BACKGROUND: Francisella tularensis, the causative agent of tularemia, is a zoonotic agent that remains across much of the northern hemisphere, where it exists in enzootic cycles. In Ukraine, tularemia has a long history that suggests a need for sustained surveillance in natural foci. To better characterize the host-vector diversity and spatial distribution of tularemia, we analyzed historical data from field collections carried out from 1941 to 2008. FINDINGS: We analyzed the spatial-temporal distribution of bacterial isolates collected from field samples.

AIM: Our aim was to determine the role of environmental variables in explaining occurrence and abundance patterns of bumblebee (Bombus) species in a mountain region. We also used a historical dataset to compare historical and recent habitat suitability predictions for forecasting variations in species' responses to regional climate warming. LOCATION: The Cantabrian Range (Iberian Peninsula, south‐western Europe).

Nabis pseudoferus Remane and N. palifer Seidenstucker are predators that feed on a wide range of insect pests. To reveal their current potential habitats, the effects of climate change and their future distribution in various areas of Iran we used maximum entropy modeling (Maxent). To produce the models, samples were collected from 218 areas of Iran resulting in discovering 271 points where the nabids were found. The accuracy and performance of distribution models were also evaluated by the area under receiver operating characteristic curve and jack‐knife analysis.

A dam's construction always imposes some risks to the environment. In this article, the environmental risks of the Polrood dam, located in a northern province of Iran, during its construction phase, were identified, ranked, and evaluated. The risk factors were initially identified by Delphi questionnaire and then rated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Subsequently, the Analytical Hierarchy Process (AHP) was applied to classify the risk factors into four major categories, and Expert Choice software was used to weight them.

Mount Kilimanjaro is considered the highest free-standing mountain in the world and a symbol of the African continent. Steep slopes and high altitudes are on the backdrop of unique biophysical characteristics, in which changes between savannas, tropical cloud forests, and subalpine vegetation can be observed in relatively small distances. In the context of this complex and heterogeneous landscape, describing the interactions between climatic variables and ecosystem functions is crucial for understanding the drivers of biodiversity.

China’s economic development over the past three decades has been remarkable due to the establishment of the “Reform and Opening-up” program. Meanwhile, urbanization, one of the most intensive human activities, has significantly changed the land cover across China. Here we used remote sensing data and landscape metrics to explore the spatiotemporal patterns of urbanization in two large Chinese cities, Chengdu (1978–2010) and Chongqing (1976–2010).

The land surface models used in numerical weather forecasts and hydrological applications rely on the accuracy of land cover maps available from satellite remote sensing to simulate the energy and water balance at the surface of the Earth. While the impact of classification accuracy on land surface simulations has already been reported, little attention has been paid on the consequences of land cover map uncertainty driven by geolocation accuracy.

Human activities in many parts of the world have greatly changed the natural land cover. This study has been conducted on Pichavaram forest, south east coast of India, famous for its unique mangrove bio-diversity. The main objectives of this study were focused on monitoring land cover changes particularly for the mangrove forest in the Pichavaram area using multi-temporal Landsat images captured in the 1991, 2000, and 2009.

PURPOSE: Many Mediterranean drylands are characterized by strong erosion in headwater catchments, where connectivity processes play an important role in the redistribution of water and sediments. Sediment connectivity describes the ease with which sediment can move through a catchment. The spatial and temporal characterization of connectivity patterns in a catchment enables the estimation of sediment contribution and transfer paths. Apart from topography, vegetation cover is one of the main factors driving sediment connectivity.

Knowledge of the factors determining species distributions is essential for developing conservation strategies. Sandgrouse Pterocles alchata and P. orientalis are threatened in Spain, the stronghold of European populations. Spatial modelling was used to: (1) assess the relative importance of abiotic, anthropogenic and geographical factors in the distribution of both sandgrouse species, (2) determine the most important anthropogenic predictors for each species occurrence, and (3) identify areas where conservation efforts should be prioritized.

The effects of land use policy and socioeconomic changes on urban landscape dynamics have been increasingly investigated around the world, but our knowledge of the underlying processes of these effects is still inadequate for sustainably managing urban ecosystems.

Image segmentation is a basic and important procedure in object-based classification of remote-sensing data. This study presents an approach to multi-scale optimal segmentation (OS), given that single-scale segmentation may not be the most suitable approach to map a variety of land-cover types characterized by various spatial structures; it objectively measures the appropriate segmentation scale for each object at various scales and projects them onto a single layer. A 1.8 m spatial resolution Worldview-2 image was used to perform successive multi-scale segmentations.