The tidal James River, a focus of VCU's Atlantic Sturgeon program, supports both commercial shipping and hydraulic dredging. These anthropogenic threats present documented but preventable sources of mortality to the endangered species. Using three separate VEMCO Positioning System (VPS) receiver arrays, spatial data of previously-tagged fish were collected. ArcGIS and Programita software were used to analyze fish spatial distributions in the presence and absence of potential threats, using additional data including automatic identification system (AIS) vessel locations, vessel passages compiled using camera footage, and dredge records provided by the US Army Corps of Engineers. The data showed a change in distribution associated with vessels that varied according to river width but not vessel type. Dredging was associated with differences in spatial distribution, but more clearly for adults than sub-adults. The responses of Atlantic Sturgeon provide information necessary to propose potential threat mitigations, including seasonal restrictions for both vessels and dredging.

Remediation of unexploded ordnance (UXO) and prioritization of excavation procedures for archaeological artifacts using electromagnetic (EM) induction are studied in this dissertation. Lowering of the false alarm rates that require excavation and artifact excavation prioritization can reduce the costs associated with unnecessary procedures. Data were taken over 5 areas at the San Jacinto Battleground near Houston, Texas, using an EM-63 metal detection instrument. The areas were selected using the archaeological concepts of cultural and natural formation processes applied to what is thought to be areas that were involved in the 1836 Battle of San Jacinto. Innovative use of a Statistical Point Pattern Analysis (PPA) is employed to identify clustering of EM anomalies. The K-function uses point {x,y} data to look for possible clusters in relation to other points in the data set. The clusters once identified using K-function will be further examined for classification and prioritization using the Weighted K-function. The Weighted K-function uses a third variable such as millivolt values or time decay to aid in segregation and prioritization of anomalies present. Once the anomalies of interest are identified, their locations are determined using the Gi-Statistics Technique. The Gi*-Statistic uses the individual Cartesian{x, y} points as origin locations to establish a range of distances to other cluster points in the data set. The segregation and location of anomalies supplied by this analysis will have several benefits. Prioritization of excavations will narrow down what areas should be excavated first. Anomalies of interest can be located to guide excavation procedures within the areas surveyed. Knowing what anomalies are of greater importance than others will help to lower false alarm rates for UXO remediation or for archaeological artifact selection. Knowing significant anomaly location will reduce the number of excavations which will subsequently save time and money. The procedures and analyses presented here are an interdisciplinary compilation of geophysics, archaeology and statistical analysis brought together for the first time to examine problems associated with UXO remediation as well as archaeological artifact selection at historic battlegrounds using electromagnetic data.

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No description available.

Multiphoton laser scanning microscopy (MPLSM) is an advanced fluorescence imaging technology which can produce a less noisy microscope image and minimize the damage in living tissue. The MPLSM image in this research is the dehydroergosterol (DHE, a fluorescent sterol which closely mimics those of cholesterol in lipoproteins and membranes) on living cell's plasma membrane area. The objective is to use a statistical image analysis method to describe how cholesterol is distributed on a living cell's membrane. Statistical image analysis methods applied in this research include image segmentation/classification and spatial analysis. In image segmentation analysis, we design a supervised learning method by using smoothing technique with rank statistics. This approach is especially useful in a situation where we have only very limited information of classes we want to segment. We also apply unsupervised leaning methods on the image data. In image data spatial analysis, we explore the spatial correlation of segmented data by a Monte Carlo test. Our research shows that the distributions of DHE exhibit a spatially aggregated pattern. We fit two aggregated point pattern models, an area-interaction process model and a Poisson cluster process model, to the data. For the area interaction process model, we design algorithms for maximum pseudo-likelihood estimator and Monte Carlo maximum likelihood estimator under lattice data setting. For the Poisson Cluster process parameter estimation, the method for implicit statistical model parameter estimate is used. A group of simulation studies shows that the Monte Carlo maximum estimation method produces consistent parameter estimates. The goodness-of-fit tests show that we cannot reject both models. We propose to use the area interaction process model in further research.

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Introduction and objectives In Vietnam, the forest resources have been declining and degrading severely in recent years. The degradation has decreased the natural forest area, changed the forest structure seriously and reduced timber volume and biodiversity. From 1999 to 2005, the rich forest area has decreased 10.2%, whereas the poor secondary forest has increased dramatically by 20.7%. Forest structure plays an important role in forestry research. Understanding forest structure will unlock an understanding of the history, function and future of a forest ecosystem (Spies, 1998). The forest structure is an excellent basis for restoration measures. Therefore, this research is necessary to contribute to improving forest area and quality, reducing difficulties in forest management. The study also enhances the grasp of forest structure, structure changes after harvesting and fills serious gaps in knowledge. In addition, the research results will contribute to improving and rescuing the poor secondary forest and restoring it, approaching the old-growth forest in Vietnam. Material and methods The study was conducted in Kon Ka Kinh national park. The park is located in the Northeastern region of Gia Lai province, 50 km from Pleiku city center to the Northeast. The park is distributed over seven different communes in three districts: K’Bang, Mang Yang and Đăk Đoa. Data were collected from 10 plots of secondary forests (Type IIb) and 10 plots of primeval forests (Type IV). Stratified random sampling was applied to select plot locations. 1 ha plots were used to investigate gaps. 2000 m2 plots were used to measure overstorey trees such as diameter at breast height, total height, crown width and species names. 500 m2 subplots were used to record tree positions. For regeneration, 25 systematic 4 m2 subplots were established inside 1 ha plots. After data were collected in the field, data analyses were conducted by using R and Excel. Firstly, some stand information, such as density, volume and so on, was calculated, and then descriptive statistics were computed for diameter and height variables. Linear mixed effect models were applied to analyze the difference of diameter and height and to check the effect of random factor between the two forest types. Diameter and height frequency distributions were also generated and compared by using permutational analysis of variance (PERMANOVA). Non-linear regression models were analyzed for diameter and height variables. Similar analyses were implemented for gaps. Regarding spatial point patterns of overstorey trees, replicated point pattern analysis techniques were applied in this research. For biodiversity, some calculations were run such as richness and biodiversity indices, comparison of biodiversity indices by using linear mixed models and biodiversity differences between two forest types tested again by permutational analysis of variance. In terms of regeneration, some analyses were implemented such as: height frequency distribution generation, frequency difference testing, biodiversity indices for the regeneration and spatial distribution checking by using a nonrandomness index. Results and discussion After analyzing the data, some essential findings were obtained as follows: Hypothesis H1 “The overstorey structure of secondary forests is more homogeneous and uniform than old-growth forests” is accepted. In other words, the secondary forest density is about 1.8 times higher than the jungle. However, the volume is only 0.56 times as large. The average diameter and height of the secondary forest is smaller by 5.71 cm and 3.73 m than the old-growth forest, respectively. Linear mixed effect model results indicate that this difference is statistically different and the effect of the random factor (Section) is not important. Type IIb has many small trees and the diameter frequency distribution is quite homogeneous. The old-growth forest has more big trees. For both forest stages, the height frequency distribution is positively skewed. PERMANOVA results illustrate that the frequency distribution is statistically different between the two forest types. Regression functions are also more variant and diverse in the old-growth forest, because all standard deviations of the parameters are greater there. Gap analysis results indicate that the number of gaps in the young forest is slightly higher, while the average gap size is much smaller. The gap frequency distribution is statistically different between the two types. In terms of the spatial point pattern of overlayer trees, the G-test and the pair correlation function results show that trees distribute randomly in the secondary forest. In contrast, the spatial point patterns of trees are more regular and diverse in the old-growth forest. The spatial point pattern difference is not significant, and this is proved by a permutational t-test for pair correlation function (pcf). Envelope function results indicate that the variation of pcf in young forests is much lower than in the primary forests. Hypothesis H2 “The overstorey species biodiversity of the secondary forest is less than in the old-growth forest” is rejected. Results show that the number of species of the secondary forest is much greater than in the old-growth forest, especially richness. The richness of the secondary forest is 1.16 times higher. The Simpson and Shannon indices are slightly smaller in the secondary forest. The average Simpson index for both forest stages is 0.898 and 0.920, respectively. However, the difference is not significant. Species accumulation curves become relatively flatter on the right, meaning a reasonable number of plots have been observed. Estimated number of species from accumulation curves in two forest types are 105 and 95/ha. PERMANOVA results show that number of species and proportion of individuals in each species are significantly different between forest types. Hypothesis H3 “The number regenerating species of the secondary forest is less and they distribute more regularly, compared to the old-growth forest” is rejected. There are both similarities and differences between the two types. The regeneration density of the stage IIb is 22,930 seedlings/ha, greater than the old forest by 9,030 seedlings. The height frequency distribution shows a decreasing trend. Similar to overstorey, the richness of the secondary forest is 141 species, higher than the old-growth forest by 9 species. Biodiversity indices are not statistically different between two types. PERMANOVA results indicate that the number of species and the proportion of individuals for each species are also not significantly different from observed forest types. Nonrandomness index results show that the regeneration distributes regularly. Up to 95% of the plots reflect this distribution trend. Hypothesis H4 “Restoration measures (with and without human intervention) could be implemented in the regenerating forest” is accepted. The investigated results show that the secondary forest still has mother trees, and it has enough seedlings to restore. Therefore, restoration solutions with and without human intervention can be implemented. Firstly, forest protection should be applied. This measure is relevant to national park regulations in Vietnam. Rangers and other related organizations will be responsible for carrying out protection activities. These activities will protect forest resources from illegal logging, grazing and tourist activities. Environmental education and awareness-raising activities for indigenous people is also important. Another measure is additional and enrichment planting. It should focus on exclusive species of the overstorey in Type IIb or exclusive species of the primary forest. Selection of these species will lead to species biodiversity increase in the future. This also meets the purpose of the maximum biodiversity solution. Conclusion Forest resources play a very important role in human life as well as maintaining the sustainability of ecosystems. However, at present, they are under serious threat, particularly in Vietnam. Central Highland, Vietnam, where forest resources are still relatively good, is also threatened by illegal logging, lack of knowledge of people and so on. Therefore, it needs the hands of the people, especially foresters and researchers. Through research, scientists can provide the knowledge and understanding of the forest, including the structure and forest restoration. This study has obtained important findings. The secondary forest is more homogeneous and uniform, while the old-growth forest is very diverse. Biodiversity of the overstorey in the secondary forest is more than the primary. The number of regenerating species in the secondary forest is higher, but other indices are not statistically different between two types. The regeneration distribute regularly on the ground. The secondary forest still has mother trees and sufficient regeneration, so some restoration measures can be applied here. Findings of the study contribute to improve people’s understanding of the structure and the structural changes after harvesting in Kon Ka Kinh national park, Gia Lai. That is a key to have better understandings of the history and values of the forests. These findings and the proposed restoration measures address rescuing degraded forests in Central Highland in particular and Vietnam in general. And further, this is a promising basis for the management and sustainable use of forest resources in the future.

Lightning-caused forest fires are one of the major natural disturbances in Ontario managed boreal forests. Survival of these forests with fires for centuries shows that such disturbances are integral to the boreal ecosystem and its ecological functioning. Characterizing the fire regimes defined by fire ignition frequency, fire sizes and their spatial distribution patterns etc. thus can help to improve our understanding of the boreal forest dynamics and provide guidance for management practices attempting to maintain biodiversity and achieve sustainability. In this thesis the lightning-caused fire ignitions data for four ecoregions in Ontario managed boreal forests (3E, 3W, 3S and 4S) for 1960–2009 were analyzed using pattern analysis and density estimation to determine the spatial nature of fire ignitions. These fire ignition spatial patterns were further used (as weighted ignition scenario) to simulate forest fire regimes in the study area. Fire regimes were also simulated using spatially unweighted ignitions (unweighted ignition scenario). Non-spatial (total number of fires, total burn area, number of fires by size classes, annual burn fraction) and spatial (spatial burn probability) indicators of the simulated fire regimes under both ignition scenarios were compared to test the null hypothesis that modeled forest fire regime is not affected by the spatial patterns of input fire ignitions. All data analysis were performed for individual ecoregions. Spatial pattern of ignitions were analyzed using the nearest neighbour index and Ripley’s K-function. Ignition densities were estimated using the adaptive kernel density estimation method and the fire regimes were simulated using BFOLDS (Boreal Forests Landscape Dynamics Simulator). Results showed that lightning-caused fire ignitions are clustered in all ecoregions. Fire ignition density also varied spatially within ecoregions. Overall fire ignition density was highest in the northwestern ecoregion (4S) and lowest in the eastern ecoregion (3E), which corresponds to the combined gradient of effective humidity and temperature in Ontario. For each ecoregion, comparison of non-spatial simulated fire regime indicators showed statistically non-significant differences between unweighted and weighted ignitions. The spatial burn probability however captured clear spatial differences between unweighted and weighted ignitions. Spatial differences in spatial burn probability between both ignition scenarios were more prominent in ecoregions of high fire occurrence. Results of the weighted ignition scenario closely followed the spatial patterns of the estimated fire ignition density in the study area. Based on these results this thesis rejects the null hypothesis and emphasizes that ignition patterns must be considered in simulating fire regime in Ontario boreal forests.

With increasing levels of motor vehicle ownership, automobile crashes have become a serious public issue in the U.S. and around the world. Knowing when, where, and how traffic accidents happen is critical in order to ensure road safety and to plan for adequate road infrastructure. There is a rich body of literature pertaining to time-related fatal crashes, most of which focuses on non-spatial factors such as a driver’s visibility at night, drinking and drug use, and road conditions. These studies provide a theoretical basis for understanding the causes of crashes from a non-spatial perspective, and a number of traffic laws and policies consequently have been enacted to minimize the impacts of non-spatial factors. Over the past few years, advances in Geographic Information Systems (GIS) have greatly enhanced our ability to analyze traffic accidents from a spatial perspective. This study aims to fill a void in traffic safety studies by comparing and analyzing the differences in the spatial distribution of fatal crashes based on temporal factors, specifically in three periods: 1) day and night; 2) A.M. rush hours and P.M. rush hours; and 3) weekdays and weekends. With the Nashville Metropolitan Area as the study area, the research utilized a number of spatial point-pattern analysis (SPPA) methods, including planar KDE, planar global auto K function, network global cross K functions, and network local cross K functions. All fatal crashes in the Nashville area were found to be clustered and generally follow the patterns of average daily traffic flow. All time-based subtypes of fatal crashes also were found to be concentrated within the central urban area of Nashville, mostly along major roads, and especially near major road intersections and highway interchanges. No notable spatial differences were detected among the subtypes of fatal crashes when applying network global cross K function. However, with the help of the network local cross K function, some localized spatial differences were identified. Some specific locations of hotspots of nighttime and P.M. rush hour fatal crashes were found not to be at the same locations as those at of daytime and A.M. rush hour fatal crashes, respectively. The approach adopted in this study not only provides a new way to analyze spatial distribution of spatial point events such as fatal crashes, but it also can be applied readily to real-world applications. A good understanding of where these spatial differences are should help various agencies practice effective measures and policies in order to improve road conditions, reduce traffic accidents, and ensure road safety.

Lightning-caused forest fires are one of the major natural disturbances in Ontario managed boreal forests. Survival of these forests with fires for centuries shows that such disturbances are integral to the boreal ecosystem and its ecological functioning. Characterizing the fire regimes defined by fire ignition frequency, fire sizes and their spatial distribution patterns etc. thus can help to improve our understanding of the boreal forest dynamics and provide guidance for management practices attempting to maintain biodiversity and achieve sustainability. In this thesis the lightning-caused fire ignitions data for four ecoregions in Ontario managed boreal forests (3E, 3W, 3S and 4S) for 1960–2009 were analyzed using pattern analysis and density estimation to determine the spatial nature of fire ignitions. These fire ignition spatial patterns were further used (as weighted ignition scenario) to simulate forest fire regimes in the study area. Fire regimes were also simulated using spatially unweighted ignitions (unweighted ignition scenario). Non-spatial (total number of fires, total burn area, number of fires by size classes, annual burn fraction) and spatial (spatial burn probability) indicators of the simulated fire regimes under both ignition scenarios were compared to test the null hypothesis that modeled forest fire regime is not affected by the spatial patterns of input fire ignitions. All data analysis were performed for individual ecoregions. Spatial pattern of ignitions were analyzed using the nearest neighbour index and Ripley’s K-function. Ignition densities were estimated using the adaptive kernel density estimation method and the fire regimes were simulated using BFOLDS (Boreal Forests Landscape Dynamics Simulator). Results showed that lightning-caused fire ignitions are clustered in all ecoregions. Fire ignition density also varied spatially within ecoregions. Overall fire ignition density was highest in the northwestern ecoregion (4S) and lowest in the eastern ecoregion (3E), which corresponds to the combined gradient of effective humidity and temperature in Ontario. For each ecoregion, comparison of non-spatial simulated fire regime indicators showed statistically non-significant differences between unweighted and weighted ignitions. The spatial burn probability however captured clear spatial differences between unweighted and weighted ignitions. Spatial differences in spatial burn probability between both ignition scenarios were more prominent in ecoregions of high fire occurrence. Results of the weighted ignition scenario closely followed the spatial patterns of the estimated fire ignition density in the study area. Based on these results this thesis rejects the null hypothesis and emphasizes that ignition patterns must be considered in simulating fire regime in Ontario boreal forests.