scholarly journals Environmental DNA reveals that rivers are conveyer belts of biodiversity information

2015 ◽  
Author(s):  
Kristy Deiner ◽  
Emanuel A. Fronhofer ◽  
Elvira Meächler ◽  
Jean-Claude Walser ◽  
Florian Altermatt

AbstractDNA sampled from the environment (eDNA) is becoming a game changer for uncovering biodiversity patterns. By combining a conceptual model and empirical data, we test whether eDNA transported in river networks can be used as an integrative way to assess eukaryotic biodiversity for broad spatial scales and across the land-water interface. Using an eDNA metabarcode approach we detected 296 families of eukaryotes, spanning 19 phyla across the catchment of a river. We show for a subset of these families that eDNA samples overcome spatial autocorrelation biases associated with classical community assessments by integrating biodiversity information over space. Additionally, we demonstrate that many terrestrial species can be detected; thus revealing that eDNA in river-water also incorporates biodiversity information across terrestrial and aquatic biomes. Environmental DNA transported in river networks offers a novel and spatially integrated way to assess total biodiversity for whole landscapes and will transform biodiversity data acquisition in ecology.“Eventually, all things merge into one, 32 and a river runs through it.” — Norman Maclean

2021 ◽  
Vol 10 (3) ◽  
pp. 186
Author(s):  
HuiHui Zhang ◽  
Hugo A. Loáiciga ◽  
LuWei Feng ◽  
Jing He ◽  
QingYun Du

Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density without considering anthropogenic impacts and landscape patterns. This study contributes two FAT estimation methods. The first method explores the statistical association between FAT and 47 tentative explanatory factors. Specifically, multi-source data, including meteorologic, vegetation, anthropogenic, landscape, lithology, and topologic characteristics are incorporated into a drainage density-FAT model in basins with complex topographic and environmental characteristics. Non-negative matrix factorization (NMF) was employed to evaluate the factors’ predictive performance. The second method exploits fractal geometry theory to estimate the FAT at the regional scale, that is, in basins whose large areal extent precludes the use of basin-wide representative regression predictors. This paper’s methodology is applied to data acquired for Hubei and Qinghai Provinces, China, from 2001 through 2018 and systematically tested with visual and statistical criteria. Our results reveal key local features useful for river network extraction within the context of complex geomorphologic characteristics at relatively small spatial scales and establish the importance of properly choosing explanatory geomorphologic characteristics in river network extraction. The multifractal method exhibits more accurate extracting results than the box-counting method at the regional scale.


Ecosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
Author(s):  
Mathieu Chevalier ◽  
Heidi Mod ◽  
Olivier Broennimann ◽  
Valeria Di Cola ◽  
Sarah Schmid ◽  
...  

Food Webs ◽  
2019 ◽  
Vol 18 ◽  
pp. e00107 ◽  
Author(s):  
Peter E. Schlichting ◽  
Cara N. Love ◽  
Sarah C. Webster ◽  
James C. Beasley

Author(s):  
Natalya Ivanova ◽  
Maxim Shashkov

Currently Russia doesn't have a national biodiversity information system, and is still not a GBIF (Global Biodiversity Information Facility) member. Nevertheless, GBIF is the largest source of biodiversity data for Russia. As of August 2020, >5M species occurrences were available through the GBIF portal, of which 54% were published by Russian organisations. There are 107 institutions from Russia that have become GBIF publishers and 357 datasets have been published. The important trend of data mobilization in Russia is driven by the considerable contribution of citizen science. The most popular platform is iNaturalist. This year, the related GBIF dataset (Ueda 2020) became the largest one for Russia (793,049 species occurrences as of 2020-08-11). The first observation for Russia was posted in 2011, but iNaturalist started becoming popular in 2017. That year, 88 observers added >4500 observations that represented 1390 new species for Russia, 7- and 2-fold more respectively, than for the previous 6 years. Now we have nearly 12,000 observers, about 15,000 observed species and >1M research-grade observations. The ratio of observations for Tracheophyta, Chordata, and Arthropoda in Russia is different compared to the global scale. There are almost an equal amount of observations in the global iNaturalist GBIF dataset for these groups. At the same time in Russia, vascular plants make up 2/3rds of the observations. That is due to the "Flora of Russia" project, which attracted many professional botanists both as observers and experts. Thanks to their activity, Russia has a high proportion of research-grade observations in iNaturalist, 78% versus 60% globally. Another consequence of wide participation by professional researchers is the high rate of species accumulation. For some taxonomic groups conspicuous species were already revealed. There are about 850 bird species in Russia of which 398 species were observed in 2018, and only 83 new species in 2019. Currently, the number of new species recorded over time is decreasing despite the increase in observers and overall user activity. Russian iNaturalist observers have shared a lot of archive photos (taken during past years). In 2018, it was nearly 1/4 of the total number of observations and about 3/4 of new species for the year, with similar trends observed during 2019. Usually archive photos are posted from December until April, but the 2020 pandemic lockdown spurred a new wave of archive photo mobilisation in April and May. There are many iNaturalist projects for protected areas in Russia: 27 for strict nature reserves and national parks, and about 300 for others. About 100,000 observations (7.5% of all Russian observations) from the umbrella project "Protected areas of Russia" represent >34% of the species diversity observed in Russia. For some regions, e.g., Novosibirsk, Nizhniy Novgorod and Vladimir Oblasts, almost all protected areas are covered by iNaturalist projects, and are often their only source of available biodiversity data. There are also other popular citizen science platforms developed by Russian researchers. The first one is the Russian birdwatching network RU-BIRDS.RU. The related GBIF dataset (Ukolov et al. 2019) is the third largest dataset for Russia (>370,000 species occurrences). Another Russian citizen science system is wildlifemonitoring.ru, which includes thematic resources for different taxonomic groups of vertebrates. This is the crowd-sourced web-GIS maintained by the Siberian Environmental Center NGO in Novosibirsk. It is noteworthy that iNaturalist activities in Russia are developed more as a social network than as a way to attract volunteers to participate in scientific research. Of 746 citations in the iNaturalist dataset, only 18 articles include co-authors from Russia. iNaturalist data are used for the management of regional red lists (in the Republic of Bashkortostan, Novosibirsk Oblast and others), and as an additional information source for regional inventories. RU-BIRDS data were used in the European Russia Breeding Bird Atlas and the new edition of the European Breeding Bird Atlas. In Russia, citizen science activities significantly contribute to filling gaps in the global biodiversity map. However, Russian iNaturalist observations available through GBIF originate from the USA. It is not ideal, because the iNaturalist GBIF dataset is growing rapidly, and in the future it will represent more than all other datasets for Russia combined. In our opinion, iNaturalist data should be repatriated during the process of publishing through GBIF, as it is implemented for the eBird dataset (Levatich and Ligocki 2020).


Author(s):  
Yvan Le Bras ◽  
Aurélie Delavaud ◽  
Dominique Pelletier ◽  
Jean-Baptiste Mihoub

Most biodiversity research aims at understanding the states and dynamics of biodiversity and ecosystems. To do so, biodiversity research increasingly relies on the use of digital products and services such as raw data archiving systems (e.g. structured databases or data repositories), ready-to-use datasets (e.g. cleaned and harmonized files with normalized measurements or computed trends) as well as associated analytical tools (e.g. model scripts in Github). Several world-wide initiatives facilitate the open access to biodiversity data, such as the Global Biodiversity Information Facility (GBIF) or GenBank, Predicts etc. Although these pave the way towards major advances in biodiversity research, they also typically deliver data products that are sometimes poorly informative as they fail to capture the genuine ecological information they intend to grasp. In other words, access to ready-to-use aggregated data products may sacrifice ecological relevance for data harmonization, resulting in over-simplified, ill-advised standard formats. This is singularly true when the main challenge is to match complementary data (large diversity of measured variables, integration of different levels of life organizations etc.) collected with different requirements and scattered in multiple databases. Improving access to raw data, and meaningful detailed metadata and analytical tools associated with standardized workflows is critical to maintain and maximize the generic relevance of ecological data. Consequently, advancing the design of digital products and services is essential for interoperability while also enhancing reproducibility and transparency in biodiversity research. To go further, a minimal common framework organizing biodiversity observation and data organization is needed. In this regard, the Essential Biodiversity Variable (EBV) concept might be a powerful way to boost progress toward this goal as well as to connect research communities worldwide. As a national Biodiversity Observation Network (BON) node, the French BON is currently embodied by a national research e-infrastructure called "Pôle national de données de biodiversité" (PNDB, formerly ECOSCOPE), aimed at simultaneously empowering the quality of scientific activities and promoting networking within the scientific community at a national level. Through the PNDB, the French BON is working on developing biodiversity data workflows oriented toward end services and products, both from and for a research perspective. More precisely, the two pillars of the PNDB are a metadata portal and a workflow-oriented web platform dedicated to the access of biodiversity data and associated analytical tools (Galaxy-E). After four years of experience, we are now going deeper into metadata specification, dataset descriptions and data structuring through the extensive use of Ecological Metadata Language (EML) as a pivot format. Moreover, we evaluate the relevance of existing tools such as Metacat/Morpho and DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) in order to ensure a link with other initiatives like Environmental Data Initiative, DataOne and Long-Term Ecological Research related observation networks. Regarding data analysis, an open-source Galaxy-E platform was launched in 2017 as part of a project targeting the design of a citizen science observation system in France (“65 Millions d'observateurs”). Here, we propose to showcase ongoing French activities towards global challenges related to biodiversity information and knowledge dissemination. We particularly emphasize our focus on embracing the FAIR (findable, accessible, interoperable and reusable) data principles Wilkinson et al. 2016 across the development of the French BON e-infrastructure and the promising links we anticipate for operationalizing EBVs. Using accessible and transparent analytical tools, we present the first online platform allowing the performance of advanced yet user-friendly analyses of biodiversity data in a reproducible and shareable way using data from various data sources, such as GBIF, Atlas of Living Australia (ALA), eBIRD, iNaturalist and environmental data such as climate data.


2021 ◽  
Vol 9 (2) ◽  
pp. 129-141 ◽  
Author(s):  
Lina Hedman ◽  
Maarten Van Ham

The literature on intergenerational contextual mobility has shown that neighbourhood status is partly ‘inherited’ from parents by children. Children who spend their childhood in deprived neighbourhoods are more likely to live in such neighbourhoods as adults. It has been suggested that such transmission of neighbourhood status is also relevant from a multiple generation perspective. To our knowledge, however, this has only been confirmed by simulations and not by empirical research. This study uses actual empirical data covering the entire Swedish population over a 25-year period, to investigate intergenerational similarities in neighbourhood status for three generations of Swedish women. The findings suggest that the neighbourhood environments of Swedish women are correlated with the neighbourhood statuses of their mothers and, to some extent, grandmothers. These results are robust over two different analytical strategies—comparing the neighbourhood status of the three generations at roughly similar ages and at the same point in time—and two different spatial scales. We argue that the finding of such effects in (relatively egalitarian) Sweden implies that similar, and possibly stronger, patterns are likely to exist in other countries as well.


Author(s):  
Gil Nelson ◽  
Deborah L Paul

Integrated Digitized Biocollections (iDigBio) is the United States’ (US) national resource and coordinating center for biodiversity specimen digitization and mobilization. It was established in 2011 through the US National Science Foundation’s (NSF) Advancing Digitization of Biodiversity Collections (ADBC) program, an initiative that grew from a working group of museum-based and other biocollections professionals working in concert with NSF to make collections' specimen data accessible for science, education, and public consumption. The working group, Network Integrated Biocollections Alliance (NIBA), released two reports (Beach et al. 2010, American Institute of Biological Sciences 2013) that provided the foundation for iDigBio and ADBC. iDigBio is restricted in focus to the ingestion of data generated by public, non-federal museum and academic collections. Its focus is on specimen-based (as opposed to observational) occurrence records. iDigBio currently serves about 118 million transcribed specimen-based records and 29 million specimen-based media records from approximately 1600 datasets. These digital objects have been contributed by about 700 collections representing nearly 400 institutions and is the most comprehensive biodiversity data aggregator in the US. Currently, iDigBio, DiSSCo (Distributed System of Scientific Collections), GBIF (Global Biodiversity Information Facility), and the Atlas of Living Australia (ALA) are collaborating on a global framework to harmonize technologies towards standardizing and synchronizing ingestion strategies, data models and standards, cyberinfrastructure, APIs (application programming interface), specimen record identifiers, etc. in service to a developing consolidated global data product that can provide a common source for the world’s digital biodiversity data. The collaboration strives to harness and combine the unique strengths of its partners in ways that ensure the individual needs of each partner’s constituencies are met, design pathways for accommodating existing and emerging aggregators, simultaneously strengthen and enhance access to the world’s biodiversity data, and underscore the scope and importance of worldwide biodiversity informatics activities. Collaborators will share technology strategies and outputs, align conceptual understandings, and establish and draw from an international knowledge base. These collaborators, along with Biodiversity Information Standards (TDWG), will join iDigBio and the Smithsonian National Museum of Natural History as they host Biodiversity 2020 in Washington, DC. Biodiversity 2020 will combine an international celebration of the worldwide progress made in biodiversity data accessibility in the 21st century with a biodiversity data conference that extends the life of Biodiversity Next. It will provide a venue for the GBIF governing board meeting, TDWG annual meeting, and the annual iDigBio Summit as well as three days of plenary and concurrent sessions focused on the present and future of biodiversity data generation, mobilization, and use.


1999 ◽  
Vol 3 (3) ◽  
pp. 260-262 ◽  
Author(s):  
Eduardo Marvez ◽  
Debra Houry ◽  
Steven Weiss ◽  
Juliette Saussy ◽  
Dawne Orgeron
Keyword(s):  

2010 ◽  
pp. 97-129 ◽  
Author(s):  
Drew M. Talley ◽  
Gary R. Huxel ◽  
Marcel Holyoak
Keyword(s):  

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