The Amazon catchment is the largest river basin on earth, and up to 30% of its waters flow across floodplains. In its open waters, floating plants known as floating meadows abound. They can act as vectors of dispersal for their associated fauna and, therefore, can be important for the spatial structure of communities. Here, we focus on amphibian diversity in the Amazonian floating meadows over large spatial scales. We recorded 50 amphibian species over 57 sites, covering around 7,000 km along river courses. Using multi-site generalised dissimilarity modelling of zeta diversity, we tested Hanski’s core-satellite (HCS) hypothesis and identified the existence of two functional groups of species operating under different ecological processes in the floating meadows. ‘Core’ species are associated with floating meadows, while ‘satellite’ species are associated with adjacent environments, being only occasional or accidental occupants of the floating vegetation. At large scales, amphibian diversity in floating meadows is mostly determined by stochastic processes, whereas at regional scales, climate and deterministic processes are central drivers. Compared with the turnover of ‘core’ species, the turnover of ‘satellite’ species increases much faster with distances and is also controlled by a wider range of climatic features. Distance is not a limiting factor for ‘core’ species, suggesting that they have a stronger dispersal ability even over large distances. This is probably related to the existence of passive long-distance dispersal of individuals along rivers via vegetation rafts. In this sense, Amazonian rivers can serve as corridors, facilitating dispersal especially for species associated with riverine habitats such as floating meadows.

Zeta diversity, the number of species shared by multiple assemblages, is a novel concept and metric that unifies incidence-based diversity measures, patterns and relationships, turning into a propitious method for measuring biological diversity (Hui and McGeoch 2014, McGeoch et al. 2019). Integrating zeta diversity into Generalised Dissimilarity Modelling (Multi-Site Generalised Dissimilarity Modelling, MS-GDM) allows to understand the importance of environmental gradients and spatial distance in explaining the compositional turnover of the whole spectrum of species, from rare to common (Latombe et al. 2017, 2018a). In this sense, zeta diversity and MS-GDM become important tools to understand and describe the diversity patterns of amphibians in the Amazonian floodplains, allowing to shed light on the processes and drivers of these patterns. Moreover, given its very characteristics, MS-GDM provides a means to test whether common species (higher orders of zeta; largely ‘core’ species) operate under different rules/processes/mechanisms from rare species (lower orders of zeta; largely ‘satellite’ species), thus becoming an excellent tool to test the Hanski’s core-satellite (HCS) hypothesis (Hanski 1982, 1991; see also Hanski and Gyllenberg 1993). Zeta diversity and MS-GDM analyses were computed in R (R CoreTeam, 2018) using the zetadiv package v.1.1.1 (Latombe et al. 2018b, c). We provide here all scripts, codes and data used to run analyses.

References:

Hanski, I. 1982. Dynamics of regional distribution: the core and satellite species hypothesis. – Oikos 38: 210–221. 

Hanski, I. 1991. Single–species metapopulation dynamics: concepts, models and observations. – Biol. J. Linn. Soc. Lond. 42: 17–38.

Hanski, I. and Gyllenberg, M. 1993. Two general metapopulation models and the core–satellite species hypothesis. – Am. Nat. 142: 17–41.

Hui, C. and McGeoch, A. 2014. Zeta diversity as a concept and metric that unifies incidence-based biodiversity patterns. – Am. Nat. 184: 684–694.

Latombe, G., Hui, C. and McGeoch, M. A. 2017. Multi–Site Generalised Dissimilarity Modelling: using zeta diversity to differentiate drivers of turnover in rare and widespread species. – Methods Ecol. Evol. 8: 431–442. 

Latombe, G., McGeoch, M. A., Nipperess, D. and Hui, C. 2018a. zetadiv: an R package for computing compositional change across multiple sites, assemblages or cases. – bioRxiv, 324897.

Latombe, G., Richardson, D. M., Pyšek, P., Kučera, T. and Hui, C. 2018b. Drivers of species turnover vary with species commonness for native and alien plants with different residence times. – Ecology, 99(12), 2763–2775. 

Latombe, G., McGeoch, M. A., Nipperess, D. A. and Hui, C. 2018c. zetadiv: Functions to compute compositional turnover using zeta diversity. R package version 1. 1. 1. https://cran. r–project. org/package=zetadiv

McGeoch, M. A., Latombe, G., Andrew, N. R., Nakagawa, S., Nipperess, D. A., Roige, M., Marzinelli, E. M., Campbell, A. H., Verges, A., Thomas, T., Steinberg, P. D., Selwood, K. E. and Hui, C. 2019. Measuring continuous compositional change using decline and decay in zeta diversity. – Ecology 100: e02832.

R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www. R–project. org/