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Landscapes are inherently heterogeneous. However, some portions of a landscape are more heterogeneous than others and are therefore not equally suitable for resource extraction by elephants. Elephants have large energy demands to meet and should spend the majority of their time in areas where they are able to forage optimally. Identifying the determinants of home range location and area may therefore provide insight into aspects of landscape utilization by elephants. Using vegetation structure as a surrogate, I investigated whether landscape heterogeneity explains the variability home range size and location of elephants occurring in the mesic savannas of Zambia and Malawi. I developed a landscape map for each of five study areas. Using these maps, I applied four FRAGSTATS metrics to quantify different aspects of landscape heterogeneity within the study areas, as well as elephant home ranges and randomly located ranges delineated using a 95% Kernel estimation. I placed similar study areas into comparable groups for each of the landscape heterogeneity metrics. Elephant home range size was not a function of landscape heterogeneity metrics and may therefore be explained by other factors. Landscape complexity and diversity of elephant home ranges varied within groups of similar study areas, suggesting that these metrics were important descriptors of home range location. Within study areas, with the exception of patch density, landscape heterogeneity metrics supported the expectation that wet season ranges would be more heterogeneous than those of the dry season. In addition, female ranges were more heterogeneous than those of males during the wet seasons with respect to both patch density and landscape diversity. In most cases, greater landscape heterogeneity within home ranges was only shown during the wet season and this suggests that water requirements preclude selection for more heterogeneous landscapes during the dry season. However, elephants of the Zambian study areas, besides Kafue, selected for metrics indicative of landscape complexity and diversity during both dry and wet seasons. I therefore concluded that elephants favoured complex landscapes with more vegetation types in irregularly arranged patches and landscape heterogeneity therefore determines the location of elephant home ranges. At a regional scale, a landscape comprises habitats of varying suitability to elephants. In a metapopulation framework, such areas may form sources or sinks and therefore contribute to driving elephant movements. The ability to identify areas of importance to elephant range utilization is therefore an essential tool to apply within the megaparks for metapopulations conservation framework. / Dissertation (MSc (Zoology))--University of Pretoria, 2007. / Zoology and Entomology / unrestricted

Spatiotemporal dynamics of resource availability can produce markedly different patterns of landscape utilization which necessitates studying habitat selection across biologically relevant extents. Feral pigs (Sus scrofa) are a prolifically expanding, generalist species and researchers have yet to understand fundamental drivers of space use in agricultural landscapes within the United States. To study multi-scale habitat selection patterns, I deployed 13 GPS collars on feral pigs within the Mississippi Alluvial Valley. I estimated resource selection using mixed-effects models to determine how feral pigs responded to changes in forage availability and incorporated those results with autocorrelated kernel density home range estimates. My results indicated season-specific habitat functional responses to changes in agricultural phenology and illustrated the interdependencies of landscape composition, hierarchical habitat selection, and habitat functional responses. These results indicate fundamental drivers of feral pig spatial distributions in an agricultural landscape which I used to predict habitat use to direct feral pig management.

Movement of organisms is a fundamental component of many ecological processes, and should be subject to strong selective pressures. Spatial selection is the process by which individuals choose the locations to acquire necessary resources or avoid risk, and the relative importance of different factors on spatial selection may change depending on the scale being analyzed. Under the framework of optimality, an individual should attempt to structure their spatial selection economically to maximize fitness. I studied black bear (Ursus americanus) space use, habitat selection, and movement under the optimality paradigm in three populations (Michigan, Missouri, and Mississippi) at four different scales: regional, annual home range, seasonal home range, and denning sites. At the regional scale, I found that black bears displayed scale-dependent land cover selection for movement, selecting forested areas at coarser scales and avoiding anthropogenic disturbance at finer scales, and that large contiguous forests and riparian corridors most facilitate connectivity among protected areas. At the annual and seasonal home range scales, I found black bears display scale-dependent optimizing strategies. Individuals locating their annual ranges to maximize access to areas of high vegetation productivity, together with the high productivity of ranges of all sizes, suggests an energy maximizing strategy, while the negative relationship between range size and both fragmentation and forest proportion suggests area minimizing. More limiting factors act at larger scales, which suggests productivity is the strongest limiting factor and energy maximizing is the dominant strategy while plasticity allows for seasonal area minimizing. At the den site scale, I found that both female and male black bears appeared to minimize anthropogenic risk during denning; however female black bears have a flexible response to anthropogenic disturbance, attempting to minimize it when alone or with older offspring, yet having increased tolerance when infanticide is greater after cubs are born and following den emergence. By quantifying black bear space use and selection across multiple scales, diverse areas, over time, and among and within individuals, I revealed consistent scale-dependent responses to environmental and biological factors while highlighting the intrinsic plasticity of this flexible omnivore.

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Recently, the Whip-poor-will (Caprimulgus vociferous) has become focus of considerable conservation concerns as the result of evidence indicating significant population declines throughout its breeding range (Veit and Petersen 1993). The lack of quantitative data concerning much of this species natural history has delayed recovery efforts and is a fundamental shortcoming in forming effective conservation strategies. Current surveys show Pitch Pine (Pinus rigida) / Scrub Oak (Quercus illicifolia) Barrens (PPSO) as habitat with high numbers of Whip-poor-wills relative to other forest types found throughout the northeastern United States (Cavanaugh in Cink 2002), so we focused our study in these habitats in an attempt to 1) identify habitat selection within PPSO, and 2) determine characteristics of PPSO that make it relatively high quality habitat. Our Study was conducted during the 2005 and 2006 breeding seasons at the Massachusetts Military Reservation on Cape Cod, Massachusetts, USA. We used mist nets to capture adult Whip-poor-wills and affix radio-transmitters for locating individuals during night hours, using triangulation techniques. A kernel analysis of these locations was used to estimate the home range of each individual, where structural characteristics of vegetation was measured, for use in habitat selection analyses. Prey availability was estimated using captures from light traps (Leroy Koehn design, Georgetown, KY) with UV bulbs. Light traps were run on 12 different nights in each habitat during both years of the study. We assessed diet from fecal samples collected at day roost locations used by radio-marked individuals on a daily basis. Samples were dissected under a 22x stereoscope with prey fragments identified to the family when possible. Generalized Linear Mixed Models were used to model habitat selection from structural variables of the habitat collected at used and random locations within the home range, while a compositional analysis of habitat use was also done by comparing the amount of radio-locations in each habitat type to the total amount of that habitat found within the home range. A compositional analysis was also used to test for prey selection. Data from 15 Whip-poor-wills were used in our analyses. Univariate and multivariate statistics showed that there was no difference in vegetation structure between used and random sites. Ground cover was the best predictor of habitat use identified by the GLMM, but was still inefficient for determining habitat use. However, the compositional analysis of habitat use did show a preference of pitch pine – oak forests over pitch pine – scrub oak communities. The fecal analysis showed Whip-poor-wills preferred moths over scarab beetles, and “other” prey items which consisted mainly of beetles other than scarabs, along with neuropterans. Light trap captures showed prey was distributed equally among habitats at the MMR. Although our study did not show any strong relationships between vegetation structure and habitat selection, this may not be the case in habitats of lesser quality (i.e. not PPSO). The habitat preference rank from the compositional analysis directly correlated with the amount of ground cover found in each habitat, which is supporting evidence that ground cover may be an important factor in selecting habitat. Low amounts of ground cover may allow Whip-poor-wills to detect and capture prey more easily, as well as provide open area for an easy escape route from potential predators. Land management techniques such as prescribed burning that reduce understory are recommended treatments to increase habitat quality for Whip-poor-wills.

Successful recovery of the federally threatened southeastern beach mouse (Peromyscus polionotus niveiventris) depends in part on an understanding of their habitat requirements. I studied habitat use by beach mice at Cape Canaveral Air Force Station, Florida from March 2005 until March 2006. I livetrapped six grids, three on coastal dunes and three within scrub located inland from the coast. On each grid and trap station, I quantified the extent of bare ground, woody vegetation, non-woody vegetation, height of vegetation, and percentage of coarse sand in the surface soil. I assessed trap success relative to these habitat variables using linear and multiple regression, correlation, and ordination. Significantly higher numbers of mice were captured in the scrub habitat relative to the coastal habitat. Linear regression of trap success against the habitat variables did not reveal any significant relationships at the level of grids. A non-metric multidimensional scaling model was designed to capture the vegetation heterogeneity at the trapping sites and clarify the results. This methodology identified a predominantly dune and predominately scrub cluster of trap sites. A bubble plot showed higher densities of beach mice using the scrub habitat types. These results suggest beach mice are selecting for those habitat variables defined by the ordination: higher vegetation height, more woody vegetation types, less bare ground, and less heterogeneity.

Habitat loss is the leading cause of species extinction. Protecting and managing habitat quality is vital to an organism's persistence, and essential to endangered species recovery. We conducted an investigation of habitat quality and potential impacts from climate change to piping plovers (Charadrius melodius) breeding on the barrier island ecosystem of New York, during 2003-2005. Our first step in this analysis was to examined the relationship between two common measures of habitat quality: density and productivity (Chapter 1). We used both central and limiting tendency data analysis to find that density significantly limited productivity across many spatial scales, especially broader scales. Our analysis of plover habitat quality (Chapter 2) focused on 1) identifying the spatial scaling of plovers to their environment; 2) determining the relative importance of four aspects of the environment (land cover, predation, management, and disturbance); and 3) determining the key environmental variables that influence productivity. We found that plover habitat selection occurred within a narrow range of spatial scales that was unique to each environmental variable. Further, we found that management and predation variables influenced population-level productivity relatively more than land cover and disturbance. Environmental variables with a significant positive influence on habitat quality were land management units, plover conservation educational signs, and symbolic string fencing erected around plover nesting areas. We found a significant negative relationship among density of people on ocean beaches, herring gull density, and land cover degradation. To quantify possible impact to plover habitat from future climate change (Chapter 3), we examined the extent of habitat change resulting from different estimates of sea-level rise (SLR) and storminess over the next 100 years. We found that the particular SLR estimate, habitat response, and storm type used to model climate changes influenced the amount of potential habitat available. Importantly, we observed synergy between SLR and storms resulting in the increasing impact of SLR and storms on plover habitat over the next 100 years. Finally, we found that coastal development contributed considerably to habitat loss when combined with climate changes. Our findings raise concerns regarding current plover recovery goals and management strategies. Density-dependent productivity may threaten the goal of a joint increase in both plover population and productivity. We advocate density monitoring and allocation of alternative nesting areas to provide the relief of possible high-density limitations. Based on our analysis of habitat selection and climate change threats, we call for a shift in management focus away from known breeding areas, towards ecosystem processes. Long-term conservation of piping plover habitat quality is more likely through protecting and promoting natural barrier island dynamics (i.e. overwash and migration) and minimizing human development on the barrier islands of New York State.

The purpose of this study is to analyze which variables influence the capercaillie’s (Tetrao urogallus) selection of lek sites in northern Sweden by using remote sensing data. The lek site is a crucial area for the species’ reproductive success. Studies outside of northern Sweden have confirmed that the landscape structure highly influences the selection of lek sites. This study examines whether the type of vegetation, forest volume and proximity to anthropogenic disturbances influence the selection of lek sites. The findings can be used to create a prioritizing map of northern Sweden to aid in conservation management and improve future inventories. 58 lek sites within five different counties were analyzed by a use-availability design, using a generalized linear mixed model with a binary distribution of the dependent variables. The vegetation types of pine forest, wet pine forest, continuous pine forest, mixed coniferous forest and wet other mixed forest were preferred by capercaillie, while other mixed forest, mire, continuous other forest, young forest, and clear cuts were avoided. Wet pine forest was the only vegetation type that had higher probability (36%) to be chosen over pine forest. For forest volume, the probability of being chosen increased with 22 % for each additional unit (m3/ha). For distance to buildings and roads, the probability of being chosen increased with 10 % for each additional unit of distance. I conclude that vegetation type, forest volume and proximity to anthropogenic disturbances influence the capercaillie selection of lek sites in northern Sweden.