Volume 28, Issue 12
MACROECOLOGICAL METHODS

Species' range model metadata standards: RMMS

Cory Merow

Corresponding Author

E-mail address: cory.merow@gmail.com

Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut

Ecology and Evolutionary Biology Department, Yale University, New Haven, Connecticut

Correspondence

Cory Merow, Ecology and Evolutionary Biology, University of Connecticut, 75 N. Eagleville Road, Unit 3043 Storrs, CT 06269‐3043.

Email: cory.merow@gmail.com

Search for more papers by this author
Brian S. Maitner

Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona

Search for more papers by this author
Hannah L. Owens

Florida Museum of Natural History, University of Florida, Gainesville, Florida

Center for Macroecology, Evolution, and Climate, University of Copenhagen, Copenhagen, Denmark

Search for more papers by this author
Jamie M. Kass

Department of Biology, City College of New York (CUNY), New York, New York

Program in Biology, The Graduate Center, CUNY, New York, New York

Search for more papers by this author
Brian J. Enquist

Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona

Search for more papers by this author
Walter Jetz

Ecology and Evolutionary Biology Department, Yale University, New Haven, Connecticut

Search for more papers by this author
Rob Guralnick

Florida Museum of Natural History, University of Florida, Gainesville, Florida

Search for more papers by this author
First published: 28 August 2019
Citations: 2

Abstract

Aim

The geographic range and ecological niche of species are widely used concepts in ecology, evolution and conservation and many modelling approaches have been developed to quantify each. Niche and distribution modelling methods require a litany of design choices; differences among subdisciplines have created communication barriers that increase isolation of scientific advances. As a result, understanding and reproducing the work of others is difficult, if not impossible. It is often challenging to evaluate whether a model has been built appropriately for its intended application or subsequent reuse. Here, we propose a standardized model metadata framework that enables researchers to understand and evaluate modelling decisions while making models fully citable and reproducible. Such reproducibility is critical for both scientific and policy reports, while international standardization enables better comparison between different scenarios and research groups.

Innovation

Range modelling metadata (RMMS) address three challenges: they (a) are designed for convenience to encourage use, (b) accommodate a wide variety of applications, and (c) are extensible to allow the research community to steer them as needed. RMMS are based on a metadata dictionary that specifies a hierarchical structure to catalogue different aspects of the range modelling process. The dictionary balances a constrained, minimalist vocabulary to improve standardization with flexibility for users to modify and extend. To facilitate use, we have developed an R package, rangeModelMetaData, to build templates, automatically fill values from common modelling objects, check for inconsistencies with standards, and suggest values.

Main conclusions

Range Modelling Metadata tools foster cross‐disciplinary advances in biogeography, conservation and allied disciplines by improving evaluation, model sharing, model searching, comparisons and reproducibility among studies. Our initially proposed standards here are designed to be modified and extended to evolve with research trends and needs.

DATA AVAILABILITY STATEMENT

All code is maintained on Github (https://github.com/cmerow/rangeModelMetadata) and also served on CRAN (http://cran.us.r-project.org/).

Number of times cited according to CrossRef: 2

  • A standard protocol for reporting species distribution models, Ecography, 10.1111/ecog.04960, 43, 9, (1261-1277), (2020).
  • A checklist for maximizing reproducibility of ecological niche models, Nature Ecology & Evolution, 10.1038/s41559-019-0972-5, (2019).

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.