Knowing the control of landscape position in greenhouse gas (GHG) emission from the Prairie pothole region is necessary to provide reliable emission estimates needed to formulate strategies for reducing emission from the region. Presented here are results of a study investigating the control of landscape position on the flux of nitrous oxide (N2O) and methane (CH4) from an agricultural soil. Field flux of N2O and CH4 and associated soil parameters from the Upper, Middle, Lower and Riparian slope positions were monitored from spring to fall of 2005, and spring of 2006, at the Manitoba Zero-Tillage Research Association (MTRZA) farm, 17.6km North of Brandon, MB. The field site consisted of a transect of 128 chambers segmented into the four landscape positions, with either all chambers or a subset of the chambers (32) sampled on select days. Spring thaw is an important period for annual inventory of N2O emission, thus, soil samples were also collected from the four slope positions in fall 2005, and treated in the laboratory to examine how antecedent moisture and landscape position affect the freeze-thaw emission of N2O from soil. Daily emissions of N2O and CH4 for 2005 were generally higher than for 2006, the former being a wetter year. There was high temporal variability in N2O and CH4 emission, with high fluxes associated with events like spring thaw and fertilizer application in the case of N2O, and rapid changes in soil moisture and temperature in the case of CH4. There was a high occurrence of hotspots for N2O emission at the Lower slope, associated with its high soil water-filled porosity (WFP) and carbon (C) availability. The Riparian zone was not a source of N2O emission, despite its soil WFP and organic C being comparable with the Lower slope. The hotspot for CH4 emission was located at the Riparian zone, associated with its high soil WFP and C availability. The Upper and Middle slope positions gave low emission or consumed CH4, associated with having low soil WFP and available C. This pattern in N2O and CH4 emission over the landscape was consistent with examination of entire 128 chambers on the transect or the 32 subset chambers. Significantly lowering the antecedent moisture content of soil by drying eliminated the freeze-thaw emission of N2O, despite the addition of nitrate to the soil. This was linked to drying slightly reducing the denitrifying enzyme activity (DEA) of soil. The highest and earliest freeze-thaw emission of N2O was from the Riparian zone, associated with its high antecedent moisture content, DEA and total organic C content. The addition of nitrate to soil before freezing failed to enhance freeze-thaw emission of N2O from the Upper, Middle and Lower slope positions, but increased emission three-fold for the Riparian zone. Despite the greater potential of the Riparian zone to produce N2O at thaw compared to the Upland slopes, there was no spring-thaw emission of N2O from the zone on the field. This was because this zone did not freeze over the winter, due to insulation by high and persistent snow cover, vegetation and saturated condition. The denitrifying potential and freeze-thaw N2O emission increased in going from the Upper to the Lower slope position, similar to the pattern of N2O emission observed on the field. The localization of hotspots for N2O and CH4 emission within the landscape was therefore found to be driven by soil moisture and C availability. When estimating GHG emission from soil, higher emission index for N2O and CH4 should be given to poorly-drained cropped and vegetated areas of the landscape, respectively. The high potential of the Riparian zone for spring-thaw emission of N2O should not be discountenanced when conducting annual inventory of N2O emission at the landscape scale. When fall soil moisture is high, snow cover is low, and winter temperature is very cold, freeze-thaw emission of N2O at the Riparian zones of the Prairie pothole region may be very high.

Knowing the control of landscape position in greenhouse gas (GHG) emission from the Prairie pothole region is necessary to provide reliable emission estimates needed to formulate strategies for reducing emission from the region. Presented here are results of a study investigating the control of landscape position on the flux of nitrous oxide (N2O) and methane (CH4) from an agricultural soil. Field flux of N2O and CH4 and associated soil parameters from the Upper, Middle, Lower and Riparian slope positions were monitored from spring to fall of 2005, and spring of 2006, at the Manitoba Zero-Tillage Research Association (MTRZA) farm, 17.6km North of Brandon, MB. The field site consisted of a transect of 128 chambers segmented into the four landscape positions, with either all chambers or a subset of the chambers (32) sampled on select days. Spring thaw is an important period for annual inventory of N2O emission, thus, soil samples were also collected from the four slope positions in fall 2005, and treated in the laboratory to examine how antecedent moisture and landscape position affect the freeze-thaw emission of N2O from soil. Daily emissions of N2O and CH4 for 2005 were generally higher than for 2006, the former being a wetter year. There was high temporal variability in N2O and CH4 emission, with high fluxes associated with events like spring thaw and fertilizer application in the case of N2O, and rapid changes in soil moisture and temperature in the case of CH4. There was a high occurrence of hotspots for N2O emission at the Lower slope, associated with its high soil water-filled porosity (WFP) and carbon (C) availability. The Riparian zone was not a source of N2O emission, despite its soil WFP and organic C being comparable with the Lower slope. The hotspot for CH4 emission was located at the Riparian zone, associated with its high soil WFP and C availability. The Upper and Middle slope positions gave low emission or consumed CH4, associated with having low soil WFP and available C. This pattern in N2O and CH4 emission over the landscape was consistent with examination of entire 128 chambers on the transect or the 32 subset chambers. Significantly lowering the antecedent moisture content of soil by drying eliminated the freeze-thaw emission of N2O, despite the addition of nitrate to the soil. This was linked to drying slightly reducing the denitrifying enzyme activity (DEA) of soil. The highest and earliest freeze-thaw emission of N2O was from the Riparian zone, associated with its high antecedent moisture content, DEA and total organic C content. The addition of nitrate to soil before freezing failed to enhance freeze-thaw emission of N2O from the Upper, Middle and Lower slope positions, but increased emission three-fold for the Riparian zone. Despite the greater potential of the Riparian zone to produce N2O at thaw compared to the Upland slopes, there was no spring-thaw emission of N2O from the zone on the field. This was because this zone did not freeze over the winter, due to insulation by high and persistent snow cover, vegetation and saturated condition. The denitrifying potential and freeze-thaw N2O emission increased in going from the Upper to the Lower slope position, similar to the pattern of N2O emission observed on the field. The localization of hotspots for N2O and CH4 emission within the landscape was therefore found to be driven by soil moisture and C availability. When estimating GHG emission from soil, higher emission index for N2O and CH4 should be given to poorly-drained cropped and vegetated areas of the landscape, respectively. The high potential of the Riparian zone for spring-thaw emission of N2O should not be discountenanced when conducting annual inventory of N2O emission at the landscape scale. When fall soil moisture is high, snow cover is low, and winter temperature is very cold, freeze-thaw emission of N2O at the Riparian zones of the Prairie pothole region may be very high.

Thesis (Ph. D.)--Montana State University--Bozeman, 2003. / Typescript. Chairperson, Graduate Committee: Jay Rotella. Includes bibliographical references.

Three wetland restoration methods: seeding, seeding + hay mulch, and seeding + hay mulch + vegetation plugs were compared via the plant community within a formerly cropped wetland in southeastern North Dakota. Arrangement of plugs were also compared to assess the success of native species establishment. Mean relative cover for native species and introduced species were recorded and analyzed to compare the restoration methods and plug arrangement. Three herbicide treatments were studied on upland prairie sites with and without prescribed burning to test effects on leafy spurge (Euphorbia esula) control and seeded native establishment. There is no difference native species richness between the restoration methods six years post restoration, and no difference in plant cover in the different arrangement of plugs. Quinclorac significantly reduced leafy spurge cover; however, glyphosate treatments had higher cover of seeded native species.

No description available.

No description available.

This dissertation presents an approach to reconstruct degenerate near-planar road surface in three-dimensional (3D) while automatically detect road defects. Three techniques are developed in this dissertation to establish the proposed approach. The first technique is proposed to reconstruct the degenerate near-planar road surface into 3D from one camera. Unlike the traditional Structure from Motion (SfM) technique which has the degeneracy issue for near-planar object 3D reconstruction, the uniqueness of the proposed technique lies in the use of near-planar characteristics of surfaces in the 3D reconstruction process, which solves the degenerate road surface reconstruction problem using only two images. Following the accuracy-enhanced 3D reconstructed road surface, the second technique automatically detects and estimates road surface defects. As the 3D surface is inversely solved from 2D road images, the detection is achieved by jointly identifying irregularities from the 3D road surfaces and the corresponding image information, while clustering road defects and obstacles using a mean-shift algorithm with flat kernel to estimate the depth, size, and location of the defects. To enhance the physics-driven automatic detection reliability, the third technique proposes and incorporates a self-supervised learning structure with data-driven Convolutional Neural Networks (CNN). Different from supervised learning approaches which need labeled training images, the road anomaly detection network is trained by road surface images that are automatically labeled based on the reconstructed 3D surface information. In order to collect clear road surface images on the public road, a road surface monitoring system is designed and integrated for the road surface image capturing and visualization. The proposed approach is evaluated in both simulated environment and through real-world experiments. The parametric study of the proposed approach shows the small error of the 3D road surface reconstruction influenced by different variables such as the image noise, camera orientation, and the vertical movement of the camera in a controlled simulation environment. The comparison with traditional SfM technique and the numerical results of the proposed reconstruction using real-world road surface images then indicate that the proposed approach effectively reconstructs high quality near-planar road surface while automatically detects road defects with high precision, accuracy, and recall rates without the degenerate issue. / Doctor of Philosophy / Road is one of the key infrastructures for ground transportation. A good road surface condition can benefit mainly on three aspects: 1. Avoiding the potential traffic accident caused by road surface defects, such as potholes. 2. Reducing the damage to the vehicle initiated by the bad road surface condition. 3. Improving the driving and riding comfort on a healthy road surface. With all the benefits mentioned above, it is important to examine and check the road surface quality frequently and efficiently to make sure that the road surface is in a healthy condition. In order to detect any road surface defects on public road in time, this dissertation proposes three techniques to tackle the road surface defects detection problem: First, a near-planar road surface three-dimensional (3D) reconstruction technique is proposed. Unlike traditional 3D reconstruction technique, the proposed technique solves the degenerate issue for road surface 3D reconstruction from two images. The degenerate issue appears when the object reconstructed has near-planar surfaces. Second, after getting the accuracy-enhanced 3D road surface reconstruction, this dissertation proposes an automatic defects detection technique using both the 3D reconstructed road surface and the road surface image information. Although physics-based detection using 3D reconstruction and 2D images are reliable and explainable, it needs more time to process these data. To speed up the road surface defects detection task, the third contribution is a technique that proposes a self-supervised learning structure with data-driven Convolutional Neural Networks (CNN). Different from traditional neural network-based detection techniques, the proposed combines the 3D road information with the CNN output to jointly determine the road surface defects region. All the proposed techniques are evaluated using both the simulation and real-world experiments. Results show the efficacy and efficiency of the proposed techniques in this dissertation.

Wetlands are significant contributors to global biodiversity, supporting disproportionately high numbers of species relative to their area. Riparian areas associated with wetlands provide many services that are both ecologically and economically important, such as groundwater recharge, sediment capture and shoreline stabilization, flood mitigation, nutrient processing, increased water quality, carbon sequestration, and essential habitat for wildlife. Agricultural activity has resulted in the drainage or modification of between 40-70% of wetland basins within the Prairie Pothole Region of the northern Great Plains. The impacts of human activity on the remaining wetlands are difficult to estimate and there is no one optimal indicator or assessment method that is applicable to all regions or situations. Locally developed riparian health assessments, designed to evaluate wetland function under different grazing regimes, are cost-effective with the potential for broader use in wetland environmental assessment, monitoring, and management or restoration activities. In this study I investigated the hypothesis that riparian health assessments can distinguish between wetlands in five categories of land use that represent different levels of anthropogenic modification: ungrazed cultivated cropland, ungrazed native grassland, grazed native grassland, ungrazed tame perennial forage, and grazed tame perennial forage. Noting that current riparian health assessment protocols lack a community composition component other than the presence and distribution of invasive and disturbance species, I also sampled plant species frequency at each of my study sites. I found that wetlands in cultivated croplands had significantly lower riparian health scores than wetlands in both tame and native grasslands. Among tame and native sites, grazing status was more important than upland cover type in determining wetland health, with grazed wetlands receiving significantly lower scores than their ungrazed counterparts. Despite their functional similarity to wetlands within native grasslands, species composition of wetlands within ungrazed tame perennial forage more closely resembled that of wetlands in cultivated uplands. Although grazing negatively affected riparian ground cover and soil stability, it significantly reduced both the overall cover and distribution of invasive plant species along wetland reaches. These results suggest that upland revegetation and restoration of function to degraded wetlands is not necessarily followed by re-establishment of original riparian species composition. If biodiversity is a desired outcome of wetland restoration efforts, additional measures must be taken to enable the establishment and persistence of preferred plant species.

Like life-history theory, wildlife management decisions are typically predicated on trade-offs between benefits associated with investing resources to achieve higher reproductive or survival rates versus costs or risks of achieving those goals. On the Canadian prairies, most waterfowl conservation resources are directed to policies and programs that seek to increase duck nesting success. Limited attention has focused on post-hatching life-cycle stages, yet, despite considerable recent work on duckling survival rates, many uncertainties remain concerning how abiotic and biotic factors affect duckling survival rates. The role of upland habitat characteristics may be important but has received limited attention. I evaluated hypothesized sources of variation in duckling survival for 617 mallard (Anas platyrhynchos) broods on 27 Canadian prairie-parkland sites, with emphasis on assessing effects of managed and remnant natural upland habitats. I contrasted suites of a priori and post hoc exploratory models that incorporated effects of landscape, weather, female and brood-related variables to explain variation in duckling survival rates. Survival was lower for ducklings that used areas with high proportions of semi-permanent wetlands, as well as for broods that travelled farther overland. Exploratory analyses revealed further that survival of ducklings was negatively related to the amount of managed hayland. In contrast, duckling survival was positively associated with the amount managed grassland. There was no evidence of trade-offs between benefits of managing habitat to enhance duck nesting success versus costs in terms of lower subsequent duckling survival.<p> I also addressed unresolved questions about how birds balance costs and benefits of selecting habitats by determining the survival consequences of habitat choices made during brood-rearing. In theory, fitness should be higher in preferred habitats, but this assumption is rarely tested. Fitness consequences (i.e., duckling survival) of habitat selection patterns were determined at landscape and local scales using logistic regression and information-theoretic model selection techniques. Best-approximating landscape-level models indicated that mallard females selected brood-rearing areas with a high proportion of wetland and perennial upland habitats, but duckling survival was not related to habitat selection patterns at this scale. At finer spatial scales, females selected brood-rearing areas with high proportions of wetland habitats, but, contrary to expectation, duckling survival was lower when females raised their broods in these areas. Females avoided areas with abundant perennial cover and wetlands with little vegetative cover and, consistent with prediction, duckling survival was higher when females selected areas with low perennial cover. Thus, females did not consistently select brood-rearing habitats that conferred the highest fitness benefits. Rather, the relationship between habitat selection and duckling survival depended on spatial scale and habitats considered.

Like life-history theory, wildlife management decisions are typically predicated on trade-offs between benefits associated with investing resources to achieve higher reproductive or survival rates versus costs or risks of achieving those goals. On the Canadian prairies, most waterfowl conservation resources are directed to policies and programs that seek to increase duck nesting success. Limited attention has focused on post-hatching life-cycle stages, yet, despite considerable recent work on duckling survival rates, many uncertainties remain concerning how abiotic and biotic factors affect duckling survival rates. The role of upland habitat characteristics may be important but has received limited attention. I evaluated hypothesized sources of variation in duckling survival for 617 mallard (Anas platyrhynchos) broods on 27 Canadian prairie-parkland sites, with emphasis on assessing effects of managed and remnant natural upland habitats. I contrasted suites of a priori and post hoc exploratory models that incorporated effects of landscape, weather, female and brood-related variables to explain variation in duckling survival rates. Survival was lower for ducklings that used areas with high proportions of semi-permanent wetlands, as well as for broods that travelled farther overland. Exploratory analyses revealed further that survival of ducklings was negatively related to the amount of managed hayland. In contrast, duckling survival was positively associated with the amount managed grassland. There was no evidence of trade-offs between benefits of managing habitat to enhance duck nesting success versus costs in terms of lower subsequent duckling survival.<p> I also addressed unresolved questions about how birds balance costs and benefits of selecting habitats by determining the survival consequences of habitat choices made during brood-rearing. In theory, fitness should be higher in preferred habitats, but this assumption is rarely tested. Fitness consequences (i.e., duckling survival) of habitat selection patterns were determined at landscape and local scales using logistic regression and information-theoretic model selection techniques. Best-approximating landscape-level models indicated that mallard females selected brood-rearing areas with a high proportion of wetland and perennial upland habitats, but duckling survival was not related to habitat selection patterns at this scale. At finer spatial scales, females selected brood-rearing areas with high proportions of wetland habitats, but, contrary to expectation, duckling survival was lower when females raised their broods in these areas. Females avoided areas with abundant perennial cover and wetlands with little vegetative cover and, consistent with prediction, duckling survival was higher when females selected areas with low perennial cover. Thus, females did not consistently select brood-rearing habitats that conferred the highest fitness benefits. Rather, the relationship between habitat selection and duckling survival depended on spatial scale and habitats considered.