Knowledge of species specific ecological requirements is a prerequisite for successful conservation[1, 2], and for understanding biogeographic and phylogeographic patterns of extant taxa[3, 4]. Information on determinants of biodiversity patterns in ecological studies has often been derived from traditional regression methods. Generally, most of these methods focus on identifying the single best model, not on quantifying the independent explanatory power of the predictor variables, yet the latter is likely to provide important insights into the variables that should be managed to achieve desired conservation outcomes. Further, the performance of traditional regression methods is influenced by multicollinearity of explanatory variables as well as by outliers and missing data. These problems may result in the exclusion of ecologically more causal variables from the models, thus potentially biasing the actual relationships between species distributions and the environment.
There are a number of alternative statistical approaches that have been developed to improve predictive performance and provide reliable identification of explanatory variables that have the strongest influence on species distribution patterns. These techniques include hierarchical partitioning[6–8], variance partitioning and boosted regression trees (BRT). The ability of partitioning methods to address the problem of multicollinearity makes them more desirable approaches for ecological studies, because explanatory variables are often only nominally independent. BRT is a relatively new approach for modelling species-environment relationships. Advantages of BRT models include superior predictive performance compared to most traditional modelling methods, ability to handle different types of explanatory variables (data can be categorical, numeric or binary), ability to accommodate missing data, and they do not require elimination of outliers or prior data transformation. BRT models are insensitive to differing scales of measurement, and they can fit complex nonlinear relationships and interactions between predictors.
Despite the additional insights that may be gained from partitioning methods and boosted regression trees, these approaches have rarely been applied to the analysis of ecological data[11–15]. The present study applied BRT and hierarchical partitioning to provide insights into the important variables that influence the distribution of stream fishes from the Cape Floristic Region (CFR) of South Africa. The CFR is a hotspot for endemic freshwater biota[16–18]. This region’s high degree of endemism is thought to have resulted from its long period of isolation and complex evolutionary history, which promoted in situ diversification. However, the majority of the native stream fishes of the CFR rank amongst the most imperilled freshwater taxa in southern Africa. Nearly all native freshwater fishes of the CFR are already listed in threatened categories of the IUCN, because their historical distributions have declined as a result of multiple anthropogenic impacts, mainly hydrological modifications, degradation of habitats and widespread invasion of the rivers by at least 15 alien fish species[19–22]. These impacts have collectively resulted in several local extinctions in a number of mountain tributaries and extirpation of almost all main-stem populations of native freshwater fishes. The remaining native fish populations persist only in undisturbed headwater tributaries, often above in-stream physical barriers that prevent upstream migration of alien invasive fishes.
Detailed understanding of natural variation of species is essential for predicting past distribution patterns, assessing conservation status, projecting potential impacts of environmental changes, designing and prioritizing conservation areas and formulating recovery programs for threatened species. Such information should best be generated from undisturbed or minimally disturbed systems. The near-natural condition of upland tributaries of the Breede River system in the south-western CFR offered a unique opportunity to study the factors that influence the distribution of stream fishes in the absence of major confounding impacts such as pollution, sedimentation and alien fishes. The Breede River system was previously thought to contain only four indigenous primary freshwater fishes, currently Galaxias zebratus, Pseudobarbus burchelli, Sandelia capensis and Barbus andrewi[28, 29]. Molecular studies have, however, discovered four deeply divergent genetic lineages within G. zebratus, three historically isolated lineages within P. burchelli and three lineages of S. capensis in the Breede River system[30–32], Chakona et al., in preparation. Taxonomic revision of these groups is underway and some of the lineages will be described as distinct species. This study assessed one lineage of Galaxias zebratus, one of Pseudobarbus burchelli and two lineages of Sandelia capensis that co-occur in a number of undisturbed or near-natural mountain tributaries of the Breede River system. Galaxias ‘nebula’ (~ 75 mm total length (TL)) has a slender body form and Pseudobarbus ‘Breede’ (~ 135 mm TL) is fusiform with forked caudal fins. The two Sandelia spp. lineages (~ 200 mm TL) are genetically closely related and have laterally compressed body form. They were therefore combined in all analyses and comparisons. Barbus andrewi was not included in the present study because it was only found at two riverine localities. This species now persists in two man made dams in the Breede River catchment.
Specifically, the study addressed three questions: (i) what are the main environmental determinants of the spatial distributions of stream fishes in the CFR? (ii) are there differences in the main determinants of distribution among species? (iii) are the results of BRT and hierarchical partitioning in concordance?
One potential source of differences in the distribution patterns and environmental relationships between stream fishes is differing body morphologies. Freshwater fishes exhibit high morphological divergence, suggesting that they evolved to exploit specific habitats that differ in their environmental stressors[33, 34]. The fishes considered in this study have distinct body forms [Additional file1. It was hypothesised that Sandelia spp. would be mainly associated with lower river reaches because fishes with laterally compressed bodies are generally adapted to life in slow flowing waters. Pseudobarbus ‘Breede’ were predicted to be capable of exploiting stream reaches with faster flowing waters because fishes with forked tails are generally considered to have improved swimming performance[36, 37]. Galaxias ‘nebula’ were hypothesised to be capable of exploiting reaches at higher elevation because anguilliform and slender bodied fishes are expected to have reduced energetic expenditure necessary to maintain position in faster flowing water[34, 36].