The physiological response curve (Figure 1) describes potential organism distribution limits along an environmental factor or resource gradient in the absence of competition by other species. However, the response of species growing intermixed with other species, the ecological response, is often different from the potential physiological response.
Figure 2 Physiological (a) and ecological (b) plant tolerance curves for soil N availability. Plant response to N availability is a typical example of an asymmetric physiological tolerance relationship (a). In most species, plant growth rate, productivity, and survivorship increase with increasing soil nitrogen availability up to relatively high N availabilities; plant performance then reaches a broad saturation level and then slowly decreases as plants start to experience osmotic stress at excess mineral N availabilities. At typical N availabilities in natural ecosystems, plants rarely are in saturation or excess situations. The hypothetical curves are shown for three different species with similar physiological N optimum (Nopt), but with different tolerances to N deficiency and with different use efficiencies of N under limiting conditions (initial slope of growth vs. N availability relationship denoted by dashed lines). When a series of different species compete for the same soil N source, species that can use N more efficiently and have higher productivity at a given N availability can outcompete neighbors. This results in distinct ecological optimums at relatively low N availabilities for different species growing in real ecological context of multispecies communities (b). A detailed discussion of tolerance of deficiency and excess of N is provided in Aber JD, McDowell WH, Nadelhoffer, et al. (1998) Nitrogen saturation in temperate forest ecosystems: Hypotheses revisited. Bioscience 48: 921-934.
For instance, different plant species can have similar optimum ranges for limiting soil resources such as phosphorus and nitrogen. In general, the optimum ranges for N and P are very high, often much higher than the availability of these nutrients in natural environments even for species generally considered characteristic to low-nutrient sites (Figure 2a). However, the species markedly differ in the efficiency of nutrient use, defined as the amount of biomass produced per unit nutrients taken up. Species with higher nutrient-use efficiency can achieve a greater share of soil nutrient resources and outcompete the species with lower nutrient-use efficiency (Figure 2b). At the same time, minimum nutrient concentrations are generally higher in plants with inherently large growth rates, and therefore the tolerance of nutrient deficiencies is lower for these species. This mechanism can explain why plant species with similar physiological optimum ranges for nutrients exhibit distinct differentiation along nutrient availability gradients (Figure 2b).
Analogously, interspecific differences in light-use efficiency can affect plant response to shade and high light. Many plant species can potentially colonize a wide range of light environments in the complete absence of competition, but there is a distinct separation of species along natural light gradients due to species differences in the efficiency of the use of either low or high light. Tree shade tolerance as defined in forestry textbooks and used to predict the succession of forest communities is not an absolute minimum light requirement, but a relative term that characterizes plant ecological tolerance to low light in multispecies forest stands.
Tolerance also varies with plant developmental stage. It is well-known that juveniles are more vulnerable to stressful conditions such as drought or heat than adult plants, while young woody plants can tolerate low light availability in the understory better than older plants that have larger amount of support structures relative to unit foliage biomass. These examples collectively illustrate the caveats of employing species physiological tolerance limits estimated commonly with young plants in predicting species distribution.
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