Dataset Information

Drainage network position and historical connectivity explain global patterns in freshwater fishes' range size.

ABSTRACT: Identifying the drivers and processes that determine globally the geographic range size of species is crucial to understanding the geographic distribution of biodiversity and further predicting the response of species to current global changes. However, these drivers and processes are still poorly understood, and no ecological explanation has emerged yet as preponderant in explaining the extent of species' geographical range. Here, we identify the main drivers of the geographic range size variation in freshwater fishes at global and biogeographic scales and determine how these drivers affect range size both directly and indirectly. We tested the main hypotheses already proposed to explain range size variation, using geographic ranges of 8,147 strictly freshwater fish species (i.e., 63% of all known species). We found that, contrary to terrestrial organisms, for which climate and topography seem preponderant in determining species' range size, the geographic range sizes of freshwater fishes are mostly explained by the species' position within the river network, and by the historical connection among river basins during Quaternary low-sea-level periods. Large-ranged fish species inhabit preferentially lowland areas of river basins, where hydrological connectivity is the highest, and also are found in river basins that were historically connected. The disproportionately high explanatory power of these two drivers suggests that connectivity is the key component of riverine fish geographic range sizes, independent of any other potential driver, and indicates that the accelerated rates in river fragmentation might strongly affect fish species distribution and freshwater biodiversity.

SUBMITTER: Carvajal-Quintero J

PROVIDER: S-EPMC6613146 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Drainage network position and historical connectivity explain global patterns in freshwater fishes' range size.

Carvajal-Quintero Juan J Villalobos Fabricio F Oberdorff Thierry T Grenouillet Gaël G Brosse Sébastien S Hugueny Bernard B Jézéquel Céline C Tedesco Pablo A PA

Proceedings of the National Academy of Sciences of the United States of America 20190617 27

Identifying the drivers and processes that determine globally the geographic range size of species is crucial to understanding the geographic distribution of biodiversity and further predicting the response of species to current global changes. However, these drivers and processes are still poorly understood, and no ecological explanation has emerged yet as preponderant in explaining the extent of species' geographical range. Here, we identify the main drivers of the geographic range size variat ...[more]

PMID: 31209040

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Project description:Understanding the spatial pattern of species distributions is fundamental in biogeography, and conservation and resource management applications. Most species distribution models (SDMs) require or prefer species presence and absence data for adequate estimation of model parameters. However, observations with unreliable or unreported species absences dominate and limit the implementation of SDMs. Presence-only models generally yield less accurate predictions of species distribution, and make it difficult to incorporate spatial autocorrelation. The availability of large amounts of historical presence records for freshwater fishes of the United States provides an opportunity for deriving reliable absences from data reported as presence-only, when sampling was predominantly community-based. In this study, we used boosted regression trees (BRT), logistic regression, and MaxEnt models to assess the performance of a historical metacommunity database with inferred absences, for modeling fish distributions, investigating the effect of model choice and data properties thereby. With models of the distribution of 76 native, non-game fish species of varied traits and rarity attributes in four river basins across the United States, we show that model accuracy depends on data quality (e.g., sample size, location precision), species' rarity, statistical modeling technique, and consideration of spatial autocorrelation. The cross-validation area under the receiver-operating-characteristic curve (AUC) tended to be high in the spatial presence-absence models at the highest level of resolution for species with large geographic ranges and small local populations. Prevalence affected training but not validation AUC. The key habitat predictors identified and the fish-habitat relationships evaluated through partial dependence plots corroborated most previous studies. The community-based SDM framework broadens our capability to model species distributions by innovatively removing the constraint of lack of species absence data, thus providing a robust prediction of distribution for stream fishes in other regions where historical data exist, and for other taxa (e.g., benthic macroinvertebrates, birds) usually observed by community-based sampling designs.

Dataset Information

Drainage network position and historical connectivity explain global patterns in freshwater fishes' range size.

Publications

Drainage network position and historical connectivity explain global patterns in freshwater fishes' range size.

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