The widespread loss and degradation of habitat constitutes the largest threat to biodiversity in North America. While regulatory programs such as the Endangered Species Act of 1973 and wetland permitting under the Clean Water Act have addressed acute assaults on critical habitat, large areas of unprotected uplands have been lost. Urban development, particularly the advent of lower density suburban and rural sprawl, has greatly diminished the extent of contiguous patches of forest habitat and introduced a host of other undesirable effects on ecosystem function. This study sought to evaluate the extent of urban sprawl and its effects on ecological integrity in Florida using Landsat-derived land cover data collected by the Florida Fish and Wildlife Conservation Commission (FWC) circa 1987 and 2003. Chapter 1 described a novel GIS technique for correcting the systematic errors in the FWC 1987 and 2003 land cover data and converting those data to a common classification system so that they could be used in any ad hoc land cover change analysis. Comparison to ground-truth observations demonstrated a significant improvement in the accuracy of the land cover data following the Land Cover Correction Process (LCCP). Change detection between 1987 and 2003 using the correct land cover revealed trends in land cover conversion that were very different from previously published results derived from the original FWC land cover data. Conversion to urban uses in the corrected data was 47,293 ha lower, and conversion to agricultural uses was reduced by 196,773 ha, resulting in 244,067 ha less anthropogenic land conversion than had been previously estimated. Although the corrected land cover data showed that overall land conversion of natural areas was lower compared to the earlier estimate, the corrected data showed proportionally greater habitat losses for four important habitat types: Pinelands (-10.08% in the corrected land cover as compared to -5.90% in the original FWC data); upland forest (-9.46% versus 6.37%); sandhill (-13.90% versus 11.18%); and scrub (-15.52% versus -9.83%). Given the relatively small areal extent of some of these habitats, the larger percent loss estimates over the study period revealed by the corrected land cover data are cause for even greater concern by conservation planners and policymakers. Now that its utility has been demonstrated, the LCCP technique can be applied to any pair of roughly similar land cover mapping datasets provided that their original classification systems can be composed by a cross-walk into a single scheme, and that one or more ancillary data sets are available to serve in the tie-breaker role performed here by the land use data from Florida's Water Management Districts. The Soil Survey Geographic (SSURGO) and State Soil Geographic (STATSGO) soils data of the National Resource Conservation Service, the National Land Cover Dataset (NLCD) or the statewide habitat mapping of the USGS GAP Analysis Program could be adapted to provide the ancillary tie-breaker data required by the LCCP to conduct change detection between disparate land cover data sources heretofore considered too incompatible for that purpose. In Chapter 2, measures of urban sprawl, habitat loss and fragmentation in Florida were estimated using the corrected land cover data for 1987 and 2003. The Northwest and North regions of the state exhibited significantly higher indices of urban sprawl, habitat loss and habitat fragmentation via application of the Moran's I statistic. Reducing urban sprawl and habitat fragmentation spatial metrics to simple ordination variables through the use of non-metric multidimensional scaling produced new measures of urban sprawl and habitat fragmentation that correlated strongly with the original FRAGSTATS metrics, but could be more easily mapped and interpreted. Urban and Habitat ordination metrics were each spatially autocorrelated (Local Moran's I and K-means grouping analyses) but not correlated to each other using the Procrustes analysis PROTEST statistic (m2 = 0.952, p = 0.061). In contrast, individual urban sprawl metrics (CA, NP, LPI, ED, SHAPE_AM and DCAD) correlated with habitat fragmentation. NP and DCAD appeared to be particularly useful in predicting fragmentation, and county governments should take measures to reduce establishment of new urban patches to minimize NP and DCAD. Chapter 3 explored the relationship between environmental outcomes in habitat loss and fragmentation and the quality of county local government comprehensive plans. The use of NMS analysis provided a powerful technique for capturing the intrinsic variability of the Local Government Comprehensive Plan (LGCP) plan scoring systems of Brody (2003) and Pannozzo (2013) into a pair of variables each that could be used to explore associations with metrics of urban sprawl, habitat fragmentation and other county characteristics that influence urban growth and development. The geographic distribution of LGCP plan quality favored coastal counties with higher quality plans over inland counties, and there was some evidence that plans in Central and South regions of Peninsular Florida were superior to those in the North and Northwest Panhandle regions. Key factors in plan quality, specifically Coordination and Management, were strongly associated with urban sprawl or habitat fragmentation outcomes. The resources available to counties in the form of tax revenues, whether the county possessed a rural or urban economy, and the county's political makeup also appeared related to LGCP plan quality, urban sprawl or habitat fragmentation outcomes. More research will be needed to elucidate the specific causal mechanisms behind the implementation of local government planning that resulted in the observed environmental outcomes.

Foredunes are formed and developed in association with vegetation. A bare sand area has been viewed as a measure of dune mobility or activity and researched in association with climate controls: particularly wind power, annual mean precipitation, and temperature, expressed in annual mean potential evapotranspiration. There has been no research that utilized the patterns of bare sand areas to classify foredune areas in coastal dune systems and investigated climate controls related to sand patch patterns, or “foredune textures” such as size, number, and distribution of sand patches Four foredune types were classified based on four landscape metrics (PLAND: percentage of bare sand area, PLADJ: proportion of like-adjacencies, NLSI: normalized landscape shape index, and ENN_RA: range of Euclidean nearest neighbor), by applying the concepts and methodologies of landscape ecology. Four climate variables (annual mean precipitation, annual mean potential evapotranspiration, Lancaster’s mobility index, and the standard deviation of annual mean precipitation) were found to affect the foredune types and help in distinguishing one foredune type from another. The amount of bare sand area on coastal foredune areas can be explained by annual mean precipitation (R^2 is 0.52 at the 99 % confidence level), standard deviation of precipitation (R^2 is 0.51 at the 99 % confidence level), and Lancaster’s mobility index (R^2 is 0.37 at the 99 % confidence level) but wind variables such as drift potential do not explain much (R^2 is 0.04 at maximum). This suggests that dune activity or stabilization in coastal dune systems is mainly controlled by vegetation cover, which is in turn affected by precipitation. Foredune textures can be a useful tool to predict foredune types in association with future climate change, and the optimal averaging period of precipitation for each bare sand area was seven years.

Made available in DSpace on 2014-07-29T15:32:05Z (GMT). No. of bitstreams: 1 Dissertacao_Mariana_N_Siqueira - pre textuais.pdf: 156975 bytes, checksum: da84656e45621079b20dac575d82ffb1 (MD5) Previous issue date: 2012-02-28 / Analisar os processos de fragmentação nos ecossistemas brasileiros através da abordagem geográfica da ecologia da paisagem demanda, prioritariamente, a utilização do sensoriamento remoto para geração dos dados espaciais de cobertura vegetal e de ocupação do solo, conhecidos como estrutura da paisagem. A sub-bacia hidrográfica do Rio das Garças, integrante da Alta Bacia do Rio Araguaia, em trabalhos anteriores, apresentou os menores índices de fragmentação e degradação em relação às demais subbacias. Por esse motivo, foi realizada análise detalhada da sua estrutura da paisagem através de imagens de satélite (LANDSAT-TM) e de índices descritores da paisagem, adotando uma comparação espacial em sucessão histórica dos anos de 1985, 1995, 2005 e 2010. Adotou-se o software FRAGSTATS, em função de sua complexidade e em consideração à diversidade e capacidade para desenvolver estimativas métricas dos polígonos que representavam os remanescentes do Cerrado e, portanto, auxiliar nas avaliações do estado de fragmentação da vegetação da área. Conclui-se que a sub-bacia estudada apresentou índice crescente de antropização no período, avançando sobre as áreas de vegetação natural, inclusive em áreas legalmente protegidas. Apesar disso, constatou-se que a formação savânica ainda é mais representativa do que as atividades antrópicas, porém, com o aumento da fragmentação muitos remanescentes tendem à homogeneidade e ficam sujeitos aos efeitos de borda. Para sua conservação é necessário reverter essa situação por meio do aumento da fiscalização ambiental, implantação de políticas públicas de conservação, preservação e uso sustentável, além de recuperação das áreas legalmente protegidas.

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

Hedonic pricing methods and GIS (Geographic Information Systems) were used to evaluate relationships between sale price of single family homes and landscape fragmentation and natural land cover. Spatial regression analyses found that sale prices increase as landscapes become less fragmented and the amount of natural land cover around a home increases. The projected growth in population and employment in the Richmond, Virginia region and subsequent increases in land development and landscape fragmentation presents a challenge to sustaining intact healthy ecosystems in the Richmond region. Spatial regression analyses helped illuminate how land cover patterns influence sale prices and landscape patterns that are economically and ecologically advantageous.

abstract: Context – Urbanization can have negative effects on bat habitat use through the loss and isolation of habitat even for volant bats. Yet, how bats respond to the changing landscape composition and configuration of urban environments remains poorly understood. Objective – This study examines the relationship between bat habitat use and landscape pattern across multiple scales in the Phoenix metropolitan region. My research explores how landscape composition and configuration affects bat activity, foraging activity, and species richness (response variables), and the distinct habitats that they use. Methods – I used a multi-scale landscape approach and acoustic monitoring data to create predictive models that identified the key predictor variables across multiple scales within the study area. I selected three scales with the intent of capturing the landscape, home range, and site scales, which may all be relevant for understanding bat habitat use. Results – Overall, class-level metrics and configuration metrics best explained bat habitat use for bat species associated with this urban setting. The extent and extensiveness of water (corresponding to small water bodies and watercourses) were the most important predictor variables across all response variables. Bat activity was predicted to be high in native vegetation remnants, and low in native vegetation at the city periphery. Foraging activity was predicted to be high in fine-scale land cover heterogeneity. Species richness was predicted to be high in golf courses, and low in commercial areas. Bat habitat use was affected by urban landscape pattern mainly at the landscape and site scale. Conclusions – My results suggested in hot arid urban landscapes water is a limiting factor for bats, even in urban landscapes where the availability of water may be greater than in outlying native desert habitat. Golf courses had the highest species richness, and included the detection of the uncommon pocketed free-tailed bat (Nyctinomops femorosaccus). Water cover types had the second highest species richness. Golf courses may serve as important stop-overs or refuges for rare or elusive bats. Urban waterways and golf courses are novel urban cover types that can serve as compliments to urban preserves, and other green spaces for bat conservation. / Dissertation/Thesis / Masters Thesis Biology 2016

This study analyzes the remaining suitable habitat of the one-horned rhinoceros, Rhinoceros unicornis, in Royal Chitwan National Park of Nepal. An April 2003 Landsat image was classified into eight land cover types: wetland, sand, water, mixed forest, sal forest, agriculture, settlement, and grassland. This image was converted into habitat suitability maps using cover, food, and water. The rhinoceros prefers grassland habitat with oxbow lakes and closed canopy during the monsoon season. Nominal values of five parameters were used to create a map of habitat suitability index. The map was categorized into four habitat classes: highly unsuitable, unsuitable, moderately suitable habitat, and suitable. Landscape metrics, patch metrics and class metrics associated with habitat were determined through the use of FRAGSTATS.