Upscaling Species Richness and Abundances in Tropical Forests. Tovo, A., Suweis, S., Formentin, M., Favretti, M., Volkov, I., Banavar, J. R., Azaele, S., & Maritan, A. 3(10):e1701438+.
Upscaling Species Richness and Abundances in Tropical Forests [link]Paper  doi  abstract   bibtex   
The quantification of tropical tree biodiversity worldwide remains an open and challenging problem. More than two-fifths of the number of worldwide trees can be found either in tropical or in subtropical forests, but only ≈0.000067\,% of species identities are known. We introduce an analytical framework that provides robust and accurate estimates of species richness and abundances in biodiversity-rich ecosystems, as confirmed by tests performed on both in silico-generated and real forests. Our analysis shows that the approach outperforms other methods. In particular, we find that upscaling methods based on the log-series species distribution systematically overestimate the number of species and abundances of the rare species. We finally apply our new framework on 15 empirical tropical forest plots and quantify the minimum percentage cover that should be sampled to achieve a given average confidence interval in the upscaled estimate of biodiversity. Our theoretical framework confirms that the forests studied are comprised of a large number of rare or hyper-rare species. This is a signature of critical-like behavior of species-rich ecosystems and can provide a buffer against extinction.
@article{tovoUpscalingSpeciesRichness2017,
  title = {Upscaling Species Richness and Abundances in Tropical Forests},
  author = {Tovo, Anna and Suweis, Samir and Formentin, Marco and Favretti, Marco and Volkov, Igor and Banavar, Jayanth R. and Azaele, Sandro and Maritan, Amos},
  date = {2017-10},
  journaltitle = {Science Advances},
  volume = {3},
  pages = {e1701438+},
  issn = {2375-2548},
  doi = {10.1126/sciadv.1701438},
  url = {https://doi.org/10.1126/sciadv.1701438},
  abstract = {The quantification of tropical tree biodiversity worldwide remains an open and challenging problem. More than two-fifths of the number of worldwide trees can be found either in tropical or in subtropical forests, but only ≈0.000067\,\% of species identities are known. We introduce an analytical framework that provides robust and accurate estimates of species richness and abundances in biodiversity-rich ecosystems, as confirmed by tests performed on both in silico-generated and real forests. Our analysis shows that the approach outperforms other methods. In particular, we find that upscaling methods based on the log-series species distribution systematically overestimate the number of species and abundances of the rare species. We finally apply our new framework on 15 empirical tropical forest plots and quantify the minimum percentage cover that should be sampled to achieve a given average confidence interval in the upscaled estimate of biodiversity. Our theoretical framework confirms that the forests studied are comprised of a large number of rare or hyper-rare species. This is a signature of critical-like behavior of species-rich ecosystems and can provide a buffer against extinction.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14461460,~to-add-doi-URL,biodiversity,data-transformation-modelling,environmental-modelling,forest-resources,species-richness,tropical-forests},
  number = {10}
}
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