Transferring biodiversity models for conservation : opportunities and challenges

Sequeira, AMM, Bouchet, PJ, Yates, KL ORCID: 0000-0001-8429-2941, Mengersen, K and Caley, MJ 2018, 'Transferring biodiversity models for conservation : opportunities and challenges' , Methods in Ecology and Evolution, 9 (5) , pp. 1250-1264.

[img] PDF - Accepted Version
Restricted to Repository staff only until 6 March 2019.

Download (948kB) | Request a copy
[img] PDF - Published Version
Restricted to Repository staff only

Download (1MB) | Request a copy

Abstract

  1. After decades of extensive surveying, knowledge of the global distribution of species still remains inadequate for many purposes. In the short to medium term, such knowledge is unlikely to improve greatly given the often prohibitive costs of surveying and the typically limited resources available.
  2. By forecasting biodiversity patterns in time and space, predictive models can help fill critical knowledge gaps and prioritise research to support better conservation and management.
  3. The ability of a model to predict biodiversity metrics in novel environments is termed “transferability,” and models with high transferability will be the most useful in this context.
  4. Despite their potentially broad utility, little guidance exists on what confers high transferability to biodiversity models.
  5. We synthesise recent advances in biodiversity model transfers to facilitate increased understanding of what underpins successful model transferability, demonstrating that a consistent approach has so far been lacking but is essential for achieving high levels of repeatability, transparency and accountability of model transfers.
  6. We provide a set of guidelines to support efficient learning and the improvement of model transferability.

Item Type: Article
Schools: Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title: Methods in Ecology and Evolution
Publisher: Wiley
ISSN: 2041-210X
Related URLs:
Depositing User: Dr K Yates
Date Deposited: 06 Jun 2018 08:47
Last Modified: 22 Oct 2018 05:36
URI: http://usir.salford.ac.uk/id/eprint/47252

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)

Downloads

Downloads per month over past year