Faculty of Forestry and Environmental Management (Fredericton)

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A comparison between the forestry sector in New Brunswick (Canada) and Hesse (Germany)
A comparison between the forestry sector in New Brunswick (Canada) and Hesse (Germany)
by Christian Scriba, This report provides an in-depth comparison of forestry and forests in the province of New Brunswick (Canada) and the state of Hesse (Germany). The first two sections describe the general situation and circumstances of forests and forestry in New Brunswick and Hesse, respectively, and the third section aims to compare the two forestry sectors to each other in more detail. The comparison shows several significant differences between the two forestry sectors in regard to forest management, forest governance, and factors influencing the economics of the respective forestry sectors. However, often it was not possible to find directly comparable data for Hesse and New Brunswick, which has several reasons. Therefore, the comparisons made in this report are of a relative nature, to see how much of an impact the forestry sector has on the economy and the people living in New Brunswick and Hesse., A Report Submitted in Partial Fulfilment of the Requirements for the Degrees of: Master of Forestry, in the Graduate Academic Unit of Faculty of Forestry and Environmental Management, University of New Brunswick; and Master of Science, Forest Sciences, Faculty of Environment and Natural Resources, Albert-Ludwigs-University Freiburg
A feasibility assessment of wold reintroduction to the Cape Breton Highlands
A feasibility assessment of wold reintroduction to the Cape Breton Highlands
by George H. Williams, This thesis reports an assessment of the feasibility of establishing a viable population of Wolves (Canis sp.) on Cape Breton Island, Nova Scotia as a means of determining if Wolves can limit Moose (Alces alces) abundance in Cape Breton Highlands National Park (CBHNP) to densities desired by Parks Canada ecologists (e.g., 0.5 Moose/km²). As apex carnivores, Wolves are effective in preventing ungulate populations from reaching hyperabundant levels. It is uncertain which Canis species was present in the region prior to pre-European settlement and therefore, I used ArcGIS and Marxan to estimate the amount of available habitat for both Gray (Canis lupus) and Eastern Wolf (C. lycaon) to form territorial packs on Cape Breton Island. The population viability analysis programme VORTEX was used to predict the population size of a viable population, as well as the size needed to limit Moose (A. a. andersoni) abundance to levels less likely to impact vegetation. VORTEX simulated the population by evaluating the annual life cycle and tracking mate selection, reproduction, mortality, increment of age by one year of individuals, as well as migration among populations, removals, and supplementation. Based on the VORTEX model simulations of the long-term viability of both Wolf species, the optimal and suboptimal habitat within the National Park and adjacent highland areas could support 30 C. lupus (16 inside the Park and 14 outside of the Park), or 33 (17 inside the Park, and 16 outside of the Park) C. lycaon, respectfully. Results identified several factors important to the long-term viability of Wolf populations: 1) the percentage of adult females breeding; 2) carrying capacity; and: 3) mortality rates. If the percentage of female breeders (C. lupus) remains 55% or higher, and Wolves are not subject to immediate and long-term anthropogenic mortality risk (modelled as 30% inn mortality pups, 10% in adults), the population maintains a carrying capacity of n = 36 with a low probability of extinction (<0.25). However, based on mainly negative public attitudes to Eastern Coyote in the region, it is presumed that mortality rates will be high outside of the National Park; a Park-only population size of 16 Gray Wolves would not be viable, nor reduce Moose density to desired levels. Even if mortality rates outside the Park were low, population models suggested Wolves may not reduce Moose to desired levels. A static functional response model of Gray Wolves to changing Moose density suggested that a larger Wolf population than theoretically modelled would be required to reduce the local Moose population to desired densities. A preliminary deterministic modelling approach indicated that 30 Wolves might reduce the Moose population to desired densities when the Moose population has a growth rate of 0.1. In conclusion, the likelihood of reintroduced Wolves reducing Moose in CBHNP to desired levels depends on mortality rates outside of the Park is low because the Park itself is too small to contain a viable population of Wolves. Further work on societal attitudes to Wolves would be vital before any Wolf reintroduction program is considered.
A high-resolution digital soil mapping framework for New Brunswick, Canada
A high-resolution digital soil mapping framework for New Brunswick, Canada
by Shane Robert Furze, For decades researchers have been studying forest soils and summarizing findings in the form of soil surveys with thematic soil maps depicting soil associations, broad polygons representing groups of individual soil types. With growing availability of high-resolution spatial data, it has become possible to model and map how individual soil properties vary, both spatially and with depth, across the landscape at high resolution. This dissertation demonstrates how this can be accomplished for the Province of New Brunswick (NB), Canada by way of digital soil mapping (DSM) based on (i) existing soil information and related data sets, (ii) principles of soil formation as dictated by location-specific changes in topography, surficial geology, and climate. For this purpose, existing elevation data sets were fused via error reduction procedures to generate a comprehensive province-wide digital elevation model (DEM) at 10m resolution. The resulting DEM was then used to delineate a variety of data sets detailing spatial variations in topography, hydrology, and climate. Various sources of spatial geology depictions were combined by way of similarities in classifications resulting in re-delineations of landform and lithological attributes. In combination, the data layers generated were used to determine how specific soil properties (n = 12,058) vary, both spatially and with increasing depth, across the province at 10m resolution. These determinations were made possible by way of machine-based random forest regression modelling. This dissertation provides details in terms of how (i) a province-wide soil database was generated from existing soil survey reports, (ii) how missing soil data were substituted through the process of pedotransfer function development and analysis, (iii) how the province-wide DEM layers were fused, and (iv) how the DSM procedure was formulated and executed. The soil properties selected for modelling and mapping purposes refer to soil depth, drainage, bulk density, texture, coarse fragment content, and soil organic matter content. In turn, these properties, in combination with spatial data sets (topography, geology, and climate), can be used to model and map other soil variables such as, e.g., pH, soil water retention at field capacity and permanent wilting point, and cation exchange capacity.
A risk assessment of the potential impact of Mountain Pine Beetle in China
A risk assessment of the potential impact of Mountain Pine Beetle in China
by Yunmiao Sun, Mountain Pine Beetle (Dendroctonus ponderosae) is a species of bark beetle native to western North America that has caused significant financial losses for the forest industry in British Columbia and Alberta, Canada. In 2002, Mountain Pine Beetle was first recorded in China, and, as a non-native species, managers were concerned about the potential impact of this species on various softwood tree species. This report reviews the management of invasive species in general, and then specific management practices used against Mountain Pine Beetle outbreaks in North America. This report then applies the knowledge gained from managing this species in North America to a risk assessment for the species in China. By evaluating its geographical distribution, as well as the probability of introduction, the species’ adaptability, persistence after colonization, and the consequences of introduction, it is concluded that the invasive risk of Mountain Pine Beetle in China is high. To reduce the risk of future beetle outbreak events in China, there will need to be effective monitoring, direct control at the incipient stage, and forest iii modification to increase tree species and age class diversity. Chemical tools plus regeneration and salvage strategies need to be ready in case of the beetle outbreak. Key words: Mountain Pine Beetle, invasive species, invasion, outbreak, management., Electronic Only. A Report Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Forestry In the Graduate Academic Unit of FOREM.
Adapting hydrological modeling for Atlantic Canada's climate, landscape, and vegetation conditions: from field to small and large watersheds
Adapting hydrological modeling for Atlantic Canada's climate, landscape, and vegetation conditions: from field to small and large watersheds
by Junyu Qi, Pollution from nonpoint sources poses a significant threat to aquatic ecosystems. Best management practices (BMPs) can be developed to control soil erosion and reduce the movement of nutrients and sediments from agricultural lands to streams. Direct assessments of the impact of land use change and BMPs on water quantity and quality through field experiments are time-consuming and costly and, as a result, model simulations of hydrological processes and BMPs impacts can serve as a complementary approach to field measurements. However, model simulations require detailed inputs and complex calibration procedures, which may delay their acceptance among decision makers. Central to this thesis is development of a simple decision-support tool for decision makers and economists to evaluate multi-year impacts of land use change and BMPs on water quantity and quality for large ungauged watersheds. The ArcGIS-based tool (i.e., the land use and BMPs assessment tool, LBAT) uses statistical models derived from simulations generated with the Soil and Water Assessment Tool (SWAT). To provide reliable simulations for Atlantic Canada, SWAT was modified to address maritime-winter climate conditions of high snow accumulation. New physically-based soil-temperature and snowmelt modules were developed and incorporated in SWAT to account for snow-insulation effects and rain-on-snow events on the seasonal evolution of soil temperature. It was hypothesized that modification of SWAT would provide superior predictions of water flow and nutrient loadings for Atlantic Canada. With appropriate calibration, the modified version of SWAT was validated against field data collected from a small experimental watershed in northwest New Brunswick, Canada, i.e., the Black Brook watershed (BBW). Once finalized, LBAT and SWAT were applied to a large watershed consisting of the BBW (i.e., Little River watershed). Results suggested that LBAT and a calibrated version of SWAT performed equally well in simulating annual stream flow and sediment and nitrate-N loadings, with LBAT performing slightly better for annual soluble-P loading. In addition, LBAT performed much better than an uncalibrated version of SWAT for sediment and nutrient loadings. The LBAT has a unique role in ungauged watershed management in New Brunswick for its simplicity and flexibility compared with process-based hydrological models. Keywords: best management practices; decision support tool; hydrology; soil and water assessment tool; soil temperature; snowmelt; water pollution
Applications of variable probability sampling using remotely sensed covariates
Applications of variable probability sampling using remotely sensed covariates
by Yung-Han Hsu, Variable probability selection methods are regarded as the most efficient sampling design because sample selection is based on parameters of interest. However, a lack of prior knowledge of covariates for study areas restrict the application in practice. This thesis explored the use of covariates derived from airborne light detection and ranging (LiDAR) scanning (ALS) and a consumer-based spherical camera in selecting sample locations with variable probability. Results shows that list sampling with big BAF sample plots is a highly efficient and cost-effective sampling strategy for effectively calibrating ALSderived estimates to local conditions. For the spherical photography study, ratio estimation also showed the capability to calibrate imprecise covariate estimates; however, sampling efficiency under variable probability selection was not improved relative to simple random sampling. The low correlation between the photo-derived covariate and parameter of interest most likely impacted these results. Optimal covariates need further exploration to improve sampling efficiency.
Assessing climate change impacts on timber supply using species-specific growth and yield impact multipliers method
Assessing climate change impacts on timber supply using species-specific growth and yield impact multipliers method
by Alexander Ryerson, The objective of this thesis is to assess climate change impacts on timber supply from 2010 to 2100 for Crown License 1 in northern New Brunswick, and effects on forest management strategies. Species-specific climate change growth and yield impact multipliers were calculated and adjusted yield curves were input to a timber supply model. Average growth potential of Abies balsamea, Picea sp., and Betula papyrifera was predicted to decrease by 36% by 2100, while Fagus grandifolia, Acer saccharum, and Betula alleghaniensis were predicted to increase by over 200%. At the forest level, the model projected 10 million m3 less softwood merchantable growing stock in year 2100 with climate change impacts under baseline management strategies. Management strategies were adjusted to adapt Crown License 1 to climate change. Softwood merchantable growing stock was 14 million m3 more in year 2070 than with baseline management strategies. This caused larger volume harvested (4 million m3) from 2070-2100.
Assessing climate change impacts on tree growth and yield with process based and statistical models in the province of Newfoundland and Labrador
Assessing climate change impacts on tree growth and yield with process based and statistical models in the province of Newfoundland and Labrador
by Rony Mazumder, Forest Growth and Yield (G&Y) modelling is essential for timber supply analysis and sustainable forest management. Empirical G& Y models are typically developed based on historical data obtained from permanent sample plots (PSP) with an assumption that forest will grow back at the same rate as in the past. With the predicted trend of global warming, growth and yield projections with traditional G& Y models would become invalid because the projected climate change will likely affect forest growth in the future. Therefore, new and innovative approaches are required to account for the potential impacts of climate change on tree growth and yield predictions. In this study, process based and statistical models were used to assess climate change on forest growth and yield in the province of Newfoundland and Labrador, Canada. A process based model (JABOWAIII) was used to assess the impact of climate change on forest G& Y. The model was calibrated with seventy PSPs that cover the entire spectrum of soil and weather conditions. The model results were used to estimate species specific climate change modifiers, which can be used to adjust the existing yield curves to account for the effects of climate change. A multiple regression and an Artificial Neural Network (ANN) models that take into account biophysical conditions and historical climate factors were developed to predict the G& Y of individual trees of forest stands. Thirteen independent variables were included in the statistical based G&Y model. Stand and tree-level independent variables included species distribution, stand age, tree height, tree diameter, stand basal area. Biophysical and climate variables including growing degree days, potential solar radiation, and annual precipitation were also included in the new model as input variables. First- and second-level auto-correlations of growth in individual trees were also considered in the models. Results from the ANN-model were compared with those produced with linear-regression models. Both JABOWAHIII model and statistical model predicted that forest G& Y will be negatively affected by warmer temperature. Uncertainties related to both process-based models and statistical models are also discussed in the thesis., Scanned from archival print submission.
Assessing effects of sampling frequency on the estimation accuracy of different water quality indicators
Assessing effects of sampling frequency on the estimation accuracy of different water quality indicators
by Lin Gao, Field sampling is an important component of water quality assessment and for early detection of water quality deterioration caused by human activities. Theoretically, the accuracy of water quality indicators estimated from water samples should increase with increasing the number of samples or the sampling frequency. However, costs related to water sample collection, transportation, storage and laboratory analyses, will also increase with increasing sampling frequency. It is a challenge to determine an adequate sampling frequency that achieves both acceptable accuracies for estimating the change in water quality indicators and acceptable cost for sample collection and laboratory analyses. The objective of this study was to analyze the effects of variation in sampling frequency on the accuracy of selected water quality indicators. Water quality variables analyzed in this study include suspended solids (ton ha-1), and concentrations of agricultural nutrients (nitrate nitrogen potassium, ortho-phosphorus, calcium, and magnesium). Water quality indicators included in this study were annual loading and Concentration Exceedance Frequency (CEF). Water quality data from Little River Watershed and its tributary Black Brook Watershed in New Brunswick were used to generalize the relationship between the estimation accuracy of the above-mentioned water quality indicators and the different sampling frequency by statistical approaches. The coefficient of variation, the relative bias, and the probability of potential error were used as measures of estimation accuracy. Results indicated that these three measures of estimation accuracy in annual loading decreased with increasing sampling frequency for sediments and all agricultural nutrients. As expected, these measures of estimation accuracy in CEF also decreased with increasing sampling frequency. This means accuracies of both annual loading and CEF increased with increasing sampling frequency.
Assessing pesticide loading and concentration with assistance of integrated hydrological models in streams of small to medium-sized watersheds
Assessing pesticide loading and concentration with assistance of integrated hydrological models in streams of small to medium-sized watersheds
by Wei Chen, Pesticides are increasingly used around the world alone with the expansion of intensive crop cultivation and food production. Pesticide residues from agriculture fields being carried to surface and ground water impose a potential threat to the aquatic ecosystem as well as to human health. However, monitoring potential threat of pesticide residuals in river systems is expensive and difficult. Previous studies indicated that traditionally used grab sampling methods could potentially underestimate the maximum concentrations of pesticide residues in streams by 10 to 1000 times. The objective of this study was to assess pesticide loading and concentration with assistance of integrated hydrological models in streams of small to medium- sized watersheds. Soil and Water Assessment Tool (SWAT) was selected for simulating hydrological processes together with pesticide loading and in stream pesticide concentration. Model predicted pesticide loading and pesticide concentration was compared with three years measured data from Black Brook Watershed and two Sub-basins within the same watershed. We found that the model predicted pesticide loading and in stream concentrations of three pesticides had the same seasonal trend with field surveys with some discrepancies. The discrepancies are likely caused by three main factors. 1. Model predicts the daily pesticide loading and daily average pesticide concentration and while actual pesticide concentrations change rapidly during stormflow period. 2. Current field sampling method could not capture the rapid change of pesticide concentration due to mechanical limitations. 3. Input data on exact pesticide application date were not available. In general, the pesticide modelling results indicate that the model is an effective tool in loading and concentration prediction in small agricultural watershed. We also found the model predicted pesticide loading during baseflow period were relatively high compare with near zero pesticide concentration observed. This suggest there is a need to improve in pesticide routing algorithm in SWAT model and current estimation during based flow period should be manually adjusted., A Report Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Forestry in the Graduate Academic Unit of Forestry & Environmental Management
Assessing soil erosion of agriculture field during winter and summer seasons using 3D scanning and close-range photogrammetry technology
Assessing soil erosion of agriculture field during winter and summer seasons using 3D scanning and close-range photogrammetry technology
by Fangzhou Zheng, Soil surface morphology is strongly affected by land management practices and soil biophysical processes such as soil erosion. Traditional methods on measuring soil surface morphology changes have been costly, time-consuming and causing extra soil disturbance. Alternatively, remote sensing technologies involving 3D scanning and photogrammetry are becoming available and capable of measuring surface morphology correctly and quickly. With these techniques, studies have focused on small-scale rill erosion during short snow-free periods. In this study, the performances and accuracies of 3D scanner and photogrammetry methods on detecting morphological features, i.e., total station scanner (TSS) and close-range photogrammetry (CRP), were evaluated and optimized. Three parameters (width, depth and area) of each morphological feature of two surfaces, a ridged and channeled plywood board (2.4 m by 3.6 m) and a ridged and channeled bare-earth plot (6 m by 20 m), were derived using both remote sensing methods and actual measurement. For the plywood board assessment, the optimal TSS and CRP root mean square errors achieved were: width = 1.3 cm vs. 0.8 cm; depth = 1.0 cm vs. 0.4 cm; areas = 7.8 cm[squared] vs. 4.2 cm[squared]. Whereas for the bare-earth plot, the optimal TSS and CRP root mean square errors were: width = 3.4 cm vs. 1.1 cm; depth = 2.2 cm vs. 1.6 cm. Hence, the performances of CRP on detecting morphological changes are better than the TSS results. However, the TSS method is more practical than CRP by allowing larger scanning distance and fewer operators. A field experiment was conducted at the Agriculture and Agri-Food Canada Fredericton Research and Development Centre, New Brunswick, on 6 m by 80 m large plots to determine surface morphological changes under three tillage treatments during two winter and summer seasons. The treatments involved (i) potato cropping with up-down-slope tillage, (ii) potato cropping with contour tillage, and (iii) fallowing with up-down-slope tillage (control). The periods lasted (i) from snowfall to after snowmelt, and (ii) from seeding to about one-third potato canopy coverage. Surface morphologies (elevation, slope, curvature) were scanned and evaluated at the beginning and end of each period. Also, soil moisture at 15 and 30 cm depth, and soil temperature at 15 cm depth were monitored within the winter period before and after freezing. For the winter period, there was an about 2.1 cm to 2.9 cm drop in elevation for the plots as a whole. Translating these changes in soil losses, assuming that these changes were due to soil erosion, and that the soil bulk density equals to 1.1 g cm[to the power of -3], they can procure a net soil loss of 231 Mg ha[to the power of -1] to 319 Mg ha[to the power of -1]. However, this elevation changes is unlikely being caused by soil erosion alone, but attribute to soil-structure and compactions caused by freeze-thaw action, snowpack compaction that could change soil aggregation and pore volumes. For the summer period, the plots revealed an elevation drop in the distance ranges of approximately 0 m – 20 m and 40 m – 50 m from the top of the plots. On the other hand, elevation rise was observed at approximately 20 – 40 m and 50 – 70 m. This drop and rise would translate into overall soil loss of 55 to 110 Mg ha[to the power of -1] for the cropped plots, and a net soil gain of 22 to 88 Mg ha[to the power of -1] for the fallow plots. In some of the winter and summer plots, water-induced erosion rill was detected using both TSS and CRP methods. For the same rill derived from the summer period, CRP yields higher and more accurate value than TSS by about 0.9 Mg ha[to the power of -1]. Overall, these results indicate that both technologies are able to capture surface elevation changes and detect erosion rills. However, neither method could be used to determine sheet erosion correctly. Hence, further methodology refinements are needed to ensure that the TSS and CRP results are not affected by the freeze-thaw action or the presence of ground-covering vegetation due to, e.g. cropping or fallowing.
Assessing the long-term impacts of high moose densities on Gros Morne National Park
Assessing the long-term impacts of high moose densities on Gros Morne National Park
by Shannon C. White, Moose (Alces alces) browsing in Gros Morne National Park (GMNP) has caused substantial damage to its current balsam fir (Abies balsamea)-dominated forest. In this study estimates of stocking rates, stand yield and carbon stocks were generated from a regeneration-survey focused on sites suppressed by moose browsing. Scenario analysis (i) assessed moose browsing and domestic harvest impacts on forest regeneration and development; (ii) carbon storage within the forest ecosystem; and (iii) quantified effectiveness of forest restoration strategies, such as moose population control and reforestation. Regeneration survey indicates that high moose browsing has resulted in a significant portion of regenerating areas to fall within the “not sufficiently regenerated” category (NSR). Scenario analysis shows continued heavy moose browsing levels will lower growth and yield expectations within the park and slowly transition balsam fir-dominated stand types to spruce. Optimizing carbon stocks within the park can increase forest ecosystem carbon stocks over baseline levels in GMNP., Thesis format not specified on title page

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