Niche Overlap Index Function
Niche overlap refers to the extent to which different species use the same resources or occupy similar ecological niches. High niche overlap might indicate intense competition, whereas low overlap suggests niche differentiation, allowing species to coexist by minimizing direct competition.
To capture the changes in density-independent abiotic response, also known as niche breadth, this implementation uses Pianka's Niche Overlap Index, as suggested by Pianka (1973). The summary statistics of this index include the mean, maximum, and minimum values across all species pairs, providing a comprehensive understanding of niche sharing within the community.
Functionality Overview
The Niche Overlap Index functions in MetaCommunityMetrics provide a robust framework for calculating niche overlap based on species abundance or presence-absence data. These functions allow you to evaluate how species share ecological space within a metacommunity, offering valuable insights into community dynamics and species interactions.
The Function
MetaCommunityMetrics.niche_overlap — Functionniche_overlap(abundance::AbstractVector, species::AbstractVector, site::AbstractVector, time::AbstractVector) -> DataFrameCalculates the overall mean, maximum, and minimum values of the niche overlap index from all species pairs in the provided data.
Arguments
abundance::AbstractVector: Vector representing the abundance of species.species::AbstractVector: Vector representing species names or IDs.site::AbstractVector: Vector representing site names or IDs.time::AbstractVector: Vector representing sampling dates.
Description
The niche overlap index is calculated based on the method suggested by Pianka (1973), with the assumption that the proportional use of resources by a species at a specific site and time is equivalent to its relative abundance at that location and time period across all sampled sites and times
Returns
DataFrame: A DataFrame containing the overall mean, maximum, and minimum values of the niche overlap index from all species pairs.
Example
julia> using MetaCommunityMetrics
julia> df = load_sample_data()
53352×12 DataFrame
Row │ Year Month Day Sampling_date_order plot Species Abundance Presence Latitude Longitude normalized_temperature normalized_precipitation
│ Int64 Int64 Int64 Int64 Int64 String3 Int64 Int64 Float64 Float64 Float64 Float64
───────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ 2010 1 16 1 1 BA 0 0 35.0 -110.0 0.829467 -1.4024
2 │ 2010 1 16 1 2 BA 0 0 35.0 -109.5 -1.12294 -0.0519895
3 │ 2010 1 16 1 4 BA 0 0 35.0 -108.5 -0.409808 -0.803663
4 │ 2010 1 16 1 8 BA 0 0 35.5 -109.5 -1.35913 -0.646369
5 │ 2010 1 16 1 9 BA 0 0 35.5 -109.0 0.0822 1.09485
⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
53348 │ 2023 3 21 117 9 SH 0 0 35.5 -109.0 -0.571565 -0.836345
53349 │ 2023 3 21 117 10 SH 0 0 35.5 -108.5 -2.33729 -0.398522
53350 │ 2023 3 21 117 12 SH 1 1 35.5 -107.5 0.547169 1.03257
53351 │ 2023 3 21 117 16 SH 0 0 36.0 -108.5 -0.815015 0.95971
53352 │ 2023 3 21 117 23 SH 0 0 36.5 -108.0 0.48949 -1.59416
53342 rows omitted
julia> result = niche_overlap(df.Abundance, df.Species, df.plot, df.Sampling_date_order)
1×3 DataFrame
Row │ mean_niche_overlap_index min_niche_overlap_index max_niche_overlap_index
│ Float64 Float64 Float64
─────┼────────────────────────────────────────────────────────────────────────────
1 │ 0.0923816 0.0 0.406837References
- MacArthur, R. & Levins, R. The limiting similarity, convergence, and divergence of coexisting species. The American Naturalist 101, 377-385 (1967).
- Pianka, E. R. (1974). "Niche overlap and diffuse competition." Proceedings of the National Academy of Sciences, 71(5), 2141-2145.
- Pianka, E. R. (1973). "The Structure of Lizard Communities." Annual Review of Ecology and Systematics, 4(1), 53-74.