Patrick M. A. James

Considering spatial and temporal scale in landscape-genetic studies of gene flow

Landscape features exist at multiple spatial and temporal scales, and these naturally affect spatial genetic structure and our ability to make inferences about gene flow. This article discusses how decisions about sampling of genotypes (including choices about analytical methods and genetic markers) should be driven by the scale of spatial genetic structure, the time frame that landscape features have existed in their current state, and all aspects of a species’ life history. Researchers should use caution when making inferences about gene flow, especially when the spatial extent of the study area is limited. The scale of sampling of the landscape introduces different features that may affect gene flow. Sampling grain should be smaller than the average home‐range size or dispersal distance of the study organism and, for raster data, existing research suggests that simplifying the thematic resolution into discrete classes may result in low power to detect effects on gene flow. Therefore, the methods used to characterize the landscape between sampling sites may be a primary determinant for the spatial scale at which analytical results are applicable, and the use of only one sampling scale for a particular statistical method may lead researchers to overlook important factors affecting gene flow. The particular analytical technique used to correlate landscape data and genetic data may also influence results; common landscape‐genetic methods may not be suitable for all study systems, particularly when the rate of landscape change is faster than can be resolved by common molecular markers.

Utility of computer simulations in landscape genetics

Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to processes by combining complex and realistic life histories, behaviours, landscape features and genetic data. Central to landscape genetics is the connection of spatial patterns of genetic variation to the usually highly stochastic space–time processes that create them over both historical and contemporary time periods. The field should benefit from a shift to computer simulation approaches, which enable incorporation of demographic and environmental stochasticity. A key role of simulations is to show how demographic processes such as dispersal or reproduction interact with landscape features to affect probability of site occupancy, population size, and gene flow, which in turn determine spatial genetic structure. Simulations could also be used to compare various statistical methods and determine which have correct type I error or the highest statistical power to correctly identify spatio‐temporal and environmental effects. Simulations may also help in evaluating how specific spatial metrics may be used to project future genetic trends. This article summarizes some of the fundamental aspects of spatial–temporal population genetic processes. It discusses the potential use of simulations to determine how various spatial metrics can be rigorously employed to identify features of interest, including contrasting locus‐specific spatial patterns due to micro‐scale environmental selection.

Spatial Genetic Structure of a Symbiotic Beetle-Fungal System: Toward Multi-Taxa Integrated Landscape Genetics

Spatial patterns of genetic variation in interacting species can identify shared features that are important to gene flow and can elucidate co-evolutionary relationships. We assessed concordance in spatial genetic variation between the mountain pine beetle (Dendroctonus ponderosae) and one of its fungal symbionts, Grosmanniaclavigera, in western Canada using neutral genetic markers. We examined how spatial heterogeneity affects genetic variation within beetles and fungi and developed a novel integrated landscape genetics approach to assess reciprocal genetic influences between species using constrained ordination. We also compared landscape genetic models built using Euclidean distances based on allele frequencies to traditional pair-wise Fst. Both beetles and fungi exhibited moderate levels of genetic structure over the total study area, low levels of structure in the south, and more pronounced fungal structure in the north. Beetle genetic variation was associated with geographic location while that of the fungus was not. Pinevolume and climate explained beetle genetic variation in the northern region of recent outbreak expansion. Reciprocal genetic relationships were only detectedin the south where there has been alonger history of beetle infestations. The Euclidean distance and Fst-based analyses resulted in similar models in the north and over the entire study area, but differences between methods in the south suggest that genetic distances measures should be selected based on ecological and evolutionary contexts. The integrated landscape genetics framework we present is powerful, general, and can be applied to other systems to quantify the biotic and abiotic determinants of spatial genetic variation within and among taxa.

Spatial genetic structure of the mountain pine beetle (Dendroctonus ponderosae) outbreak in western Canada: historical patterns and contemporary dispersal

Environmental change has a wide range of ecological consequences, including species extinction and range expansion. Many studies have shown that insect species respond rapidly to climatic change. A mountain pine beetle epidemic of record size in North America has led to unprecedented mortality of lodgepole pine, and a significant range expansion to the northeast of its historic range. Our goal was to determine the spatial genetic variation found among outbreak population from which genetic structure, and dispersal patterns may be inferred. Beetles from 49 sampling locations throughout the outbreak area in western Canada were analysed at 13 microsatellite loci. We found significant north‐south population structure as evidenced by: (i) Bayesian‐based analyses, (ii) north‐south genetic relationships and diversity gradients; and (iii) a lack of isolation‐by‐distance in the northernmost cluster. The north‐south structure is proposed to have arisen from the processes of postglacial colonization as well as recent climate‐driven changes in population dynamics. Our data support the hypothesis of multiple sources of origin for the outbreak and point to the need for population specific information to improve our understanding and management of outbreaks. The recent range expansion across the Rocky Mountains into the jack/lodgepole hybrid and pure jack pine zones of northern Alberta is consistent with a northern British Columbia origin. We detected no loss of genetic variability in these populations, indicating that the evolutionary potential of mountain pine beetle to adapt has not been reduced by founder events. This study illustrates a rapid range‐wide response to the removal of climatic constraints, and the potential for range expansion of a regional population.

Characterizing the physical and genetic structure of the lodgepole pine × jack pine hybrid zone: mosaic structure and differential introgression

Understanding the physical and genetic structure of hybrid zones can illuminate factors affecting their formation and stability. In north‐central Alberta, lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia) and jack pine (Pinus banksiana Lamb) form a complex and poorly defined hybrid zone. Better knowledge of this zone is relevant, given the recent host expansion of mountain pine beetle into jack pine. We characterized the zone by genotyping 1998 lodgepole, jack pine, and hybrids from British Columbia, Alberta, Saskatchewan, Ontario, and Minnesota at 11 microsatellites. Using Bayesian algorithms, we calculated genetic ancestry and used this to model the relationship between species occurrence and environment. In addition, we analyzed the ancestry of hybrids to calculate the genetic contribution of lodgepole and jack pine. Finally, we measured the amount of gene flow between the pure species. We found the distribution of the pine classes is explained by environmental variables, and these distributions differ from classic distribution maps. Hybrid ancestry was biased toward lodgepole pine; however, gene flow between the two species was equal. The results of this study suggest that the hybrid zone is complex and influenced by environmental constraints. As a result of this analysis, range limits should be redefined.

Spatial Community Structure of Mountain Pine Beetle Fungal Symbionts Across a Latitudinal Gradient

Symbiont redundancy in obligate insect–fungal systems is thought to buffer the insect host against symbiont loss and to extend the environmental conditions under which the insect can persist. The mountain pine beetle is associated with at least three well-known and putatively obligate ophiostomatoid fungal symbionts that vary in their environmental tolerances. To better understand the spatial variation in beetle–fungal symbiotic associations, we examined the community composition of ophiostomatoid fungi associated with the mountain pine beetle as a function of latitude and elevation. The region investigated represents the leading edge of a recent outbreak of mountain pine beetle in western Canada. Using regression and principal components analysis, we identified significant spatial patterns in fungal species abundances that indicate symmetrical replacement between two of the three fungi along a latitudinal gradient and little variation in response to elevation. We also identified significant variation in the prevalence of pair-wise species combinations that occur within beetle galleries. Frequencies of pair-wise combinations were significantly different from what was expected given overall species abundances. These results suggest that complex processes of competitive exclusion and coexistence help determine fungal community composition and that the consequences of these processes vary spatially. The presence of three fungal symbionts in different proportions and combinations across a wide range of environmental conditions may help explain the success of mountain pine beetle attacks across a broad geographic range.

Identifying significant scale-specific spatial boundaries using wavelets and null models: spruce budworm defoliation in Ontario, Canada as a case study

We combine wavelet analysis and multiple null models to identify significant spatial scales of pattern and spatial boundaries in historical spruce budworm defoliation in Ontario, Canada. Previous analyses of budworm defoliation in Ontario over the last two outbreaks have suggested three distinct zones of defoliation. We asked the following three questions: (1) is there statistical support for the existence of these three zones? (2) Are the locations of these boundaries consistent between outbreak periods? And (3) how does boundary identification depend on the spatial null model used? Defoliation data for the two outbreak periods (1941–1965 and 1966–2001), and the combined period (1941–2001) were analyzed using a 1D continuous wavelet transform. Boundaries were identified through comparison of wavelet power spectra of each outbreak period to reference distributions based on three different spatial null models: (1) a complete spatial randomness model, (2) an autoregressive model, and (3) a Gaussian random field model. The Gaussian random field model identified coarser scales of pattern than the autoregressive model. Locally, the Gaussian random field model found significant boundaries similar to those previously described, whereas the autoregressive model only did so for the first outbreak. These results indicate that the coarse scale spatial factors that influenced defoliation were more consistent between outbreaks relative to fine scale factors, and that previously described boundaries were strongly driven by the first outbreak. Wavelet analysis combined with spatial null models provides a powerful tool for identifying non-arbitrary scales of structure and significant spatial boundaries in non-stationary ecological data.

Two-dimensional wavelet analysis of spruce budworm host basal area in the Border Lakes landscape

Increases in the extent and severity of spruce budworm (Choristoneura fumiferana Clem.) outbreaks over the last century are thought to be the result of changes in forest structure due to forest management. A corollary of this hypothesis is that manipulations of forest structure and composition can be used to reduce future forest vulnerability. However, to what extent historical forest management has influenced current spatial patterns of spruce budworm host species is unknown. To identify landscape-scale spatial legacies of forest management in patterns of spruce budworm host species (i.e., Abies balsamea and Picea spp.), we analyzed remotely sensed forest data from the Border Lakes landscape of northern Minnesota and northwestern Ontario. Our study area contains three regions with different management histories: (1) fine-scale logging patterns in Minnesota, (2) coarse-scale logging patterns in Ontario, and (3) very limited logging history in the Boundary Waters Canoe Area and adjacent Quetico Provincial Park. We analyzed forest basal-area data using wavelets and null models to identify: (1) at which scales forest basal area is structured, (2) where those scales of pattern are significantly present, and (3) whether regions of local significance correspond to regional boundaries that separate the study area. Results indicate that spatial patterns in host basal area are created by nonstationary processes and that these processes are further constrained by lakes and wetlands. Wavelet analysis combined with significance testing revealed a bimodal distribution of scale-specific wavelet variance and separate zones of host species basal area that partially correspond with regional boundaries, particularly between Minnesota and the Wilderness region. This research represents one of the first comparisons of forest spatial structure in this region across an international border and presents a novel method of two-dimensional wavelet analysis that can be used to identify significant scale-specific structure in spatial data.

Life‐stage differences in spatial genetic structure in an irruptive forest insect: implications for dispersal and spatial synchrony

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 seven geographic locations. We show that (i) gene flow among populations is likely very high (Fst ≈ 0); (ii) despite an overall low level of genetic structure, important differences exist between adult (moth) and juvenile (larvae) life stages; and (iii) 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.

Assessing Knowledge Ambiguity in the Creation of a Model Based on Expert Knowledge and Comparison with the Results of a Landscape Succession Model in Central Labrador

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.