Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

Assessment of deep aquifer groundwater quality in a geographically unique climatic region of Southern Western Ghats,India using water quality indices

Water quality index (WQI) models are generally used in hydrochemical studies to simplify complex data into single values to reflect the overall quality. In this study, deep groundwater quality in the Chittur and Palakkad Taluks of the Bharathapuzha river basin of Kerala, India, was assessed by employing the WQI method developed by the Canadian Council of Ministers of the Environment (CCME). The assessment of overall water quality is indispensable due to the specific characteristics of the study area, such as geography, climate, over-drafting, and prevalent agricultural practices. Forty representative samples were collected from the study area for monsoon (MON) and pre-monsoon (PRM) seasons. The results showed a general increase of contents from MON to PRM. The major cations were spread in the order Ca²⁺>Na+>Mg²⁺>K⁺ and the anions HCO₃⁻>Cl⁻>CO₃²⁻ based on their relative abundance. Among various parameters analysed, alkalinity and bicarbonate levels during MON were comparatively high, which is indicative of carbonate weathering, and 90% of the samples failed to meet the World Health Organization (WHO, 2017)/Bureau of Indian Standards (BIS, 2012) drinking water guidelines. The CCME WQI analysis revealed that nearly 50% of the samples during each season represented good and excellent categories. The samples in the poor category comprised 10% in MON and 15% in PRM. The overall WQI exhibited 15% of poor category samples as well. The spatial depiction of CCME WQI classes helped to expose zones of degraded quality in the centre to eastward parts. The spatial and temporal variations of CCME WQI classes and different physicochemical attributes indicated the influence of common factors attributing to the deep groundwater quality. The study also revealed inland salinity at Kolluparamba and Peruvamba stations, where agricultural activities were rampant with poor surface water irrigation.     

西北地区水窖水质的污染原因及防治措施

文章结合我国西北地区雨水集蓄利用工程水质的基本情况,对典型地区水窖水质的检测数据、结果和污染成因作了分析,并提出了水窖防治水质污染的措施。     

沙口水厂水源保护管理体系的建立

介绍了我国、广东省、其他市出台的有关水源保护管理的一些政策,阐述了佛山市禅城区在沙口水厂水源保护工作体制、技术、资金等方面的一些创新做法。     

珠江流域水污染现状与主要问题成因分析

对珠江流域在云南省境内的主要河流的水环境现状进行了分析,对主要污染物排放量、入河量进行了测算,对污染物的来源构成、空间分布及其特征进行了分析,在此基础上对主要环境问题进行系统地识别,分析造成水体污染的原因。     

大王滩水库秋季浮游植物分布初探

2011年秋季对大王滩水库开展了藻类采样监测,分别从藻类定性和定量分析入手,分析了种类组成与数量的分布特征,并进行了富营养化评价。监测表明秋季大王滩水库主要是蓝藻门的细鞘丝藻占优势。垂直分布上,表层浮游植物密度大大高于底层密度,从藻类生物量看和从优势种看,大王滩水库秋季可判定为富营养状态。     

水葫芦大面积种植对滇池浮游植物的影响研究

对滇池水葫芦大面积种植区域开展了浮游植物群落结构和细胞丰度变化的调查研究,经过数据统计分析发现水葫芦大面积种植对水体浮游植物种群种类组成影响不显著,但对蓝藻生长具一定的抑制作用,对绿藻和硅藻可能具一定促进作用。     

高锰酸盐指数测定中影响因素的探讨

通过对酸性法测定高锰酸盐指数全过程的分析,结果表明水样静置时间、水样浓度、水浴时间、反应温度等因素影响测定结果。文章总结了测定过程中需要注意的几个关键环节,确保获得准确数据。     

大凌河朝阳段大型底栖无脊椎动物监测及BI指数评价

通过对大凌河朝阳段5个采样点9个样本的底栖动物监测分析,检出底栖动物59种,采用BI指数进行水质评价。调查结果表明,大凌河南大桥及上游河段为清洁,市区段下游为轻污染至中污染。     

基于熵权的改进密切值法在水质综合评价的应用

将2003至2008年宁德市金涵水库水质监测值与地表水环境质量标准相结合,建立了环境样本矩阵,运用信息熵原理确定各指标的权重,并应用改进密切值法进行水质综合评价。结果表明：金涵水库从2003至2008年水质都是Ⅱ类以上,水质总体良好。该评价方法操作简便易行,结论切实可行,并可反映出各评价单元的优劣变化。