A GIS-based plant prediction model for wetland ecosystems

An existing non-spatial model for the prediction of response of wetland plant species on ecological factors has been transformed into a GIS-based prediction model which produces spatial output at the landscape scale. The input, spatial patterns of the ecological factors, were constructed with geostatistical spatial interpolation (kriging). With this GIS-based model the spatial patterns of presence and absence of 78 wetland plant species are predicted for an area with wetlands in the Netherlands of approximately 500 square kilometers. The GIS-based model has been validated, and the estimated uncertainty of the input has been propagated through the model. At the species level the output shows spatially coherent and non-random patterns. The validation is affected by the propagation of input errors through the model. The number of valid predictions declines approximately 10–20% when 95% confidence intervals are used in the validation. This study shows that it is feasible to use a geostatistical interpolation method to construct spatial patterns of ecological factors on a landscape scale and to use these patterns as input for a GIS-based prediction model. The added uncertainty on the input values however, affects the number of valid predictions of the model.     

Sporulation of Pyrenopeziza brassicae (light leaf spot) on oilseed rape (Brassica napus) leaves inoculated with ascospores or conidia at different temperatures and wetness durations

In controlled environment experiments, sporulation of Pyrenopeziza brassicae was observed on leaves of oilseed rape inoculated with ascospores or conidia at temperatures from 8 to 20°C at all leaf wetness durations from 6 to 72 h, except after 6 h leaf wetness duration at 8°C. The shortest times from inoculation to first observed sporulation ( l ₀), for both ascospore and conidial inoculum, were 11–12 days at 16°C after 48 h wetness duration. For both ascospore and conidial inoculum (48 h wetness duration), the number of conidia produced per cm² leaf area with sporulation was seven to eight times less at 20°C than at 8, 12 or 16°C. Values of Gompertz parameters c (maximum percentage leaf area with sporulation), r (maximum rate of increase in percentage leaf area with sporulation) and l ₃₇ (days from inoculation to 37% of maximum sporulation), estimated by fitting the equation to the observed data, were linearly related to values predicted by inserting temperature and wetness duration treatment values into existing equations. The observed data were fitted better by logistic equations than by Gompertz equations (which overestimated at low temperatures). For both ascospore and conidial inoculum, the latent period derived from the logistic equation (days from inoculation to 50% of maximum sporulation, l ₅₀) of P. brassicae was generally shortest at 16°C, and increased as temperature increased to 20°C or decreased to 8°C. Minimum numbers of spores needed to produce sporulation on leaves were ≈25 ascospores per leaf and ≈700 conidia per leaf, at 16°C after 48 h leaf wetness duration.     

Growth of the mycoparasitic fungus Verticillium biguttatum from different geographical origins at near-minimum temperatures

Sclerotia ofRhizoctonia solani collected from potato tubers from different countries were assayed for the presence of mycoparasites. Among the mycoparasites observedVerticillium biguttatum predominated. Its geographical distribution was not restricted to certain latitudes or soil types;V. biguttatum occurred worldwide in potato fields.The minimum growth temperature of 57V. biguttatum isolates was found to be in the narrow range from 10 to 13°C, irrespective of their geographical origin. A non-linear logistic growth model was used to describe the radial growth onRhizoctonia mycelium and nutrient agar plates. At near-minimum temperature the maximum colony radii varied considerably; they were up to 3.8 times that of the reference isolate M73. Based on parameter values for logistic growth, fast-and slow-growing isolates could be distinguished. Although the growth properties ofV. biguttatum isolates from different locations varied, the presence of fast- and slow-growing isolates was not restricted to particular areas and both types could be found in the same field. However, bioassays with selected fast- and slow-growing isolates do not support the assumption that growth at near-minimum temperatures is a relevant criterion for screening isolates ofV. biguttatum in terms of effectiveness for biological control ofR. solani.     

快速城镇化地区农户生计资本分化特征及其对生计策略的影响——以上海市青浦区为例

在中国快速城镇化背景下,探讨农户生计资本与生计策略二者之间的关系对实现农户可持续生计具有重要意义。以上海市青浦区为例,在分析农户生计资本分化特征的基础上,运用多分类逻辑回归模型对农户生计资本和生计策略的关系进行了定量化模拟,以揭示影响农户生计策略选择的主要因素。结果表明:1)作为快速城镇化背景下的发达地区,农户生计策略类型分化为传统农业型、专业农业型、农业兼业型、非农兼业型和非农型等多种形态。2)不同生计策略类型农户的资本状况存在差异,大小顺序依次为专业农业型、非农兼业型、非农型、农业兼业型和传统农业型。其中,专业农业型农户在自然资本、物质资本和金融资本等方面均具有显著优势,非农型农户在人力资本方面具有优势,非农兼业型农户在社会资本方面表现最佳。3)多分类逻辑回归模型结果显示家庭整体劳动能力等7个变量是影响农户生计策略选择的主要因素,其中,户均家庭年收入起到重要作用。研究表明,农户所拥有的生计资本状况影响着其生计策略的选择,政府可以通过对不同生计类型农户采取针对性措施来改善其生计资本状况,以实现农户生计转型与可持续发展。     

基于Logistic-GTWR模型的武汉城市圈城镇用地扩展驱动力分析

该文以武汉城市圈为例,利用1995年、2000年、2005年、2010年、2015年5期土地利用数据、社会经济因子、邻域因子和自然因子,构建耦合空间异质性和时间非平稳性的Logistic-GTWR(逻辑斯蒂-时空地理加权回归)模型,挖掘武汉城市圈城镇用地扩展驱动力及其时空分异格局。结果表明:1)耦合空间异质性和时间非平稳性的Logistic-GTWR模型比全局Logistic回归模型和Logistic-GWR(逻辑斯蒂-地理加权回归)模型具有更好的拟合效果,验证了Logistic-GTWR模型在城镇用地扩展驱动力分析研究中的适用性。2)武汉城市圈城镇用地扩展的不同影响因子系数时空分异格局各不相同,人口因子高值分布区围绕武汉市先收缩后扩散并逐渐稳定,最终形成绕武汉城市圈中部沿线周边环状分布格局;地均GDP因子高值分布区先向西部转移,后逐渐趋于均衡,最终形成绕武汉、麻城和崇阳县周边集聚分布的空间格局。武汉市极化作用占据主导地位,且影响范围不断扩大。3)人口和经济是20年间武汉城市圈城镇扩展的核心驱动因子,且影响力呈逐年上升趋势;国道、高速和省道影响力整体呈略微升高态势。4)武汉城市圈中部及东部城市多为人口、经济核心驱动型城市,高程影响在武汉市发展中逐渐凸显;西部城市主要受高程限制,并以交通及经济驱动为主,东西差异显著;但西部城市1995年以来人口和经济的作用强度逐步增加。人口因子作用强度在咸宁和黄冈呈逐渐上升趋势,经济因子作用强度在武汉、孝感、仙桃、天门、潜江和黄冈逐年上升。     

基于无人机多光谱影像的棉叶螨识别方法

【目的】利用无人机遥感在空间分辨率和光谱分辨率上的优势,研究大面积棉田棉叶螨监测方法,为类似的农作物虫害遥感监测研究提供参考。【方法】选20种光谱指数作为螨害监测的特征因子,使用赤池信息准则作为模型优选依据,获取最佳建模特征,建立棉田螨害监测识别的logistic回归模型。【结果】在所分析的全部光谱指数中,TVI、DVI和RDVI为螨害监测的最佳特征因子,基于该3个因子构建的logistic回归模型的分类准确率为95%,F1值为95.1%,能够较好地实现棉田螨害识别。【结论】监测模型可以实现区域范围的棉叶螨快速识别。     

Eurasian perch Perca fluviatilis growth and fish community structure,inside and outside a marine‐protected area in the Baltic Sea

Growth of Eurasian perch Perca fluviatilis L. and fish community structure between sites within a marine‐protected area (MPA) and unprotected sites in the Baltic Sea were examined. Von Bertalanffy, logistic and Gompertz growth models were fitted to P. fluviatilis length at age data, and the logistic model was the most parsimonious for growth between locations. A larger mean maximum size (L_∞) and a smaller instantaneous growth rate (g) were found within the MPA. All three models also predicted that after age seven, fish inside the MPA would be larger. Community structure differed with more P. fluviatilis collected outside of the MPA, and more roach Rutilus rutilus (L.) and bleak Alburnus alburnus (L.) collected inside the MPA. These growth differences may be indicative of recreational fishing effects on P. fluviatilis outside of the MPA, a result of complex interspecific and intraspecific species interactions, or other undetected environmental variation between locations.     

岩羊和马鹿对人与机动车反应的差异分析

人为干扰会对野生动物种间关系、个体适合度、群落结构和繁殖成功率等产生中长期的影响。因此,研究野生动物反干扰行为对于我们认识该物种对其生境的行为适应和进化机制具有重要意义。2017年11—12月在内蒙古贺兰山国家级自然保护区内通过建立多元逻辑斯蒂回归模型研究了岩羊(Pseudois nayaur)、马鹿(Cervus elaphus)的反干扰策略,本研究共设置33条样线,记录了10种在人为干扰下可能会影响岩羊、马鹿反应行为的变量,经模型分析发现影响岩羊反应行为的变量有5种,影响马鹿反应行为的变量有4种,共同影响因子分别是干扰源、性别、头的朝向和地形特征,而植被类型则只对岩羊产生影响。最后根据逻辑模型得出的数据计算发生比,从而了解各个分类变量与反应行为的关系。     

民族地区农户兼业意愿及影响因素分析

【目的】深入考察民族地区农户兼业意愿及影响因素,为民族地区农户兼业政策的制定提供理论依据。【方法】对重庆市石柱县进行实地调查,以问卷、访谈等方式收集数据,并利用Logistic模型分析农户兼业影响因素。【结果】民族地区农户兼业意愿强烈,农户的性别、年龄、文化程度、家庭规模、是否拥有专业技能、小孩能否在父母打工地入学、土地是否容易转租、兼业信息渠道和致富意愿等因素均显著影响农户兼业意愿。【建议】地方政府应加强职业教育培训、完善土地流转制度、统筹城乡发展、建立农户兼业信息网络体系等,以推动民族地区农户兼业发展。     

生态畜牧业视角下农户经济行为的实证研究——基于甘肃省576个牧户的样本数据

近年来,生态环境的恶化严重困扰着我国社会经济的可持续发展,也影响到畜产品的安全和质量。发展生态畜牧业已成为我国畜牧业发展的必然选择和未来方向。文中基于对生态脆弱地区牧户的实地调查,通过建立计量经济模型,实证分析了牧户对生态畜牧业的认知现状及影响认知的因素。结果表明:牧户对生态畜牧业的认知程度较低,同时,政府对生态畜牧业的宣传情况、政府技术推广情况、政府对疫病和药物残留的监管情况、牧户的专业化程度、牧户使用畜牧良种情况、畜牧业收入占家庭收入比例对牧户的生态畜牧业认知有显著的正向影响。