Modeling WEPP erodibility parameters in calcareous soils in northwest Iran

Modeling soil detachment rates at the regional scale is important for better understanding of the processes of erosion and the development of erosion models. Soil erodibility is an important factor for predicting soil loss, but its direct measurement at the watershed scale is difficult, time-consuming and costly. This study used stepwise multiple-linear regression (MLR) and artificial neural networks (ANNs) to model Water Erosion Prediction Project (WEPP) soil erodibility parameters, including the baseline inter-rill erodibility (K_ib), baseline rill erodibility (K_rb) and critical shear stress (τ_cb) of cropland conditions in calcareous soils of northwest Iran. Simulated inter-rill and rill erosion experiments were conducted at 100 locations with three replications. K_ib, K_rb and τ_cb and basic soil properties were measured at each location. Auxiliary variables related to soil erodibility were derived from a Landsat 7 satellite image and a 30 m × 30 m digital elevation model (DEM). MLR and ANN models were employed to predict K_ib, K_rb and τ_cb using two groups of input variables: i) more easily measurable basic soil properties (pedo-transfer functions (PTFs)) and ii) more easily measurable basic soil properties and auxiliary data (soil spatial prediction functions (SSPFs)). The results indicated that the WEPP models performed poorly in comparison to the derived models. PTFs and SSPFs generated from ANN models provided more reliable predictions than the MLR models. ANN-based SSPF models yielded the best results (with the highest R² and lowest RMSE values) for predicting Kib and Krb. ANN-based PTF model performed reasonably well for predicting τ_cb. These results show that information from terrain attributes and remote sensing data are potential auxiliary variables for improving prediction of soil erodibility parameters.     

COI序列:影响动物分类学与生态学的DNA barcode

DNA barcode是一段特殊的、可用于物种鉴定的DNA序列.目前在动物中最常用的DNA barcode是细胞色素C氧化酶1号基因(COI)的部分序列.随着标准数据库的建立,基于COI基因的DNA barcode在动物分类学和生态学中得到了广泛应用.但是,采用COI基因作为DNA barcode所隐含的涉及线粒体的进化历史、遗传特性和物种成种时间的默认前提,并非完全成立,由此引发了许多问题.本文阐述了基于COI基因的DNA barcode对分类学和生态学的影响,目前存在的问题,以及可能的研究方向.     

植物挥发性气体(VOCs)研究进展

植物挥发性气体(VOCs)在植物一植食性昆虫-天敌三级营养关系、植物间信息传递及适应性改变上都发挥着重要作用.植物释放VOCs具特异性、系统性、时序性与节律性等特点,VOCs主要在寄主选择行为、产卵行为、求偶行为、引来昆虫夭敌干涉等方面影响植食性昆虫.VOCs-介导的植物间信息传递作用包括4个过程:"释放者"植物合成及释放气体、气体在空气中的运输、气体在植物表面的吸附及"接收者"植株对气体信号的感知.收集VOCs的方法主要有吸附-溶剂洗脱法和吸附-热脱附法.     

Developing pedotransfer functions to estimate the S-index for indicating soil quality

Indicating soil quality usually requires many soil properties of which the measurements are time consuming. Therefore, it is desirable to developing simple and effective indices for reflecting soil quality based on soil properties that can be readily obtained. The soil physical quality index, S-index, derived from the slope at the inflection point of the water retention curve (particularly the Van-Genuchten equation), is a comprehensive index for indicating soil properties. By comparing the S-index with a widely used soil quality index (SQI), this study used 298 samples to determine soil chemical and physical properties for calculating SQI, and found that the correlation coefficient between the S-index and SQI was 0.88, indicating that the S-index can represent soil quality well. An artificial neural network (ANN) model and a linear regression (LR) model were proposed for estimating S-index. Results showed that the ANN model was better than LR model in estimating S-index. Particularly, the ANN model with the soil bulk density and soil organic carbon (scenario A1) as inputs, had the highest R² of 0.807, while the LR model get the highest R² (predicted v.s. observed) of 0.75 with the combination of soil organic carbon, soil bulk density, total nitrogen and available nitrogen. This study is helpful for extending the applications of S-index.     

Spatial metrics for detecting ecosystem degradation in the ridge-slough patterned landscape

Indicators of landscape condition should be selected based on their sensitivity to environmental changes and their capacity to provide early warning detection of those changes. We assessed the performance of a suite of spatial-pattern metrics selected to quantify the condition of the ridge-slough landscape in the Everglades (South Florida, USA). Spatial pattern metrics (n = 14) that describe landscape composition, geometry and hydrologic connectivity were enumerated from vegetation maps of twenty-five 2 × 2 km primary sampling units (PSUs) that span a gradient of hydrologic and ecological condition across the greater Everglades ecosystem. Metrics were assessed in comparison with field measurements from each PSU of landscape condition obtained from regional surveys of soil elevation, which have previously been shown to capture dramatic differences between conserved and degraded locations. Elevation-based measures of landscape condition included soil elevation bi-modality (BI_SE), a binary measure of landscape condition, and also the standard deviation of soil elevation (SD_SE), a continuous measure of condition. Metric performance was assessed based on the strength (sensitivity) and shape (leading vs. lagging) of the relationship between spatial pattern metrics and these elevation-based measures. We observed significant logistic regression slopes with BI_SE for only 4 metrics (slough width, ridge density, directional connectivity index – DCI, and least flow cost – LFC). More significant relationships (n = 8 metrics) were observed with SD_SE, with the strongest associations for slough density, mean ridge width, and the average length of straight flow, as well as for a suite of hydrologic connectivity metrics (DCI, LFC and landscape discharge competence – LDC). Leading vs. lagging performance, inferred from the curvature of the association obtained from the exponent of fitted power functions, suggest that only DCI was a leading metric of the loss of soil elevation variation; most metrics were indeterminate, though some were clearly lagging. Our findings support the contention that soil elevation changes from altered peat accretion dynamics precede changes in landscape pattern, and offer insights that will enable efficient monitoring of the ridge-slough landscape as part of the ongoing Everglades restoration effort.     

混合菌群发酵秸秆合成菌体蛋白及其动力学分析

混合菌群发酵秸秆可有效提高秸秆纤维的降解率及菌体蛋白的转化率,对拓广蛋白饲料来源、减少环境污染起到积极的作用。本研究以小麦秸秆为原料,在纤维素酶水解预处理的基础上,以米曲霉作为先导菌,进一步分解残留的粗纤维,为后期发酵提供充足的碳源。根据不同微生物的代谢特征和协同机理,试验确定了发酵阶段混合菌群的组成为:米曲霉、产朊假丝酵母和枯草芽胞杆菌;接种顺序为:先接种米曲霉,再接种产朊假丝酵母,最后接种枯草芽胞杆菌。正交试验表明,影响发酵主要因素的主次顺序为:秸秆与麸皮配比>接种比例>发酵时间>接种量>发酵温度;发酵的最适条件为:米曲霉的接种量2.5%,发酵12h后接入5%的产朊假丝酵母,继续发酵8h后接入2.5%的枯草芽胞杆菌,发酵温度为28℃,秸秆与麸皮的配比为4∶1,尿素添加量为1.2%;结合动力学分析,将混合菌群的发酵时间优化为35h,发酵产物中粗蛋白含量由原来的5.47%提高到25%左右。对最适发酵条件下的动力学过程进行了探讨,建立了以Logistic方程为基础的数学模型和动力学方程。本研究表明,混合菌群发酵秸秆提高了发酵产物中的粗蛋白含量。动力学分析对于了解发酵机理、掌握整个发酵过程中混合菌群生长的动态变化、优化发酵工艺具有重要的指导意义。     

Identification of soil quality indicators for assessing the effect of different tillage practices through a soil quality index in a semi-arid environment

Tillage is known to potentially affect soil quality in various ways. In this study, a soil quality index (SQI) was developed by quantifying several soil attributes either sensitive or insensitive to physical disturbance, using factor analysis as a dimension reduction technique, in order to discriminate different tillage systems. Soil properties including physical (MWD), chemical (pH, organic C, total N, available P and POM contents) and microbial (MBC, MBN, PCM, PNM and three enzymes) parameters were measured to establish a minimum data set (MDS) for the assessment of overall SQI. The soil attributes were determined on samples (0–20 cm depth) collected under moldboard (MP) and disk (DP) plows as conventional tillage (CT), and rotary (RP) and chisel (CP) plows as reduced tillage (RT) systems with a similar plant C input rate and cover crop over a period of six years (2005–2011) in a semi-arid calcareous soil (Calcixerepts) from Central Iran. Results indicated a clear difference in soil quality among the tillage systems with a significant increase of SQI under RT over time, particularly under CP practices. Although RT improved most soil microbial attributes, not all attributes contributed to SQI because of their close interrelationship. The final SQI consisted only of geometric mean of microbial activity (GMA, the square root of the product of PCM and PNM) and geometric mean of enzyme activity (GME, the cube root of the product of enzyme activities). Soil GME and GMA were found to be as key indicators contributing 55% and 36% to SQI, respectively. Therefore, the GME and GMA were the most important indicators effectively discriminating tillage systems, and could be used to monitor the enhancement of soil quality under RT in this semiarid environment. The influence of tillage year on SQI was greater than that of tillage practices. In conclusion, RT systems were characterized by a higher value of SQI, suggesting a good recovery of soil capacity and functions after abandoning CT in the studied area. Smallholder farmers should therefore be aware of the potential for high soil quality in future as a result of continuing RT systems, especially with surface tillage using CP practices.     

Energy budgeting and emergy synthesis of rainfed maize–wheat rotation system with different soil amendment applications

Soil is a non-renewable resource and its preservation is essential for food security, ecosystem services and our sustainable future. Simultaneously, it is a major challenge to substitute non-renewable fossil based resources with renewable resources to reduce environmental load. In order to check soil erosion vis-a-vis degradation of sloppy lands of rainfed maize–wheat rotation system, fertilization with organic manure supplemented with inorganic fertilizers is required. In order to address these issues, substitution of 50% NPK through four organic manures viz. farmyard manure (FYM), vermicompost (VC), poultry manure (PM) and in situ green manuring (GM) of sunnhemp (Crotalaria juncea L.) were evaluated against 100% NPK through inorganic fertilizers and through FYM for energy budgeting and emergy synthesis during 2009–2014. Integrated use of FYM along with 50% NPK fertilizers could maintain the highest energy ratio (7.3), human energy profitability (142.4), energy productivity (0.22 kg MJ⁻¹), and energy profitability (6.3 MJ ha⁻¹) over other treatments. However, GM and inorganic fertilizers on equal NPK basis maintained the highest energy intensiveness (24.61 MJ US $⁻¹) and exhibited higher emergy yield ratio (2.66) and lower emergy investment ratio (0.60) and environmental loading ratio (3.74) which resulted into higher environmental sustainability index (0.71) over other treatments. Fertilization with organic manure (FYM) alone could not compete with other fertilized options to energy budgeting and emergy synthesis except specific energy. The study demonstrated that innovative integrated nutrient management of chemical fertilizers and organic manures particularly FYM for energy budgeting and GM for emergy synthesis may be considered as feasible and environment-friendly options for soil conservation, thereby benefiting a 50% saving on costly chemical fertilizers in non-OPEC countries which import most of its phosphorus and potassium fertilizers.     

Alpine vascular plant species richness: the importance of daily maximum temperature and pH

Species richness in the alpine zone varies dramatically when communities are compared. We explored (i) which stress and disturbance factors were highly correlated with species richness, (ii) whether the intermediate stress hypothesis (ISH) and the intermediate disturbance hypothesis (IDH) can be applied to alpine ecosystems, and (iii) whether standing crop can be used as an easily measurable surrogate for causal factors determining species richness in the alpine zone. Species numbers and standing crop were determined in 14 alpine plant communities in the Swiss Alps. To quantify the stress and disturbance factors in each community, air temperature, relative air humidity, wind speed, global radiation, UV-B radiation, length of the growing season, soil suction, pH, main soil nutrients, waterlogging, soil movement, number of avalanches, level of denudation, winter dieback, herbivory, wind damage, and days with frost were measured or observed. The present study revealed that 82% of the variance in␣vascular species richness among sites could be explained by just two abiotic factors, daily maximum temperature and soil pH. Daily maximum temperature and pH affect species richness both directly and via their effects on other environmental variables. Some stress and disturbance factors were related to species richness in a monotonic way, others in an unimodal way. Monotonic relationships suggest that the harsher the environment is, the fewer species can survive in such habitats. In cases of unimodal relationships (ISH and IDH) species richness decreases at both ends of the gradients due to the harsh environment and/or the interaction of other environmental factors. Competition and disturbance seemed only to play a secondary role in the form of fine-tuning species richness in specific communities. Thus, we concluded that neither the ISH nor the IDH can be considered useful conceptual models for the alpine zone. Furthermore, we found that standing crop can be used as an easily measurable surrogate for causal factors determining species richness in the alpine zone, even though there is no direct causality.