Biology subjects

Fortin, M.-J.

Publications and source records attributed to Fortin, M.-J..

16 recordsLinked to original sources

bioRxiv2026

A single attractor governs the population dynamics of marine fishes worldwide

Population fluctuations are now empirically recognized to be nonlinear, but the governing attractors are poorly understood. Here we show that population dynamics of 457 marine fish stocks from 121 species worldwide are governed by a single attractor that partitions into three archetypes reflecting top predators, mesopredators and forage fish, with stock-specific ecological and evolutionary variation. Correlation between attractors was high across all stocks (mean 0.53 to 0.63), greater within archetypes (0.57 to 0.77), and increased with geographic, phylogenetic and life history similarity. Leveraging shared attractors increased prediction skill in ~90% of cases, raising mean recruitment skill from 0.38 to 0.75 and even enabling moderate prediction for otherwise poorly predictable stocks. These results reveal that marine fish population dynamics are not heterogeneous but are realizations of a single attractor structured by trophic level, with immediate predictive benefits for global fisheries.

ecology↗

bioRxiv2026

Characterizing benthic community structure across Western Pacific seamounts to ~5,000 m depth: Implications for conservation

AimSeamounts are key components of deep-sea ecosystems. Yet, their biodiversity patterns and conservation needs remain poorly understood, presenting a critical knowledge gap as they face multiple environmental stressors. Here, we aim to characterize benthic community structure across multiple seamounts along the Kyushu-Palau Ridge (KPR) and identify conservation priorities. LocationPhilippine Sea in the Western Pacific. Major taxa studiedDeep-sea benthos. MethodsWe surveyed six transects (13.3{degrees}N-22.9{degrees}N; 614-5,055 m depth; 165 kilometers in total length) using a towed camera system, yielding 31,342 images and 14,218 identified individuals. Community structure was assessed through species depth-range overlap analysis to distinguish nestedness versus turnover patterns. {beta}-diversity was partitioned into local contributions (LCBD) and species contributions (SCBD) to evaluate site-level uniqueness and species-level influence. Generalized linear mixed models were used to relate LCBD and SCBD to depth, slope, aspect, bathymetric position, and functional traits. ResultsCommunity structures varied among slopes and seamounts. Western, steeper slopes were dominated by nestedness, whereas gentler eastern slopes showed mixed patterns of nestedness and gradual turnover. Sessile species largely exhibited nestedness, while mobile taxa showed mixed structures. LCBD declined with depth overall but increased on north-facing slopes and sites with higher broad-scale bathymetric position. Wide-ranging generalist species, particularly among Echinoidea and Holothuroidea, contributed disproportionately to {beta}-diversity. Main conclusionsSeamount benthic communities along the KPR are structured by interactions between depth, geomorphology, and species ecological breadth. The dominance of nestedness on western slopes suggests that protecting shallow, species-rich habitats could capture much of the biodiversity therein. In contrast, the mixed structures on eastern slopes indicate the need for a hybrid conservation approach that includes both shallow summits and deeper, compositionally distinct zones. Our findings highlight the importance of slope-specific, depth-informed strategies to conserve these vulnerable marine ecosystems.

ecology↗

bioRxiv2026

The effects of fox movement and landscape heterogeneity on the spread of sarcoptic mange in urban settings

ContextThe movement of vertebrate hosts across urbanized landscapes can play a key role in the transmission of direct-contact diseases. Understanding how wildlife hosts move in urban landscapes, and how transmission is affected by their landscape-constrained and disease-altered movements, is imperative for better predicting the spread of disease. ObjectiveWe assess how the movement of red foxes (Vulpes vulpes) according to landcover type, and their infection status, affect the spread of mange (caused by Sarcoptes scabiei) in an urbanized landscape. MethodsWe developed a mange transmission model (MTM) using an agent-based model to compare two movement behaviours of foxes in Scarborough (Ontario, Canada): random and landcover-based. We further assessed the effects of movement on disease transmission by considering the foxs infection status and comparing a range of movement probability scenarios. We quantified the number of effective contact events and the effective reproduction number (Re) according to each scenario. ResultsWe found that both landcover-dependent movement and infection status influenced the spread of mange within fox populations. The number of effective contact events and effective reproduction number Re was greatest when landscape heterogeneity was included in the model and foxes moved through paths of least resistance to movement, and when susceptible and infected foxes had an equal probability of leaving a fragmented habitat patch. ConclusionsOur findings suggest that mange spread may be accelerated along movement corridors in fragmented, heterogenous landscapes. As urban areas expand and remnant habitat within these is further lost and animals are relegated to fewer movement pathways, disease transmission may increase.

ecology↗

bioRxiv2025

Changes in sea ice alter genetic structure of an iconic Arctic apex predator in less than three decades

Climate change is having profound effects on biodiversity and species distributions worldwide. Nowhere are these effects potentially more pronounced than in the Arctic, where warming is almost two times the global average, and where year-round sea ice extent has significantly decreased, affecting many ice-dependent species. The polar bear (Ursus maritimus) is a circumpolar, apex Arctic predator, a sentinel of climate change, and a symbol of conservation. It is of immense cultural and spiritual importance to Inuit peoples and is hunted across the Arctic. Declines in sea ice have caused habitat fragmentation and loss, disrupting movement and prey access, potentially altering genetic structure and influencing polar bears potential to persist. Using samples collected from 1997 to 2020 by Inuit across much of the Canadian Arctic, 322 genome-wide autosomal DNA markers specifically designed to quantify polar bear genetic structure and a very stringent spatial-temporal method, we compare polar bear spatial genetic structure and landscape features between two periods across a consistent distribution:1997-2008 and 2009-2020. We observe marked changes in spatial genetic structure across the Arctic Archipelago over just two decades, shifting the boundaries between polar bear genetic clusters by [~]250 km. Landscape resistance models reveal the importance of sea ice and land cover type for each period, with spatial lag models showing that genetic change is best predicted by sea ice shifts between periods. Our study reveals rapid changes in genetic structure of polar bears in the Canadian Arctic, helps to inform conservation and management, and offers insight on future polar bear persistence across its immense, remote distribution.

genomics↗

bioRxiv2025

Identifying Priority Stepping Stone Reefs to Maintain Global Networks of Connected Coral Reefs

Conserving coral reef climate refugia is a key conservation strategy to address climate change. Yet, the accelerating impacts of coral bleaching and other anthropogenic pressures can jeopardize refugia persistence. The dispersal of coral larvae can increase long-term reef persistence through metapopulation dynamics if connected reefs can share beneficial adaptations to bleaching and facilitate demographic recovery. Here, we modelled reef connectivity using a network approach to identify present-day coral larval dispersal networks of predicted climate refugia and then determined locations of stepping stone reefs that can be used to connect these global networks of refugia. We identify 10 key locations of coral reef stepping stones in Indonesia, Mozambique, Glorioso Islands, and Malaysia that may ensure that 84,564km2 of refugia could remain connected together even if other (non-refugia) reefs become degraded. Global coral reef conservation efforts should consider prioritizing these stepping stones to build more redundancy and resilience into future-proofing conservation strategies.

ecology↗

bioRxiv2023

Unveiling Urban Complexity: Integrating OpenStreetMap to enhance representation of fine-scale landscape heterogeneity

Landscape heterogeneity has an impact on wildlife behavior, their interactions, and their persistence. Urban landscapes are among the worlds most heterogeneous landscapes, yet current global landcover maps classify developed land in a single landcover type. This limits the spatial scale at which urban ecologists can approach research questions. OpenStreetMap (OSM), an open-source mapping platform, can be leveraged to enhance the representation of landscape heterogeneity in developed areas. For this, we extracted OSM features with attributes representing infrastructure, land use and green cover, integrating these into a continental landcover map through a globally applicable computational framework. We validated our OSM-enhanced landcover layer against existing remote sensing, aerial photography, and local governmental maps for 33 cities in North America. Our frameworks output provides an 89% accurate representation of landscape heterogeneity. We discuss caveats, potential improvements, and ecological applications. Our OSM-based landcover enhancement framework will facilitate the use of open-source landscape information for improved ecological modeling and urban planning.

ecology↗

bioRxiv2022

Reconceptualizing beta diversity: a hypervolume geometric approach

Beta diversity--the variation among community compositions in a region--is a fundamental measure of biodiversity. Despite a diverse set of measures to quantify beta diversity, most measures have posited that beta diversity is maximized when each community has a single distinct species. However, this assumption overlooks the ecological significance of species interactions and non-additivity in ecological systems, where the function and behaviour of species depend on other species in a community. Here, we introduce a geometric approach to measure beta diversity as the hypervolume of the geometric embedding of a metacommunity. This approach explicitly accounts for non-additivity and captures the idea that introducing a unique, species-rich community composition to a metacommunity increases beta diversity. We show that our hypervolume measure is closely linked to and naturally extends previous information- and variation-based measures while providing a unifying geometric framework for widely adopted extensions of beta diversity. Applying our geometric measures to empirical data, we address two long-standing questions in beta diversity research--the latitudinal pattern of beta diversity and the effect of sampling effort--and present novel ecological insights that were previously obscured by the limitations of traditional approaches. In sum, our geometric approach reconceptualizes beta diversity, offering an alternative and complementary perspective to previous measures, with immediate applicability to existing data.

ecology↗

bioRxiv2022

Conservation networks do not match ecological requirements of amphibians

O_LIAmphibians are among the most threatened taxa as they are highly sensitive to habitat degradation and fragmentation. They are considered as model species to evaluate habitats quality in agricultural landscapes. In France, all amphibian species have a protected status requiring recovery plans for their conservation. Conservation networks combining protected areas and green infrastructure can help the maintenance of their habitats while favouring their movement in fragmented landscapes such as farmlands. Yet, assessing the effectiveness of conservation networks is challenging. C_LIO_LIHere, we compared the ecological requirements of amphibian species with existing conservation network coverage in a human-dominated region of western France. First, we mapped suitable habitat distributions for nine species of amphibian with varying ecological requirements and mobility. Second, we used stacking species distribution modelling (SSDM) to produce multi-species habitat suitability maps. Then, to identify spatial continuity in suitable habitats at the regional scale, we defined species and multi-species core habitats to perform a connectivity analysis using Circuitscape theory. Finally, we compared different suitability maps with existing conservation networks to assess conservation coverage and efficiency. C_LIO_LIWe highlighted a mismatch between the most suitable amphibian habitats at the regional scale and the conservation network, both for common species and for species of high conservation concern. We also found two bottlenecks between areas of suitable habitat which might be crucial for population movements induced by global change, especially for species associated with hedgerow mosaic landscapes. These bottlenecks were not covered by any form of protection and are located in an intensive farmland context. C_LIO_LISynthesis and applications - We advocate the need to better integrate agricultural landscape mosaics into species conservation planning as well as to protect and promote agroecological practices suitable for biodiversity, including mixed and extensive livestock farming. We also emphasize the importance of interacting landscape elements of green infrastructure for amphibian conservation and the need for these to be effectively considered in land-use planning policies. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/500425v4_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1b6446forg.highwire.dtl.DTLVardef@146e7c7org.highwire.dtl.DTLVardef@1ad210org.highwire.dtl.DTLVardef@d545a0_HPS_FORMAT_FIGEXP M_FIG C_FIG PCI recommendation : https://ecology.peercommunityin.org/articles/rec?id=504

ecology↗

bioRxiv2022

Rapid monitoring for ecological persistence

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of ecological communities is largely supported by its structured architecture of species interactions, known as an ecological network. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, we can only monitor small subsets of these networks due to logistical sampling constraints. There is therefore an urgent need to establish links between the small snapshots of data conservationists are able to collect, and the big picture conclusions about ecosystem health demanded by policy makers, scientists and societies. Here we show that the persistence of small subnetworks in isolation -- that is, their persistence when considered separately from the larger network of which they are a part -- is a reliable probabilistic indicator of the persistence of the network as a whole. Our results are general across both antagonistic and mutualistic interaction networks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies. This could significantly improve our ability to monitor progress towards achieving policy targets, such as those enshrined in the UN Convention on Biological Diversity.

ecology↗

bioRxiv2020

Dynamic larval dispersal can mediate the response of marine metapopulations to multiple climate change impacts

Climate change is having multiple impacts on marine species characterized by sedentary adult and pelagic larval phases, from increasing adult mortality to changes in larval duration and ocean currents. Recent studies have shown impacts of climate change on species persistence through direct effects on individual survival and development, but few have considered the indirect effects mediated by ocean currents and species traits such as pelagic larval duration. We used a density-dependent and stochastic metapopulation model to predict how changes in adult mortality and dynamic connectivity can affect marine metapopulation stability. We analyzed our model with connectivity data simulated from a biophysical ocean model of the northeast Pacific coast forced under current (1998-2007) and future (2068-2077) climate scenarios in combination with scenarios of increasing adult mortality and decreasing larval duration. Our results predict that changes of ocean currents and larval duration mediated by climate change interact in complex and opposing directions to shape local mortality and metapopulation connectivity with synergistic effects on regional metapopulation stability: while species with short larval duration are most sensitive to temperature-driven reduction in larval duration, the response of species with longer larval duration are mostly mediated by changes in both the mean and variance of larval connectivity driven by ocean currents. Our results emphasize the importance of considering the spatiotemporal structure of connectivity in order to predict how the multiple effects of climate change will impact marine populations.

ecology↗

bioRxiv2020

Networks of marine protected areas under fluctuating connectivity: the importance of within-MPA dynamics

The design of marine protected areas (MPAs) has been optimized under assumptions of spatially and temporally homogeneous larval dispersal, despite complex spatiotemporal patterns displayed by ocean currents. Here we studied the effect of dispersal variability on the effectiveness of MPA networks across scales. We adopted a nested approach integrating the dynamics of both within and among MPA connectivity into a stochastic metapopulation model and first derived metapopulation persistence (required reproductive effort) and stability over MPA networks by partitioning within and among MPA contributions in relation to the spatial resolution of within-MPA connectivity. We applied this framework over a range of dispersal traits (spawning time and pelagic larval duration) and MPA network configurations, based on simulated biophysical connectivity along the northeast Pacific coast. Our results show how within-MPA dynamics affect predictions based on parameters of MPA networks such as MPA size, spacing, and pelagic larval duration. Increasing within-MPA spatial resolution predicted increasing population persistence and stability independently of other network properties. High-resolution within-MPA dynamics also predicted a negative relationship between species persistence and MPA spacing while that relationship was non-monotonic under low-resolution within-MPA dynamics. Our analysis also resolved the role of pelagic larval duration for scaling up within-MPA dynamics to MPA networks: species with short larval duration led to increasing network stability with MPA spacing while the opposite was observed for species with long larval duration. Our study stresses the importance of integrating fluctuating larval connectivity, both within and among MPAs, and more specifically suggest the benefit of small and nearby MPAs under increasing ocean variability.

ecology↗

bioRxiv2020

Modelling the spatial-temporal distributions and associated determining factors of a keystone pelagic fish

Mobile pelagic species habitat is structured around dynamic oceanographic and ecological processes which operate and interact horizontally and vertically throughout the water column and change over time. However, pelagic species movements and distributions are often poorly understood. We use the Maxent species distribution model to assess how changes in the relative importance of modelled oceanographic (e.g., temperature) and climatic variables (e.g., the North Atlantic Oscillation) over 17-years affect the monthly average horizontal and vertical distribution of a keystone pelagic forage species, Atlantic Canadian capelin (Mallotus villosus). We show the range and distribution of capelin occurrence probabilities vary across horizontal and vertical axes over time, with binary presence/absence predictions indicating capelin occupy between 0.72% (April) and 3.45% (November) of the total modelled space. Furthermore, our analysis reveals that the importance of modelled oceanographic variables, such as temperature, vary between months (44% permutation importance in August to 2% in May). By capturing the spatial dynamics of capelin over horizontal, vertical, and temporal axes, our analysis builds on work that improves our understanding and predictive modelling ability of pelagic species distributions under current and future conditions for pro-active ecosystem-based management.

ecology↗

bioRxiv2018

Revealing biases in the sampling of ecological interaction networks

The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases in both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These issues may affect the accuracy of empirically constructed ecological networks. Yet statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying ecological networks structure. To explore properties of large-scale modular networks, we developed EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different sampling designs that may be employed in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties accurately depends both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, the modules with nested structure were the easiest to detect, regardless of sampling design. Sampling according to species degree (number of interactions) was consistently found to be the most accurate strategy to estimate network structure. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. We recommend that these findings be incorporated into field sampling design of projects aiming to characterize large species interactions networks to reduce sampling biases.\n\nAuthor SummaryEcological interactions are commonly modeled as interaction networks. Analyses of such networks may be sensitive to sampling biases and detection issues in both the interactors and interactions (nodes and links). Yet, statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying networks structure. For insight into ecological networks, we developed software EcoNetGen (available in R and Python). These allow the generation and sampling of several types of large-scale modular networks with predetermined topologies, representing a wide variety of communities and types of ecological interactions. Networks can be sampled according to designs employed in field observations. We demonstrate, through first uses of this software, that underlying network topology interacts strongly with empirical sampling design, and that constructing empirical networks by starting with highly connected species may be the give the best representation of the underlying network.

ecology↗

bioRxiv2017

Integrating Over Uncertainty In Spatial Scale Of Response Within Multispecies Occupancy Models Yields More Accurate Assessments Of Community Composition

O_LISpecies abundance and community composition are affected not only by the local environment, but also by broader landscape and regional context. Yet determining the spatial scale at which landscapes affect species remains a persistent challenge that hinders ecologists abilities to understand how environmental gradients influence species presence and shape entire communities, especially in the face of data deficient species and imperfect species detection.\nC_LIO_LIHere we present a Bayesian framework that allows uncertainty surrounding the true spatial scale of species responses (i.e., changes in presence/absence) to be integrated directly into a community hierarchical model.\nC_LIO_LIThis scale selecting multi-species occupancy model (ssMSOM) estimates the scale of response, and shows high accuracy and correct type I error rates across a broad range of simulation conditions. In contrast, ensembles of single species GLMs frequently fail to detect the correct spatial scale of response, and are often falsely confident in favoring the incorrect spatial scale, especially as species detection probabilities deviate from perfect.\nC_LIO_LIIntegrating spatial scale selection directly into hierarchical community models provides a means of formally testing hypotheses regarding spatial scales of response, and more accurately determining the environmental drivers that shape communities.\nC_LI

ecology↗

bioRxiv2017

Analyzing ecological networks of species interactions

Networks provide one of the best representations for ecological communities, composed of many species with sometimes complex connections between them. Yet the methodological literature allowing one to analyze and extract meaning from ecological networks is dense, fragmented, and unwelcoming. We provide a general overview to the field of using networks in community ecology, outlining both the intent of the different measures, their assumptions, and the contexts in which they can be used. When methodologically justified, we suggest good practices to use in the analysis of ecological networks. We anchor this synopsis with examples from empirical studies, and conclude by highlighting what identified as needed future developments in the field.

ecology↗

bioRxiv2016

Geographical restructuring of Arabidopsis thaliana’s genetic makeup in the Iberian Peninsula due to climate change based on genetic cluster membership

AimTo assess the effects of climate change on genetic lineages of Arabidopsis thaliana at the admixed population level by directly modelling genetic cluster membership values to predict potential genetic cluster memberships across the Iberian Peninsula.\n\nLocationIberian Peninsula\n\nMethodsWe used a dataset of 274 accessions structured in four genetic clusters as inferred from 250 nuclear single-nucleotide polymorphisms with Bayesian clustering methods. We predicted the change in percentages of genetic cluster membership at a population level and the changes in potential suitability across the study area by combining parametric (Beta regression) and non-parametric (Recursive trees) methods.\n\nResultsClimate change will affect genetic lineages of Arabidopsis thaliana differently. Genetic clusters GC1 and GC2 will suffer a substantive reduction of their respective suitable areas while GC3 and GC4 will expand northward. At the population level, except for GC4, the rest of the lineages will undergo a genetic turnover for many of their populations.\n\nMain conclusionsA. thaliana in the Iberian Peninsula will undergo a major internal genetic restructuring and range change due to climate change. Genetic lineages of Arabidopsis thaliana in the Iberian Peninsula will be affected differently which reinforce the need for taking into account intraspecific genetic variation when modelling species distribution. Despite limited predictive power of individual statistical models, the combination of distinct models can compensate this shortcoming.

ecology↗