J Plant Ecol ›› 2021, Vol. 14 ›› Issue (5): 771-780.DOI: 10.1093/jpe/rtab030

• Research Articles • Previous Articles     Next Articles

The need for alternative plant species interaction models

Christian Damgaard1, *, and Jacob Weiner2   

  1. 1 Department of Bioscience, Aarhus University, Vejlsøvej 25, DK-8600 Silkeborg, Denmark, 2 Department of Plant and Environmental Sciences, University of Copenhagen, DK-1871 Frederiksberg, Denmark

    *Corresponding author. E-mail: cfd@bios.au.dk
  • Received:2020-11-16 Revised:2020-12-26 Accepted:2021-02-26 Online:2021-03-26 Published:2021-10-01



The limitations of classical Lotka–Volterra models for analyzing and interpreting competitive interactions among plant species have become increasingly clear in recent years. Three of the problems that have been identified are (i) the absence of frequency-dependence, which is important for long-term coexistence of species, (ii) the need to take unmeasured (often unmeasurable) variables influencing individual performance into account (e.g. spatial variation in soil nutrients or pathogens) and (iii) the need to separate measurement error from biological variation.


We modified the classical Lotka–Volterra competition models to address these limitations. We fitted eight alternative models to pin-point cover data on Festuca ovina and Agrostis capillaris over 3 years in an herbaceous plant community in Denmark. A Bayesian modeling framework was used to ascertain whether the model amendments improve the performance of the models and increase their ability to predict community dynamics and to test hypotheses.

Important Findings

Inclusion of frequency-dependence and measurement error, but not unmeasured variables, improved model performance greatly. Our results emphasize the importance of comparing alternative models in quantitative studies of plant community dynamics. Only by considering possible alternative models can we identify the forces driving community assembly and change, and improve our ability to predict the behavior of plant communities.

Key words: plant competition, plant–plant interaction, interspecific interaction model, frequency-dependence, unmeasured variables, measurement uncertainty, hierarchical modeling

近年来,经典的Lotka-Volterra模型在分析和解释植物物种间竞争性相互作用方面的局限性愈发凸显。目前已经明确的3个问题是:(1)缺乏频率依赖性,其对于物种的长期共存至关重要;(2)需要考虑影响个体表现的未测量(通常不可测量)的变量(例如,土壤养分或病原体的空间变化);以及(3)需要将测量误差与生物变异度分开。本文改进了经典的Lotka-Volterra竞争模型以期突破模型的局限。同时,我们将8个备选模型与丹麦草本植物群落中羊茅(Festuca ovina)和细弱剪股颖 (Agrostis capillaris) 3年以上的盖度数据拟合,应用贝叶斯建模框架来确定模型改进是否提高了模型的性能,并提高了其预测群落动态并因此检验假设的能力。研究结果表明,纳入频率依赖性和测量误差极大地改进了模型性能,但将可能的未测量变量考虑在内却未能改进其性能。我们的研究结果强调了在植物群落动态的定量研究中比较备选模型的重要性。只有考虑可能的备选模型,我们才能确定驱动群落构建和变化的因子,并提高我们预测植物群落行为的能力。

关键词: 植物竞争, 植物-植物相互作用, 种间相互作用模型, 频率依赖性, 未测量变量, 测量不确定性, 层次模型