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The species–area relationship or species–area curve describes the relationship between the area of a habitat, or of part of a habitat, and the number of species found within that area. Larger areas tend to contain larger numbers of species, and empirically, the relative numbers seem to follow systematic mathematical relationships. [ 1 ]
The rank abundance curve visually depicts both species richness and species evenness. Species richness can be viewed as the number of different species on the chart i.e., how many species were ranked. Species evenness is reflected in the slope of the line that fits the graph (assuming a linear, i.e. logarithmic series, relationship).
It is then possible to predict how many species are in the community by calculating the total area under the curve (N): N = n 0 π a {\displaystyle N={\frac {n_{0}{\sqrt {\pi }}}{a}}} The number of species missing from the data set (the missing area to the left of the veil line) is simply N minus the number of species sampled. [ 2 ]
The species-area relationship equation is: =. [10] An example of what a species-area relationship may look like when graphed. In this equation, represents the measure of diversity of a species (for example, the number of species) and is a constant representing the y-intercept.
When plotted as a histogram of number (or percent) of species on the y-axis vs. abundance on an arithmetic x-axis, the classic hyperbolic J-curve or hollow curve is produced, indicating a few very abundant species and many rare species. [2] The SAD is central prediction of the Unified neutral theory of biodiversity.
[11] [12] It turns out that a two dimensional analysis yields an Allee curve in human exploiter and biological population space and that this curve separating species destined to extinction vs persistence can be complicated. Even very high population sizes can potentially pass through the originally proposed Allee thresholds on predestined ...
For a given species, the realized and fundamental niches might be the same, but if a species is geographically confined due to dispersal limitation or species interactions, the realized niche will be smaller than the fundamental niche. Correlative SDMs are easier and faster to implement than mechanistic SDMs, and can make ready use of available ...
Another example by Higgins and Strauss (2008), modeling fish assemblages, found that fish communities from different habitats and with different species compositions conform to different niche apportionment models, thus the entire species assemblage was a combination of models in different regions of the species range.