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Data from: Life-stage differences in spatial genetic structure in an irruptive forest insect: implications for dispersal and spatial synchrony
James, Patrick M. A.; Cooke, Barry; Brunet, Bryan; Lumley, Lisa; Sperling, Felix; Fortin, Marie-Josée; Quinn, Vanessa S.; Sturtevant, Brian R.; Brunet, Bryan M. T.; Lumley, Lisa M.; Sperling, Felix A. H. — 2014-12-03 Dispersal determines the flux of individuals, energy, and information and is therefore a key determinant of ecological and evolutionary dynamics. Yet, it remains difficult to quantify its importance relative to other factors. This is particularly true in cyclic populations in which demography, drift, and dispersal contribute to spatio-temporal variability in genetic structure. Improved understanding of how dispersal influences spatial genetic structure is needed to disentangle the multiple processes that give rise to spatial synchrony in irruptive species. In this study, we examined spatial genetic structure in an economically important irruptive forest insect, the spruce budworm (Choristoneura fumiferana) to better characterize how dispersal, demography, and ecological context interact to influence spatial synchrony in a localized outbreak. We characterized spatial variation in microsatellite allele frequencies using 231 individuals and 7 geographic locations. We show that: (1) gene flow among populations is likely very high (Fst ≈ 0); (2) despite an overall low level of genetic structure, important differences exist between adult (moth) and juvenile (larvae) life-stages; and (3) the localized outbreak is the likely source of moths captured elsewhere in our study area. This study demonstrates the potential of using molecular methods to distinguish residents from migrants and for understanding how dispersal contributes to spatial synchronization. In irruptive populations, the strength of genetic structure depends on the timing of data collection (e.g., trough vs. peak), location, and dispersal. Taking into account this ecological context allows us to make more general characterizations of how dispersal can affect spatial synchrony in irruptive populations.
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Data from: Asymmetric oceanographic processes mediate connectivity and population genetic structure as revealed by RADseq in a highly dispersive marine invertebrate (Parastichopus californicus)
Xuereb, Amanda; Benestan, Laura; Normandeau, Eric; Daigle, Rémi M.; Curtis, Janelle M.R.; Bernatchez, Louis; Fortin, Marie-Josée; Curtis, Janelle M. R. — 2018-03-20 Marine populations are typically characterized by weak genetic differentiation due to the potential for long-distance dispersal favouring high levels of gene flow. However, strong directional advection of water masses or retentive hydrodynamic forces can influence the degree of genetic exchange among marine populations. To determine the oceanographic drivers of genetic structure in a highly dispersive marine invertebrate, the giant California sea cucumber (Parastichopus californicus), we first tested for the presence of genetic discontinuities along the coast of North America in the northeastern Pacific Ocean. Then, we tested two hypotheses regarding spatial processes influencing population structure: (i) isolation-by-distance (IBD: genetic structure is explained by geographic distance), and (ii) isolation-by-resistance (IBR: genetic structure is driven by ocean circulation). Using RADseq, we genotyped 717 individuals from 24 sampling locations across 2,719 neutral SNPs to assess the degree of population differentiation, and integrated estimates of genetic variation with inferred connectivity probabilities from a biophysical model of larval dispersal mediated by ocean currents. We identified two clusters separating north and south regions, as well as significant, albeit weak, substructure within regions (FST = 0.002, p = 0.001). After modeling the asymmetric nature of ocean currents, we demonstrated that local oceanography (IBR) was a better predictor of genetic variation (R2 = 0.48) than geographic distance (IBD) (R2 = 0.17) and directional processes played an important role in shaping fine-scale structure. Our study contributes to the growing body of literature identifying significant population structure in marine systems and has important implications for the spatial management of P. californicus and other exploited marine species.
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Data from: State-and-transition simulation models: a framework for forecasting landscape change
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Daniel, Colin; Frid, Leonardo; Sleeter, Benjamin; Fortin, Marie-Josée; Daniel, Colin J. — 2017-05-23 A wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features. We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states. We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years. State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.
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Data from: Integrating continuous stocks and flows into state-and-transition simulation models of landscape change
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Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée — 2017-12-11 1.State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete. 2.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions. 3.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years. 4.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between them. With the addition of stocks and flows, STSMs provide a conceptually simple yet powerful approach for characterizing uncertainties in projections of a wide range of questions regarding landscape change.
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Data from: Putatively adaptive genetic variation in the giant California sea cucumber (Parastichopus californicus) as revealed by environmental association analysis of restriction‐site associated DNA sequencing data
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Xuereb, Amanda; Kimber, Christopher M.; Curtis, Janelle M.R.; Bernatchez, Louis; Fortin, Marie-Josée; Curtis, Janelle M. R. — 2018-10-29 Understanding the spatial scale of local adaptation and the factors associated with adaptive diversity are important objectives for ecology and evolutionary biology, and have significant implications for effective conservation and management of wild populations and natural resources. In this study, we used an environmental association analysis (EAA) to identify important bioclimatic variables correlated with putatively adaptive genetic variation in a benthic marine invertebrate – the giant California sea cucumber (Parastichopus californicus) – spanning coastal British Columbia and southeastern Alaska. We used a redundancy analysis (RDA) with 3,699 SNPs obtained using RAD sequencing to detect candidate markers associated with 11 bioclimatic variables, including sea bottom and surface conditions, across two spatial scales (entire study area and within sub-regions). At the broadest scale, RDA revealed 59 candidate SNPs, 86% of which were associated with mean bottom temperature. Similar patterns were identified when population structure was accounted for. Additive polygenic scores, which provide a measure of the cumulative signal across all candidate SNPs, were strongly correlated with mean bottom temperature, consistent with spatially varying selection across a thermal gradient. At a finer scale, 23 candidate SNPs were detected, primarily associated with surface salinity (26%) and bottom current velocity (17%). Our findings suggest that environmental variables may play a role as drivers of spatially varying selection for P. californicus. These results provide context for future studies to evaluate the genetic basis of local adaptation in P. californicus and help inform the relevant scales and environmental variables for in situ field studies of putative adaptive variation in marine invertebrates.
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Data from: The response of amphibian larvae to environmental change is both consistent and variable
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Edge, Christopher B.; Houlahan, Jeff E.; Jackson, Donald A.; Fortin, Marie-Josée — 2016-06-15 Many environments are undergoing rapid environmental change and there is a need to understand the mechanisms by which species can persist in altered environments. Model systems, such as amphibian metamorphosis, which can be generalized across many types of environmental change and across many species, are a powerful tool for understanding mechanisms that facilitate persistence in altered and disturbed environments. Amphibian larvae respond to environmental change by varying age at metamorphosis, or size at metamorphosis. Differential selection pressures on age or size at metamorphosis may result in a differential response among taxa to environmental change. Using a meta-analysis, we investigated whether age at metamorphosis, size at metamorphosis, and larval growth rate vary within and among taxonomic families of amphibians in experiments that modified the environmental temperature, density of individuals, food, hydroperiod and the presence of predators. For all environmental factors except predators, the direction of the response was consistent across most of the studied taxa. However, there was considerable variation in effect size both within and among families. Results demonstrate that amphibian metamorphosis is a valuable model system for studying the effects of environmental change. Yet, we stress the need for caution in making generalizations about how individuals respond to environmental factors that have an indirect effect on physiology and require the perception of an environmental cue, such as the presence of predators.

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(auteur : Fortin, Marie-Josée)

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