relative roles of dispersal limitation and environmental variation
In all the analyses, environmental differences were found to be far stronger predictors of site-wide changes in floristic differences than the geographical distances between sample plots. In transect 2, geographical distance effects were apparently stronger than in the other data sets, which may be because the ends of this transect corresponded to two habitat extremes, whose effect was only partly accounted for by our environmental data. Otherwise the environmental and geographical effects on floristic composition appeared to be largely independent of each other, as partialling out the effect of one had little effect on the results for the other in the Mantel tests.
Our study plots covered an environmental gradient running from richer, poorly drained swamp and recent alluvial soils to poorer, well-drained upland soils. Floristic variation was seen to correspond clearly to this edaphic-topographic gradient. When based on species presence-absence data, variation partitioning showed that the measured environmental differences alone explained 49% of the variation in floristic distances site-wide, and 17% when the environmental gradient was curtailed by including upland sites only. For species abundance data, the proportion of explained variation was lower: environmental differences explained 32% of site-wide variation in floristic distances and 9% in the upland soils. Geographical distances alone explained 0.5% or less of the variation in floristic distances in all cases. Restricting our analyses to the more environmentally homogeneous upland soils did not significantly strengthen the relationship between geographical distance and floristic variation (cf. Duque et al. 2002).
These findings are contrary to the dispersal assembly view of plant communities (Hubbell 2001), according to which floristic similarity between sites decreases as a monotonic function of the geographical distance between those sites. The results provide more support for the niche-assembly view, although half or more of the variation in floristic distances could not be accounted for by variation in either the measured environmental differences or geographical distances.
We reasoned in advance that as small areas harbour less environmental variation than large areas, we should find a smaller role for environmental variation at the mesoscale than has been found earlier at broader spatial scales. Similarly, as the effect of dispersal limitation is related to the logarithm of geographical distance (Hubbell 2001), per unit distance its effects should be more noticeable at small than at large geographical distances. These expectations were only partly borne out. Four studies in western Amazonia have recently estimated the relative roles of geographical and environmental distances at landscape to regional scales by regression analysis, and in these the unique contribution of geographical distances was 20–40% in the broadest-scale studies (Tuomisto, Ruokolainen & Yli-Halla 2003; Vormisto, Svenning, Hall & Balslev 2004) and 1.4–10% in the intermediate-scale studies (Phillips et al. 2003; Tuomisto, Ruokolainen, Aguilar & Sarmiento 2003). The contribution of less than 1% in the present study was hence much lower than expected. As to the unique contribution of environmental distances, the values reported in the four Amazonian studies ranged from 8% to 40%. This is similar to the range found in the present mesoscale study. Consequently, the only result that conformed to our prior expectations was that the contribution of environmental distances in the present study decreased when the environmental gradient was truncated by excluding the plots representing swamp and alluvial soils from the analyses. In comparing these studies, it should be acknowledged that they incorporated different aspects of environmental variation. All included some soil variables (except Tuomisto, Ruokolainen, Aguilar & Sarmiento 2003, who used satellite imagery as a surrogate for environmental data), but our study also included canopy openness and detailed topographic data, which probably allowed us to explain slightly more floristic variation than if we had analysed soils alone. Phillips et al. (2003) designed their landscape-scale sampling of trees to minimize the correlation between environmental and geographical distances, but nevertheless found geographical distance to explain 10% of the variation in floristic differences. This is a much larger proportion than in our study.
We did find a rapid decline in mean floristic similarity at very short distances. However, mean floristic similarity at these short distances, as described by the spline curve, diverged considerably from a linear relationship with log-geographical distance (Fig. 5). Thus, this decline appears too steep to fit the predictions of neutral theory. At distances greater than 100 m the decline was much gentler and slightly irregular. Apart from these small irregularities, which are likely to be partly random noise and partly related to changes in environmental conditions with distance (cf. Tuomisto, Ruokolainen & Yli-Halla 2003), mean floristic similarity at these distances did not depart much from a linear relationship, which could be an indication of some dispersal limitation that fits neutral theory.
Spatial autocorrelation in floristic similarities over short distances is related to both biotic processes, such as a higher probability of dispersal to nearby sites, and to spatial autocorrelation in habitat variables (Legendre 1993). Environmental conditions at our study site are highly autocorrelated at the same local scales at which we observed steeply declining floristic similarity. A move of 100 m often represents a change in topographic position (Fig. 2), and distances much shorter than this represent changes from gap to understorey conditions (Sanford et al. 1986; M. M. Jones et al., personal observations). Consequently, the decline we observed over short distances is confounded by environmental effects and cannot be attributed to dispersal limitation alone. Condit et al. (2002) came to a similar conclusion regarding the rapid decline in floristic similarity they observed at short distances (also to c. 100 m) in a study on canopy trees in Panama and Ecuador. They concluded that the trees were more aggregated than expected under Hubbell's neutral theory (Hubbell 2001) over these short distances, possibly due to light gap effects. In a temperate forest study carried out within an area of 10 km2, Gilbert & Lechowicz (2004) found that distance did not predict species turnover in six plant groups, and made only a slight contribution to turnover in a seventh. The genus Carex, for which floristic similarity fluctuated with distance, was chosen to illustrate deviations at their site from neutral expectations. They did not observe a decline in similarity even at the shortest distances included in their study, but this may have been because the minimum distance between any pair of sample plots was 135 m.
In conclusion, dispersal limitation is of little importance as a determinant of variation in pteridophyte composition at the mesoscale, but may be of increasing importance, alongside environmental differences, at landscape to regional scales. At La Selva, most fern species are continually fertile and produce large quantities of spores (although spore shadows are generally leptokurtic, Wolf et al. 2001), whereas only a few species appear reliant upon vegetative reproduction (M. M. Jones et al., personal observations). This, in conjunction with relatively small-scale environmental variation and strong environmental effects on the probability of germination and survival, is likely to account for the small effect of geographical distance we observed at scales of up to a few km.
relative roles of different environmental variables
Floristic patterns were most strongly associated with the main drainage (topographic) and soil fertility gradient. This confirms earlier results for large trees and palms at the same site (Clark et al. 1995, 1998, 1999). The patterns were the same whether floristic similarity was calculated from species presence-absence or abundance data, although the environmental data were able to explain a higher proportion of the variation in presence-absence than in abundance data. In one earlier study (Tuomisto, Poulsen, Ruokolainen, Moran, Quintana & Cañas 2003), floristic differences based on abundance data were better predicted than differences based on presence-absence data, but in another, the results varied from between localities (Tuomisto & Poulsen 2000). The reasons for these differences are not clear but may have to do with the scales at which species abundances vary over the landscape relative to the size of the sampling unit.
Qualitative soil data were useful for predicting floristic differences when the full environmental gradient was modelled, specifically to distinguish the swamp and recent alluvial or residual soils from the other soil types. As can be seen from the ordination diagram (Fig. 3), these soil types represent the extremes of the main drainage and soil fertility gradient. The importance of soil drainage and topography for floristic variation is generally acknowledged (e.g. Lieberman et al. 1985; Svenning 1999; Webb & Peart 2000; Harms et al. 2001; Pélissier et al. 2001). Two of the identified broad floristic groups were associated with the more poorly drained recent alluvial and swamp soils. The other three groups included a combination of upland and stream valley soils. However, there were also floristically distinct areas within these broad groups, which did not clearly correspond to changes in soil type or topographic position.
Within the restricted environmental gradient of the upland soils, the qualitative distinction between old alluvial and residual soils was not useful for predicting floristic differences. Instead, as over the full environmental gradient, information on topographic position was informative. Streamside sites are floristically variable and distinct from other topographic positions. In addition, valleys and lower slopes are usually floristically distinct from ridges and upper slopes (see clustering results, Fig. 2).
An earlier paper by Lieberman et al. (1985) suggested that altitude was the main factor behind a continuous floristic gradient for large woody plants at our study site. Our results suggest that relative topographic position is much more important than elevation per se. La Selva lies at the base of a mountain, so there is a c. 100 m rise in elevation over the site. Our transects were positioned almost at right angles to this gradient at different average elevations, so stream valley sites in the highest transect (transect 3) were found at elevations equivalent to ridge tops in the lowest transect (transect 1). Within each transect individually, elevation was a good proxy for topographic position and hence for environmental change among sample plots, and yielded significant correlations in the Mantel tests. However, site-wide there was no correlation between elevational distance and floristic distance, unless the relative elevations within each transect were used. Even then, the correlations with topographic position were clearly higher.
Quantitative soil chemistry was incorporated into all but one of the predictive models of floristic distances (Table 3), in the form of soil Ca and, in one case, pH. At the site-wide scale, the highest correlations with floristic distances were obtained with the distance matrices based on quantitative soil chemical data (soil Mg, Al, Ca or pH) (Table 2). As was suggested by Clark et al. (1999), quantitative soil data were found to provide more ecologically useful information for this site than qualitative data. Strong relationships between floristic distances and distances based on soil cation levels have also been observed at wider spatial and environmental scales in western Amazonia, both for pteridophytes and other plant groups (e.g. Ruokolainen et al. 1997; Phillips et al. 2003; Tuomisto, Poulsen, Ruokolainen, Moran, Quintana & Cañas 2003; Tuomisto, Ruokolainen, Aguilar & Sarmiento 2003; Tuomisto, Ruokolainen & Ylihalla 2003; Vormisto, Svenning, Hall & Balslev 2004).
Canopy openness was moderately correlated with floristic differences in all data sets, and was a significant predictor of floristic differences in all the regression models. Pteridophyte responses to gap-formation are multiple: the resulting disturbance and environmental change have positive effects on some species and negative effects on others (M. M. Jones et al., personal observations). In addition, gap formation changed the suite of species sampled in a plot because a few species more typical of the canopy were found on fallen trees. However, the inclusion of canopy openness in the models cannot be interpreted unambiguously as a gap effect, because many streamsides and some swamps also have relatively open canopies (Table 1).
The forest at La Selva is very dynamic, with a high tree stem turnover (2.3–2.8% year−1 for canopy level trees; Clark et al. 2004) and frequency of gap formation (Sanford et al. 1986). This may partly account for the high proportion of variation in floristic distances (50–90%) that was unexplained by either geographical distance or our large environmental data set, especially in the upland soil subset. Forest successional dynamics have an obvious impact on pteridophyte communities at local scales, and it seems likely that the shorter the soil or drainage gradient considered, the more dominant are species responses to gap formation and subsequent succession in contributing to floristic variation. Consequently, our inability to include information on past light and disturbance environments limits the degree to which we can predict floristic patterns at the mesoscale.