Annual Precipitation Research Articles

Using proxy data and vegetation modelling to predict past, current and future distributional shifts of Butea monosperma, a marker of land degradation in India

Extensive deviations in spatio-temporal social and environmental dynamics currently alter the health of ecosystems and the services they provide. Detecting the causes that contribute to the distribution of a natural forest species capable of restoring the lost ecosystem function and productivity will aid in determining better food security, livelihoods and provision of ecosystem goods and services. We modelled the spatial range of Butea monosperma (B. monosperma) under past, that is, Last Glacial Maximum (LGM), Middle Holocene (MH), current and future (2070) climatic scenarios with Maximum Entropy (MaxEnt) trained on present-day occurrences. We identified areas of suitable habitats for which the estimation of habitat stability is predicted in all the models at different times. To validate the inferred suitable habitat, we tested the model by the current occurrence and fossil pollen data of B. monosperma. Our distribution models agree with the fossil pollen records for the MH (4,500–7,000 yr BP) and predict the prevalence of B. monosperma covering 84.22% of the Indian subcontinent with maximum habitat stability in western and southwestern India (10.95%). The widespread potential distribution of the plant species during the LGM supports the presence of the last remnants of tropical dry deciduous forest in the region. However, a decline in habitat suitability (62.84%) is predicted under current and future climatic scenarios with maximum stability (0.90%–3.09%) along the Western Ghats, Nilgiri hills, Gir range in the western India and north-eastern region covering the Assam Valley and foothills of Tripura and Mizo hills. Temperature seasonality (33.6%) measured in terms of variable contribution in MaxEnt model significantly affects the distribution shift of B. monosperma, along with annual precipitation (22.8%) and annual mean temperature (16.2%). Model results provide evidence of habitat reduction and identify the stability hotspots for B. monosperma for its conservation and establishment of land management policies mainly for the dry tropics.

Effectiveness assessment of protected areas based on the states, trends, and relative changes in forest ecosystem: a case study in the Three Parallel Rivers Region, China

Establishing protected areas (PAs) is a major measure of biodiversity conservation, and various methods have been explored to assess PAs’ effectiveness. However, those methods mainly compared the relative changes in land cover between treated samples inside the PAs and their matched samples outside the PAs, which would produce misjudgments, especially in some climax communities with a relatively steady state. Thus, in this study, we constructed an integrated framework through a series of assessments according to the state, trend, and relative change of each PA to explore the conservation effectiveness of PAs in the Three Parallel Rivers Region in China from 2000 to 2020. Here, “state” refers to the difference among samples from within and outside the PA, assessed through yearly sample mean comparison. “Trend” means linear regression of mean forest area of each PA throughout the assessment period. “Relative change” means the difference in the mean value of the slope of forest changes between the treated samples inside each PA and their matched control samples outside of PAs. The entire forest area within all PAs in the Three Parallel Rivers Region showed a significant increasing trend from 2000 to 2020 (R2 = 0.919, P<0.05). Among all the PAs, twelve (86%) had a positive effect on protecting the forest ecosystem, and two had a nonsignificant effect. Among the factors affecting the state and relative change in PAs’ forests, the annual total precipitation was the most important, followed by distance to the nearest road. Moreover, the management-level variable was an essential factor in the state of PAs’ forest ecosystems, which indicated that national PAs (nature reserves and natural parks) were in a better state than local (provincial- and county-level) nature reserves. Overall, the conservation effectiveness of forests in PAs was assessed at a regional scale in the Three Parallel Rivers Region, implying that our framework would be additional useful in regions with high biodiversity and steady ecosystems. This framework better avoids underestimating conservation effectiveness assessment tasks than traditional methods do. Thus, we posit that this framework is suitable for future global or country-level assessments.

Uncertainty estimation of hydrological modelling using gridded precipitation as model inputs in the Gandaki River Basin

Study RegionFour subbasins in the Gandaki River Basin in the southern Himalayan region. Study FocusIn the southern Himalayan region, gridded precipitation datasets are often used to complement sparse gauge network observations in hydrological modelling for water resource assessment. However, the applicability and uncertainty of using these datasets in hydrological modelling remain to be evaluated. In this study, nine high spatial resolution gridded precipitation datasets were used to force a widely used hydrological model to simulate the daily runoff at four hydrological stations in this region. The accuracy of these datasets was evaluated, and the model calibration results and modelling uncertainty were analyzed. New Hydrological Insights for the RegionOur analysis revealed large differences among the nine gridded precipitation datasets, and most datasets underestimated the annual precipitation in the low-elevation regions and overestimated that in the high Himalayas. Furthermore, through the adjustments of model parameters, the underestimations of precipitation by gridded datasets were compensated for by the overestimation of glacial melt. Therefore, the model performance was better, and the model uncertainty was lower in basins with higher glacial coverage. Notably, our findings indicated that the performances of gridded precipitation datasets were heterogeneous and that their direct use in hydrological modelling may result in unreasonable hydrological process variables; thus, these datasets should be evaluated and used with caution in water resource assessments in Himalayan regions.

Comparison of bias correction methods to regional climate model simulations for climate change projection in Muger Subbasin, Upper Blue Nile Basin, Ethiopia

ABSTRACT The objective of this study was to evaluate the best performed bias correction methods to simulate the regional climate models for future climate change projections in Muger Subbasin. Delta change methods perform very well with a coefficient of correlation of 0.99 and a percent of bias –3. When we compare its corrected simulation result with observed data, the delta change method seems to have with no biases for maximum temperature, but increases by 1.67 °C from the mean for minimum temperature of 0.39 and 38.41 mm for monthly and annual precipitation, respectively. Delta change methods underestimate the model result for both temperature and precipitation. Linear scaling and variance scaling methods overestimate the maximum temperature of the simulation by 0.002 and 0.004 °C from the mean of the observed data, but it underestimates 1.59 and 1.56 °C the minimum temperature, respectively. The long-term temperature projection values (2060–2090) are higher than the near-term projections (2030–2060) for both RCP2.6 and RCP8.5 scenarios. Similarly, the change in annual precipitation for the long-term is higher than the near-term projections. As a conclusion, the results draw attention to the fact that bias-adjusted regional climate models data are crucial for the provision of local climate change impact studies in the Muger Subbasin.

The Bioclimates of India in Relation to the Vegetational Criteria

The purpose of a climatic classification is to characterise the climatic regions in terms of meteorological elements like temperature and precipitation which are the most decisive factors in determining the landscape of the earth. The plant-climate relation is so close that it is possible to differentiate the types of climates such as equatorial, tropical, mediterranean, with their different shades such as humid, sub-humid, arid using the characters of the plant-cover. In a physical classification of the climate, an arid or a humid region is defined on the basis of annual precipitation, the number of dry days or dry months in the year or by means of several climatic formulae.In the present work emphasis is laid on the term "bioclimate". It is defined as the climate in relation to the life and is expressed by an index of aridity-humidity. This index is proposed on the basis of combining three essential ecological factors viz. temperature, precipitation and dry period. Correlations are obtained between the above index of aridity-humidity and four distinct criteria of the plant-kingdom : (1) Floristic criteria, (2) Vegetational criteria, (3) Morpho-ecological criteria and (4) Agronomic criteria.

Modeling Environmental Vulnerability for 2050 Considering Different Scenarios in the Doce River Basin, Brazil

Understanding climate change and land use impacts is crucial for mitigating environmental degradation. This study assesses the environmental vulnerability of the Doce River Basin for 2050, considering future climate change and land use and land cover (LULC) scenarios. Factors including slope, elevation, relief dissection, precipitation, temperature, pedology, geology, urban distance, road distance, and LULC were evaluated using multicriteria analysis. Regional climate models Eta-HadGEM2-ES and Eta-MIROC5 under RCP 4.5 and RCP 8.5 emission scenarios were employed. The Land Change Modeler tool simulated 2050 LULC changes and hypothetical reforestation of legal reserve (RL) areas. Combining two climate and two LULC scenarios resulted in four future vulnerability scenarios. Projections indicate an over 300 mm reduction in average annual precipitation and an up to 2 °C temperature increase from 2020 to 2050. Scenario 4 (RCP 8.5 and LULC for 2050 with reforested RLs) showed the greatest basin area in the lowest vulnerability classes, while scenario 3 (RCP 4.5 and LULC for 2050) exhibited more high-vulnerability areas. Despite the projected relative improvement in environmental vulnerability by 2050 due to reduced rainfall, the complexity of associated relationships must be considered. These results contribute to mitigating environmental damage and adapting to future climatic conditions in the Doce River Basin.

Modeling climate change impacts under future CCM3 scenario on sorghum (Sorghum bicolor) as an drought resilient crop in tropical arid Lombok Island, Indonesia

Abstract. Wibowo AA, Meylani V. 2024. Modeling climate change impacts under future CCM3 scenario on sorghum (Sorghum bicolor) as an drought resilient crop in tropical arid Lombok Island, Indonesia. Intl J Trop Drylands 8: 35-43. The arid ecosystems and drought conditions exacerbated by climate change and rising CO2 levels necessitate the identification of alternative drought-tolerant crops. Sorghum bicolor L. has emerged as a promising option due to its resilience to drought. However, there is dearth of information regarding its future potential distribution, particularly in arid regions like Lombok Island, Indonesia, where sorghum is being considered as a viable alternative to ensure food security. This study employs Maximum Entropy (MaxEnt) modeling, incorporating environmental and bioclimatic variables, along with the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) scenario reflecting doubled CO2 levels, to model the future potential distribution of S. bicolor. The model projects a total suitable habitat area of 1,875 km2, constituting 39.56% of Lombok Island’s land area. Notably, very high-suitability areas of 175 km2, and high-suitability areas of 200 km2 encompass 3.69% and 4.22% of the island’s territory, respectively, predominantly concentrated in the southern region of the island and characterized by low precipitation and high temperatures, particularly at altitudes ranging from 0 to 1,000 meters. The model's performance, evaluated using the Area Under the Curve (AUC), yields a score of 0.725, indicating a good level of accuracy. Key factors influencing sorghum distribution include annual precipitation (68.69%), isothermality (9.56%), temperature seasonality (9.56%), precipitation seasonality (8.69%), and annual mean temperature (3.47%). The CCM3 model forecasts an expansion of sorghum distribution toward the north, occupying approximately 6.25% of Lombok's total area. These findings highlight sorghum’s adaptability and resilience to future climate changes, positioning it as a valuable resource for sustainable agriculture in arid environments.

Evaluation of the characteristics of Indian summer monsoon simulated by CMIP6 models

AbstractThe present research is aimed at evaluating the climate coupled models with respect to the observational datasets for the investigation of the characteristics of the Indian summer monsoon (ISM). The monthly averaged historical simulations from 12 coupled climate models that participated in Coupled Model Intercomparison Project Phase 6 (CMIP6) are compared with the ground based observational data, satellite and reanalysis datasets for the study period of 1980–2014. This study uses these high‐resolution models to investigate monsoon features, onset and withdrawal dates, primarily focusing on individual model performances rather than highly documented multi‐model mean performance. Performance evaluation of the models suggests that sea surface temperature (SST) simulations by the models are in better agreement for the Arabian Sea than the Bay of Bengal with respect to the ERA5 reanalysis data sets. Further, inter‐model differences amongst the CMIP6 models in estimating the spatial distribution of various monsoon system variables during pre‐monsoon and monsoon seasons are noted which may be attributed to the different model components and varying physics configuration, nonetheless, models like NESM3 and INM‐CN5 are able to reproduce ISM pattern reasonably well. The annual precipitation cycle demonstrates a good agreement between most climate models and IMD data. Evolution of tropospheric temperature gradient (ΔTT) estimated from the CMIP6 models mimics the temporal pattern of the annual rainfall and therefore, is used to estimate the onset and withdrawal dates from CMIP6 models; however, high variability is noted amongst the CMIP6 models in retrieving the onset and withdrawal dates when compared with the IMD observations. Most of the models show a shorter rainy season except NorESM2‐MM. Overall our results suggest that the CMIP6 models can be used for the seasonal mean evaluation of monsoon system parameters and process‐based studies to improve our present understanding of the ISM system.

Data-driven analysis of annual rain distributions

Rainfall is an important component of the climate system, and its statistical properties are vital for prediction purposes. In this study, we have developed a statistical method for constructing the distribution of annual precipitation. The method is based on the convolution of the measured monthly rainfall distributions and does not depend on any presumed annual rainfall distribution. Using a simple statistical model, we demonstrate that our approach allows for a better prediction of extremely dry or wet years with a recurrence time several times longer than the original time series. The method that has been proposed can be utilized for other climate variables as well. Published by the American Physical Society 2024

Robust hydraulic traits correlation in woody species despite large trait variation along natural and experimental environmental gradients

Abstract Hydraulic traits are major determinants of plant fitness, thus exerting control over vegetation structure, function and distribution. Yet it remains unclear whether and how hydraulic traits respond to environmental stimuli (i.e. phenotypic variation of hydraulic traits; PVHT) and if the coordination between different hydraulic traits and the trait–climate relationship are affected by PVHT. Here, we synthesized data of PVHT (maximum hydraulic conductivity and water potential inducing 50% loss of hydraulic conductivity) and potentially related morphological and anatomical traits (e.g. sapwood density, branch Huber value, mean and hydraulic weighted conduit diameter). We analysed the magnitude, direction and source of variation of the plastic response, as well as the influence of environmental factors on trait coordination. Additionally, we compared the intra‐ and inter‐specific variation between key hydraulic traits and climate metrics (mean annual precipitation and mean annual temperature) at the site of growth, as well as across the population range. PVHT was highly variable in both magnitude and direction, which was contingent on the environmental factor. The variation in PVHT mainly occurred at high taxonomic levels (i.e. family and genus), whereas phenology explained little variation for PVHT. Despite the high variability, trait correlation remained robust in the presence of environmental stimuli. Moreover, trait–climate relationships differed at inter‐specific and intra‐specific levels. The intra‐specific variation of hydraulic traits in most species showed no correlation with climate metrics compared with the high correlation of hydraulic traits with climate metrics across species. Our findings suggest that the high variability of PVHT does not affect the trait correlation which may be valuable in predicting vegetation dynamics under varying environments. The distinct trait–climate relationships highlight the need to unravel the driving force of PVHT, as well as the adaptive strategy across populations. Read the free Plain Language Summary for this article on the Journal blog.

Assessment of Rainfall and Temperature Trends in the Yellow River Basin, China from 2023 to 2100

China’s Yellow River Basin (YRB) is sensitive to climate change due to its delicate ecosystem and complex geography. Water scarcity, soil erosion, and desertification are major challenges. To mitigate the YRB’s ecological difficulties, climate change must be predicted. Based on the analysis of the evolution features of hydro-meteorological elements, the CMIP6 climate model dataset with Delta downscaling and the Empirical Orthogonal Function (EOF) is utilized to quantitatively explore the future variations in precipitation and temperature in the YRB. The following results are drawn: The spatial resolution of the CMIP6 climate model is less than 0.5° × 0.5° (i.e., about 55 km × 55 km), which is improved to 1 km × 1 km by the downscaling of Delta and has outstanding applicability to precipitation and temperature in the YRB. The most accurate models for monthly mean temperature are CESM2-WACCM, NorESM2-LM, and ACCESS-CM2, and for precipitation are ACCESS-ESM1-5, CESM2-WACCM, and IPSL-CM6A-LR. Between 2023 and 2100, annual precipitation increases by 6.89, 5.31, 7.02, and 10.18 mm/10a under the ssp126, ssp245, ssp370, and ssp585 climate scenarios, respectively, with considerable variability in precipitation in the YRB. The annual temperature shows a significant upward trend, and the change rates under the different climate scenarios are, respectively, 0.1 °C/10a, 0.3 °C/10a, 0.5 °C/10a, and 0.7 °C/10a. The increase is positively correlated with emission intensity. Based on the EOF analysis, temperature and precipitation mainly exhibit a consistent regional trend from 2023 to 2100, with the primary modal EOF1 of precipitation for each scenario exhibiting a clear spatial distribution in the southeast–northwest.

The future of droughts in Iran according to CMIP6 projections

ABSTRACT Anthropogenic climate change is exerting immense pressure on water resources in Iran. This study investigates future precipitation and meteorological droughts across the country considering performances of 41 general circulation models (GCMs). The findings indicate a significant increase in long-term average annual precipitation (LAAP) across Iran with an overall north-to-south increasing gradient, particularly in areas prone to extreme events. However, focusing solely on LAAP is misleading. Projected precipitation reveals substantial inter-annual variability, impacting both the severity and duration of meteorological droughts. For instance, 100-year return period droughts are expected to intensify in severity (The Shared Socio-economic Pathway SSP1-2.6: 4–91%, SSP8-5.5: 46–204%) and duration (SSP1-2.6: 19–76%, SSP8-5.5: 40–127%) across most regions, except the Persian Gulf coastal zone, where droughts may become less severe (SSP1-2.6: 23%, SSP8-5.5: 23%) and shorter in duration (SSP1-2.6: 27%, SSP8-5.5: 10%). Additionally, bivariate frequency analysis suggests that major droughts could become significantly more frequent in the future.

Investigation of the Historical Trends and Variability of Rainfall Patterns during the March–May Season in Rwanda

This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen’s slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda’s critical MAM season.

Climate of origin shapes variations in wood anatomical properties of 17 Picea species.

Variations in hydraulic conductivity may arise from species-specific differences in the anatomical structure and function of the xylem, reflecting a spectrum of plant strategies along a slow-fast resource economy continuum. Spruce (Picea spp.), a widely distributed and highly adaptable tree species, is crucial in preventing soil erosion and enabling climate regulation. However, a comprehensive understanding of the variability in anatomical traits of stems and their underlying drivers in the Picea genus is currently lacking especially in a common garden. We assessed 19 stem economic properties and hydraulic characteristics of 17 Picea species grown in a common garden in Tianshui, Gansu Province, China. Significant interspecific differences in growth and anatomical characteristics were observed among the species. Specifically, xylem hydraulic conductivity (Ks) and hydraulic diameter exhibited a significant negative correlation with the thickness to span ratio (TSR), cell wall ratio, and tracheid density and a significant positive correlation with fiber length, and size of the radial tracheid. PCA revealed that the first two axes accounted for 64.40% of the variance, with PC1 reflecting the trade-off between hydraulic efficiency and mechanical support and PC2 representing the trade-off between high embolism resistance and strong pit flexibility. Regression analysis and structural equation modelling further confirmed that tracheid size positively influenced Ks, whereas the traits DWT, D_r, and TSR have influenced Ks indirectly. All traits failed to show significant phylogenetic associations. Pearson's correlation analysis demonstrated strong correlations between most traits and longitude, with the notable influence of the mean temperature during the driest quarter, annual precipitation, precipitation during the wettest quarter, and aridity index. Our results showed that xylem anatomical traits demonstrated considerable variability across phylogenies, consistent with the pattern of parallel sympatric radiation evolution and global diversity in spruce. By integrating the anatomical structure of the stem xylem as well as environmental factors of origin and evolutionary relationships, our findings provide novel insights into the ecological adaptations of the Picea genus.

Expanding information for flood frequency analysis using a weather generator: Application in a Spanish Mediterranean catchment

Study regionThe proposed methodology has been applied in the Segura River basin (south-eastern Spain) whose hydrological regime has a high anthropic alteration and catastrophic floods have occurred at different times for centuries. The climate is generally semi-arid, with frequent droughts but also floods caused mainly by rainfall associated with mesoscale convective systems. Study focusWe present a methodology that exploits all available information to obtain reliable low-frequency flood quantiles through the integration of different methods. First, a Weather Generator (WG) was implemented with the results from a regional study of annual maximum precipitation. Second, a rainfall temporal disaggregation procedure was carried out to capture the sub-daily behavior of flood generating storms. Third, a fully-distributed Hydrological Model (HM) was implemented including the role of sediments in extreme events. Finally, the estimation of flood quantiles using plotting positions was validated with systematic and non-systematic information. New Hydrological Insights for the regionThe use of this process-based approach allows to reproduce the main hydrometeorological mechanisms associated with floods in the region studied. Accurate flood quantiles up to 200 years have been possible to obtain, which represents an important advance in the knowledge of the basin since reliable flood quantiles of only 20 years were adequately captured with the current observations. Finally, sediment yield has been proven to be an important factor for the region hydrographs’ reconstruction.

Green manuring alters reactive N losses and N pools in arable soils: A meta-regression study

Green manuring is a conservation agricultural practice that improves soil quality and crop yield. However, increasing the active nitrogen (N) and carbon (C) pools during green manure (GM) amendment may accelerate soil N transformation and stimulate N loss. Previous studies have reported the effects of cover crop incorporation on N2O emission; however, the driving mechanisms and other N losses remain unclear. Therefore, we conducted a comprehensive meta-analysis of 109 published articles (517 paired observations) to clarify the effects of GM amendment on soil reactive N (Nr) losses (N2O emissions, NH3 volatilization, and N leaching and runoff), N pools, and N cycling functional gene abundance. The results showed that green manuring increased soil microbial biomass N (MBN) and NO3−-N concentrations and stimulated N2O emission but significantly lowered N leaching and yield-scaled NH3 volatilization. Practices of green manuring made a dominant contribution to the variation in N2O emissions and NH3 volatilization after GM application. Furthermore, applying legume-based GM, using N derived from GM (GMN) as an additional input, and short-term GM amendment each stimulated N2O emissions. In contrast, adopting non-legume GM, using GMN to partially substitute mineral N, and applying GM to the soil surface or paddy field mitigated NH3 loss during GM amendment. Additionally, the variation in NH3 volatilization was positively related to soil pH and N application rate (NAR) but had a negative relationship with mean annual precipitation (MAP). This study highlighted the marked effects of green manuring on soil N retention and loss. Agricultural operations that adopt GM amendment should select suitable GM species and optimize mineral N inputs to minimize N loss.

Characterization and Multi-Scenario Prediction of Habitat Quality Evolution in the Bosten Lake Watershed Based on the InVEST and PLUS Models

Habitat quality is an important basis for human well-being and the achievement of sustainable development. Based on land-use data for the Bosten Lake Basin in 2000, 2005, 2010, 2015, and 2022, the PLUS and InVEST models are applied in this study to predict and analyze land-use changes and explore the spatial and temporal evolution characteristics of the region’s habitat quality. Additionally, we use a geographic detector model to reveal the drivers of spatial variation in habitat quality. The results show that: (1) Land use in Bosten Lake Basin is dominated by grassland and bare land, with an area share of 93.21%. Habitat quality shows a trend of degradation followed by improvement, with a spatial pattern of high in the northwest and low in the southeast. (2) Habitat quality in 2030 increased from 2022 in all cases, with a mean of 0.354 for the natural development scenario, a maximum of 0.355 for the ecological development scenario, and a minimum of 0.353 for the economic development scenario. (3) The main drivers affecting habitat quality in the Bosten Lake watershed are DEM, mean annual precipitation (MAP), and GDP per capita. X1∩X4 (0.50) and X4∩X10 (0.51) are the interaction factors with the largest dominant effect in 2000, 2010 and 2020, respectively.

Trends in temperature and precipitation at high and low elevations in the main mountain ranges of the Iberian Peninsula (1894–2020): The Sierra Nevada and the Pyrenees

AbstractThis study describes temperature and precipitation trends in the two National Parks located in the two highest mountain ranges on the Iberian Peninsula: the Sierra Nevada (Sierra Nevada National Park, SN) and the Pyrenees (Aigüestortes i Sant Maurici National Park, ASM). Special focus is placed on analysing disparities between the lowlands and the highlands, as well as the agreement between observational data and grid data (IBERIA01 and E‐OBS). For this purpose, a quality‐controlled and homogeneity‐adjusted database of the daily maximum temperature, minimum temperature and precipitation (SMADS database) has been generated. Regional trends in mean temperature indicate that warming in ASM (0.17°C·decade−1) was greater than in the Sierra Nevada (SN) (0.13°C·decade−1) in the longest joint period, 1930–2020. For annual precipitation, the trends over the past nine decades were negative, although not significantly. Only the summer in SN showed a significant negative trend, which has intensified in recent decades to −13.4%·decade−1 for 1975–2020. A parallel evolution was observed in the annual mean temperature of the highlands (>1500 m) and lowlands (<1500 m) of ASM, with a common trend of 0.17°C·decade−1, while in SN negative elevation‐dependent warming was detected. Differences between lowlands and highlands were also noted in precipitation trends in both mountain ranges: a positive trend in precipitation was found in the lowlands while in the highlands practically null trends (ASM) or decreasing precipitation trends (SN) were detected. The comparison of the Spanish Mountain Adjusted Daily Series (SMADS) results with the IBERIA01 and E‐OBS grid series yielded differences no greater than ±0.2°C·decade−1. No notable differences were detected between the regional trends calculated with observational series or with grid series. These results worsened when the differences in the trends detected in the individual observed temperature series were compared against the corresponding grid series.

Agricultural Land Suitability Assessment Based on GIS at the County Scale in Yibin, China

As agricultural land resources scarce, food security has emerged as a pressing global concern. Conducting a suitability assessment of agricultural land is crucial for agricultural resources and food security. To establish an evaluation index system, we incorporated land, water, climate, and society four dimensions of 16 indicators. And we incorporated Entropy Weight Method (EWM), an objective method, with integrated evaluation model to assess agricultural land suitability in Yibin. Based on actual agricultural production, areas of land of urban construction, rural settlement and mining and water are subtracted. The Findings found that agricultural land suitability in Yibin presented a significant spatial heterogeneity. Areas with suitability and relative suitability accounted for 57.61% of Yibin’s land areas, which suggest Yibin has an abundance of agricultural land resources. Regions moderately suitable predominantly lie in the western and southern areas, covering 32.22% of the land area. Generally suitable areas accounted for 10.03% of Yinbin’s land areas, spatial distribution of which is similar to moderately suitable regions. Moderately and generally areas are potential areas for agricultural production. And regions for unsuitable accounted for only 0.14% of land areas. Overall, results mentioned above indicate that Yibin's agricultural land resources are in good condition. Considered terrain and water sources, this study revealed that the spatial distribution of topography and annual precipitation in Yibin closely mirrored both suitable and relatively suitable regions.

Leaf wax n-alkane distribution and hydrogen isotopic fractionation in fen plant communities of two Mediterranean wetlands (Tenaghi Philippon, Nisí fen—Greece)

Many continental paleoclimate archives originate from wetland sedimentary sequences. While several studies have investigated biomarkers derived from peat-generating vegetation typical of temperate/boreal bogs (e.g., Sphagnum), only scant information is available on emergent plants predominant in temperate/subtropical coastal marshlands, peri-lacustrine and fen environments. Here, we address this gap, focusing on two wetlands in the Mediterranean (Nisí fen and Tenaghi Philippon, Greece). We examined the concentration, homologue distribution, and hydrogen stable isotopic composition (δ2H) of leaf wax n-alkanes in 13 fen plant species, their surrounding soil, and surface water during the wet growing season (spring) and the declining water table period (summer). Our findings indicate that local graminoid species primarily contribute to the soil n-alkane signal, with a lesser influence from forbs, likely owing to differences in morphology and vegetation structure. The δ2H values of surface and soil water align with local average annual precipitation δ2H, reflecting winter-spring precipitation. Consistently, the average δ2H of local surface, soil, and lower stem water showed negligible evaporative enrichment, confirming minimal 2H-fractionation during water uptake. We find that δ2H values of source water for wax compound synthesis in local fen plants accurately mirror local annual precipitation. Furthermore, despite differences between leaves and lower stems in n-alkane production rates, their δ2H values exhibit remarkable similarity, indicating a shared metabolic substrate, likely originating in leaves. Our net 2H-fractionation values (i.e., precipitation to leaf n-alkanes) align with those in Chinese highlands and other similar environments, suggesting consistency across diverse climatic zones. Notably, our data reveal a seasonal decrease in the carbon preference index (CPI) in plant samples, indicating wax lipid synthesis changes associated with increased aridity. Additionally, we introduce a new parity isotopic difference index (PID) based on the consistent δ2H difference between odd and even n-alkane homologues. The PID demonstrates a strong anticorrelation with plant CPI, suggesting a potential avenue to trace long-term aridity shifts through δ2H analysis of odd and even n-alkane homologues in sedimentary archives. While further development of the PID is necessary for broad application, these findings highlight the intricate interplay between plant physiology, environmental parameters, and sedimentary n-alkanes in unravelling past climatic conditions.