Climate Types Research Articles

Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)

Abstract. This work presents the first step in the development of the VISION toolkit, a set of Python tools that allows easy, efficient, and more meaningful comparison between global atmospheric models and observational data. Whilst observational data and modelling capabilities are expanding in parallel, there are still barriers preventing these two data sources from being used in synergy. This arises from differences in spatial and temporal sampling between models and observational platforms: observational data from a research aircraft, for example, are sampled on specified flight trajectories at very high temporal resolution. Proper comparison with model data requires generating, storing, and handling a large number of highly temporally resolved model files, resulting in a process which is data-, labour-, and time-intensive. In this paper we focus on comparison between model data and in situ observations (from aircraft, ships, buoys, sondes, etc.). A standalone code, In-Situ Observations Simulator, or ISO_simulator for short, is described here: this software reads modelled variables and observational data files and outputs model data interpolated in space and time to match observations. These model data are then written to NetCDF files that can be efficiently archived due to their small sizes and directly compared to observations. This method achieves a large reduction in the size of model data being produced for comparison with flight and other in situ data. By interpolating global gridded hourly files onto observation locations, we reduce data output for a typical climate resolution run, from ∼3 Gb per model variable per month to ∼15 Mb per model variable per month (a 200-times reduction in data volume). The VISION toolkit is relatively fast to run and can be automated to process large volumes of data at once, allowing efficient data analysis over a large number of years. Although this code was initially tested within the Unified Model (UM) framework, which is shared by the UK Earth System Model (UKESM), it was written as a flexible tool and it can be extended to work with other models.

From Dry to Temperate: How Climate Change Alters Growing Seasons?

ABSTRACTThe thermal growing season, which represents a plant's theoretical growth season, is a key indicator of phenology's response to climate change. Using thermal growing season indices (start, end and length) and their sensitivity to air temperature, this study examines how climate change impacts them. For various climate types of Iran, Mann–Kendall and Sen's slope tests were applied to examine trends in thermal growing season indices at two temperature thresholds: 5°C (for cold‐season plants) and 10°C (for tropical plants) between 1995 and 2020. Using a novel heuristic algorithm, multiple linear regressions were used to determine the most influential seasonal air temperature indices including mean, range and extreme on thermal growth indices as well. Plants in cold and temperate climates experienced significant early onset and lengthening of their growing seasons, with tropical plants on northern coasts experiencing the earliest onset (14.7 days/decade) and the lengthening growing season (16 days/decade). For plants in cold climates, the end of the growing season was also delayed (5 days/decade). The onset growth season was most sensitive to spring minimum and average temperatures in cold and temperate climates, while it was most sensitive to winter average temperatures in dry climates. In cold climates, changing spring and winter temperature ranges also affected the onset of the growing season, while in dry climates, changing autumn temperature ranges affected the end of the growing season. However, extreme temperatures only affect the end of the growing season in temperate climates. Furthermore, the early onset of the growing season is the primary factor contributing to the lengthening of the growing season in all climates. The findings of this study can assist in developing and implementing agriculture and water resource management strategies that mitigate climate change's adverse effects.

Fate and Transport of Heavy Metals in Soil, Surface Water, and Groundwater: Implications for Environmental Management

Critical challenges caused by heavy metals, such as hexavalent chromium, arsenic, and cadmium, emanate from their persistence and toxicity. This work discusses the fate and transport of heavy metals in the soil, surface water, and groundwater, focusing on their sources, pathways, and mechanisms of mobility. The research, therefore, underlines the key processes governing the behavior of heavy metals in environmental media by using a comprehensive review of field data and advanced modeling techniques. It becomes evident that mining, discharge of industrial waste, and agricultural activities are the predominant anthropogenic sources of contamination. Besides these factors, speciation and, further, the bioavailability of metals depend upon the climatic and soil type, which affects the paths of transport of these species. This research has shown a dire need for some effective environmental management strategies using remediation technologies and regulatory frameworks that might help minimize the risks to ecosystems and human health.

Exploring the Bioactives and Therapeutic Properties of Traditional Rice Landraces for Human Health and Food Security: A Review

Rice has been found to have anti-cancer, anti-diabetic, anti-inflammatory properties and it is believed to be due to its antioxidant properties. The research work on characterization of rice landraces for nutritional and medicinal properties is gaining importance due to increase in lifestyle related health issues such as diabetes, cancer, heart problems, obesity etc and increasing trend among consumers and profitable market is reversing and focusing towards traditional rice landraces. These rice land races exploited by the rural folks to treat to treat skin diseases, blood pressure, fever rheumatism, lactation and also uses as health tonic. Some of the rice landraces used in sidda and ayurvedic for exploiting curative value and is used in many medicinal preparations. Based on Vedic evidences, India was had more than 2,00,000 (2 lakh) rice varieties which is an huge biodiversity, genetically rich nation, no other nation in the world as that resources. The rice landraces cultivation are confined to certain pockets depending on the suitability of local climate and soil type, under varied quantity of water requirement, also having resistance to pest and diseases. Currently, a few hundreds of traditional landraces are in existenceand being cultivated in small pockets by farmers. Conserve the available landraces, the nutraceutical and nutritional properties in rice landraces, needs to be examined and validated with popularization. Indigenous cultivars will help for explore the scientific basis of therapeutic values by the scientist for sustaining food as well as the nutritional security and human health.

Assessment of a Temperature-Based Artificial Neural Network Designed for Global Solar Radiation Estimation in Regions with Sparse Experimental Data

The aim is to evaluate a model of monthly mean global solar radiation based on a simple ANN that uses geographic and temperature data as input variables and is designed for estimations in regions with few radiometric stations. Using data from 414 Spanish stations, the performance of the model is evaluated when both the number and the percentage of data collected for training the network are significantly modified while maintaining the clustering algorithms. The statistical indicators obtained show a compromise between achieving a lower mean error for all stations and limiting the maximum error at each station. In the worst case, the average error is less than 10% for all stations, and the maximum local error only exceeds 20% in less than 2% of the estimates. The least accurate predictions seem to be related to climate types where the clearness index tends to be higher in winter than in summer, which is the case in some locations on the northern Spanish coast. The results are consistent with estimates obtained for 16 non-Spanish stations, selected within the same input data range, suggesting that the variation of the clearness index over the year could be an important factor for local climate characterization.

Solar Energy in Buildings: Feasibility Analysis of Integrated and Conventional Photovoltaic Panels

The feasibility study is crucial for decision-making in the investment stage of photovoltaic systems projects. A cost–benefit analysis for a project should not be evaluated solely in terms of money in-flows and outflows; it is important to consider other characteristics such as climate, solar irradiation, and the hours of sunshine in different spaces, as well as the electricity rates of the electricity supply company. Therefore, analyzing and simulating the performance conditions, both technical and economic, of photovoltaic systems is key. The objective of this study was to analyze the investment models in two types of photovoltaic systems: one integrated into the construction and the other conventional in a building in the Mexican Republic, considering ideal conditions, thus evaluating the energy efficiency in cities, as they consume around two-thirds of the world’s energy and are responsible for 70% of global greenhouse gas emissions. The methodological proposal was to select a location, determine the predominant type of climate and collect data on solar radiation, the electricity supplier rates, the profitability for a cost–benefit analysis, and the inflation rates to determine the viability of a project that comprehensively covers the variables for decision-making.

A Snow-Based Hydroclimatic Aggregate Drought Index for Snow Drought Identification

Climate change has increased the risk of snow drought, which is associated with a deficit in snowfall and snowpack. The objectives of this research are to improve drought identification in a warming climate by developing a new snow-based hydroclimatic aggregate drought index (SHADI) and to assess the impacts of snowpack and snowmelt in drought analyses. To derive the SHADI, an R-mode principal component analysis is performed on precipitation, snowpack, surface runoff, and soil water storage. Then, a joint probability distribution function of drought frequencies and drought classes, conditional expectation, and k-means clustering are used to categorize droughts. The SHADI was applied to the Red River of the North Basin (RRB), a typical cold climate region, to characterize droughts in a mostly dry period from 2003 to 2007. The SHADI was compared with the hydroclimatic aggregate drought index (HADI) and U.S. drought monitor (USDM) data. Cluster analysis was also utilized as a benchmark to compare the results of the HADI and SHADI. The SHADI showed better alignment with cluster analysis results than the HADI, closely matching the identified dry/wet conditions in the RRB. The major differences between the SHADI and HADI were observed in cold seasons and in transition periods (dry to wet or wet to dry). The derived variable threshold levels for different categories of drought based on the SHADI were close to, but different from, those of the HADI. The SHADI can be used for short-term lead prediction of droughts in cold climate regions and, in particular, can provide an early warning for drought in the warming climate.

Soil Fertility and Influencing Factors of Cultivated Land Based on the Geodetector

Taihe County in Jiangxi Province was chosen as the study area to analyze the soil fertility condition and affecting elements of cultivation at the county level. Classical statistics, geostatistics, and geodetector were utilized to examine soil fertility quality and investigate its primary affecting aspects based on experimental data from 206 cultivated soil samples. The results showed that： ① Taihe County had an average soil pH of 4.87, indicating slightly acidic soil. A total of 97.39% of the sample sites had CEC contents of four and five levels, and the EC content levels were concentrated in the second level, 63.48% of the SOC contents were in the medium levels, 73.92% of the TN contents were higher than 1.5 g·kg-1, 72.17% of the TP contents were lower than 0.6 g·kg-1, and the AP contents were in the high level, greater than 20 mg·kg-1, accounting for 86.09% of the sample sites. The soil fertility in the research area was poor, and the soil was of light and medium salinization, lacking organic matter and total phosphorus. The lump gold effect values of pH, EC, AP, SOC, TN, and TP were 0.17, 0.21, 0.18, 0.52, 0.45, and 0.59, respectively. The spatial correlation between soil pH, EC, and AP was strong, while soil SOC, TN, and TP had a moderate degree of spatial correlation. The spatial variation of soil fertility in Taihe County was influenced by both structural factors （topography, climate, and soil type） and random factors （fertilization, cultivation methods, soil pollution, etc.）. ② The results of the weight coefficients of farmland soil fertility were TN （0.210）, SOC （0.195）, EC （0.190）, CEC （0.171）, TP （0.170）, AP （0.117）, and pH （-0.053）. Soil TN, SOC, and EC were key indicators that affected farmland soil fertility in the study area. The comprehensive score grading of soil fertility quality showed that most of the soil fertility quality in the study area was level three, and the soil fertility in Shangmo Township was relatively fertile. The soil fertility quality level was Level 2 and Level 3. The soil fertility in Yanxi Town and Wanhe Town was relatively poor, and the soil fertility quality level was Level 3 and Level 4. ③ X54, X31, X32, X21, and X14 were the main driving factors affecting farmland soil fertility. The explanatory power of each factor interaction was greater than that of single factor interactions, manifested in two types： double factor enhancement and nonlinear synergistic effect. The soil fertility of farmland was the result of the joint action of multiple influencing factors. The results of the research revealed the status quo and spatial distribution characteristics of soil fertility in the study area, investigated the factors influencing soil fertility in farmland, and analyzed the foundation for improving the intrinsic quality and output capacity of cultivable land and the ecological environment of agriculture.

Analyze of The Effects of Possible Climate Change Scenarios for Biomass and Grain Yields of Sunflower and Winter Wheat with AquaCrop Model in The Thrace Region of Türkiye

Prediction of crop yield and biomass in agricultural production is crucial for both food safety and national economic projections. This study aimed to determine the relationship between the effects of climate change and biomass and grain yield of two crops (winter wheat and sunflower) at two locations, Kirklareli (KRK), Edirne-Orhaniye (EOR), with different soil textures, in the Thrace region. The scenarios (n=S1, S2,…,S65) of sensitivity analysis established by considering the expected trend of climate change were evaluated in terms of biomass and grain yield for sunflower and winter wheat crops with the AquaCrop model. The model predicted the highest losses of grain yield and biomass, when the air temperature was increased by 5 °C and the precipitation was decreased by 50% during the growing seasons of both crops (in the scenario S42). In the scenarios where only temperature was increased, grain and biomass yield values of sunflower was decreased, while those of winter wheat was increased. The combined effects of increased global solar radiation and decreased temperature had a negative effect on wheat production at EOR. For both sunflower and wheat, the most negative impacts on yield and biomass production were observed with the combined scenarios of various temperature increases and precipitation decreases during each growing season at each location. According to the simulation results of the defined single and combined scenarios in both spatial areas, while the grain and biomass yields of the summer planted sunflower plant were negative linear relations every scenario, non-linear relations were determined in the yields of the winter-wheat plant. Finally, with the defined sensitivity scenarios, the correlation coefficients between biomass and grain yield of sunflower and winter wheat under similar climate but different soil types in two locations were found to be R2= 0.88 and 0.87 for KRK and R2 = 0.56, and 0.79, for EOR, respectively.

Influence of land-use type on earthworm diversity and distribution in Yunnan: Insights from soil properties

This study explores the soil biodiversity and distribution of earthworms in Yunnan Province. Employing a quadrat survey method, the province was divided into six climate types, among which four representative land-use types (arable land, wasteland, grassland, and garden) were selected for sampling of earthworms and soil. In total, 1984 earthworm individuals were gathered from 148 plots, representing 27 species occurrences across four families, with Moniligastridae being dominant. The present study emphasized that different land use modes can affect the distribution of earthworm communities; there are differences in soil physical and chemical properties under different land use types; therefore, various land use modes can further affect the density and biomass of earthworms by influencing soil physical and chemical properties. Soil properties such as SOM, TN, TK, and OP significantly affect earthworm communities. For example, SOM had a significant positive correlation with earthworm density in Wasteland and Arable land and a significant positive correlation with earthworm biomass in Grassland and Garden; in addition, soil temperature and TK content had a significant negative correlation with earthworm density in Garden. This study provides data support for understanding earthworm species diversity and its spatial distribution characteristics in Yunnan Province. It gives a scientific basis for further discussion of the influence of land use on soil fauna conservation and its ecological functions.

A113: The Impact of Motivational Climate on Class Engagement

Background/Purpose: An accomplishment within physical education classes involves actively involving students. Research underscores the importance of nurturing situational interest and self-efficacy to foster this engagement. Both self-determination theory and achievement goal theory propose that teachers can cultivate a supportive classroom environment, thereby boosting students' interest and confidence in their capabilities. Nevertheless, the transformable mechanism from motivational climate to actual class engagement needs further investigation. The purpose of this study was to examine the extent to which motivational climate variables (e.g., autonomy supportive climate, task-involving climate, and socially supportive climate) impacted student engagement via the mediative roles of situational interest and self-efficacy. Method: We employed a convenience sampling approach among 802 middle school students from 18 classes across three different levels of middle schools in Wuhan (52% male, average age 13, with 34.5%, 31.8%, and 33.7% in grades 7, 8, and 9, respectively). Validated surveys were administered in physical education classes for the purpose of the study. Path analyses and bootstrap methods were conducted. Results: All variables exhibited a normal distribution, with correlations ranging from 0.33 to 0.84. There was no apparent collinearity among study variables. Model fit indices indicated that the data fit the model well (RMSEA < 0.005, CFI and TLI > 0.95). The paths from task-involving climate and autonomy supportive climate to situational interest (β = 0.45, p < 0.01; β = 0.24, p < 0.01), as well as from task-involving climate to self-efficacy (β = 0.30, p < 0.01), were significant. Paths from situational interest and self-efficacy to student engagement were also significant (β = 0.51, p < 0.01; β = 0.36, p < 0.01). None of the direct paths from the three types of motivational climates to engagement were significant. Bootstrap analysis indicated significant mediating effects of situational interest on the relationships between task-involving climate, autonomy supportive climate, and class engagement. Self-efficacy also showed significant mediating effects on the relationship between task-involving climate and the engagement. Conclusion/Discussion: In crafting and executing PE programs, educators ought to adopt a "student-centered" methodology, prioritizing the establishment of nurturing teaching environments that inspire student dedication and offer suitable assistance and direction. This approach will promote students' feelings of competence and enthusiasm, ultimately fostering their motivation as well as their physical and mental engagement.

Analysis of Rainfall Projections in Historical and Future Periods Using Coupled Model Intercomparison Project (CMIP) Phase 6 in Indonesia

Abstract Climate change is a phenomenon that occurs today and has great potential in the future. The impact of this climate change phenomenon is hydrometeorological disasters such as 7loods, droughts, and storms, where the agricultural sector is the most vulnerable sector to the impact of these issues. Therefore, the aims of this study to assess the conditions that have occurred in the past (between 1950 - 2013) to project the potential that will occur in the future (between 2035 - 2080) of hydrometeorological disasters. The model results show that historically, areas with tropical rainfall (Af), tropical monsoon (Am), and tropical savanna (Aw) climate types experienced a decrease in total annual rainfall of up to 500 mm/year during 1950 - 2013. However, in contrast, future projections for the region show a signi7icant increase with a rainfall range of 3000 - 4500 mm/year. The above conditions will certainly spread to various problems in other agricultural cultivation environments such as soil capability levels to research results so that research on the study of rainfall conditions and hydrometeorological disasters is very important.

A Digital-based Model Proposal for Optimum Building Orientation in Architecture in Ecological Context Nur Sumeyye

In order to make optimum use of the heat energy coming from the sun and the cooling effect of the wind, it is very important that the buildings are positioned on the land in positions that can provide the highest level of user comfort with minimum energy consumption. Determining the layout of the building is a critical design parameter that affects energy consumption. However, when there are vistas such as sea, forest, etc. that are desired to be seen from the first degree interior volumes around the building, this factor becomes decisive in the building orientations. As a result of this, climatic comfort factors such as natural ventilation provided by wind and heat energy from the sun are ignored. While the orientation of the interior spaces towards the landscape is preferred by the users, the climate element and the comfort it provides should be the priority in the architectural design. In this study, an orientation optimization model has been proposed for building orientation based on utilizing vista and climatic data in the context of passive design. With the parametric and numerical-based approach developed in the study, the way to use the vista factor, which has a multivariate and complex structure, as an “input data” has been investigated. In order to test and verify the developed optimization model, “The Canal Istanbul” artificial waterway project area, which is a very up-to-date subject, was chosen as the plot research area. The Canal feasibility studies have been prepared by the authorities. The data obtained from these reports were used quantitatively in the model. In this context, the technical and ecological data of the canal route were investigated from the reports prepared for the Canal Istanbul route. Thus, as a result of the data accessed from various sources, the climate type and ecological characteristics of the region have been moved to a quantitative dimension as numerical data. An optimization model has been developed for optimum building orientation in terms of regional climate, taking into account the zoning decisions and basic planning criteria determined in the focus of these data. The developed model primarily places the building in the desired point position over the 1000 and 5000 zoning plans of the region, with the vista as priority. Afterwards, the model perceives the vista spline that enters the field of view of the building. Then, staying within the boundaries of this spline, it turns the structure in alternative directions and analyzes it according to each direction. At this stage, the model presents a mathematical dataset by comparing the alternative orientations of the building with the “optimal direction”, “prevailing wind direction” and “north direction” angles. Finally, these data are optimized within the model and suggestions are made to the designer to make a choice, based on the results obtained.

Comprehensive characterization of anthraquinones in Damnacanthus indicus using mass spectrometry molecular networking and metabolomics-based herb discrimination.

Damnacanthus indicus is a widely used folk medicine in China, renowned for its various bioactivities. The key active components, anthraquinones, have not been comprehensively profiled due to their complex chemical nature. Establishing a high-throughput strategy to systematically characterize these anthraquinones is essential. Additionally, the cultivation of D. indicus across various provinces results in significant quality differences in the harvested herbs. Thus, developing an effective strategy to distinguish herbs from different regions and identify characteristic chemical markers for quality evaluation and control is crucial. In this study, a strategy based on ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) was employed to systematically characterize the chemical composition of D. indicus. Mass spectrometry molecular networking was utilized to rapidly recognize and identify anthraquinones. Principal component analysis (PCA) was applied to cluster the herbs from different habitats, while partial least square discriminant analysis (PLS-DA) was used to screen for chemical markers distinguishing herb origins. The result showed that a total of 112 anthraquinones and 66 non-anthraquinone compounds were identified in D. indicus. The biosynthetic pathways of anthraquinones in this herb were proposed. PCA grouped 15 batches of herbs from different origins into three clusters, corresponding to the climate types of their habitats. PLS-DA identified 27 significant chemical markers that could robustly distinguish the geographical origins of the herbs. This study provides a valuable reference for the quality evaluation and control of D. indicus and offers a scientific basis for the pharmacological research and rational utilization of these medicinal resources.

High- and low-latitude forcings on regional hydroclimate variability in Northeast China during Marine Isotope Stage 2

The scarcity of well-dated, highly temporally resolved, paleoclimate records during the Marine Isotope Stage (MIS) 2 in Northeast (NE) China limits our understanding of the hydroclimate history in East Asian monsoon (EAM) region under different boundary conditions and the prediction of future hydroclimate changes. Meanwhile, it has not been comprehensively investigated how high- and low-latitude forcings, as crucial driving factors of global climate change, impact regional hydroclimate on various timescales during the MIS 2. This study applies phytolith-based principal component 1 scores, sum proportions of grain size-based end-members 2 and 3, and values of loss-on-ignition at 550 °C from the Dadong profile, to provide new evidence of hydroclimate changes during the MIS 2 in NE China. The results suggest that the regional humidity was low during the Last Glacial Maximum, and gradually increased during the subsequent Last Deglaciation. Additionally, the typical climate pattern of “warm-humid/cold-dry” in the EAM region was showed during a series of millennial oscillations. Combined with multiple records from NE China, it is observed that the orbital-scale hydroclimate changes during the MIS 2 were relatively consistent in different regions, and were mainly regulated by the ice sheet extents under the control of Northern Hemisphere high-latitude summer insolation. On the millennial scale, however, the hydroclimate changes suggested significant asynchrony or even anti-phase, indicating that the climate pattern may not always be similar to the typical EAM pattern. We propose that a series of sea-land-air interactions under the coupling of North Atlantic Deep Water activities in high latitudes and El Niño-Southern Oscillation in low latitudes, may be responsible for this complicated pattern. This study provides new insights into the climate evolution in NE china and its relationship with the high- and low-latitude forcings, which is beneficial for the explanation of mechanisms behind climate variability in this region.

A novel U-LSTM-AFT model for hourly solar irradiance forecasting

Countries emphasize the development of renewable energy to combat climate change, ensure energy security, and promote sustainable economic growth. Grid-connected photovoltaic (PV) power generation, a key to energy transition, can significantly reduce power generation costs. Still, its output power is unstable due to the weather, so an accurate solar irradiance forecast is crucial. The current hybrid model mainly suffers from inadequate feature extraction and insufficient time-dependent processing when dealing with complex time series data, which affects prediction accuracy. Therefore, a new solar irradiance forecast model, U-Shaped LSTM-AFT (U-LSTM-AFT) is proposed in this paper, which draws on the architecture and ideas of U-Net. The model improves the efficiency of feature extraction through the up-sampling and down-sampling modules while combining with smaller pooling kernels to optimize feature processing further. In addition, the model introduces the Long Short-Term Memory Network (LSTM) and Attention-Free Transformer (AFT) to enhance prediction accuracy and achieve more efficient forecast performance. The method was validated using three real-world irradiance datasets from diverse US locations representing different climate types. The experimental results demonstrate that the proposed U-LSTM-AFT model achieves higher forecasting accuracy in predicting PV power generation than traditional models like LSTM and U-Net, with significant performance improvements. Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Normalized Root Mean Square Error (nRMSE), R-squared (R2), and Forecast Skill (FSnRMSE) are the performance evaluation metrics of this forecasting scheme. The three datasets reached mean values of 23.076 W/m2, 50.142 W/m2, 0.046, 98.680 %, and 0.238, respectively.

Cultivation Practices Affect Biomass Yield and Quality of “Felina 32”, an Industrial Hemp Variety

Hemp is a multipurpose crop that produces high amounts of lignocellulosic biomass. There are few studies dealing with hemp’s biomass production (lignocellulosic and fiber) under cropping strategies such as irrigation and nitrogen fertilizer. Therefore, the aim of the current study was to assess the effect of irrigation and N-fertilization on the lignocellulosic biomass of one of the most well-known industrial hemp (Cannabis sativa L.) varieties worldwide (Felina 32) under a typical Mediterranean climate. For the purposes of this study, a field experiment was conducted in central Greece (Thessaly region) over the cultivating years 2022 and 2023. We determined the produced biomass dry yield and the dry biomass yield vs. N-uptake relation, as well as quality characteristics for hemp (cv. Felina 32) under three irrigation (I1: 33%, I2: 66%, and I3: 100% ETo) and three N-fertilization levels (N1: 0, N2: 70, and N3: 140 kg ha−1). A significant difference in the dry biomass yield was found, ranging between 10–11.2 t ha−1 using I2 and/or I3 irrigation levels and remaining at 8.6 t ha−1 with lower irrigation (I1). In terms of fertilization factor, it appeared that in samplings where statistically significant changes were observed, all degrees of fertilization differed from one another, with the N3 treatment exhibiting the highest production (11.4 t ha−1). The average protein content varied between 10% in 2023 and 14% in 2023. A linear biomass yield–nutrient uptake relationship was found with high R2, pointing to a nitrogen use efficiency of 55.15 kg kg−1. Thus, it would seem that nitrogen fertilization and irrigation are both crucial factors of industrial hemp cultivation, helping to raise the crop’s overall yield of lignocellulosic biomass. The introduction of hemp into land-use systems necessitates thorough evaluation, as hemp shows considerable potential as a crop that can yield substantial quantities of above-ground biomass (lignocellulosic: stems and fibers). This is especially true in regions where irrigation is possible, and the application of nitrogen fertilizers can further enhance these yields.

Whether niche changes promote the evolution of species: a case study of Paeonia in Asia and North America.

Ecological changes have been observed to promote rates of lineage diversification, yet the precise roles of ecological factors, species evolution, and environmental variability in driving species diversity remain research hot spots. The association between ecological change and lineage diversification, particularly with regard to the size of the time scale, remains poorly understood. To explore whether ecological change facilitates species evolution, we focused on the unique family Paeoniaceae, which encompasses both herbaceous and woody taxa, to investigate the evolutionary rates. As a unique family characterized by a single genus of angiosperms and comprising various climatic types, the ecological niche changes of Paeoniaceae are closely associated with the evolution, making it an ideal model for conducting association analysis. In this study, we integrated the molecular fragments and ecological factors to explore the relationship between species evolution and niche changes in Paeoniaceae. The phylogenetic tree revealed that Paeoniaceae forms a sister relationship with Penthoraceae, Haloragidaceae, Iteaceae, Crassulaceae, and Saxifragaceae, constituting an independent clade based on the positive selection of molecular fragments including two protein-coding genes and eight non-coding regions. The divergence time was estimated to be between 102 and 116 Mya (Million years ago). The phylogenetic tree within Paeonia revealed a clear division into three groups: sections of Paeonia, Moutan, and Onaepia with high support values for each branch based on the ten positive selection of molecular fragments. The rapid rate of evolution observed in Paeonia, about 0-5 Mya. In addition, ecological niche modeling showed that the potential distributions for Paeonia expanded from middle Asia to eastern Asia, and from central North America to the Northern part of North America during the Last Glacial Maximum (LGM) to Mid Holocene (MID) period. This suggests that Paeonia continuously adapted to changing ecological environments over time. Compared to the rate of climatic niche divergence and lineage diversification, the ecological niche of Paeonia underwent significant changes during the period of 3-11 Mya, occurring 5 Mya earlier than the period of evolutionary rate change. These findings offer comprehensive insights into the relationship between niche change and the evolution of species, providing valuable perspectives for further ecological cultivation efforts.

Convergence and differentiation of tree radial growth in the Northern Hemisphere

Tree radial growth records both ontogenetic growth trends and environmental information. Although the former is usually excluded from climate-growth analyses, its gradual changes have a more profound effect on forest carbon sequestration. Elucidating the kinetic mechanism behind this intrinsic trend will greatly improve our understanding and prediction of climate-growth relationships. The iterative growth model (IGM) and its extensions link organism growth, lifespan, and respiration, providing important insights into this trend. Here, we extended the IGM to the tree-ring scale (IGMR) and used tree-ring width datasets across the Northern Hemisphere to analyse the constraints of tree ontogenetic growth trends on radial growth rate (along the radius gradient). On this basis, we further elucidated the convergence and differentiation of these growth trends across different climate types and clades. The results showed that: (i) ontogenetic growth trends of trees cause the radial growth rate to follow a typical unimodal pattern along the radius gradient. (ii) This unimodal pattern is a function of tree radial size, metabolic exponent, and maintenance metabolic rate, constraining the response of tree radial growth to climate. (iii) Ontogenetic growth trends result in an inherent trade-off between tree radial growth rate and lifespan. In conclusion, different growth drivers do not alter the constraining effect of tree size on radial growth. Ontogenetic growth trends should be considered in future studies of climate-growth relationships.

A study of the correlation between summer outdoor meteorological parameters and hydropower station ventilation schemes

For an underground hydropower stations, understanding the heat and mass transfer behaviour of outdoor air flowing through ventilation tunnel can help improve the design of ventilation systems and reduce energy consumption. The aim of this paper is to investigate the influences of summer outdoor meteorological parameters on the tandem ventilation process and the designed parameter requirements in the main plant. A series of field tests and numerical simulations were conducted to determine the variations in outdoor air parameters passing through the ventilation tunnel. Theoretical analyses were developed to clarify the variations in air parameters through the ventilation process in i-d diagram. Results show that the outdoor meteorological temperature has the largest influence on heat transfer between the ventilation tunnel and airflow. The relative humidity in the air at the tunnel outlet could reach 90% under most conditions. The reasonable air supply area and the critical air supply temperature of the mechanical ventilation were determined. Once the outdoor air passes through the ventilation tunnel and the i-d diagram falls in air supply area II, the outlet air can be directly supplied to the main plant. For conditions that did not satisfy the mechanical air supply scheme, the measure of setting dehumidifiers at 200—250 m arranging intervals in the tunnel were proposed to improve the air humidity. Based on the meteorological parameters of typical climate zones in China, a reasonable air supply scheme for the main plant was determined. The results could technically guide the ventilation design of underground hydropower stations, which can help to enchance energy-efficient and low-carbon ventilation schemes.