Search Results (2,332)

A large proportion of global peanut cultivation occurs in arid and semiarid environments, where water scarcity poses a major limitation to productivity. Climate change further intensifies this challenge by causing irregular rainfall patterns. This study aimed to investigate the physiological and yield responses of peanut genotypes under well-watered and water-stressed conditions. Seven genotypes, five drought-tolerant (C76-16, Line-8, PI 502120, AU-NPL-17 and AU16-28) and two drought-sensitive (Valencia-C and AP-3) were evaluated under two irrigation regimes across consecutive years (2024 and 2025). Seven yield-associated traits (number of pods per plant, pod length, pod width, pod yield per plant, seed weight, hundred-seed weight and pod yield per plot) along with three physiological traits (stomatal conductance, photosynthetic efficiency and leaf temperature) were measured at three growth stages. Drought stress caused a significant reduction in almost all traits, including pod yield per plot (42–44%) and hundred-seed weight (24–38%). Stomatal conductance showed the greatest reduction at all stages, especially during flowering (31–80%) and pod filling (45–74%) stages. Correlation analysis revealed that yield-related traits were negatively correlated with stomatal conductance at pod-filling under water-stress conditions. Genotypes such as PI 502120, AU-NPL-17 and C76-16 maintained higher yields with less reduction under water-stressed conditions. This study also confirmed that Line-8 employs a water-saver strategy, whereas PI 502120 uses a water-spender mechanism to cope with water stress. Additionally, findings showed that the flowering and pod-filling stages are more severely affected physiologically by drought stress, which likely contributed to the observed yield reduction. Full article

This study evaluates GNSS water-vapor tomography across the Lisbon metropolitan area and explores how increasing network density with low-cost receivers improves three-dimensional humidity fields for meteorological applications. Three configurations were tested for December 2022, a month characterized by several rainfall events, including a severe urban-impacting one: (i) a hybrid setup combining permanent and low-cost stations (TOMO_PL), (ii) a dense network of only low-cost stations (TOMO_L), (iii) a sparse arrangement using only permanent stations (TOMO_P). Tomographic water vapor density fields were compared with independent references from the Weather Research and Forecasting (WRF) model, ERA 5 reanalysis, and radiosonde data. All products show the expected exponential decline in water vapor with increasing altitude. Tomography consistently underestimates moisture in the lowest 2.0 to 2.5 km and tends to overestimate it at higher levels, with a weaker correlation above mid-tropospheric heights. Vertical RMSE remains below 2 g m⁻³ for all solutions, but TOMO_P performs the worst due to weak and uneven spatial geometry. Time–height analysis reveals that densified setups capture the changing moisture in the lower atmosphere, including increased near-surface humidity during December 11–13, when rainfall exceeded 120 mm in 24 h, although mid-level intrusions and dry layers observed by radiosondes are not captured. Mean PWV patterns show realistically low points over the Sintra mountain range and align best with TOMO_PL (spatial RMSE 0.6 g m⁻³, bias 0.4 g m⁻³, correlation 0.9), while TOMO_P creates artifacts that mimic mesoscale gradients. Categorized skill analysis shows the highest accuracy under high-moisture conditions and limited ability to detect dry conditions, with TOMO_PL showing the best overall performance against both ERA5 and WRF. Overall, low-cost densification significantly enhances boundary-layer humidity and PWV retrievals, supporting their use for urban heavy-rain monitoring and, with error-aware integration, for short-term forecasting. Full article

Dryland farming systems in South Dakota face rainfall variability and rising water demand, which can reduce crop productivity and threaten long-term soil health. We combined field experiments across three dryland sites in South Dakota (Roscoe, Selby, Fort Pierre) with continuous soil moisture monitoring (0–15, 15–30, 30–45 cm) and HYDRUS-1D modeling to evaluate cover crops and soil amendments (biochar, manure) on water retention. During the active cover crop growth period, plots with cover crops consistently exhibited lower soil water content than plots without cover crops, likely due to increased transpiration. Plots with no cover crop (NCC) retained more water than cover crop (CC) plots (Roscoe: 26.27% vs. 24.16% at 0–15 cm). During the primary crop growing season, biochar consistently increased soil moisture (θ) compared with manure and unamended plots. Following a 43-day dry spell (1 July–13 August 2024), soil moisture declined by approximately 0.096 m³ m⁻³ in the biochar plots, compared with 0.125 m³ m⁻³ under manure and 0.216 m³ m⁻³ in the unamended control, exhibiting differences in water retention capacity among treatments. HYDRUS inverse modeling reproduced observed soil moisture dynamics (R² ~ 0.91) and demonstrated higher water content under biochar. Scenario analysis using representative wet (2008) and dry (2012) years showed the cover crop + biochar combination maintained the highest average water content. Results support integrating biochar with cover cropping to buffer drought and improve soil water availability in dryland farming. Full article

Climate variability poses major challenges to agriculture worldwide amid an increasing world population and growing food demand. This study evaluates the impact of climate variability on rice production in Liberia. Rice yields and production data (1990–2023) were attained from the Food and Agriculture Organization Statistics (FAOSTAT), while temperature and precipitation were sourced from ERA5 Agrometeorological Indicators and the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). Trends and relationships were analyzed using Mann–Kendall, Sen’s slope tests, and Spearman’s rank correlation. Multiple linear regression estimates climate variables’ impact on rice productivity. The results show that mean, minimum, and maximum temperatures increased by 0.57 °C, 0.55 °C, and 0.55 °C, respectively, with precipitation variability at 180.31 mm. Climate variables showed diverse correlations with rice production. Regression results revealed a significant negative impact of minimum temperature (p-value = 0.015) on production and a positive effect of precipitation on yields (p-value = 0.036). Farmers in Liberia recognized climate impacts and adopted adaptation strategies, but resilience is hindered by limited credit access, low technology adoption, reliance on traditional practices, and inadequate extension services. Overall, the findings highlight the sensitivity of rice production in Liberia to climate variability and underscore the need for guided adaptation and institutional support to augment farmer resilience. Full article

Soil erosion in mountain environments is governed by the interaction of climatic drivers, surface conditions, and geomorphic connectivity. Recently, disturbance by large herbivores has been recognized as a potentially important but poorly quantified geomorphic driver. However, the combined effects of freeze–thaw processes and ungulate disturbance on sediment production remain unclear. This study provides quantitative field-based evidence linking deer activity to hillslope sediment flux in a montane forest catchment in central Japan. A six-year dataset (2019–2025), including climatic conditions, deer detections from camera traps, understory vegetation cover, and hillslope sediment flux (<9.5 mm) was analyzed. Multiple regression analysis was conducted using daily sediment flux as the response variable and maximum 1 h rainfall, freeze–thaw frequency, and daily deer detections as explanatory variables. The results showed that deer detections had a significant positive effect on sediment flux, whereas rainfall intensity and freeze–thaw frequency did not exhibit strong independent effects. Particle-size analysis further indicated that eroded sediment was markedly coarser than the surface soil, suggesting that short-term climatic drivers alone did not control sediment transport. These findings demonstrate that biotic disturbance by large herbivores can play a dominant role in hillslope sediment flux under cold, high-elevation conditions by modifying surface conditions and sediment connectivity. From a sustainability perspective, these results highlight the importance of managing deer populations to maintain ecosystem stability, prevent land degradation, and support sustainable forest and watershed management under changing environmental conditions. Full article

This study evaluates the impact of assimilating the Crustal Movement Observation Network of China (CMONOC) global navigation satellite system (GNSS) tropospheric products on heavy-rainfall simulation over the complex terrain of the Sichuan Basin. Using the Weather Research and Forecasting model with the WRF Data Assimilation (WRF/WRFDA) three-dimensional variational (3DVar) system, we conducted a control (CTRL) experiment and a data-assimilation (DA) experiment for a primary heavy-rainfall event during 10–12 August 2020. The DA experiment applied 6 h cycling assimilation of station-based zenith total delay (ZTD) and precipitable water vapor (PWV). Compared with CTRL, DA improved the placement of the primary rainband and the depiction of peak rainfall. On 10 August, the observed rainfall core (~40 mm) over the northwestern basin was underestimated in CTRL (~15 mm) but was strengthened in DA (~25 mm). Hourly verification at a threshold of 2 mm h⁻¹ showed a higher maximum Threat Score (TS) in DA (0.292) than in CTRL (0.250), and the largest instantaneous gain reached 0.061. For 72 h accumulated precipitation, TS was higher in DA across multiple thresholds (≥10, ≥25, ≥50, and ≥100 mm), with the most pronounced improvement for heavier rainfall categories. Diagnostic analysis indicates that GNSS assimilation introduces dynamically consistent low-level moistening and strengthened convergence at 850 hPa, together with a better-aligned vertical ascent structure during the key stage of the event. An additional heavy-rainfall event during 21–23 August 2021 was further examined as a compact robustness test, and the results showed a generally consistent improvement in precipitation distribution and TS after GNSS assimilation. Overall, the present results suggest that cycling assimilation of CMONOC GNSS ZTD/PWV products can provide effective moisture constraints and improve heavy-rainfall simulation over the Sichuan Basin in the examined cases. Full article

The terrain and climate of the Qinghai–Tibetan Plateau make it hard to assess satellite precipitation. GSMaP (Global Satellite Mapping of Precipitation) is a widely used rainfall dataset, but direct comparisons of its versions and products over the Plateau are still limited. In this study, we evaluate four GSMaP products—Gauge, GNRT, MVK and NRT—across four versions (v05–v08) using daily station precipitation data from 2001 to 2022 as the reference. We assess both precipitation amount and precipitation event detection. The analysis is carried out at the station scale and then examined by month, season, year, rainfall intensity and space. We also compare regional patterns across the Plateau. The results show that GSMaP performance generally improves in later versions. Among them, v08 is usually more stable and more consistent, especially for gauge-corrected products. This improvement appears not only in better agreement with station data but also in smaller differences among stations for some products. Still, the size of the improvement is not the same for all products, seasons, rainfall classes and regions. The improvement is more clear in wetter areas and in warm seasons. By contrast, uncertainty is still relatively large in cold seasons, under strong rainfall and in the high-elevation interior of the Plateau. Non-gauge products also show wider variation than the Gauge product, which suggests that gauge correction still plays an important role in improving consistency. In general, version updates help improve GSMaP performance under some conditions, but the gains are not the same across different climate settings, rainfall intensities, or elevation zones. This study provides a systematic evaluation of GSMaP over the Qinghai–Tibetan Plateau for 2001–2022 and offers practical support for choosing and using GSMaP products in complex terrain. Full article

Against the backdrop of accelerating climate change, extreme weather events have increasingly caused yield losses in agricultural crops. Meanwhile, they undermine the stability of production systems, posing an increasingly severe threat to agriculture. This study draws on the “diversity–stability” hypothesis to construct a country-level measure of agricultural production resilience in China (ARES). Using output time series for multiple agricultural products, we capture the co-movements of shocks and system resilience through output stability and volatility. By combining ARES with climate exposure measures, we assemble a panel dataset covering 1343 counties over the period 2000–2023 and employ a dynamic panel threshold model to jointly account for persistence in ARES and state-dependent nonlinearities in climate impacts. The results reveal significant path dependence in ARES and pronounced threshold effects across climate dimensions. In the full sample, extreme high-temperature days become significantly detrimental after crossing the threshold, whereas extreme low-temperature days become significantly beneficial in the high-exposure regime. Extreme rainfall days and extreme drought days generally exhibit positive effects that weaken markedly beyond their respective thresholds, indicating diminishing marginal gains in ARES under severe exposure. The comprehensive climate physical risk index significantly suppresses ARES when it is below the threshold value; however, after surpassing the threshold, its marginal effect becomes significantly weaker. Heterogeneity analyses across hilly, plain, and mountainous areas, as well as nationally designated key counties for poverty alleviation and development, further show that threshold locations and regime-specific effects differ substantially by terrain and development conditions. These findings highlight the need for “threshold-based” climate adaptation governance, emphasizing targeted investments and risk-financing instruments to prevent ARES collapse under tail-risk regimes. Full article

Heilongjiang Province is China’s largest commercial grain-producing base, meaning that understanding the stability and climatic sensitivity of its major crops are essential for national food security. Using statistical and meteorological data from 2004 to 2023, this study systematically examines the impacts of climate change on cropping structure, yield dynamics, and production stability. The results show that over two decades the total grain crops-sown area and the yield per unit area increased by 79.4% and 38.4%, respectively. The cropping pattern shifted from a diversified structure to a maize-soybean-rice dominated pattern, while the wheat area declined by 92.2%. Additionally, mean and extreme yield fluctuations decreased by 52.3% and 42%, respectively. Rice exhibited the highest yield stability, whereas maize and soybeans experienced marked reductions in interannual variability. Spatial analysis identified Harbin and Daqing as hotspots for yield stability risk, characterized by higher yield standard deviations relative to other cities in the province. Climate elasticity analysis revealed that soybeans and rice were sensitive to warming, while wheat responded positively to increased rainfall. Overall, Heilongjiang’s grain production system has expanded and become more stable at the provincial scale, but it remains vulnerable to emerging climatic risks. Strengthening climate adaptation through crop-specific management, varietal improvement, and field water regulation is vital for enhancing system resilience and sustaining food production in cold-region agroecosystems. Full article

Reliable precipitation data are fundamental for climate and hydrological research, especially in regions with sparse ground-based observations. This study evaluates and compares the accuracy of two satellite-based precipitation products—CMORPH and GPCP—across daily, monthly, and annual scales over Iran. Daily, monthly, and annual precipitation estimates from CMORPH and GPCP were validated against observations from 128 meteorological stations distributed throughout the country. The assessment employed two statistical indices—correlation coefficient (CC) and root mean square error (RMSE)—alongside three categorical indices: probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). At the daily scale, CMORPH outperformed GPCP in terms of CC, RMSE, POD, and CSI, while GPCP exhibited a lower FAR. At the monthly scale, correlations between satellite-derived and station-based precipitation were stronger than those at the daily scale; CMORPH achieved the highest correlation (CC = 0.84), whereas GPCP yielded a lower RMSE, with a mean value of 26.2 mm. At the annual scale, GPCP demonstrated better performance in CC, while CMORPH showed superior accuracy in RMSE. CMORPH consistently underestimated precipitation, whereas GPCP tended to overestimate rainfall across Iran. Although both datasets provided reliable precipitation estimates at the national scale, CMORPH demonstrated higher overall accuracy and efficiency. Its superior performance across most indices makes CMORPH the more suitable dataset for precipitation monitoring in Iran, despite its tendency to underestimate rainfall relative to ground observations. Full article

Ranked 30th globally in dryness, South Africa faces severe challenges in ensuring fodder security, which is worsened by climate change impacts on agriculture. However, there is still limited knowledge about optimising fodder radish cultivation under shifting climatic conditions. This study investigated the effects of planting dates (December to March), cultivars (Nooitgedacht, Line 2 and Endurance) and seasons (2020/21 and 2021/22) on growth, yield, and crude protein (CP) and mineral concentrations under rainfed conditions. Seasonal variation significantly (p < 0.05) influenced emergence, relative growth, and flowering across planting dates. Fresh tuber yield was highest when Nooitgedacht was planted in December (2052 and 2102 kg ha⁻¹). In contrast, January planting enhanced aboveground biomass and crude protein (CP) yield, with Endurance recording the highest biomass (1260 and 1157.95 kg ha⁻¹ DM) and tuber CP yield (19.2 and 18 kg ha⁻¹). December planting favoured tuber production, whereas January planting optimised biomass, CP yield, and persistence. Planting date and cultivar significantly affected leaf and tuber mineral concentrations. December–January plantings generally enhanced leaf P, K, and Zn concentrations. Endurance and Nooitgedacht accumulated higher micronutrients than Line 2, particularly under early planting. The late flowering of Endurance extended the grazing period, aligning with late-winter forage demand under rainfed conditions. Overall, this study offers practical guidance for improving the quantity and quality of fodder radish in diverse agricultural settings. Future work should evaluate these cultivars across more sites to confirm performance stability under variable rainfall patterns. Full article

This study examines selected factors influencing white maize price movements in South Africa over the period 1994–2024. Given the importance of white maize for food security, understanding the drivers of producer price dynamics is essential for effective policy formulation and managing price stability. Annual time-series data are analysed using an Autoregressive Distributed Lag (ARDL) modelling framework, complemented by bounds testing, an error-correction model, Toda–Yamamoto causality and structural break tests. The bounds test confirms the existence of a stable long-run cointegrating relationship between maize prices and the selected explanatory variables. In the short run, imports and fuel prices exert significant upward pressure on maize producer prices, while lagged fuel prices and rainfall reduce prices. In the long run, imports and fuel prices remain statistically significant determinants, whereas maize production, exports, the exchange rate, and rainfall are insignificant. Complemented with the structural break tests that identify regime shifts in the early 2000s, 2012, and 2021, causality results indicate that imports, rainfall and fuel prices lead to Granger causality in maize producer prices. Collectively the findings reinforce the conclusion that white maize prices in South Africa are governed by long-run structural relationships, while short-run price movements reflect temporary adjustments rather than permanent shifts in market fundamentals. An integrated, long-horizon analysis that jointly incorporates climatic, trade, and macroeconomic determinants within an ARDL framework is provided by the study. Therefore, the findings have important implications for climate-risk management, transport cost containment, trade and price-stabilisation policies. Full article

Rice grain yield and drought tolerance are critical for global food security. So far, only a few genes have been reported to regulate both traits simultaneously. Here, we characterize OsFLO1, a previously unreported FAD-linked oxidoreductase, as a dual regulator of grain development and drought stress tolerance in rice. Genome-wide association studies (GWAS) revealed natural variation in OsFLO1, with haplotypes showing geographic adaptation to local rainfall. Functional analysis demonstrated that overexpression (OX) lines exhibited larger grains and improved panicle traits, while knockout (CR) lines showed reduced grain size and yield components despite increased tiller number. Regarding drought tolerance, OX lines of OsFLO1 enhanced drought tolerance, as evidenced by increased root length and antioxidant activities, whereas knockout (CR) lines displayed impaired stress responses. We further show that OsWRKY53 directly binds the OsFLO1 promoter, thereby activating its expression and coordinating both grain development and stress responses. Together, these results suggest that OsFLO1 functions as a key regulator coordinating grain development and drought tolerance, making it a promising target for improving rice productivity. Full article

Climate change poses increasing challenges to livestock production in tropical regions, where rising temperatures, rainfall variability, and feed cost fluctuations affect productivity and economic stability. However, few studies have jointly quantified the effects of climatic and economic variables on swine production in tropical production systems, particularly in Brazil. This study examined the effects of maximum temperature, precipitation, and feed price on swine production density in Brazil’s main producing states. The analysis included Paraná and Rio Grande do Sul as the principal empirical base, while Mato Grosso was retained because of its strategic relevance but contributed only limited observations and was therefore interpreted more cautiously. Using monthly observations and a multiple linear regression model with heteroskedasticity- and autocorrelation-consistent (HAC, Newey–West) standard errors, we found that higher maximum mean temperatures were associated with lower production density: a 1 °C increase corresponded to an estimated decline of 1.34 × 10⁶ kg/km². Precipitation showed a positive association, with each additional millimeter corresponding to an increase of approximately 1.82 × 10⁵ kg/km², whereas a 0.173 USD/kg increase in feed price was associated with a reduction of about 6.2 × 10⁶ kg/km². Although the model explained only a modest share of monthly variation (R² = 0.162), the results suggest that climatic exposure and feed-cost pressure are relevant components of swine production dynamics in Brazil and should be considered in future climate-risk and agricultural planning. Full article

Projected climate change indicates that drought intensity will increase across much of the Global South, intensifying water stress in semi-arid regions. In Botswana, rising temperatures and increasingly variable rainfall are exacerbating drought conditions, particularly for livestock-based systems that depend on reliable grazing and water resources. This study was conducted in the Lake Ngami basin, Botswana, a predominantly pastoral community, to examine the adaptation and resilience of pastoralists to drought and climate change. The study examines the extent to which current coping strategies and institutional frameworks in the Lake Ngami basin contribute to long-term climate resilience among pastoral communities. It also assesses combinations of Climate-Resilient Development Pathways (CRDPs) that are most critical for enabling a transition from reactive coping to proactive and sustainable adaptation. We utilized in-depth community interviews, focus group discussions, and policy content analysis guided by the Climate-Resilient Development Pathways (CRDPs) framework to gather and analyze data using thematic analysis. Key findings indicated that droughts, intensified by factors like El Niño, have negatively affected the community’s livelihood, including grazing systems, access to water, and livestock productivity. The effectiveness of coping strategies was assessed through triangulation of thematic frequency, participant narratives of livelihood recovery, and analysis of policy implementation gaps. Pastoralists employed coping methods such as herd reduction, seasonal migration, and informal alternative livelihoods, but these were largely ineffective in promoting long-term resilience. While seasonal mobility provided short-term relief through access to distant grazing areas, forced livestock sales and herd reduction reduced herd size, weakening households’ long-term recovery capacity and increasing vulnerability. Institutional support programs such as the National Disaster Risk Reduction Strategy and the National Committee on Climate Change were found not adequate to build the necessary long-term pastoralists’ resilience. The study emphasizes that enhancing climate resilience in dryland pastoral systems necessitates combining traditional knowledge with improved infrastructure, climate information, and inclusive governance in comprehensive CRDPs. Full article