five

Toxicity of metal mixtures to two Antarctic marine microalgae

收藏
Research Data Australia2024-12-14 收录
下载链接:
https://researchdata.edu.au/toxicity-metal-mixtures-marine-microalgae/1329918
下载链接
链接失效反馈
官方服务:
资源简介:
This metadata record contains observed and predicted toxicity data from bioassays with two species of Antarctic marine microalgae: Phaeocystis antarctica (Prymnesiophyceae) and Cryothecomonas armigera (Cercoza). Bioassay exposures were of mixtures of 5 metals at two ratios, an Environmental (ENV) and Equitoxic (EC) mixture. The measured dissolved metal concentrations were used in two mixture reference models, Independent Action (IA) and Concentration Addition (CA), to predict toxicity as population growth rate inhibition. A Flow Cytometer (BD-FACSVerse) was used to measure the density of microalgae over time, which was then converted to a growth rate. An inductively coupled plasma-atomic emission spectrometry (ICP-AES; Varian 730-ES), was used to measure metal concentrations.Data for each microalga is provided in individual excel spreadsheets, identified by the species tested. A word document is provided that contains the R code used to predict toxicity to the two microalgae by the reference models Independent Action and Concentration Addition. The R code also includes the steps required to extend the models to include a deviation parameter “a” that allows for departure from model additivity. A nested F-test then tests for significance between the fit of each test to observed toxicities. This R code has been adapted to use EC10 as parameter estimates, rather than EC50s. The code was adapted from the approach outlined in Hochmuth, J. D.; Asselman, J.; De, S. Are Interactive Effects of Harmful Algal Blooms and Copper Pollution a Concern for Water Quality Management? Water Res. 2014, 60, 41–53. DOI: 10.1016/j.watres.2014.03.041.Single-metal toxicity data and experimental protocols for P. antarctica from the following paper: and C. armigera used in this study can be found in the following papers: A robust bioassay to assess the toxicity of metals to the Antarctic marine microalga Phaeocyctis antarctica. Francesca Gissi, Merrin S. Adams, Catherine K. King, Dianne F. Jolley (2015). Environmental Toxicology and Chemistry. 2015 Feb 20. doi: 10.1002/etc.2949.Chronic toxicity of five metals to the polar marine microalga Cryothecomonas armigera – Application of a new bioassay. Darren J. Koppel, Francesca Gissi, Merrin S. Adams, Catherine K. King, and Dianne F. Jolley, (2017). Environmental Pollution, Volume 228, 2017, Pages 211-221, doi.org/10.1016/j.envpol.2017.05.034.

本元数据记录包含两种南极海洋微藻生物测定实验(bioassay)的观测毒性数据与预测毒性数据:南极棕囊藻(*Phaeocystis antarctica*,定鞭藻纲Prymnesiophyceae)与带刺隐单胞虫(*Cryothecomonas armigera*,丝足虫门Cercoza)。生物暴露实验采用两种配比的5种金属混合物:环境配比(ENV)混合物与等效毒理配比(EC)混合物。实测溶解金属浓度被用于两种混合毒理参考模型——独立作用模型(Independent Action, IA)与浓度加和模型(Concentration Addition, CA),以种群生长速率抑制率作为毒性预测指标。采用流式细胞仪(Flow Cytometer,BD-FACSVerse型号)实时测定微藻密度,随后将密度数据转换为生长速率。采用电感耦合等离子体原子发射光谱仪(inductively coupled plasma-atomic emission spectrometry, ICP-AES,Varian 730-ES型号)测定金属溶液浓度。每种微藻的实验数据均存储于独立的Excel电子表格中,以受试物种名称进行标识。附带一份Word文档,内含用于通过上述两种参考模型预测两种微藻毒性的R代码;该代码还包含了拓展模型的相关步骤,可引入偏离参数"a"以修正模型加和性偏差。随后通过嵌套F检验(nested F-test),对各模型拟合观测毒性数据的显著性差异进行验证。本R代码已适配为以10%有效浓度(EC10)作为参数估计值,而非半数有效浓度(EC50)。该代码改编自Hochmuth等人2014年发表于《水研究》(Water Research)的研究:Hochmuth, J. D.; Asselman, J.; De, S. Are Interactive Effects of Harmful Algal Blooms and Copper Pollution a Concern for Water Quality Management? Water Res. 2014, 60, 41–53. DOI: 10.1016/j.watres.2014.03.041.本研究中使用的南极棕囊藻单金属毒性数据与实验方案来自以下文献:《一种用于评估金属对南极海洋微藻南极棕囊藻毒性的可靠生物测定方法》(Francesca Gissi、Merrin S. Adams、Catherine K. King、Dianne F. Jolley,2015年,《环境毒理学与化学》(Environmental Toxicology and Chemistry),2015年2月20日在线发表,DOI: 10.1002/etc.2949)。本研究使用的带刺隐单胞虫相关数据则来自以下文献:《五种金属对极地海洋微藻带刺隐单胞虫的慢性毒性——一种新型生物测定方法的应用》(Darren J. Koppel、Francesca Gissi、Merrin S. Adams、Catherine K. King、Dianne F. Jolley,2017年,《环境污染》(Environmental Pollution),第228卷,2017年,第211-221页,DOI: 10.1016/j.envpol.2017.05.034)。
提供机构:
Australian Antarctic Division
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作