biodiversity studies (Dong et al, 2020;Duan et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, citizen science has become popular in China, and many citizen science projects are continuously producing data, which has been used in many biodiversity studies (Dong et al, 2020;Duan et al, 2020). Although studies have indicated that such observation-based data in China have large gaps in various dimensions (Yang et al, 2013;Huang et al, 2020), China is an excellent geographical unit for exploring whether there are differences in the diversity-environment relationships between species inventories compiled from different sources.…”

Section: Introductionmentioning

confidence: 99%

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Species inventories from different data sources “shaping” slightly different avifauna diversity patterns

Huang

Lin

et al. 2023

Front. Ecol. Evol.

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IntroductionSpecies inventories based on various data sources have been widely used in biodiversity research, conservation policy formulation, reserve designation and biodiversity resource management. In this paper, we explored the relationships of species inventories obtained from different sources and whether they would affect the inference of biodiversity patterns and their environmental drivers.MethodsWe compiled the species inventories from different data sources (observational data including large amounts of citizen-based observational records and digitalized specimens, and avifauna data extracted from avifaunas which mainly integrated professional-based species surveys, expert knowledge and documentary records) at the prefectural level in China. Then we explored the relationships of different inventories and compared the correlations between the taxonomic, phylogenetic, functional diversity calculated from different datasets and the environmental factors.Results and DiscussionThe results showed that the avifauna datasets contributed more additional species to the combined species inventories when the species richness was relatively low and vice versa. Species inventories integrated from two different data sources formed complementary relationship rather than nested or totally different relationships. In addition, the species inventories based on observational data had no obvious disadvantage or were even better at inferring the biodiversity patterns than those based on avifauna data. The stepwise multiple regression analyses showed that the best models were the ones using the species inventories combined by observational and avifauna dataset, and the best models built with different datasets included inconsistent environmental variables. Thus, the species inventories from different data sources will indeed affect the inference of the correlations between taxonomic diversity, phylogenetic diversity, functional diversity and environmental factors. Moreover, although it may be more reliable to use a combined species inventory to analyze the relationship between diversity indices and environmental factors, individualized improvement schemes should be proposed for different data sources to fill the data gaps.

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Section: Bird Lists and Plant Richnessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Species inventories from different data sources “shaping” slightly different avifauna diversity patterns

Huang

Lin

et al. 2023

Front. Ecol. Evol.

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“…We analyzed the impacts of rivers, roads, and protected areas on data completeness. To analyze the impact of rivers on data completeness, we downloaded the shape le of African Rivers (World Agroforestry Centre, http://landscapeportal.org/layers/geonode:africa_rivers_1, accessed on 26 August 2022); the road network we used was downloaded from Africa -Road Network (Africa -Road Network, https://energydata.info/dataset/road-network, accessed on 26 August 2022); and the shape le of the protected areas was downloaded from Protected planet (Protected planet, https://www.protectedplanet.net/region/AF, accessed on 27 August 2022). The function "over" of the "sp" package was therefore used to retrieve the identi cation codes of the grid cells (half-degree and onedegree spatial grid cells) and added them to the respective data frames of the rivers, roads, and protected areas.…”

Section: 3-analysis Of the Impacts Of Accessibility And Protected Are...mentioning

confidence: 99%

Will Africa meet the challenge of biodiversity conservation in the digital age?

Ganglo

2022

Preprint

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Digital accessible knowledge (DAK) is of utmost importance for biodiversity conservation; indeed, its use is indispensable to provide evidence and strategies to support decision-making on natural resource management and sustainable use. The Global Biodiversity Information Facility (GBIF, www.gbif.org) is a mega data infrastructure with more than two billion occurrence records as of 28 May 2022. It is by far the largest initiative assembling and sharing DAK to support scientific research, conservation, and sustainable development. We decided to analyze plant data published at the GBIF site at the scale of Africa. This will highlight the contribution of the continent to the GBIF and thereby underline data gaps across taxonomic groups, the basis of records, and geographic space. To achieve our purpose, we downloaded data from the Plantae kingdom from Africa. They are available at https://doi.org/10.15468/dl.f79228. We achieved data treatment and analysis using R, several packages and related functions. Although Africa is home to rich biodiversity with many hotspots, the global data contribution of Africa to the GBIF is still incredibly low (1.37%). Furthermore, there are huge disparities between African countries, with South Africa contributing alone for 65% of the data of the continent. The plant data of Africa (2,713,790 occurrence records) accounted for 9.11% of the data of the continent; this underlines huge gaps between taxonomic groups. Furthermore, Magnoliopsida was the dominant plant class with the highest number of records (79.62%) and the highest number of species (71.85%), followed by Liliopsida, with 15.10% of the records and 18.16% of the species. Two sources of records were dominant: preserved specimens (75.49%) and human observation (18.60%). In geographic space, plant data gaps are also quite large across the continent at either spatial resolution (half degree or one degree spatial grid cells); data completeness is more achieved in West Africa, East Africa, Southern Africa, and Madagascar. The large multidimensional data gaps identified in this study should be a priority addressed in future data collections. Accessibility either by roads or waterways and protected areas are underpinning factors of data completeness across the continent. We deplored important data loss during the process of data cleaning; indeed, the total number of records with adequate coordinates accounted for 71.03% of the initial data, while the data fitness for use in completeness analysis (records with adequate coordinates and full dates) was only approximately 65% of the total data records initially downloaded.

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“…However, the existing digital accessible dataset could not fill the gap completely in China’s bird distributions. The most prominent portal of diversity data, Global Biodiversity Information Facility (GBIF) has a number of occurrence data of China’s birds, but the tremendously low temporal coverage hinders researchers from revealing the distributional dynamics of each species ( Huang et al 2020 ). The Birdlife International and Handbook of the Birds of the World also provide digitised distribution maps for birds, but static maps could not show the distributional dynamics.…”

Section: Introductionmentioning

confidence: 99%

A dataset of bird distributions in zoogeographical regions of China

Han¹,

Xia²,

Møller³

2022

BDJ

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China, the largest country in Asia, has a land area of approximately 9.6 million square kilometres. There are 1481 bird species (following the taxonomy of IOC World Bird List version 12.1) recorded in two zoogeographical realms, seven regions and 19 subregions in the country. From 1955 to 2017, six authoritative monographs were published, which recorded the distribution area for all bird species in China and were widely quoted by research papers and field guides. This massive amount of data could be used to address many hot topics in ornithology, biogeography and ecology. However, rapid changes in the taxonomic status and different schemes of zoogeographical regionalisation in these six monographs provided limits to the utilisation of these valuable data. By integrating the data from the six monographs, we presented an open-access dataset on the occurrences and residence types of all Chinese bird species in zoogeographical regions over the past 60 years. The taxonomic statuses for these species were determined following the IOC World Bird List version 12.1 and the zoogeographical regions were based on the updated scheme. These data provide valuable information for the research in bird ecology and conservation biology.

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The persistent multi-dimensional biases of biodiversity digital accessible knowledge of birds in China

Cited by 13 publications

References 68 publications

Species inventories from different data sources “shaping” slightly different avifauna diversity patterns

Species inventories from different data sources “shaping” slightly different avifauna diversity patterns

Will Africa meet the challenge of biodiversity conservation in the digital age?

A dataset of bird distributions in zoogeographical regions of China

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