[Show abstract][Hide abstract] 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 · 2.86 Impact Factor
[Show abstract][Hide abstract] 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 · 1.68 Impact Factor
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] ABSTRACT: 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.
Catalonia (north-eastern Spain).
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.
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.
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 · 4.59 Impact Factor
[Show abstract][Hide abstract] 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 · 3.23 Impact Factor
[Show abstract][Hide abstract] 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 · 3.67 Impact Factor
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] 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 · 2.10 Impact Factor
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] ABSTRACT: 1. Variation in forest gap size and duration are a result of spatial contiguity and continuity of gap infilling and tree mortality over time, which influences both species recruitment and successional pathways.
2. As many gaps in boreal forests are small, their size and duration will affect the conditions influencing species recruitment. We investigate the spatial dynamics of these gaps (i.e. those which are persistent, ephemeral, expanding, displaced or disappearing) and tested whether gap spatio-temporal patterns are consistent over different temporal periods (1998–2003 and 2003–2007).
3. Forest canopy gaps were reconstructed for three plots (10, 10 and 6 ha in size) in southern boreal mixedwood forests around Lake Duparquet, north-western Quebec (Canada), using a time series of high-resolution canopy surface profiles from three light and ranging detection (lidar) system surveys during a 9-year window. High-resolution images were used to individually identify early and late successional gap makers. Dynamic changes in canopy gaps over a 9-year period were investigated by implementing concepts of random set theory within a temporal GIS framework. Mortality was higher on the gap edges than in the forest interior, and shade tolerant species were more likely to be gap makers than shade intolerant species. Edge trees that died causing the expansion of gaps were much smaller than trees creating new gaps. Although the overall gap size distribution was consistent over the 9 years studied, the proportion of the total area opening and closing varied between periods. Independent analyses of time windows show an abundance of small gaps (below 40 m2) appearing and disappearing; however, analysis of spatial contiguity shows that the majority (over 80%) of gaps of all sizes were displaced and/or expanded.
4. Synthesis. Contrary to the previous perception that small gaps are ephemeral, which would favour the recruitment of late successional species, our findings indicate that gap displacement and expansion may be a mechanism explaining the maintenance of favourable conditions for the recruitment of shade intolerant individuals, which has been previously observed in high-latitude old-growth boreal forests.
Journal of Ecology 09/2012; 100(5):1257-1268. DOI:10.2307/23257547 · 5.52 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A critical part of ecological studies is to quantify how landscape spatial heterogeneity affects species’ distributions. With advancements in remote sensing technology and GIS, we now live in a data-rich era allowing us to investigate species–environment relationships in heterogeneous landscapes at multiple spatial scales. However, the degree and type of spatial heterogeneity changes depending on the spatial scale at which species–environment relationships are analysed. Here we present the current spatial analytic methods used in ecological studies to quantify ecological spatial heterogeneity. To determine the key spatial scales at which underlying ecological processes act upon species, we recommend use of spectral decomposition techniques such as wavelet analysis or Moran’s eigenvector maps. Following this, a suite of spatial regression methods can be used to quantify the relative influence of environmental factors on species’ distributions. Finally, spatial graph metrics can be employed to quantify the effects of spatial heterogeneity on landscape connectivity across or within species’ ranges and can be used as additional predictors in spatial regression models. We emphasize how spatial statistics, spatial regression, and spatial graph theory can be used to provide insights into how landscape spatial complexity influences species distributions and to better understand species response to global change.
[Show abstract][Hide abstract] ABSTRACT: Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.
[Show abstract][Hide abstract] ABSTRACT: The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.
[Show abstract][Hide abstract] ABSTRACT: Landscape connectivity is a multi-scalar concept
allowing the investigation of how the interaction
between species movement abilities and landscape
structure affects species survival, gene flow and other
key ecological processes in fragmented landscapes.
This requires the determination of functional connectivity
which is the end result of a complex combination
of multiple factors such as habitat amount and
arrangement, matrix quality and permeability, species
perceptions and dispersal behaviour, population density,
etc. Functional connectivity quantification necessitates
also the consideration of the impacts and
constraints imposed by the increasing rates of landscape
and environmental change, which are ultimately
driven by socioeconomic factors and are likely to
continue putting more pressures on both managed and
[Show abstract][Hide abstract] ABSTRACT: Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance.
International Journal of Molecular Sciences 12/2011; 12(2):865-89. DOI:10.3390/ijms12020865 · 2.86 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Sustainable forest management (SFM) recognizes that the spatial and temporal patterns generated at different scales by natural
landscape and stand dynamics processes should serve as a guide for managing the forest within its range of natural variability
(Landres et al. 1999; Gauthier et al. 2008). Landscape simulation modeling is a powerful tool that can help encompass such
complexity and support SFM planning (Messier et al. 2003). Forecasting the complex behaviors of a forested landscape involving
patterns and processes that interact at multiple temporal and spatial scales poses significant challenges (Gunderson and Holling
2002). Empirical evidence for the functioning of key elements, such as succession and disturbance regimes, is crucial for
model parameterization (Mladenoff 2004). However, reliable empirical data about the forest vegetation dynamics that arise
in response to forest management and other disturbances may be scarce, particularly in remote areas where harvesting activity
has been historically limited.
Expert Knowledge and Its Application in Landscape Ecology, 10/2011: pages 189-210;