How geographic productivity patterns affect food-web evolution

被引:3
|
作者
Wickman, Jonas [1 ]
Dieckmann, Ulf [2 ,3 ]
Hui, Cang [4 ,5 ]
Braennstroem, Ake [1 ,2 ]
机构
[1] Umea Univ, Dept Math & Math Stat, Integrated Sci Lab, SE-90187 Umea, Sweden
[2] Int Inst Appl Syst Anal IIASA, Evolut & Ecol Program, Schlosspl 1, A-2361 Laxenburg, Austria
[3] Grad Univ Adv Studies Sokendai, Dept Evolutionary Studies Biosyst, Hayama, Kanagawa 2400193, Japan
[4] Stellenbosch Univ, Ctr Invas Biol, Dept Math Sci, ZA-7602 Matieland, South Africa
[5] African Inst Math Sci, Math & Phys Biosci, ZA-7945 Cape Town, South Africa
基金
新加坡国家研究基金会; 瑞典研究理事会;
关键词
Spatial models; Adaptive dynamics; Productivity-diversity relationship; LOCALLY WEIGHTED REGRESSION; COMPETITIVE-EXCLUSION; SPATIAL DYNAMICS; SPECIES-RICHNESS; BIODIVERSITY; DIVERSITY; EMERGENCE; ECOLOGY; MAINTENANCE; COEXISTENCE;
D O I
10.1016/j.jtbi.2020.110374
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
It is well recognized that spatial heterogeneity and overall productivity have important consequences for the diversity and community structure of food webs. Yet, few, if any, studies have considered the effects of heterogeneous spatial distributions of primary production. Here, we theoretically investigate how the variance and autocorrelation length of primary production affect properties of evolved food webs consisting of one autotroph and several heterotrophs. We report the following findings. (1) Diversity increases with landscape variance and is unimodal in autocorrelation length. (2) Trophic level increases with landscape variance and is unimodal in autocorrelation length. (3) The extent to which the spatial distribution of heterotrophs differ from that of the autotroph increases with landscape variance and decreases with autocorrelation length. (4) Components of initial disruptive selection experienced by the ancestral heterotroph predict properties of the final evolved communities. Prior to our study reported here, several authors had hypothesized that diversity increases with the landscape variance of productivity. Our results support their hypothesis and contribute new facets by providing quantitative predictions that also account for autocorrelation length and additional properties of the evolved communities. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:12
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