Is uneven-aged silviculture best for maximizing ecosystem functioning, services, biodiversity, and resilience in Walloon forests? - Frédéric André; Arthur Guignabert; Hugues Goosse; François de Coligny; Gauthier Ligot; Benoit Courbaud; Mathieu Fortin; Mathilde Pau; Sylvain Marchi; Mathieu Jonard (Regional Environmental Change, 2026)

Data fusion approach for predicting high resolution estimates of crop evapotranspiration - Farshina Nazrul Shimim; Mathieu Pagé Fortin; Mallika Nocco; Bradley Whitaker; Andrew Gal; Dawson Diaz; Radomir Schmidt; Gaurav Jha (Precision Agriculture, 2025)

New sensitive tools to characterize meta-metabolome response to short- and long-term cobalt exposure in dynamic river biofilm communities - Simon Colas; Benjamin Marie; Soizic Morin; Mathieu Milhe-Poutingon; Pierre Foucault; Siann Chalvin; Clémentine Gelber; Patrick Baldoni-Andrey; Nicholas Gurieff; Claude Fortin; Séverine Le Faucheur (Science of The Total Environment, 2024)

Meta-metabolomic responses of river biofilms to cobalt exposure and use of dose-response model trends as an indicator of effects - Simon Colas; Benjamin Marie; Mathieu Milhe-Poutingon; Marie-Claire Lot; Amiel Boullemant; Claude Fortin; Séverine Le Faucheur (Journal of Hazardous Materials, 2024)

Forest adaptation strategies to reconcile timber production and carbon sequestration objectives under multiple risks of extreme drought and windstorm events - Sandrine Brèteau-Amores; Rasoul Yousefpour; Marc Hanewinkel; Mathieu Fortin (Ecological Economics, 2023)

Group selection cutting for regenerating Mediterranean Pinus pinaster plantations: Gap effects on seedling survival - de Frutos Sergio; Fortin Mathieu; Roig-Gómez Sonia; Ruiz-Peinado Ricardo; del Río Miren; Bravo-Fernández José Alfredo (Forest Ecology and Management, 2023)

Is Diversification a Suitable Option to Reduce Drought-Induced Risk of Forest Dieback? An Economic Approach Focused on Carbon Accounting - Sandrine Brèteau-Amores; Mathieu Fortin; Pablo Andrés-Domenech; Nathalie Bréda (Environmental Modeling & Assessment, 2022)

Comparison of uncertainty quantification techniques for national greenhouse gas inventories - Mathieu Fortin (Mitigation and Adaptation Strategies for Global Change, 2021)

Improved β‐diversity estimators based on multiple‐site dissimilarity: Distinguishing the sample from the population - Mathieu Fortin; Anna Kondratyeva; Rosalinde Van Couwenberghe (Global Ecology and Biogeography, 2020)
Aim β‐diversity is often measured through incidence‐based dissimilarity indices, such as the Simpson and Sørensen indices. Multiple‐site versions of these indices, which have been recently developed, enhance the accountability of global heterogeneity relative to the original formulations. However, they are known to be sensitive to the number of sites, which hinders the comparison of β‐diversity between two populations of unequal sizes. Moreover, the populations are never completely measured and the dissimilarity must be estimated from a sample of sites. Innovation In this study, we propose adapted multiple‐site versions of the Simpson, Sørensen and nestedness indices that are population size‐independent as well as estimators of these indices. The properties of the indices and their estimators were tested through simulation studies. These simulation studies show that the adapted indices were population size‐independent. The estimators and their estimated standard errors were nearly unbiased for moderate sample sizes ( n ≥ 25). Main conclusions These estimators of these adapted multiple‐site dissimilarity indices now make it possible to compare the β‐diversity of two populations of unequal sizes.

Simultaneous Prediction of Plot-Level and Tree-Level Harvest Occurrences with Correlated Random Effects - Rubén Manso; François Ningre; Mathieu Fortin (Forest Science, 2018)

Plastic response of fearful prey to the spatiotemporal dynamics of predator distribution - Mathieu Basille; Daniel Fortin; Christian Dussault; Guillaume Bastille-Rousseau; Jean-Pierre Ouellet; Réhaume Courtois (Ecology, 2015)
Ecological theory predicts that the intensity of antipredator responses is dependent upon the spatiotemporal context of predation risk (the risk allocation hypothesis). However, most studies to date have been conducted over small spatial extents, and did not fully take into account gradual responses to predator proximity. We simultaneously collected spatially explicit data on predator and prey to investigate acute responses of a threatened forest ungulate, the boreal caribou ( Rangifer tarandus ), to the spatiotemporal dynamics of wolf ( Canis lupus ) distribution during spring. Movement analysis of GPS‐collared individuals from both species revealed high plasticity in habitat‐selection decisions of caribou. Female caribou avoided open areas and deciduous forests and moved relatively fast and toward foraging areas when wolves were closer than 2.5 km. Caribou also avoided food‐rich areas only when wolves were within 1 km. Our results bridge the gap between long‐term perceived risk and immediate flight responses by revealing dynamic antipredator tactics in response to predator proximity.

Modeling Jack Pine ( Pinus banksiana ) Foliage Density Distribution - Robert Schneider; Mathieu Fortin; Frank Berninger; Chhun-Huor Ung; D. Edwin Swift; S.Y. Zhang (Forest Science, 2011)
The vertical distribution of foliage biomass is important because it is associated with photosynthesis and is closely related to some wood quality attributes such as branch diameter and sapwood content. In this article we propose a model to predict foliage biomass distribution within the crown for jack pine trees in Eastern Canada. This model has two parts. The first one distinguishes the proportion of nodal (formed at the end of each yearly shoot) and internodal (formed during the growing season) foliage biomass. The second part of the model predicts the distribution of the biomass depending on the type of foliage (nodal or internodal). This second part is based on a two-parameter beta cumulative distribution function (cdf). The parameterization of this cdf was performed using a mixed-effects nonlinear regression. The proportion of foliage biomass found in the nodal whorls is proportional to dbh and age and inversely proportional to total height. The distribution of the foliage biomass in the nodal whorls is dependent only on tree-level variables whereas the internodal foliage biomass is influenced by both tree- and stand-level variables. The internodal foliage biomass maximum is closer to the crown base than that of nodal foliage biomass. Decomposing the distribution into whorl types leads to a better description of crown characteristics.

Using biodiversity deconstruction to disentangle assembly and diversity dynamics of understorey plants along post‐fire succession in boreal forest - Ermias T. Azeria; Mathieu Bouchard; David Pothier; Daniel Fortin; Christian Hébert (Global Ecology and Biogeography, 2011)
Aim The study aims to decipher the co‐occurrence of understorey plant assemblages and, accordingly, to identify a set of species groups (diversity deconstruction) to better understand the multiple causal processes underlying post‐fire succession and diversity patterns in boreal forest. Location North‐eastern Canadian boreal forest (49°07′–51°44′ N; 70°13′–65°15′ W). Methods Data on understorey plant communities and habitat factors were collected from 1097 plots. Species co‐occurrence was analysed using null model analysis. We derive species groups (i.e. biodiversity deconstruction) using the strength of pairwise species co‐occurrences after accounting for random expectation under a null model and cluster analyses. We examine the influence of a set of spatiotemporal environmental variables (overstorey composition, time‐since‐fire, spatial location and topography) on richness of species groups using Bayesian model averaging, and their relative influence through hierarchical partitioning of variance. Results Understorey plant assemblages were highly structured, with co‐occurrence‐based classification providing species groups that were coherently aggregated within, but variably segregated between, species groups. Group richness models indicate both common and distinct responses to factors affecting plant succession. For example, Group 2 (e.g. Rhododendron groenlandicum and Cladina rangiferina ) showed concurrent contrasting responses to overstorey composition and was strongly segregated from Groups 3 (e.g. Clintonia borealis and Maianthenum canadense ) and 4 (e.g. Epilobium angustifolium and Alnus rugosa ). Groups 3 and 4 showed partial similarity, but they differed in their response to time‐since‐fire, drainage and latitude, which were more important for Group 1 (e.g. Ptilium crista‐castrensis and Empetrum nigrum ). A single successional model based on total richness masked crucial group‐level relationships with factors that we examined, such as latitude. Main conclusions By demonstrating the co‐occurrence structure and linking to causal factors, the results from this study characterize both common and distinct responses of understorey plants to biophysical attributes of sites, and potential interspecific interactions, behind non‐random assemblage structure during post‐fire succession. A biodiversity deconstruction approach could offer a concise and explicit framework to gain a better understanding of the complex assembly of ecological communities during succession.

A simple stem taper model with mixed effects for boreal black spruce - Geneviève Lejeune; Chhun-Huor Ung; Mathieu Fortin; Xiao Jing Guo; Marie-Claude Lambert; Jean-Claude Ruel (European Journal of Forest Research, 2009)

Spatial structure effects on the detection of patches boundaries using local operators - Mathieu D. Philibert; Marie-Josée Fortin; Ferenc Csillag (Environmental and Ecological Statistics, 2008)

A variance-covariance structure to take into account repeated measurements and heteroscedasticity in growth modeling - Mathieu Fortin; Gaétan Daigle; Chhun-Huor Ung; Jean Bégin; Louis Archambault (European Journal of Forest Research, 2007)

Modeling Tree Recruitment with Zero-Inflated Models: The Example of Hardwood Stands in Southern Québec, Canada - Mathieu Fortin; Josianne DeBlois (Forest Science, 2007)
In recruitment modeling, the response variable is a count and its distribution is often characterized by an excess number of zeros. As a result, standard distributions of probabilities, such as Poisson, are inappropriate. A common approach in forestry consists of using two-part conditional models. These models have two distinct components aimed to predicting the occurrence and abundance of recruitment, respectively. For such data, zero-inflated models might provide a more adequate framework by combining the two components into a joint distribution of probabilities. In this article, a conditional model is compared with two different zero-inflated models, namely, a zero-inflated Poisson (ZIP) and a zero-inflated discrete Weibull (ZIdiW) model. The three models were calibrated using a data set provided by permanent sample plots located in hardwood stands. Parsimony criteria (the Akaike information criterion and the Bayesian information criterion) and diagnostic plots were used to perform the comparison. The results show that the ZIdiW model has the best fit. The flexibility of the Weibull function and the possibility of obtaining a more parsimonious model are two advantages related to the use of a ZIdiW model in recruitment modeling.

Calibrating a Generalized Diameter Distribution Model with Mixed Effects - Mathieu Fortin; Chhun-Huor Ung; Louis Archambault; Jean Bégin (Forest Science, 2006)
This article proposes a mixed model approach as an alternative to the traditional parameter prediction method in diameter distribution modeling. Unthinned and thinned plots established in mixed stands were used for calibrating a generalized diameter distribution model. The model was based on a two-parameter Weibull cumulative density function (cdf). This cdf was linearized through a complementary log–log link function. Plot random effects were included to account for autocorrelation and the dependent variable, i.e., cumulative stem frequency, was assumed to follow a binomial distribution. With respect to the parameter prediction method, this mixed model approach may generate a consistent estimator with consistent and unbiased variance for the vector of parameters when the variance-covariance matrix of the error terms is properly parameterized. Moreover, the approach enables a better assessment of the different variance components. For the whole group of plots, it provides a predicted average diameter distribution. At the plot level, the random effects can be considered as a departure from this average distribution. As long as the diameter distributions of the individual plots do not exhibit major departures from unimodality, the method proposed in this study should be used to calibrate generalized diameter distribution models.