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Broad-scale determinants of non-native fish species richness are context-dependent.

ABSTRACT: Identifying the factors determining the non-native species richness (NNSR) in a given area is essential for preventing species invasions. The relative importance of human-related and natural factors considered for explaining NNSR might depend upon both the spatial scale (i.e. the extent of the gradients sampled) and the historical context of the area surveyed. Here, using a worldwide database of freshwater fish occurrences, we tested whether the relative influence of human and ecological determinants of non-native fish species establishment at the scale of the biogeographic realm was consistent (i) with that observed worldwide, and (ii) among the different biogeographical realms. The prominent role of human activity in shaping the global (i.e. worldwide) pattern of NNSR cannot be directly extrapolated to the biogeographic realms. Furthermore, the relationships between human and ecological determinants and NNSR vary strikingly across biogeographic realms, revealing a strong context dependency of the determinants of NNSR. In particular, the human-related factors play a predominant role in explaining the establishment of non-native species in economically developed realms, while in the other realms environmental characteristics of the river basins best explained geographical patterns of NNSR. In the face of future biological invasions, considering both the spatial scale and the historical context of the surveyed area is crucial to adopt effective conservation strategies.

SUBMITTER: Blanchet S

PROVIDER: S-EPMC2690461 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

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Broad-scale determinants of non-native fish species richness are context-dependent.

Blanchet Simon S Leprieur Fabien F Beauchard Olivier O Staes Jan J Oberdorff Thierry T Brosse Sébastien S

Proceedings. Biological sciences 20090325 1666

Identifying the factors determining the non-native species richness (NNSR) in a given area is essential for preventing species invasions. The relative importance of human-related and natural factors considered for explaining NNSR might depend upon both the spatial scale (i.e. the extent of the gradients sampled) and the historical context of the area surveyed. Here, using a worldwide database of freshwater fish occurrences, we tested whether the relative influence of human and ecological determi ...[more]

PMID: 19324737

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Project description:AimMapping the geographic distribution of non-native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to single species, due to the challenges of data acquisition at larger scales. Here, we map the distribution of non-native freshwater species richness across the continental United States and investigate the role of human activity in driving macro-scale patterns of aquatic invasion.LocationThe continental United States.MethodsWe assembled maps of non-native aquatic species richness by compiling occurrence data on exotic animal and plant species from publicly accessible databases. Using a dasymetric model of human population density and a spatially explicit model of recreational freshwater fishing demand, we analysed the effect of these metrics of human influence on the degree of invasion at the watershed scale, while controlling for spatial and sampling bias. We also assessed the effects that a temporal mismatch between occurrence data (collected since 1815) and cross-sectional predictors (developed using 2010 data) may have on model fit.ResultsNon-native aquatic species richness exhibits a highly patchy distribution, with hotspots in the Northeast, Great Lakes, Florida, and human population centres on the Pacific coast. These richness patterns are correlated with population density, but are much more strongly predicted by patterns of recreational fishing demand. These relationships are strengthened by temporal matching of datasets and are robust to corrections for sampling effort.Main conclusionsDistributions of aquatic non-native species across the continental US are better predicted by freshwater recreational fishing than by human population density. This suggests that observed patterns are driven by a mechanistic link between recreational activity and aquatic non-native species richness and are not merely the outcome of sampling bias associated with human population density.

Project description:Estimates of spatial patterns of broad-scale species richness are central to major questions in ecology, evolution and conservation. Yet, they are scarce due to incomplete information on species distributions. Often the only germane data derives from museum specimens collected during non-standardized sampling. Rarefaction, a promising approach to estimate broad-scale richness with these data, estimates the expected number of species represented in subsets of n specimens drawn from N specimens collected in a sampling unit. One version of rarefaction, known as individual-based rarefaction, assumes that the N specimens collected in a sampling unit constitute a random sample of individuals in that sampling unit. Another version, known as spatially explicit rarefaction, assumes that the N specimens collected in a sampling unit are spatially aggregated. We examined the working hypothesis that, when applied to museum specimen data, spatially explicit rarefaction is less biased than individual-based rarefaction because it reduces overestimation due to spatially aggregated sampling. We derived five predictions from this working hypothesis and tested them using computer simulation experiments based on a database of 129,782 plant specimens from Nicaragua, and sampling units of 5 x 5, 50 x 50, and 100 x 100 km. One experiment was a negative control, whereby we simulated collection of randomly chosen individuals from each sampling unit. In contrast, three other experiments included spatially aggregated sampling. In all experiments we applied individual-based and spatially explicit rarefaction to estimate richness, with n = 200 and n = 500 specimens. As expected, the experiment designed as a negative control did not support the working hypothesis. The other three experiments supported the working hypothesis in analyses of larger sampling units, but not in 5 x 5 km sampling units. The predictions we derived from the working hypothesis can be used to assess which rarefaction version is best in particular systems.

Dataset Information

Broad-scale determinants of non-native fish species richness are context-dependent.

Publications

Broad-scale determinants of non-native fish species richness are context-dependent.

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