The underpinnings of the relationship of species richness with space and time

Abstract

Various ecological mechanisms influence the forms of species richness relationships (SRRs). These mechanisms can be gathered under five general categories: more individuals, environmental heterogeneity, dispersal limitations, biotic interactions, and multiple species pools. Often only the first two categories are discussed. In contrast, we examine all five and explore how they can influence the form of SRRs. We discuss how various sampling schemes and methods of SRR construction can be used to gain insight about how various processes influence species richness patterns. The field is ripe for probing these effects through more complex simulation models or more sophisticated mathematical approaches. To facilitate deeper understanding, we need to embrace the full spectrum of SRRs and reconsider the assumed common knowledge about the functional form of SRRs. The relationship between species richness and the space or time over which it is sampled has received increasing attention over the past decade, resulting in extensive debates about terminology and methods of construction. These debates reflect deep conceptual issues; to resolve them we discuss the long history of species richness relationships (SRRs) and the connections among different methodological and terminological approaches. We reinforce recent calls to organize the variety of methods used to construct SRRs into a cohesive structure. SRRs are descriptors of various aspects of inventory (α‐ and γ‐) diversity and the various types of SRRs serve different purposes. Contrary to most claims, SRRs do not provide a direct measure of differentiation (β‐) diversity.

Zeta Diversity as a Concept and Metric That Unifies Incidence-Based Biodiversity Patterns

“…However, z can also be expressed as a function of other survey design parameters, such as distance, area, or grain, and for either aggregate (including hierarchical, nested) or independent sampling schemes (sensu Scheiner et al 2011). z diversity relationships can therefore be used for estimating sampling completeness, for understanding how diversity is affected by the spatial properties of the samplings scheme (grain, distance, and extent), and for analyzing multiscale patterns of species diversity (Veech and Crist 2010;McGlinn and Hurlbert 2012).…”

“…As a result, here we discuss only the implications of these two specific forms of z diversity decline for incidence-based biodiversity patterns. The exponential and power-law forms of z diversity decline are underpinned by distinct hypotheses about ecological process; that is, they represent species turnover as either largely stochastic (exponential z) or driven principally by niche differentiation processes (power-law z; Munoz et al 2008;Scheiner et al 2011).…”

“…As with all biodiversity metrics, z diversity is sensitive to the scale at which a study is conducted, that is, the grain and extent (Scheiner et al 2011). When sampling grain increases, the species richness in each sample and the number of species shared by multiple samples will increase ( fig.…”

“…Both b and z diversity components are nonindependent across hierarchical levels, or nested sample grains, because they represent part-to-whole associations (sensu Scheiner et al 2011). Nonetheless, z diversity scaling can also be used for nonhierarchical sampling schemes, to better understand how diversity changes across spatial scales and, for example, the contribution of different habitats to regional diversity (Veech and Crist 2010).…”

Phylogenetic diversity–area curves

“…This pattern, termed the species-area curve (or the species-area relationship, SAR) has been recognized since the 19th century and is important for many issues in ecology, biogeography, evolution, and conservation (Rosenzweig 1995, Lomolino 2000, Tjørve 2003, Scheiner et al 2011. The mechanisms underlying any specific SAR can vary White 1994, Drakare et al 2006).…”