1,720,976 research outputs found
Classifying wetlands using random forest machine learning, airborne light detection and ranging and Earth observation satellite data in the Okanagan basin, British Columbia
No full textDespite wetlands being critical components of healthy functioning landscapes and providing valuable ecosystem services, they are being lost at alarming rates due to human influence. Their dynamic nature and varying hydrology and vegetation make identification and classification challenging. Recent advancements in satellite remote sensing and light detection and ranging (LiDAR) provide opportunities to predict and map wetland classes at regional scales. In the semi-arid region of the Okanagan Basin, wetlands are rare biodiversity hotspots that provide critical habitat for many species at risk. Building on existing wetland inventories that have limited coverage, a random forest probabilistic model was developed to predict, classify and map wetlands in the Okanagan at a 10 m spatial scale. In total, 22 covariates representing multispectral and synthetic aperture radar metrics derived from Sentinel-2 and Sentinel-1; topography and vegetation derived from LiDAR; and ancillary geospatial data were used to classify wetlands. The model was trained using an existing wetland database and provincial datasets to predict the probability of each pixel belonging to the following six-classes: fen, marsh, shallow-water, swamp, upland, and open-water.
Model performance was evaluated using a confusion matrix and had an overall accuracy of 84.8%. The model predicted that 313.9 km² (3.6%) of the 8,635 km² study area represented areas where wetland probability was ≥ 50%. Marshes were the most commonly occurring wetland (159.0 km²) followed by swamp (150.3 km²), shallow-water (3.7 km²), and fen (0.9 km²). The most important predictor variables for wetlands were slope, distance from streams, probability of depression, number of days above five degrees Celsius, topographic position index, seasonal change in the normalized difference vegetation index, standard deviation of vegetation height, and the red band from Sentinel-2. The wetland model developed here identified and classified new wetlands and provided a comprehensive inventory of wetlands in the Okanagan using a replicable approach with publicly available data. The resulting wetland inventory can help inform regional wetland conservation and management and will serve as an important baseline for land use planning and climate change mitigation.Science, Irving K. Barber Faculty of (Okanagan)Earth, Environmental and Geographic Sciences, Department of (Okanagan)Graduat
Quantifying spatial-temporal change in habitat occupancy patterns of grizzly bears (Ursus arctos) in the context of industrial activities in western Alberta
No full textLandscape change is a primary driver of global species decline, requiring effective approaches for monitoring wildlife populations. Occupancy modelling, which estimates the probability of a species being present on a landscape, has become a popular method for monitoring wildlife populations and habitat quality. Among large mammal species in North America, grizzly bears (Ursus arctos) are particularly vulnerable to and threatened by anthropogenic pressures.
Using hair-snag data collected in 2004 and 2014 from a threatened grizzly bear population in Alberta, Canada, this research developed single-season occupancy models to understand how anthropogenic disturbance and landscape conditions influence occupancy patterns of male and female grizzly bears over a decade. I then quantified spatial patterns of grizzly bear occupancy and density using measures of spatial autocorrelation to assess relationships between occupancy and density and landscape processes related to anthropogenic disturbance and topography. By examining the spatial relationships between predicted grizzly bear occupancy-abundance estimates over a decade, I was able to provide a better understanding how observed patterns are influenced by disturbance and identify important habitat.
Occupancy models showed the average occupancy probability decreased slightly (0.35 to 0.34), despite observed increases in grizzly bear population (36.0 to 71.3 individuals) over a decade. However, spatial patterns of occupancy showed previously unoccupied cells in eastern portions of the study area were colonized from 2004 to 2014. Male occupancy was negatively related to anthropogenic disturbance, including cutblocks and all disturbance, compared to females. Anthropogenic disturbance had an increased influence over time, highlighting the need to consider cumulative effects in occupancy monitoring. Spatial patterns of occupancy and density estimates were similar, with clusters of high occupancy and density occurring where terrain is complex and human access is limited. These areas may act as important source habitat for the population with dispersers occupying potential sink habitats where disturbance and mortality are higher. The occupancy modelling framework and results provide a better understanding of the impacts of anthropogenic disturbance on grizzly bear occupancy and population persistence for regulatory bodies, wildlife managers, and industry, which will contribute to the conservation of grizzly bears and other large carnivores.Science, Irving K. Barber Faculty of (Okanagan)Earth, Environmental and Geographic Sciences, Department of (Okanagan)Graduat
Spatial variation in grizzly bear diet across British Columbia
No full textDietary niche variation is a key facet of an animal’s niche and can be a driver of spatial variation
in behaviour, population dynamics, and sensitivity to anthropogenic threats. Spatial assessments
of the variation of an animal’s dietary niche helps provide key baseline knowledge for the
research and management of a species and are particularly important for species with large
geographic ranges and highly variable niches. Grizzly bears (Ursus arctos) are a wide-ranging
omnivorous mammal with enormous dietary flexibility and a species of concern in Canada. I
estimated the proportion of vegetation, terrestrial meat, anadromous salmon, and non-
anadromous kokanee salmon in the diet of over 1800 grizzly bears via stable isotope analyses of
over 2500 guard hair samples collected across the province of British Columbia. Using these
estimates, I created fine-scale maps of grizzly bear diet using a parametric generalized additive
mixed effects model with spatial random fields. The results of these predictive models showed
that spatial distribution of grizzly bear’s dietary niche in B.C. can be broadly categorized into
coastal areas where bears are reliant on salmon, and interior areas where they are reliant on plant
foods. Terrestrial meat sources and kokanee salmon provided important supplements to bear diet
in certain regions, but nowhere were they as important to bear diet as plants or salmon. These
results also showed that spatial variation in grizzly bear diet is not currently reflected in the
boundaries of B.C.’s Grizzly Bear Population Units, which represents a major obstacle to
effective management across the province.Science, Irving K. Barber Faculty of (Okanagan)Earth, Environmental and Geographic Sciences, Department of (Okanagan)Graduat
Classifying riparian forests of the Okanagan Basin, British Columbia, Canada, through random forest modelling with LiDAR and spectral derived parameters
No full textRiparian forests are integral components of landscapes due to their ecological significance and the services they provide to both terrestrial and aquatic ecosystems. These unique ecosystems act as buffers, regulating water quality, stabilizing streambanks, providing habitat for diverse flora and fauna, and influencing local microclimates. Accurate assessment and classification of riparian forests are essential for effective land management and conservation efforts, especially in regions like the Okanagan Basin, where water resources are particularly vulnerable to anthropogenic impacts and climate change. Recent advancements in remote sensing (RS) technologies, particularly the integration and availability of multispectral and LiDAR data, offer opportunities to predict and delineate riparian forest composition at larger scales and over potentially inaccessible terrain, enabling comprehensive assessments of these ecosystems' spatial distribution, structural attributes, and species composition. This study integrated fine-scale RGB RS imagery with LiDAR data to classify riparian forest tree species in select fish-bearing streams within the Okanagan River system, to develop a reproducible and cost-effective process for predicting ten native tree species classes and one infrastructure class. To inform the random forest (RF) classification model, a total of 23 explanatory covariates created from LiDAR and RGB data were incorporated. The model was trained using 1,611 observations, collected through in-situ field visits and supplemented by open-access tree inventory data, sourced from various reaches of the study area, encompassing diverse locations, elevations, and ecosystem types.
The RF model achieved an overall accuracy of 96.03%, evaluated through a confusion matrix. In the 100 m buffers used to describe riparian environments of the study area, (129,802 ha), 85,679 ha (66% of the area) were classified into 11 classes. The spruce class was the most predicted class (54.16% of classified cells), followed by western redcedar (15.01%), and lodgepole pine (7.46%). Of the 23 explanatory covariates used, LiDAR-derived covariates were found to be more influential than RGB-derived covariates. This research provides valuable insights for land management strategies and conservation efforts, especially in regions like the Okanagan Basin, where water resources are particularly vulnerable to anthropogenic impacts and climate change.Science, Irving K. Barber Faculty of (Okanagan)Earth, Environmental and Geographic Sciences, Department of (Okanagan)Graduat
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Quantifying grizzly bear (Ursus arctos) habitat selection for a seasonal resource, the Canadian buffaloberry (Sheperdia canadensis) in southern British Columbia
No full textWildlife conservation requires timely information on the availability and use of key
habitats and resources by a species. Among large terrestrial carnivores in North America,
grizzly bears (Ursus arctos) are experiencing substantial reductions in range and population
size due to habitat loss and anthropogenic activities. To support grizzly bear conservation,
this research will quantify the impacts of anthropogenic disturbance and habitat
characteristics on grizzly bear habitat selection for an essential seasonal resource,
buffaloberry (Sheperdia canadensis).
Using grizzly bear telemetry data across southern British Columbia, Canada, this
research first develops a resource selection function to predict buffaloberry selection based
on the influence of disturbance and habitat characteristics. Grizzly bear recursive
movements were then quantified using a revisitation analysis to test competing hypotheses
related to the influence of buffaloberry availability, resource availability and disturbance
conditions on foraging behaviour during the buffaloberry ripe period.
The probability of selection for habitat with buffaloberry was widely distributed
throughout southern BC, with notable clusters of high probabilities. Six variables influenced
the probability of selection: available kilocalories of buffaloberry, elevation, distance to
roads, aspect, terrain ruggedness index, and canopy height. Selection for habitat with
buffaloberry generally increased as available kilocalories increased, between 400 – 1500m
and 2500 – 2700m elevation, occurred near roads but increased as the distance from a
road increased, was highest on northern and southern aspects, in habitat with low terrain
ruggedness, and moderate canopy height. The number of revisits to a site increased as the
percent cover of fruiting buffaloberry increased. This work has several direct and indirect
applications to the management of grizzly bears in southern BC. Our research identified that
the most important factors influencing grizzly bear habitat selection for buffaloberry was
iv
buffaloberry productivity (i.e., moderate to high available kilocalories of buffaloberry and high
percent cover of fruiting buffaloberry), highlighting the need to create more areas that foster
understory growth and encourage buffaloberry production. Analyzing the drivers of grizzly
bear habitat selection for buffaloberry provides a better understanding of the impacts of
anthropogenic disturbance and habitat quality on behaviour helping to inform pro-active and
adaptive grizzly bear conservation.Science, Irving K. Barber Faculty of (Okanagan)Earth, Environmental and Geographic Sciences, Department of (Okanagan)Graduat
Spatiotemporal analysis of ecosystem change and landscape connectivity using satellite imagery in west-central British Columbia, Canada
No full textEnvironmental change poses a significant threat to landscape connectivity and threatened wildlife populations. There is a growing need to understand the impacts of broad-scale change across dynamic landscapes on wildlife movement to inform conservation strategies and landscape management plans. As the availability of satellite imagery time series increases, there are new opportunities to monitor broad-scale changes in ecosystems and landscape connectivity. The objective of this thesis is to apply novel methodological approaches using a time series of Landsat imagery to quantify spatiotemporal changes in ecosystem cover and landscape connectivity from 1997 to 2019 in west-central British Columbia, Canada. Using Time-Weighted Dynamic Time Warping (TWDTW) and Landsat imagery, spatiotemporal changes in biogeoclimatic ecosystem classification (BEC) zones were quantified to summarize complex patterns of change that reflect the influence of landscape disturbance. The TWDTW classification showed a transition of the IDF Dry ecosystem to MS Dry and SPBS Dry in the north and northeast of the study area in response to large wildfires in the region. Reduced IDF Dry cover signifies a loss in ungulate habitat, variation in the “green-up” date of vegetation, and increased low productivity forest cover. Omniscape, a circuit theory approach for omni-directional landscape connectivity modelling, was then used to quantify and map landscape connectivity for moose (Alces alces) populations in 1997, 2009, and 2019 and assess the impacts of ecosystem change on potential wildlife movement. Overall landscape connectivity for moose reduced by 70.23% between 1997 and 2019, during which time broad-scale disturbance resulted in ecosystem change. Results represent a novel spatiotemporal analysis of landscape connectivity, reveal variation in overall connectivity for moose across the region in response to disturbance, and predict the location of potential movement corridors. In summary, this thesis demonstrates the application of the TWDTW approach to classify spatiotemporal changes in ecosystem cover across heterogeneous landscapes and the suitability of the Omniscape method for quantifying changing patterns of potential landscape connectivity in the context of ongoing ecosystem change. The combination of time series ecosystem change monitoring and connectivity modelling provides the opportunity to examine the important spatiotemporal relationship between ecosystem cover, disturbance, and wildlife movement.Science, Irving K. Barber Faculty of (Okanagan)Earth, Environmental and Geographic Sciences, Department of (Okanagan)Graduat
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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