Effects of surrounding land use and water depth on seagrass dynamics relative to a catastrophic algal bloom

Seagrasses are the foundation of many coastal ecosystems and are in global decline because of anthropogenic impacts. For the Indian River Lagoon (Florida, U.S.A.), we developed competing multistate statistical models to quantify how environmental factors (surrounding land use, water depth, and time [year]) influenced the variability of seagrass state dynamics from 2003 to 2014 while accounting for time‐specific detection probabilities that quantified our ability to determine seagrass state at particular locations and times. We classified seagrass states (presence or absence) at 764 points with geographic information system maps for years when seagrass maps were available and with aerial photographs when seagrass maps were not available. We used 4 categories (all conservation, mostly conservation, mostly urban, urban) to describe surrounding land use within sections of lagoonal waters, usually demarcated by land features that constricted these waters. The best models predicted that surrounding land use, depth, and year would affect transition and detection probabilities. Sections of the lagoon bordered by urban areas had the least stable seagrass beds and lowest detection probabilities, especially after a catastrophic seagrass die‐off linked to an algal bloom. Sections of the lagoon bordered by conservation lands had the most stable seagrass beds, which supports watershed conservation efforts. Our results show that a multistate approach can empirically estimate state‐transition probabilities as functions of environmental factors while accounting for state‐dependent differences in seagrass detection probabilities as part of the overall statistical inference procedure.     

Predicting Extinction Risk of Brazilian Atlantic Forest Angiosperms

Understanding how plant life history affects species vulnerability to anthropogenic disturbances and environmental change is a major ecological challenge. We examined how vegetation type, growth form, and geographic range size relate to extinction risk throughout the Brazilian Atlantic Forest domain. We used a database containing species‐level information of 6,929 angiosperms within 112 families and a molecular‐based working phylogeny. We used decision trees, standard regression, and phylogenetic regression to explore the relationships between species attributes and extinction risk. We found a significant phylogenetic signal in extinction risk. Vegetation type, growth form, and geographic range size were related to species extinction risk, but the effect of growth form was not evident after phylogeny was controlled for. Species restricted to either rocky outcrops or scrub vegetation on sandy coastal plains exhibited the highest extinction risk among vegetation types, a finding that supports the hypothesis that species adapted to resource‐limited environments are more vulnerable to extinction. Among growth forms, epiphytes were associated with the highest extinction risk in non‐phylogenetic regression models, followed by trees, whereas shrubs and climbers were associated with lower extinction risk. However, the higher extinction risk of epiphytes was not significant after correcting for phylogenetic relatedness. Our findings provide new indicators of extinction risk and insights into the mechanisms governing plant vulnerability to extinction in a highly diverse flora where human disturbances are both frequent and widespread. Predicción del Riesgo de Extinción de Angiospermas del Bosque Atlántico Brasileño     

Expanding Kenya's protected areas under the Convention on Biological Diversity to maximize coverage of plant diversity

Biodiversity is highly valuable and critically threatened by anthropogenic degradation of the natural environment. In response, governments have pledged enhanced protected‐area coverage, which requires scarce biological data to identify conservation priorities. To assist this effort, we mapped conservation priorities in Kenya based on maximizing alpha (species richness) and beta diversity (species turnover) of plant communities while minimizing economic costs. We used plant‐cover percentages from vegetation surveys of over 2000 plots to build separate models for each type of diversity. Opportunity and management costs were based on literature data and interviews with conservation organizations. Species richness was predicted to be highest in a belt from Lake Turkana through Mount Kenya and in a belt parallel to the coast, and species turnover was predicted to be highest in western Kenya and along the coast. Our results suggest the expanding reserve network should focus on the coast and northeastern provinces of Kenya, where new biological surveys would also fill biological data gaps. Meeting the Convention on Biological Diversity target of 17% terrestrial coverage by 2020 would increase representation of Kenya's plant communities by 75%. However, this would require about 50 times more funds than Kenya has received thus far from the Global Environment Facility.     

生物炭和草酸活化磷矿粉对镉镍复合污染土壤的应用效果

采用室内培养实验,利用生物炭和草酸活化磷矿粉对镉镍复合污染土壤进行修复,比较两者不同配比对土壤重金属镉镍的修复效果及对土壤无机氮和微生物量氮(MBN)转化的影响.结果表明,随着草酸活化磷矿粉和生物炭施用量的增加,土壤p H逐渐增加,镉和镍均由弱酸提取态逐渐向可还原态、可氧化态和残渣态转化,生物有效性降低.其中,C50P3(50 g·kg~(-1)生物炭与3 g·kg~(-1)草酸活化磷矿粉)配施的修复效果最好,弱酸提取态Ni占全量的质量分数降低了37.0%,残渣态Ni增加了14.8%,弱酸提取态Cd含量占全量的质量分数降低了40.2%,残渣态增加了35.2%.施用修复剂40 d后,相较于C0P0(空白对照)处理,C50P0(单施50 g·kg~(-1)生物炭)处理与C0P3(单施3 g·kg~(-1)草酸活化磷矿粉)处理微生物量氮含量均分别增加了1.5倍和1倍;铵态氮含量分别减少了12.5%和6.4%,硝态氮含量分别降低了11.6%和10.2%.综合比较可知,生物炭和草酸活化磷矿粉配施对土壤重金属镉镍复合污染的修复效果要优于单施,且50 g·kg~(-1)生物炭与3 g·kg~(-1)草酸活化磷矿粉(C50P3)配施的修复效果最好,修复剂的加入促进了土壤无机氮向有机氮的转化.     

顶空气相色谱法测定水和废水中的邻二氯苯

采用顶空采样,填充柱分离,ECD测定水和废水中的邻二氯苯,在柱温150℃,进样室温200℃,ECD温300％下,邻二氯苯的保留时间为3．78min,该方法灵敏度高,最低检出浓度为0．02μg／L;精密度好,对标准样品六次测定的相对标准偏差小于3．9％;准确度高,加标回收率在95％～104％之间。操作简便、测定快速,克服了萃取法烦琐、有毒、易污染色谱柱等缺点。     

微波消解－ICP－AES法测底泥中的铜、镍等金属元素

采用微波消解－ICP－AES法测定底泥中的铜、镍等金属元素。通过实验和加标回收率的测定,回收率在88～102％之间。     

Zn/Ni/Cu-BTC强化吸附刚果红性能研究

运用水热合成法制备了一种新型三金属单配体多孔材料Zn/Ni/Cu-BTC,运用氮气吸脱附、扫描电镜、X射线衍射等对材料进行了表征.研究了其常温常压条件下（25℃,1atm）静态吸附刚果红的性能.结果表明,由于三金属不饱和配位点的协同效应导致刚果红在Zn/Ni/Cu-BTC多孔材料上的吸附容量从630mg/g增加到1250mg/g,增加了98.4%.准二级动力学模型和Langmuir吸附模型较好地描述了Zn/Ni/Cu-BTC对刚果红的吸附行为.     

Understanding the electrode reaction process of dechlorination of 2,4-dichlorophenol over Ni/Fe nanoparticles: Effect of pH and 2,4-dichlorophenol concentration

Herein,with the exploitation of iron and nickel electrodes,the 2,4-dichlorophenol(2,4-DCP)dechlorinating processes at the anode and cathode,respectively,were separately studied via various electrochemical techniques(e.g.,Tafel polarization,linear polarization,electrochemical impedance spectroscopy).With this in mind,Ni/Fe nanoparticles were prepared by chemical solution deposition,and utilized to test the dechlorination activities of 2,4-DCP over a bimetallic system.For the iron anode,the results showed that higher 2,4-DCP concentration and solution acidity aggravated the corrosion within the electrode.The charge transfer resistance(R_(ct))values of the iron electrode were 703,473,444,and 437Ω·cm~2 for the initial 2,4-DCP concentrations of0,20,50,and 80 mg/L,respectively.When the bulk pH of the 2,4-DCP solution varied from 3.0,5.0to 7.0,the corresponding R_(ct) values were 315,376,and 444Ω·cm~2,respectively.For the nickel cathode,the reduction current densities on the electrode at-0.75 V(vs.saturated calomel electrode)were 80,106,and 111μA/cm~2,for initial 2,4-DCP concentrations of 40,80,and125 mg/L.The dechlorination experiments demonstrated that when the initial pH of the solution was 7.0,5.0,and 3.0,the dechlorination percentage of 2,4-DCP by Ni/Fe nanoparticles was 62%,69%,and 74%,respectively,which was in line with the electrochemical experiments.10 wt.%Ni loading into Ni/Fe bimetal was affordable and gave a good dechlorination efficiency of 2,4-DCP,and fortunately the Ni/Fe nanoparticles remained comparatively stable in the dechlorination processes at pH 3.0.     

ICP-AES法测定煤矸石中的Ni、Fe、Mn、Cr

取1.000g矸石样品于聚四氟乙烯坩埚中,加入5mLH2O2放置过夜,加6mL浓HCl,4mL浓HNO3,在微波炉中消解至近干,再加2mLHF,继续消解至粘稠状,用温热稀HCl溶解残渣,转入50mL容量瓶中,加1%HNO3定容,用ICP-AES法测定煤矸中Ni、Fe、Mn、Cr。在选定的测定条件下,检出限分别为0.013mg/L、0.0044mg/L、0.0014mg/L和0.0069mg/L;精密度的相对标准偏差分别为2.9%、3.4%、3.1%、2.1%;准确度实验铬的回收率在97.5%～106.0%之间。     

废物水泥窑共处置产品中Ni释放的pH影响

通过模拟煅烧实验制取水泥熟料,并制取混凝土样品。参照NEN7375浸出方法,设定5种不同pH值的浸取液,研究了pH值对混凝土块中重金属Ni释放的影响.结果表明,浸取液的pH=2.00、3.50、5.00、7.35和10.0时,混凝土中Ni的累积释放量分别为1.64、0.167、0.038、0.019和0.025mg/kg;酸性范围内,累积释放量随着pH值的增大而减小,并在弱碱性条件下达到最小值,碱性范围内,随pH值的增大而呈增加的趋势。pH值对Ni的释放过程有影响,pH=3.50和7.35的浸取液中,混凝土中Ni的释放机理为扩散控制,释放曲线与斜率为0.5的直线拟合较佳,且不同区间浸出量曲线的斜率均在0.35～0.65范围内;pH=2.00和5.00的溶液中,Ni的释放在前、中期为扩散控制,后期发生了耗竭作用;pH为10.0条件下,Ni的释放在前期发生了延滞现象,中期为扩散控制,而后期发生了耗竭。