Data-moderate assessments of Cape monkfish Lophius vomerinus and west coast sole Austroglossus microlepis in Namibian waters

There is global interest in providing scientific advice on optimal harvesting of all commercially exploited fish stocks. Nevertheless, many commercially important stocks lack analytical assessments. Therefore, we evaluate a data-moderate stock assessment method: the stochastic surplus production model in continuous time (SPiCT). The method was applied to two Namibian stocks: (i) the data-rich Cape monkfish Lophius vomerinus, where results are compared to a new data-rich assessment using a state–space assessment model (SAM); and (ii) the data-moderate west coast sole Austroglossus microlepis, which is an important bycatch species in the Cape monkfish fishery, but currently unassessed. The information available to the data-moderate assessment is total commercial catch, commercial catch per unit effort (CPUE), and survey CPUE. SPiCT and SAM gave largely consistent estimates of relative fishing mortality (F/F_MSY) and relative exploitable biomass (B/B_MSY) for the Cape monkfish stock, although with some discrepancies. Differences in the biomass estimates between the two assessments suggest that further investigation is required to understand the cause, and that some caution is necessary when considering the biomass of the stock. SPiCT shows that the west coast sole may be overexploited, although the confidence bounds were too wide for a firm conclusion. Similarity in the estimates of F/F_MSY for Cape monkfish in recent years, using SPiCT relative to SAM, likewise indicates the suitability of SPiCT for managing west coast sole.     

真三轴条件下非饱和黄土的有效应力屈服特性

为了研究非饱和黄土在有效应力空间的屈服特性,利用真三轴仪对非饱和原状黄土进行了不排水等向净应力压缩固结和不同中主应力参数b值的剪切试验,研究了真三轴压缩条件下非饱和黄土的有效应力屈服变化规律。研究结果表明：有效应力比随着中主应力或净围压的增大而减小,中主应力的增大作用对有效球应力的影响大于广义剪应力;由有效应力比?体应变关系曲线确定的剪缩屈服曲线在有效应力空间具有良好的规律性,屈服点的有效屈服应力随着中主应力和初始吸力的增大而增大;π平面上的有效应力屈服强度面和强度破坏面与SMP强度准则稳合较好,有效球应力和初始吸力越大,屈服强度面和强度破坏面越大。提出了真三轴条件下弹性剪应变和塑性剪应变的计算公式,通过分析有效应力与塑性应变关系得出有效应力空间中不同子午平面内的塑性势面呈椭圆形,且随着中主应力的增大,椭圆屈服面增大。     

Assessing the benefit of satellite-based Solar-Induced Chlorophyll Fluorescence in crop yield prediction

Large-scale crop yield prediction is critical for early warning of food insecurity, agricultural supply chain management, and economic market. Satellite-based Solar-Induced Chlorophyll Fluorescence (SIF) products have revealed hot spots of photosynthesis over global croplands, such as in the U.S. Midwest. However, to what extent these satellite-based SIF products can enhance the performance of crop yield prediction when benchmarking against other existing satellite data remains unclear. Here we assessed the benefits of using three satellite-based SIF products in yield prediction for maize and soybean in the U.S. Midwest: gap-filled SIF from Orbiting Carbon Observatory 2 (OCO-2), new SIF retrievals from the TROPOspheric Monitoring Instrument (TROPOMI), and the coarse-resolution SIF retrievals from the Global Ozone Monitoring Experiment-2 (GOME-2). The yield prediction performances of using SIF data were benchmarked with those using satellite-based vegetation indices (VIs), including normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near-infrared reflectance of vegetation (NIRv), and land surface temperature (LST). Five machine-learning algorithms were used to build yield prediction models with both remote-sensing-only and climate-remote-sensing-combined variables. We found that high-resolution SIF products from OCO-2 and TROPOMI outperformed coarse-resolution GOME-2 SIF product in crop yield prediction. Using high-resolution SIF products gave the best forward predictions for both maize and soybean yields in 2018, indicating the great potential of using satellite-based high-resolution SIF products for crop yield prediction. However, using currently available high-resolution SIF products did not guarantee consistently better yield prediction performances than using other satellite-based remote sensing variables in all the evaluated cases. The relative performances of using different remote sensing variables in yield prediction depended on crop types (maize or soybean), out-of-sample testing methods (five-fold-cross-validation or forward), and record length of training data. We also found that using NIRv could generally lead to better yield prediction performance than using NDVI, EVI, or LST, and using NIRv could achieve similar or even better yield prediction performance than using OCO-2 or TROPOMI SIF products. We concluded that satellite-based SIF products could be beneficial in crop yield prediction with more high-resolution and good-quality SIF products accumulated in the future.     

不同土地-气候情景下三江源地区产水和水土流失评价（英文）

探讨三江源地区产水和土壤保持对整个青藏高原地区、黄河流域、长江流域及澜沧江流域的生态稳定和人类社会的可持续发展具有重要意义。以4期(2000年、2005年、2010年、2015年)土地利用现状数据、降水及气温日值数据集、1∶1000000中国土壤数据库为研究的数据源,结合居民点、道路、河流等矢量数据及人口、经济栅格数据集和CCSM4通用气候模式预测成果数据,以三江源地区为案例区,基于FLUS模型和降尺度校正方法设计4种土地利用发展情景和2种气候变化情景,应用InVEST模型对研究区域2030年不同情景下的产水和土壤侵蚀进行定量模拟。结果表明:(1)不同土地利用发展情景下,草地仍然是三江源地区的优势土地利用类型,面积占比始终大于67%。(2)RCP4.5气候情景下,年产水量和土壤侵蚀量增加幅度分别超过7%和3.9%;RCP8.5气候情景下,年产水量和土壤侵蚀量的减少幅度分别超过3.3%和1.3%。(3)气候变化在产水量和土壤侵蚀量变化中起主导作用。气候变化对产水量变化的贡献率高达89.97%–98.00%,对土壤侵蚀模数变化的贡献率在60.49%–95.64%之间;而土地利用类型变化对区域产水量变化的贡献率仅在2.00%–10.03%之间,对土壤侵蚀模数变化的贡献率在4.36%–39.91%之间。因此,三江源地区土地开发策略应综合考虑区域发展、退耕还林还草的投入及产生的生态效益等多方面问题。     

Influence of non-photosynthetic pigments on light absorption and quantum yield of photosynthesis in the western equatorial Pacific and the Subarctic North Pacific

Regional variations in the contribution of non-photosynthetic pigments (ā _np^*) to the total light absorption of phytoplankton (ā _ph^*) and its influence on the maximum quantum yield of photosynthesis (φ _m) were investigated. In the western equatorial Pacific, the surface ā _np^* : ā _ph^* ratio was higher in the western warm pool than that in the upwelling region. This difference appears to be attributable to severe nitrate depletion and higher percentage of prokaryotes, which can accumulate very high concentrations of zeaxanthin in the western warm pool. In the subarctic North Pacific, the ā _np^* : ā _ph^* ratio was expected to be higher in the Alaskan Gyre where the thermocline is sharper and iron limitation may possibly be more severe than in the Western Subarctic Gyre. However, the ratio was actually higher in the Western Subarctic Gyre, contradictory to our expectations. This east-west variation appears to be attributable to changes in the taxonomic composition; cyanobacteria were more abundant in the Western Subarctic Gyre. The values of ā _np^* : ā _ph^* and its vertical variations were relatively small in the subarctic North Pacific compared to those in the western equatorial Pacific. These inter-regional variations appear to be attributable to the lower solar radiation intensity, smaller percentage of cyanobacteria, and relatively strong vertical mixing in the subarctic North Pacific. The spatial variations in ā _np^* : ā _ph^* significantly influence φ _m. In comparison with φ _m based on the total light absorption (φ _{m ph}), the values corrected for the contribution of non-photosynthetic pigments (φ _{m ps}) showed an increase in both the western equatorial Pacific and the subarctic North Pacific.     

Integration of maximum crop response with machine learning regression model to timely estimate crop yield

Timely and reliable estimation of regional crop yield is a vital component of food security assessment, especially in developing regions. The traditional crop forecasting methods need ample time and labor to collect and process field data to release official yield reports. Satellite remote sensing data is considered a cost-effective and accurate way of predicting crop yield at pixel-level. In this study, maximum Enhanced Vegetation Index (EVI) during the crop-growing season was integrated with Machine Learning Regression (MLR) models to estimate wheat and rice yields in Pakistan's Punjab province. Five MLR models were compared using a fivefold cross-validation method for their predictive accuracy. The study results revealed that the regression model based on the Gaussian process outperformed over other models. The best performing model attained coefficient of determination (R2), Root Mean Square Error (RMSE, t/ ha), and Mean Absolute Error (MAE, t/ha) of 0.75, 0.281, and 0.236 for wheat; 0.68, 0.112, and 0.091 for rice, respectively. The proposed method made it feasible to predict wheat and rice 6– 8 weeks before the harvest. The early prediction of crop yield and its spatial distribution in the region can help formulate efficient agricultural policies for sustainable social, environmental, and economic progress.     

黄河中游的侵蚀环境与植被恢复前景

黄土高原的土壤侵蚀和生态环境问题世界瞩目。在保证蓄水拦沙效益基础上,提高林、草保存率,使植被恢复得到最佳的生态效益,是黄土高原环境整治中亟待解决的关键问题。本文根据黄土高原不同空间地理位置的流域、重点县水文监测资料,研究了气候、地表覆被、土地利用方式的变化对流域侵蚀产沙的影响以及流域产沙与地理环境要素间的耦合关系,定量分析了黄土高原,特别是多沙粗沙区自然与人文要素对流域侵蚀产沙的综合影响和因子的权重分析,并利用天然降雨植被生态需水适宜性系数和林、草恢复度的概念,重点探讨了黄河中游主要产沙区、尤其是多沙粗沙区退耕还林等土地利用方式宏观格局变化与植被恢复前景。研究表明,在植被生长主要依赖天然降雨的黄土高原,生物措施(植被类型)要与自然带相适应,应根据植被恢复度和植被生态需水适应性系数来进行宏观植被的恢复与实施。这是目前在不断增长的人口压力下,进行水土保持,解决好经济发展与环境保护、减少垦殖率与保证老百姓的基本农田、造林种草与植被类型的自然适应性、以及控制泥沙作用中生物措施与工程措施合理布局等诸多矛盾的关键所在。     

Fluctuation in Ommastrephe bartrami yield in the North Pacific

The fluctuation in Ommastrephe bartrami yield from 1995 to 2001 in the North Pacific was shown obvious, on which this study was conducted using data of sea surface temperature (SST), chlorophyll-a (chl-a) and statistical production. The study shows that, cool water and low food abundance caused by abnormal Kuroshio resulted in the reduction in abundance of O. bartrami, which was worsened by excessive catch and the unawareness to local fishery resources protection.     

气候变暖有益于中国的社会和谐

中国传统农业的产量受气候控制,气候表现为冷暖和干湿交替的循环,因此农业产量也出现循环演变的规律,在冷期中生活资源的短缺所造成的生存压力,加剧了矛盾,促进了战争。而气候变暖可以缓解这些矛盾,因此,气候变暖有益于中国的社会和谐。     

Sediment delivery from hillslopes and the Universal Soil Loss Equation: some perceptions and misconceptions

The Universal Soil Loss Equation (USLE) or the revised USLE (RUSLE) are often used together with sediment delivery ratios in order to predict sediment delivery from hillslopes. In using sediment delivery ratios for this purpose, it is assumed that the sediment delivery ratio for a given hillslope does not vary with the amount of erosion occurring in the upslope area. This assumption is false. There is a perception that hillslope erosion is calculated on the basis that hillslopes are, in effect, simply divided into 22·1 m long segments. This perception fails to recognize the fact the inclusion of the 22·1 m length in the calculation has no physical significance but simply produces a value of 1·0 for the slope length factor when slopes have a length equal to that of the unit plot. There is a perception that the slope length factor is inappropriate because not all the dislodged sediment is discharged. This perception fails to recognize that the USLE and the RUSLE actually predict sediment yield from planar surfaces, not the total amount of soil material dislocated and removed some distance by erosion within an area. The application of the USLE/RUSLE to hillslopes also needs to take into account the fact that runoff may not be generated uniformly over that hillslope. This can be achieved by an equation for the slope length factor that takes account of spatial variations in upslope runoff on soil loss from a segment or grid cell. Several alternatives to the USLE event erosivity index have been proposed in order to predict event erosion better than can be achieved using the EI₃₀ index. Most ignore the consequences of changing the event erosivity index on the values for the soil, crop and soil conservation protection factors because there is a misconception that these factors are independent of one another. Copyright © 2007 John Wiley & Sons, Ltd.