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The representation of snow processes in forest growth models is necessary to accurately predict the hydrological cycle in boreal ecosystems and the isotopic signature of soil water extracted by trees, photosynthates and tree-ring cellulose. Yet, most process-based models do not include a snow module; consequently, their simulations may be biased in cold environments. Here, we modified the MAIDENiso model to incorporate a new snow module that simulates snow accumulation, melting and sublimation, as well as thermal exchanges driving freezing and thawing of the snow and the soil. We tested these implementations in two sites in eastern and western Canada for black spruce (Picea mariana (Mill.) B.S.P.) and white spruce (Picea glauca (Moench) Voss) forests, respectively. The new snow module improves the skills of the model to predict components of the hydrological cycle. The MAIDENiso model is now able to reproduce the spring discharge peak and to simulate stable oxygen isotopes in tree-ring cellulose more realistically than in the original snow-free version of the model. The new implementation also results in simulations with a higher contribution from the source water on the oxygen isotopic composition of the simulated cellulose, leading to more accurate estimates of cellulose isotopic composition. Future work may include the development of inverse modelling with this new version of MAIDENiso to produce robust reconstructions of the hydrological cycle and isotope processes in cold environments. [ABSTRACT FROM AUTHOR]

The representation of snow processes in forest growth models is necessary to accurately predict the hydrological cycle in boreal ecosystems and the isotopic signature of soil water extracted by trees, photosynthates and tree-ring cellulose. Yet, most process-based models do not include a snow module, consequently their simulations may be biased in cold environments. Here, we modified the MAIDENiso model to incorporate a new snow module that simulates snow accumulation, melting and sublimation, as well as thermal exchanges driving freezing and thawing of the snow and the soil. We tested these implementations in two sites in East and West Canada for black spruce (Picea mariana) and white spruce (Picea glauca) forests, respectively. The new snow module improves the skills of the model to predict components of the hydrological cycle. The model is now able to reproduce the spring discharge peak and to simulate stable oxygen isotopes in tree-ring cellulose more realistically than in the original, snow-free version of the model. The new implementation also results in simulations with a higher contribution from the source water on the oxygen isotopic composition of the simulated cellulose, leading to more accurate estimates. Future work may include the development of inverse modelling with the new version of MAIDENiso to produce robust reconstructions of the hydrological cycle and isotope processes in cold environments. [ABSTRACT FROM AUTHOR]

The objective of this study was to explore the use of multi-source remotely sensed data for individual tree species. To achieve this, a neutrosophic logic-based method was developed for tree species classification using the combined spectral, textural and structural information derived from WorldView-2 (WV-2) multispectral bands, WV-2 panchromatic band, and LiDAR (Light Detection And Ranging)-derived canopy height model (CHM), respectively. The developed method was tested on the data obtained over the Keele campus, York University, Toronto Canada and the KNN (K Nearest Neighbour) classification method. Twenty-one spectral, three textural and three structural features were used to classify five species (Norway maple, honey locust, Austrian pine, blue spruce, and white spruce). For this study, 522 trees were used for training and 223 for testing. The overall classification accuracy obtained by the proposed method was 0.82. It was significantly improved compared with the KNN (0.73), weighted KNN (0.76), and fuzzy KNN (0.75) methods. In addition, Dempster-Shafer (DS) theory was explored to perform information fusion at the decision level in comparison to that at the feature level. The accuracies obtained by the fusion at the decision level were generally lower than those at the feature level. Even though promising results based on the neutrosophic logic were obtained during this proof-concept stage, studies are underway to perform more tests with a large number of tree crowns and more species and exploit other classification methods, such as support vector machine. [ABSTRACT FROM AUTHOR]

The existence of non-serotinous, non-sprouting species in fire regimes where serotiny confers an adaptive advantage is puzzling, particularly when these species recruit poorly from soil seed banks or from burn edges. In this paper, white spruce (Picea glauca (Moench) Voss) was used to show how the timing of fire relative to seed development may permit non-serotinous species to recolonize burned areas from the aerial seed banks of fire-killed trees. To estimate survival of seeds within closed cones during crown fires, cone heating was simulated using a one-dimensional conduction model implemented in a three-dimensional computational fluid dynamics fire behavior model. To quantify the area burned when germinable seed would be contained within closed cones during a mast year, empirical fire occurrence and seed development (germinability and cone opening) data were compared for multiple locations across the white spruce range. Approximately 12% of cones contained viable seed following crown fire simulations (0.072m s-1 mean spread rate; 9147kW m-1 mean intensity), and roughly half of the historical area burned resulted from fires that occurred when closed cones would contain germinable seed. Together, these results suggest that non-serotinous species may recolonize burned areas from in situ aerial seed banks, and that this may be an important cause of their existence in fire regimes to which they otherwise seem poorly suited. [ABSTRACT FROM AUTHOR]

The existence of non-serotinous, non-sprouting species in fire regimes where serotiny confers an adaptive advantage is puzzling, particularly when these species recruit poorly from soil seed banks or from burn edges. In this paper, white spruce (Picea glauca (Moench) Voss) was used to show that the timing of fire relative to seed development can control aerial seed bank availability for non-serotinous species. To estimate seed survival in closed cones during crown fires, cone heating was simulated using a one-dimensional conduction model implemented in a computational fluid dynamics (Navier--Stokes) fire spread model. To quantify the area burned when germinable seed would be contained in closed cones, empirical fire occurrence and seed development (germinability and cone opening) data were compared for multiple locations across the white spruce range. Approximately 12% of cones contained viable seed following crown fire simulations (0.072ms -1 mean spread rate; 9147 kWm-1 mean intensity), and roughly half of the historical area burned resulted from fires that occurred when closed cones would contain germinable seed. Post-fire recruitment from in situ aerial seed banks can occur for non-serotinous species, and may be an important cause of their existence in fire regimes to which they otherwise seem poorly suited. [ABSTRACT FROM AUTHOR]

High northern latitude regions are experiencing some of the most rapid environmentalchanges. Carbon sequestration might be enhanced by increased forest productivity due towarming temperatures and potentially higher atmospheric CO2, but declines in tree growthand mortality due to drought stress could counteract this enhancement by releasing CO2 tothe atmosphere. Observed changes in boreal forest dynamics are already altering theglobal carbon and hydrological cycles, albedo and land surface feedbacks. Here, wecombined ring-width data with annually resolved stable carbon (δ13C) and oxygenisotope (δ18O) records to investigate the physiological responses of white spruce(Picea glauca [Moench] Voss) trees to warming and increased atmospheric CO2concentrations at northern treeline sites. We developed an extensive network of δ13Cand δ18O tree-ring chronologies covering the 20th century derived from 10 sitesacross North America (NA) spanning from 60.5º to 68.7ºN and 104º to 162ºW. Weused a range of observational data and a climate model to interpret signals in theseannually-resolved tree-ring series. At most sites, the inter-tree correlations werehigher for δ18O than δ13C series. Both δ13C and δ18O were highly influenced bytemperature variations, although the dominant season was different: summer and spring,respectively. This suggests that different processes associated with temperature variationsmay be operating. Physiological processes occurring at leaf level during summermainly influenced δ13C. Spring climate had the strongest influence on tree-ringδ18O via temperature effects on the δ18O of source water, and to a lesser degree,in summer, physiological process at leaf level may also occur. Accordingly, wefound weak relationships between the tree-ring δ18O and atmospheric circulation(such as integrated moisture transport) during summer using the GISS ModelE2isotopically-equipped general circulation model. Calibration and simulations of tree-ring datain the process-based mechanistic model MAIDENiso will help us to elucidate thecomplex linkages between increases in temperature and CO2 driven tree responses.This tree-ring isotope network provides a unique opportunity to disentangle theclimatic and physiological controls driving growth patterns at the northern treeline. [ABSTRACT FROM AUTHOR]