The species-area relationship is one of the oldest known and most documented patterns in ecology. It describes the general pattern of increase in species richness with increasing area of observation, but it can take on different forms and be explained by various mechanisms. Research exploring species-area relationships has taken multiple directions since coming to prominence in the ecological literature in the early 19th century. Most early discussions focused on quantifying the relationship through mathematical functions, particularly Olof Arrhenius’s power function and Henry Gleason’s exponential relationship (Arrhenius 1921 and Gleason 1922, both cited under Species-Area Functions). More recently, ecologists have attempted to infer ecological process from the form and parameters of these models. The impact of habitat heterogeneity and increased risk of extinction in small areas have been explored most often, but other key ecological processes (e.g., speciation, dispersal, fragmentation, and habitat specificity) also have been suggested to influence the relationship. In addition, several studies have examined how aspects of sampling design, such as whether observations are nested or scattered across space or are of regular or irregular shapes and sizes, influence the shape and parameters of the species-area relationship through their different sensitivities to species aggregation, habitat heterogeneity, and biogeographic processes. Furthermore, species-area relationships are often quantified differently, depending on the goals of a study. A nested sampling design can be used to highlight patterns of species aggregation due to dispersal and environmental filtering, samples scattered across a landscape are best for estimating species diversity in larger areas, and an “isolate” or island design may be best for assessing the role of immigration and extinction processes and for predicting the number of extinctions with habitat loss and fragmentation. Despite the fact that most studies of species-area relationships focus on inferring ecological phenomena from the form of the relationship, small-scale trends often reflect spatial processes that limit the number of individuals that can fit in a small area. In summary, the mathematical functions used to characterize species-area relationships often have different parameters when applied to data from different ranges of area, and these differences in observed species-area functions are often attributed to sampling methodologies and underlying ecological and biogeographical processes. Looking forward, ecological research is expanding from its past species-centric perspective to a greatly increased focus on traits of organisms and their phylogenetic relationships, which is leading to examination of how these factors also vary with area (see Beyond Species-Area Relationships).
Species-area relationships were first documented and debated among plant ecologists seeking to characterize and compare plant communities. The subject later gained popularity among animal ecologists with the seminal work of Preston 1962 on species abundance distributions and with Robert MacArthur and Edward O. Wilson’s equilibrium theory of island biogeography (MacArthur and Wilson 1967, cited under Habitat Heterogeneity and Area). An excellent historical review is provided in McGuinness 1984, which connects debates over the form and function of species-area relationships with emerging ecological theory. Connor and McCoy 1979 also reviews the evidence linking species-area relationships to biological and ecological explanations, but the authors focus on the statistical validity of attempts to use the form and parameters of species-area curves to discern ecological causality. Rosenzweig 1995 explores in detail several examples of species-area curves and uses them to discuss the many factors that influence the shape of these curves, while Drakare, et al. 2006 builds on the work of Michael Rosenzweig and others through a meta-analysis of species-area relationships to show that the relationship is influenced by habitat, type of organism, sampling scheme, and spatial scale. Because of the variety of research goals inherent in studies of species-area relationships, sampling and analytical methods, as well as definitions of what constitutes a species-area relationship, often vary among studies. Scheiner 2003 defines six types of species-area curves that differ in the spatial arrangement of samples, whether larger samples are constructed in a spatially explicit fashion from adjacent smaller samples, and whether means or single values are used for a given spatial scale. Dengler 2009, however (and references cited therein), considers true species-area relationships to have a narrower definition, because in the author’s view area is a biologically meaningful variable only when it implies that samples are spatially contiguous.
Connor, Edward F., and Earl D. McCoy. 1979. The statistics and biology of the species-area relationship. American Naturalist 113.6: 791–833.
Evaluates evidence that species-area relationships are best fit by the power law and are predicted by equilibrium theory. The authors find no unique theoretical basis for any one model or ecological explanation and observe that parameter values may be influenced more by statistical characteristics than by biological drivers.
Dengler, Jürgen. 2009. Which function describes the species-area relationship best? A review and empirical evaluation. Journal of Biogeography 36.4: 728–744.
Reviews the literature on functional form and definitions of species-area relationships, distinguishing species-area relationships from species-sampling relationships deduced from species accumulation and rarefaction curves. The author recognizes only nested, spatially explicit, and island curves as true species-area relationships because each point in the curve is internally contiguous.
Drakare, Stina, Jack J. Lennon, and Helmut Hillebrand. 2006. The imprint of the geographical, evolutionary and ecological context on species-area relationships. Ecology Letters 9.2: 215–227.
A meta-analysis of 794 species-area relationships from the literature, which synthesizes how the parameter z from Arrhenius’s power law (see Species-Area Functions) varies across sampling designs, organisms, body sizes, habitats, and spatial scales.
McGuinness, Keith A. 1984. Equations and explanations in the study of Species–area curves. Biological Reviews 59.3: 423–440.
A useful review of the history of the study of species-area relationships, highlighting attempts to connect explanations to the functional form of the relationship.
Preston, Frank W. 1962. The canonical distribution of commonness and rarity: Part I. Ecology 43.2: 185–215.
Connects species-area relationships to the lognormal distribution of species abundance under assumptions of spatial uniformity and a canonical lognormal distribution of species and individuals. Predicts z-value of 0.262 for the power-law species-area relationship, and documents, and documents that many empirical z-values are remarkably close to this prediction and that those that are not arise from truncated lognormal distributions.
Rosenzweig, Michael L. 1995. Species diversity in space and time. Cambridge, UK: Cambridge Univ. Press.
Summarizes and differentiates the shapes and underlying causes of species-area relationships, including differentiating curves built from small areas within a single biota, from large areas in a single biota, from island archipelagos, and from those built across two or more biogeographic regions. Discusses the use of power law c-values (see Species-Area Functions) in comparing richness across areas.
Scheiner, Samuel M. 2003. Six types of species-area curves. Global Ecology and Biogeography 12.6: 441–447.
Summarizes what species-area curves are, and discusses the various ways they can be constructed. Has a more inclusive definition than that in Dengler 2009 but recognizes that certain types reflect phenomena similar to species accumulation or rarefaction curves.
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- Accounting for Ecological Capital
- Allocation of Reproductive Resources in Plants
- Animals, Functional Morphology of
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