Can eDNA Replace Trawl Surveys for Estuarine Species Distribution Modeling: Insights From Collichthys lucidus in the Yangtze River Estuary by Xiaoyu Geng, Wei Tang, Jianhui Wu, Chunxia Gao, Xuefang Wang

“…The results showed that although eDNA and trawl data produced similar performance metrics (AUC, Kappa, RMSE), eDNA‐based models exhibited weaker spatial discrimination and inconsistent seasonal predictions, misidentifying offshore areas as unsuitable under certain conditions. …”
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Environmental and geostatistical modelling of soil properties toward precision agriculture by Tobore Anthony, Ugonna Nkwunonwo, Anoke Emmanuel, Oyerinde Ganiyu

“…At the same time, NDVI, and EVI highlight a significant decrease in vegetation cover, respectively. The modelling of soil properties based on cross-validation showed that soil properties in the studied area ranged between strong (< 0.25) and weak (0.25 to 0.75) spatial autocorrelations. …”
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TEMPERATURE AND PRECIPITATION AS PREDICTORS OF SPECIES RICHNESS IN NORTHERN ANDEAN AMPHIBIANS FROM COLOMBIA by Ortiz-Yusty Carlos Eduardo, Páez Vivian, Zapata Fernando

“…<div>Our objective was to explore the spatial distribution patterns of amphibian species</div><div>richness in Antioquia, as model for the tropical Andes, and determine how annual</div><div>mean temperature, annual precipitation, and elevation range influence it. …”
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Multi-scenario simulation of carbon stock and landscape ecological risk changes in Jinpu new area and analysis of spatial conflict relationships by Jin Peng Wang, Li Wang, Peng Du

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Enhancing Range Use in Free-Range Laying Hen Systems: The Impact of Vegetation Cover over Time by Markus Pacher-Deutsch, Philipp Meyer, Harald Meimberg, Martin Gierus

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Global multi-ensemble approach for assessing the invasion potential of tropical fire ant in South Korea by Dae-hyeon Byeon, Wang-Hee Lee

“…The highest true skill statistics among the eight ensemble models was 0.77, showing potential distribution in North America, South America, South Asia, Southeast Asia, and Australia. …”
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Spatial pattern of the Chinese economy and spatial heterogeneity of its influential factors: An empirical study based on nighttime lighting data by Yifeng Hai, Yuanjie Deng, Hang Chen, Dingdi Jize, Ji Luo

“…Third, spatial correlation shows spatial positive correlation, the degree of which is increasing, with strong spatial heterogeneity and regional agglomeration. …”
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Spatial correlations of charm and anticharm quarks at hadronisation by Marek Gazdzicki, Daniel Kikoła, Ivan Pidhurskyi, Leonardo Tinti

“…We introduce a method to correct the measured joint momentum distribution for smearing effects caused by hadronisation, making the results directly sensitive to spatial correlations. …”
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Characterizing, predicting, and mapping of soil spatial variability in Gharb El-Mawhoub area of Dakhla Oasis using geostatistics and GIS approaches by Salman Selmy, Salah Abd El-Aziz, Ahmed El-Desoky, Moatez El-Sayed

“…Following data normalization, classical and geostatistical approaches have been performed to characterize soil parameters and their spatial distribution. Semi-variogram models were used to quantify the spatial variation of physicochemical properties, and the ordinary kriging technique was applied to generate the respective maps. …”
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Spatial and temporal evolution of the coupling of new urbanization and ecological efficiency and its influencing factors: 84 cities in Western China by Dalai Ma, Zuman Guo, Jiawei Zhang, Bitan An, Fengtai Zhang, Yin Yan, Ruonan Chang

“…By the end of the observation period, all cities in the study area—except Chongqing—had reached the bare coordination level or higher. Spatial evolution reveals a significant and stable positive agglomeration effect in the spatial distribution of CCD. …”
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Fine-Scale Environmental Heterogeneity Drives Intra- and Inter-Site Variation in <i>Taraxacum officinale</i> Flowering Phenology by Myung-Hyun Kim, Young-Ju Oh

“…We applied the nlstimedist package in R to model flowering distributions and to estimate key phenological metrics including flowering onset (5%), peak (50%), and end (95%). …”
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Uncovering the Uncertainties and Variability of Travel Time and Fuel Consumption Using Floating Car Data: A Case Study in Wuhan by Wenxin Teng, Fei Liu, Jianbing Yang, Chaoyang Shi, Yunfei Zhang, Fuqiang Wang

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Improving Distribution Prediction by Integrating Expert Range Maps and Opportunistic Occurrences: Evidence From Japanese Sea Cucumber by Bingqing Xiao, Songxi Yuan, Ákos Bede‐Fazekas, Jinxin Zhou, Xingyu Song, Qiang Lin, Lei Cui, Zhixin Zhang

“…Our results showed that integrating an expert range map into the opportunistic occurrence model improved distribution prediction by avoiding overprediction in the south of the dispersal barrier for this species. …”
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Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence by Sai Li, Boyang Jiang, Hongying Zhou, Sifu Yang, Liu Yang, Yupeng Hong

“…The ICRPI model, incorporating CD68+, CD68 + PD-L1+, and spatial variables, effectively stratified patients into high- and low-risk groups, with high-risk patients showing significantly poorer OS. …”
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Vegetation Structure and Distribution Across Scales in a Large Metropolitan Area: Case Study of Austin MSA, Texas, USA by Raihan Jamil, Jason P. Julian, Meredith K. Steele

“…The spatial distribution of vegetation across metropolitan areas is important for wildlife habitat, air quality, heat mitigation, recreation, and other ecosystem services. …”
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A Spatial Estimation of Groundwater Recharge in Southern Ontario, Canada by Abdelhaleem Khader

“…PRMS results will be used in the groundwater monitoring network design because they are spatially distributed, and because PRMS conceptual model better represents the physical processes.…”
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Unveiling the Impact of Climatic Factors on the Distribution Patterns of <i>Caragana</i> spp. in China’s Three Northern Regions by Weiwei Zhao, Yujia Liu, Yanxia Li, Chunjing Zou, Hideyuki Shimizu

“…The main results showed that (1) compared to other environmental factors, climate is the key factor affecting the distribution of <i>Caragana</i> spp. (2) The current distribution centroid of <i>Caragana</i> spp. is located in Alxa Left Banner, Inner Mongolia. …”
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Exploring the effects of climatic and environmental heterogeneity on the spatial activity of Patagonian bats by Analía Laura Giménez, Marta Gladys Grech, Óscar De Paz

“…Using generalized linear mixed-effects models (GLMMs), we analyzed how climatic and environmental variables influenced the spatial activity of Patagonian bat phonic groups. …”
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Mapping the distribution of pine wilt disease based on selected machine learning algorithms and high-resolution Gaofen-2/7 remote sensing by Yifan Wang, Xiaocheng Zhou, Chongcheng Chen, Xiaoqin Wang, Hao Wu, Fanglin Tan, Ruijiao Wu

“…Existing research has struggled to accurately capture the large-scale spatial distribution of the PWD, particularly for precise extraction at provincial level. …”
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A novel ensemble learning algorithm integrating WRF-CMAQ and downscaling models for hourly estimation of regional air pollution along with vegetation exposure risk detection by Peng Zhou, Jieming Chou, Shan Ye, Leiku Yang, Mengting Sun, Pengao Li, Huanpeng Wang, Jie Luo, Zhaoxiang Cao, Qian Yao, Hao Zhang, Hongze Pei

“…Furthermore, the spatial distribution of composite pollution events was significantly influenced by topography and regional meteorological conditions, with pollutant concentrations being notably higher in the foothill areas. …”
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