Modélisation de l'utilisation de l'habitat du béluga du Saint-Laurent en fonction de ses proies à l'embouchure de la rivière Saguenay et à la baie Sainte-Marguerite

Le béluga du Saint-Laurent est une espèce menacée au Canada et protégée par la Loi sur les espèces en péril du Canada. La détermination des fonctions biologiques de ses habitats essentiels est nécessaire afin d’assurer le rétablissement de la population. Parcs Canada a entamé en 2009 un suivi des proies du béluga dans deux de ses aires de fréquentation intensive situées dans le Parc marin du Saguenay–Saint-Laurent : l’embouchure de la rivière Saguenay et la baie Sainte-Marguerite. L’étude de l’abondance et de la distribution des proies est réalisée par sondage hydroacoustique le long de transects à l’aide d’un échosondeur multifréquences. Un protocole d’observations systématiques du béluga est mené simultanément aux sondages hydroacoustiques à partir de sites terrestres. Le premier objectif de cette étude est de développer la méthodologie concernant le traitement, la classification et la cartographie des données hydroacoustiques échantillonnées. L’objectif principal consiste à déterminer si l’abondance et la distribution des proies pélagiques ont une influence sur l’utilisation de ces deux habitats par le béluga. La cartographie de la biomasse relative de poissons a été réalisée pour la couche de surface, la couche en profondeur et pour l’ensemble de la colonne d’eau par krigeage ordinaire pour les deux habitats pour les 29 transects. À la baie Sainte-Marguerite, le nombre de bélugas observés augmente avec la biomasse relative des proies en surface et en profondeur. À l’embouchure de la rivière Saguenay, les résultats n’ont pas été concluants. Les résultats suggèrent que l’alimentation pourrait être l’une des fonctions biologiques de la baie Sainte-Marguerite.

Contributions of local, lateral and contextual habitat variables to explaining variation in fisheries productivity metrics in the littoral zone of a reservoir

Puisque l’altération des habitats d’eau douce augmente, il devient critique d’identifier les composantes de l’habitat qui influencent les métriques de la productivité des pêcheries. Nous avons comparé la contribution relative de trois types de variables d’habitat à l’explication de la variance de métriques d’abondance, de biomasse et de richesse à l’aide de modèles d’habitat de poissons, et avons identifié les variables d’habitat les plus efficaces à expliquer ces variations. Au cours des étés 2012 et 2013, les communautés de poissons de 43 sites littoraux ont été échantillonnées dans le Lac du Bonnet, un réservoir dans le Sud-est du Manitoba (Canada). Sept scénarios d’échantillonnage, différant par l’engin de pêche, l’année et le moment de la journée, ont été utilisés pour estimer l’abondance, la biomasse et la richesse à chaque site, toutes espèces confondues. Trois types de variables d’habitat ont été évalués: des variables locales (à l’intérieur du site), des variables latérales (caractérisation de la berge) et des variables contextuelles (position relative à des attributs du paysage). Les variables d’habitat locales et contextuelles expliquaient en moyenne un total de 44 % (R2 ajusté) de la variation des métriques de la productivité des pêcheries, alors que les variables d’habitat latérales expliquaient seulement 2 % de la variation. Les variables les plus souvent significatives sont la couverture de macrophytes, la distance aux tributaires d’une largeur ≥ 50 m et la distance aux marais d’une superficie ≥ 100 000 m2, ce qui suggère que ces variables sont les plus efficaces à expliquer la variation des métriques de la productivité des pêcheries dans la zone littorale des réservoirs.

Evaluating the Potential Impact of a Gas Pipeline on Whimbrel Breeding Habitat in the Outer Mackenzie Delta, Northwest Territories

We used ground surveys to identify breeding habitat for Whimbrel (Numenius phaeopus) in the outer Mackenzie Delta, Northwest Territories, and to test the value of high-resolution IKONOS imagery for mapping additional breeding habitat in the Delta. During ground surveys, we found Whimbrel nests (n = 28) in extensive areas of wet-sedge low-centered polygon (LCP) habitat on two islands in the Delta (Taglu and Fish islands) in 2006 and 2007. Supervised classification using spectral analysis of IKONOS imagery successfully identified additional areas of wet-sedge habitat in the region. However, ground surveys to test this classification found that many areas of wet-sedge habitat had dense shrubs, no standing water, and/or lacked polygon structure and did not support breeding Whimbrel. Visual examination of the IKONOS imagery was necessary to determine which areas exhibited LCP structure. Much lower densities of nesting Whimbrel were also found in upland habitats near wetlands. We used habitat maps developed from a combination of methods, to perform scenario analyses to estimate the potential effects of the Mackenzie Gas Project on Whimbrel habitat. Assuming effective complete habitat loss within 20 m, 50 m, or 250 m of any infrastructure or pipeline, the currently proposed pipeline development would result in loss of 8%, 12%, or 30% of existing Whimbrel habitat. If subsidence were to occur, most Whimbrel habitat could become unsuitable. If the facility is developed, follow-up surveys will be required to test these models.

A method for setting the size of plant conservation target areas

Realistic time frames in which management decisions are made often preclude the completion of the detailed analyses necessary for conservation planning. Under these circumstances, efficient alternatives may assist in approximating the results of more thorough studies that require extensive resources and time. We outline a set of concepts and formulas that may be used in lieu of detailed population viability analyses and habitat modeling exercises to estimate the protected areas required to provide desirable conservation outcomes for a suite of threatened plant species. We used expert judgment of parameters and assessment of a population size that results in a specified quasiextinction risk based on simple dynamic models The area required to support a population of this size is adjusted to take into account deterministic and stochastic human influences, including small-scale disturbance deterministic trends such as habitat loss, and changes in population density through processes such as predation and competition. We set targets for different disturbance regimes and geographic regions. We applied our methods to Banksia cuneata, Boronia keysii, and Parsonsia dorrigoensis, resulting in target areas for conservation of 1102, 733, and 1084 ha, respectively. These results provide guidance on target areas and priorities for conservation strategies.

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Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.

Spatial Relationships among Hydroacoustic, Hydrographic and Top Predator Patterns: Cetacean Distributions in the Mid-Atlantic Bight

Effective conservation and management of top predators requires a comprehensive understanding of their distributions and of the underlying biological and physical processes that affect these distributions. The Mid-Atlantic Bight shelf break system is a dynamic and productive region where at least 32 species of cetaceans have been recorded through various systematic and opportunistic marine mammal surveys from the 1970s through 2012. My dissertation characterizes the spatial distribution and habitat of cetaceans in the Mid-Atlantic Bight shelf break system by utilizing marine mammal line-transect survey data, synoptic multi-frequency active acoustic data, and fine-scale hydrographic data collected during the 2011 summer Atlantic Marine Assessment Program for Protected Species (AMAPPS) survey. Although studies describing cetacean habitat and distributions have been previously conducted in the Mid-Atlantic Bight, my research specifically focuses on the shelf break region to elucidate both the physical and biological processes that influence cetacean distribution patterns within this cetacean hotspot.

In Chapter One I review biologically important areas for cetaceans in the Atlantic waters of the United States. I describe the study area, the shelf break region of the Mid-Atlantic Bight, in terms of the general oceanography, productivity and biodiversity. According to recent habitat-based cetacean density models, the shelf break region is an area of high cetacean abundance and density, yet little research is directed at understanding the mechanisms that establish this region as a cetacean hotspot.

In Chapter Two I present the basic physical principles of sound in water and describe the methodology used to categorize opportunistically collected multi-frequency active acoustic data using frequency responses techniques. Frequency response classification methods are usually employed in conjunction with net-tow data, but the logistics of the 2011 AMAPPS survey did not allow for appropriate net-tow data to be collected. Biologically meaningful information can be extracted from acoustic scattering regions by comparing the frequency response curves of acoustic regions to theoretical curves of known scattering models. Using the five frequencies on the EK60 system (18, 38, 70, 120, and 200 kHz), three categories of scatterers were defined: fish-like (with swim bladder), nekton-like (e.g., euphausiids), and plankton-like (e.g., copepods). I also employed a multi-frequency acoustic categorization method using three frequencies (18, 38, and 120 kHz) that has been used in the Gulf of Maine and Georges Bank which is based the presence or absence of volume backscatter above a threshold. This method is more objective than the comparison of frequency response curves because it uses an established backscatter value for the threshold. By removing all data below the threshold, only strong scattering information is retained.

In Chapter Three I analyze the distribution of the categorized acoustic regions of interest during the daytime cross shelf transects. Over all transects, plankton-like acoustic regions of interest were detected most frequently, followed by fish-like acoustic regions and then nekton-like acoustic regions. Plankton-like detections were the only significantly different acoustic detections per kilometer, although nekton-like detections were only slightly not significant. Using the threshold categorization method by Jech and Michaels (2006) provides a more conservative and discrete detection of acoustic scatterers and allows me to retrieve backscatter values along transects in areas that have been categorized. This provides continuous data values that can be integrated at discrete spatial increments for wavelet analysis. Wavelet analysis indicates significant spatial scales of interest for fish-like and nekton-like acoustic backscatter range from one to four kilometers and vary among transects.

In Chapter Four I analyze the fine scale distribution of cetaceans in the shelf break system of the Mid-Atlantic Bight using corrected sightings per trackline region, classification trees, multidimensional scaling, and random forest analysis. I describe habitat for common dolphins, Risso’s dolphins and sperm whales. From the distribution of cetacean sightings, patterns of habitat start to emerge: within the shelf break region of the Mid-Atlantic Bight, common dolphins were sighted more prevalently over the shelf while sperm whales were more frequently found in the deep waters offshore and Risso’s dolphins were most prevalent at the shelf break. Multidimensional scaling presents clear environmental separation among common dolphins and Risso’s dolphins and sperm whales. The sperm whale random forest habitat model had the lowest misclassification error (0.30) and the Risso’s dolphin random forest habitat model had the greatest misclassification error (0.37). Shallow water depth (less than 148 meters) was the primary variable selected in the classification model for common dolphin habitat. Distance to surface density fronts and surface temperature fronts were the primary variables selected in the classification models to describe Risso’s dolphin habitat and sperm whale habitat respectively. When mapped back into geographic space, these three cetacean species occupy different fine-scale habitats within the dynamic Mid-Atlantic Bight shelf break system.

In Chapter Five I present a summary of the previous chapters and present potential analytical steps to address ecological questions pertaining the dynamic shelf break region. Taken together, the results of my dissertation demonstrate the use of opportunistically collected data in ecosystem studies; emphasize the need to incorporate middle trophic level data and oceanographic features into cetacean habitat models; and emphasize the importance of developing more mechanistic understanding of dynamic ecosystems.

Modeling Habitat Associations for the Common Loon (Gavia immer) at Multiple Scales in Northeastern North America

Common Loon (Gavia immer) is considered an emblematic and ecologically important example of aquatic-dependent wildlife in North America. The northern breeding range of Common Loon has contracted over the last century as a result of habitat degradation from human disturbance and lakeshore development. We focused on the state of New Hampshire, USA, where a long-term monitoring program conducted by the Loon Preservation Committee has been collecting biological data on Common Loon since 1976. The Common Loon population in New Hampshire is distributed throughout the state across a wide range of lake-specific habitats, water quality conditions, and levels of human disturbance. We used a multiscale approach to evaluate the association of Common Loon and breeding habitat within three natural physiographic ecoregions of New Hampshire. These multiple scales reflect Common Loon-specific extents such as territories, home ranges, and lake-landscape influences. We developed ecoregional multiscale models and compared them to single-scale models to evaluate model performance in distinguishing Common Loon breeding habitat. Based on information-theoretic criteria, there is empirical support for both multiscale and single-scale models across all three ecoregions, warranting a model-averaging approach. Our results suggest that the Common Loon responds to both ecological and anthropogenic factors at multiple scales when selecting breeding sites. These multiscale models can be used to identify and prioritize the conservation of preferred nesting habitat for Common Loon populations.

MODELING POTENTIAL TIGER HABITAT IN HUPINGSHAN-HOUHE ANDMANGSHAN-NANLING NATIONAL NATURE RESERVES, CHINA

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Modeling Potential Tiger Habitat in Hupingshan-Houhe and Mangshan-Nanling National Nature Reserves, China

After declining steadily for several decades, the South China tiger (Panthera tigris amoyensis) is now thought to be extinct in the wild. However, there is some hope of reintroduction, with Hupingshan-Houhe and Mangshan-Nanling National Nature Reserves in southern China seeming to hold the most promise. Our study used slope, elevation, vegetation, and landcover variables to construct a rough habitat suitability index for tigers in these two parks. According to our model, there are areas of suitable habitat within both parks. However, there are some important variables that we were unable to include in our model, such as human population density and prey availability. Considerable in-depth research will be necessary to evaluate the suitability of these locations before reintroduction is considered.

Modeling Habitat Split: Landscape and Life History Traits Determine Amphibian Extinction Thresholds

Habitat split is a major force behind the worldwide decline of amphibian populations, causing community change in richness and species composition. In fragmented landscapes, natural remnants, the terrestrial habitat of the adults, are frequently separated from streams, the aquatic habitat of the larvae. An important question is how this landscape configuration affects population levels and if it can drive species to extinction locally. Here, we put forward the first theoretical model on habitat split which is particularly concerned on how split distance - the distance between the two required habitats - affects population size and persistence in isolated fragments. Our diffusive model shows that habitat split alone is able to generate extinction thresholds. Fragments occurring between the aquatic habitat and a given critical split distance are expected to hold viable populations, while fragments located farther away are expected to be unoccupied. Species with higher reproductive success and higher diffusion rate of post-metamorphic youngs are expected to have farther critical split distances. Furthermore, the model indicates that negative effects of habitat split are poorly compensated by positive effects of fragment size. The habitat split model improves our understanding about spatially structured populations and has relevant implications for landscape design for conservation. It puts on a firm theoretical basis the relation between habitat split and the decline of amphibian populations. © 2013 Fonseca et al.

DISTRIBUTION OF CAPYBARAS IN AN AGROECOSYSTEM, SOUTHEASTERN BRAZIL, BASED ON ECOLOGICAL NICHE MODELING

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

Investigating habitat association of breeding birds using public domain satellite imagery and land cover data.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies