Marie-Josée Fortin

University of Toronto, Toronto, Ontario, Canada

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Publications (74)193.77 Total impact

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    ABSTRACT: The International Journal of Molecular Science has previously granted [1–3], and is continuing with our practice of granting, annual awards to recognize outstanding papers in the area of chemistry, molecular physics and molecular biology published in its journal. We are therefore pleased to announce the " International Journal of Molecular Science Best Paper Award " for 2015. Nominations were made by the Editorial Board Members chosen from all papers published in 2011. The awards are issued to reviews and research articles separately. We proudly reveal the following eight papers that have been chosen:
    International Journal of Molecular Sciences 01/2015; 16(122):3700-3704. DOI:10.3390/ijms16023700 · 2.34 Impact Factor
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    ABSTRACT: Peripheral populations often experience more extreme environmental conditions than those in the centre of a species' range. Such extreme conditions include habitat loss, defined as a reduction in the amount of suitable habitat, as well as habitat fragmentation, which involves the breaking apart of habitat independent of habitat loss. The 'threshold hypothesis' predicts that organisms will be more affected by habitat fragmentation when the amount of habitat on the landscape is scarce (i.e., less than 30%) than when habitat is abundant, implying that habitat fragmentation may compound habitat loss through changes in patch size and configuration. Alternatively, the 'flexibility hypothesis' predicts that individuals may respond to increased habitat disturbance by altering their selection patterns and thereby reducing sensitivity to habitat loss and fragmentation. While the range of Canada lynx (Lynx canadensis) has contracted during recent decades, the relative importance of habitat loss and habitat fragmentation on this phenomenon is poorly understood. We used a habitat suitability model for lynx to identify suitable land cover in Ontario, and contrasted occupancy patterns across landscapes differing in cover, to test the 'threshold hypothesis' and 'flexibility hypothesis'. When suitable land cover was widely available, lynx avoided areas with less than 30% habitat and were unaffected by habitat fragmentation. However, on landscapes with minimal suitable land cover, lynx occurrence was not related to either habitat loss or habitat fragmentation, indicating support for the 'flexibility hypothesis'. We conclude that lynx are broadly affected by habitat loss, and not specifically by habitat fragmentation, although occurrence patterns are flexible and dependent on landscape condition. We suggest that lynx may alter their habitat selection patterns depending on local conditions, thereby reducing their sensitivity to anthropogenically-driven habitat alteration.
    PLoS ONE 11/2014; 9(11):e113511. DOI:10.1371/journal.pone.0113511 · 3.53 Impact Factor
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    Darren Norris, Marie-Josée Fortin, William E. Magnusson
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    ABSTRACT: Background Ecological monitoring and sampling optima are context and location specific. Novel applications (e.g. biodiversity monitoring for environmental service payments) call for renewed efforts to establish reliable and robust monitoring in biodiversity rich areas. As there is little information on the distribution of biodiversity across the Amazon basin, we used altitude as a proxy for biological variables to test whether meso-scale variation can be adequately represented by different sample sizes in a standardized, regular-coverage sampling arrangement. Methodology/Principal Findings We used Shuttle-Radar-Topography-Mission digital elevation values to evaluate if the regular sampling arrangement in standard RAPELD (rapid assessments (“RAP”) over the long-term (LTER [“PELD” in Portuguese])) grids captured patters in meso-scale spatial variation. The adequacy of different sample sizes (n = 4 to 120) were examined within 32,325 km2/3,232,500 ha (1293×25 km2 sample areas) distributed across the legal Brazilian Amazon. Kolmogorov-Smirnov-tests, correlation and root-mean-square-error were used to measure sample representativeness, similarity and accuracy respectively. Trends and thresholds of these responses in relation to sample size and standard-deviation were modeled using Generalized-Additive-Models and conditional-inference-trees respectively. We found that a regular arrangement of 30 samples captured the distribution of altitude values within these areas. Sample size was more important than sample standard deviation for representativeness and similarity. In contrast, accuracy was more strongly influenced by sample standard deviation. Additionally, analysis of spatially interpolated data showed that spatial patterns in altitude were also recovered within areas using a regular arrangement of 30 samples. Conclusions/Significance Our findings show that the logistically feasible sample used in the RAPELD system successfully recovers meso-scale altitudinal patterns. This suggests that the sample size and regular arrangement may also be generally appropriate for quantifying spatial patterns in biodiversity at similar scales across at least 90% (≈5 million km2) of the Brazilian Amazon.
    PLoS ONE 08/2014; 9(8):106150. DOI:10.1371/journal.pone.0106150 · 3.53 Impact Factor
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    ABSTRACT: Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., non-independence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.
    05/2014; 1. DOI:10.1002/wat2.1023
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    ABSTRACT: Patterns of jack pine (Pinus banksiana Lambert) pollen cone production are of interest because they may help explain jack pine budworm (Choristoneura pinus pinus Freeman) outbreak patterns. We used generalized linear mixed models to analyze pollen cone production in 180 permanent plots in Ontario, Canada between 1992 and 2008. Pollen cone production increased with stand age, and large trees in sparsely-populated stands produced more pollen cones. Defoliation decreased the propensity of trees to produce pollen cones for at least two years. We also identified important patterns that are not explained by defoliation and stand characteristics. Pollen cone production is spatially synchronized among years, trees in central Ontario produced more pollen cones than trees in northwestern Ontario, and background cone production increased over time in the central region but not in more northwestern plots. Synchronized reproduction is common among tree species, but has not previously been noted for jack pine pollen cones. Increasing cone production in central Ontario may be evidence of changing forest and (or) climatic conditions and deserves further investigation. Our model can be used to quantitatively predict pollen cone production and assess the risk of jack pine budworm defoliation.
    Canadian Journal of Forest Research 03/2014; 44(3). DOI:10.1139/cjfr-2013-0089 · 1.66 Impact Factor
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    ABSTRACT: The persistence of landscape-scale disturbance legacies in forested ecosystems depends in part on the nature and strength of feedback among disturbances, their effects, and subsequent recovery processes such as tree regeneration and canopy closure. We investigated factors affecting forest recovery rates over a 25-year time period in a large (6 million ha) landscape where geopolitical boundaries have resulted in important land management legacies (managed forests of Minnesota, USA; managed forests of Ontario, Canada; and a large unmanaged wilderness). Stand-replacing disturbance regimes were quantified across management zones, both inside and outside a central ecoregion, using a time series of classified land cover data constructed at 5-year intervals between 1975 and 2000. The temporally variable disturbance regime of the wilderness was characterized by fine-scaled canopy disturbances punctuated by less frequent large disturbance events (i.e., fire and blow down). The comparably consistent disturbance regimes of the managed forests of Minnesota and Ontario differed primarily in the size distribution of disturbances – principally clearcut harvesting. Using logistic regression we found that a combination of time since disturbance, mapped disturbance attributes, climate, and differences among management zones affected pixel-scale probabilities of forest recovery that reflect recovery rates. We conclude that the magnitude of divergence in landscape disturbance legacies of this region will be additionally reinforced by regional variations in the human and natural disturbance regimes and their interactions with forest recovery processes. Our analyses compliment traditional plot-scale studies that investigate post-disturbance recovery by (a) examining vegetation trends across a wide range of variability and (b) quantifying the cumulative effects of disturbances as they affect recovery rates over a broad spatial extent. Our findings therefore have implications for sustainable forestry, ecosystem-based management, and landscape disturbance and succession modeling.
    Forest Ecology and Management 02/2014; 313:199–211. DOI:10.1016/j.foreco.2013.10.039 · 2.67 Impact Factor
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    Santiago Saura, Rjan Bodin, Marie-Joseé Fortin
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    ABSTRACT: 1. Climate and land-use changes will require species to move large distances following shifts in their suitable habitats, which will frequently involve traversing intensively human-modified landscapes. Practitioners will therefore need to evaluate and act to enhance the degree to which habitat patches scattered throughout the landscape may function as stepping stones facilitating dispersal among otherwise isolated habitat areas. 2. We formulate a new generalized network model of habitat connectivity that accounts for the number of dispersing individuals and for long-distance dispersal processes across generations. By doing so, we bridge the gap between complex dynamic population models, which are generally too data demanding and hence difficult to apply in practical wide-scale decision-making, and simpler static connectivity models that only consider the amount of habitat that can be reached by a single average disperser during its life span. 3. We find that the loss of intermediate and sufficiently large stepping-stone habitat patches can cause a sharp decline in the distance that can be traversed by species (critical spatial thresholds) that cannot be effectively compensated by other factors previously regarded as crucial for long-distance dispersal (fat-tailed dispersal kernels, source population size). 4. We corroborate our findings by showing that our model largely outperforms previous connectivity models in explaining the large-scale range expansion of a forest bird species, the Black Woodpecker Dryocopus martius, over a 20-year period. 5. The capacity of species to exploit the opportunities created by networks of stepping-stone patches largely depends on species-specific life-history traits, suggesting that species assemblages traversing fragmented landscapes may be exposed to a spatial filtering process driving long-term changes in community composition. 6. Synthesis and applications. Previous static connectivity models seriously underestimate the importance of stepping-stone patches in sustaining rare but crucial dispersal events. We provide a conceptually broader model that shows that stepping stones (i) must be of sufficient size to be of conservation value, (ii) are particularly crucial for the spread of species (either native or invasive) or genotypes over long distances and (iii) can effectively reduce the isolation of the largest habitat blocks in reserves, therefore largely contributing to species persistence across wide spatial and temporal scales.
    Journal of Applied Ecology 01/2014; 51(1):171-182. DOI:10.1111/1365-2664.12179 · 4.75 Impact Factor
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    Santiago Saura, Rjan Bodin, Marie-Joseé Fortin
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    ABSTRACT: All trees with diameter at breast height dbh >= 10.0 cm were stem-mapped in a "terra firme" tropical rainforest in the Brazilian Amazon, at the EMBRAPA Experimental Site, Manaus, Brazil. Specifically, the relationships of tree species with soil properties were determined by using canonical correspondence analyses based on nine soil variables and 68 tree species. From the canonical correspondence analyses, the species were grouped into two groups: one where species occur mainly in sandy sites, presenting low organic matter content; and another one where species occur mainly in dry and clayey sites. Hence, we used Ripley's K function to analyze the distribution of species in 32 plots ranging from 2,500 m(2) to 20,000 m(2) to determine whether each group presents some spatial aggregation as a soil variations result. Significant spatial aggregation for the two groups was found only at over 10,000 m(2) sampling units, particularly for those species found in clayey soils and drier environments, where the sampling units investigated seemed to meet the species requirements. Soil variables, mediated by topographic positions had influenced species spatial aggregation, mainly in an intermediate to large distances varied range (>= 20 m). Based on our findings, we conclude that environmental heterogeneity and 10,000 m(2) minimum sample unit sizes should be considered in forest dynamic studies in order to understand the spatial processes structuring the "terra firme" tropical rainforest in Brazilian Amazon.
    Bosque 01/2014; 35(3):347-355. DOI:10.4067/S0717-92002014000300009 · 0.40 Impact Factor
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    ABSTRACT: Grizzly bear (Ursus arctos) populations across their range are being threatened by anthropogenic development and associated increases in human-caused mortality. However, details surrounding the impact of cumulative human effects are not yet fully understood, as prior research has focused primarily on habitat selection of individual disturbance features, rather than the spatio-temporal dynamics of aggregated disturbance processes. We used grizzly bear relative-abundance information from a DNA population inventory alongside a GIS database of human footprint dynamics to gain insight into the relationships between human disturbance features and the spatial distribution of grizzly bears in west-central Alberta, Canada: a landscape experiencing heavy resource development. We used candidate model-selection techniques and zero-inflated Poisson regression models to test competing hypotheses about disturbance processes, neighborhood effect and landscape characteristics. The best model explained about 57% of the overall variation in relative grizzly bear abundance. Areas with lower 'disturbance exposure' (i.e. high mean distance to new disturbances over time), lower 'neighborhood disturbance' (i.e. disturbance density around those areas), and higher 'availability of regenerating forest', were associated with higher bear abundance. In addition, areas located further away from an adjacent protected area exhibited a higher probability of 'excess absences', accounting indirectly for the cumulative effects of disturbance and the history of human-caused mortality. Our results suggest that managing the spatio-temporal exposure of grizzly bears to new disturbance features may be an important consideration for conserving this species in rapidly changing landscapes.
    Biological Conservation 10/2013; 166:54-63. DOI:10.1016/j.biocon.2013.06.012 · 4.04 Impact Factor
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    ABSTRACT: Aim: We investigate first whether fire regimes resulting from the combination of climate change and fire-fighting policy may affect species distributions in Mediterranean landscapes, and second to what extent distributional dynamics may be constrained by the spatial legacy of historical land use. Location: Catalonia (north-eastern Spain). Methods: We modelled the distributional responses of 64 forest and open-habitat bird species to nine fire-regime scenarios, defined by combining different levels of climate change and fire suppression efficiency. A fire-succession model was used to stochastically simulate land-cover changes between 2000 and 2050 under these scenarios. We used species distribution models to predict habitat suitability and occupancy dynamics under either no dispersal or full dispersal assumptions. Results: Under many simulated scenarios, the succession from shrubland to forest dominated over the creation of new low-vegetation areas derived from wildfires. Consequently, open-habitat specialists were the group most affected by losses of suitable habitat. Fire regimes obtained under scenarios including high fire suppression efficiency resulted in a larger number of bird species experiencing reductions in their distribution area. Main conclusions: Anthropogenic factors, such as historical land-use change and fire suppression, can drive regional distribution dynamics in directions opposite to those expected from climatic trends. This raises the question of what drivers and interactions should be given priority in the prediction of biodiversity responses to global change at the regional scale.
    Journal of Biogeography 08/2013; 40(8). DOI:10.1111/jbi.12111 · 4.97 Impact Factor
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    ABSTRACT: Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies.
    PLoS ONE 05/2013; 8(5):e62392. DOI:10.1371/journal.pone.0062392 · 3.53 Impact Factor
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    ABSTRACT: Aim: Species distribution models (SDMs) coupled with metapopulation dynamics models can integrate multiple threats and population-level processes that influence species distributions. However, multiple sources of uncertainties could lead to substantial differences in model outputs and jeopardize risk assessments. We evaluate uncertainties in coupled species distribution—metapopulation dynamics models and focus on two often underappreciated sources of uncertainty: the choice of general circulation model (GCM) and demographic parameter uncertainty of the metapopulation model. We rank the risks associated with potential climate changes and habitat loss on projected range margin dynamics of the Hooded Warbler (Setophaga citrina). Location: Breeding range of the Hooded Warbler, North America. Methods: Using SDMs, we quantified variability in projected future distributions using four GCMs and a consensus model at the biogeographic scale and assessed the propagation of uncertainty through to metapopulation viability projections. We applied a global sensitivity analysis to the coupled species distribution—metapopulation models to rank the influence of choice of GCM, parameter uncertainty and simulated effects of habitat loss on metapopulation viability, thereby addressing error propagation through the whole modelling process. Results: The Hooded Warbler range was consistently projected to shift north: choice of GCMs influenced the magnitude of change, and variability was spatially structured. Variability in the choice of GCMs propagated through to metapopulation viability at the northern range boundary. Although viability measures were sensitive to the GCM used, measures of direct habitat loss were more influential. Despite the high ranking of vital rates in the global sensitivity analysis, direct habitat loss had a larger negative influence on extinction risk than potential future climate changes. Main conclusions: This work underscores the importance of a global sensitivity analysis framework applied to coupled models to disentangle the relative influence of uncertainties on projections. The use of multiple GCMs enabled the exploration of a range of possible outcomes relative to the consensus GCM, helping to inform risk estimates. Ranking uncertainties informs the prioritization of management actions for species affected by dynamic anthropogenic threats over multiple spatial scales.
    Diversity and Distributions 05/2013; 19(5):541-554. DOI:10.2307/23479776 · 5.47 Impact Factor
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    ABSTRACT: Bayesian state-space movement models have been proposed as a method of inferring behavioural states from movement paths (Morales et al. 2004), thereby providing insight into the behavioural processes from which patterns of animal space use arise in heterogeneous environments. It is not clear, however, how effective state-space models are at estimating behavioural states. We use stochastic simulations of two movement models to quantify how behavioural state movement characteristics affect classification error. State-space movement models can be a highly effective approach to estimating behavioural states from movement paths. Classification accuracy was contingent upon the degree of separation between the distributions that characterize the states (e.g. step length and turn angle distributions) and the relative frequency of the behavioural states. In the best case scenarios classification accuracy approached 100%, but was close to 0% when step length and turn angle distributions of each state were similar, or when one state was rare. Mean classification accuracy was uncorrelated with path length, but the variance in classification accuracy was inversely related to path length. Importantly, we find that classification accuracy can be predicted based on the separation between distributions that characterize the movement paths, thereby providing a method of estimating classification accuracy for real movement paths. We demonstrate this approach using radiotelemetry relocation data of 34 moose (Alces alces). We conclude that Bayesian state-space models offer powerful new opportunities for inferring behavioural states from relocation data.
    Methods in Ecology and Evolution 05/2013; 4(5-5):433-441. DOI:10.1111/2041-210X.12026 · 5.32 Impact Factor
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    ABSTRACT: Understanding the consequences of environmental change on populations is an essential prerequisite for informed management of ecosystems and landscapes. In lieu of quantifying fitness effects directly, which is often difficult, behavioural functional responses provide insight into how animals balance trade-offs, and into thresholds in responses to environmental change.Here, we explore this principle using the response of moose Alces alces L. to roads and restricted-access tracks as a case study. Because roads are associated with the conversion of conifer to mixed deciduous–conifer forest that provides better foraging opportunities, moose in Ontario favour areas of moderate road density at a landscape scale. At a finer scale, however, moose avoid roads. These opposing effects indicate a cost–benefit trade-off. We quantified behavioural responses of moose to roads using road-crossing rate. An expected distribution of crossing rates was derived from correlated random walk null model simulations.Moose exhibited a seasonally variable, nonlinear functional response in road-crossing rate at the within seasonal range scale. A pronounced response to roads was observed when road density reached approximate thresholds of 0·2 and 0·4 km km in summer and winter respectively. Road-crossing rate was proportional to road density, though crossing rates were higher in summer than winter. Crossing rates were best explained by the interaction between mean movement rate and road density. Seasonal differences in road-crossing rate arise from seasonal differences in movement rate and seasonal range area, but not road density within seasonal ranges. Within the protected park, moose did not appear to respond to tracks. Our analysis implies that for the majority of the landscape outside of protected areas the response of moose to roads is pronounced.Synthesis and applications. Identifying thresholds in nonlinear responses to landscape modification is a key management objective as they represent transition zones where small changes can have disproportionately large effects on wildlife populations. We establish these thresholds for moose and roads, but find no response to tracks, implying that the effects of tracks can be mitigated by restricting access to them. We discuss the implications of this work on the problem of moose–vehicle collisions.
    Journal of Applied Ecology 04/2013; 50(2-2):286-294. DOI:10.1111/1365-2664.12042 · 4.75 Impact Factor
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    ABSTRACT: Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).
    Ecology Letters 03/2013; 16(5). DOI:10.1111/ele.12084 · 13.04 Impact Factor
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    ABSTRACT: Woodpecker species have significantly expanded their ranges in the last decades of the twentieth century in Mediterranean Europe, which seems to be closely related to forest maturation following large-scale decline in traditional uses. Here we assess the explicit role of forest landscape connectivity in the colonization of the Great Spotted Woodpecker (Dendrocopos major) and the Black Woodpecker (Dryocopus martius) in Catalonia (NE Spain). For this purpose we combined data on breeding bird atlas (10 × 10 km; 1980–2000) and forest inventories (c. 1 × 1 km, 2000). Forest connectivity was measured through graph theory and habitat availability metrics (inter- and intra-patch connectivity) according to species median natal dispersal distances. The best regressions from a set of alternative models were selected based on AICc. Results showed that connectivity between areas of mature forests [diameter at breast height (dbh) ≥ 35 cm] affected Black Woodpecker colonization events. The probability of colonization of the Great Spotted Woodpecker was greater at localities near the sources of colonization in 1980 and with a high connectivity with other less developed forest patches (dbh < 35 cm). The spatial grain at which landscape connectivity was measured influenced the model performance according to the species dispersal abilities, with the species with the lower mobility (D. major) responding better to the forest connectivity patterns at finer spatial scales. Overall, it seems that both species could expand further in European Mediterranean forests in upcoming years but at slower rates if landscape connectivity according to species requirements does not continue to increase. Hence, a proactive and adaptive management should be carried out in order to preserve these species while considering the related major impacts of global change in Mediterranean Europe.
    European Journal of Forest Research 01/2013; 132(1). DOI:10.1007/s10342-012-0666-x · 1.68 Impact Factor
  • Patrick M. A. James, Marie-Josée Fortin
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    ABSTRACT: Ecological processes such as forest disturbances act on ecosystems at multiple spatial and temporal scales to generate complex spatial patterns. These patterns in turn influence ecosystem dynamics and have important consequences for ecosystem sustainability. Analysis of ecosystem spatial structure is a first step toward understanding these dynamics and the uncertain interactions among processes. There are many spatial statistics available to describe and test spatial pattern within ecosystems and to infer the character of the processes that generated them. Indeed, improving understanding of the processes that create spatial pattern is a central objective of spatial pattern analysis. In addition to standard tests of spatial autocorrelation and patch structure, methods for multi-scale decomposition of spatial data and identification of stationarity are necessary to determine the key spatial scales at which the processes operate and affect ecosystems and to identify meaningful spatial subunits within larger contexts. Finally, tools for identifying ecosystem boundaries are also important to monitor boundary movement and changes in local ecosystem characteristics through time.
    Ecological Systems, 01/2013: pages 101-124; , ISBN: 978-1-4614-5754-1
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    ABSTRACT: Theoretical and empirical studies suggest that well-connected networks of forest habitat facilitate animal movement and contribute to species' persistence and thereby the maintenance of biodiversity. Many structural and functional connectivity metrics have been proposed, e.g., distance to nearest neighboring patch or graph-based measures, but the relative importance of these measures in contrast to nesting habitat at fine spatial scales is not well established. With graph-based measures of connectivity, Euclidean distances between forest patches can be directly related to the preferred gap crossing distances of a bird (functional connectivity). We determined the relative predictive power of nesting habitat, forest cover, and structural or functional connectivity measures in describing the breeding distribution of Hooded Warblers (Setophaga citrina) over two successive breeding seasons in a region highly fragmented by agriculture in southern Ontario. Logistic regression models of nesting occurrence patterns were compared using Akaike's information criterion and relative effect sizes were compared using odds ratios. Our results provide support for the expectation that nest-site characteristics are indeed related to the breeding distribution of S. citrina. However, models based on nesting habitat alone were 4.7 times less likely than a model including functional connectivity as a predictor for the breeding distribution of S. citrina. Models of nest occurrence in relation to surrounding forest cover had lower model likelihoods than models that included graph-based functional connectivity, but these measures were highly confounded. Graph-based measures of connectivity explained more variation in nest occurrence than structural measures of forest connectivity, in both 2004 and 2005. These results suggest that S. citrina selected nesting areas that were functionally connected at their preferred gap crossing distances, but nesting habitat was a critically important predictor of nest occurrence patterns.
    Avian Conservation and Ecology 12/2012; 7(2):3. DOI:10.5751/ACE-00530-070203 · 0.25 Impact Factor
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    ABSTRACT: Understanding what features of the landscape affect species distribution is critical to effectively implement conservation strategies. This study investigates how a boundary analysis framework can be used to characterize the spatial association between boundaries (i.e., spatial locations of high rates of change) in bird species’ distributions and landscape features at the regional scale. The study area covers 92,000 km2 in southern Ontario (Canada) and extends from the Great Lakes-St. Lawrence biome to the southern Canadian Shield biome. Landcover composition was derived from Ontario Land Cover data (1991–1998; 7 types) and elevation data were derived from the Canada3D digital elevation model. Bird distributions were estimated using indicator kriging based on point counts obtained from the Ontario Breeding Bird Atlas data (2001–2005; 60 species). Boundaries were delineated for both data types using a 10 × 10 km cell resolution. Spatial boundary overlap statistics were used to quantify the spatial relationship between landscape features and bird boundaries and tested using a randomization procedure. There was significant positive association and spatial overlap between delineated landscape feature boundaries and bird boundaries. The number of spatially overlapping cells between the two boundary types was 67 out of 164 (41 %) and 76 % of cells were within 11.42 km of each other. These results were statistically significant (P < 0.001) and suggest a strong spatial relationship between high rates of change in landscape features and bird species’ distributions at the regional scale. A boundary analysis framework could be used to identify boundary shifts in response to climate change and anticipate changes in species distributions.
    Landscape Ecology 12/2012; 27(10). DOI:10.1007/s10980-012-9804-6 · 3.57 Impact Factor

Publication Stats

2k Citations
193.77 Total Impact Points

Institutions

  • 2002–2014
    • University of Toronto
      • Department of Ecology and Evolutionary Biology
      Toronto, Ontario, Canada
  • 2010
    • Central University of Venezuela
      • Facultad de Ciencias
      Caracas, Distrito Capital, Venezuela
  • 2004
    • Simon Fraser University
      • School of Resource and Environmental Management
      Burnaby, British Columbia, Canada