Biology subjects

Didier, G.

Publications and source records attributed to Didier, G..

11 recordsLinked to original sources

bioRxiv2026

Environmental DNA enables rapid detection of invasive coypu and complements camera trapping

Effective management of invasive species requires surveillance methods that reliably detect populations while minimizing field effort. Environmental DNA (eDNA) offers a potentially rapid alternative to conventional monitoring, but direct comparisons with other non-invasive methods remain limited for invasive mammals. Here, we compared eDNA water sampling and camera trapping for detecting established populations of coypu (Myocastor coypus), an invasive semi-aquatic rodent. Using replicated data collected across Mediterranean river systems in southern France, we estimated detection probabilities conditional on coypu presence using Bayesian generalized linear mixed models and quantified the sampling effort required to achieve high cumulative detection probability. Detection probability was 93.0% (95% credible interval: 72.1-98.9%) for a single eDNA water sample, compared with 52.8% (22.6-91.1%) for 30 camera-trap days, with a 96.9% posterior probability that eDNA detection was higher. Two eDNA samples were sufficient to achieve a median cumulative detection probability above 95%, compared with four 30-day camera-trapping periods. Detection also varied at different spatial scales, with camera-trap detectability being heterogeneous among local camera locations and eDNA detectability varying more among catchments. These results show that eDNA provides a rapid and reliable approach for confirming the presence of established coypu populations, while camera traps provide complementary information on activity, behaviour and habitat use. Combining rapid eDNA screening with targeted camera trapping may therefore provide an efficient surveillance strategy for invasive semi-aquatic mammals.

ecology↗

bioRxiv2026

Phylogenetic reconstruction of trait summary statistics and disparity dynamics

Summary statistics are essential tools for understanding the overall behaviour of a collection of measurements. In a phylogenetic context, however, trait measurements are generally observed only for extant taxa and, when available, fossil taxa, while the questions of interest concern the evolution of the trait through time rather than only its static properties among the observed taxa. To investigate how the empirical mean and variance of a trait evolve through time, we derive, under Brownian evolution, their conditional distributions given trait values observed at extant or fossil tips. This provides reconstructed trajectories of both summary statistics together with a direct quantification of their uncertainty. Among these two summaries, the empirical variance is of particular interest as a measure of past phenotypic disparity. To assess reconstructed disparity, we define the disparity level at any time as the probability that a value drawn from the conditional distribution of the empirical variance exceeds an independent value drawn from the corresponding unconditional Brownian distribution. As a dimensionless quantity with a common interpretation, the disparity level enables comparisons across times, clades, phylogenies, and datasets. Applications to cetacean body length reveal contrasting trajectories among major subclades and suggest that much of the disparity reconstructed for the complete clade is associated with differences among these subclades. An analysis of body mass in living and fossil mammaliaforms identifies low disparity relative to the Brownian reference through most of the Mesozoic, followed by a sustained expansion around and after the K--Pg boundary. These patterns are broadly consistent with previous analyses of the same datasets, while providing a direct reconstruction of changes in the location and spread of trait distributions through time. The methods are implemented in the R package PastMoments.

evolutionary biology↗

bioRxiv2026

Comparative efficiency of eDNA, camera traps and scat surveys to detect a semi-aquatic mammal across multiple catchments

Semi-aquatic mammals lie at the intersection of several key conservation issues such as wetland deterioration or species invasions, and monitoring their distribution in space and time is essential to inform conservation strategies. However, gathering information about their presence is challenging due to their elusive lifestyle and generally low abundance. The Eurasian otter (Lutra lutra), a near-threatened and strictly protected species in Europe, is currently recolonizing part of its historical range. Its high conservation interest, combined with a dynamic more commonly associated with range-expanding or invasive species, makes it a particularly compelling case study. Otter monitoring has traditionally relied on scat surveys, but recent environmental DNA (eDNA) and camera-trapping initiatives have emerged offering promising complementary tools. Yet, these approaches have rarely been formally compared, either to one another or across regions. Here, we compared the efficiency of spraint surveys, camera traps, and eDNA for detecting otters, and assessed how their performance varied among four catchments in southern France where the species is known to be present. All three methods provided otter detections with varying efficiency. Scat surveys were the most effective method, with an average detection probability of 0.71 and no strong variability between catchments. Although camera-traps had the lowest detection rate, they provided detections at two of the four sites where no spraint was found, highlighting the complementarity of these two approaches. Detection rates varied greatly between individual cameras rather than between catchments, underscoring sensitivity to camera-placement. eDNA showed important variability between catchments, with detection probabilities differing by roughly sixfold across regions. All in all, our results highlight differences in efficiency between methods and across environmental conditions, and show the value of combining approaches for future monitoring programs.

ecology↗

bioRxiv2023

The Cauchy Process on Phylogenies: a Tractable Model for Pulsed Evolution

Phylogenetic comparative methods use random processes, such as the Brownian Motion, to model the evolution of continuous traits on phylogenetic trees. Growing evidence for non-gradual evolution motivated the development of complex models, often based on Levy processes. However, their statistical inference is computationally intensive, and currently relies on approximations, high dimensional sampling, or numerical integration. We consider here the Cauchy Process (CP), a particular pure-jump Levy process in which the trait increment along each branch follows a centered Cauchy distribution with a dispersion proportional to its length. In this work, we derive an exact algorithm to compute both the joint probability density of the tip trait values of a phylogeny under a CP, and the ancestral trait values and branch increments posterior densities in quadratic time. A simulation study shows that the CP generates patterns in comparative data that are distinct from any Gaussian process, and that Restricted Maximum Likelihood (REML) parameter estimates and root trait reconstruction are unbiased and accurate for trees with 200 tips or less. The CP has only two parameters but is rich enough to capture complex pulsed evolution. It can reconstruct posterior ancestral trait distributions that are multimodal, reflecting the uncertainty associated with the inference of the evolutionary history of a trait from extant taxa only. Applied on empirical datasets taken from the Evolutionary Ecology and Virology literature, the CP suggests nuanced scenarios for the body size evolution of Greater Antilles Lizards and for the geographical spread of the West Nile Virus epidemics in North America, both consistent with previous studies using more complex models. The method is efficiently implemented in C with an R interface in package cauphy, that is open source and freely available online. Cauchy process, Phylogenetic Comparative Methods, Evolutionary jumps, Quantitative traits, Phylogeography

evolutionary biology↗

bioRxiv2021

Distributions of extinction times from fossil ages and tree topologies: the example of some mid-Permian synapsid extinctions

Given a phylogenetic tree that includes only extinct, or a mix of extinct and extant taxa, where at least some fossil data are available, we present a method to compute the distribution of the extinction time of a given set of taxa under the Fossilized-Birth-Death model. Our approach differs from the previous ones in that it takes into account (i) the possibility that the taxa or the clade considered may diversify before going extinct and (ii) the whole phylogenetic tree to estimate extinction times, whilst previous methods do not consider the diversification process and deal with each branch independently. Because of this, our method can estimate extinction times of lineages represented by a single fossil, provided that they belong to a clade that includes other fossil occurrences. We assess and compare our new approach with a standard previous one using simulated data. Results show that our method provides more accurate confidence intervals. This new approach is applied to the study of the extinction time of three Permo-Carboniferous synapsid taxa (Ophiacodontidae, Edaphosauridae, and Sphenacodontidae) that are thought to have disappeared toward the end of the Cisuralian (early Permian), or possibly shortly thereafter. The timing of extinctions of these three taxa and of their component lineages supports the idea that the biological crisis in the late Kungurian/early Roadian consisted of a progressive decline in biodiversity throughout the Kungurian.

evolutionary biology↗

bioRxiv2019

Testing for correlation between traits under directional evolution

Being confounding factors, directional trends are likely to make two quantitative traits appear as spuriously correlated. By determining the probability distributions of independent contrasts when traits evolve following Brownian motions with linear trends, we show that the standard independent contrasts can not be used to test for correlation in this situation. We propose a multiple regression approach which corrects the bias caused by directional evolution.\n\nWe show that our approach is equivalent to performing a Phylogenetic Generalized Least Squares (PGLS) analysis with tip times as covariables by providing a new and more general proof of the equivalence between PGLS and independent contrasts methods.\n\nOur approach is assessed and compared with three previous correlation tests on data simulated in various situations and overall outperforms all the other methods. The approach is next illustrated on a real dataset to test for correlation between hominin cranial capacity and body mass.

evolutionary biology↗

bioRxiv2018

Exact distribution of divergence times from fossil ages and tree topologies

Being given a phylogenetic tree of both extant and extinct taxa in which the fossil ages are the only temporal information (namely, in which divergence times are considered unknown), we provide a method to compute the exact probability distribution of any divergence time of the tree with regard to any speciation (cladogenesis), extinction and fossilization rates under the Fossilized-Birth-Death model. We use this new method to obtain a probability distribution for the age of Amniota (the synapsid/sauropsid or bird/mammal divergence), one of the most-frequently used dating constraints. Our results suggest an older age (between about 322 and 340 Ma) than has been assumed by most studies that have used this constraint (which typically assumed a best estimate around 310-315 Ma) and provide, for the first time, a method to compute the shape of the probability density for this divergence time.

evolutionary biology↗

bioRxiv2018

Exact distribution of divergence times under the birth-death-sampling model

Dating the tree of life is a task far more complicated that only determining the evolutionary relationships between species. It is therefore of interest to develop approaches able to deal with undated phylogenetic trees. The main result of this work is a method to compute probabilities of undated phylogenetic trees under piecewiseconstant-birth-death-sampling models by constraining some of the divergence times to belong to given time intervals and by allowing diversification shifts on certain clades. The computation is quite fast since its time complexity is quadratic with the size of the tree topology and linear with the number of time constraints and of "pieces" in the model. The interest of this computation method is illustrated with three applications, namely, O_LIto compute the exact distribution of the divergence times of a tree topology with temporal constraints, C_LIO_LIto directly sample the divergence times of a tree topology, and C_LIO_LIto test for a diversification shift at a given clade. C_LI

evolutionary biology↗

bioRxiv2017

Parsimonious identification of evolutionary shifts for quantitative characters

Detecting shifts in the rate or the trend of a character evolution is an important question which has been widely addressed. To our knowledge, all the approaches developed so far for detecting such shifts from a quantitative character strongly involved stochastic models of evolution.\n\nWe propose here a novel method based on an asymmetric version of the linear parsimony (aka Wagner parsimony) for identifying the most parsimonious split of a tree into two parts between which the evolution of the character is allowed to differ. To this end, we evaluate the cost of splitting a phylogenetic tree at a given node as the integral, over all pairs of asymmetry parameters, of the most parsimonious cost which can be achieved by using the first parameter on the subtree pending from this node and the second parameter elsewhere. By testing all the nodes, we then get the most parsimonious split of a tree with regard to the character values at its tips.\n\nA study of the partial costs of the tree enabled us to develop a polynomial algorithm for determining the most parsimonious splits and their evolutionary costs. Applying this algorithm on two toy examples shows that using more than one asymmetry parameter does not always lower parsimonious costs. By using the approach on biological datasets, we obtained splits consistent with those identified by previous stochastic approaches.

evolutionary biology↗

bioRxiv2017

Detecting Molecular Basis Of Phenotypic Convergence

Convergence is the process by which several species independently evolve similar traits. This evolutionary process is not only strongly related to fundamental questions such as the predictability of evolution and the role of adaptation, its study also may provide new insights about genes involved in the convergent character. We focus on this latter question and aim to detect molecular basis of a given phenotypic convergence. After pointing out a number of concerns about detection methods based on ancestral reconstruction, we propose a novel approach combining an original measure of the extent to which a site supports a phenotypic convergence, with a statistical framework for selecting genes from the measure of their sites. First, our measure of \"convergence level\" outperforms two previous ones in distinguishing simulated convergent sites from non-convergent ones. Second, by applying our detection approach to the well-studied case of convergent echolocation between dolphins and bats, we identified a set of genes which is very significantly annotated with audition-related GO-terms. This result constitutes an indirect evidence that genes involved in a phenotypic convergence can be identified with a genome-wide approach, a point which was highly debated, notably in the echolocation case (the latest articles published on this topic were quite pessimistic). Our approach opens the way to systematic studies of numerous examples of convergent evolution in order to link (convergent) phenotype to genotype.

evolutionary biology↗

bioRxiv2016

Time-dependent-asymmetric-linear-parsimonious ancestral state reconstruction

The time-dependent-asymmetric-linear parsimony is an ancestral state reconstruction method which extends the standard linear parsimony (a.k.a. Wagner parsimony) approach by taking into account both branch lengths and asymmetric evolutionary costs for reconstructing quantitative characters (asymmetric costs amount to assuming an evolutionary trend toward the direction with the lowest cost).\n\nA formal study of the influence of the asymmetry parameter shows that the time-dependent-asymmetric-linear parsimony infers states which are all taken among the known states, except for some degenerate cases corresponding to special values of the asymmetry parameter. This remarkable property holds in particular for the Wagner parsimony.\n\nThis study leads to a polynomial algorithm which determines, and provides a compact representation of, the parametric reconstruction of a phylogenetic tree, that is for all the unknown nodes, the set of all the possible reconstructed states associated to the asymmetry parameters leading to them. The time-dependent-asymmetric-linear parsimony is finally illustrated with the parametric reconstruction of the body size of cetaceans.

evolutionary biology↗