Research in Macroecology and Biodiversity Conservation


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Modelling unicorns to improve our capacity to accurately model real species

This is the repost of an article we wrote for the Ecography blog In 1990, Stuart H. Hurlbert analysed the “Spatial Distribution of the Montane Unicorn”. The Montane Unicorn was a rare organism, at that time only recently described, and Hurlbert was the first to report data on this singular species. His data showed that unicorn populations had extremely unusual and varying abundance distributions. He therefore analysed these abundance distributions.. Read More

The Anthropocene, or the disturbing beginnings of the era of Man

We are increasingly hearing about “the Anthropocene”, both in and outside of the scientific community. The Anthropocene is a term used by geologists to describe the geological era in which we now live. It means ‘the era of Man’, i.e. the era in which we recognise Man as a major geological force, a force that alters significantly and globally the Earth. Although this term is increasingly used, the Anthropocene is.. Read More

Reduce the number of light bulbs or reduce their consumption?

Environmental destruction hastens as human population increases, and current efforts are unlikely to improve indicator trends. Intuitively, one may consider reducing human population size by a reduction in fertility as one of the most urgent actions to undertake to ensure our future on this planet. It is already the case in developed countries, which have access to contraception, or more drastically in China, with the one-child policy. However, most populations.. Read More

SDMs – Schrödinger Distribution Models

Everybody knows Schrödinger’s cat. That famous cat that would be both dead and alive according to a quantic model. We can make an analogy with predictions of climate change impacts on species distributions. Most of these predictions were done using species distribution models (SDMs). The problem is that SDMs are rather uncertain techniques. A small technical definition Technically, SDMs consist in correlating the occurrence of a species (i.e., places where.. Read More

New job, new website, new projects… new blog!

Until now, the main use of this website was as an online CV, to show my research, and, to be honnest, to help me finding a permanenent position in the retlentless world of research. Well, voilà! It’s done! I’ve been recruited as a lecturer in the Muséum National d’Histoire Naturelle (Paris), in the lab. Biodiversity & Macroecology, UMR Biology of Aquatic Organisms & Ecosystems. I’ve decided to make profit of.. Read More

Future invasions and climate change

Biological invasion is increasingly recognized as one of the greatest threats to biodiversity. The International Union for the Conservation of Nature has defined a list of the “100 of the world’s worst invasive species”. A research team (CNRS / Université Paris-Sud / Université Joseph Fourier Grenoble 1 / Université de Rennes 1 / MNHN / Institute for Environmental Protection and Research, Rome / Netherlands Environmental Assessment Agency) has predicted that.. Read More

Correlation plots in R

I have just released the version 1.2 1.2-1 of the Rarity package, and this new version introduces a new function to make what I called “correlation plots”. These correlation plots provide a synthetic and convenient representation of the correlation between 2 or more variables, allowing an easy analysis. The above figure is an example with data of crab sizes (from the package MASS). The plot is split in two: the.. Read More

Rarity package for calculation of Indices of rarity

The package “Rarity”, which allows calculating rarity indices for species and assemblages of species, is now available on the Comprehensive R Archive Network. This package allows easy calculation of the new indices integrating rarity cut-offs; this flexibility allows fitting indices to the considered taxon, geographical area and/or spatial scale, i.e., to the considered database. See the rarity indices section for more details and examples. This package simply requires occurrence data.. Read More