Literature DB >> 33290672

What processes must we understand to forecast regional-scale population dynamics?

Jesse R Lasky1, Mevin B Hooten2,3,4, Peter B Adler5.   

Abstract

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.

Keywords:  climate change; local adaptation; macroecology; range dynamics

Year:  2020        PMID: 33290672      PMCID: PMC7739927          DOI: 10.1098/rspb.2020.2219

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  81 in total

1.  Ecological forecasts: an emerging imperative.

Authors:  J S Clark; S R Carpenter; M Barber; S Collins; A Dobson; J A Foley; D M Lodge; M Pascual; R Pielke; W Pizer; C Pringle; W V Reid; K A Rose; O Sala; W H Schlesinger; D H Wall; D Wear
Journal:  Science       Date:  2001-07-27       Impact factor: 47.728

Review 2.  Genome-wide association studies for common diseases and complex traits.

Authors:  Joel N Hirschhorn; Mark J Daly
Journal:  Nat Rev Genet       Date:  2005-02       Impact factor: 53.242

3.  Local adaptation and the evolution of phenotypic plasticity in Trinidadian guppies (Poecilia reticulata).

Authors:  Julián Torres-Dowdall; Corey A Handelsman; David N Reznick; Cameron K Ghalambor
Journal:  Evolution       Date:  2012-06-11       Impact factor: 3.694

Review 4.  Determining the evolutionary forces shaping G × E.

Authors:  Emily B Josephs
Journal:  New Phytol       Date:  2018-03-25       Impact factor: 10.151

Review 5.  What genomic data can reveal about eco-evolutionary dynamics.

Authors:  Seth M Rudman; Matthew A Barbour; Katalin Csilléry; Phillip Gienapp; Frederic Guillaume; Nelson G Hairston; Andrew P Hendry; Jesse R Lasky; Marina Rafajlović; Katja Räsänen; Paul S Schmidt; Ole Seehausen; Nina O Therkildsen; Martin M Turcotte; Jonathan M Levine
Journal:  Nat Ecol Evol       Date:  2017-11-20       Impact factor: 15.460

6.  A model-based approach for analysis of spatial structure in genetic data.

Authors:  Wen-Yun Yang; John Novembre; Eleazar Eskin; Eran Halperin
Journal:  Nat Genet       Date:  2012-05-20       Impact factor: 38.330

Review 7.  Predicting changes in the distribution and abundance of species under environmental change.

Authors:  Johan Ehrlén; William F Morris
Journal:  Ecol Lett       Date:  2015-01-22       Impact factor: 9.492

8.  Natural variation in abiotic stress responsive gene expression and local adaptation to climate in Arabidopsis thaliana.

Authors:  Jesse R Lasky; David L Des Marais; David B Lowry; Inna Povolotskaya; John K McKay; James H Richards; Timothy H Keitt; Thomas E Juenger
Journal:  Mol Biol Evol       Date:  2014-05-21       Impact factor: 16.240

9.  On the predictability of infectious disease outbreaks.

Authors:  Samuel V Scarpino; Giovanni Petri
Journal:  Nat Commun       Date:  2019-02-22       Impact factor: 14.919

10.  Eco-evolutionary community turnover following environmental change.

Authors:  Jesse R Lasky
Journal:  Evol Appl       Date:  2019-02-20       Impact factor: 5.183

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  1 in total

Review 1.  Genomic reaction norms inform predictions of plastic and adaptive responses to climate change.

Authors:  Rebekah A Oomen; Jeffrey A Hutchings
Journal:  J Anim Ecol       Date:  2022-05-18       Impact factor: 5.606

  1 in total

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