松花江流域沉积物ATP微生物量的分布特征

分析松花江流域沉积物中三磷酸腺苷(ATP)微生物量的分布,结果表明,ATP分布具有显著的空间特征,在河流发源地及部分城市地区河流段沉积物中具有高的ATP含量,统计分析(主成分分析,多元回归树分析和响应模型分析)表明:ATP是沉积物的主要成分性质之一,在本研究所涉及11个因子中,影响ATP分布变异的第一因子是空间位置(纬度,39.79%),然后是环境因子(总氮,18.49%;硝氮,16.24%),其中ATP随纬度呈二次曲线变化(P<0.001),与总氮呈显著正相关(P=0.027),和硝氮呈显著负相关(P<0.01).同时ATP也随有机质、总磷和海拔的增加而呈增加趋势(P<0.05).沉积物ATP与多种营养元素及其不同形态具有显著相关性,表明通过ATP活性微生物量可以反映水体环境的营养水平.     

有机碳对土壤中有机氯污染物分布特征的影响

为了研究清洁地区土壤中w(OC)对有机氯污染物分布特征的影响,选择2006年春秋季采集于四川卧龙自然保护区高海拔地区的25个土壤样品,利用GC-HRMS方法测试有机氯污染物的残留量,利用回归分析方法研究有机氯污染物质量分数与w(OC)和海拔高度之间的关系. 结果表明:卧龙自然保护区有机氯污染物的质量分数均小于1 ng/g,与世界上其他边远地区的非农业土壤相似;土壤中w(OC)对有机氯污染物的分布特征有重要影响,分析的10种有机氯污染物质量分数〔以w(OC)校正〕与海拔高度均表现出较好的指数相关,且具有显著的统计学意义;有机氯污染物的质量分数〔以w(OC)校正〕随海拔高度上升而增加,表现出明显的“冷捕集”效应. 因此,在研究清洁地区土壤中有机氯污染物的分布特征时,以w(OC)进行校正是合理和重要的.      

Comparison of alternative strategies for invasive species distribution modeling

Species distribution models (SDMs) can provide useful information for managing biological invasions, such as identification of priority areas for early detection or for determining containment boundaries. However, prediction of invasive species using SDMs can be challenging because they typically violate the core assumption of being at equilibrium with their environment, which may lead to poorly guided management resulting from high levels of omission. Our goal was to provide a suite of potential decision strategies (DSs) that were not reliant on the equilibrium assumption but rather could be chosen to better match the management application, which in this case was to ensure containment through adequate surveillance. We used presence-only data and expert knowledge for model calibration and presence/absence data to evaluate the potential distribution of an introduced mesquite (Leguminoseae: Prosopis) invasion located in the Pilbara Region of northwest Western Australia. Five different DSs with varying levels of conservatism/risk were derived from a multi-criteria evaluation model using ordered weighted averaging. The performance of DSs over all possible thresholds was examined using receiver operating characteristic (ROC) analysis. DSs not on the convex hull of the ROC curves were discarded. Two threshold determination methods (TDMs) were compared on the two remaining DSs, one that assumed equilibrium (by maximizing overall prediction success) and another that assumed the invasion was ongoing (using a 95% threshold for true positives). The most conservative DS fitted the validation data most closely but could only predict 75% of the presence data. A more risk-taking DS could predict 95% of the presence data, which identified 8.5 times more area for surveillance, and better highlighted known populations that are still rapidly invading. This DS and TDM coupling was considered to be the most appropriate for our management application. Our results show that predictive niche modeling was highly sensitive to risk levels, but that these can be tailored to match specified management objectives. The methods implemented can be readily adapted to other invasive species or for conservation purposes.     

Modeling soil and plant phosphorus within DSSAT

The crop models in the Decision Support System for Agrotechnology Transfer (DSSAT) have served worldwide as a research tool for improving predictions of relationships between soil and plant nitrogen (N) and crop yield. However, without a phosphorus (P) simulation option, the applicability of the DSSAT crop models in P-deficient environments is limited. In this study, a soil-plant P model integrated to DSSAT was described, and results showing the ability of the model to mimic wide differences in maize responses to P in Ghana are presented as preliminary attempts to testing the model on highly weathered soils. The model simulates P transformations between soil inorganic labile, active and stable pools and soil organic microbial and stable pools. Plant growth is limited by P between two concentration thresholds that are species-specific optimum and minimum concentrations of P defined at different stages of plant growth. Phosphorus stress factors are computed to reduce photosynthesis, dry matter accumulation and dry matter partitioning. Testing on two highly weathered soils from Ghana over a wide range of N and P fertilizer application rates indicated that the P model achieved good predictability skill at one site (Kpeve) with a final grain yield root mean squared error (RMSE) of 535 kg ha⁻¹and a final biomass RMSE of 507 kg ha⁻¹. At the other site (Wa), the RMSE was 474 kg ha⁻¹ for final grain yield and 1675 kg ha⁻¹ for final biomass. A local sensitivity analysis indicated that under P-limiting conditions and no P fertilizer application, crop biomass, grain yield, and P uptake could be increased by over 0.10% due to organic P mineralization resulting from a 1% increase in organic carbon. It was also shown that the modeling philosophy that makes P in a root-free zone unavailable to plants resulted in a better agreement of simulated crop biomass and grain yield with field measurements. Because the complex soil P chemistry makes the availability of P to plants extremely variable, testing under a wider range of agro-ecological conditions is needed to complement the initial evaluation presented here, and extend the use of the DSSAT-P model to other P-deficient environments.     

Unified methodology for site-characterization and sampling of highway runoff

Hydrology, roadway traffic conditions, and atmospheric deposition are three essential data categories for the planning and implementation of highway-runoff monitoring and characterization programs. Causal variables pertaining to each data category could be site specific but have been shown to correlate with runoff pollutant loads. These data categories were combined to derive statistical relationships for characterization and prioritization of the respective pollutant loads at highway runoff sites. Storm runoff data of total suspended solids (TSS), total dissolved solid (TDS), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN) and total phosphorus (TP) collected from three highway sites in Charlotte, North Carolina, USA, were used to illustrate the development of site-specific highway-runoff pollutant loading models. This unified methodology provides a basis for initial assessment of the pollutant-constituent loads from highway runoff using hydrologic component variables. Improved reliability is achievable when additional traffic and/or atmospheric component variables are incorporated into the basic hydrologic regression model. In addition, operational guidance is suggested for implementing highway-runoff monitoring programs that are subject to sampling and resources constraints.     

Application of spatial and non-spatial data analysis in determination of the factors that impact municipal solid waste generation rates in Turkey

In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation data is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global scale, the MSW generation rates in Turkey are significantly related to unemployment rate and asphalt-paved roads ratio. Yet, significances of these variables may diminish at local scale for some provinces. At local scale, different factors may be important in affecting MSW generation rates.     

江苏中部农业园小麦和土壤镉元素含量关系研究

为研究江苏中部农业园土壤和小麦镉元素含量［ω(Cd_soil)和ω（Cd_wheat）］关系,采集了土壤和小麦样品40组,采用多元线性回归分析方法建立ω(Cd_wheat)的预测模型。结果表明：（1）研究区表层土壤呈中性偏弱酸性,ω(Cd_soil)含量范围为0.083~0.239 mg/kg,平均值为0.152 mg/kg,均低于《土壤环境质量 农用地土壤污染风险管控标准（试行）》（GB 15618—2018）中农用地土壤污染风险筛选值,属于优先保护类土壤;（2）依据《食品安全国家标准 食品中污染物限量》（GB 2762—2017）中ω(Cd_wheat)限定值(0.1 mg/kg),小麦籽实Cd超标率为10%;（3）ω(Cd_wheat)主要受表层ω(Cd_soil)控制,同时受到土壤钼（Mo）、铅（Pb）、砷（As）、钙（Ca）和镉（Cd）等元素有效态影响,另外,还受土壤理化性质（pH值和有机质）的影响。     

多维视角下新型城市化对中国二氧化碳排放影响的时空变化特征

城市化和碳排放之间关系密切,现有研究多从单一维度来衡量城市化,而忽略了城市化的多维性.本文从人口、经济、社会、空间和生态5个维度建立了新型城市化的评价体系,利用中国30个省、自治区和直辖市2004—2016年的面板数据,基于熵值法和地理加权回归（GWR）模型,从多维视角下研究了新型城市化对中国二氧化碳排放影响的时空变化特征,结果表明：①北京的新型城市化水平最高,东部沿海地区的新型城市化水平高于西部、西南和东北地区.②新型城市化对碳排放有显著促进作用.人口城市化、社会城市化和生态城市化对碳排放的影响存在明显的区域差异,在不同地区分别表现出促进作用和抑制作用,经济城市化和空间城市化对碳排放有显著促进作用.③人口城市化对碳排放影响的空间集聚性呈现出从西南、南部及东部地区往北部、东北部转移的特征.经济城市化对碳排放影响的空间集聚性呈现出从南部往东部沿海及东北地区逆时针转移的特征.社会城市化对碳排放影响的空间集聚性呈现出从南部、西南地区往西部及东北部顺时针转移的特征.空间城市化对碳排放影响的空间集聚性呈现出从北部、东北部地区往西部、西南地区逆时针转移的特征.生态城市化对碳排放影响的空间集聚性呈现出从东部往中西部转移的特征.     

中国产区苹果越冬冻害的风险评估

越冬期冻害是影响苹果种植分布和质量形成的主要气象灾害之一。论文利用1961-2014年2 084个气象站点资料和冻害调查数据,基于二分类Logistic回归分别建立了越冬期初冬冻害和极端低温冻害发生的概率预测模型,并按照风险极低、低、中度、高、极高等5个等级进行了空间划分。结果表明：建立的初冬冻害和极端低温冻害风险概率预测模型均通过了Hosmer-Losmer检验,独立样本的预测准确率分别达到了83.6%和91.4%。中国产区苹果的越冬冻害主要以初冬冻害为主,覆盖了除黄河故道和云南产区外的大部分果区,而极端低温冻害主要分布在纬度或海拔较高的环渤海湾北部产区、黄土高原西北部和北疆。两种冻害的高风险区域面积基本相当,中度以上风险面积较大的省份依次为甘肃、辽宁、河北和山西,但苹果种植面积最大的陕西和山东遭遇两种冻害特别是极端低温冻害的风险概率总体较低。     

社区水平森林景观格局的动态变化与未来情景模拟

论文以重庆市石柱县三星乡石星村为样区,基于2004年森林景观格局的相关数据,运用Logistic逐步回归方法筛选出了不同时期对石星村森林景观格局具有决定作用的影响因子,并采用CLUE-S模型对石星村2014年森林景观分布格局进行了模拟与验证。此基础上,分别基于历史发展趋势、“农二代”返乡潮以及工商资本介入3种情景模拟石星村2024年的森林景观格局,利用景观格局指数对2004-2024年间3种情景下的景观格局动态及破碎度进行研究。结果表明：1） 利用石星村2004年的森林景观格局分布图对2014年森林景观格局进行模拟,总体精度达到了85%,Kappa指数均值达到0.816,这表明CLUE-S模型对石星村森林景观的格局变化具有良好的模拟能力;2） 在预设的3种情景下,样区森林景观一直占据20 a间景观基质的主导地位,林区分析结果显示出林地总面积没有明显减少,且相较于2004年的林地总面积表现出增加的趋势。3种情景下退化林地面积均呈减少的趋势,其中,相较于历史发展趋势,“农二代”返乡潮情景下退化林地的减少均伴随着人工林和农用地面积的增加,而工商资本介入情景下退化林地的减少伴随着人工林面积的增加和农用地面积的减少;3） 在林地的空间分布上,各林地类型的分布存在一定的规律性,其中退化原始林主要集中分布在中东部低山、深丘区,次生林、退化林地和人工林呈镶嵌格局,分散于主要基质性景观中;4） 样区在3种情景模拟下,森林景观破碎化程度存在差异。总体来说,“农二代”返乡潮和工商资本介入两种情景下森林景观恢复较好。研究结论可为石星村未来森林景观管理、规划及政策的制定等提供参考依据和决策支持。