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Climate is an important limiting factor of species' niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over their lifespan and within their geographical range which is unlikely captured by long-term means. Further, depending on their physiology, distinct groups of species cope with climate variability differently. Ectothermic species, which are directly dependent on the thermal environment are expected to show a different response to temporal or spatial variability in temperature than endothermic groups that can decouple their internal temperature from that of their surroundings. Here, we explore the degree to which spatial variability and long-term temporal variability in temperature and precipitation change niche estimates for ectothermic (730 amphibian, 1276 reptile), and endothermic (1961 mammal) species globally. We use three different species distribution modelling (SDM) algorithms to quantify the effect of spatial and temporal climate variability, based on global range maps of all species and climate data from 1979 to 2013. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). The mean performance of SDMs using only climatic means as predictors was TSS = 0.71 and AUC = 0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS = 0.74, mean AUC = 0.92), as does the inclusion of temporal variability (mean TSS = 0.80, mean AUC = 0.94). Including both spatial and temporal variability in SDMs shows the highest scores in AUC and TSS. Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in ectotherm groups such as amphibians and reptiles, while for endothermic mammals no such improvement was observed. These results indicate that including long term climate interannual climate variability into niche estimations matters most for ectothermic species that cannot decouple their physiology from the surrounding environment as endothermic species can.
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http://dx.doi.org/10.1038/s41598-023-39637-x | DOI Listing |
Health Commun
September 2025
College of Journalism and Communications, University of Florida.
As family communication is significantly related to individuals' health decision-making, it is crucial to tap into the power of this relationship for public health initiatives. The COVID-19 pandemic provided a ripe context in which to explore whether vaccination messaging could be tailored in such a way as to target specific family communication climates to encourage vaccine promotion among family members. Specifically, our study ( = 1,276) designed pro-vaccination messaging tailored based on two types of family communication styles.
View Article and Find Full Text PDFJ Environ Qual
September 2025
Department of Crop Science, Federal University of Santa Maria, Santa Maria, Brazil.
Brazil is the world's largest producer and exporter of soybeans (Glycine max L. Merr.).
View Article and Find Full Text PDFPest Manag Sci
September 2025
AgResearch Ltd, Tuhiraki, Lincoln, New Zealand.
Background: Conventional weed risk assessments (WRAs) are time-consuming and often constrained by species-specific data gaps. We present a validated, algorithmic alternative, the model, that integrates climatic suitability ( ), weed-related publication frequency (P) and global occurrence data ( ), using publicly available databases and artificial intelligence (AI)-assisted text screening with a large language model (LLM).
Results: The model was tested against independent weed hazard classifications for New Zealand and California.
Environ Monit Assess
September 2025
Department of Forestry Engineering, Federal University of Lavras (UFLA), Lavras, Minas Gerais State, Brazil.
In general, species on our planet are adapted to phenological patterns of vegetation, which are strongly influenced by various climatic and environmental factors that, when altered, can threaten biodiversity. Recent studies have utilized the spatiotemporal variability of vegetation to understand its dynamics, directly affecting biodiversity. Therefore, this research aimed to generate indices of temporal variability considering vegetation phenology and indices of spatial variability of vegetation to subsequently identify priority areas for biodiversity conservation in the Cerrado and Caatinga regions in Minas Gerais State, Brazil.
View Article and Find Full Text PDFEnviron Monit Assess
September 2025
Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Sleman, Yogyakarta, DIY, 55281, Indonesia.
Understanding seagrass dynamics is crucial for the effective management and conservation of seagrass meadows. However, such information remains limited for many regions worldwide, including Kuta Mandalika on Lombok Island, Indonesia. This rapidly developing coastal area, which is home to both tourism infrastructure and an international race circuit, hosts extensive seagrass meadows whose condition and dynamics require careful assessment.
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