International Journal of Biometeorology最新文献

Arctic warming is rapidly altering hydroclimatic conditions, yet its implications for the timing and reliability of terrestrial breeding environments remain poorly quantified. This study assesses how changes in temperature, snow dynamics, and rainfall extremes affect the snow-free reproductive window across Arctic tundra systems. We combined ERA5 reanalysis (1940–2024), daily output from ten CMIP6 Earth System Models, and long-term equilibrium simulations (400 years) from EC-Earth3 under present-day and doubled CO₂ conditions. Analyses focused on lowland tundra regions and quantified changes in snow cover, timing and duration of the productive period, and the frequency and magnitude of extreme rainfall events. Results show substantial Arctic warming under SSP2-4.5 (approximately 4.9 °C by 2081–2100 relative to 1995–2014), reductions in snowfall, and declining snow cover across the Arctic. Separately, the idealized EC-Earth equilibrium experiment, representing approximately 6 °C of global-mean warming relative to pre-industrial conditions in the 2×CO₂ state, shows how reproductive-season hydroclimate responds under strong sustained warming. Between the 1×CO₂ and 2×CO₂ equilibrium states, the snow-free period lengthens substantially due to earlier snowmelt (–28 days) and delayed snow onset (+36 days), while rainfall extremes intensify sharply. Extremely wet days become up to sixteen times more frequent, and rainfall events with a 100-year return period in the 1×CO₂ climate recur every 2–9 years in the 2×CO₂ climate, with particularly large relative changes in historically dry regions. These results show that a longer snow-free season under strong warming can coincide with substantially greater exposure to rainfall extremes, highlighting the importance of hydroclimatic extremes when assessing ecological responses to Arctic climate change.

The aim of the study is to examine the impact of climate change on plant phenology and the shift of phenological seasons. This paper considers phenophases of wild-growing plants in Poland at 36 observation stations over the past nearly 80 years. The analysis was conducted for two 15-year periods: a reference period (1946–1960) and a recent period (2007–2021), during which rapid global warming has been observed. This study applies the phenological calendar method. The results indicate shifts in the onset of successive phenological seasons in the recent period compared to the reference period, as well as in the duration of individual seasons. The most significant changes include (i) a shortening of winter due to an earlier onset of very early spring (by an average of 10 days across Poland); (ii) an advancement of subsequent seasons from early spring to early autumn, ranging from nearly 4 to more than 10 days, with the smallest shift observed for early autumn); (iii) a delay in the autumn onset by approximately 4 days; and (iv) a stable timing of winter onset throughout the entire study period. With regard to seasons length, in addition to the shortening of winter, an extension of the warmest phenological seasons was observed, with the greatest increase of 8 days for early autumn. Due to its location in the temperate transitional climate zone, Poland is characterized by high weather variability, which is reflected in substantial interannual variability in both the onset and duration of successive phenological seasons.

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This study was conducted to investigate the effects of climatic parameters—particularly the Physiological Equivalent Temperature (PET) index—on the risk of preterm birth (PB) in the city of Tehran. The present research is an ecological time-series study with daily data from March 2018 to March 2024. Data on preterm births, meteorological parameters from four synoptic stations, and air pollutants (PM₂.₅, PM₁₀, NO₂, SO₂, CO, O₃) from 13 air quality monitoring stations were collected. To analyze non-linear relationships and delayed effects, Distributed Lag Non-linear Models (DLNM) were used, controlling for air pollutants, long-term trends, and seasonality. Results showed the mean daily number of preterm births was 37.04. The mean PET was 19.25 °C, ranging from − 7.6 °C to 41.6 °C. Exposure to extreme cold (1st percentile PET = -1.7 °C) over a 0–30 day lag period significantly increased the cumulative relative risk of preterm birth (RR = 1.25; 95% CI: 1.02–1.52), with this effect primarily observed at lags of 20 to 30 days. In contrast, extreme heat (99th percentile PET = 39.1 °C) had no significant effect (RR = 0.94; 95% CI: 0.81–1.10). A significant negative correlation was found between PET and combustion-related pollutants, indicating the accumulation of these pollutants under cold conditions. In the semi-arid climate and polluted air of Tehran, extreme cold—not extreme heat—is a significant environmental risk factor for preterm birth. This finding highlights the necessity of developing early warning systems for cold waves, providing seasonal guidance to pregnant women, and ensuring equitable access to heating facilities.

Extreme cold profoundly shapes health, livelihoods, and social well-being in northern communities, yet research on social vulnerability to such conditions remains limited. This study provides a framework for integrating social, demographic, infrastructural, and institutional dimensions into an assessment of vulnerability to extreme cold in northern Norway. It utilizes the Extremely Cold Social Vulnerability Index (ECSVI, ranging from 0 to 1) derived from the Universal Thermal Climate Index (UTCI), and indices of social sensitivity and social adaptivity for 83 communities across Nordland, Troms, and Finnmark in Northern Norway during 2000–2019. Finnmark experienced substantially greater cold exposure than Nordland and Troms, although annual exposure to UTCI < − 27 °C declined from 1011 to 883 h between 2000 and 2009 and 2010–2019. ECSVI showed marked regional differences, with Finnmark remaining the most vulnerable county (0.69 and 0.67 in two decades), compared with substantially lower values in Troms and Nordland. At the community level, Social Sensitivity ranged from 0.27 to 0.61 and Social Adaptivity from 0.39 to 0.64. Low-income households (r = 0.64), foreign-born population (r = 0.62), and income inequality (r = 0.60) showed the strongest positive associations with Social Sensitivity. Infrastructure metrics such as connectivity to the municipal water supply (r = 0.61) and roads with street lighting (r = 0.46) were the highest correlators with Social Adaptivity. Overall, the results demonstrate that vulnerability to extreme cold reflects the combined effects of climatic exposure and socioeconomic conditions, while stronger adaptive capacity can reduce vulnerability. By quantifying vulnerability across and within regions, this study offers actionable insights for targeted adaptation and resilience planning.

Balneotherapy (BT) is widely used as a non-pharmacological intervention for osteoarthritis (OA); however, potential sex differences in treatment response remain poorly understood. This scoping review mapped randomized controlled trials (RCTs) of BT in OA to describe (i) how participants’ sex was reported, (ii) whether sex-stratified or sex-by-treatment interaction analyses were performed and (iii) the sex-related findings of such analyses. Twenty-two publications, derived from 21 distinct RCTs, were included. Sex distribution was reported for 20 trials, including 2,211 participants (594 males and 1,617 females; 73.1% female). The greatest imbalance was observed in knee OA trials (497 males vs. 1,216 females). Overall, BT was associated with reduced pain, improved physical function and enhanced quality of life in predominantly female samples. However, only one trial formally tested sex as an effect modifier, reporting significant treatment × sex interactions for pain, stiffness, physical function and quality of life, and one further trial enrolled women only. No other trial, including those with a relatively balanced sex distribution, reported outcomes separately for women and men. Therefore, the available evidence is insufficient to establish whether sex modifies the clinical response to BT. Sex-related differences in thermoregulation, nociceptive processing and immune modulation provide a biologically plausible, but as yet untested, rationale for such effect modification. Future BT trials should report outcomes separately for women and men and include pre-specified, adequately powered sex-by-treatment interaction analyses.

Understanding plant phenology patterns under global warming is important because they influence many processes, from specific dynamics, such as species interactions, to ecosystem functions, for instance, carbon uptake. Studying phenological changes requires long-term data covering the species’ distribution. However, such data is typically only locally available and restricted to certain phenophases, e.g., flowering. One common alternative is to use the space-for-time substitution (SFTS) approach. However, this method relies on the rarely tested space-time equivalence assumption. In this study, we assessed the space-time equivalence of flowering phenology by comparing its response to temperature along temporal and spatial gradients. Furthermore, we evaluated the influence of recent climate change on this assumption, analyzing the responses between 1950-1985 and 1986–2022. We used mean annual temperature data from the Era5-Land product and long-term flowering onset records of 23 herbaceous and dwarf shrub species from the PEP725 database. We found that flowering responses to temperature were mostly negative, and the responses were 67% similar between both gradients. However, the response variation along the spatial gradient did not represent the total variation observed in the temporal one. The similarity in responses between both gradients was higher (73.6%) in warmer decades (73.6% in 1986–2022 compared to 65.8% in 1950–1985), suggesting that high temperatures may synchronize phenology across space and time. We conclude that the SFTS predicts the phenological response direction to the temperature correctly. However, we recommend considering that the use of spatial gradients may not reveal the full expected response variation to temperature in a temporal gradient, especially when making general conclusions from species-specific inferences.

Climate conditions can significantly affect plant dormancy and growing season, impacting crop development and its productivity. Temperature is considered the primary driver of grapevine phenology, with endodormancy and ecodormancy largely regulated by chilling and forcing accumulations, respectively. Nevertheless, additional climatic factors, such as precipitation, radiation and atmospheric circulation patterns, may also contribute and regulate variability of different phenological phases. As hotspot of climate change, Mediterranean regions are witnessing negative compounding effects by enhanced warming and changes in precipitation patterns on crop systems and linked agro-industry. Among these, viticulture is a particularly relevant economic crop in Mediterranean regions. This research aims to assess some conventional phenological modeling approaches to project several phenological stages of grapevine in Sardinia (Italy), comparing the results to regression-based stepwise Statistical Learning that can potentially account for effect of several climate variables. Combined models (i.e. Chilling Hours-Growing Degree Hours) improve prediction of budburst phenological timing (RMSEs: 7 days) in relation to more complex models (i.e., PhenoFlex). The Growing Degree Days model was more accurate than complex phenological models in predicting blooming and veraison (RMSEs of 6 and 4 days, respectively). The regression-based statistical learning approach achieved phenological prediction performances comparable to the best of the conventional models (RMSEs: 4–7 days). Regression-based statistical learning approach was able to infer contribution of several climate variables on grapevine phenology, at a larger seasonal scale. Implementing both modeling approaches showed similar spatial patterns, except for budburst phase which indicated earlier timings over mountainous regions through regression-based statistical learning contrary to conventional model, highlighting the influence of maximum and minimum temperatures from previous year.

Mountainous regions hold considerable wellness tourism potential, backed by abundant ecological and climatic resources. Yet research has largely focused on spatial zoning rather than linking spatial patterns to the economic valuation of ecological resources. This gap constrains evidence-based planning and hinders effective industrial conversion of ecological products. This study therefore develops an integrated framework that combines citywide wellness tourism resource zoning with Gross Ecosystem Product (GEP)-based economic valuation, using Chongqing, China, as a case study. We constructed a 13-indicator evaluation system encompassing natural resources and supporting facilities, integrating meteorological observations, satellite remote sensing products, and socio-economic data. The mismatch was quantified with a standardized spatial mismatch index. Based on zoning outputs, the Three Gorges Cool Capital—a high-altitude summer-retreat area in northeastern Chongqing—was selected for value accounting across regulating, cultural, and wellness services. The results reveal a pronounced spatial mismatch: high-quality natural wellness resources concentrate in the northeastern mountainous region, whereas supporting facilities cluster in the central-western urban corridor. Resource-leading mismatch covers 57.0% of the municipal area, whereas facility-leading mismatch covers 21.5%. In 2023, the total economic value of summer-retreat wellness climate resources in the Three Gorges Cool Capital reached CNY 15.454 billion, with regulating services contributing 85.7%, cultural services 9.7%, and wellness services 4.6%. Notably, this ecological value exceeded local GDP by more than fourfold, underscoring high ecological endowment but insufficient industrial conversion. These findings provide a scientific basis for differentiated wellness tourism planning, targeted infrastructure investment, and ecological product value realization in mountainous cities worldwide.

Climate change has intensified thermal challenges in livestock production systems, reinforcing the need to understand adaptive mechanisms in locally adapted breeds. This study aimed to characterize the seasonal adaptive profile of North Tinerfeña goats, an autochthonous breed from the Canary Islands. Thirty adult non-pregnant female goats were evaluated under standardized management conditions. Repeated measurements of rectal temperature (RT), respiratory rate (RR), and coat surface temperature (CST) were obtained twice daily, in the morning and afternoon, throughout a one-year study period encompassing winter and summer. Coat characteristics (coat thickness [CT], hair length [HL], hair diameter [HD], and hair angle) were measured once per day during winter and summer. Physiological variables were significantly affected by season and period of the day (p < 0.001), with a significant season × period interaction for RR and CST (p < 0.01). Coat traits showed pronounced seasonal variation, with CT significantly greater in winter (p < 0.001) and HL significantly greater in summer (p < 0.001), whereas HD did not differ between seasons (p > 0.05). Multivariate analyses revealed distinct seasonal adaptive patterns, with CT and HL identified as the main discriminant variables between winter and summer (discriminant analysis, p < 0.001). Decision tree (CHAID) analysis identified coat thickness as the primary classifier of seasonal condition, with a threshold value of CT ≤ 8.7 mm predominantly characterizing summer (p < 0.001). These findings demonstrate that North Tinerfeña goats rely on integrated and season-dependent thermoregulatory strategies, in which morphological coat traits predominate during winter, while rapid and sensitive physiological responses are preferentially activated during summer to maintain homeothermy. This study provides novel phenotypic evidence of local adaptation and highlights the potential use of objective morphological thresholds, such as coat thickness, combined with simple physiological indicators, to support management and conservation strategies for insular goat breeds under climate change scenarios.