Relative nonlinearity
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Relative nonlinearity is a coexistence mechanism that maintains species diversity via differences in the response to and effect on variation in
resource Resource refers to all the materials available in our environment which are technologically accessible, economically feasible and culturally sustainable and help us to satisfy our needs and wants. Resources can broadly be classified upon their ...
density or some other factor mediating competition. Relative nonlinearity depends on two processes: 1) species have to differ in the curvature of their responses to resource density and 2) the patterns of resource variation generated by each species must favor the relative growth of another species. In its most basic form, one species grows best under equilibrium competitive conditions and another performs better under variable competitive conditions. Like all coexistence mechanisms, relative nonlinearity maintains species diversity by concentrating
intraspecific competition Intraspecific competition is an interaction in population ecology, whereby members of the same species compete for limited resources. This leads to a reduction in fitness for both individuals, but the more fit individual survives and is able to r ...
relative to interspecific competition. Because resource density can be variable, intraspecific competition is the reduction of per-capita growth rate under variable resources generated by conspecifics (i.e. individuals of the same species). Interspecific competition is the reduction of per-capita growth rate under variable resources generated by heterospecifics (i.e. individuals of a different species). Like some other coexistence mechanisms (see the storage effect), relative nonlinearity can allow coexistence of at least two species on a single resource.


Functional components


Differential nonlinear responses to resources

Relative nonlinearity requires that species differ in the curvature of their fitness response \phi_i to some competitive factor, ''F'', like resource density. The nonlinearity of a response to competition is the
second derivative In calculus, the second derivative, or the second order derivative, of a function is the derivative of the derivative of . Roughly speaking, the second derivative measures how the rate of change of a quantity is itself changing; for example, ...
of the per-capita growth rate with respect to the competitive factor \phi_i^(F), which is zero if the growth response is linear, positive if the response is accelerating (
convex Convex or convexity may refer to: Science and technology * Convex lens, in optics Mathematics * Convex set, containing the whole line segment that joins points ** Convex polygon, a polygon which encloses a convex set of points ** Convex polytop ...
), and negative if the response is decelerating (
concave Concave or concavity may refer to: Science and technology * Concave lens * Concave mirror Mathematics * Concave function, the negative of a convex function * Concave polygon, a polygon which is not convex * Concave set * The concavity of a ...
). For competition between two species, the greater the difference in the curvatures of their response to changes in a competitive factor, the greater the differences in their overall specialization on competitive factor variation. For example, by Jensen's inequality, compared to constant resource density, variation in a competitive factor has no effect on species with zero curvature, positive effects on species with positive curvature, and negative effects on species with negative curvature. Thus, \phi_i^(F) indicates a species response to variation in competitive factors, a dimension of competition that can be partitioned. Competitive factors are best thought of as dimensions of the environment that are jointly used by more than one species and contribute to a reduction in performance of individuals when used. For example, space is a common competitive factor for trees because many species require space for new trees to grow and the reduction in space reduces opportunities for other species to capture that space and grow. Resources and predators have similar properties and count as competitive factors. For competition between two species for a single shared resource, it is easy enough to think of the competitive factor as the reduction in species density due to consumption. In the absence of resource consumption, resources will tend to be at some equilibrium value, K. Thus, the competitive factor for our example is F = K - R for any value of R. The original demonstration of relative nonlinearity was in a consumer-resource model with differences in functional responses of the two species. One species has a Type I functional response and has zero curvature. The second species has a Type II functional response - which occurs when individuals must spend time handling resources before moving on to the next resource - and has negative curvature. Because the second species is limited by time when capturing resources, it is unable to exploit resources at high density compared to its competitor. If the Type II functional response species does better under average conditions than the species with a Type I functional response, the species differ in their ''response to'' equilibrium and variable resource density.


Differential effect on resource variation

Not only must species respond differently to variation in competition, species must also affect variation in competition differently. Given these two processes, differential effects on and response to resource variation, species may coexist via relative nonlinearity.


Mathematical derivation

Here, we will show how relative nonlinearity can occur between two species. We will start by deriving the average growth rate of a single species. Let us assume that each species' growth rate depends on some density-dependent factor, ''F'', such that : \frac = \phi_j(F)N_j , where ''N''''j'' is species ''js population density, and \phi_j(F) is some function of the density-dependent factor ''F''. For example, under a Monod
chemostat A chemostat (from ''chem''ical environment is ''stat''ic) is a bioreactor to which fresh medium is continuously added, while culture liquid containing left over nutrients, metabolic end products and microorganisms is continuously removed at the sa ...
model, ''F'' would be the resource density, and \phi_j(F) would be a_jF - d, where ''a''''j'' is the rate that species ''j'' can uptake the resource, and ''d'' is its death rate. In a classic paper by Armstrong and McGehee ite Armstrong \phi_j(F) was the a Type I functional response for one species and a Type II functional response for the other. We can approximate the per-capita growth rate, r_j = \frac \frac, using a
Taylor series In mathematics, the Taylor series or Taylor expansion of a function is an infinite sum of terms that are expressed in terms of the function's derivatives at a single point. For most common functions, the function and the sum of its Taylor ser ...
approximation as : r_j \approx \phi_j(\overline) + (F - \overline) \phi_j(\overline)' + \frac (F - \overline)^2 \phi_j(\overline)'' , where \overline is the average value of ''F''. If we take the average growth rate over time (either over a
limit cycle In mathematics, in the study of dynamical systems with two-dimensional phase space, a limit cycle is a closed trajectory in phase space having the property that at least one other trajectory spirals into it either as time approaches infinity o ...
, or over an infinite amount of time), then it becomes :\overline \approx \phi_j(\overline) + \frac \sigma^2_F \phi_j(\overline)'' , where \sigma^2_F is the
variance In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its population mean or sample mean. Variance is a measure of dispersion, meaning it is a measure of how far a set of numbe ...
of ''F''. This occurs because the average of (F - \overline) is 0, and the average of (F - \overline)^2 is the variance of ''F''. Thus, we see that a species' average growth rate is helped by variation if ''Φ'' is convex, and it is hurt by variation if ''Φ'' is concave. We can measure the effect that relative nonlinearity has on coexistence using an invasion analysis. To do this, we set one species' density to 0 (we call this the invader, with subscript ''i''), and allow the other species (the resident, with subscript ''r'') is at a long-term steady state (e.g., a
limit cycle In mathematics, in the study of dynamical systems with two-dimensional phase space, a limit cycle is a closed trajectory in phase space having the property that at least one other trajectory spirals into it either as time approaches infinity o ...
). If the invader has a positive growth rate, then it cannot be excluded from the system. If both species have a positive growth rate as the invader, then they can coexist. Though the resident's density may fluctuate, its average density over the long-term will not change (by assumption). Therefore, \overline = 0. Because of this, we can write the invader's density as : \overline = \overline - \overline . Substituting in our above formula for average growth, we see that :\overline \approx \left(\phi_i(\overline) + \frac \sigma^2_F \phi_i(\overline)'' \right) - \left(\phi_r(\overline) + \frac \sigma^2_F \phi_r(\overline)'' \right) . We can rearrange this to :\overline \approx \left(\phi_i(\overline) - \phi_r(\overline) \right) + \Delta N_i, where \Delta N_i quantifies the effect of relative nonlinearity, :\Delta N_i = \frac \sigma^2_F \left( \phi_i(\overline)''- \phi_r(\overline)'' \right) . Thus, we have partition the invader's growth rate into two components. The left term represents the variation-independent mechanisms, and will be positive if the invader is less hindered by a shortage of resources. Relative nonlinearity, \Delta N_i will be positive, and thus help species ''i'' to invade, if \phi_i(\overline)''> \phi_r(\overline)'' (i.e., if the invader is less harmed by variation than the resident). However, relative nonlinearity will hinder species ''is ability to invade if \phi_i(\overline)'' < \phi_r(\overline)''. Under most circumstances, relative nonlinearity will help one species to invade, and hurt the other. It will have a net positive impact on coexistence if its sum across all species is positive (i.e., \Delta N_j + \Delta N_k > 0 for species ''j'' and ''k''). The \phi_j(\overline) terms will generally not change much when the invader changes, but the variation in ''F'' will. For the sum of the \Delta N_i terms to be positive, the variation in ''F'' must be larger when the species with the more positive (or less negative) \phi_j(\overline)'' is the invader.


References

{{reflist Community ecology Ecological theories Theoretical ecology