Mapping forest composition from the Canadian National Forest Inventory and land cover classification maps

Tree diversity increases decadal forest soil carbon and nitrogen accrual

Increasing soil carbon and nitrogen storage can help mitigate climate change and sustain soil fertility^1,2. A large number of biodiversity-manipulation experiments collectively suggest that high plant diversity increases soil carbon and nitrogen stocks^3,4. It remains debated, however, whether such conclusions hold in natural ecosystems^5-12. Here we analyse Canada's National Forest Inventory (NFI) database with the help of structural equation modelling (SEM) to explore the relationship between tree diversity and soil carbon and nitrogen accumulation in natural forests. We find that greater tree diversity is associated with higher soil carbon and nitrogen accumulation, validating inferences from biodiversity-manipulation experiments. Specifically, on a decadal scale, increasing species evenness from its minimum to maximum value increases soil carbon and nitrogen in the organic horizon by 30% and 42%, whereas increasing functional diversity enhances soil carbon and nitrogen in the mineral horizon by 32% and 50%, respectively. Our results highlight that conserving and promoting functionally diverse forests could promote soil carbon and nitrogen storage, enhancing both carbon sink capacity and soil nitrogen fertility.

Linking genotype to phenotype to identify genetic variation relating to host susceptibility in the mountain pine beetle system

Identifying genetic variants responsible for phenotypic variation under selective pressure has the potential to enable productive gains in natural resource conservation and management. Despite this potential, identifying adaptive candidate loci is not trivial, and linking genotype to phenotype is a major challenge in contemporary genetics. Many of the population genetic approaches commonly used to identify adaptive candidates will simultaneously detect false positives, particularly in nonmodel species, where experimental evidence is seldom provided for putative roles of the adaptive candidates identified by outlier approaches. In this study, we use outcomes from population genetics, phenotype association, and gene expression analyses as multiple lines of evidence to validate candidate genes. Using lodgepole and jack pine as our nonmodel study species, we analyzed 17 adaptive candidate loci together with 78 putatively neutral loci at 58 locations across Canada (N > 800) to determine whether relationships could be established between these candidate loci and phenotype related to mountain pine beetle susceptibility. We identified two candidate loci that were significant across all population genetic tests, and demonstrated significant changes in transcript abundance in trees subjected to wounding or inoculation with the mountain pine beetle fungal associate Grosmannia clavigera. Both candidates are involved in central physiological processes that are likely to be invoked in a trees response to stress. One of these two candidate loci showed a significant association with mountain pine beetle attack status in lodgepole pine. The spatial distribution of the attack-associated allele further coincides with other indicators of susceptibility in lodgepole pine. These analyses, in which population genetics was combined with laboratory and field experimental validation approaches, represent first steps toward linking genetic variation to the phenotype of mountain pine beetle susceptibility in lodgepole and jack pine, and provide a roadmap for more comprehensive analyses.

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year. Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

How the mountain pine beetle (Dendroctonus ponderosae) breached the Canadian Rocky Mountains

The mountain pine beetle (MPB; Dendroctonus ponderosae Hopkins), a major pine forest pest native to western North America, has extended its range north and eastward during an ongoing outbreak. Determining how the MPB has expanded its range to breach putative barriers, whether physical (nonforested prairie and high elevation of the Rocky Mountains) or climatic (extreme continental climate where temperatures can be below −40 °C), may contribute to our general understanding of range changes as well as management of the current epidemic. Here, we use a panel of 1,536 single nucleotide polymorphisms (SNPs) to assess population genetic structure, connectivity, and signals of selection within this MPB range expansion. Biallelic SNPs in MPB from southwestern Canada revealed higher genetic differentiation and lower genetic connectivity than in the northern part of its range. A total of 208 unique SNPs were identified using different outlier detection tests, of which 32 returned annotations for products with putative functions in cholesterol synthesis, actin filament contraction, and membrane transport. We suggest that MPB has been able to spread beyond its previous range by adjusting its cellular and metabolic functions, with genome scale differentiation enabling populations to better withstand cooler climates and facilitate longer dispersal distances. Our study is the first to assess landscape-wide selective adaptation in an insect. We have shown that interrogation of genomic resources can identify shifts in genetic diversity and putative adaptive signals in this forest pest species.

Effects of introgression on the genetic population structure of two ecologically and economically important conifer species: lodgepole pine (Pinus contorta var. latifolia) and jack pine (Pinus banksiana)

Forest trees exhibit a remarkable range of adaptations to their environment, but as a result of frequent and long-distance gene flow, populations are often only weakly differentiated. Lodgepole and jack pine hybridize in western Canada, which adds the opportunity for introgression through hybridization to contribute to population structure and (or) adaptive variation. Access to large sample size, high density SNP datasets for these species would improve our ability to resolve population structure, parameterize introgression, and separate the influence of demography from adaptation. To accomplish this, 454 transcriptome reads for lodgepole and jack pine were assembled using Newbler and MIRA, the assemblies mined for SNPs, and 1536 SNPs were selected for typing on lodgepole pine, jack pine, and their hybrids (N = 536). We identified population structure using both Bayesian clustering and discriminate analysis of principle components. Introgressed SNP loci were identified and their influence on observed population structure was assessed. We found that introgressed loci resulted in increased differentiation both within lodgepole and jack pine populations. These findings are timely given the recent mountain pine beetle population expansion in the hybrid zone, and will facilitate future studies of adaptive traits in these ecologically important species.