模拟酸雨对木兰科树种叶片膜脂过氧化和抗氧化系统的影响

酸雨对森林、水体和农田等生态系统造成的危害受到许多研究者的重视,并已取得一些成果,但关于木本园林植物的伤害机理及抗性机制没有得到澄清,尤其是对抗氧化系统的影响研究较少。采用盆栽法,以木兰科(Magnoliaceae)树种抗酸性强的阔瓣含笑(Michelia platypetala)和抗酸性弱的红花木莲(Manglieta insignis)为试材,研究了不同pH值模拟酸雨处理对叶片膜脂过氧化和抗氧化系统的影响。结果表明,随着酸雨pH值的下降,两树种叶片抗氧化剂抗坏血酸(ASA)和谷胱甘肽(GSH)质量分数下降;抗氧化酶超氧化物歧化酶(SOD)及谷胱甘肽还原酶(GR)活性下降,而过氧化物酶(POD)活性变化趋势不一致,阔瓣含笑一直呈上升趋势,红花木莲则先上升后下降。此外,超氧阴离子(O2?·)产生速率上升,丙二醛(MDA)含量和膜透性增加;相关性分析表明,O2?·产生速率与MDA和膜透性呈显著正相关,与抗氧化酶SOD,GR和抗氧化剂ASA质量分数呈显著负相关,说明酸雨降低了植物体防御活性氧伤害有关的酶系统和非酶系统抗性能力,提高了体内活性氧含量,膜脂过氧化加剧。与红花木莲相比,阔瓣含笑具有较强的抗氧化能力。本研究结果从自由基的产生及清除的角度,探讨木本园林植物的伤害机理以及抗性机制,也为该类园林树种在江南城市中的选择提供一些科学参考依据。     

五种亚热带树苗的生长与干物质分配格局对大气污染胁迫的响应

将乡土木本植物猫尾木Dolichandronecauda-felina、蒲桃Syzygiumjambos、野牡丹Melastomacandidum、翻白叶树Pterospermumheterophyllum以及鸭脚木Scheffleraoctophylla1年生袋装苗盆栽,置半庇荫环境下适应4周,之后按株数均等分成两组,分别放置在南海五星污染区和广州华南植物园清洁区进行试验。5个月后进行植物构形生长参数和干物质量的测定,以探讨这5种亚热带树苗对大气污染响应的差异。结果表明,①这5种树苗均能在清洁区和污染区都存活,但生长特征表现明显差别。②除翻白叶树基径有少许增大外,大气污染基本上都使植物基径生长减小;树高方面,除了蒲桃外,其余树种树高都有所降低,鸭脚木树高受到的影响最为严重。③翻白叶树与猫尾木单株侧枝数有少许增加,而蒲桃和鸭脚木单株侧枝数有大幅度地下降,分别减少为清洁区单株侧枝数的46.5%和65.1%,野牡丹单株侧枝数基本上没有受到影响。④在污染区生长的5个树种单株干物质总量除了翻白叶树有所增加外,其余4个树种单株干物质量均有不同程度地下降。⑤除了蒲桃保持不变外,污染区?生长4种植物冠根比(CRR)均有不同程度地增加。在污染区生长的植株叶质量比(LWR)和叶面积比(LAR)与清洁区相比存在差异,野牡丹和蒲桃叶质量比和叶面积比下降,而其余3种植物叶质量比和叶面积比上升。综合实验结果表明,5种植物幼苗中对大气污染抗性最强的是翻白叶树和蒲桃,抗性最弱的是鸭脚木。     

上海市公园绿地常见落叶树木叶片汞浓度时空特征及环境意义

植物叶片汞浓度与大气气态单质汞(GEM/Hg0)浓度的线性关系表明叶片汞浓度大小可用于指示植物生长区内GEM浓度的高低水平.通过分析上海市绿地公园(25座)中常见落叶树木樱花、水杉、法桐叶片汞浓度的时空变化特征,探究区域内GEM含量水平及分布特征.2017年5-10月对7座公园中这3种树木叶汞浓度进行连续监测,结果显示...     

除草剂阿特拉津的环境毒理研究进展

叙述了阿特拉津的应用概况及其在生产实践中所存在问题;阿特拉津在生物体内和环境中的降解代谢过程。综述了近年来国内外在阿特拉津的残留分析方法、环境毒理学和微生物降解等方面的研究进展。     

An evaluation of environmental factors affecting species distributions

Many different models can be built to explain the distributions of species. Often there is no single model that is clearly better than the alternatives, and this leads to uncertainty over which environmental factors are limiting species’ distributions. We investigated the support for different environmental factors by determining the drop in model performance when selected predictors were excluded from the model building process. We used a paired t-test over 37 plant species so that an environmental factor was only deemed significant if it consistently improved the results for multiple species. Geology and winter minimum temperatures were found to be the environmental factors with the most support, with a significant drop in model performance when either of these factors was excluded. However, there was less support for summer maximum temperature, as other environmental factors could combine to produce similar model performance. Our method of evaluating environmental factors using multiple species will not be capable of detecting predictors that are only important for one or two species, but it is difficult to distinguish these from spurious correlations. The strength of the method is that it increases inference for factors that consistently affect the distributions of many species. We discourage the assessment of models against predefined benchmarks, such as an area under the curve (AUC) of more than 0.7, as many alternative models for the same species produce similar results. Therefore, the benchmarks do not provide any indication of how the performance of the selected model compares to alternative models, and they provide weak inference to accept any selected model.     

Model based grouping of species across environmental gradients

We present a novel approach to the statistical analysis and prediction of multispecies data. The approach allows the simultaneous grouping and quantification of multiple species’ responses to environmental gradients. The underlying statistical model is a finite mixture model, where mixing is performed over the individual species’ responses to environmental gradients. Species with similar responses are grouped with minimal information loss. We term these groups species archetypes. Each species archetype has an associated GLM that can be used to predict distributions with appropriate measures of uncertainty. Initially, we illustrate the concept and method using artificial data and then with application to real data comprising 200 species from the Great Barrier Reef (GBR) lagoon on 13 oceanographic and geological gradients from 12°S to 24°S. The 200 species from the GBR are well represented by 15 species archetypes. The model is interpreted through maps of the probability of presence for a fine scale set of locations throughout the study area. Maps of uncertainty are also produced to provide statistical context. The presence of each species archetype was strongly influenced by oceanographic gradients, principally temperature, oxygen and salinity. The number of species in each group ranged from 4 to 34. The method has potential application to the analysis of multispecies distribution patterns and for multispecies management.     

手性农药对映体选择性环境行为的研究进展

目前使用的农药中有25%是手性的,手性农药的生物活性存在对映体差异性,其活性往往只存在于一个或少数几个对映体中,而手性农药的对映体在环境中的消解和归趋往往也有明显的不同,即一个手性化合物的不同对映体具有不同的毒性.只有在对映体水平上研究手性农药的环境行为,考察手性农药的归趋和生态效应,才能更准确的评估其生态风险性以及对人类健康的影响,对手性农药的合理使用也有较好的指导作用.文章综述了近年来国际上有机氯、芳氧基羧酸和酰胺、有机磷和菊酯等手性农药对映体选择性环境行为的研究进展.提出今后的研究方向是拓展手性农药的研究种类、研究深度和广度,对映体选择性的毒理学研究,手性稳定性和手性转化,选择性的机制与相关微生物和酶学研究等.     

Toxicity of environmental nanosilver: mechanism and assessment

Environmental Chemistry Letters - Nanosilver (nAg) is increasingly being used in a wide array of fields, and its toxicity has been extensively studied. Here we present a review of environmental nAg...     

Potential effects of climate change on ecosystem and tree species distribution in British Columbia

A new ecosystem-based climate envelope modeling approach was applied to assess potential climate change impacts on forest communities and tree species. Four orthogonal canonical discriminant functions were used to describe the realized climate space for British Columbia's ecosystems and to model portions of the realized niche space for tree species under current and predicted future climates. This conceptually simple model is capable of predicting species ranges at high spatial resolutions far beyond the study area, including outlying populations and southern range limits for many species. We analyzed how the realized climate space of current ecosystems changes in extent, elevation, and spatial distribution under climate change scenarios and evaluated the implications for potential tree species habitat. Tree species with their northern range limit in British Columbia gain potential habitat at a pace of at least 100 km per decade, common hardwoods appear to be generally unaffected by climate change, and some of the most important conifer species in British Columbia are expected to lose a large portion of their suitable habitat. The extent of spatial redistribution of realized climate space for ecosystems is considerable, with currently important sub-boreal and montane climate regions rapidly disappearing. Local predictions of changes to tree species frequencies were generated as a basis for systematic surveys of biological response to climate change.     

Incorporating detectability of threatened species into environmental impact assessment

Environmental impact assessment (EIA) is a key mechanism for protecting threatened plant and animal species. Many species are not perfectly detectable and, even when present, may remain undetected during EIA surveys, increasing the risk of site‐level loss or extinction of species. Numerous methods now exist for estimating detectability of plants and animals. Despite this, regulations concerning survey protocol and effort during EIAs fail to adequately address issues of detectability. Probability of detection is intrinsically linked to survey effort; thus, minimum survey effort requirements are a useful way to address the risks of false absences. We utilized 2 methods for determining appropriate survey effort requirements during EIA surveys. One method determined the survey effort required to achieve a probability of detection of 0.95 when the species is present. The second method estimated the survey effort required to either detect the species or reduce the probability of presence to 0.05. We applied these methods to Pimelea spinscens subsp. spinescens, a critically endangered grassland plant species in Melbourne, Australia. We detected P. spinescens in only half of the surveys undertaken at sites where it was known to exist. Estimates of the survey effort required to detect the species or demonstrate its absence with any confidence were much higher than the effort traditionally invested in EIA surveys for this species. We argue that minimum survey requirements be established for all species listed under threatened species legislation and hope that our findings will provide an impetus for collecting, compiling, and synthesizing quantitative detectability estimates for a broad range of plant and animal species. Incorporación de la Capacidad de Detectar una Especie Amenazada a la Evaluación de Impacto Ambiental