The Mid‐Domain Effect and Species Richness Patterns:What Have We Learned So Far?

Abstract

If species' ranges are randomly shuffled within a bounded geographical domain free of environmental gradients, ranges overlap increasingly toward the center of the domain, creating a "mid-domain" peak of species richness. This "mid-domain effect" (MDE) has been controversial both in concept and in application. Empirical studies assess the degree to which the evolutionary, ecological, and historical processes that undeniably act on individual species and clades produce geographical patterns that resemble those produced by MDE models. MDE models that resample empirical range size frequency distributions (RSFDs) balance the risk of underestimating and overestimating the role of MDE, whereas theoretical RSFDs are generally biased toward underestimating MDE. We discuss the inclusion of nonendemic species in MDE models, rationales for setting domain limits, and the validity of one- and two-dimensional MDE models. MDE models, though null models, are not null hypotheses to be simplistically rejected or accepted. They are a means of estimating the expected effect of geometric constraints within the context of multiple causality. We call for assessment of MDE on an equal statistical footing with other candidate explanations for richness gradients. Although some critics have categorically dismissed MDE, an overview of the 21 MDE studies published to date reveals a substantial signature of MDE in natural patterns and justifies continued work.

Distribution of megabenthic gastropods along environmental gradients: the mid-domain effect and beyond

“…The finding that a stochastic rearrangement of species ranges on a bounded domain generates a pattern in which species richness peaks at the middle of 1-dimensional domains, declining towards the borders following a parabolic curve, has repeatedly been demonstrated for several geographic gradients (see Colwell et al 2004, Arita 2005. In the present paper, we extended the use of MDE models to stress gradients (in the sense of Chase & Leibold 2003), showing that a random re-shuffling of empirical tolerance ranges generated the characteristic parabolic pattern for 1-dimensional MDE models.…”

“…This assumption is usually not a source of substantial bias for most taxa (Colwell et al 2004) and would seem particularly reasonable for environmental, rather than geographical, gradients. For the bathymetric ranges, we used the direct observations of maximum and minimum depth where a particular species was recorded (when available), or checked the literature for existing data.…”

“…To estimate predicted richness under the assumption of random placement of interpolated richness, we drew ranges at random from the empirical range size frequency distribution (RSFD) and placed them randomly within each unidimensional physiological domain (Model 4 of the computer application RangeModel 5, see Colwell 2008). Resampling RSFDs balances the risk of underestimating and overestimating the role of MDE (Colwell et al 2004). We chose to truncate empirical physiological ranges that may extend beyond the physiological domain limits represented in the study area, treating the portion occurring within the domain as endemic.…”

“…latitude, depth, elevation, river courses) (Pineda 1993, Colwell & Hurtt 1994, Grytnes & Vetaas 2002, Sanders 2002, Brehm et al 2007. In view of the fact that an overview of 21 MDE studies (Colwell et al 2004(Colwell et al , 2005) revealed a substantial signature of MDE in natural patterns, it seems possible to argue that stochastic geometric phenomena are indeed affecting (although in variable degrees) the patterns of species richness within any bounded domain. The only previous MDE-related study of marine gastropods (Pineda & Caswell 1998) reported that a random rearrangement of species' ranges within geographic boundaries did not fully explain observed bathymetric patterns for deep sea gastropods and polychaetes in the western North Atlantic, but partial contributions of MDE to these patterns were not assessed.…”

Combinando informações ambientais e estrutura da paisagem para explicar padrões de biodiversidade: busca por alternativas eficientes para planejamento ambiental

“…Esse padrão foi sugerido por Rahbek em 1995. Esse pico de riqueza em altitudes intermediárias é chamado de efeito do domínio médio (mid-domain effect) (Colwell et al, 2004). Quando concorremos os modelos separadamente para as três regiões observamos esse padrão se repete para região da Mata Atlântica do Litoral mas não para as outras regiões.…”