Abstract

The study of elevational diversity patterns, and the attempt to disentangle the factors that create them, has proved a challenging and controversial research venue over the last few decades (Terborgh 1977, 1985, Stevens 1992, Rahbek 1995, 1997, 2005, Korner 2000, Brown 2001, Lomolino 2001, McCain 2005). Studies of elevational gradients fall into two general categories, regional studies that summarize known distributions from complete elevational bands (zones) within a defined geographical or political region, and local-scale transect studies that are based on a single survey scheme (Rahbek 1995, 2005). Elevational band area (the compiled area of each elevational zone) of a mountainous region is generally expected to decline with altitude (MacArthur 1972, Korner 2000, Lomolino 2001), although the smallest area per elevational zone can also be found at mid-elevation, where slope is sometimes steeper (Rahbek 1997). That area of regional elevational bands can influence the number of species found in each band was first clearly demonstrated by Rahbek (1997), and several studies since then have explicitly investigated this regional area effect on elevational diversity gradients (Sanders 2002, Sanders et al. 2003, Bachman et al. 2004). In recent years there has been a renewed interest in the analysis of standardized species richness data sets from transects in order to evaluate simultaneously the potential drivers of elevational diversity gradients (Md. Nor 2001, Sanchez-Cordero 2001, Grytnes 2003, Kattan and Franco 2004, Herzog et al. 2005). A number of factors such as climate-derived productivity, source-sink dynamics and the mid-domain effect, have been evaluated, and the diversity of results confirm the belief that no single factor is responsible for all observed richness patterns (Rahbek 1995, 2005, Brown 2001, Lomolino 2001, McCain 2006, Dunn et al. 2007). Most transect studies attempt to control the influence of area by sampling equal-area plots, although unstandardized plots also frequently occur (Lieberman et al. 1996, Hoffmann et al. 2001, Herzog et al. 2005). However, in addition to the direct influence of the area of the sampled plot, local communities can be perceived as dynamic samples drawn from a regional species pool (Terborgh 1973, Graves and Gotelli 1983, Cornell 1985, Ricklefs 1987). The size of the surrounding region can be thought of as a surrogate variable for the size of the regional species pool (Terborgh and Faaborg 1980, Cornell and Lawton 1992, Caley and Schluter 1997, Cornell 1999). This additional effect of area on elevational transects was, to our knowledge, first discussed by Beehler (1981), who found that a linear decrease in New Guinean forest birds on an elevational transect was paralleled by a decrease in regional area. Several other authors have suggested that regional habitat area influenced observed elevational richness patterns (Holloway 1987, Stotz 1998, Patterson et al. 1998, Brehm et al. 2003), while Heaney (2001) and Sanders et al. (2003) presented results contrasting with the hypothesis. Some recent studies have attempted to analyse this area effect quantitatively. Grytnes (2003) found that elevational band area was only correlated with site richness in two out of seven elevational gradients of plant richness in Norway. In contrast, a considerable influence from measures of surrounding habitat area has recently been demonstrated on a tropical transect measuring avian richness (Herzog et al. 2005). We will use the term indirect area effect to describe the effect of regional area on the pattern of local species richness. In an attempt to quantitatively evaluate the importance of the indirect area effect we have performed a meta-analysis on data from 71 elevational Ecography 30: 440 448, 2007 doi: 10.1111/J.2007.0906-7590.04954.x Copyright # Ecography 2007, ISSN 0906-7590

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