A unified analysis of niche overlap incorporating data of different types

Abstract

Summary1. Competition theory predicts that community structure may be shaped by resource partitioning between co-occurring species. As such, quantifying the degree of resource partitioning (i.e., niche overlap) is a key component of studies examining community structure and species coexistence. 2. For many organisms, multiple resource axes quantify niche space. Each axis may be described by a different type of data (e.g. categorical, continuous, count or binary data, as well as electivity scores), with different data types requiring different statistical treatments. Therefore, incorporating multiple axes into a single measure of niche space is problematic. 3. Here, we propose general methods for combining multiple niche axes, each characterized by different data types, within a unified analysis of niche overlap. Using appropriate transformations and probability models, we show that each data type can give rise to directly comparable measures of niche overlap, with the overlap statistic between two species defined as the overlapping area between the distributions for each species. 4. Measurements derived from different types of data can be combined into a single unified analysis of niche overlap by averaging over multiple axes. 5. We then describe null model permutation tests that assess statistical differences in niche overlap, which can address questions commonly posed by population ecologists (e.g. do two species occupy different niche space?) and community ecologists (e.g. are multiple species evenly distributed across niche space?). 6. To illustrate the use of these newly devised indices, we use an example from reef fishes that combines ratio, categorical and electivity data, and an example from alpine plants that combines continuous and ratio data. 7. The methods described in this article are relevant to a wide variety of ecological projects, including the investigation of invasive species, relative abundance distributions, global change, species coexistence and evolutionary diversification.

Assessing phytoplankton realized niches using a French national phytoplankton monitoring network

“…a total of 595 combinations. As D may represent a measure of association between a pair of taxa, (1 À D) may be considered a distance measure for each pair of taxonomic units (Geange et al, 2011). These results were used to build an n  n matrix, where n corresponds to the number of taxonomic units referenced in this study.…”

“…Different types of data can be used for niche analyses (Mouillot et al, 2005;Geange et al, 2011;Irwin et al, 2012). For phytoplankton species, niche characteristics have already been studied using abundance-oriented methods (Heino and Soininen, 2006;Gebühr et al, 2009) among others.…”

“…Niche position and niche breadth have been applied, for example, to separate niches of invasive plant species based on climate, landscape and human-pressure factors . The multidimensional space shared by two or more species called niche overlap (Mouillot et al, 2005;Geange et al, 2011) has been widely used to investigate resource partitioning (Schoener, 1968) and, more recently, to compare the space occupied by native and nonnative populations of invasive species (Broennimann et al, 2007). A range of methods has already been used to determine species niches and to assess niche differences.…”

Determining t in t-closeness using Multiple Sensitive Attributes

“…From these two inferences it can be saidthat if it is possible to capture the diversity oftwo or more sensitive attribute by the diversity of their equivalence classes andthen it can be used to get a common diversity measure by comparing the Niche Overlap [20]between the two distributions.…”

“…The area of overlap calculated in terms of Niche Overlap [20] which gives the area of overlap between two discrete distributions between the attributes provided for any SA S i where Kgives all possible discrete values S i takes. Since all the SA distributions are converted to SND the criteria is met.…”