Abstract
Multidimensional data are integral to many community-ecological studies and come in various forms, such as stable isotopes, compound specific analyses (e.g., amino acids and fatty acids), and both biodiversity and life history traits. Scientists employing such data often lack standardized metrics to evaluate communities in niche space where more than 2 dimensions are involved. To alleviate this problem, we developed a graphing and analytical approach for use with more than two variables, based on previously established stable isotope bi-plot metrics. We introduce here our community metrics as R scripts. By extending the original metrics to multiple dimensions, we created n-dimensional plots and metrics to characterize any set of quantitative measurements of a community. We demonstrate the utility of these metrics using stable isotope data; however, the approaches are applicable to many types of data. The resulting metrics provide more and better information compared to traditional analytic frameworks. The approach can be applied in many branches of community ecology, and it offers accessible metrics to quantitatively analyze the structure of communities across ecosystems and through time.
Highlights
The niche concept is a central organizing aspect of modern ecology and has been defined in many ways throughout the field’s history[1,2,3,4,5,6]
Metric values first offered by Layman et al.[17] included: (1) ranges for each variable considered; (2) mean distance to the centroid of points in 2-dimensional space (CD), which acts as a measure of species spread; (3) mean nearest neighbor distance in 2-dimensional space (NDD), functioning as a measure of density of species packing; (4) standard deviation of nearest neighbor distance (SDNND), measuring evenness of species packing in 2-dimensional space; and (5) total convex hull area, acting as a measure of the total amount of niche space occupied by the community
We use stable isotope data because: (a) this method is employed widely to assess the structure and dynamics of food webs; (b) such analyses often use two-dimensional Layman metrics; and (c) we believe that many of these bulk-tissue and amino acid isotope analyses as well as fatty-acid studies would benefit from multivariate analyses of three or more dimensions
Summary
The niche concept is a central organizing aspect of modern ecology and has been defined in many ways throughout the field’s history[1,2,3,4,5,6]. One of the most commonly used isotopic niche methods was developed by Layman et al.[17,18] It has proven useful in measuring dispersion of carbon (δ13C) and nitrogen (δ15N) isotope ratios in bivariate space The δ18O and δ2H values of groundwater and precipitation vary at multiple spatial scales, allowing researchers to decipher patterns across small-scale environmental gradients[27,28,29,30] or decode large-scale dietary patterns across geographic regions[31,32,33] These elemental tracers are most frequently plotted and analyzed in a bivariate approach. We offer meaningful metrics that can accommodate more axes and allow researchers to explore a greater number of niche dimensions simultaneously
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