Functional diversity metrics using kernel density n-dimensional hypervolumes

Show full item record



Permalink

http://hdl.handle.net/10138/325969

Citation

Mammola , S & Cardoso , P 2020 , ' Functional diversity metrics using kernel density n-dimensional hypervolumes ' , Methods in Ecology and Evolution , vol. 11 , no. 8 , pp. 986-995 . https://doi.org/10.1111/2041-210X.13424

Title: Functional diversity metrics using kernel density n-dimensional hypervolumes
Author: Mammola, Stefano; Cardoso, Pedro
Contributor: University of Helsinki, Finnish Museum of Natural History
University of Helsinki, Zoology
Date: 2020-08
Language: eng
Number of pages: 10
Belongs to series: Methods in Ecology and Evolution
ISSN: 2041-210X
URI: http://hdl.handle.net/10138/325969
Abstract: The use ofn-dimensional hypervolumes in trait-based ecology is rapidly increasing. By representing the functional space of a species or community as a Hutchinsonian niche, the abstract Euclidean space defined by a set of independent axes corresponding to individuals or species traits, these multidimensional techniques show great potential for the advance of functional ecology theory. In the panorama of existing methods for delineating multidimensional spaces, therpackagehypervolume(Global Ecology and Biogeography, 23, 2014, 595-609) is currently the most used. However, functions for calculating the standard set of functional diversity (FD) indices-richness, divergence and regularity-have not been developed within thehypervolumeframework yet. This gap is delaying its full exploitation in functional ecology, meanwhile preventing the possibility to compare its performance with that of other methods. We develop a set of functions to calculate FD indices based onn-dimensional hypervolumes, including alpha (richness), beta (and respective components), dispersion, evenness, contribution and originality. Altogether, these indices provide a coherent framework to explore the primary mathematical components of FD within a multidimensional setting. These new functions can work either with hypervolume objects or with raw data (species presence or abundance and their traits) as input data, and are versatile in terms of input parameters and options. These functions are implemented withinbat(Biodiversity Assessment Tools), anrpackage for biodiversity assessments. As a coherent corpus of functional indices based on a common algorithm, it opens the possibility to fully explore the strengths of the Hutchinsonian niche concept in community ecology research.
Subject: alpha diversity
beta diversity
functional divergence
functional evenness
functional richness
fundamental niche
Hutchinsonian hypervolume
traits
RICHNESS
ECOLOGY
NICHE
URBANIZATION
BIODIVERSITY
REDUNDANCY
SIMILARITY
FRAMEWORK
INDEXES
RARITY
1181 Ecology, evolutionary biology
Rights:


Files in this item

Total number of downloads: Loading...

Files Size Format View
2041_210X.13424.pdf 1.857Mb PDF View/Open

This item appears in the following Collection(s)

Show full item record