The ecological distribution of Cytauxzoon felis, an often-fatal tick-borne apicomplexan that infects domestic cats, has not been evaluated or identified despite its continued emergence. Infection of C. felis is characterized by lethargy, icterus, fever, anorexia, anemia, and death. The natural vertebrate reservoir of C. felis is the bobcat (Lynx rufus). To determine the possible distribution of C. felis in three states where infection is common (Oklahoma, Missouri, and Arkansas), two separate approaches to ecological niche modeling were implemented.

Characterizing and quantifying distributions of shrubland ecosystem components is one of the major challenges for monitoring shrubland vegetation cover change across the United States. A new approach has been developed to quantify shrubland components as fractional products within National Land Cover Database (NLCD). This approach uses remote sensing data and regression tree models to estimate the fractional cover of shrubland ecosystem components.

Although recent climatic warming has markedly increased fire activity in many biomes, this trend is spatially heterogeneous. Understanding the patterns and controls of this heterogeneity is important for anticipating future fire regime shifts at regional scales and for developing land management policies. To assess climatic and land cover controls on boreal forest fire regimes, we conducted macroscopic‐charcoal analysis of sediment cores and GIS analysis of landscape variation in south‐central Alaska, USA.

We attempt to describe and explain the peculiarly restricted distribution of the globally threatened Ethiopian Bush-crow Zavattariornis stresemanni. At a regional scale, models containing only correlates of land cover suggested a far wider distribution of suitable habitat in north-east Africa than the area actually occupied. However, models including only climate variables predicted the known distribution almost perfectly, and suggested that the species’ area of occupancy is delimited by a pocket of climate that is cooler, dryer and more seasonal than surrounding areas.

The Ethiopian Rift Valley is a dry land zone where for a long time pastoral communities have made their living from acacia-based woodlands. But many pastoralists have changed from a pastoral way of life to mixed farming over time. The aim of this study was to evaluate land-use and land cover (LULC) changes in the Central Rift Valley dry lands of Ethiopia, and determine the role of drought vulnerability as a driver. A combination of GIS/remote sensing techniques, drought vulnerability analyses, field observation and surveying were employed.

Land-cover proportions of mixed pixels can be predicted using soft classification. From the land-cover proportions, a hard land-cover map can be predicted at sub-pixel spatial resolution using super-resolution mapping techniques. It has been demonstrated that the Hopfield Neural Network (HNN) provides a suitable method for super-resolution mapping. To increase the detail and accuracy of the sub-pixel land-cover map, supplementary information at an intermediate spatial resolution can be used.

Widespread anthropogenic land-cover change over the last five centuries has influenced the global climate system through both biogeochemical and biophysical processes. Models indicate that warming from carbon emissions associated with land cover conversion have been partially offset if not outweighed by cooling from elevated albedo, but considerable uncertainty remains partly because of uncertainty in model treatments of albedo.

Over the course of 1681 hours between May 5 and September 30, 2006, air temperatures measured at the 1.5-m height at seven sites in and near the city of Baltimore, MD were used to empirically model Δ [Formula: see text] R₋ₚ , the difference in air temperature between a site in downtown Baltimore and the six other sites. Variables in the prediction equation included difference between the downtown reference and each of the other sites in upwind tree cover and impervious cover as obtained from 10-m resolution geographic information system (GIS) data.

Stream fish distributions are commonly linked to environmental disturbances affecting terrestrial landscapes. In Great Plains prairie streams, the independent and interactive effects of watershed impoundments and land cover changes remain poorly understood despite their prevalence and assumed contribution to declining stream fish diversity.

We describe a process for developing an index of biotic integrity (IBI) for resident fish communities in an ecoregion that exhibits low natural species richness. From 1990 to 2006, fish community samples were collected by the North Carolina Division of Water Quality (NCDWQ) at 36 sample sites in the Cape Fear, Lumber, and Yadkin river basins within the Sandhills region of North Carolina. The NCDWQ does not currently have an IBI capable of distinguishing significant differences between reference and non-reference streams.

Texture in high resolution satellite images requires substantial improvement in the conventional segmentation algorithms. The use of wavelet packet transforms for texture analysis and image classification of high spatial resolution LISS IV imagery provide more details about the urban areas. This paper analyses the performance of a combination of Wavelet Packet Statistical Features (WPSFs) and Wavelet Packet Co-occurrence Features (WPCFs) for the classification of LISS IV images. The classification accuracy per pixel is improved in this paper by varying the window size.

A desirable feature of a global sampling design for estimating forest cover change based on satellite imagery is the ability to adapt the design to obtain precise regional estimates, where a region may be a country, state, province, or conservation area. A sampling design stratified by an auxiliary variable correlated with forest cover change has this adaptability. A global stratified random sample can be augmented by additional sample units within a region selected by the same stratified protocol and the resulting sample constitutes a stratified random sample of the region.