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Stable isotopes in wood cellulose of tree rings provide a high-resolution record of environmental conditions, yet intra-annual analysis of carbon and oxygen isotopes and their associations with physiological responses to seasonal environmental changes are still lacking. We analyzed tree-ring stable carbon (δ C) and oxygen (δ O) isotope variations in the earlywood (EW) and latewood (LW) of pines from a secondary forest ( ) and from a natural forest ( ) in southwestern China. There was no significant difference between δ C and δ C in , while δ C was significantly higher than δ C in . For both and , δ C was highly correlated with previous year's δ C , indicating a strong carbon carry-over effect for both pines. The intrinsic water use efficiency (iWUE) in the earlywood of was slightly higher than that of , and iWUE of both pine species showed an increasing trend, but at a considerably higher rate in . Respective δ C and δ C series were not correlated between the two pine species and could be influenced by local environmental factors. δ C of was positively correlated with July to September monthly mean temperature (MMT), whereas δ C of was positively correlated with February to May MMT. Respective δ O and δ O in were positively correlated with those in , indicating a strong common climatic forcing in δ O for both pine species. δ O of both pine species was negatively correlated with May relative humidity and δ O in was negatively correlated with May precipitation, whereas δ O in both pine species was negatively correlated with precipitation during autumn months, showing a high potential for climate reconstruction. Our results reveal slightly higher iWUE in natural forest pine species than in secondary forest pine species, and separating earlywood and latewood of for δ O analyses could provide seasonally distinct climate signals in southwestern China.

[This corrects the article on p. 2050 in vol. 7, PMID: 28119725.].

Iraq, the land of two rivers, has a history that extends back millennia and is the subject of much archaeological research. However, little environmental research has been carried out, and as such relatively little is known about the interaction between Iraq’s vegetation and climate. This research serves to fill this knowledge gap by investigating the relationship between the Normalized Difference Vegetation Index (NDVI) and two climatic factors (precipitation and air temperature) over the last decade. The precipitation and air temperature datasets are from the Water and Global Change Forcing Data ERA-Interim (WFDEI), and the NDVI dataset was extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m spatial resolution and 16 day temporal resolution. Three different climatic regions in Iraq, Sulaymaniyah, Wasit, and Basrah, were selected for the period of 2001–2015. This is the first study to compare these regions in Iraq, and one of only a few investigating vegetation’s relationship with multiple climatic factors, including precipitation and air temperature, particularly in a semi-arid region. The interannual, intra-annual and seasonal variability for each region is analysed to compare the different responses of vegetation growth to climatic factors. Correlations between NDVI and climatic factors are also included. Plotting annual cycles of NDVI and precipitation reveals a coherent onset, fluctuation (peak and decline), with a time lag of 4 months for Sulaymaniyah and Wasit (while for the Basrah region, high temperatures and a short rainy season was observed). The correlation coefficients between NDVI and precipitation are relatively high, especially in Sulaymaniyah, and the largest positive correlation was (0.8635) with a time lag of 4 months. The phenological transition points range between 3 and 4 month time lag; this corresponds to the duration of maturity of the vegetation. However, when correlated with air temperature, NDVI experiences an inverse relationship, although not as strong as that of NDVI and precipitation; the highest negative correlation was observed in Wasit with a time lag of 2 months (− 0.7562). The results showed that there is a similarity between temporal patterns of NDVI and precipitation. This similarity is stronger than that of NDVI and air temperature, so it can be concluded that NDVI is a sensitive indicator of the inter-annual variability of precipitation and that precipitation constitutes the primary factor in germination while the air temperature acts with a lesser effect.

The climate of the Arabian Peninsula is characterized by significant spatial and temporal variations, due to its complex topography and the large-scale atmospheric circulation. Furthermore, the role of dust in the formation of regional climate is considered to be crucial. In this work, the regional climatology for the Arabian Peninsula has been studied by employing a high resolution state of the art atmospheric model that included sophisticated physical parameterization schemes and online treatment of natural aerosol particles. The simulations covered a 30-year period (1986–2015) with a temporal resolution of 3 h and a spatial distance of 9 km. The main focus was given to the spatial and temporal variations of mean temperature and temperature extremes, wind speed and direction, and relative humidity. The results were evaluated using in situ measurements indicating a good agreement. An examination of possible climatic changes during the present climate was also performed through a comprehensive analysis of the trends of mean temperature and temperature extremes. The statistical significant trend values were overall positive and increased over the northwestern parts of the examined area. Similar spatial distributions were found for the daily minimum and maximum temperatures. Higher positive values emerged for the daily maxima.

Lake surface water temperature (LSWT) is an important parameter with which to assess aquatic ecosystems and to study the lake’s response to climate change. The AVHRR archive of the University of Bern offers great potential to derive consistent LSWT data suited for the study of climate change and lake dynamics. To derive such a dataset, challenges such as orbit drift correction, non-water pixel detection, and homogenization had to be solved. The result is a dataset covering over 3.5 decades of spatial LSWT data for 26 European lakes. The validation against in-situ temperature data at 19 locations showed an uncertainty between ±0.8 K and ±2.0 K (standard deviation), depending on locations of the lakes. The long-term robustness of the dataset was confirmed by comparing in-situ and satellite derived temperature trends, which showed no significant difference. The final trend analysis showed significant LSWT warming trends at all locations (0.2 K/decade to 0.8 K/decade). A gradient of increasing trends from south-west to north-east of Europe was revealed. The strong intra-annual variability of trends indicates that single seasonal trends do not well represent the response of a lake to climate change, e.g., autumn trends are dominant in the north of Europe, whereas winter trends are dominant in the south. Intra-lake variability of trends indicates that trends at single in-situ stations do not necessarily represent the lake’s response. The LSWT dataset generated for this study gives some new and interesting insights into the response of European lakes to climate change during the last 36 years (1981–2016).

France has a latitudinal range for the expansion of Aedes albopictus invasive populations that is not yet completely colonized providing a critical opportunity to address key invasion processes. We propose a spatio-temporal model (DISTIGRI) to describe and predict current and future expansions at intra- and inter-annual scales of A. albopictus. This process-based model integrates mechanistic descriptions of the developmental cycle and the dispersal process of A. albopictus within a reaction-diffusion framework, depending on climatic suitability and photoperiod with a high spatio-temporal resolution. Using this model coupled with a climatic database, we propose several maps describing the current intra-annual distribution of A. albopictus, including the date of first emergence and the length of the period with significant adult presence. We also compute its future distribution over the next 10 years under several climatic scenarios, which shows a range expansion with a strong dependence on the climatic scenario. The outputs of the model may constitute a valuable asset for designing control and avoidance strategies, and to anticipate the biting nuisance with a high spatio-temporal resolution. These outputs also emphasize the importance of taking dispersal and life cycle into account to obtain accurate descriptions of out-of-equilibrium processes such as ongoing invasions.

This study presents a 31-year (1993–2023) wave hindcast using a high-resolution two-domain nested numerical wave model implemented with Simulating Waves Nearshore (SWAN). The spatiotemporal variability and long-term trends of two wave parameters (significant wave height Hs and spectral peak period Tpeak) are systematically analyzed for the Yangtze River Delta (YRD) and its adjacent waters. Validation against in situ buoy measurements confirms that the SWAN model effectively reproduces the regional wave conditions. Results indicate that mean wave conditions are primarily modulated by the Asian monsoon, whereas extreme wave events are predominantly influenced by typhoons. This leads to pronounced differences in spatial patterns and seasonal variability between mean and maximum Hs values. In addition, the regional interannual variations of Hs and Tpeak exhibit different degrees of correlation with the Niño 3.4 index, the Pacific Decadal Oscillation (PDO) index and the Western Pacific Subtropical High Ridge Position (WPSH) Index. Overall, both Hs and Tpeak exhibit positive trends over the study period, and both positive trends shift remarkably between seasons. The positive trends in mean wave conditions are mild during spring and summer but more pronounced in autumn and winter. Statistically significant increases in seasonal mean Hs are identified in parts of the East China Sea (0.35 cm a−1 in autumn) and the southern Yellow Sea (0.27 cm a−1 in winter). Notably, not all trends are positive: the 90th percentiles of both Hs and Tpeak during summer exhibit widespread declining trends, although they are not statistically significant.