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Spatial heterogeneity in species richness and species composition

Masae Shiyomi, Jun Chen, Taisuke Yasuda

Open publisher page 5 citations

Abstract

Abstract Visually detecting and measuring actual spatial heterogeneity is relatively easy using traits of grassland vegetation communities, e.g. ‘quantitative’ traits such as spatial heterogeneity in biomass, vegetation cover and frequency of occurrence for each species. In the present paper, we consider substantively ‘qualitative’ aspects of vegetation, such as species richness (number of species) and species composition (numerically expressed using the Bray–Curtis measure [S‐value]). We constructed two frequency distributions of number of species and S‐values based on observations of many small quadrats in two grassland systems. At the same time, we mathematically generated a hypothetical community in which all plant individuals of each species occupy arbitrary (random) positions in proportion to the abundance of each species in the surrounding area (referred to as the ‘null distribution’). This hypothetical community was expressed using two frequency distributions of number of species and S‐values per quadrat, and observed and null distributions of these variables were then compared. The difference between observed and null distributions was indicative of the level of spatial heterogeneity in terms of number of species and species composition of the grassland vegetation. We explain this concept using a simple artificial example and actual grassland vegetation data.

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What this paper is about

Abstract Visually detecting and measuring actual spatial heterogeneity is relatively easy using traits of grassland vegetation communities, e.g. ‘quantitative’ traits such as spatial heterogeneity in biomass, vegetation cover and frequency of occurrence for each species. In the present paper, we consider substantively ‘qualitative’ aspects of vegetation, such as species richness (number of species) and species composition (numerically expressed using the Bray–Curtis measure [S‐value]). We constructed two frequency distributions of number of species and S‐values based on observations of many small quadrats in two grassland systems. At the same time, we mathematically generated a hypothetical community in which all plant individuals of each species occupy arbitrary (random) positions in proportion to the abundance of each species in the surrounding area (referred to as the ‘null distribution’). This hypothetical community was expressed using two frequency distributions of number of species and S‐values per quadrat, and observed and null distributions of these variables were then compared. The difference between observed and null distributions was indicative of the level of spatial heterogeneity in terms of number of species and species composition of the grassland vegetation. We explain this concept using a simple artificial example and actual grassland vegetation data.

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Available abstract

Abstract Visually detecting and measuring actual spatial heterogeneity is relatively easy using traits of grassland vegetation communities, e.g. ‘quantitative’ traits such as spatial heterogeneity in biomass, vegetation cover and frequency of occurrence for each species. In the present paper, we consider substantively ‘qualitative’ aspects of vegetation, such as species richness (number of species) and species composition (numerically expressed using the Bray–Curtis measure [S‐value]). We constructed two frequency distributions of number of species and S‐values based on observations of many small quadrats in two grassland systems. At the same time, we mathematically generated a hypothetical community in which all plant individuals of each species occupy arbitrary (random) positions in proportion to the abundance of each species in the surrounding area (referred to as the ‘null distribution’). This hypothetical community was expressed using two frequency distributions of number of species and S‐values per quadrat, and observed and null distributions of these variables were then compared. The difference between observed and null distributions was indicative of the level of spatial heterogeneity in terms of number of species and species composition of the grassland vegetation. We explain this concept using a simple artificial example and actual grassland vegetation data.

Key concepts: Quadrat, Species richness, Grassland, Abundance (ecology), Null model, Vegetation (pathology), Ecology, Spatial heterogeneity

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