How sensitive are climatic niche inferences to distribution data sampling? A comparison of Biota of North America Program (BONAP) and Global Biodiversity Information Facility (GBIF) datasets

Climatic niche modeling is widely used in modern macroecology and evolutionary biology to model species' distributions and ecological niches. Frequently, Global Biodiversity Information Facility (GBIF) distribution data are used as raw data for such models. Unfortunately, the accuracy of resulting niche estimates is difficult to assess, and GBIF users continue to call for a better understanding of GBIF data precision and uncertainty. Our research evaluates how GBIF data perform in comparison with curated, county-level species distributions from the Biota of North America Program (BONAP; www.bonap.org) to estimate the climatic niche for Carex (Cyperaceae), one of the largest angiosperm genera in the temperate zone. In particular, we investigate the complementary strengths and weaknesses of the two datasets in the context of climatic niche estimation, namely (1) the incomplete sampling coverage of species distributions of GBIF data, and (2) elevation bias in climatic niche estimates resulting from the coarse resolution of the BONAP distribution dataset. To do so, we quantified climatic niches for 388 North American Carex species and calculated the distance of GBIF and BONAP climatic niche estimates in principal component space. We found little to no relationship between differences in climatic niche estimates and sampling coverage metrics, suggesting that sparse sampling coverage of GBIF data may have negligible average effects on mean climate estimates at the species level. However, elevation had a significant effect on differences in niche estimates, suggesting that using county-level distribution data—in our study, represented by BONAP—may introduce a bias in estimated climatic niche. To investigate if any such bias is phylogenetically structured, we examined the relationship between GBIF and BONAP climatic niche tip states using Phylogenetic Generalized Least Squares Regression (PGLS), estimating phylogenetic signal in the residuals of the regression by estimating Pagel's λ simultaneously with other regression parameters. Estimates were tightly correlated, with little to no phylogenetic signal—low λ—in the regression residuals, suggesting that any potential bias is more or less independent of phylogeny for the sedges of North America. Based on our results, we recommend a hybrid GBIF and BONAP data approach for the best understanding of species' climatic niche, relying on BONAP to fill in distributions primarily where collection records may be sparse. Our findings provide needed context and perspective on the implications of alternative distribution datasets for climatic niche estimation, especially in a macroevolutionary context.     

Global patterns of fern species diversity: An evaluation of fern data in GBIF

Despite that several studies have shown that data derived from species lists generated from distribution occurrence records in the Global Biodiversity Information Facility (GBIF) are not appropriate for those ecological and biogeographic studies that require high sampling completeness, because species lists derived from GBIF are generally very incomplete, Suissa et al. (2021) generated fern species lists based on data with GBIF for 100 km × 100 km grid cells across the world, and used the data to determine fern diversity hotspots and species richness–climate relationships. We conduct an evaluation on the completeness of fern species lists derived from GBIF at the grid–cell scale and at a larger spatial scale, and determine whether fern data derived from GBIF are appropriate for studies on the relations of species composition and richness with climatic variables. We show that species sampling completeness of GBIF is low (<40%) for most of the grid cells examined, and such low sampling completeness can substantially bias the investigation of geographic and ecological patterns of species diversity and the identification of diversity hotspots. We conclude that fern species lists derived from GBIF are generally very incomplete across a wide range of spatial scales, and are not appropriate for studies that require data derived from species lists in high completeness. We present a map showing global patterns of fern species diversity based on complete or nearly complete regional fern species lists.     

Meeting Report: Hackathon-Workshop on Darwin Core and MIxS Standards Alignment (February 2012)

The Global Biodiversity Information Facility and the Genomic Standards Consortium convened a joint workshop at the University of Oxford, 27-29 February 2012, with a small group of experts from Europe, USA, China and Japan, to continue the alignment of the Darwin Core with the MIxS and related genomics standards. Several reference mappings were produced as well as test expressions of MIxS in RDF. The use and management of controlled vocabulary terms was considered in relation to both GBIF and the GSC, and tools for working with terms were reviewed. Extensions for publishing genomic biodiversity data to the GBIF network via a Darwin Core Archive were prototyped and work begun on preparing translations of the Darwin Core to Japanese and Chinese. Five genomic repositories were identified for engagement to begin the process of testing the publishing of genomic data to the GBIF network commencing with the SILVA rRNA database.     

A specialist’s audit of aggregated occurrence records

Occurrence records for named, native Australian millipedes from the Global Biodiversity Information Facility (GBIF) and the Atlas of Living Australia (ALA) were compared with the same records from the Millipedes of Australia (MoA) website, compiled independently by the author. The comparison revealed some previously unnoticed errors in MoA, and a much larger number of errors and other problems in the aggregated datasets. Errors have been corrected in MoA and in some data providers’ databases, but will remain in GBIF and ALA until data providers have supplied updates to these aggregators. An audit by a specialist volunteer, as reported here, is not a common occurrence. It is suggested that aggregators should do more, or more effective, data checking and should query data providers when possible errors are detected, rather than simply disclaim responsibility for aggregated content.     

Communication gaps in knowledge of freshwater fish biodiversity: implications for the management and conservation of Mexican biosphere reserves

To detect differences in the information available on freshwater fish species found in Mexican biosphere reserves, the number of species considered in three sources of information: management programmes, Global Biodiversity Information Facility (GBIF) and the scientific literature were compared. Additionally, management actions for the reserves were evaluated. More than 55% of freshwater fish species registered for the reserves were found only in one of the three sources of information, while just 12% was shared among all the three. Fifteen threatened species were registered in GBIF and the scientific literature that were not found in management programmes. Although all the management programmes described conservation actions, none of them gave details about how they would be implemented. Lack of communication among the sources studied, unawareness of the existence of threatened species and the absence of detailed management actions hinder the development of adequate conservation strategies.     

A web-based GIS tool for exploring the world's biodiversity: The Global Biodiversity Information Facility Mapping and Analysis Portal Application (GBIF-MAPA)

Legacy biodiversity data from natural history and survey collections are rapidly becoming available in a common format over the Internet. Over 110 million records are already being served from the Global Biodiversity Information Facility (GBIF). However, our ability to use this information effectively for ecological research, management and conservation lags behind. A solution is a web-based Geographic Information System for enabling visualization and analysis of this rapidly expanding data resource. In this paper we detail a case study system, GBIF Mapping and Analysis Portal Application (MAPA), developed for deployment at distributed database portals. Building such a system requires overcoming a series of technical and research challenges. These challenges include: assuring fast speed of access to the vast amounts of data available through these distributed biodiversity databases; developing open standards based access to suitable environmental data layers for analyzing biodiversity distribution; building suitably flexible and intuitive map interfaces for refining the scope and criteria of an analysis; and building appropriate web-services based analysis tools that are of primary importance to the ecological community and make manifest the value of online biodiversity GBIF data. After discussing how we overcome these challenges, we provide case studies showing two examples of the use of GBIF-MAPA analysis tools.     

Filling in the GAPS: evaluating completeness and coverage of open‐access biodiversity databases in the United States

Primary biodiversity data constitute observations of particular species at given points in time and space. Open‐access electronic databases provide unprecedented access to these data, but their usefulness in characterizing species distributions and patterns in biodiversity depend on how complete species inventories are at a given survey location and how uniformly distributed survey locations are along dimensions of time, space, and environment. Our aim was to compare completeness and coverage among three open‐access databases representing ten taxonomic groups (amphibians, birds, freshwater bivalves, crayfish, freshwater fish, fungi, insects, mammals, plants, and reptiles) in the contiguous United States. We compiled occurrence records from the Global Biodiversity Information Facility (GBIF), the North American Breeding Bird Survey (BBS), and federally administered fish surveys (FFS). We aggregated occurrence records by 0.1° × 0.1° grid cells and computed three completeness metrics to classify each grid cell as well‐surveyed or not. Next, we compared frequency distributions of surveyed grid cells to background environmental conditions in a GIS and performed Kolmogorov–Smirnov tests to quantify coverage through time, along two spatial gradients, and along eight environmental gradients. The three databases contributed >13.6 million reliable occurrence records distributed among >190,000 grid cells. The percent of well‐surveyed grid cells was substantially lower for GBIF (5.2%) than for systematic surveys (BBS and FFS; 82.5%). Still, the large number of GBIF occurrence records produced at least 250 well‐surveyed grid cells for six of nine taxonomic groups. Coverages of systematic surveys were less biased across spatial and environmental dimensions but were more biased in temporal coverage compared to GBIF data. GBIF coverages also varied among taxonomic groups, consistent with commonly recognized geographic, environmental, and institutional sampling biases. This comprehensive assessment of biodiversity data across the contiguous United States provides a prioritization scheme to fill in the gaps by contributing existing occurrence records to the public domain and planning future surveys.     

Monitoring records of plant species in the Hakone region of Fuji-Hakone-Izu National Park, Japan, 2001–2010

The monitoring of species occurrences is a crucial aspect of biodiversity conservation, and regional volunteerism can serve as a powerful tool in such endeavors. The Fuji-Hakone-Izu National Park in the Hakone region of Kanagawa Prefecture, Japan, boasts a volunteer association of approximately 100 members. These volunteers have monitored plant species occurrences from 2001 to the present along several hiking trails in the region. In this paper, I present the annual observation records of plant occurrences in Hakone from 2001 to 2010. This data set includes 1,071 species of plants from 151 families. Scientific names follow the Y List, and this data set includes several threatened plant species. Data files are formatted based on the Darwin Core and Darwin Core Archives, which are defined by the Biodiversity Information Standards (BIS) or Biodiversity Information Standards Taxonomic Databases Working Group (TDWG). Data files filled on required and some additional item on Darwin Core. The data set can download from the author’s personal Web site as of July 2012. These data will soon be published for the Global Biodiversity Information Facility (GBIF) through GBIF Japan. All users can then access the data from the GBIF portal site.     

Assessing the Primary Data Hosted by the Spanish Node of the Global Biodiversity Information Facility (GBIF)

In order to effectively understand and cope with the current ‘biodiversity crisis’, having large-enough sets of qualified data is necessary. Information facilitators such as the Global Biodiversity Information Facility (GBIF) are ensuring increasing availability of primary biodiversity records by linking data collections spread over several institutions that have agreed to publish their data in a common access schema. We have assessed the primary records that one such publisher, the Spanish node of GBIF (GBIF.ES), hosts on behalf of a number of institutions, considered to be a highly representative sample of the total mass of available data for a country in order to know the quantity and quality of the information made available. Our results may provide an indication of the overall fitness-for-use in these data. We have found a number of patterns in the availability and accrual of data that seem to arise naturally from the digitization processes. Knowing these patterns and features may help deciding when and how these data can be used. Broadly, the error level seems low. The available data may be of capital importance for the development of biodiversity research, both locally and globally. However, wide swaths of records lack data elements such as georeferencing or taxonomical levels. Although the remaining information is ample and fit for many uses, improving the completeness of the records would likely increase the usability span for these data.     

GBIF information is not enough: national database improves the inventory completeness of Amazonian epiphytes

Distribution data sharing in global databases (e.g. GBIF) allowed the knowledge synthesis in several biodiversity areas. However, their Wallacean shortfalls still reduce our capacity to understand distribution patterns. Including exclusive records from other databases, such as national ones (e.g. SpeciesLink), could mitigate these shortfall problems, but it remains not evaluated. Therefore, we assessed whether (i) the inventory completeness, (ii) taxonomic contribution and (iii) spatial biases could be improved when integrating both global and national biodiversity databases. Using Amazonian epiphytes as a model, we compared the available taxonomic information spatially between GBIF and SpeciesLink databases using a species contribution index. We obtained the inventory completeness from sources using species accumulation curves and assessed their spatial biases by constructing spatial autoregressive models. We found that both databases have a high amount of exclusive records (GBIF: 36.7%; SpeciesLink: 21.7%) and species (17.8%). Amazonia had a small epiphyte inventory completeness, but it was improved when we analyzed both databases together. Individually, both database records were biased to sites with higher altitude, population and herbarium density. Together, river density appeared as a new predictor, probably due to the higher species contribution of SpeciesLink along them. Our findings provide strong evidence that using both global and national databases increase the overall biodiversity knowledge and reduce inventory gaps, but spatial biases may persist. Therefore, we highlight the importance of aggregating more than one database to understand biodiversity patterns, to address conservation decisions and direct shortfalls more efficiently in future studies.

     

The contribution of small collections to species distribution modelling: A case study from Fuireneae (Cyperaceae)

The recent and rapid digitization of biodiversity data from natural history collection (NHC) archives has enriched collections based data repositories; this data continues to inform studies of species' geographic distributions. Here we investigate the relative impact of plant data from small natural history collections (collections with < 100,000 specimens) on species distributional models in an effort to document the potential of data from small NHCs to contribute to and inform biodiversity research. We modelled suitable habitat of five test case species from Fuireneae (Cyperaceae) in the United States using specimen records available via the Global Biodiversity Information Facility and that of data ready to mobilize from two regional small herbaria. Data were partitioned into three datasets based on their source: 1) collections-based records from large NHCs accessed GBIF, 2) collections-based records from small NHCs accessed from GBIF, and 3) collections-based records from two small regional herbaria not yet mobilized to GBIF. We extracted and evaluated the ecological niche represented for each of the three datasets by applying dataset occurrences to 14 environmental factors, and we modelled habitat suitability using Maxent to compare the represented distribution of the environmental values among the datasets. Our analyses indicate that the data from small NHCs contributed unique information in both geographic and environmental space. When data from small collections were combined with data from large collections, species models of the ecological niche resulted in more refined predictions of habitat suitability, indicating that small collections can contribute unique occurrence data which enhance species distribution models by bridging geographic collection gaps and shifting modelled predictions of suitable habitat. Inclusion of specimen records from small collections in ongoing digitization efforts is essential for generating informed models of a species' niche and distribution.     

台湾生物多样性资料整合之经验与策略

台湾生物多样性数据库之整合从2001年开始, 是因为数位典藏计划、生物多样性推动方案, 及台湾加入全球生物多样性信息网络(Global Biodiversity Information Facility, GBIF), 均在这一年启动。2002年“中研院”开始建置台湾物种名录数据库(TaiBNET), GBIF之台湾入口网TaiBIF则是在2004年时建置, 用来整合台湾生物多样性的资料并与国际接轨。所采用之方法及格式均依循GBIF所发展的交换标准, 一来可以整合台湾的数据, 二来可及时与国际交换数据。虽然TaiBNET及TaiBIF已突破智慧财产权(知识产权)的障碍, 可搜集整合数位典藏各子计划逐年累积的资料, 但跨部门间及非数位典藏计划所产生的数据, 仍因各单位及个人的本位主义而难以整合分享, 特别是生态分布原始数据。因此2008年在“中研院”成立了跨主管部门的委员会, 制订可行之资料搜集、整合与公开的政策, 并要求各主管部门在委办合约中纳入。无人否认数据库整合的重要, 但在现行对研究人员考评制度下, 研究人员大多不愿投入数据库建置的学术服务工作, 所获得的人力与经费亦日益短缺而难以永续经营。亟需相关部门的重视与支持。TaiBIF在过去6年来的推动成果虽未臻理想, 但所获的经验和心得仍有可供外界参考与借镜之处。     

A Tenebrionid beetle’s dataset (Coleoptera,Tenebrionidae) from Peninsula Valdés (Chubut,?Argentina)

The Natural Protected Area Peninsula Valdés, located in Northeastern Patagonia, is one of the largest conservation units of arid lands in Argentina. Although this area has been in the UNESCO World Heritage List since 1999, it has been continually exposed to sheep grazing and cattle farming for more than a century which have had a negative impact on the local environment. Our aim is to describe the first dataset of tenebrionid beetle species living in Peninsula Valdés and their relationship to sheep grazing. The dataset contains 118 records on 11 species and 198 adult individuals collected. Beetles were collected using pitfall traps in the two major environmental units of Peninsula Valdés, taking into account grazing intensities over a three year time frame from 2005–2007. The Data quality was enhanced following the best practices suggested in the literature during the digitalization and geo-referencing processes. Moreover, identification of specimens and current accurate spelling of scientific names were reviewed. Finally, post-validation processes using DarwinTest software were applied. Specimens have been deposited at Entomological Collection of the Centro Nacional Patagónico (CENPAT-CONICET). The dataset is part of the database of this collection and has been published on the internet through GBIF Integrated Publishing Toolkit (IPT) (http://data.gbif.org/datasets/resource/14669/). Furthermore, it is the first dataset for tenebrionid beetles of arid Patagonia available in GBIF database, and it is the first one based on a previously designed and standardized sampling to assess the interaction between these beetles and grazing in the area. The main purposes of this dataset are to ensure accessibility to data associated with Tenebrionidae specimens from Peninsula Valdés (Chubut, Argentina), also to contribute to GBIF with primary data about Patagonian tenebrionids and finally, to promote the Entomological Collection of Centro Nacional Patagónico (CENPAT-CONICET) and its associated biodiversity data. For these reasons, we believe that this information will certainly be useful for future faunistic, ecological, conservational and biogeographical studies.     

The ABCD of primary biodiversity data access

Abstract

Within the context of the Global Biodiversity Information Facility (GBIF), the Biological Collections Access Service (BioCASe) has been set up to foment data provision by natural history content providers. Products include the BioCASe Protocol and the PyWrapper software, a web service allowing to access rich natural history data using complex schemas like ABCD (Access to Biological Collection Data). New developments include the possibility to produce DarwinCore-Archive files using PyWrapper, in order to facilitate the indexing of large datasets by aggregators such as GBIF. However, BioCASe continues to be committed to distributed data access and continues to provide the possibility to directly query the web service for up-to-date data directly from the provider's database. ABCD provides comprehensive coverage of natural history data, and has been extended to cover DNA collections (ABCD-DNA) and geosciences (ABCD-EFG, the extension for geosciences). BioCASe also developed web portal software that allows to access and display rich data provided by special interest networks. We posit that the XML-based networking approach using a highly standardised data definition such as ABCD continues to be a valuable approach towards mobilising natural history information. Some suggestions are made regarding further improvements of ABCD.     

Harvestmen of the BOS Arthropod Collection of the University of Oviedo (Spain) (Arachnida,Opiliones)

There are significant gaps in accessible knowledge about the distribution and phenology of Iberian harvestmen (Arachnida: Opiliones). Harvestmen accessible datasets in Iberian Peninsula are unknown, an only two other datasets available in GBIF are composed exclusively of harvestmen records. Moreover, only a few harvestmen data from Iberian Peninsula are available in GBIF network (or in any network that allows public retrieval or use these data). This paper describes the data associated with the Opiliones kept in the BOS Arthropod Collection of the University of Oviedo, Spain (hosted in the Department of Biología de Organismos y Sistemas), filling some of those gaps. The specimens were mainly collected from the northern third of the Iberian Peninsula. The earliest specimen deposited in the collection, dating back to the early 20^th century, belongs to the P. Franganillo Collection. The dataset documents the collection of 16,455 specimens, preserved in 3,772 vials. Approximately 38% of the specimens belong to the family Sclerosomatidae, and 26% to Phalangidae; six other families with fewer specimens are also included. Data quality control was incorporated at several steps of digitisation process to facilitate reuse and improve accuracy. The complete dataset is also provided in Darwin Core Archive format, allowing public retrieval, use and combination with other biological, biodiversity of geographical variables datasets.     

From GenBank to GBIF: Phylogeny-Based Predictive Niche Modeling Tests Accuracy of Taxonomic Identifications in Large Occurrence Data Repositories

Accuracy of taxonomic identifications is crucial to data quality in online repositories of species occurrence data, such as the Global Biodiversity Information Facility (GBIF), which have accumulated several hundred million records over the past 15 years. These data serve as basis for large scale analyses of macroecological and biogeographic patterns and to document environmental changes over time. However, taxonomic identifications are often unreliable, especially for non-vascular plants and fungi including lichens, which may lack critical revisions of voucher specimens. Due to the scale of the problem, restudy of millions of collections is unrealistic and other strategies are needed. Here we propose to use verified, georeferenced occurrence data of a given species to apply predictive niche modeling that can then be used to evaluate unverified occurrences of that species. Selecting the charismatic lichen fungus, Usnea longissima, as a case study, we used georeferenced occurrence records based on sequenced specimens to model its predicted niche. Our results suggest that the target species is largely restricted to a narrow range of boreal and temperate forest in the Northern Hemisphere and that occurrence records in GBIF from tropical regions and the Southern Hemisphere do not represent this taxon, a prediction tested by comparison with taxonomic revisions of Usnea for these regions. As a novel approach, we employed Principal Component Analysis on the environmental grid data used for predictive modeling to visualize potential ecogeographical barriers for the target species; we found that tropical regions conform a strong barrier, explaining why potential niches in the Southern Hemisphere were not colonized by Usnea longissima and instead by morphologically similar species. This approach is an example of how data from two of the most important biodiversity repositories, GenBank and GBIF, can be effectively combined to remotely address the problem of inaccuracy of taxonomic identifications in occurrence data repositories and to provide a filtering mechanism which can considerably reduce the number of voucher specimens that need critical revision, in this case from 4,672 to about 100.     

The future of the past in the present: biodiversity informatics and geological time

The biological and palaeontological communities have approached the problem of informatics separately, creating a divide between communities that is both technological and sociological in nature. In this paper we describe one new advance towards solving this problem - expanding the Scratchpads platform to deal with geological time. In creating this system we have attempted to make our work open to existing communities by providing a webservice of geological time data via the GBIF Vocabularies site. We have also ensured that our system can adapt to changes in the definition of geological time intervals and is capable of querying datasets independently of the format of geological age data used.     

Software identification tools for biodiversity and biosecurity monitoring

The taxonomic crisis, associated with declining taxonomic expertise and resources, poses serious problems for biodiversity and biosecurity monitoring and management. While there has been a dramatic increase in the amount of taxonomic information available on the Web, resulting from such global initiatives as Species 2000, All Species and the Global Biodiversity Information Facility (GBIF), the lack of identification services has meant this information is often not accessible to many potential users. Apart from the immediate problems raised by the inability of ecologists, conservation managers, plant health inspectors and other practitioners to identify specimens of concern, this in turn means they are also unable to access the increasing wealth of information about particular organisms that is potentially available to them.     

生物多样性信息学:一个正在兴起的新方向及其关键技术

生物多样性科学和生物信息学是生命科学中两个极为重要也是十分活跃的交叉学科,生物多样性信息学则是目前正在兴起的一个新方向,基发展必将进一步深化信息技术在生物多样性研究中的应用。本文简要介绍了国内外该领域的主要目标与进展,讨论了有关的关键技术（如数据库间的互操作与数字图书馆）,并列出了两个原型系统（Ｓｐｅｃｉｅｓ２０００和ＧＢＩＦ）和其他相关系统的网址。