Modelling the biological invasion of Prosopis juliflora using geostatistical-based bioclimatic variables under climate change in arid zones of southwestern Iran

Invasive species have been the focus of ecologists due to their undesired impacts on the environment.The extent and rapid increase in invasive plant species is recognized as a natural cause of global-biodiversity loss and degrading ecosystem services.Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions.Understanding the impact of climate change on species invasion is crucial for sustainable biodiversity conservation.In this study,the possibility of mapping the distribution of invasive Prosopis juliflora(Swartz)DC.was shown using present background data in Khuzestan Province,Iran.After removing the spatial bias of background data by creating weighted sampling bias grids for the occurrence dataset,we applied six modelling algorithms(generalized additive model(GAM),classification tree analysis(CTA),random forest(RF),multivariate adaptive regression splines(MARS),maximum entropy(Max Ent)and ensemble model)to predict invasion distribution of the species under current and future climate conditions for both optimistic(RCP2.6)and pessimistic(RCP8.5)scenarios for the years 2050 and 2070,respectively.Predictor variables including weighted mean of CHELSA(climatologies at high resolution for the Earth’s land surface areas)-bioclimatic variables and geostatistical-based bioclimatic variables(1979–2020),physiographic variables extracted from shuttle radar topography mission(SRTM)and some human factors were used in modelling process.To avoid causing a biased selection of predictors or model coefficients,we resolved the spatial autocorrelation of presence points and multi-collinearity of the predictors.As in a conventional receiver operating characteristic(ROC),the area under curve(AUC)is calculated using presence and absence observations to measure the probability and the two error components are weighted equally.All models were evaluated using partial ROC at different thresholds and other statistical indices derived from confusion matrix.Sensitivity analysis showed that mean diurnal range(Bio2)and annual precipitation(Bio12)explained more than 50% of the changes in the invasion distribution and played a pivotal role in mapping habitat suitability of P.juliflora.At all thresholds,the ensemble model showed a significant difference in comparison with single model.However,Max Ent and RF outperformed the others models.Under climate change scenarios,it is predicted that suitable areas for this invasive species will increase in Khuzestan Province,and increasing climatically suitable areas for the species in future will facilitate its future distribution.These findings can support the conservation planning and management efforts in ecological engineering and be used in formulating preventive measures.     

Land Use – Land Cover Conversion, Regeneration and Degradation in the High Elevation Bolivian Andes

Regional land-cover change affects biodiversity, hydrology, and biogeochemical cycles at local, watershed, and landscape scales. Developing countries are experiencing rapid land cover change, but assessment is often restricted by limited financial resources, accessibility, and historical data. The assessment of regional land cover patterns is often the first step in developing conservation and management plans. This study used remotely sensed land cover and topographic data (Landsat and Shuttle Radar Topography Mission), supervised classification techniques, and spectral mixture analysis to characterize current landscape patterns and quantify land cover change from 1985 to 2003 in the Altiplano (2535–4671 m) and Intermediate Valley (Mountain) (1491–4623 m) physiographic zones in the Southeastern Bolivian Andes. Current land cover was mapped into six classes with an overall accuracy of 88% using traditional classification techniques and limited field data. The land cover change analysis showed that extensive deforestation, desertification, and agricultural expansion at a regional scale occurred in the last 20 years (17.3% of the Mountain Zone and 7.2% of the Altiplano). Spectral mixture analysis (SMA) indicated that communal rangeland degradation has also occurred, with increases in soil and non-photosynthetic vegetation fractions in most cover classes. SMA also identified local areas with intensive management activities that are changing differently from the overall region (e.g., localized areas of increased green vegetation). This indicates that actions of local communities, governments, and environmental managers can moderate the potentially severe future changes implied by the results of this study.     

Evaluation of Breeding Value and Selection of Bull Dams in the Danish Dairy Breeds: I. Studies on Realized Efficiency of Bull Dam and Bull Sire Selection

Abstract

The relationship between twice the adjusted daughter yield deviation (DYD) of the son and the average of the estimated breeding values (EBV) of his parents was investigated for milk and fat yield. Deviations from expectations of DYD minus the pedigree index and the regression of DYD on the EBV for each of the parents were estimated. The EBV of each bull dam was calculated in several ways using different combinations of pedigree information and their own records. In all, 1693 bulls (880 Black and White (BW), 418 Red Danish (RD) and 395 Danish Jersey (DJ)) with Direct Updating indices for milk and fat yield were included in the investigation. Mean discrepancies between estimated and observed genetic merit for kg of milk yield were ?348 for BW, ?213 for RD and ?228 for DJ, when all of the bull dams' individual records were utilized in breeding value estimation. The corresponding mean discrepancies for kg of fat yield were ?14.7, ?11.5 and ?11.9, respectively. The discrepancies were positively correlated with the number of lactation records included in the dams' EBVs. Regression coefficients of bull DYDs on bull dam breeding values were significantly lower than expected for RD and BW regardless of the number of individual lactation records included in the dams' indexes for milk and fat yield. For all three breeds, the regression coefficients were lowest for fat yield. The most probable cause of overestimation in bull dam EBVs is preferential treatment, particularly in second and later lactations. To avoid this bias, estimation of a bull dam's breeding value should be based on pedigree information and on records from only her first lactation.     

论光敏核不育系HN5s的分类地位

程氏指数法、外稃双峰乳突鉴定法、同工酶分析及亲和性分析等4种方法研究了光敏核不育系HN5s的分类地位.结果显示:HN5s在程氏指数、外稃双峰乳突鉴定均表现类似籼稻的特征,但脱粒性明显属粳型;除Amp外.同工酶Acp和Est也都呈籼稻的特征;亲和性研究表明,HN5s对4个广亲和性鉴定标准测验种和7个典型籼、粳品种均有较高的杂交亲和     

来源和质量不同对山羊卵母细胞体外成熟率的影响

比较了卵母细胞级别对体外成熟率的影响,以及促卵泡素(FSH)处理山羊对卵母细胞采集的数量和质量的影响。结果表明:卵母细胞级别对体外成熟率有显著影响,不论是来源于FSH处理卵巢还是屠宰场卵巢,均是A、B级卵母细胞的成熟率高于C级卵母细胞,差异极显著(P<0.01)。但是A、B级卵母细胞之间差异不显著;卵巢来源对卵母细胞采集的数量和质量有显著影响,A、B级卵母细胞在获卵总数中所占的比例,平均每个卵巢获卵母细胞数及A、B级卵母细胞数,均是FSH处理卵巢高于屠宰场卵巢,差异显著(P<0.05);卵巢来源对卵母细胞体外成熟率有显著影响,来自于FSH处理卵巢的卵母细胞体外成熟率高于屠宰场卵巢(81.6%比67.6%),差异极显著(P<0.01)。     

Postharvest noninvasive assessment of fresh chestnut (Castanea spp.) internal decay using computer tomography images

X-ray computed tomography (CT) is an effective noninvasive tool to visualize fresh agricultural commodities’ internal components and quality attributes, including those of chestnuts (Castanea spp). There is no procedure to automatically, effectively and efficiently classify fresh commodities from a continuous inline flow through a CT system. If the information obtained by CT scanning of fresh agricultural commodities is to be used in an industrial application (e.g. inline sorting), automated interpretation of CT images is essential. For this purpose, an image analysis method (algorithm) for the automatic classification of CT images obtained from 2848 fresh chestnuts (cv. ‘Colossal’ and ‘Chinese seedlings’), during the harvesting years from 2009 to 2012, was developed and tested. Classification accuracy was evaluated by comparing the classes obtained from six CT images per chestnut to their internal quality assessment. An experienced human rater performed internal quality assessment by visually and invasively rating fresh chestnut internal decay severity (quality) into 5-, 3- and 2-classes.After CT image preprocessing, cropping and segmentation, 1194 grayscale intensity and textural features were extracted from six resultant CT images per sample. Relevant features were selected using a sequential forward selection algorithm with the Fisher discriminant objective function. 86, 155 and 126 features were effective in designing a quadratic discriminant classifier with a 4-fold cross-validation with a performance accuracy of 85.9%, 91.2% and 96.1% for 5, 3 and 2 classes, respectively. This method is accurate and objective in determining fresh chestnut internal quality, and the methodology is applicable to automatic noninvasive inline CT sorting system development.     

Reliability model for Subsystems of CNC machine tool with small samples

Many subsystems in CNC machine tool have only a few failures, so they are small samples. In this case, classical reliability modeling method often has large errors. For the failure data of small sample, maximum likelihood estimation method is used to estimate the Weibull distribution model parameters of time between failures of the subsystems. Then, the Weibull distribution model parameters are modified by parameter bias correction method. Finally, the effect of bias correction parametersis tested by the D test and the error area ratio test method. The test results show that the modified models are better.     

景观分类在自然资源有效管理中的应用

通过对景观类型的分灰，结合不同景观类型的特点，论述了不同景观类型采取不同管理、组织、措施的观点。     

土地利用动态监测中多源影像融合方法的比较研究--以陕北黄土丘陵沟壑区为例

在陕北黄土丘陵沟壑区,采用单一传感器的遥感影像提取土地利用信息,存在着识别的土地利用类别少、某些类别混分现象较严重、分类结果的精度较低等问题。以TM多光谱数据和SPOT全色光谱数据的融合为例,提出了适宜于该地区的两种影像融合方法:主成分变换法和乘积运算法,并从影像的光谱质量、纹理信息和目视效果等方面对其进行了对比与评价。结果显示,主成分变换法为较理想的融合方法。以陕北无定河流域为实验样区的土地利用自动分类结果表明,该方法的应用使土地利用各类别的提取精度都有不同程度的提高;水体、水田和城镇用地等面积较小的类别分类正确率提高达到10%以上;坡耕地与林草地的混分明显减少,分类精度均提高了5%以上;分类总精度从82.0%提高到89.2%,取得了良好的分类效果。此研究对于遥感影像融合技术的评价与应用进行了有益的探索,同时为该地区的土地利用动态监测提供了关键技术。     

南方地区高水分玉米安全度夏技术探讨

根据水分的高低,对新收购的高水分玉米分别储存在露天囤和高大平房仓中,将露天囤里的玉米通风降水后转入高大平房仓储存,再对玉米通风降温,并采取仓房密封、悬挂防晒网、空调控温等配套措施控制粮温,期间采取磷化铝多次补药熏蒸杀灭粮堆内害虫及霉菌,使玉米安全度夏。