Literature DB >> 29923606

Major challenges for correlational ecological niche model projections to future climate conditions.

A Townsend Peterson1, Marlon E Cobos1, Daniel Jiménez-García2.   

Abstract

Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions.
© 2018 New York Academy of Sciences.

Keywords:  biodiversity; climate change; ecological niche model; niche truncation; uncertainty

Mesh:

Year:  2018        PMID: 29923606     DOI: 10.1111/nyas.13873

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  14 in total

1.  Temperature, topography, soil characteristics, and NDVI drive habitat preferences of a shade-tolerant invasive grass.

Authors:  Anna K M Bowen; Martin H H Stevens
Journal:  Ecol Evol       Date:  2020-09-23       Impact factor: 2.912

2.  Modeling impacts of climate change on the potential habitat of an endangered Brazilian endemic coral: Discussion about deep sea refugia.

Authors:  Umberto Diego Rodrigues de Oliveira; Paula Braga Gomes; Ralf Tarciso Silva Cordeiro; Gislaine Vanessa de Lima; Carlos Daniel Pérez
Journal:  PLoS One       Date:  2019-05-21       Impact factor: 3.240

3.  kuenm: an R package for detailed development of ecological niche models using Maxent.

Authors:  Marlon E Cobos; A Townsend Peterson; Narayani Barve; Luis Osorio-Olvera
Journal:  PeerJ       Date:  2019-02-06       Impact factor: 2.984

4.  Potential Spatial Distribution of the Newly Introduced Long-horned Tick, Haemaphysalis longicornis in North America.

Authors:  R K Raghavan; S C Barker; M E Cobos; D Barker; E J M Teo; D H Foley; R Nakao; K Lawrence; A C G Heath; A T Peterson
Journal:  Sci Rep       Date:  2019-01-24       Impact factor: 4.379

5.  Assessing the exposure of forest habitat types to projected climate change-Implications for Bavarian protected areas.

Authors:  Claudia Steinacker; Carl Beierkuhnlein; Anja Jaeschke
Journal:  Ecol Evol       Date:  2019-11-28       Impact factor: 2.912

6.  Effects of climate change and land cover on the distributions of a critical tree family in the Philippines.

Authors:  Sean E H Pang; Jose Don T De Alban; Edward L Webb
Journal:  Sci Rep       Date:  2021-01-11       Impact factor: 4.379

7.  Vulnerability to climate change of species in protected areas in Thailand.

Authors:  Nirunrut Pomoim; Alice C Hughes; Yongyut Trisurat; Richard T Corlett
Journal:  Sci Rep       Date:  2022-04-05       Impact factor: 4.379

8.  Impacts of climate change on Capparis spinosa L. based on ecological niche modeling.

Authors:  Uzma Ashraf; Muhammad N Chaudhry; Sajid R Ahmad; Irfan Ashraf; Muhammad Arslan; Hassaan Noor; Mobeen Jabbar
Journal:  PeerJ       Date:  2018-10-16       Impact factor: 2.984

9.  Predicting the potential distribution of Amblyomma americanum (Acari: Ixodidae) infestation in New Zealand, using maximum entropy-based ecological niche modelling.

Authors:  R K Raghavan; A C G Heath; K E Lawrence; R R Ganta; A T Peterson; W E Pomroy
Journal:  Exp Appl Acarol       Date:  2020-01-21       Impact factor: 2.132

10.  Automatic variable selection in ecological niche modeling: A case study using Cassin's Sparrow (Peucaea cassinii).

Authors:  John L Schnase; Mark L Carroll
Journal:  PLoS One       Date:  2022-01-21       Impact factor: 3.240

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