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22 pages, 3231 KiB  
Article
Evapotranspiration in a Small Well-Vegetated Basin in Southwestern China
by Zitong Zhou, Ying Li, Lingjun Liang, Chunlin Li, Yuanmei Jiao and Qian Ma
Sustainability 2025, 17(15), 6816; https://doi.org/10.3390/su17156816 - 27 Jul 2025
Viewed by 257
Abstract
Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where [...] Read more.
Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where extreme drought events are prevalent due to complex terrain and climate warming, ET becomes a key factor in understanding water availability and drought dynamics. Using the SWAT model, this study investigates ET dynamics and influencing factors in the Jizi Basin, Yunnan Province, a small basin with over 71% forest coverage. The model calibration and validation results demonstrated a high degree of consistency with observed discharge data and ERA5, confirming its reliability. The results show that the annual average ET in the Jizi Basin is 573.96 mm, with significant seasonal variations. ET in summer typically ranges from 70 to 100 mm/month, while in winter, it drops to around 20 mm/month. Spring ET exhibits the highest variability, coinciding with the occurrence of extreme hydrological events such as droughts. The monthly anomalies of ET effectively reproduce the spring and early summer 2019 drought event. Notably, ET variation exhibits significant uncertainty under scenarios of +1 °C temperature and −20% precipitation. Furthermore, although land use changes had relatively small effects on overall ET, they played crucial roles in promoting groundwater recharge through enhanced percolation, especially forest cover. The study highlights that, in addition to climate and land use, soil moisture and groundwater conditions are vital in modulating ET and drought occurrence. The findings offer insights into the hydrological processes of small forested basins in southwestern China and provide important support for sustainable water resource management and effective climate adaptation strategies, particularly in the context of increasing drought vulnerability. Full article
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31 pages, 6501 KiB  
Review
From Hormones to Harvests: A Pathway to Strengthening Plant Resilience for Achieving Sustainable Development Goals
by Dipayan Das, Hamdy Kashtoh, Jibanjyoti Panda, Sarvesh Rustagi, Yugal Kishore Mohanta, Niraj Singh and Kwang-Hyun Baek
Plants 2025, 14(15), 2322; https://doi.org/10.3390/plants14152322 - 27 Jul 2025
Viewed by 721
Abstract
The worldwide agriculture industry is facing increasing problems due to rapid population increase and increasingly unfavorable weather patterns. In order to reach the projected food production targets, which are essential for guaranteeing global food security, innovative and sustainable agricultural methods must be adopted. [...] Read more.
The worldwide agriculture industry is facing increasing problems due to rapid population increase and increasingly unfavorable weather patterns. In order to reach the projected food production targets, which are essential for guaranteeing global food security, innovative and sustainable agricultural methods must be adopted. Conventional approaches, including traditional breeding procedures, often cannot handle the complex and simultaneous effects of biotic pressures such as pest infestations, disease attacks, and nutritional imbalances, as well as abiotic stresses including heat, salt, drought, and heavy metal toxicity. Applying phytohormonal approaches, particularly those involving hormonal crosstalk, presents a viable way to increase crop resilience in this context. Abscisic acid (ABA), gibberellins (GAs), auxin, cytokinins, salicylic acid (SA), jasmonic acid (JA), ethylene, and GA are among the plant hormones that control plant stress responses. In order to precisely respond to a range of environmental stimuli, these hormones allow plants to control gene expression, signal transduction, and physiological adaptation through intricate networks of antagonistic and constructive interactions. This review focuses on how the principal hormonal signaling pathways (in particular, ABA-ET, ABA-JA, JA-SA, and ABA-auxin) intricately interact and how they affect the plant stress response. For example, ABA-driven drought tolerance controls immunological responses and stomatal behavior through antagonistic interactions with ET and SA, while using SnRK2 kinases to activate genes that react to stress. Similarly, the transcription factor MYC2 is an essential node in ABA–JA crosstalk and mediates the integration of defense and drought signals. Plants’ complex hormonal crosstalk networks are an example of a precisely calibrated regulatory system that strikes a balance between growth and abiotic stress adaptation. ABA, JA, SA, ethylene, auxin, cytokinin, GA, and BR are examples of central nodes that interact dynamically and context-specifically to modify signal transduction, rewire gene expression, and change physiological outcomes. To engineer stress-resilient crops in the face of shifting environmental challenges, a systems-level view of these pathways is provided by a combination of enrichment analyses and STRING-based interaction mapping. These hormonal interactions are directly related to the United Nations Sustainable Development Goals (SDGs), particularly SDGs 2 (Zero Hunger), 12 (Responsible Consumption and Production), and 13 (Climate Action). This review emphasizes the potential of biotechnologies to use hormone signaling to improve agricultural performance and sustainability by uncovering the molecular foundations of hormonal crosstalk. Increasing our understanding of these pathways presents a strategic opportunity to increase crop resilience, reduce environmental degradation, and secure food systems in the face of increasing climate unpredictability. Full article
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25 pages, 1668 KiB  
Article
The Impact of Climate Change on the Sustainability of PGI Legume Cultivation: A Case Study from Spain
by Betty Carlini, Javier Velázquez, Derya Gülçin, Víctor Rincón, Cristina Lucini and Kerim Çiçek
Agriculture 2025, 15(15), 1628; https://doi.org/10.3390/agriculture15151628 - 27 Jul 2025
Viewed by 148
Abstract
Legume crops are sensitive to shifting environmental conditions, as they depend on a narrow range of climatic stability for growth and nitrogen fixation. This research sought to assess the sustainability of Faba Asturiana (FA) cultivation under current and future climatic scenarios by establishing [...] Read more.
Legume crops are sensitive to shifting environmental conditions, as they depend on a narrow range of climatic stability for growth and nitrogen fixation. This research sought to assess the sustainability of Faba Asturiana (FA) cultivation under current and future climatic scenarios by establishing generalized linear mixed models (GLMMs). Specifically, it aimed to (1) investigate the effects of significant climatic stressors, including higher nighttime temperatures and extended drought periods, on crop viability, (2) analyze future scenarios based on Representative Concentration Pathways (RCP 4.5 and RCP 8.5), and (3) recommend adaptive measures to mitigate threats. Six spatial GLMMs were developed, incorporating variables such as extreme temperatures, precipitation, and the drought duration. Under present-day conditions (1971–2000), all the models exhibited strong predictive performances (AUC: 0.840–0.887), with warm nights (tasminNa20) consistently showing a negative effect on suitability (coefficients: −0.58 to −1.16). Suitability projections under future climate scenarios revealed considerable variation among the developed models. Under RCP 4.5, Far Future, Model 1 projected a 7.9% increase in the mean suitability, while under RCP 8.5, Far Future, the same model showed a 78% decline. Models using extreme cold, drought, or precipitation as climatic stressors (e.g., Models 2–4) revealed the most significant suitability losses under RCP 8.5, with the reductions exceeding 90%. In contrast, comprising variables less affected by severe fluctuations, Model 6 showed relative stability in most of the developed scenarios. The model also produced the highest mean suitability (0.130 ± 0.207) in an extreme projective scenario. The results highlight that high night temperatures and prolonged drought periods are the most limiting factors for FA cultivation. ecological niche models (ENMs) performed well, with a mean AUC value of 0.991 (SD = 0.006) and a mean TSS of 0.963 (SD = 0.024). According to the modeling results, among the variables affecting the current distribution of Protected Geographical Indication-registered AF, prspellb1 (max consecutive dry days) had the highest effect of 28.3%. Applying advanced statistical analyses, this study provides important insights for policymakers and farmers, contributing to the long-term sustainability of PGI agroecosystems in a warming world. Full article
(This article belongs to the Special Issue Sustainable Management of Legume Crops)
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22 pages, 1649 KiB  
Article
High Warming Restricts the Growth and Movement of a Larval Chinese Critically Endangered Relict Newt
by Wei Li, Shiyan Feng, Shanshan Zhao, Di An, Jindi Mao, Xiao Song, Wei Zhang and Aichun Xu
Biology 2025, 14(8), 942; https://doi.org/10.3390/biology14080942 - 27 Jul 2025
Viewed by 252
Abstract
Amphibians are the most threatened vertebrates, yet their resilience in relation to growth and locomotor performance with rising temperatures remains poorly understood. Here, we chose a critically endangered amphibian—the Chinhai spiny newt (Echinotriton chinhaiensis)—as the study species and set four water [...] Read more.
Amphibians are the most threatened vertebrates, yet their resilience in relation to growth and locomotor performance with rising temperatures remains poorly understood. Here, we chose a critically endangered amphibian—the Chinhai spiny newt (Echinotriton chinhaiensis)—as the study species and set four water temperature gradients (20 °C, 24 °C, 28 °C, and 32 °C) to simulate climate changes. The thermal performance to climate warming was quantified by measuring morphometric parameters, basal metabolic rate (oxygen consumption rate), and the locomotor performance of Chinhai spiny newt larvae. We found that the optimal temperature range for Chinhai spiny newt larvae is 24–28 °C. Within the temperature range of 24–28 °C, the growth, oxygen consumption rate, and locomotor performance of the larvae were positively correlated with temperature. High temperatures inhibited larval growth, oxygen consumption rate, and locomotor performance, and the temperature threshold was 32 °C. In addition, Chinhai spiny newt larvae are more sensitive to acute temperature changes, meaning that climate-driven extreme events (e.g., heatwaves and droughts) pose significant threats to their larvae. The optimal temperature range obtained from this study could guide artificial breeding and early warming; future studies should integrate controlled temperature fluctuations in order to understand the thermal adaption of this threatened species. Full article
(This article belongs to the Special Issue Progress in Wildlife Conservation, Management and Biological Research)
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21 pages, 3566 KiB  
Article
Dendrometer-Based Analysis of Intra-Annual Growth and Water Status in Two Pine Species in a Mediterranean Forest Stand Under a Semi-Arid Climate
by Mehmet S. Özçelik
Forests 2025, 16(8), 1229; https://doi.org/10.3390/f16081229 - 26 Jul 2025
Viewed by 246
Abstract
Stem radius growth (GRO), tree water deficit (TWD), and maximum daily shrinkage (MDS) were monitored throughout 2023 in a semi-arid Mediterranean forest stand in Burdur, Türkiye, where Pinus nigra subsp. pallasiana (Lamb.) Holmboe and Pinus brutia Ten. naturally co-occur. These indicators, derived from [...] Read more.
Stem radius growth (GRO), tree water deficit (TWD), and maximum daily shrinkage (MDS) were monitored throughout 2023 in a semi-arid Mediterranean forest stand in Burdur, Türkiye, where Pinus nigra subsp. pallasiana (Lamb.) Holmboe and Pinus brutia Ten. naturally co-occur. These indicators, derived from electronic band dendrometers, were analyzed in relation to key climatic variables. Results indicated that P. brutia had a longer growth period, while P. nigra exhibited a higher average daily increment under the environmental conditions of 2023 at the study site. Annual stem growth was nearly equal for both species. Based on dendrometer observations, P. brutia exhibited lower normalized TWD and higher normalized MDS values under varying vapor pressure deficit (VPD) and soil water potential (SWP) conditions. A linear mixed-effects model further confirmed that P. brutia consistently maintained lower TWD than P. nigra across a wide climatic range, suggesting a comparatively lower degree of drought-induced water stress. GRO was most influenced by air temperature and VPD, and negatively by SWP. TWD was strongly affected by both VPD and SWP, while MDS was primarily linked to minimum air temperature and VPD. Moreover, MDS in P. brutia appeared more sensitive to climate variability compared to P. nigra. Although drought limited stem growth in both species during the study year, the lower TWD and higher MDS observed in P. brutia may indicate distinct physiological strategies for coping with drought. These findings offer preliminary insights into interspecific differences in water regulation under the particular climatic conditions observed during the study year in this semi-arid Mediterranean ecosystem. Full article
(This article belongs to the Section Forest Ecophysiology and Biology)
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24 pages, 5977 KiB  
Article
An Investigation into the Evolutionary Characteristics and Expression Patterns of the Basic Leucine Zipper Gene Family in the Endangered Species Phoebe bournei Under Abiotic Stress Through Bioinformatics
by Yizhuo Feng, Almas Bakari, Hengfeng Guan, Jingyan Wang, Linping Zhang, Menglan Xu, Michael Nyoni, Shijiang Cao and Zhenzhen Zhang
Plants 2025, 14(15), 2292; https://doi.org/10.3390/plants14152292 - 25 Jul 2025
Viewed by 254
Abstract
The bZIP gene family play a crucial role in plant growth, development, and stress responses, functioning as transcription factors. While this gene family has been studied in several plant species, its roles in the endangered woody plant Phoebe bournei remain largely unclear. This [...] Read more.
The bZIP gene family play a crucial role in plant growth, development, and stress responses, functioning as transcription factors. While this gene family has been studied in several plant species, its roles in the endangered woody plant Phoebe bournei remain largely unclear. This study comprehensively analyzed the PbbZIP gene family in P. bournei, identifying 71 PbbZIP genes distributed across all 12 chromosomes. The amino acid count in these genes ranged from 74 to 839, with molecular weights varying from 8813.28 Da to 88,864.94 Da. Phylogenetic analysis categorized the PbbZIP genes into 12 subfamilies (A-K, S). Interspecific collinearity analysis revealed homologous PbbZIP genes between P. bournei and Arabidopsis thaliana. A promoter cis-acting element analysis indicated that PbbZIP genes contain various elements responsive to plant hormones, stress signals, and light. Additionally, expression analysis of public RNA-seq data showed that PbbZIP genes are distributed across multiple tissues, exhibiting distinct expression patterns specific to root bark, root xylem, stem bark, stem xylem, and leaves. We also performed qRT-PCR analysis on five representative PbbZIP genes (PbbZIP14, PbbZIP26, PbbZIP32, PbbZIP67, and PbbZIP69). The results demonstrated significant differences in the expression of PbbZIP genes under various abiotic stress conditions, including salt stress, heat, and drought. Notably, PbbZIP67 and PbbZIP69 exhibited robust responses under salt or heat stress conditions. This study confirmed the roles of the PbbZIP gene family in responding to various abiotic stresses, thereby providing insights into its functions in plant growth, development, and stress adaptation. The findings lay a foundation for future research on breeding and enhancing stress resistance in P. bournei. Full article
(This article belongs to the Special Issue Advances in Forest Tree Genetics and Breeding)
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17 pages, 2548 KiB  
Article
Enhancing Multi-Step Reservoir Inflow Forecasting: A Time-Variant Encoder–Decoder Approach
by Ming Fan, Dan Lu and Sudershan Gangrade
Geosciences 2025, 15(8), 279; https://doi.org/10.3390/geosciences15080279 - 24 Jul 2025
Viewed by 228
Abstract
Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, [...] Read more.
Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, in this study, we propose a novel time-variant encoder–decoder (ED) model designed specifically to improve multi-step reservoir inflow forecasting, enabling accurate predictions of reservoir inflows up to seven days ahead. Unlike conventional ED-LSTM and recursive ED-LSTM models, which use fixed encoder parameters or recursively propagate predictions, our model incorporates an adaptive encoder structure that dynamically adjusts to evolving conditions at each forecast horizon. Additionally, we introduce the Expected Baseline Integrated Gradients (EB-IGs) method for variable importance analysis, enhancing interpretability of inflow by incorporating multiple baselines to capture a broader range of hydrometeorological conditions. The proposed methods are demonstrated at several diverse reservoirs across the United States. Our results show that they outperform traditional methods, particularly at longer lead times, while also offering insights into the key drivers of inflow forecasting. These advancements contribute to enhanced reservoir management through improved forecasting accuracy and practical decision-making insights under complex hydroclimatic conditions. Full article
(This article belongs to the Special Issue AI and Machine Learning in Hydrogeology)
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28 pages, 2503 KiB  
Article
The Identification of Transcriptomic and Phytohormonal Biomarkers for Monitoring Drought and Evaluating the Potential of Acibenzolar-S-Methyl Root Application to Prime Two Apple Rootstock Genotypes for Drought Resistance
by Kirstin V. Wurms, Tony Reglinski, Erik H. A. Rikkerink, Nick Gould, Catrin S. Günther, Janine M. Cooney, Poppy Buissink, Annette Ah Chee, Christina B. Fehlmann, Dwayne J. A. Jensen and Duncan Hedderley
Int. J. Mol. Sci. 2025, 26(14), 6986; https://doi.org/10.3390/ijms26146986 - 21 Jul 2025
Viewed by 277
Abstract
Droughts are predicted to intensify with climate change, posing a serious threat to global crop production. Increasing drought tolerance in plants requires an understanding of the underlying mechanisms. This study measured the physiological, phytohormonal and transcriptomic responses to drought in two apple rootstocks [...] Read more.
Droughts are predicted to intensify with climate change, posing a serious threat to global crop production. Increasing drought tolerance in plants requires an understanding of the underlying mechanisms. This study measured the physiological, phytohormonal and transcriptomic responses to drought in two apple rootstocks to identify drought ‘biomarkers’ and investigated whether the application of acibenzolar-S-methyl (ASM) to the roots could enhance drought tolerance. Two potted-plant trials were conducted on dwarfing (M9) and semi-dwarfing (CG202) apple rootstocks. In both trials, the response patterns in the roots and leaves were compared between irrigated and non-irrigated plants over a 14-day period. In trial 2, ASM was applied 14 days before and immediately before withdrawing irrigation. Drought induced significant decreases in transpiration, photosynthesis and stomatal conductance in both trials. This was accompanied by the accumulation of abscisic acid (ABA) metabolites and the upregulation of ABA pathway transcripts (CYP707A1/A2 and NCED3), a decrease in 12-oxophytodienoic acid (cis-OPDA) and the downregulation of ABA receptor genes (PYL4). The responses to drought were greater in the roots than the leaves, broadly similar across both rootstocks, but differed in strength and timing between the rootstocks. The application of ASM to the roots did not significantly affect the responsiveness to drought in either rootstock. The identified phytohormonal and transcriptomic biomarkers require further validation across a broader range of genotypes. Full article
(This article belongs to the Special Issue Phytohormones: From Physiological Response to Application)
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12 pages, 1033 KiB  
Article
Hydration-Dehydration Effects on Germination Tolerance to Water Stress of Eight Cistus Species
by Belén Luna
Plants 2025, 14(14), 2237; https://doi.org/10.3390/plants14142237 - 19 Jul 2025
Viewed by 279
Abstract
Seeds in soil are often exposed to cycles of hydration and dehydration, which can prime them by triggering physiological activation without leading to germination. While this phenomenon has been scarcely studied in wild species, it may play a critical role in enhancing drought [...] Read more.
Seeds in soil are often exposed to cycles of hydration and dehydration, which can prime them by triggering physiological activation without leading to germination. While this phenomenon has been scarcely studied in wild species, it may play a critical role in enhancing drought resilience and maintaining seed viability under the warmer conditions predicted by climate change. In this study, I investigated the effects of hydration–dehydration cycles on germination response under water stress in eight Cistus species typical of Mediterranean shrublands. First, seeds were exposed to a heat shock to break physical dormancy, simulating fire conditions. Subsequently, they underwent one of two hydration–dehydration treatments (24 or 48 h) and were germinated under a range of water potentials (0, –0.2, –0.4, –0.6, and –0.8 MPa). Six out of eight species showed enhanced germination responses following hydration–dehydration treatments, including higher final germination percentages, earlier germination onset (T0), or increased tolerance to water stress. These findings highlight the role of water availability as a key factor regulating germination in Cistus species and evidence a hydration memory mechanism that may contribute in different ways to post-fire regeneration in Mediterranean ecosystems. Full article
(This article belongs to the Section Plant Response to Abiotic Stress and Climate Change)
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15 pages, 5045 KiB  
Article
Transpiration and Water Use Efficiency of Mediterranean Eucalyptus Genotypes Under Contrasting Irrigation Regimes
by Juan C. Valverde, Rafael A. Rubilar, Alex Medina, Matías Pincheira, Verónica Emhart, Yosselin Espinoza, Daniel Bozo and Otávio C. Campoe
Plants 2025, 14(14), 2232; https://doi.org/10.3390/plants14142232 - 19 Jul 2025
Viewed by 276
Abstract
Water scarcity is a key constraint for commercial Eucalyptus plantations, particularly given the increasing frequency of droughts driven by climate change. This study assessed annual transpiration (Tr) and water use efficiency (WUE) across eight genotypes subjected to contrasting irrigation regimes (WR). A split-plot [...] Read more.
Water scarcity is a key constraint for commercial Eucalyptus plantations, particularly given the increasing frequency of droughts driven by climate change. This study assessed annual transpiration (Tr) and water use efficiency (WUE) across eight genotypes subjected to contrasting irrigation regimes (WR). A split-plot design was implemented, comprising two irrigation levels: high (maintained above 75% of field capacity) and low (approximately 25% above the permanent wilting point). The genotypes included Eucalyptus globulus (EgH, EgL), E. nitens × globulus (EngH, EngL), E. nitens (En), E. camaldulensis × globulus (Ecg), E. badjensis (Eb), and E. smithii (Es). Between stand ages of 7 and 9 years (2020–2023), we measured current annual increment (CAI), leaf area index (LAI), Tr, and WUE. Under high WR, CAI ranged from 8 to 36 m3 ha−1 yr−1, Tr from 520 to 910 mm yr−1, and WUE from 0.7 to 2.9 kg m−3. Low irrigation reduced CAI by 5–25% and Tr by 10–35%, while WUE responses varied across genotypes, ranging from a 12% decrease to a 48% increase. Based on their functional responses, genotypes were grouped as follows: (i) stable performers (Es, Ecg, Eb) exhibited high WUE and consistent Tr under both WR; (ii) partially plastic genotypes (EgH, EngH) combined moderate reductions in Tr with improved WUE; and (iii) water-sensitive genotypes (EgL, EngL, En) showed substantial declines in Tr alongside variable WUE gains. These findings underscore the importance of selecting genotypes with adaptive water-use traits to improve the resilience and long-term sustainability of Eucalyptus plantations in Mediterranean environments. Full article
(This article belongs to the Section Plant Response to Abiotic Stress and Climate Change)
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25 pages, 3721 KiB  
Article
Phenotyping for Drought Tolerance in Different Wheat Genotypes Using Spectral and Fluorescence Sensors
by Guilherme Filgueiras Soares, Maria Lucrecia Gerosa Ramos, Luca Felisberto Pereira, Beat Keller, Onno Muller, Cristiane Andrea de Lima, Patricia Carvalho da Silva, Juaci Vitória Malaquias, Jorge Henrique Chagas and Walter Quadros Ribeiro Junior
Plants 2025, 14(14), 2216; https://doi.org/10.3390/plants14142216 - 17 Jul 2025
Viewed by 364
Abstract
The wheat planted at the end of the rainy season in the Cerrado suffers from a strong water deficit. A selection of genetic material with drought tolerance is necessary. In improvement programs that evaluate a large number of materials, efficient, automated, and non-destructive [...] Read more.
The wheat planted at the end of the rainy season in the Cerrado suffers from a strong water deficit. A selection of genetic material with drought tolerance is necessary. In improvement programs that evaluate a large number of materials, efficient, automated, and non-destructive phenotyping is essential, which requires the use of sensors. The experiment was conducted in 2016 using a phenotyping platform, where irrigation gradients ranging from 184 (WR4) to 601 mm (WR1) were created, allowing for the comparison of four genotypes. In addition to productivity, we evaluated plant height, hectoliter weight, the number of spikes per square meter, ear length, photosynthesis, and the indices calculated by the sensors. For most morphophysiological parameters, extreme stress makes it difficult to discriminate materials. WR1 (601 mm) and WR2 (501 mm) showed similar trends in almost all variables. The data validated the phenotyping platform, which creates an irrigation gradient, considering that the results obtained, in general, were proportional to the water levels. The similar trend between sensors (NDVI, PRI, and LIFT) and morphophysiological, plant growth, and crop yield evaluations validated the use of sensors as a tool in selecting drought-tolerant wheat genotypes using a non-invasive methodology. Considering that only four genotypes were used, none showed absolute and unequivocal tolerance to drought; however, each genotype exhibited some desirable characteristics related to drought tolerance mechanisms. Full article
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28 pages, 6267 KiB  
Article
Detection of Pine Wilt Disease Using a VIS-NIR Slope-Based Index from Sentinel-2 Data
by Jian Guo, Ran Kang, Tianhe Xu, Caiyun Deng, Li Zhang, Siqi Yang, Guiling Pan, Lulu Si, Yingbo Lu and Hermann Kaufmann
Forests 2025, 16(7), 1170; https://doi.org/10.3390/f16071170 - 16 Jul 2025
Viewed by 273
Abstract
Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus Steiner & Buhrer (pine wood nematodes, PWN), impacts forest carbon sequestration and climate change. However, satellite-based PWD monitoring is challenging due to the limited spatial resolution of Sentinel’s MSI sensor, which reduces its sensitivity to [...] Read more.
Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus Steiner & Buhrer (pine wood nematodes, PWN), impacts forest carbon sequestration and climate change. However, satellite-based PWD monitoring is challenging due to the limited spatial resolution of Sentinel’s MSI sensor, which reduces its sensitivity to subtle biochemical alterations in foliage. We have, therefore, developed a slope product index (SPI) for effective detection of PWD using single-date satellite imagery based on spectral gradients in the visible and near-infrared (VNIR) range. The SPI was compared against 15 widely used vegetation indices and demonstrated superior robustness across diverse test sites. Results show that the SPI is more sensitive to changes in chlorophyll content in the PWD detection, even under potentially confounding conditions such as drought. When integrated into Random Forest (RF) and Back-Propagation Neural Network (BPNN) models, SPI significantly improved classification accuracy, with the multivariate RF model achieving the highest performance and univariate with SPI in BPNN. The generalizability of SPI was validated across test sites in distinct climate zones, including Zhejiang (accuracyZ_Mean = 88.14%) and Shandong (accuracyS_Mean = 78.45%) provinces in China, as well as Portugal. Notably, SPI derived from Sentinel-2 imagery in October enables more accurate and timely PWD detection while reducing field investigation complexity and cost. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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26 pages, 7975 KiB  
Article
Soil Moisture Prediction Using the VIC Model Coupled with LSTMseq2seq
by Xiuping Zhang, Xiufeng He, Rencai Lin, Xiaohua Xu, Yanping Shi and Zhenning Hu
Remote Sens. 2025, 17(14), 2453; https://doi.org/10.3390/rs17142453 - 15 Jul 2025
Viewed by 441
Abstract
Soil moisture (SM) is a key variable in agricultural ecosystems and is crucial for drought prevention and control management. However, SM is influenced by underlying surface and meteorological conditions, and it changes rapidly in time and space. To capture the changes in SM [...] Read more.
Soil moisture (SM) is a key variable in agricultural ecosystems and is crucial for drought prevention and control management. However, SM is influenced by underlying surface and meteorological conditions, and it changes rapidly in time and space. To capture the changes in SM and improve the accuracy of short-term and medium-to-long-term predictions on a daily scale, an LSTMseq2seq model driven by both observational data and mechanism models was constructed. This framework combines historical meteorological elements and SM, as well as the SM change characteristics output by the VIC model, to predict SM over a 90-day period. The model was validated using SMAP SM. The proposed model can accurately predict the spatiotemporal variations in SM in Jiangxi Province. Compared with classical machine learning (ML) models, traditional LSTM models, and advanced transformer models, the LSTMseq2seq model achieved R2 values of 0.949, 0.9322, 0.8839, 0.8042, and 0.7451 for the prediction of surface SM over 3 days, 7 days, 30 days, 60 days, and 90 days, respectively. The mean absolute error (MAE) ranged from 0.0118 m3/m3 to 0.0285 m3/m3. This study also analyzed the contributions of meteorological features and simulated future SM state changes to SM prediction from two perspectives: time importance and feature importance. The results indicated that meteorological and SM changes within a certain time range prior to the prediction have an impact on SM prediction. The dual-driven LSTMseq2seq model has unique advantages in predicting SM and is conducive to the integration of physical mechanism models with data-driven models for handling input features of different lengths, providing support for daily-scale SM time series prediction and drought dynamics prediction. Full article
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23 pages, 10215 KiB  
Article
A Simplified Sigmoid-RH Model for Evapotranspiration Estimation Across Mainland China from 2001 to 2018
by Jiahui Fan, Yunjun Yao, Yajie Li, Lu Liu, Zijing Xie, Xiaotong Zhang, Yixi Kan, Luna Zhang, Fei Qiu, Jingya Qu and Dingqi Shi
Forests 2025, 16(7), 1157; https://doi.org/10.3390/f16071157 - 13 Jul 2025
Viewed by 261
Abstract
Accurate terrestrial evapotranspiration (ET) estimation is crucial for understanding land–atmosphere interactions, evaluating ecosystem functions, and supporting water resource management, particularly across climatically diverse regions. To address the limitations of traditional ET models, we propose a simple yet robust Sigmoid-RH model that characterizes the [...] Read more.
Accurate terrestrial evapotranspiration (ET) estimation is crucial for understanding land–atmosphere interactions, evaluating ecosystem functions, and supporting water resource management, particularly across climatically diverse regions. To address the limitations of traditional ET models, we propose a simple yet robust Sigmoid-RH model that characterizes the nonlinear relationship between relative humidity and ET. Unlike conventional approaches such as the Penman–Monteith or Priestley–Taylor models, the Sigmoid-RH model requires fewer inputs and is better suited for large-scale applications where data availability is limited. In this study, we applied the Sigmoid-RH model to estimate ET over mainland China from 2001 to 2018 by using satellite remote sensing and meteorological reanalysis data. Key driving inputs included air temperature (Ta), net radiation (Rn), relative humidity (RH), and the normalized difference vegetation index (NDVI), all of which are readily available from public datasets. Validation at 20 flux tower sites showed strong performance, with R-square (R2) ranging from 0.26 to 0.93, Root Mean Squard Error (RMSE) from 0.5 to 1.3 mm/day, and Kling-Gupta efficiency (KGE) from 0.16 to 0.91. The model performed best in mixed forests (KGE = 0.90) and weakest in shrublands (KGE = 0.27). Spatially, ET shows a clear increasing trend from northwest to southeast, closely aligned with climatic zones, with national mean annual ET of 560 mm/yr, ranging from less than 200 mm/yr in arid zones to over 1100 mm/yr in the humid south. Seasonally, ET peaked in summer due to monsoonal rainfall and vegetation growth, and was lowest in winter. Temporally, ET declined from 2001 to 2009 but increased from 2009 to 2018, influenced by changes in precipitation and NDVI. These findings confirm the applicability of the Sigmoid-RH model and highlight the importance of hydrothermal conditions and vegetation dynamics in regulating ET. By improving the accuracy and scalability of ET estimation, this model can provide practical implications for drought early warning systems, forest ecosystem management, and agricultural irrigation planning under changing climate conditions. Full article
(This article belongs to the Section Forest Meteorology and Climate Change)
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13 pages, 3254 KiB  
Article
Shifting Climate Patterns in the Brazilian Savanna Evidenced by the Köppen Classification and Drought Indices
by Khályta Willy da Silva Soares, Rafael Battisti, Felipe Puff Dapper, Alexson Pantaleão Machado de Carvalho, Marcos Vinícius da Silva, Jhon Lennon Bezerra da Silva, Henrique Fonseca Elias de Oliveira and Marcio Mesquita
Atmosphere 2025, 16(7), 849; https://doi.org/10.3390/atmos16070849 - 12 Jul 2025
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Abstract
The Brazilian savanna, South America’s second-largest biome, is vital to Brazil’s economy but has suffered from environmental degradation due to unregulated agricultural and urban expansion. This study assesses climate change in the biome from 1961 to 2021 using the Köppen climate classification, drought [...] Read more.
The Brazilian savanna, South America’s second-largest biome, is vital to Brazil’s economy but has suffered from environmental degradation due to unregulated agricultural and urban expansion. This study assesses climate change in the biome from 1961 to 2021 using the Köppen climate classification, drought indices, historical trend analyses, and the climatological water balance. Fourteen municipalities across the biome were analyzed. According to the Köppen classification, most municipalities were identified as Aw (tropical with dry winters) and Am (tropical monsoon), with Dourados, MS, and Sapezal, MT, alternating between Am and Aw. The standardized precipitation index (SPI) revealed changes in rainfall distribution. The Mann–Kendall test detected rising air temperatures in 13 of the 14 municipalities, with Sen’s slope ranging from 0.0156 to 0.0605 °C per year. Rainfall decreased in seven municipalities, with decreases from −4.54 to −12.77 mm per year. The climatological water balance supported the observed decrease in precipitation. The results indicated a clear warming trend and declining rainfall in most of the Brazilian savanna, highlighting potential challenges for water availability in the face of ongoing climate change. Full article
(This article belongs to the Special Issue Climate Change and Agriculture: Impacts and Adaptation (2nd Edition))
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