J Plant Ecol ›› 2020, Vol. 13 ›› Issue (4): 431-441.DOI: 10.1093/jpe/rtaa031

• Research Articles • Previous Articles     Next Articles

Variation in the methods leads to variation in the interpretation of biodiversity–ecosystem multifunctionality relationships

Xin Jing1,2,8, *, Case M. Prager1,3, Aimée T. Classen1,2 , Fernando T. Maestre4,5 , Jin-Sheng He6 and Nathan J. Sanders2,3,7   

  1. 1 Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT 05405, USA, 2 Gund Institute for Environment, University of Vermont, Burlington, VT 05405, USA, 3 Center for Macroecology, Evolution, and Climate, Natural History Museum of Denmark, Copenhagen, Denmark, 4 Departamento de Biología, Geología, Física y Química Inorgánica, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad Rey Juan Carlos, Móstoles 28933, Spain, 5 Departamento de Ecología and Instituto Multidisciplinar para el Estudio del Medio “Ramon Margalef”, Universidad de Alicante, Alicante, Spain, 6 Department of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, China, 7 Environmental Program, Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT 05405, USA, 8 Present address: Department of Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E, 3001 Leuven, Belgium

    *Corresponding author. E-mail: xin.jing@kuleuven.be
  • Received:2019-11-01 Revised:2020-05-25 Accepted:2020-06-08 Online:2020-06-11 Published:2020-08-01

Abstract:

Aims

Biodiversity is often positively related to the capacity of an ecosystem to provide multiple functions simultaneously (i.e. multifunctionality). However, there is some controversy over whether biodiversity–multifunctionality relationships depend on the number of functions considered. Particularly, investigators have documented contrasting findings that the effects of biodiversity on ecosystem multifunctionality do not change or increase with the number of ecosystem functions. Here, we provide some clarity on this issue by examining the statistical underpinnings of different multifunctionality metrics.

Methods

We used simulations and data from a variety of empirical studies conducted across spatial scales (from local to global) and biomes (temperate and alpine grasslands, forests and drylands). We revisited three methods to quantify multifunctionality including the averaging approach, summing approach and threshold-based approach.

Important Findings

Biodiversity–multifunctionality relationships either did not change or increased as more functions were considered. These results were best explained by the statistical underpinnings of the averaging and summing multifunctionality metrics. Specifically, by averaging the individual ecosystem functions, the biodiversity–multifunctionality relationships equal the population mean of biodiversity-single function relationships, and thus will not change with the number of functions. Likewise, by summing the individual ecosystem functions, the strength of biodiversity–multifunctionality relationships increases as the number of functions increased. We proposed a scaling standardization method by converting the averaging or summing metrics into a scaling metric, which would make comparisons among different biodiversity studies. In addition, we showed that the range-relevant standardization can be applied to the threshold-based approach by solving for the mathematical artefact of the approach (i.e. the effects of biodiversity may artificially increase with the number of functions considered). Our study highlights different approaches yield different results and that it is essential to develop an understanding of the statistical underpinnings of different approaches. The standardization methods provide a prospective way of comparing biodiversity–multifunctionality relationships across studies.

Key words: averaging approach, biodiversity, ecosystem multifunctionality, multiple threshold approach, plant species richness, spatial scale

摘要:

生物多样性常常和生态系统多功能性(生态系统同时提供多个生态系统功能的能力)正相关。然而,生物多样性与生态系统多功能性的关系是否依赖于生态系统功能的数目有诸多争议。其中,生物多样性对生态系统多功能性的影响或许不随生态系统功能数目的变化而变化,或者随生态系统功能数目的增多而增强。我们期望通过研究不同生态系统多功能性指数的统计原理来解决这些争议。 我们使用了模型模拟和一系列来自不同空间尺度(从局域到全球)和不同生物群系(温带和高寒草地、森林和干旱地)的经验数据。我们回顾了量化生态系统多功能性的三种方法,包括平均值法、加和法和阈值法。我们发现随着生态系统功能数目的增加,生物多样性与生态系统多功能性的关系要么不变,要么增强。这些结果可由平均和加和的多功能性指数的统计原理来解释。具体来讲,当利用生态系统功能的平均值计算多功能性指数时,由于多样性对多功能性的效应等于多样性对单个生态系统功能效应的平均值,所以不会随生态系统功能数目的变化而变化。同样的道理,当利用单个生态系统的加和值计算多功能性指数时,多样性的效应会随着生态系统功能数目的增加而增强。我们提出了一个改进的多功能性指数,将平均或加和多功能性指数转化为标准化的多功能性指数, 以便于对不同研究的结果进行比较。此外,我们提出了基于变量数值范围的标准化方法来解决阈值法的数学假象问题(多样性效应随生态系统功能数目的增加而增强)。我们的研究结果表明,量化多功能性指数的方法不同,结果也不同。因此,有必要加深对不同方法数理基础的理解。而标准化的多功能性指数为比较不同研究中的生物多样性与生态系统多功能性的关系提供了有效的方法。

关键词: 平均值法, 生物多样性, 生态系统多功能性, 多阈值法, 植物物种丰富度, 空间尺度