Disentangling the importance of ecological niches from stochastic processes across scales

Abstract

Deterministic theories in community ecology suggest that local, niche-based processes, such as environmental filtering, biotic interactions and interspecific trade-offs largely determine patterns of species diversity and composition. In contrast, more stochastic theories emphasize the importance of chance colonization, random extinction and ecological drift. The schisms between deterministic and stochastic perspectives, which date back to the earliest days of ecology, continue to fuel contemporary debates (e.g. niches versus neutrality). As illustrated by the pioneering studies of Robert H. MacArthur and co-workers, resolution to these debates requires consideration of how the importance of local processes changes across scales. Here, we develop a framework for disentangling the relative importance of deterministic and stochastic processes in generating site-to-site variation in species composition (β-diversity) along ecological gradients (disturbance, productivity and biotic interactions) and among biogeographic regions that differ in the size of the regional species pool. We illustrate how to discern the importance of deterministic processes using null-model approaches that explicitly account for local and regional factors that inherently create stochastic turnover. By embracing processes across scales, we can build a more synthetic framework for understanding how niches structure patterns of biodiversity in the face of stochastic processes that emerge from local and biogeographic factors.

Figure 1.

Predicted change in β-diversity along (a,b) spatial and (c,d) environmental gradients for a completely (a,c) stochastic (neutral) and (b,d) deterministic (niche-based) models of community assembly. Here, β-diversity represents the dissimilarity in species composition between pairs of communities. Figure modified from [95].

Figure 2.

Hypothetical depiction of how β-diversity (Jaccard's dissimilarity) should vary as α-diversity changes within a given species pool. When α-diversity is very low relative to the pool, dissimilarity is expected by random chance to be very high, and when α-diversity is high relative to the size of the pool, dissimilarity is expected to be very low. This relationship is depicted by the solid line (modified from [104]). The star represents the expected dissimilarity at one value of α-diversity, and the arrows pointing in different directions indicate hypothetical cases where some environmental factor either decreases (pointing to the left) or increases (pointing to the right) α-diversity. In each case, measured values of dissimilarity that are not significantly different from the null expectation (points labelled with i) would indicate that community assembly is completely stochastic. This contrasts with measured values of dissimilarity that are higher than expected (points labelled with ii) and lower than expected (points labelled with iii), each indicating some degree of determinism in community structure. The magnitude of the deviations from the null expectation can provide insights into whether the relative importance of deterministic processes varies along ecological gradients that might influence α-diversity.

Figure 3.

The influence of regional species pools on the signature of deterministic processes (niche selection) in different biogeographic regions. The figure shows three hypothetical examples in which regional sampling effects influence the relationship between niche selection and the size of the regional species pool. In (a), niche selection does not vary with increasing regional pool size in nature (solid line, actual), but stronger regional sampling effects in high-diversity regions (i.e. region B relative to region A) result in an observed pattern (dashed line, observed) where niche selection decreases with regional pool size. In (b), niche selection decreases with increasing regional pool size in nature (e.g. via stronger ecological drift in regions with more rare species), but stronger regional sampling effects in high-diversity regions result in an observed pattern where the negative correlation is steeper. By contrast, in (c), niche selection increases with increasing regional pool size (e.g. via more species sorting in high-diversity regions), but stronger sampling effects in high-diversity regions result in no observed correlation. In all cases, it is necessary to account for differences in the regional sampling effect (e.g. using a null-model approach) before comparing the relative importance of niche selection among biogeographic regions. For simplicity, we have only plotted linear relationships between niche selection and regional pool size, while recognizing that nonlinear relationships may exist in empirical datasets.