Graduate Research

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A comparison between the forestry sector in New Brunswick (Canada) and Hesse (Germany)
(University of New Brunswick, 2020) Scriba, Christian; Leblon, Brigitte; Hanewinkel, Marc
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 feasibility assessment of wolf reintroduction to the Cape Breton Highlands
(University of New Brunswick, 2018) Williams, George H.; Forbes, Graham
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 forest operations management plan for 7 stands within the Noonan Research Forest owned by the University of New Brunswick in the city of Fredericton - NB
(University of New Brunswick, 2022-01) Pimenta Arao de Brito, Leonardo; Golding, Jasen
Understanding and estimating cost of forest operations is critical to the economic success of the logging business and an important tool for forest management decisions. The purpose of this research is to develop an understanding of how to design, cost and implement a forest operations management plan. The research project is conducted within the Noonan Research Forest (NRF), an Acadian mixedwood forest parcel owned and managed by the University of New Brunswick, located approximately 25 km North-East of the city of Fredericton (45.993905 N, -66.410996 E). The management plan encompasses all requirements necessary to construct and calculate a machine rental rate or proforma for forest harvesting equipment and assess expected revenue prominent from a forest stand. The scope of this report is to analyze pre-collected inventory data of 7 forest stands within the NRF, summarizing forest attributes, with respective variance, and hence, recommend most suitable harvest prescriptions for each stand. Identification of a harvest system based upon prescription, computing costs for harvesting, processing, and transportation of products from stump to roadside. Then, upon to product market assessment, calculate distance and time from stand to mills based upon the most cost-effective delivery location. Lastly, this report aims to calculate the products stumpage value providing to the landowner with a better understanding of expected revenue and timber cost management.
A high-resolution digital soil mapping framework for New Brunswick, Canada
(University of New Brunswick, 2018) Furze, Shane; Arp, Paul
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
(University of New Brunswick, 2019) Sun, Yunmiao; Forbes, Graham
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.
A systems approach for estimating forest attributes from LiDAR
(University of New Brunswick, 2021) Yang, Ting-Ru; Kershaw, John
Light detection and ranging (LiDAR) is a popular technique in landscape-level forest inventory design, analyses, and implementation. The application of LiDAR in forestry has developed a set of standard analysis methods. However, many current methods ignore the importance of sample design, which is replaced with opportunistic samples, and focus on machine learning imputation to independently estimate different forest attributes leading to inconsistency across estimates that limit the practical applicability of LiDAR in forest management decision-making. In this dissertation, a workflow for LiDAR-assisted forest inventory is developed. Starting with sample designs (Chapter 2), variable probability sampling methods, previously limited by insufficient prior information. are explored. Appropriate LiDAR sampling designs obtain higher accuracy estimates at a lower cost. Rather than independent single forest attribute modeling, methods to obtain simultaneous estimates of multiple forest attributes is developed. A systems approach, composed by three allometric equations with five unknowns, is developed to obtain compatible and consistent forest inventory estimates in central New Brunswick (Chapter 3). To test the portability, this systems approach is applied to a large landscape in eastern Nova Scotia, Canada (Chapter 4). Both regions show that using this systems approach eliminates inconsistency and produce estimates with biological relevance among forest attributes. Finally, copulas are used to demonstrate the potential of obtaining stand Height – Diameter distributions with the use of LiDAR (Chapter 5). Although less precise point cloud co-registration is required, the current results varied among actual field conditions. In the future, applying the systems approach in the areas with different periods of LiDAR data collection might be able to detect changes in stand structure. In addition to area-based estimates, the combinations of the systems approach with the copulas could improve the stand Height – Diameter distribution estimates.
Adapting hydrological modeling for Atlantic Canada's climate, landscape, and vegetation conditions: from field to small and large watersheds
(University of New Brunswick, 2017) Qi, Junyu; Fan-Rui Meng; Bourque, Charles P.-A; Li, Sheng
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
An examination of thresholds and forest succession in the Acadian Forest of New Brunswick under a changing climate
(University of New Brunswick, 2022-08) MacLellan, Benjamin Reiber; Bourque, Charles
Climate change has warmed the atmosphere over scales relevant to modern society, causing widespread and rapid changes to the pedosphere, cryosphere, biosphere, and oceanic systems. Through our actions or inactions, we may be fundamentally altering the very nature of our environmental systems by forcing them beyond critical environmental thresholds. These environmental systems are complex and have many interconnected and interacting parts, so when a disturbance occurs the whole ecosystem can be impacted in ways that may not be readily apparent. To deal with this complexity, I have developed a conceptual framework to examine the historical simplifying assumptions foresters have used, from the simplest logistic curves to representations of forest dynamics as seen in hybrid process-based models, such as the Forest Landscape Model. The conceptual framework is separated into two parts, namely (i) ecological, and (ii) socio-economic constraints, each with their own results. Using this framework, this thesis seeks to unpack how the structure, composition, and function of forests will shift under anticipated climate change. My results led me to conclude that our simplifying assumptions of human-ecosystem interactions may point to competition as a driver of system thresholds and tipping points. I was able to identify various scenarios focusing on interspecific competition between southern and northern species that will require due consideration in the future. Nevertheless, a flexible response to dynamic system shifts in human-forest ecosystem interactions suggests that a flexible option would provide resilience to a complex system. My results lead me to conclude that a scenario with increasing species diversity will allow us to create more robust solutions for the future and reduce uncertainty.
An investigation of recent sudden mortality of balsam fir in Eastern North America: Climate, stand and site drivers of mortality
(University of New Brunswick, 2023-06) Broom, James; D’Orangeville, Loïc
In 2018, a widespread, balsam fir mortality event occurred across the species southern range limit. The purpose of this thesis was to determine the role of climate and local factors as drivers of mortality in Atlantic Canada. A Random Forest model associated a combination of climate anomalies with mortality, notably a summer drought in the previous year. This model was able to predict a similar event that occurred in 1986 with a remarkable accuracy of 95% (kappa = 0.88). Looking at local factors, I find that sites associated with elevated temperatures (i.e., lower elevations and south facing aspects), higher competition for water and taller trees display higher mortality risks. Mortality probability was also associated with low depth to water values with minimal influence observed for drainage and slope variables. This research highlights the vulnerability of balsam fir to drought induced mortality.
Application and expansion of wood-based derivatives as reinforcement of packaging
(University of New Brunswick, 2024-05) Zhou, Yuyang; Gong, Meng
Fiber-based energy absorption tubes could be designed as corner post reinforcement for packaging. This thesis explored the impact of geometric parameters, material composition, and relative humidity (RH) on the mechanical properties of fiber-based tubes, designed as reinforcement for corrugated cardboard boxes. It examined the compressive response of boxes under varying RH conditions, noting that an increase in RH from 50% to 90% significantly reduced peak load (plc) and specific energy absorption (SEA) by up to 20%. Moisture adversely affected the modulus of elasticity, inducing buckling in longer columns and crushing in shorter ones. Both types of columns showed a 20% reduction in performance at greater lengths. The findings underscored the effectiveness of fiber-based reinforcements in enhancing the compression resistance of cardboard packaging, with increases of approximately 230% and 710% for paper-based and veneer-based reinforcements, respectively. A 20% RH increase resulted in a 40% decrease in the compression strength of the packaging.
Application of a dendroecology approach to red spruce provenance trials to study species and population vulnerability to climate change
(University of New Brunswick, 2022-04) Moura dos Santos, Jessé; D'Orangeville, Loïc
Red spruce (Picea rubens) is a tree species unique to the Acadian Forest, providing numerous ecosystem goods and services, including timber for the forest industry. With the expected decline of the species due to climate change, assisted migration of more southern, warm-adapted populations could help maintain the species in New Brunswick, but empirical evidence is lacking. Here, I compared the climate sensitivity of 16 populations of 60-yr-old red spruce trees across provenance trials, using a Bayesian model relating annual growth to historical climate from 1975 to 2018, while controlling explicitly for treelevel competition and size, stand-level development, thinning, blocking design and local soil conditions. Overall, climate explained a small fraction of the interannual growth variation, while stand development, thinning events and tree size were the strongest predictors. Our results do not provide strong support for assisted migration, as all populations displayed similar phenotypical plasticity in response to 45 years of climate variations.
Applications of variable probability sampling using remotely sensed covariates
(University of New Brunswick, 2019) Hsu, Yung-Han; Kershaw, John
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
(University of New Brunswick, 2016) Ryerson, Alexander; Fan-Rui Meng; MacLean, David
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
(University of New Brunswick, 2015) Mazumder, Rony; Fan-Rui Meng; Zhu, Xinbiao
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.
Assessing effects of sampling frequency on the estimation accuracy of different water quality indicators
(University of New Brunswick, 2017) Gao, Lin; Fan-Rui Meng; Li, Sheng; Benoy, Glenn; Xing, Zisheng
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
(University of New Brunswick, 2020) Chen, Wei; Fan-Rui Meng
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.
Assessing soil erosion of agriculture field during winter and summer seasons using 3D scanning and close-range photogrammetry technology
(University of New Brunswick, 2016) Zheng, Fangzhou; Fan-Rui Meng; Li, Sheng
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 landscape drivers of cold-water temperatures at tributary confluence plumes: A multi-spatial analysis
(University of New Brunswick, 2024-08) Green, Hannah S.; Sacobie, Charles; Ogilvie, Jae
The impact of climate change and human disturbances affects the thermal regime of rivers, increasing the need for conservation of thermal refuges. Tributary confluence plumes are a classification of thermal refuges on the Restigouche River watershed. The objectives of this thesis were to use landscape attributes to predict water temperatures at tributary confluence plumes at two spatial scales (global and reach-specific) and identify how landscape drivers vary at the sub-catchment. Model 3D explored three variables, and a second model (12D) included the addition of nine other variables. We increased global variability explained between model 3D (R2 = 0.07) and model 12D (R2= 0.88). We classified reach-scale models under three categories of high relative importance: bedrock, climate and canopy cover. We recommend that the Kedgwick (canopy), Restigouche and Upsalquitch Southeast (climate) tributaries be of high priority for protection, while continuing exploration into the effects of geomorphology on the watershed.
Assessing the long-term impacts of high moose densities on Gros Morne National Park
(University of New Brunswick, 2020) White, Shannon Calvin; Fanrui Meng; Zhu, Xinbiao; Bourque, Charles
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.
Assessing the outcomes of stocking of hatchery juveniles in the presence of wild Atlantic salmon
(University of New Brunswick, 2017) Wallace, Ben; Curry, Allen
Stocking of hatchery-reared, juvenile Atlantic Salmon (Salmo salar) is a common enhancement and recovery strategy across jurisdictions, yet its impact remains uncertain. We investigated the potential effectiveness of stocking in the Miramichi River system where approximately 150,000 first-feeding fry are stocked annually in reaches where wild juveniles are present. Local site and landscape level characteristics were used to fit predictive models for wild parr densities measured as Percent Habitat Saturation (PHS) using Partial Least Squares Regression (PLSR). The observed PHS of stocked sites was found to be significantly lower than predicted, suggesting stocking has not been effective in increasing the PHS in the studied stocked sites. The results suggest that habitat and other density dependent effects likely limit productive capacity in this system, and consequently, may limit the effectiveness of stocking in other systems with natural production.

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