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Stephen Hubbell's unified neutral theory of biodiversity (Hubbell 2001) provoked intense debate among ecologists (e.g. McGill 2003; Volkov et al. 2003; Gilbert & Lechowicz 2004; Wootton 2005). Hubbell's theory considers communities to consist of ecologically equivalent individuals distributed across a fixed number of species derived from a regional species pool. Population dynamics is modelled at regional and local scales. Replacement individuals at a local scale immigrate from the regional species pool, while at regional scales new individuals result from speciation. The dynamics of a community can therefore be modelled with a minimum of parameters: regional population size, speciation rate, migration rate and death rate. Such an approach can successfully generate patterns consistent with species–area (MacArthur & Wilson 1967) and abundance–frequency relationships (Tokeshi 1999). Neutral theory explicitly ignores differences between individuals in response to local ecological conditions. In contrast niche theory suggests that patterns of biodiversity should closely relate to underlying variability in ecological parameters such as physico-chemistry, disturbance regime, productivity and competition with other species (e.g. Tilman 1982; Tokeshi 1999).
Neutral theory is difficult to test in practice (Harte 2003; Gilbert & Lechowicz 2004; Wootton 2005) particularly as key population parameters have rarely been measured (but see Wootton 2005). Attempts to fit species-abundance curves generated by neutral theory and other models to real data have been made (McGill 2003; Volkov et al. 2003; Adler 2004; Alonso & McKane 2004; Chisholm & Burgman 2004), but differences in model fit are often negligible (Harte 2003; Hubbell & Borda-de-Agua 2004). Even when the model fits (such as the log-normal curve fitted to Panamanian tree diversity by McGill 2003) it may not inform us about the underlying biological processes. There have been attempts in recent years to test empirically patterns expected to emerge from neutral processes (e.g. Condit et al. 2002; Gilbert & Lechowicz 2004; Wootton 2005). One of these emergent patterns is that of ‘distance decay’ (Hubbell 2001). Because dispersal limitation underlies differences between sites in a neutral world, it is expected that widely separated points will harbour different communities (Harte 2003). Differences in local species richness between sites can be explained by random extinctions and replacements of species through time, a process Hubbell (2001) calls ‘ecological drift’. This process has a direct analogy with ‘neutral allele theory’ (Kimura 1983), the process whereby changes in genomes are accumulated passively through time via ‘genetic drift’. As in genetics, where the relative importance of genetic drift vs. natural selection has been widely debated (e.g. Mayr 1991; Ridley 2002), so too has Hubbell's assertion of the dominance of ecological drift over local determinism (Nee & Stone 2003).
Neutral theory can be tested by comparing the fit of community data to local ecological conditions, vs. their fit to distance decay expectations. Under niche theory, similarity between species-abundance matrices will be positively correlated with similarity in local ecological conditions. Neutral theory predicts a negative correlation with distance between sites. Such a test is made more difficult because distance between sites is often positively correlated with differences in local ecological factors (Gilbert & Lechowicz 2004). Such an approach is only valid when local conditions and spatial separation are independent of one another. Stream systems provide a useful test system because they generate a spatially constrained set of local conditions with intervening inhospitable habitat. Aerial dispersal of adults allows movement of individuals between patches on realistic scales.
We used macroinvertebrate communities from a set of stream sites in a large river catchment in New Zealand to test neutral and niche predictions. Neutral theory predicts decreased similarity between invertebrate communities that are spatially distant. Niche theory predicts decreased community similarity with lower similarity in ecological conditions. Alternatively, we might expect both neutral and niche processes to contribute to patterns of local diversity, leading to a pattern of decreased similarity in communities as spatial distance increases and niche similarity decreases. Because dispersal limitation underlies neutral expectations, we also analyse separately communities with varying dispersal ability. Community similarity for species with poor dispersal should be strongly negatively associated with spatial separation of sites, while species with good dispersal should overcome dispersal limitation and be strongly positively associated with local ecological conditions.
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The 10 streams contained a total of 89 taxa, 67·4% of which we identified to species (Table 3). We identified 64·2% of individuals to species level and 98·7% to genus. Seventy-two of the taxa could be attributed a dispersal ability value.
Table 3. Summary of invertebrate data from the 10 locations showing number of individuals identified, total number of taxa and number of taxa in different trophic and dispersal ability groupings
|Stream||No. of individuals||No. of taxa||Trophic grouping||Dispersal ability|
|Blackrock||3206||40||11|| 9||5||25|| 7|
|Broad||2845||37||12|| 9||7||22|| 5|
|German||3041||32|| 5|| 6||3||22|| 5|
|Kye Burn||2778||35|| 9|| 6||4||22|| 7|
|Little Kye||3305||29|| 7|| 7||2||16|| 6|
|Sutton||2787||35|| 9||12||4||20|| 8|
There was no statistically significant correlation between spatial location of sites and their local ecological conditions (Pearson's Correlation = 0·108, P = 0·165) (Fig. 1). Therefore our analyses of effects of spatial location and ecological conditions were independent. There were high correlation coefficients between the spatial matrix and invertebrate matrices for all taxa, grazers and taxa with low dispersal ability (Table 4). However, these invertebrate groups, as well as predatory taxa and taxa with moderate dispersal abilities, also showed moderate to strong correlations with local ecological conditions (Table 4). For all invertebrate taxa, grazers, and taxa with low and moderate dispersal abilities, Mantel test's found the highest correlation with the predictor matrix combining spatial separation and local ecological conditions (Table 4).
Table 4. Pearson's correlation coefficients from Mantel tests between invertebrate abundance matrices and the three predictor matrices
| ||Spatial||Local ecology||Local ecology + spatial|
Distance between sites was negatively related to similarity in patterns of abundance for all invertebrate taxa and for grazers and predators separately (Fig. 2a–c). Grazing community similarity had a negative relationship with variability in depth, and a positive relationship with disturbance and average current (Fig. 2d). In contrast, similarity between predator communities was negatively associated with current and positively associated with channel slope and width (Fig. 2e). Similarities in the overall invertebrate communities were not well predicted by any of the ecological variables (Fig. 2f). Linear models incorporating spatial distance and ecological factors were the best predictors of similarities in invertebrate community structure (Fig. 2g–i), although support for the predator community model was relatively weak. The models for all groups included average current speed, with the model for grazers also including negative associations with pH and variability in current (Fig. 2g).
Figure 2. Relationships between community similarity (Bray–Curtis) and best linear models (shown on x-axis), for grazers, predators and all invertebrates from the 10 streams. Regression lines are shown where the slope is significant (P < 0·05) and r2 > 0·10. sd = standard deviation, av = average, disturb = disturbance, curr = current, dist = distance. For units see Tables 1 and 2.
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When the invertebrate community was differentiated according to dispersal ability, a negative relationship was found between spatial distance between sites and community similarity for low dispersal and moderate dispersal groups (Fig. 3a,b), but no relationship was found for the high dispersal group (Fig. 3c). The slope of this relationship was higher for the low dispersal taxa than the moderate dispersal taxa (ancova; F1,86 = 4·343, P = 0·040). A model including disturbance, primary production, seston, algal biofilm biomass, pH and average depth was the best predictor of similarity between moderate dispersal groups (Fig. 3e), but low and high dispersal groups were not well predicted by ecological variables (Fig. 3d,f). Models incorporating spatial distance together with a variety of ecological factors were reasonable predictors of community similarity for low and moderate dispersal groups (Fig. 3g,h), but not for their high dispersal counterpart (Fig. 3i). Models combining spatial distance and ecological factors were the best predictors of similarity in all community combinations (Table 4, Figs 3 and 4).
Figure 3. Relationships between community similarity (Bray–Curtis) and best linear models (shown on x-axis), for taxa with low, moderate and high dispersal ability. Regression lines are shown where the slope is significant (P < 0·05) and r2 > 0·10. sd = standard deviation, av = average. For units see Tables 1 and 2.
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Figure 4. Akaike Information Criterion (AIC) values for models predicting community similarity for grazers, predators, all taxa, and taxa with low, moderate and high dispersal abilities. Lower AIC values indicate a better fitting model. The results for the best models incorporating distance only, ecological factors only and both sets of predictors are shown (see Fig. 3 for model parameters).
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Our results are consistent with predictions of neutral theory and a role for local ecological conditions. Patterns of species occurrence and abundance were correlated with the spatial arrangement of sites and the conditions that were present at each. Grazer communities (the numerically dominant component of these streams) were most strongly correlated with a combined model of local ecological conditions and spatial distance, followed by local ecology alone then spatial distance alone. In contrast, the predatory component of the community was most strongly correlated with ecological factors alone followed by the combined model. There was also evidence for an interaction with species’ dispersal ability. While the strongest correlation for taxa with moderate dispersal ability was with the combined model, taxa with low dispersal ability were most strongly correlated with spatial distance, and high dispersal taxa were weakly correlated with all models. Perhaps the latter taxa disperse over scales that exceed those in this study. A previous investigation of communities from a much wider range of sites throughout the Taieri catchment showed that geographical location was generally influential in accounting for community composition but not in the case of invertebrates with strongly flying adults (Townsend et al. 2003).
There have now been a series of studies reporting limited or no support for neutrality. The majority of these have concentrated on sessile organisms: rainforest trees (Clark & MacLachlan 2003; McGill 2003; Tuomisto, Ruokolainen & Yli-Halla 2003; Alonso & McKane 2004), grasses (Adler 2004), boreal forest (Alonso & McKane 2004), barnacles (Wootton 2005), understorey plants (Gilbert & Lechowicz 2004) and parasites (Poulin 2004). Sessile organisms operate under a set of constraints that may favour dispersal limitation and thus neutrality: they rely on broadcasting propagules into the environment, and the eventual site occupied is strongly dependent on the initial settlement site. Sessile organisms are also often limited by space, so that lottery effects of establishment may predominate, and many (such as rainforest trees or grasses) may be considered ecologically equivalent, apparently satisfying the requirements of neutral theory. Despite these tendencies, local ecological factors have generally been found to better predict sessile communities than neutrality. Our study incorporated mobile organisms that may have greater control over where in the landscape they and their offspring occur. Aquatic insects can select suitable habitat by choosing oviposition sites (e.g. Timm 1994; Winterbourn 2003) or by habitat selection as larvae (e.g. Holomuzki & Messier 1993; Townsend et al. 1997b). For that reason we expected that associations between local ecological conditions and macroinvertebrate communities may be stronger than occur for sessile organisms. While we did find associations with ecological conditions, the strong role indicated for spatial separation of sites suggests that on this scale dispersal limitation is important even for highly mobile organisms.
Scale, as in other areas of ecology, has become an increasingly important consideration with regard to neutrality (Adler 2004; Alonso & McKane 2004). Given the importance of dispersal in neutral theory, the scale of investigation can be expected to affect whether neutral patterns are observed. Some rigorous tests of neutral theory have been carried out on relatively small spatial scales (1–10 km) (Adler 2004; Gilbert & Lechowicz 2004). However, Alonso & McKane (2004) raised the contention that neutral theory may be valid only at extremely large spatial scales. We attempted to assess whether dispersal limitation was a relevant factor at the scale of this study by incorporating dispersal ability in the analysis. It may be expected that species with poor dispersal may be influenced to a greater degree by neutrality than those with high dispersal. Our results were consistent with this – the slope of the negative relationship between spatial separation and community similarity was steepest for low dispersal species, less steep for moderate dispersal species and nonsignificant for high dispersal species. The moderate dispersal group was also more strongly influenced by local ecological conditions than the low and high dispersal groups. The biological trait ‘dispersal ability’ deserves to be incorporated into future tests of neutral theory. In fact, we suggest that suitably designed studies at an appropriate scale may reveal a role for dispersal limitation, along with local conditions, even in plant and other sessile communities.
Neutral theory relates to within-trophic level diversity (Poulin 2004). Therefore our test of the theory for an entire invertebrate community goes beyond that imagined by Hubbell (2001). Despite this, the entire community showed evidence of a negative relationship between spatial separation and community similarity. This is likely due to aerial dispersal being the primary means of reaching different locations. It is also probable that lottery effects that favour the founding of populations in a particular location may cause the development of local nodes of abundance for some species. The apparent strong effect of dispersal on species in this study is not surprising given the nature of the communities. For instance, many of the predatory species show high dietary overlap (Thompson & Townsend 2004), are taxonomically closely related (primarily occurring in the trichopteran family Rhyacophilidae), and are morphologically difficult to distinguish (R. Thompson pers. obs.). These species are likely to be largely functionally equivalent and therefore ‘exchangeable’ in communities as stochastic events remove species. The effect of phylogenetic relatedness in determining the role to which species compete and coexist is worthy of attention in future studies. High degrees of phylogenetic relatedness within communities may favour ecological equivalence and therefore increase the relative importance of neutral factors.
The finding that dispersal limitation is an important factor in determining community structure in these streams cannot, in isolation, be taken as confirmation that neutral theory is correct. Bell (2000) emphasized that neutral patterns (i.e. random accumulations of differences between sites) may result from non-neutral processes and showed (Bell 2001) that metapopulation dynamics can provide neutral type patterns through populations ‘blinking in and out’ at a landscape scale as local extinctions and recolonizations take place. This scenario does not require the explicit assumptions of neutrality. Distinguishing between explanations is likely to require a direct assessment of life-history traits, such as individual reproductive success, that underpin the neutral model (sensuWootton 2005). We can also not rule out the possibility that differences in the invertebrate communities result from an unmeasured ecological factor that was correlated with distance. Two things appear to make this unlikely, (1) there is no readily identifiable unmeasured ecological factor, and (2) it seems unlikely that this factor would be correlated with distance when no other ecological factor in the analysis was.
Given that neutral theory alone cannot explain species-abundance relationships in this data set, can we integrate some of the assumptions of neutrality into a niche-based framework? Sophisticated niche assembly models have already been generated that explain species–abundance patterns well (Mouillot, George-Nascimento & Poulin 2003; Sugihara et al. 2003; Tilman 2004). Of these, the hierarchical niche model (Sugihara et al. 2003), like the neutral model, requires underlying generalizations (such as constant variance) that we know are unlikely to be true. Like the neutral model, however, it also incorporates processes whose importance is supported by our results, such as the interaction between multiple ecological factors to generate a niche. The manner in which niche and neutral models interact provides a rich opportunity for mathematicians, modellers and empirical scientists to collaborate. The production of a synthetic model incorporating neutrality and niche assembly has already been attempted (Etienne & Oliff 2004; Schwilk & Ackerley 2005). A continuation of this process needs to take into account the results presented here – that trophic groupings and species traits are important factors in determining the weighting of niche and neutral factors.
The literature addressing neutral theory has largely been phrased in terms of either fully accepting or fully rejecting the theory. In part this is due to the way in which the original theory was established – complete neutrality provides no room for any of the processes that niche theory relies upon. On the other hand, the important processes that underlie neutral theory – dispersal limitation, stochastic loss and speciation – have largely been ignored by community ecologists entrenched in a niche paradigm (but see Ricklefs & Schluter 1993). If neutral theory is treated as an idealization of the real world (in much the same way that many physical laws are unrealistic idealizations) then many of its unrealistic assumptions become acceptable (Harte 2003), and incorporating other theories such as niche theory to explain variability about the idealization becomes conceptually tenable. The current results are compatible with both neutral theory and niche theory: dispersal limitation apparently contributes to differences in local community structure, as do differences in local ecological conditions. These results clearly show that local ecological conditions play a part in determining local patterns of macroinvertebrate abundance and diversity. However, the simultaneous influence of spatial distance in determining patterns indicates an equally important role for dispersal limitation. It is no longer a matter of neutral theory or niche theory, but how they operate together.