Object-oriented and pixel-based image classification using Landsat multispectral and Hyperion hyperspectral imagery in boreal conditions

Current environmental trends dictate a need for new methods, initiatives, and technologies that provide reliable, up-to-date forest information. Canada, which is home to ten percent of the Earth's forests, has made national and international commitments to better monitor the sustainable development of its forest ecosystems. In Ontario, the Ministry of Natural Resources monitors its natural resources through the Ontario Land Cover Database (OLCD). The OLCD is a large area land classification that uses Landsat multispectral imagery with a traditional pixel-based classifier. The goal of this thesis is to explore new ways to improve upon large area land classifications such as the OLCD. This thesis evaluates two alternative approaches: (1) it compares Landsat-5 TM multispectral imagery to Hyperion hyperspectral imagery, and (2) it compares a traditional pixel-based classifier to eCognition's object-oriented image classifier. Eight boreal cover classes were used consisting of water, wetland (aggregated marsh, fen and bog), black spruce, jack pine, mixedwood, dense deciduous, sparse deciduous and clearcuts

Selection for Forage and Avoidance of Risk by Woodland Caribou (Rangifer Tarandus Caribou) at Coarse andLocal Scales

The relationship between selection at coarse and fine spatiotemporal spatial scales is still poorly understood. Some authors claim that, to accommodate different needs at different scales, individuals should have contrasting selection patterns at different scales of selection, while others claim that coarse scale selection patterns should reflect fine scale selection decisions. Here we examine site selection by 110 woodland caribou equipped with GPS radio‐collars with respect to forage availability and predation risk across a broad gradient in availability of both variables in boreal forests of Northern Ontario. We tested whether caribou selection for forage and avoidance of risk was consistent between coarse (seasonal home range) and fine scales of selection. We found that local selection patterns predicted coarse scale selection patterns, indicating a close relationship between the drivers of selection at both spatial scales

Landscape-Level Wolf Space Use is Correlated With Prey Abundance, Ease of Mobility and the Distribution of Prey Habitat

Predator space use influences ecosystem dynamics, and a fundamental goal assumed for a foraging predator is to maximize encounter rate with prey. This can be achieved by disproportionately utilizing areas of high prey density or, where prey are mobile and therefore spatially unpredictable, utilizing patches of their prey\u27s preferred resources. A third, potentially complementary strategy is to increase mobility by using linear features like roads and/or frozen waterways. Here, we used novel population-level predator utilization distributions (termed localized density distributions ) in a single-predator (Wolf), two-prey (moose and caribou) system to evaluate these space-use hypotheses. The study was conducted in contrasting sections of a large boreal forest area in northern Ontario, Canada, with a spatial gradient of human disturbances and predator and prey densities. Our results indicated that wolves consistently used forest stands preferred by moose, their main prey species in this part of Ontario. Direct use of prey-rich areas was also significant but restricted to where there was a high local density of moose, whereas use of linear features was pronounced where local moose density was lower. These behaviors suggest that Wolf foraging decisions, while consistently influenced by spatially anchored patches of prey forage resources, were also determined by local ecological conditions, specifically prey density. Wolves appeared to utilize prey-rich areas when regional preferred prey density exceeded a threshold that made this profitable, whereas they disproportionately used linear features that promoted mobility when low prey density made directly tracking prey distribution unprofitable

Data from: Wolves adapt territory size, not pack size to local habitat quality

1. Although local variation in territorial predator density is often correlated with habitat quality, the causal mechanism underlying this frequently observed association is poorly understood and could stem from facultative adjustment in either group size or territory size. 2. To test between these alternative hypotheses, we used a novel statistical framework to construct a winter population-level utilization distribution for wolves (Canis lupus) in northern Ontario, which we then linked to a suite of environmental variables to determine factors influencing wolf space use. Next, we compared habitat quality metrics emerging from this analysis as well as an independent measure of prey abundance, with pack size and territory size to investigate which hypothesis was most supported by the data. 3. We show that wolf space use patterns were concentrated near deciduous, mixed deciduous/coniferous and disturbed forest stands favoured by moose (Alces alces), the predominant prey species in the diet of wolves in northern Ontario, and in proximity to linear corridors, including shorelines and road networks remaining from commercial forestry activities. 4. We then demonstrate that landscape metrics of wolf habitat quality – projected wolf use, probability of moose occupancy and proportion of preferred land cover classes – were inversely related to territory size but unrelated to pack size. 5. These results suggest that wolves in boreal ecosystems alter territory size, but not pack size, in response to local variation in habitat quality. This could be an adaptive strategy to balance trade-offs between territorial defence costs and energetic gains due to resource acquisition. That pack size was not responsive to habitat quality suggests that variation in group size is influenced by other factors such as intraspecific competition between wolf packs

Space-Use Behavior of Woodland Caribou Based on a Cognitive Movement Model

1. Movement patterns offer a rich source of information on animal behaviour and the ecological significance of landscape attributes. This is especially useful for species occupying remote landscapes where direct behavioural observations are limited. In this study, we fit a mechanistic model of animal cognition and movement to GPS positional data of woodland caribou (Rangifer tarandus caribou; Gmelin 1788) collected over a wide range of ecological conditions. 2. The model explicitly tracks individual animal informational state over space and time, with resulting parameter estimates that have direct cognitive and ecological meaning. Three biotic landscape attributes were hypothesized to motivate caribou movement: forage abundance (dietary digestible biomass), wolf (Canis lupus; Linnaeus, 1758) density and moose (Alces alces; Linnaeus, 1758) habitat. Wolves are the main predator of caribou in this system and moose are their primary prey. 3. Resulting parameter estimates clearly indicated that forage abundance is an important driver of caribou movement patterns, with predator and moose avoidance often having a strong effect, but not for all individuals. From the cognitive perspective, our results support the notion that caribou rely on limited sensory inputs from their surroundings, as well as on long-term spatial memory, to make informed movement decisions. Our study demonstrates how sensory, memory and motion capacities may interact with ecological fitness covariates to influence movement decisions by free-ranging animals