Introduced or established? Convergent evidence indicates imported pine wood nematode vectors occupy gaps in native distribution - Jean-Claude Grégoire; Jean Artois; Julien Claude; Marius Gilbert; Serge Morand; Géraldine Roux; Gilles San Martin; Dimitrios Avtzis; Nick Berkvens; Jochem Bonte; Hans Casteels; Sandra Closa; et al. (Journal of Pest Science, 2026)
Monitoring regulated quarantine plant pathogens and, when relevant, their vectors is compulsory in the European Union. Local Monochamus species (Coleoptera, Cerambycidae) vector the pine wood nematode, Bursaphelenchus xylophilus , a non-native pest already established in most of Portugal. Only 29 M. galloprovincialis individuals were trapped in Belgium in ten years (2013–2022), despite a dense coverage of pheromone-baited traps, suggesting absence or a very rare local occurrence in the country. In the northern neighbouring countries, only one single established population is known in The Netherlands and one in Denmark. A species distribution model based on pheromone-trap catches (negative and positive) of M. galloprovincialis from 4,914 traps in 29 European countries between 2008 and 2019 was developed, using the overall climate conditions and the distribution of seven pine tree species as explanatory variables. The effect of spatial scale was tested with a multi-scale approach. With a 225*225 km spatial grain, the major explanatory variables were the mean diurnal temperature range and, to a lesser extent, the presence of Pinus spp. The model predicted a low probability of presence in Belgium, the Netherlands, Great Britain and north-western Germany compared to southern Europe. Genotyping allowed to conclude that at least some of the beetles caught in Belgium originated from foreign locations. All catches were located close to entry points, suggesting introduction with imported material. The small size of most of the Belgian pine stands may also explain the absence or apparently transient status, or rareness of Monochamus spp. This study thus suggests that surveys in Belgium should privilege entry points rather than local forest stands.

Sensitivity analysis of parameters, emission factors, and coefficients for estimating animal emissions of ruminant species in the Global Livestock Environmental Assessment Model (GLEAM) - Armando Rivera Moncada; Marie-Cécile Dupas; Giuseppe Tempio; Lydia Lanzoni; Yushan Li; Narindra Rakotovao; Dominik Wisser; Marius Gilbert (The International Journal of Life Cycle Assessment, 2025)

Gastro-protective effects and anti-Helicobacter pylori activities of the aqueous and methanol extracts of the stem-back of Nauclea pobeguinii (Rubiaceae) - Madjo Kouam Yacine Karelle; Mbiantcha Marius; Fagni Njoya Zenab Linda; Matah Marthe Vanessa Mba; Ngoufack Azanze Elvira; Tsafack Eric Gonzal; Djuichou Nguemnang Stephanie Flore; Adjouzem Carine Flore; Ateufack Gilbert (Advances in Traditional Medicine, 2024)

Chromosomal inversions can limit adaptation to new environments - Marius Roesti; Kimberly J. Gilbert; Kieran Samuk (Molecular Ecology, 2022)
Chromosomal inversions are often thought to facilitate local adaptation and population divergence because they can link multiple adaptive alleles into non‐recombining genomic blocks. Selection should thus be more efficient in driving inversion‐linked adaptive alleles to high frequency in a population, particularly in the face of maladaptive gene flow. But what if ecological conditions and hence selection on inversion‐linked alleles change? Reduced recombination within inversions could then constrain the formation of optimal combinations of pre‐existing alleles under these new ecological conditions. Here, we outline this idea of inversions limiting adaptation and divergence when ecological conditions change across time or space. We reason and use simulations to illustrate that the benefit of inversions for local adaptation and divergence under one set of ecological conditions can come with a concomitant constraint for adaptation to novel sets of ecological conditions. This limitation of inversions to adaptation may contribute to the maintenance of polymorphism within species.

Anti-hypernociceptive effects of methanol extract of Boswellia dalzielii on STZ-induced diabetic neuropathic pain - Marius Mbiantcha; Rauf Khalid; Donatien Albert Atsamo; Isaac S. Njoku; Arif Mehreen; Gilbert Ateufack; Dar Hamza; William Yousseu Nana; Rehman Ur Naeem; Ahmad Izhar (Advances in Traditional Medicine, 2020)

Anti-inflammatory and anti-arthritic properties of aqueous extract of Nauclea diderrichii (Rubiaceae) stem bark in rats - Marius Mbiantcha; Marcelle Bejoutance Djami; Gilbert Ateufack; Donatien Albert Atsamo; Gonzal Eric Tsafack; William Nana Yousseu; Flore Stéphanie Nguemnang Djuichou; Vanessa Marthe Mba Matah; Liliane Kamdem Kenmogne; Flore Carine Adjouzem; Linda Fagni Zenab Ndjoya; Giresse Lambou Tiokeng (Advances in Traditional Medicine, 2020)

Antihypernociceptive and neuroprotective effects of Combretin A and Combretin B on streptozotocin-induced diabetic neuropathy in mice - Marius Mbiantcha; Rauf Khalid; Amadou Dawe; Arif Mehreen; Donatien Albert Atsamo; Gilbert Ateufack; Dar Hamza; William Yousseu Nana; Francis Tatsinkou Desire Bomba; Rehman Ur Naeem; Ahmad Izhar (Naunyn-Schmiedeberg's Archives of Pharmacology, 2019)

Anti-inflammatory and anti-arthritic effects of methanol extract of the stem bark of Boswellia dalzielii Hutch (Burseraceae) in rats - Marius Mbiantcha; Jabeen Almas; Albert Donatien Atsamo; Gilbert Ateufack; Simjee U. Shabana; Desire Francis Bomba Tatsinkou; William Yousseu Nana; Dastagir Nida (Inflammopharmacology, 2018)

H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data - Jean Artois; Shengjie Lai; Luzhao Feng; Hui Jiang; Hang Zhou; Xiangping Li; Madhur S. Dhingra; Catherine Linard; Gaëlle Nicolas; Xiangming Xiao; Timothy P. Robinson; Hongjie Yu; et al. (Stochastic Environmental Research and Risk Assessment, 2017)

Climate change and the spread of vector‐borne diseases: using approximate B ayesian computation to compare invasion scenarios for the bluetongue virus vector C ulicoides imicola in I taly - Patrick Mardulyn; Maria Goffredo; Annamaria Conte; Guy Hendrickx; Rudolf Meiswinkel; Thomas Balenghien; Soufien Sghaier; Youssef Lohr; Marius Gilbert (Molecular Ecology, 2013)
Bluetongue ( BT ) is a commonly cited example of a disease with a distribution believed to have recently expanded in response to global warming. The BT virus is transmitted to ruminants by biting midges of the genus C ulicoides , and it has been hypothesized that the emergence of BT in Mediterranean Europe during the last two decades is a consequence of the recent colonization of the region by C ulicoides imicola and linked to climate change. To better understand the mechanism responsible for the northward spread of BT , we tested the hypothesis of a recent colonization of Italy by C . imicola , by obtaining samples from more than 60 localities across I taly, C orsica, S outhern F rance, and N orthern A frica (the hypothesized source point for the recent invasion of C . imicola ), and by genotyping them with 10 newly identified microsatellite loci. The patterns of genetic variation within and among the sampled populations were characterized and used in a rigorous approximate B ayesian computation framework to compare three competing historical hypotheses related to the arrival and establishment of C . imicola in I taly. The hypothesis of an ancient presence of the insect vector was strongly favoured by this analysis, with an associated P ≥ 99%, suggesting that causes other than the northward range expansion of C . imicola may have supported the emergence of BT in southern Europe. Overall, this study illustrates the potential of molecular genetic markers for exploring the assumed link between climate change and the spread of diseases.

Resource allocation for efficient environmental management - Michael A. McCarthy; Colin J. Thompson; Cindy Hauser; Mark A. Burgman; Hugh P. Possingham; Melinda L. Moir; Thanawat Tiensin; Marius Gilbert (Ecology Letters, 2010)
Ecology Letters (2010) Abstract Environmental managers must decide how to invest available resources. Researchers have previously determined how to allocate conservation resources among regions, design nature reserves, allocate funding to species conservation programs, design biodiversity surveys and monitoring programs, manage species and invest in greenhouse gas mitigation schemes. However, these issues have not been addressed with a unified theory. Furthermore, uncertainty is prevalent in environmental management, and needs to be considered to manage risks. We present a theory for optimal environmental management, synthesizing previous approaches to the topic and incorporating uncertainty. We show that the theory solves a diverse range of important problems of resource allocation, including distributing conservation resources among the world’s biodiversity hotspots; surveillance to detect the highly pathogenic avian influenza H5N1 virus in Thailand; and choosing survey methods for the insect order Hemiptera. Environmental management decisions are similar to decisions about financial investments, with trade‐offs between risk and reward.

Species richness coincidence: conservation strategies based on predictive modelling - Dirk Maes; Dirk Bauwens; Luc De Bruyn; Anny Anselin; Glenn Vermeersch; Wouter Van Landuyt; Geert De Knijf; Marius Gilbert (Biodiversity and Conservation, 2005)

Prediction of butterfly diversity hotspots in Belgium: a comparison of statistically focused and land use‐focused models - Dirk Maes; Marius Gilbert; Nicolas Titeux; Philippe Goffart; Roger L. H. Dennis (Journal of Biogeography, 2003)
Aim We evaluate differences between and the applicability of three linear predictive models to determine butterfly hotspots in Belgium for nature conservation purposes. Location The study is carried out in Belgium for records located to Universal Transverse Mercator (UTM) grid cells of 5 × 5 km. Methods We first determine the relationship between factors correlated to butterfly diversity by means of modified t ‐tests and principal components analysis; subsequently, we predict hotspots using linear models based on land use, climate and topographical variables of well‐surveyed UTM grid cells ( n = 197). The well‐surveyed squares are divided into a training set and an evaluation set to test the model predictions. We apply three different models: (1) a ‘statistically focused’ model where variables are entered in descending order of statistical significance, (2) a ‘land use‐focused’ model where land use variables known to be related to butterfly diversity are forced into the model and (3) a ‘hybrid’ model where the variables of the ‘land use‐focused model’ are entered first and subsequently complemented by the remaining variables entered in descending order of statistical significance. Results A principal components analyses reveals that climate, and to a large extent, land use are locked into topography, and that topography and climate are the variables most strongly correlated with butterfly diversity in Belgium. In the statistically focused model, biogeographical region alone explains 65% of the variability; other variables entering the statistically focused model are the area of coniferous and deciduous woodland, elevation and the number of frost days; the statistically focused model explains 77% of the variability in the training set and 66% in the evaluation set. In the land use‐focused model, biogeographical region, deciduous and mixed woodland, natural grassland, heathland and bog, woodland edge, urban and agricultural area and biotope diversity are forced into the model; the land use‐focused model explains 68% of the variability in the training set and 57% in the evaluation set. In the hybrid model, all variables from the land use‐focused model are entered first and the covariates elevation, number of frost days and natural grassland area are added on statistical grounds; the hybrid model explains 78% of the variability in the training set and 67% in the evaluation set. Applying the different models to determine butterfly diversity hotspots resulted in the delimitation of spatially different areas. Main conclusions The best predictions of butterfly diversity in Belgium are obtained by the hybrid model in which land use variables relevant to butterfly richness are entered first after which climatic and topographic variables were added on strictly statistical grounds. The land use‐focused model does not predict butterfly diversity in a satisfactory manner. When using predictive models to determine butterfly diversity, conservation biologists need to be aware of the consequences of applying such models. Although, in conservation biology, land use‐focused models are preferable to statistically focused models, one should always check whether the applied model makes sense on the ground. Predictive models can target mapping efforts towards potentially species‐rich sites and permits the incorporation of un‐surveyed sites into nature conservancy policies. Species richness distribution maps produced by predictive modelling should therefore be used as pro‐active conservation tools.