Canard, E. F., Mouquet, N., Mouillot, D., Stanko, M., Miklisova, D., & Gravel, D. (2014). Empirical Evaluation of Neutral Interactions in HostParasite Networks. American Naturalist, 183(4), 468–479.
Résumé: While nichebased processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 hostparasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite hostparasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

Mante, C., Kide, S. O., YaoLafourcade, A.  F., & Mérigot, B. (2016). Fitting the truncated negative binomial distribution to count data A comparison of estimators, with an application to groundfishes from the Mauritanian Exclusive Economic Zone. Environ. Ecol. Stat., 23(3), 359–385.
Résumé: Modeling empirical distributions of repeated counts with parametric probability distributions is a frequent problem when studying species abundance. One must choose a family of distributions which is flexible enough to take into account very diverse patterns and possess parameters with clear biological/ecological interpretations. The negative binomial distribution fulfills these criteria and was selected for modeling counts of marine fish and invertebrates. This distribution depends on a vector of parameters, and ranges from the Poisson distribution (when ) to Fisher's logseries, when . Moreover, these parameters have biological/ecological interpretations which are detailed in the literature and in this study. We compared three estimators of K, and the parameter of Fisher's logseries, following the work of Rao CR (Statistical ecology. Pennsylvania State University Press, University Park, 1971) on a threeparameter unstandardized variant of the negative binomial distribution. We further investigated the coherence underlying parameter values resulting from the different estimators, using both real count data collected in the Mauritanian Exclusive Economic Zone (MEEZ) during the period 19872010 and realistic simulations of these data. In the case of the MEEZ, we first built homogeneous lists of counts (replicates), by gathering observations of each species with respect to “typical environments” obtained by clustering the sampled stations. The best estimation of was generally obtained by penalized minimum Hellinger distance estimation. Interestingly, the parameters of most of the correctly sampled species seem compatible with the classical birthanddead model of population growth with immigration by Kendall (Biometrika 35:615, 1948).
