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Leroy, B., Dias, M. S., Giraud, E., Hugueny, B., Jezequel, C., Leprieur, F., et al. (2019). Global biogeographical regions of freshwater fish species. J. Biogeogr., .
Résumé: Aim To define the major biogeographical regions and transition zones for freshwater fish species. Taxon Strictly freshwater species of actinopterygian fish (i.e. excluding marine and amphidromous fish families). Methods We based our bioregionalization on a global database of freshwater fish species occurrences in drainage basins, which, after filtering, includes 11,295 species in 2,581 basins. On the basis of this dataset, we generated a bipartite (basin-species) network upon which we applied a hierarchical clustering algorithm (the Map Equation) to detect regions. We tested the robustness of regions with a sensitivity analysis. We identified transition zones between major regions with the participation coefficient, indicating the degree to which a basin has species from multiple regions. Results Our bioregionalization scheme showed two major supercontinental regions (Old World and New World, 50% species of the world and 99.96% endemics each). Nested within these two supercontinental regions lie six major regions (Nearctic, Neotropical, Palearctic, Ethiopian, Sino-Oriental and Australian) with extremely high degrees of endemism (above 96% except for the Palearctic). Transition zones between regions were of limited extent compared to other groups of organisms. We identified numerous subregions with high diversity and endemism in tropical areas (e.g. Neotropical), and a few large subregions with low diversity and endemism at high latitudes (e.g. Palearctic). Main conclusions Our results suggest that regions of freshwater fish species were shaped by events of vicariance and geodispersal which were similar to other groups, but with freshwater-specific processes of isolation that led to extremely high degrees of endemism (far exceeding endemism rates of other continental vertebrates), specific boundary locations and limited extents of transition zones. The identified bioregions and transition zones of freshwater fish species reflect the strong isolation of freshwater fish faunas for the past 10-20 million years. The extremely high endemism and diversity of freshwater fish fauna raises many questions about the biogeographical consequences of current introductions and extinctions.
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Lezama-Ochoa, A., Grados, D., Lebourges Dhaussy, A., Irigoien, X., Chaigneau, A., & Bertrand, A. (2015). Biological characteristics of the hydrological landscapes in the Bay of Biscay in spring 2009. Fisheries Oceanography, 24(1), 26–41.
Résumé: In the present study we investigated the biogeography of macrozooplankton and fish biomass in the Bay of Biscay. In this region, we defined six different landscapes based on the hydrogeographical characteristics observed in spring 2009. We then related landscape's characteristics and environmental parameters such as light attenuation depth and chlorophyll-a with macrozooplankton and fish acoustic biomass. Hydrodynamic structures together with coastal influences (river discharges, predation pressure and depth preference) and vertical thermohaline structure/mixing (feeding modes and ability to stay in preferred layers) appeared as the main factors determining the biological distribution. Besides, variance partitioning was used to assess the respective roles played by the hydrological environment, the geographical space and the biological environment alone, and their interactions. Results revealed that: (i) macrozooplankton and fish have a preference for different hydrogeographical landscapes; (ii) the association between hydrological conditions and geographical features, i.e. the spatial structure of the hydrological environment, plays a key role in the distribution of macrozooplankton; and (iii) prey-predator relationships have to be taken into account to provide a comprehensive characterization of habitat suitability.
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Marr, S. M., Olden, J. D., Leprieur, F., Arismendi, I., Ćaleta, M., Morgan, D. L., et al. (2013). A global assessment of freshwater fish introductions in mediterranean-climate regions. Hydrobiologia, , 1–13.
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Matthews, T. J., Triantis, K. A., Rigal, F., Borregaard, M. K., Guilhaumon, F., & Whittaker, R. J. (2016). Island species–area relationships and species accumulation curves are not equivalent: an analysis of habitat island datasets. Global Ecology and Biogeography, 25(5), 607–618.
Résumé: Aim The relationship between species number and area is of fundamental importance in macroecology and conservation science, yet the implications of different means of quantitative depiction of the relationship remain contentious. We set out (1) to establish the variation in form of the relationship between two distinct methods applied to the same habitat island datasets, (2) to explore the relevance of several key dataset properties for variation in the parameters of these relationships, and (3) to assess the implications for application of the resulting models. Locations Global. Methods Through literature search we compiled 97 habitat island datasets. For each we analysed the form of the island species–area relationship (ISAR) and several versions of species accumulation curve (SAC), giving priority to a randomized form (Ran-SAC). Having established the validity of the power model, we compared the slopes (z-values) between the ISAR and the SAC for each dataset. We used boosted regression tree and simulation analyses to investigate the effect of nestedness and other variables in driving observed differences in z-values between ISARs and SACs. Results The Ran-SAC was steeper than the ISAR in 77% of datasets. The differences were primarily driven by the degree of nestedness, although other variables (e.g. the number of islands in a dataset) were also important. The ISAR was often a poor predictor of archipelago species richness. Main conclusions Slopes of the ISAR and SAC for the same data set can vary substantially, revealing their non-equivalence, with implications for applications of species–area curve parameters in conservation science. For example, the ISAR was a poor predictor of archipelagic richness in datasets with a low degree of nestedness. Caution should be employed when using the ISAR for the purposes of extrapolation and prediction in habitat island systems.
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Matthews, T. J., Triantis, K. A., Whittaker, R. J., & Guilhaumon, F. (2019). sars: an R package for fitting, evaluating and comparing species-area relationship models. Ecography, 42(8), 1446–1455.
Résumé: The species-area relationship (SAR) constitutes one of the most general ecological patterns globally. A number of different SAR models have been proposed. Recent work has shown that no single model universally provides the best fit to empirical SAR datasets: multiple models may be of practical and theoretical interest. However, there are no software packages available that a) allow users to fit the full range of published SAR models, or b) provide functions to undertake a range of additional SAR-related analyses. To address these needs, we have developed the R package 'sars' that provides a wide variety of SAR-related functionality. The package provides functions to: a) fit 20 SAR models using non-linear and linear regression, b) calculate multi-model averaged curves using various information criteria, and c) generate confidence intervals using bootstrapping. Plotting functions allow users to depict and scrutinize the fits of individual models and multi-model averaged curves. The package also provides additional SAR functionality, including functions to fit, plot and evaluate the random placement model using a species-sites abundance matrix, and to fit the general dynamic model of oceanic island biogeography. The 'sars' R package will aid future SAR research by providing a comprehensive set of simple to use tools that enable in-depth exploration of SARs and SAR-related patterns. The package has been designed to allow other researchers to add new functions and models in the future and thus the package represents a resource for future SAR work that can be built on and expanded by workers in the field.
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