@article{Soberon2015,
author = {Soberon, Jorge and Cavner, Jeffrey},
journal = {Biodiversity Informatics},
pages = {22--34},
title = {{Indices of Biodiversity Pattern Based on Presence-Absence Matrices: A GIS Implementation}},
volume = {10},
year = {2015}
}


@article{Strona2014,
abstract = {A well-known problem in numerical ecology is how to recombine presence-absence matrices without altering row and column totals. A few solutions have been proposed, but all of them present some issues in terms of statistical robustness (that is, their capability to generate different matrix configurations with the same probability) and their performance (that is, the computational effort that they require to generate a null matrix). Here we introduce the 'Curveball algorithm', a new procedure that differs from existing methods in that it focuses rather on matrix information content than on matrix structure. We demonstrate that the algorithm can sample uniformly the set of all possible matrix configurations requiring a computational effort orders of magnitude lower than that required by available methods, making it possible to easily randomize matrices larger than 108 cells. {\textcopyright} 2014 Macmillan Publishers Limited. All rights reserved.},
author = {Strona, Giovanni and Nappo, Domenico and Boccacci, Francesco and Fattorini, Simone and San-Miguel-Ayanz, Jesus},
doi = {10.1038/ncomms5114},
file = {::},
issn = {20411723},
journal = {Nature Communications},
keywords = {Theoretical ecology},
month = {jun},
number = {1},
pages = {1--9},
publisher = {Nature Publishing Group},
title = {{A fast and unbiased procedure to randomize ecological binary matrices with fixed row and column totals}},
url = {https://www.r-project.org},
volume = {5},
year = {2014}
}

@article{SoberonOsorio,
   abstract = {Abstract Aims The aim of this study is to propose and analyse a general, dynamic, process-oriented theory of the area of distribution. Location Mexico, Southern United States and the Caribbean. Taxon Pierid butterflies. Methods The area of distribution is modelled by combining (by multiplication) three matrices: one matrix represents movements, another niche tolerances and a third, biotic interactions. Results are derived from general properties of this product and from simulation of a cellular automaton defined in terms of the matrix operations. Everything is implemented practically in an R package. Results Results are obtained by simulation and mathematical analysis. We show that the mid-domain effect is a direct consequence of dispersal; that to include movements to Ecological Niche Modelling significantly affect results, but cannot be done without choosing an ancestral area of distribution. We discuss ways of estimating such ancestral areas. We show that, in our approach, movements and niche effects are mixed in ways almost impossible to disentangle, and show this is a consequence of the singularity of a matrix. We introduce a tool (the Connectivity-Suitability-Dispersal plot) to extend the results of simple niche modelling to understand the effects of dispersal. Main conclusions The conceptually straightforward scheme we present for the area of distribution integrates, in a mathematically sound and computationally feasible way, several key ideas in biogeography: the geographic and environmental matrix, the Grinnellian niche, dispersal capacity and the ancestral area of origin of groups of species. We show that although full simulations are indispensable to obtain the dynamics of an area of distribution, interesting results can be derived simply by analysing the matrices representing the dynamics.},
   author = {Jorge Soberón and Luis Osorio-Olvera},
   doi = {https://doi.org/10.1111/jbi.14587},
   journal = {Journal of Biogeography6},
   keywords = {BAM,Dismorphia amphinoe,Grinnellian niche,cellular automaton,dipersal simulation,dispersal,distributional range},
   pages = {1037-1048},
   title = {A dynamic theory of the area of distribution},
   volume = {50},
   url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jbi.14587},
   year = {2023},
}



@article{Soberon2022,
  title={Visualizing species richness and site similarity from presence-absence matrices},
  volume={16}, url={https://journals.ku.edu/jbi/article/view/14782},
  DOI={10.17161/bi.v16i1.14782},
  abstractNote={&amp;lt;p&amp;gt;Species richness and similarity of biotas among distinct sites are important quantities in biogeography. Indices derived from presence-absence matrices are used to represent these quantities in so-called diversity-range plots. &amp;amp;nbsp;The most commonly used diversity-range plot, however, has multiple special cases and its interpretation is cumbersome. Here we present an equivalent formulation that is geometrically simpler and has no special cases. In addition, we introduce a method to identify the statistical significance of the dispersion field, an index that represents how similar species composition is in a cell with respect to the whole area. The new diversity-range plot is a promising tool to explore biodiversity and endemism in a region as the values shown in this plot and whether they are statistically significant or not can also be represented in geography.&amp;lt;/p&amp;gt;},
  number={1},
  journal={Biodiversity Informatics},
  author={Soberón, Jorge and Cobos, Marlon E. and Nuñez-Penichet, Claudia},
  year={2021},
  month={Jul.},
  pages={20–27} }

@article{Gordard2022,
    author = {Godard, Karl and Neal, Zachary P},
    title = "{fastball: a fast algorithm to randomly sample bipartite graphs with fixed degree sequences}",
    journal = {Journal of Complex Networks},
    volume = {10},
    number = {6},
    pages = {cnac049},
    year = {2022},
    month = {12},
    abstract = "{Many applications require randomly sampling bipartite graphs with fixed degrees or randomly sampling incidence matrices with fixed row and column sums. Although several sampling algorithms exist, the ‘curveball’ algorithm is the most efficient with an asymptotic time complexity of \\$O(n~log~n)\\$ and has been proven to sample uniformly at random. In this article, we introduce the ‘fastball’ algorithm, which adopts a similar approach but has an asymptotic time complexity of \\$O(n)\\$. We show that a C\\$\\texttt\\{++\\}\\$ implementation of fastball randomly samples large bipartite graphs with fixed degrees faster than curveball, and illustrate the value of this faster algorithm in the context of the fixed degree sequence model for backbone extraction.}",
    issn = {2051-1329},
    doi = {10.1093/comnet/cnac049},
    url = {https://doi.org/10.1093/comnet/cnac049},
    eprint = {https://academic.oup.com/comnet/article-pdf/10/6/cnac049/47758701/cnac049.pdf},
}


 @Article{Kembel2010,
    title = {Picante: {R} tools for integrating phylogenies and ecology},
    author = {S.W. Kembel and P.D. Cowan and M.R. Helmus and W.K. Cornwell and H. Morlon and D.D. Ackerly and S.P. Blomberg and C.O. Webb},
    journal = {Bioinformatics},
    volume = {26},
    pages = {1463--1464},
    year = {2010},
  }
