Search Results (99)

This study analyzes precipitation patterns and future trends in the Kuye River Basin in the context of climate change, providing a scientific foundation for water resource management and ecological protection. Using methods such as the Mann–Kendall test, Pettitt test, and complex Morlet wavelet analysis, this study examines both interannual and intra-annual variability in historical precipitation data, identifying abrupt changes and periodic patterns. Future projections are based on CMIP5 models under RCP4.5 and RCP8.5 scenarios, forecasting changes over the next 30 years (2023–2052). The results reveal significant spatiotemporal variability in precipitation, with 88.16% concentrated in the summer and flood seasons, while only 1.07% falls in winter. The basin’s multi-year average precipitation is 445 mm, exhibiting stable interannual variability, but with a significant increase starting in 2006. Projections indicate that the average annual precipitation will rise to 524.69 mm from 2023 to 2052, with a notable change point in 2043. Precipitation is expected to increase spatially from northwest to southeast. This research underscores the importance of understanding precipitation dynamics in managing drought and flood risks. It highlights the role of soil and water conservation and vegetation restoration in improving water resource efficiency, supporting sustainable development, and guiding climate adaptation strategies. Full article

Background: One of the greatest challenges to biologists is to understand the adaptive mechanisms of how plants will respond to climate at all levels from individual physiology to whole populations. For example, variation (plasticity) in the composition and concentration of metabolites will determine productivity, reproduction, and ultimately survival and distribution of plants, especially those subjected to rapid climate change. Objectives: Our aim was to study how interspecific and intraspecific metabolic variation in plant species within a single community can be elucidated. Methods: We used a metabolomics approach to study metabolic acclimation (by measuring the metabolome between plants under “common garden” controlled environment conditions) and metabolic plasticity (using field based reciprocal transplant studies) in a set of Atlantic sand dune annual communities along a latitudinal gradient from Portugal to England. Results: In the common garden study, metabolically phenotyping (using a fingerprinting direct injection mass spectrometry approach) five species of annual plants showed that species living together in a community have distinct metabolic phenotypes (high inter-specific metabolic variation). There was low intra-specific metabolic variation between populations growing under standard environmental conditions. The metabolic variation in one species Veronica arvensis was measured in the reciprocal transplant study. Metabolic phenotypes obtained from all samples were similar across all sites regardless of where the plants originated from. Conclusions: This implies that the metabolome is highly plastic and the measurable metabolome in this study was influenced more by local environmental factors than inherent genetic factors. This work highlights that species are fulfilling different niches within this community. Furthermore, the measurable metabolome was highly plastic to environmental variation. Full article

The seasonal and interannual temporal variation in the composition, richness, diversity, and similarity of fish larval assemblages associated with an Eastern Tropical Pacific (ETP) coral reef system was studied in March (cold water) and September (warm water) during the years 2017, 2018, and 2019. Throughout the study period, we collected 4779 fish larvae and identified 88 taxa, encompassing 46 families. This increased the total number of recorded fish taxa for the region to 146. Fish larvae were collected by daytime and nighttime surface trawls, using a bongo net 30 cm in diameter and 180 cm in length, equipped with mesh sizes of 300 and 500 μm. The species diversity and abundance of ichthyoplankton over this ETP coral reef changed by intra-annual variation of the hydrological conditions of the upper layer of the sea. Six significant assemblages were identified (SIMPROF, p < 0.05), each one associated with each sampling period (ANOSIM, R = 0.764); Cetengraulis mysticetus, Diaphus pacificus, Anchoa sp., Anisotremus sp., Bremaceros bathymaster, Oligoplites saurus, Caranx sp., Seriola sp., Gobiidae sp., Microgobius sp., and Synodus evermanni were the species that contributed to dissimilitude between groups. Canonical correspondence analysis revealed significant associations between specific larval fish taxa abundance and temperature, salinity, dissolved oxygen, and zooplankton biomass. Overall, the assemblage of ichthyoplankton in this ETP coral reef system is sensitive to seasonal changes in water column hydrographic conditions. Full article

Estimating daily continuous evapotranspiration (ET) can significantly enhance the monitoring of crop stress and drought on regional scales, as well as benefit the design of agricultural drought early warning systems. However, there is a need to verify the models’ performance in estimating the spatiotemporal continuity of long-term daily evapotranspiration (ET_d) on regional scales due to uncertainties in satellite measurements. In this study, a thermal-based two-surface energy balance (TSEB) model was used concurrently with Terra/Aqua MODIS data and the ERA5 atmospheric reanalysis dataset to calculate the surface energy balance of the soil–canopy–atmosphere continuum and estimate ET at a 1 km spatial resolution from 2000 to 2022. The performance of the model was evaluated using 11 eddy covariance flux towers in various land cover types (i.e., savannas, woody savannas, croplands, evergreen broadleaf forests, and open shrublands), correcting for the energy balance closure (EBC). The Bowen ratio (BR) and residual (RES) methods were used for enforcing the EBC in the EC observations. The modeled ET was evaluated against unclosed ET and closed ET (ET_BR and ET_RES) under clear-sky and all-sky observations as well as gap-filled data. The results showed that the modeled ET presented a better agreement with closed ET compared to unclosed ET in both Terra and Aqua datasets. Additionally, although the model overestimated ET_d across all different land cover types, it successfully captured the spatiotemporal variability in ET. After the gap-filling, the total number of days compared with flux measurements increased substantially, from 13,761 to 19,265 for Terra and from 13,329 to 19,265 for Aqua. The overall mean results including clear-sky and all-sky observations as well as gap-filled data with the Aqua dataset showed the lowest errors with ET_RES, by a mean bias error (MBE) of 0.96 mm.day⁻¹, an average mean root square (RMSE) of 1.47 mm.day⁻¹, and a correlation (r) value of 0.51. The equivalent figures for Terra were about 1.06 mm.day⁻¹, 1.60 mm.day⁻¹, and 0.52. Additionally, the result from the gap-filling model indicated small changes compared with the all-sky observations, which demonstrated that the modeling framework remained robust, even with the expanded days. Hence, the presented modeling framework can serve as a pathway for estimating daily remote sensing-based ET on regional scales. Furthermore, in terms of temporal trends, the intra-annual and inter-annual variability in ET can be used as indicators for monitoring crop stress and drought. Full article

The Qinling Mountains, serving as a natural geographical and climatic boundary in China, require comprehensive climatic records to elucidate the trends in climate changes across the country. While stable isotopes in tree rings are widely employed to indicate historical environmental changes, investigations into tree ring isotopes in the Qinling Mountains, particularly within the widespread broad-leaf oaks, remain limited. In this study, we investigated both intra- and inter-annual variations in the δ¹³C values of tree rings and their correlations with climatic signals over the past two decades for Quercus aliena var. acuteserrata, a dominant species among oak trees on the main peak of the Qinling Mountains. Our results reveal that responses to climate differ among altitudes and individual trees, with trees at higher altitudes exhibiting higher sensitivity to extreme climate, which is low temperatures and rainfall fluctuations during the growth period in intra-annual δ¹³C variations. Furthermore, the positive correlations are observed between temperature during growing season and both tree growth and the inter-annual δ¹³C variations. However, the climate signal appears to be hampered by oak-specific factors, such as intense competition among individuals and the age of trees. Therefore, we suggest a more rigorous selection of sampling and propose further investigations into isotopic fractionation processes in oaks for future studies. Full article

This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of monitoring data in order to (a) identify the main temporal patterns and their interactions at a decadal, annual and seasonal scale, (b) estimate precipitation effects on load formation and evaluate whether and to which extent the hydrological regime affects nutrient export across the years and (c) analyse the nutrient export regime at a monthly scale and the main transport dynamic of N and P chemical species (hydrological vs. biogeochemical control). The long-term analysis shows a general decrease of both P and N loadings, but the trends are different between the elements and their chemical species, as well as undergoing different seasonal variations. We found a statistically significant relationships between precipitation and loads, which demonstrates that precipitation patterns drive the exported load at the intra- and interannual time scales considered in this study. Precipitation-induced load trends trigger seasonal changes in nutrient deliveries to the sea, peaking in spring and autumn. The nitrogen decrease is mainly concentrated in the summer dry period, while total phosphorus diminishes mainly in spring and autumn. This mismatch of N and P results in variable molar N:P ratios within the year. The effects of extreme drought and flood events, along with the progressive decrease in the snowmelt contribution to water fluxes, are expected to exacerbate the variability in the N and P loadings, which in turn is expected to perturbate the biodiversity, food webs and trophic state of the Northern Adriatic Sea. Full article

Freshwater availability in Pacific equatorial atolls is highly variable because of the influence of El Niño–Southern Oscillation (ENSO) on rainfall. IPCC projections for the central and western tropical Pacific suggest annual rainfall (P_a) will increase as sea surface temperature (SST) rises. Future changes in ENSO frequency and intensity and in hydrological droughts, however, are uncertain. Here, trends in monthly, seasonal, annual, annual maximum, and minimum rainfall in two equatorial atolls in the eastern and central tropical Pacific are compared with trends in the SST of the surrounding Nino regions from 1951 to 2023. Significant increasing trends in the warm season, annual, and annual maximum SST in the Nino1 + 2, Nino3, and Nino4 regions were of order +1.0 °C/100 y. There were no significant trends in the cool season or annual minimum SST. Despite ocean warming, there were no significant trends in atoll P_a, in intra-annual or interannual variability over 7 decades for either SST or P_a, or in the relative strengths of warm/cool and wet/dry seasons. Extreme, large P_a only occurred after 1987, indicative of ocean warming. Extreme, small P_a happened throughout the period, suggesting no change in drought frequency. Correlations between 12-month P and SST were very strong, with historic rates of increases in P_a of around 1200 mm/y/°C, consistent with projections. The results indicate that the recharge of atoll groundwater will increase as oceans warm, but droughts will remain a major challenge. Full article

Remote sensing is a valuable tool for surveying submerged aquatic vegetation (SAV) distribution patterns at extensive spatial and temporal scales. Only regular mapping over successive time periods (e.g., months, years) allows for a quantitative assessment of SAV loss or recolonization extent. Still, there are only a limited number of studies assessing temporal changes in SAV patterns. ESA Sentinel-2 (S2) has a high revisiting frequency permitting the multi-temporal assessment of SAV dynamics both seasonally and inter-annually. In the current study, a physics-based IDA (Image Data Analysis) model was used for the reconstruction of past SAV percent cover (%cover) patterns in the Baltic Sea coastal waters based on S2 archived images. First, we aimed at capturing and quantifying intra-annual spatiotemporal SAV dynamics happening during a growing season. Modeling results showed that significant changes took place in SAV %cover: the extent of low-cover (0–30% coverage) and intermediate-cover (30–70% coverage) areas decreased, while high-cover (70–100% coverage) areas increased during the growing period. Secondly, we also aimed at detecting SAV %cover spatiotemporal variations inter-annually (over the years 2016–2022). Inter-annual variability in %cover patterns was greater in the beginning of the vegetation period (May). The peak of the growing period (July/August) showed greater stability in the areal extent of the %cover classes. Full article

The Tarim Basin is located in an arid inland area; the ecological environment is fragile, and it is extremely sensitive to climate change. For the purpose of studying dynamic changes in the vegetation response of vegetation in the Tarim Basin to extreme climate, this study used the Vegetation Ecological Quality Index (EQI) as a vegetation indicator and calculated 12 extreme climate indices using Rclimdex. Pearson correlation analysis was used to explore the relationship between EQI values and various extreme climate indices at both inter-annual and intra-annual scales. Additionally, geographic detector analysis was employed to examine the single and interactive effects of extreme climate on the EQI for different vegetation types. The following was found: (1) During 2000–2022, the EQI showed an upward trend in the Tarim Basin, and the increase in agricultural vegetation was the fastest. (2) Since 2000, the extreme warm temperature indices have risen, whereas the extreme cold temperature indices have declined. The warming rate of nighttime temperatures exceeds that of daytime, and the extreme precipitation rises intensively. Simultaneously, continuous dry days have also increased. (3) On an inter-annual scale, the EQI is primarily negatively correlated with the most extreme warm temperature indices, while it is positively correlated with extreme cold temperatures and extreme precipitation indices. On an intra-annual scale, there is an obvious regional concentration in the correlation between the EQI and extreme climate indices. The diurnal temperature range (DTR) and cold daytimes (TX10P) have inhibitory and promoting effects on areas with high and low EQI, respectively. The extremum indices, temperature warm indices, and precipitation intensity indices have a promoting effect on areas with a high EQI and an inhibiting effect on areas with a low EQI. The interaction between extreme climate indices has a greater impact on the EQI than the effect of a single extreme climate index, especially with a significant impact on forests and shrubs. This study provides a reference for the early warning of meteorological disasters, ecosystem protection, and sustainable management in the Tarim Basin. Full article

Coasts are continually changing and remote sensing from satellites has the potential to both map and monitor coastal change at multiple scales. Unlike optical technology, synthetic aperture radar (SAR) is uninfluenced by darkness, clouds, and rain, potentially offering a higher revision period to map shoreline position and change, but this can only be feasible if we have a better interpretation of what shorelines as extracted from SAR imagery represent on the ground. This study aims to assess the application of shorelines extracted from SAR from publicly available satellite imagery to map and capture intra-annual to inter-annual shoreline variability. This is assessed in three tidally controlled coastal study areas that represent sand and gravel beaches with different backshore environments: low-lying dunes and marsh; steep, rocky cliff; and urban environments. We have found that SAR shorelines consistently corresponded to positions above the high-water mark across all three sites. We further discuss the influence of the scene geometry, meteorological and oceanographic conditions, and backshore environment and provide a conceptual interpretation of SAR-derived shorelines. In a low-lying coastal setting, the annual change rate derived through SAR presents a high degree of alignment with the known reference values. The present study contributes to our understanding of the poorly known aspect of using shorelines derived from publicly available SAR satellite missions. It outlines a quantitative approach to automatically assess their quality with a new automatic detection method that is transferable to shoreline evolution assessments worldwide. Full article

Glacier velocity is a crucial parameter in understanding glacier dynamics and mass balance, especially in response to climate change. Despite numerous studies on glaciers in the West Kunlun Mts., there is still insufficient knowledge about the details of inter- and intra-annual velocity changes under global warming. This study analyzed the glacier velocity changes in the West Kunlun Mts. using Sentinel-1A satellite data. Our results revealed that: (1) The velocity of glaciers across the region shows an increasing trend from 2014 to 2023. (2) Five glaciers were found to have been surged during the study period, among which two of them were not reported before. (3) The surges in the study region were potentially controlled through a combination of hydrological and thermal mechanisms. (4) The glacier N2, Duofeng Glacier, and b2 of Kunlun Glacier exhibit higher annual velocities (32.82 m a⁻¹) compared to surging glaciers in quiescent phases (13.22 m a⁻¹), and were speculated as advancing or fast-flowing glaciers. Full article

The mountain systems of the Himalayan regions are changing rapidly due to climatic change at a local and global scale. The Indian Western Himalaya ecosystem (between the tree line and the snow line) is an underappreciated component. Yet, knowledge of vegetation distribution, rates of change, and vegetation interactions with snow-hydroclimatic elements is lacking. The purpose of this study is to investigate the linkage between the spatiotemporal variability of vegetation (i.e., greenness and forest) and related snow-hydroclimatic parameters (i.e., snow cover, land surface temperature, Tropical Rainfall Measuring Mission (TRMM), and Evapotranspiration (ET)) in Himachal Pradesh (HP) Basins (i.e., Beas, Chandra, and Bhaga). Spatiotemporal variability in forest and grassland has been estimated from MODIS land cover product (MCD12Q1) using Google Earth Engine (GEE) for the last 19 years (2001–2019). A significant inter- and intra-annual variation in the forest, grassland, and snow-hydroclimatic factors have been observed during the data period in HP basins (i.e., Beas, Chandra, and Bhaga basin). The analysis demonstrates a significant decrease in the forest cover (214 ha/yr.) at the Beas basin; however, a significant increase in grassland cover is noted at the Beas basin (459 ha/yr.), Chandra (176.9 ha/yr.), and Bhaga basin (9.1 ha/yr.) during the data period. Spatiotemporal forest cover loss and gain in the Beas basin have been observed at ~7504 ha (6.6%) and 1819 ha (1.6%), respectively, from 2001 to 2019. However, loss and gain in grassland cover were observed in 3297 ha (2.9%) and 10,688 ha (9.4%) in the Beas basin, 1453 ha (0.59%) and 3941 ha (1.6%) in the Chandra basin, and 1185 ha (0.92%) and 773 ha (0.60%) in the Bhaga basin, respectively. Further, a strong negative correlation (r = −0.65) has been observed between forest cover and evapotranspiration (ET). However, a strong positive correlation (r = 0.99) has been recorded between grassland cover and ET as compared to other factors. The main outcome of this study in terms of spatiotemporal loss and gain in forest and grassland shows that in the Bhaga basin, very little gain and loss have been observed as compared to the Chandra and Beas basins. The present study findings may provide important aid in the protection and advancement of the knowledge gap of the natural environment and the management of water resources in the HP Basin and other high-mountain regions of the Himalayas. For the first time, this study provides a thorough examination of the spatiotemporal variability of forest and grassland and their interactions with snow-hydroclimatic factors using GEE for Western Himalaya. Full article

Baseflow is a stable part of streamflow and the main component of streamflow during the dry season. Baseflow plays an important role in the water cycle, and in ecological environment protection of the Yellow River basin (YRB). Taking the Zuli, Kuye, and Tuwei basins, and the Jingle sub-basin as examples, the baseflow was separated using a recursive digital filtering method. The intra-annual, inter-annual, and chronological characteristics of baseflow and the baseflow index (BFI) were analyzed, and driving factors were analyzed from the perspective of climate-change and human-impact factors. The results showed that: (1) The annual baseflow of the basins mainly declined, trending downward in all four test basins, while the BFI increased in two of the basins and remained nearly constant in the other two basins; however, the distributions of baseflow and the BFI were more uniform. (2) The intra-annual patterns for baseflow and the BFI showed changes between earlier and later periods. (3) Precipitation and soil and water conservation measures were the primary driving forces of baseflow change in the basins. The influence of the former weakened while the latter strengthened, and coal mining in the Kuye River and Tuwei River basins also influenced baseflow significantly. (4) When the normalized difference vegetation index (NDVI) < 0.375, the BFI of test watersheds gradually decreased with the increase in the NDVI. When 0.375 < NDVI < 0.65, the BFI of the basins gradually increased with the increase in the NDVI and the underlying surface continued to improve. When NDVI > 0.65, the increase rate of the BFI decreased and the soil and water conservation capacity of the underlying surface tended to be stable. Full article

Qinghai Lake is the largest lake in Qinghai-Tibet Plateau and China, it is also an important part of the national ecological security strategy. Since 1950s, the water level of Qinghai Lake has been changing rapidly, which induces great effects on the surrounding traffic facilities, residents’ safety and the development of animal husbandry, etc. Therefore, it is necessary to study the water level evolution and water balance of Qinghai Lake under the main impact of climate change. Based on meteorological and hydrological data from Buha River Hydrological Station, Xiashe Hydrological Station, and Gangcha Meteorological Station, CMFD, and water balance equation, this article first analyzes the interannual and intra-year water level evolution characteristics of Qinghai Lake from 1956 to 2020, including lake surface precipitation (P), runoff into the lake (${\mathrm{R}}_{\mathrm{s}}$) and evaporation (E). Secondly, we conducted a study on the water level change characteristics calculated for fixed months. Finally, the contribution rate of each factor to the fluctuation of Qinghai Lake water level was quantitatively calculated using the ridge regression method. Results show that the annual average water level declined at a rate of 0.8 m decade⁻¹ from 1956 to 2004, primarily due to E exceeding the sum of P and ${\mathrm{R}}_{\mathrm{s}}$. However, from 2004 to 2020, the water level increased at a rate of 1.7 m decade⁻¹, mainly attributed to the increase in P and ${\mathrm{R}}_{\mathrm{s}}$. Qinghai Lake exhibits evident intra-year variations, with the water level starting to rise in May and reaching its peak in September, which aligns with the monthly variations of ${\mathrm{R}}_{\mathrm{s}}$, P, and E. Furthermore, the impacts of the current year’s P, ${\mathrm{R}}_{\mathrm{s}}$, and E on the annual water level fluctuations for fixed months of September to December is greater than that of the previous year. Specifically, the contributions of the current year’s P, ${\mathrm{R}}_{\mathrm{s}}$ and E to the water level fluctuations calculated based on December data are 10%, 70%, and 20%, respectively. The contribution rate of meteorological factors to the rise and fall of water level was wind speed (33%), downward short-wave radiation (27%), precipitation (27%), downward long-wave radiation (11%) and specific humidity (2%). Full article

Climate and topography are pivotal factors influencing snow cover variation, highlighting the significance of investigating the altitudinal response of snow cover to climate change. This study adopted a new MODIS snow cover extent product over China, reanalysis climate data, and digital elevation model (DEM) data to analyze the variation characteristics of snow cover frequency (SCF) and climatic factors with elevation in the Keriya River Basin (KRB) during the hydrological years from 2000 to 2020. The Partial Least Squares Regression (PLSR) method was utilized to explore the elevation-based relationships between SCF and climatic factors. Our findings can be summarized as follows: (1) The SCF exhibited an “increasing–decreasing–increasing–decreasing” pattern intra-annually, with insignificant monthly inter-annual variations. Only November, January, April, and May demonstrated upward trends, whereas October and December remained relatively stable, and other months exhibited declines. (2) Vertical variations in SCF and climatic factors revealed fluctuating upward trends in SCF and wind speed. On the other hand, the air temperature consistently decreased at a lapse rate ranging from 0.60 to 0.85 °C/100 m. Precipitation demonstrated “rising–falling” or “rapidly rising–slowly rising” patterns, bounded by 3821 m (range 3474–4576 m). (3) A new decision scheme, which took into account the alteration of the primary SCF controlling factors and shifts between positive and negative impacts caused by these factors, was used to determine five threshold elevation zones: 2585 m (range 2426–2723 m), 3447 m (range 3125–3774 m), 4251 m (range 4126–4375 m), 5256 m (range 4975–5524 m), and 5992 m (range 5874–6425 m). These threshold elevation zones were evident in spring, with four of these appearing in autumn (excluding 4251 m) and summer (excluding 2585 m). Only two threshold elevation zones were observed in winter with elevation values of 3447 m and 5992 m, respectively. Our findings are crucial for a deeper understanding of snow cover variation patterns at different elevations and offer essential insights for the responsible management of regional water resources. Full article