From MFKP_wiki

Jump to: navigation, search

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

Heather E. Glon, Benjamin W. Heumann, J. Richard Carter, Jessica M. Bartek, Anna K. Monfils

Specimen data from small collections compliment those in large collections.
Small collections contribute to a more robust definition of a species habitat.
Species distribution models are impacted when small collections data are included.

Abstract. 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.

Ecological Informatics, Vol. 42 (November 2017), pp. 67-78, 
Key: INRMM:14599397



Article-Level Metrics (Altmetrics)
Digital Object Identifier

Available versions (may include free-access full text)

DOI, Pubget, PubMed (Search)

Versions of the publication are also available in Google Scholar.
Google Scholar code: GScluster:839057210331976043

Works citing this publication (including grey literature)

An updated list of who cited this publication is available in Google Scholar.
Google Scholar code: GScites:839057210331976043

Further search for available versions

Search in ResearchGate (or try with a fuzzier search in ResearchGate)
Search in Mendeley (or try with a fuzzier search in Mendeley)

Publication metadata

Bibtex, RIS, RSS/XML feed, Json, Dublin Core
Metadata search: CrossRef DOI, DataCite DOI

Digital preservation of this INRMM-MiD record

Internet Archive

Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
Search only within the INRMM-MiD publication records:
Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.