Climate variability and maize production in Cameroon: Simulating the effects of extreme dry and wet years

The effects of interyear variability of extreme rainfall events on maize yields at locations in Cameroon, in central‐west sub‐Saharan Africa were investigated through a simulation assessment combining a weather generator with a crop growth model. This study analyzes the potential of using dry/wet year predictions to reduce risk in subsistence agricultural production associated with climate variability at the site level. Weather data sets from eight provincial study localities were classified into three precipitation scenarios – dry (lower threshold), normal and wet (upper threshold) years. According to the modelling results, there is a less than 12 per cent variance in mean maize yields across six out of the eight localities when planting occurs in March, May and August. The variance is equivalent to approximately 100–300 kg per ha, which represents a significant amount of food in the household security of the majority impoverished sectors of rural and urban society, and which could greatly impact the socioeconomic activities of the entire populace. The results lead to the conclusion that all extreme dry and wet years are not equal in terms of their regional manifestation. This calls for precise monthly and sub‐seasonal local level forecasts and the effective dissemination of this information to farming communities in Cameroon, thereby facilitating the adaptive management of indigenous cropping practices and reducing their vulnerability to climate related disasters.     

玉米净作和间作植株间光强的时空分布(英文)

作物多样性种植能够有效减少病虫危害,显著增加产量,但其中的机理尚不清楚。太阳辐射是最重要的影响因子之一。本试验研究了玉米净作(A)及玉米/大豆2:2(B,2行玉米2行大豆)和2:4(C,2行玉米4行大豆)两种间作模式下,玉米冠层内太阳辐射强度的时空变化。研究结果表明,多样性种植可在不同高度上对玉米植株间的受光强度和受光时间产生明显影响。在玉米穗期,相比净作,在30cm高度上,B和C模式下光强都超过了2倍,在70cm高度上,光强超过10倍。花粒期,在110、160和210cm位置上,相比净作,B和C模式下光强分别提高了5倍、2倍和12%,而且随着测量高度的下降,间作模式下光强下降较为缓慢。从第7–18叶,相比净作,各叶位间作模式下光强平均增加2倍,而且日有效辐射时间平均提高了5小时。此外,玉米的一些生物学性状,如千粒重、每株产量和穗位叶叶面积等也表现出间作B和C模式都显著高于净作。因此,间作提高了玉米的受光强度和有效辐射时间,是改善玉米生物学性状的重要因子。     

湘中安化黑色页岩土壤玉米的元素地球化学分析

利用等离子质谱(ICP-MS)等分析技术,对产于安化东坪、烟溪黑色页岩土壤上的玉米进行元素地球化学分析.结果.表明:尽管东坪、烟溪黑色页岩土壤重金属元素富集的程度及其元素组合特征明显不同,但生长在其上的玉米有相似的主量元素和重金属元素的富集特征.玉米中Cd、Cr、Sc、Tl、Zn等重金属相对富集,以Cd的富集尤为明显;而Ba、Co、Cu、Fe、Mo、Ni、Pb、Sb、U、V等重金属相对亏损.黑色页岩土壤重金属污染的环境地球化学效应表现为Sc、Cr、Cd、Tl等生物毒性重金属元素在玉米中富集,而Ba、V、Co、Ni、Mo、Rb、Sr等生物必需微量金属在玉米中亏损.     

Overland runoff erosion dynamics on steep slopes with forages under field simulated rainfall and inflow

Although numerous studies have acknowledged that vegetation can reduce erosion, few process-based studies have examined how vegetation cover affect runoff hydraulics and erosion processes. We present field observations of overland flow hydraulics using rainfall simulations in a typical semiarid area in China. Field plots (5 × 2 m²) were constructed on a loess hillslope (25°), including bare soil plot as control and three plots with planted forage species as treatments—Astragalus adsurgens, Medicago sativa and Cosmos bipinnatus. Both simulated rainfall and simulated rainfall + inflow were applied. Forages reduced soil loss by 55–85% and decreased overland flow rate by 12–37%. Forages significantly increased flow hydraulic resistance expressed by Darcy–Weisbach friction factor by 188–202% and expressed by Manning's friction factor by 66–75%; and decreased overland flow velocity by 28–30%. The upslope inflow significantly increased overland flow velocity by 67% and stream power by 449%, resulting in increased sediment yield rate by 108%. Erosion rate exhibited a significant linear relationship with stream power. M. sativa exhibited the best in reducing soil loss which probably resulted from its role in reducing stream power. Forages on the downslope performed better at reducing sediment yield than upslope due to decreased rill formation and stream power. The findings contribute to an improved understanding of using vegetation to control water and soil loss and land degradation in semiarid environments.     

地表反照率动态参数化对陆-气通量模拟的影响：以东北玉米农田为例

利用考虑了生物因子(叶面积指数)和环境因子(太阳高度角、表层土壤湿度)影响的地表反照率α动态参数化方案对BATS1e模型进行改进,基于2008年玉米农田生态系统的通量、气象及生物因子的连续观测资料,研究α动态参数化对玉米农田生态系统与大气间通量交换的影响.结果表明,引入α动态参数化方案后,模型实现了地表反照率α的日、季动态模拟,模型效率系数提高0.65,误差明显减小,使陆气通量交换热力作用的模拟准确性有所提高,其中,净入射短波辐射模拟改进最为明显,全年改进量为81772 kJ/m2,占年总辐射的1.7％;表层土壤温度的年均改进量为0.62 K,多数月份的改进量在1 K以上.另外,模型改进实现了叶面积指数和植被覆盖度等决定下垫面性质各参数的动态变化,使各种通量交换过程更接近于实际,感热和潜热模拟的模型效率系数分别提高0.516和0.1,模拟值对实测值的解释能力在生长季分别提高6％和9％,大于非生长季.     

Short-term effects of shrub control on two different plant communities in Argentina

The aim of this work was to study the effect of controlling jarilla (Larreaspp.), nonforage shrubs for livestock, on two plant communities with different forage production in the arid mid-west of Argentina. Total vegetation cover, forage species cover and carrying capacity were determined during three growing seasons, for cleared and uncleared plots. At the end of the study, significant differences were found in theLarrea cuneifoliacommunity, where average forage species cover increased by 156% over the control, and greater carrying capacity (129%) was also obtained from the cleared treatment. No significant differences were found in theLarrea divaricatacommunity. Data lead us to recommend shrub control as an improvement practice only in areas with low forage species cover and poor carrying capacity.     

气候变化背景下1981-2010年中国玉米物候变化时空分异

基于中国玉米种植区内114个农气站1981-2010年的长序列物候观测数据,量化分析了玉米8个连续物候期的时空分异特征和相应的生长阶段长度变化规律。结果表明：1981-2010年间,玉米生育期内平均温度和有效积温(GDD）呈现增加趋势,降水量和日照时数呈现减少趋势。气候变化背景下,玉米物候期发生了显著变化。春玉米物候期以提前趋势为主,包括西北内陆玉米区春玉米、西南山地丘陵玉米区春玉米;夏玉米和春夏播玉米各物候期在不同区域均呈现推迟的趋势,西北内陆玉米区夏玉米各物候期推迟的幅度大于黄淮平原夏玉米各物候期推迟的幅度。玉米物候期的变化改变了相应生长阶段的长度,中国春/夏/春夏播玉米营养生长期（播种期—抽雄期）呈现不同程度的缩短趋势,而对应的生殖生长期（抽雄期—成熟期）呈现不同程度的延长趋势;春玉米生育期（播种期—成熟期）延长,夏/春夏播玉米生育期缩短。     

东北春玉米非线性积温模型参数改进

结合我国东北地区春玉米生长发育的实际情况,以观测年份较多、观测地点较广为原则选取4个春玉米品种,分别为东农248、龙单13、四单19和丹玉13,利用生长发育观测资料和同期气象观测资料,判断4个玉米品种的相对熟型并对沈国权非线性积温模型（简称NLM）进行参数拟合,讨论参数的生物学意义及其与品种熟型的关系,对NLM进行有效改进及验证。结果表明:4个春玉米品种NLM均不存在无效参数,参数K与参数Q存在显著的相关性,说明K可能仅是一个统计参数,没有明确的生物学意义;积温在品种间存在显著差异,全生育期模型参数Q与多年站次平均有效积温或活动积温有较好的相关性,由于不同的积温意味着不同的玉米品种熟型,说明Q与玉米品种的熟型有关,将模型参数Q和K用反映玉米品种熟型的参数（有效积温、活动积温）表示,建立了适用于不同品种的通用积温模型,取得较好的应用效果。     

Maize seed choice and perceptions of climate variability among smallholder farmers

Despite decades of research and interventions, crop yields for smallholder farmers across sub-Saharan Africa are dramatically lower than in developed countries. Attempts to address low yields of staple crops in Africa since the Green Revolution through policies and investments in advanced seed cultivars have had mixed results. Numerous countries have heartily embraced and promoted hybrid cultivars through government subsidy programs and investments in research and seed multiplication. One possible explanation for why these programs have not resulted in more significant yield improvements is the challenge faced by farmers to select cultivars that are suited to their local environmental conditions. The question of what seeds farmers choose is exceptionally complex as it is often affected by local seed availability, the availability of information on seed performance, and the transfer of that information to farmers. At the foundation of this choice are farmers’ perceptions of different seed varieties coupled with their perceptions of climate variability. We examine seed choice in Zambia, a country with decades of hybrid maize seed development and supporting policies. We demonstrate how input subsidy programs and seed market liberalization have led to choice overload and a discontinuity in information exchange between farmers and seed companies. The decision making environment is further complicated by the heterogeneity in growing conditions and its variable impact on seed performance, which complicates characterization of seed duration at the farm level. Perceptions and biases related to climate variability effect seed choice, and potentially lead farmers to make risk averse decisions, which ultimately depress maize yields.     

Upscaling plot-scale soil respiration in winter wheat and summer maize rotation croplands in Julu County,North China

Soil respiration (R_s) data from 45 plots were used to estimate the spatial patterns of R_s during the peak growing seasons of winter wheat and summer maize in Julu County, North China, by combining satellite remote sensing data, field-measured data, and a support vector regression (SVR) model. The observed R_s values were well reproduced by the model at the plot scale, with a root-mean-square error (RMSE) of 0.31 μmol CO₂ m⁻² s⁻¹ and a coefficient of determination (R²) of 0.73. No significant difference was detected between the prediction accuracy of the SVR model for winter wheat and summer maize. With forcing from satellite remote sensing data and gridded soil property data, we used the SVR model to predict the spatial distributions of R_s during the peak growing seasons of winter wheat and summer maize rotation croplands in Julu County. The SVR model captured the spatial variations of R_s at the county scale. The satellite-derived enhanced vegetation index was found to be the most important input used to predict R_s. Removal of this variable caused an RMSE increase from 0.31 μmol CO₂ m⁻² s⁻¹ to 0.42 μmol CO₂ m⁻² s⁻¹. Soil properties such as soil organic carbon (SOC) content and soil bulk density (SBD) were the second most important factors. Their removal led to an RMSE increase from 0.31 μmol CO₂ m⁻² s⁻¹ to 0.37 μmol CO₂ m⁻² s⁻¹. The SVR model performed better than multiple regression in predicting spatial variations of R_s in winter wheat and summer maize rotation croplands, as shown by the comparison of the R² and RMSE values of the two algorithms. The spatial patterns of R_s are better captured using the SVR model than performing multiple regression, particularly for the relatively high and relatively low R_s values at the center and northeast study areas. Therefore, SVR shows promise for predicting spatial variations of R_s values on the basis of remotely sensed data and gridded soil property data at the county scale.