as sinks. However, movement out of favorable source areas, which generally occurred during high-flow events, is also the mechanism whereby newly created Beaver ponds can be colonized by fishes, so there are potential advantages for movement out of areas with high population densities.
The distribution of Bayou Darters in Bayou Pierre of western Mississippi, with juvenile and adult fish occurring in discrete riffle patches (Figure 4.2) and not in intervening pools, suggested that Bayou Darters might comprise a linear metapopulation. Because a primary tenet of a metapopulation is movement among patches, Slack et al. (2004) first demonstrated that larval drift was occurring, such that larvae produced in an upstream patch could supply a downstream patch. Next, they tested the hypothesis that patches of riffle habitat lower in the stream system, where the substratum was softer and particle size generally smaller, functioned as sinks and that they were supplied by more upstream source areas (Ross et al. 2001; Slack et al. 2004). Although densities of Bayou Darters were greater in more upstream riffles, downstream riffles also supported Bayou Darters. The source-sink hypothesis was tested indirectly by comparing the age structure and somatic condition of the fish. In a sink, populations would be expected to have an altered age structure with fewer old individuals because of increased mortality. In fact, there were no differences in age structure between upstream and downstream riffles, with both supporting age-0 to age-3 fish in approximately the same proportions. Body condition also did not differ between upstream and downstream riffles. The data are consistent with a linear metapopulation model, but although apparent riffle quality is lower in downstream riffles, predictions of a source-sink hypothesis were not supported.
RELATING ASSEMBLAGES TO THE ENVIRONMENT
Conceptual and Statistical Models
Various conceptual and/or statistical models have been proposed relating the primary structure of assemblages (i.e., species presence and/or relative abundance), emergent assemblage structure (i.e., species richness, diversity, assemblage complexity, and trophic relationships), or ecological/life-history traits of species to environmental factors (Marsh-Matthews and Matthews 2000). Such models provide insight into how fish assemblages are formed and maintained. At the risk of oversimplification, these models can be placed into two groups: (1) conceptually based a priori approaches where general features of the habitat are used to make predictions of ecological traits of species or assemblages, or (2) databased a posteriori approaches where species occurrences and/or abundances are related to habitat features, using some type of univariate or multivariate analysis. In contrast to the first group, which is based on a mechanistic understanding of how communities operate, this second approach is largely nonmechanistic.
A Priori Models
There are three principal conceptual models (e.g., a set of predictions arising from basic ecological principles) that are prevalent in the literature on lotic systems relating species traits or the emergent structure of assemblages to general environmental features (Goldstein and Meador 2004)—habitat templates (Southwood 1977), landscape filters (Poff 1997), and the river continuum concept (Vannote et al. 1980).
Habitat Template
In 1977 and 1988, Southwood suggested that the habitat is a template providing a predictive pattern for the evolutionary assembly of communities and life-history traits thereof, much like the periodic table of elements in chemistry. A key presumption is that the present-day ecological traits of the organisms will match the current ecological conditions, which, as previous chapters have suggested, is not always the case. Although very much aware of the importance of historical factors, Townsend and Hildrew (1994) set out to develop testable predictions of the habitat template model for species as well as assemblage traits. They used two axes, temporal habitat heterogeneity and spatial heterogeneity, in developing predictions of how species traits (e.g., reproductive type, age and size, parental care, movement, etc.) or assemblage traits (e.g., importance of biotic interactions) would respond to the habitat template (Figure 4.4). They viewed temporal heterogeneity as primarily a measure of the frequency of disturbance and habitat heterogeneity as primarily a measure of the availability of refugia. Thus as disturbance increases, the availability of refugia would become more important. Their model was developed with the Rhône River drainage, France, in mind as a testing arena, but the general constructs should apply to other systems, both lentic and lotic. For instance, considering the species trait of life span, the model would predict that life span should be short on the unstable side of the template (Figure 4.4) and long or short on the stable side (see also Chapter 9). Similarly, body size should be small on the unstable side and large or small on the stable side. In terms of assemblage characteristics, the more stable and complex habitats on the left side should lead to greater specialization in resource use, greater importance of biotic interactions, and increased potential for coevolution. The unstable and low complexity habitats on the right side should favor more generalists in resource use, as well as little potential for biotic interactions or coevolution.
Tests of the species-trait predictions of Townsend and Hildrew’s habitat template model have been equivocal. For instance, an important prediction is that species traits such as body size and parental care should decrease in environments with low spatial heterogeneity and high temporal heterogeneity—the lower right side of the figure. Tests of these and other predictions based on the responses of 13 taxonomic groups of plants and animals occurring in the Rhône River drainage resulted in only mixed support, and support for fishes in this system was totally lacking (Resh et al. 1994). However, Resh et al. (1994) pointed out that the large preexisting data set used to test the predictions might have had methodological limitations that precluded a fair test of the model. Also, the occurrence of species in a habitat might reflect more of chance movement rather than actual habitat selection—resulting in a blurring of the match between species traits and the nature of the habitat.
FIGURE 4.4. The habitat template model showing relationships of species or assemblage traits to the frequency of disturbance and complexity of the physical habitat. The large shaded triangles show areas of different predicted traits. The dashed line shows the transition points between traits on the upper left and lower right. The transition can shift to the left for short-lived species and to the right for long-lived species. Adapted from Resh et al. (1994) and Townsend and Hildrew (1994).
Studies of northern U.S. midwestern streams (Poff and Allan 1995), and comparisons of functional convergence between European and eastern North American fish assemblages (Lamouroux et al. 2002), offer somewhat stronger support for the habitat template model—at least in terms of assemblage predictions. For instance, Poff and Allan (1995) found that two predictions of the habitat template model—variable habitats should contain more resource generalists and nonvarying habitats should contain more specialists (cf. Figure 4.4)—were supported for stream fish assemblages. Hydrologic variables used by Poff and Allan (1995) included flow predictability and variation, base flow stability, and frequency of spates.
Landscape Filters
Recognizing that assemblages are the end products of “interacting multiple causes” at “multiple spatial and temporal scales,” Poff (1997) proposed that functional attributes of species in assemblages are shaped by a hierarchical series of landscape filters that include both physicochemical and biotic factors. A particular community thus comprises species possessing the appropriate ecological “shapes” to have passed through the filters. The heuristic model presented earlier (see figure in Part 2) is similar to this approach. Key elements in the operation of Poff’s landscape filters are categorical niches, defined as discrete levels of species requirements along a given resource axis, and categorical filters, defined as the strength or resistance of a filter in allowing species to pass through it. The combination of categorical filter strength with the categorical niche determines the probabilities for a species to pass
