Assessing climate niche similarity between persian fallow deer (Dama mesopotamica) areas in Iran.

The Persian fallow deer or Mesopotamian fallow Deer (Dama mesopotamica, Brook 1875), a species of significant ecological importance, had faced the threat of extinction in Iran. One conservation strategy involved the translocation of Persian deer to enclosed areas across Iran, where they were afforded protection from external threats and provided with essential care by human caretakers. While human caretakers diligently attend to their needs and mitigate external threats, climate variables may now become critical factors affecting population dynamics in enclosed areas. This study aims to assess the similarity in climate niches between the original area (Dez and Karkheh) of the Persian deer species and 11 newly enclosed areas. To achieve this, we employed climate data and ecological niche modeling (ENM) techniques to assess the variations in climate among 12 areas. We utilized the environmental equivalency test to determine whether the environmental spaces of area pairs exhibit significant differences and whether these spaces are interchangeable. Extrapolation analyses were also constructed in the next steps to explore climatic conditions in original fallow deer habitats that are non-analogous to those in other parts of Iran. Our results reveal significant disparities in climate conditions between the original and all translocated areas. Based on observations of population growth in specific enclosed areas where translocated deer populations have thrived, we hypothesize that the species may demonstrate a non-equilibrium distribution in Iran. Consequently, these new areas could potentially be regarded as part of the species' potential climate niche. Extrapolation analysis showed that for a significant portion of Iran, extrapolation predictions are highly uncertain and potentially unreliable for the translocation of Persian fallow deer. However, the primary objective of translocation efforts remains the establishment of self-sustaining populations of Persian deer capable of thriving in natural areas beyond enclosed areas, thus ensuring their long-term survival and contributing to preservation efforts. Evaluating the success of newly translocated species requires additional time, with varying levels of success observed. In cases where the growth rate of the species in certain enclosed areas falls below expectations, it is prudent to consider climate variables that may contribute to population declines. Furthermore, for future translocations, we recommend selecting areas with climate similarities to regions where the species has demonstrated growth rates.

Energy-based corridor identification for mammals between protected areas in Iran.

Body mass plays a crucial role in determining the mass-specific energy expenditure during terrestrial locomotion across diverse animal taxa, affecting locomotion patterns. The energy landscape concept offers a framework to explore the relationship between landscape characteristics and energy expenditure, enhancing our understanding of animal movement. Although the energy landscape approach solely considers the topographic obstacles faced by animals, its suitability compared to previous methods for constructing resistance maps and delineating corridors has not been comprehensively examined. In this study, we utilized the enerscape R package to generate resistance maps in kilocalories (kcal) by incorporating digital elevation models (DEMs) and body size data (kg). We assigned body sizes ranging from 0.5 to 100 kg to encompass a wide range of small and large mammals in Iran, adjusting maximum dispersal distances accordingly from 50 to 200 km. By analyzing these scenarios, we produced four resistance maps for each body size. Next, we identified potential corridors between terrestrial protected areas in Iran using the Linkage Mapper toolkit and examined barriers and pinch-points along these paths. Our study revealed significant findings regarding the shared corridors between small and large mammals in Iran's landscape. Despite their differing body sizes and energy requirements, many corridors were found to be utilized by both small and large mammal species. For example, we identified 206 corridors for mammals weighing 500 g, which were also recognized as the least-cost paths for 100 kg mammals. Thus, embracing a comprehensive method in resistance map creation, one that incorporates species-specific traits and human infrastructure becomes imperative for accurately identifying least-cost paths and consequently pinpointing pinch points and barriers.

Analysis of long-term spatio-temporal changes of plateau urban wetland reveals the response mechanisms of climate and human activities: A case study from Dianchi Lake Basin 1993-2020.

Wetlands serve many functions, including conserving water, providing habitats for animals and plants, and regulating climate change. Their unique ecological effects on the natural environment are indispensable in the whole ecosystem. Dianchi Lake Basin is located in Yunnan-Guizhou Plateau, China, and mainly in Kunming. It is a typical plateau urban wetland area. Based on spatio-temporal hotspot mining, spatio-temporal geographically weighted regression, and adaptive multidimensional grey prediction, we conducted correlation analyses of the wetland changes in Dianchi Lake Basin from 1993 to 2020 under the influence of human activities and natural conditions. The results show that (1) the active wetland change zone in Dianchi Lake Basin is mainly located around Dianchi Lake, and (2) the wetlands in some areas on the north and south of Dianchi Lake declined in the early 21st century, but under the protection policy in recent years, the wetlands in these areas gradually recovered. Meanwhile, the wetlands in most areas around Dianchi Lake showed a significant growth trend from 2018 to 2020. The results suggest that the wetland change in Dianchi Lake Basin is mainly related to the urbanization of Kunming, and it can be divided into five regions (strong negative correlation, weak negative correlation, weak correlation, weak positive correlation, and strong positive correlation) according to the different correlation of human activity intensity, among which the main factors affected by nature are different, but they are all related to temperature. This study shows that, although wetlands in plateau cities can be properly restored under proper protection, wetland protection should be kept in step with the development of plateau cities to support sustainable urban development and carbon neutrality.

Integration of Moran's I, geographically weighted regression (GWR), and ordinary least square (OLS) models in spatiotemporal modeling of COVID-19 outbreak in Qom and Mazandaran Provinces, Iran.

Globally, the COVID-19 pandemic is a top-level public health concern. This paper attempts to identify the COVID-19 pandemic in Qom and Mazandaran provinces, Iran using spatial analysis approaches. This study was based on secondary data of confirmed cases and deaths from February 3, 2020, to late October 2021, in two Qom and Mazandaran provinces from hospitals and the website of the National Institute of Health. In this paper, three geographical models in ArcGIS 10.8.1 were utilized to analyze and evaluate COVID-19, including geographic weight regression (GWR), ordinary least squares (OLS), and spatial autocorrelation (Moran I). The results from this study indicate that the rate of scattering of confirmed cases for Qom province for the period was 44.25%, while the rate of dispersal of the deaths was 4.34%. Based on the GWR and OLS model, Moran's statistics demonstrated that confirmed cases, deaths, and recovered followed a clustering pattern during the study period. Moran's Z-score for all three indicators of confirmed cases, deaths, and recovered was confirmed to be greater than 2.5 (95% confidence level) for both GWR and OLS models. The spatial distribution of indicators of confirmed cases, deaths, and recovered based on the GWR model has been more scattered in the northwestern and southwestern cities of Qom province. Whereas the spatial distribution of the recoveries of the COVID-19 pandemic in Qom province was 61.7%, the central regions of this province had the highest spread of recoveries. The spatial spread of the COVID-19 pandemic from February 3, 2020, to October 2021 in Mazandaran province was 35.57%, of which 2.61% died, according to information published by the COVID-19 pandemic headquarters. Most confirmed cases and deaths are scattered in the north of this province. The ordinary least squares model results showed that the spatial dispersion of recovered people from the COVID-19 pandemic is more significant in the central and southern regions of Mazandaran province. The Z-score for the deaths Index is more significant than 14.314. The results obtained from this study and the information published by the National Headquarters for the fight against the COVID-19 pandemic showed that tourism and pilgrimages are possible factors for the spatial distribution of the COVID-19 pandemic in Qom and Mazandaran provinces. The spatial information obtained from these modeling approaches could provide general insights to authorities and researchers for further targeted investigations and policies in similar circumcises.

Monitoring, Mapping, and Modeling Spatial-Temporal Patterns of PM2.5 for Improved Understanding of Air Pollution Dynamics Using Portable Sensing Technologies.

Fine particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) is highly variable in space and time. In this study, the dynamics of PM2.5 concentrations were mapped at high spatio-temporal resolutions using bicycle-based, mobile measures on a university campus. Significant diurnal and daily variations were revealed over the two-week survey, with the PM2.5 concentration peaking during the evening rush hours. A range of predictor variables that have been proven useful in estimating the pollution level was derived from Geographic Information System, high-resolution airborne images, and Light Detection and Ranging (LiDAR) datasets. Considering the complex interplay among landscape, wind, and air pollution, variables influencing the PM2.5 dynamics were quantified under a new wind wedge-based system that incorporates wind effects. Panel data analysis models identified eight natural and built environment variables as the most significant determinants of local-scale air quality (including four meteorological factors, distance to major roads, vegetation footprint, and building and vegetation height). The higher significance level of variables calculated using the wind wedge system as compared to the conventional circular buffer highlights the importance of incorporating the relative position of emission sources and receptors in modeling.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.