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Assessing competition among species through simultaneously modeling marginal counts and respective proportions

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Abstract

Evolution processes of multiple competitive and non-competitive species have traditionally been handled using different methods. In particular, evolution processes of multiple competitive species have usually been evaluated by the continuous and discrete proportions analysis; however, such evolution processes cannot be solely characterized by their relative proportions in practice. In this paper, we introduce a community based Poisson model with multivariate random effects to explicitly characterize marginal counts and respective proportions simultaneously. Furthermore, our method provides a unified approach to handle evolution processes of competitive and non-competitive species. In fact, the existence and strength of the competition among species can be assessed through our approach. Unlike those marginal modelling methods, our approach explicitly predicts random effects. Our model inference does not rely on distributional assumption of observed multivariate random effects, and thus is more robust than traditional approaches assuming parametric random effects.

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Acknowledgements

This research was supported in part by grants from the National Natural Science Foundation of China (11501073), the talents for scientific research project of Guizhou University of Finance and Economics (2018YJ104), the Natural Sciences and Engineering Research Council of Canada, the Atlantic Association for Research in the Mathematical Sciences and the postdoctoral fellowships from the Canadian Statistical Sciences Institute. The authors thank the associate editor and three referees for their helpful comments that greatly improved the presentation of these results.

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Correspondence to Renjun Ma.

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Handling Editor: Bryan F. J. Manly

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Duan, X., Ma, R. Assessing competition among species through simultaneously modeling marginal counts and respective proportions. Environ Ecol Stat 28, 35–52 (2021). https://doi.org/10.1007/s10651-020-00472-2

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  • DOI: https://doi.org/10.1007/s10651-020-00472-2

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