Literature DB >> 28405770

Comparing mechanistic and empirical approaches to modeling the thermal niche of almond.

Lauren E Parker1, John T Abatzoglou2.   

Abstract

Delineating locations that are thermally viable for cultivating high-value crops can help to guide land use planning, agronomics, and water management. Three modeling approaches were used to identify the potential distribution and key thermal constraints on on almond cultivation across the southwestern United States (US), including two empirical species distribution models (SDMs)-one using commonly used bioclimatic variables (traditional SDM) and the other using more physiologically relevant climate variables (nontraditional SDM)-and a mechanistic model (MM) developed using published thermal limitations from field studies. While models showed comparable results over the majority of the domain, including over existing croplands with high almond density, the MM suggested the greatest potential for the geographic expansion of almond cultivation, with frost susceptibility and insufficient heat accumulation being the primary thermal constraints in the southwestern US. The traditional SDM over-predicted almond suitability in locations shown by the MM to be limited by frost, whereas the nontraditional SDM showed greater agreement with the MM in these locations, indicating that incorporating physiologically relevant variables in SDMs can improve predictions. Finally, opportunities for geographic expansion of almond cultivation under current climatic conditions in the region may be limited, suggesting that increasing production may rely on agronomical advances and densifying current almond plantations in existing locations.

Entities:  

Keywords:  Agroclimatology; Almond; Phenology; Species distribution modeling

Mesh:

Year:  2017        PMID: 28405770     DOI: 10.1007/s00484-017-1338-9

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  13 in total

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3.  Prioritizing climate change adaptation needs for food security in 2030.

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Review 4.  Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation.

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Review 5.  Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges.

Authors:  Michael Kearney; Warren Porter
Journal:  Ecol Lett       Date:  2009-04       Impact factor: 9.492

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Authors:  Luciana L Porfirio; Rebecca M B Harris; Edward C Lefroy; Sonia Hugh; Susan F Gould; Greg Lee; Nathaniel L Bindoff; Brendan Mackey
Journal:  PLoS One       Date:  2014-11-24       Impact factor: 3.240

7.  Climate-driven spatial mismatches between British orchards and their pollinators: increased risks of pollination deficits.

Authors:  Chiara Polce; Michael P Garratt; Mette Termansen; Julian Ramirez-Villegas; Andrew J Challinor; Martin G Lappage; Nigel D Boatman; Andrew Crowe; Ayenew Melese Endalew; Simon G Potts; Kate E Somerwill; Jacobus C Biesmeijer
Journal:  Glob Chang Biol       Date:  2014-05-02       Impact factor: 10.863

8.  Climatic changes lead to declining winter chill for fruit and nut trees in California during 1950-2099.

Authors:  Eike Luedeling; Minghua Zhang; Evan H Girvetz
Journal:  PLoS One       Date:  2009-07-16       Impact factor: 3.240

9.  The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

Authors:  Mindy M Syfert; Matthew J Smith; David A Coomes
Journal:  PLoS One       Date:  2013-02-14       Impact factor: 3.240

10.  Appetitive, dietary and health effects of almonds consumed with meals or as snacks: a randomized, controlled trial.

Authors:  S Y Tan; R D Mattes
Journal:  Eur J Clin Nutr       Date:  2013-10-02       Impact factor: 4.016

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