SUBWATERSHED SPATIAL ANALYSIS TOOL: DISCRETIZATION OF A DISTRIBUTED HYDROLOGIC MODEL BY STATISTICAL CRITERIA1

ABSTRACT: Complex hydrologic models, designed for simulating larger watersheds, require a huge amount of input data. Most of these models use spatially distributed data as inputs. Spatial data can be aggregated or disaggregated for use as input to a model, which can impact model outputs. Although, it is efficient to minimize data redundancy by aggregating the spatial data, upscaling reduces the detail/resolution of input information and increases model uncertainty. On the other hand, a large number of model inputs with high degrees of disaggregation take more computer time and space to process. Hence, a balance between striving for a maximum level of aggregation and a minimum level of information loss has to be achieved. This study presents a definition of an appropriate level of discretization, derived by establishing a relationship between a model's efficiency and the number of subwater‐sheds modeled. An entropy based statistical approach/tool called Subwatershed Spatial Analysis Tool (SUSAT) was developed to find an objective choice of an appropriate level of discretization. The new approach/tool was applied to three watersheds, each representing different hydrologic conditions, using a hydrologic model. Coefficients of efficiency and entropy estimated at different levels of discretization were used to validate the success of the new approach.     

Combining geodiversity with climate and topography to account for threatened species richness

Understanding threatened species diversity is important for long‐term conservation planning. Geodiversity—the diversity of Earth surface materials, forms, and processes—may be a useful biodiversity surrogate for conservation and have conservation value itself. Geodiversity and species richness relationships have been demonstrated; establishing whether geodiversity relates to threatened species’ diversity and distribution pattern is a logical next step for conservation. We used 4 geodiversity variables (rock‐type and soil‐type richness, geomorphological diversity, and hydrological feature diversity) and 4 climatic and topographic variables to model threatened species diversity across 31 of Finland's national parks. We also analyzed rarity‐weighted richness (a measure of site complementarity) of threatened vascular plants, fungi, bryophytes, and all species combined. Our 1‐km² resolution data set included 271 threatened species from 16 major taxa. We modeled threatened species richness (raw and rarity weighted) with boosted regression trees. Climatic variables, especially the annual temperature sum above 5 °C, dominated our models, which is consistent with the critical role of temperature in this boreal environment. Geodiversity added significant explanatory power. High geodiversity values were consistently associated with high threatened species richness across taxa. The combined effect of geodiversity variables was even more pronounced in the rarity‐weighted richness analyses (except for fungi) than in those for species richness. Geodiversity measures correlated most strongly with species richness (raw and rarity weighted) of threatened vascular plants and bryophytes and were weakest for molluscs, lichens, and mammals. Although simple measures of topography improve biodiversity modeling, our results suggest that geodiversity data relating to geology, landforms, and hydrology are also worth including. This reinforces recent arguments that conserving nature's stage is an important principle in conservation.     

Nitrogen deposition alters soil chemical properties and bacterial communities in the Inner Mongolia grassland

Nitrogen deposition has dramatically altered biodiversity and ecosystem functioning on the earth; however, its effects on soil bacterial community and the underlying mechanisms of these effects have not been thoroughly examined. Changes in ecosystems caused by nitrogen deposition have traditionally been attributed to increased nitrogen content. In fact, nitrogen deposition not only leads to increased soil total N content, but also changes in the NH₄⁺-N content, NO₃^--N content and pH, as well as changes in the heterogeneity of the four indexes. The soil indexes for these four factors, their heterogeneity and even the plant community might be routes through which nitrogen deposition alters the bacterial community. Here, we describe a 6-year nitrogen addition experiment conducted in a typical steppe ecosystem to investigate the ecological mechanism by which nitrogen deposition alters bacterial abundance, diversity and composition. We found that various characteristics of the bacterial community were explained by different environmental factors. Nitrogen deposition decreased bacterial abundance that is positively related to soil pH value. In addition, nitrogen addition decreased bacterial diversity, which is negatively related to soil total N content and positively related to soil NO₃^--N heterogeneity. Finally, nitrogen addition altered bacterial composition that is significantly related to soil NH₄⁺-N content. Although nitrogen deposition significantly altered plant biomass, diversity and composition, these characteristics of plant community did not have a significant impact on processes of nitrogen deposition that led to alterations in bacterial abundance, diversity and composition. Therefore, more sensitive molecular technologies should be adopted to detect the subtle shifts of microbial community structure induced by the changes of plant community upon nitrogen deposition.     

秦岭中段北坡不同海拔土壤中细菌群落的分布特征及区域差异比较

为深入理解土壤细菌群落沿海拔梯度的分布特征,以秦岭山脉中段的朱雀国家森林公园朱雀山北坡（简称“朱雀北坡”）与太白山自然保护区太白山北坡（简称“太白山北坡”）为研究区域,海拔梯度上每隔400 m设置采样点,通过高通量测序研究土壤细菌群落的海拔变化规律及其关键影响因素.结果表明:研究区域内,随海拔升高,土壤pH趋于降低（太白山北坡不明显）,w（TC）、w（TN）、w（TOC）均显著升高,w（TP）也趋于升高（朱雀北坡不明显）.两个区域土壤细菌中相对丰度最高的均为变形菌门和酸杆菌门,朱雀北坡随海拔梯度变化显著的细菌主要包括变形菌门、硝化螺旋菌门、浮霉状菌门、酸杆菌门、放线菌门,其中,硝化螺旋菌门相对丰度与海拔呈正相关,放线菌门相对丰度与海拔呈负相关;太白山北坡随海拔梯度变化显著的细菌主要包括放线菌门、疣微菌门、浮霉状菌门、绿弯菌门,其中,放线菌门相对丰度与海拔呈负相关,其余三者相对丰度与海拔呈正相关.两个区域土壤细菌多样性指数（如Shannon-Wiener指数、Chao1指数、observed-species指数、PD_whole_tree指数等）沿海拔梯度均无明显变化规律,但太白山北坡数值整体上高于朱雀北坡.典范对应分析（canonical correlation analysis,CCA）结果显示,影响朱雀北坡和太白山北坡土壤细菌群落结构的主要因素均为pH和w（TOC）.研究显示,不同海拔梯度也是导致秦岭中段北坡土壤细菌群落差异的重要因素.      

气候变化和人类活动对东部沿海地区NDVI变化的影响分析

植被是陆地生态系统的重要组成部分,特别是在人类活动密集地区,良好的植被覆盖对于维持区域生态环境稳定、增进居民生活福祉和促进社会经济可持续发展意义重大.基于归一化植被指数(NDVI)、气温、降水和太阳辐射数据,采用趋势分析、偏相关分析和残差分析等方法,探究了1982～2019年中国东部沿海地区NDVI时空变化特征及其与气候因子的关系,评估了气候因素和人类活动等非气候因素对NDVI变化的影响.结果表明：(1)1982～2019年研究区NDVI变化趋势具有明显区域性、阶段性和季节性差异,就区域平均而言,2000年以前(第一阶段)的生长季NDVI比2001年以后(第二阶段)增加更快,而两阶段春季NDVI增加速率均为各季节最快;(2)同一阶段NDVI与各气候因子的关系在不同季节存在差异,而同一季节NDVI的主要气候控制因子在不同阶段也不一致,并且NDVI与气候因子的关系具有很大空间差异.总体上,1982～2019年研究区生长季NDVI的增加与气温的持续上升关系紧密,第二阶段降水和太阳辐射的增加也产生了积极作用;(3)相比于人类活动等非气候因素的影响,气候变化对近38年来研究区生长季NDVI变化的...     

Leaching of atrazine, metolachlor and diuron in the field in relation to their injection depth into a silt loam soil

A field experiment was conducted on a Calcaric Cambisol soil to study the consequences of the penetration depth and properties of pesticides on the risk of subsequent leaching. Three pesticides with different mobility characteristics and bromide were injected at 30 cm (where soil organic matter (OM) was 2%) and 80 cm (soil OM 0.5%) on irrigated plots without a crop. The migration of injected solutes was assessed for two years by sampling the soil solution using six porous cups installed at 50 and 150 cm depth and by relating solute contents to drainage water flux estimated by the STICS model (Simulateur mulTIdisciplinaire pour les Cultures Standard). Pesticides injected at 30 cm were strongly retained so that no metolachlor or diuron was detected at 50 and 150 cm. The ratio of atrazine peak concentration in the soil solution to concentration in the injected solution (C/C₀) was 1 × 10⁻³ and 0.2 × 10⁻³, respectively, at 50 and 150 cm. When injected at 80 cm, (C/C₀) of atrazine, metolachlor and diuron were 10 × 10⁻³, 1 × 10⁻³ and 0.3 × 10⁻³ at 150 cm, respectively; 1/(C/C₀) was correlated with K_oc values reported from databases. The ratio of drainage volume to the amount of water at field capacity in the soil layer between the injection point at 30 cm and the water sampling level (V/V₀) at 50 and 150 cm was 0.6 and 0.9, respectively, for bromide and 1.6 and 1.0 for atrazine. V/V₀ of the injected solutes at 80 cm was for bromide, atrazine, metolachlor and diuron 0.6, 0.9, 1.2 and 1.7, respectively; pesticide V/V₀ was correlated with K_oc. The retardation factor was a good indicator of migration risk, but tended to overestimate retardation of molecules with high K_oc. Atrazine desorption represented an additional leaching risk as a source of prolonged low contamination. The large variability in soil solution of bromide and pesticide concentrations in the horizontal plane was attributed to flow paths and clods in the tilled soil layer. This heterogeneity was assumed to channel water fluxes into restricted areas and thereby increase the risk of groundwater contamination. The methodology used in the field proves to provide consistent results.     

The Botanist Effect Revisited: Plant Species Richness, County Area, and Human Population Size in the United States

Abstract:  The "botanist effect" is thought to be the reason for higher plant species richness in areas where botanists are disproportionately present as an artefactual consequence of a more thorough sampling. We examined whether this was the case for U.S. counties. We collated the number of species of vascular plants, human population size, and the area of U.S. counties. Controlling for spatial autocorrelation and county area, plant species richness increased with human population size and density in counties with and without universities and/or botanical gardens, with no significant differences in the relation between the two subsets. This is consistent with previous findings and further evidence of a broad-scale positive correlation between species richness and human population presence, which has important consequences for the experience of nature by inhabitants of densely populated regions. Combined with the many reports of a negative correlation between the two variables at a local scale, the positive relation between plant species richness in U.S. counties and human population presence stresses the need for the conservation of seminatural areas in urbanized ecosystems and for the containment of urban and suburban sprawl.     

Resampling methods for estimating dispersion indices in random and adaptive designs

In many surveys in environmental and natural phenomena the aim is to evaluate the heterogeneity, and the skewness of the distribution of the number point-objects in the study area opportunely partitioned in sub-regions. For this purpose, in this paper the estimation of dispersion indices is considered by using simple random sampling and adaptive sampling with initial simple random sampling selected with replacement or without replacement. The jackknife and the bootstrap procedures are proposed in both cases for reducing bias. Finally, both a simulation study and a case study on biological population referred to a Oidium tuckeri contamination in a growing vineyard is performed to assess the accuracy of the proposed estimators.     

青藏高原典型高寒草甸区土壤有机碳氮的变异特性

本研究应用地统计学的基本原理与方法(半方差分析)对青藏高原典型高寒草甸区0～10 cm土壤有机碳和全氮空间变异性进行了分析.结果表明,0～10 cm的土壤有机碳和全氮的平均含量分别为11.45 g·kg^-1和1.02 g·kg^-1,平均变异系数分别为0.23和0.21,反映出该植被区土壤肥力较为贫瘠.土壤有机碳和全氮随机因素的变异占总空间异质性变异的比率分别为44.7%和49.9%,变异尺度分别为210.9 m和200.1 m,随机因素的影响主要发生在采样尺度＜10 m的范围之内.在该研究区域上土壤有机碳和全氮均表现出空间自相关因素大于随机因素的变异格局;在空间结构的变异上,由土壤内在属性如土壤矿物质、地形等空间自相关因素和人为因素如放牧及工程施工等对土壤表层的践踏引起的随机因素共同起作用,影响程度呈中等水平.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.