Summary

多氯联苯同系物净营养转移效率湖鳟鱼实验室估计(<em>红点鲑namaycush</em>),从它的猎物

Published: August 29, 2014
doi:

Summary

一种技术实验室评估中的多氯联苯(PCB)同系物的净营养转换效率从他们的猎物肉食性鱼类呈现。最大化的实验室结果的适用性领域,食鱼鱼应喂是通常食用的字段猎物鱼。

Abstract

一种技术实验室评估中的多氯联苯(PCB)同系物的净营养转换效率(γ),从它们的猎物肉食性鱼类在此说明。在135天的实验室实验中,我们给bloater( 白鲑hoyi)已被夹在密歇根湖到湖鳟鱼( 红点鲑namaycush)保持在八个实验室坦克。 Bloater是一种天然猎物的湖鳟。在四个罐的,相对高的流率被用来确保由湖鳟相对高的活性,而较低的流速在其它四个罐使用时,可以实现很低的湖鳟活性。上的槽由槽的基础上,被记录了食物对试验的每一天吃掉湖鳟鱼的数量。每个湖鳟鱼是在实验的开始和结束称重。处死四至九湖鳟从每八个坦克在实验开始时,所有的10湖鳟残留在每一个池中分别euthan美化版在实验结束。我们确定的75​​多氯联苯同系物在湖鳟浓度在实验开始时,在湖鳟鱼在试验结束,并在bloaters在实验过程中提供给湖红点鲑。基于这些测量,γ计算每75 PCB同系物中的每个8罐。意思是γ计算每个75 PCB同系物的激活和未激活湖鳟鱼。因为该试验重复在8缸,对标准误差平均值γ可估计。结果这种类型的实验都是在风险评估模型有助于预测未来的风险,人类和野生动物在环境污染的各种情景食用受污染的鱼类。

Introduction

Of all of the factors affecting the rate at which fish accumulate contaminants, the efficiency with which fish retain contaminants from the food that they eat is one of the most important1-3. Risk assessment models have been developed to predict future risks to both people and wildlife eating contaminated fish under various scenarios of environmental contamination, and the reliability of these predictions critically depends on the accuracy of the estimates of the efficiency at which fish retain contaminants from their food4.

The efficiency with which the contaminant in the food ingested by the predator is transported through the gut wall is known as gross trophic transfer efficiency5. A portion of the quantity of the contaminant transported through the gut wall of the predator may eventually be lost through depuration and/or metabolic transformation. The efficiency with which the contaminant in the food ingested by the predator is retained by the predator, including any losses due to elimination and metabolic transformation, is known as net trophic transfer efficiency6.

Gross trophic transfer efficiency of organic contaminants to fish from their prey appears to vary with the contaminant’s chemical properties, including lipid affiliation as measured by the octanol-water partition coefficient, Kow3,7. According to an empirical relationship developed by Thomann3, gross trophic transfer efficiency is relatively high when log Kow is equal to a value between 5 and 6. Gross trophic transfer efficiency declines exponentially at a rate of 50% per unit of log Kow as log Kow increases from 6 to 10, according to the Thomann3 relationship.

Nevertheless, the gross and net trophic transfer efficiencies of polychlorinated biphenyl (PCB) congeners to fish from their prey do not appear to follow the Thomann3 relationship in most cases. Although the trophic transfer efficiencies of PCB congeners to lake whitefish (Coregonus clupeaformis) from its food followed the relationship proposed by Thomann8, trophic transfer efficiencies of PCB congeners were either just weakly related or not related at all to log Kow for Atlantic salmon (Salmo salar)9, rainbow trout (Oncorhynchus mykiss)10, coho salmon (Oncorhynchus kisutch)11, and northern pike (Esox lucius)11.

The overall goal of this study was to present a laboratory technique for estimating the net trophic transfer efficiencies of PCB congeners to a piscivorous fish from its prey. Lake trout (Salvelinus namaycush) was chosen as the piscivorous fish for our experiment because lake trout are relatively easy to maintain in laboratory tanks. Bloater (Coregonus hoyi) was selected as the prey fish to be fed to the lake trout because bloater is eaten by lake trout in its natural setting12. In addition, we determined whether the net trophic transfer efficiencies for lake trout estimated from our laboratory experiment followed the Thomann3 relationship. We also determined whether the degree of activity by the lake trout had a significant effect on net trophic transfer efficiency (γ) of the PCB congeners. Activity by lake trout in the Laurentian Great Lakes is believed to have recently increased because changes in the food webs have caused lake trout to allocate more energy toward searching for food13. Lake trout were forced to exercise in one set of tanks by subjecting these lake trout to relatively high flow rates, whereas the other lake trout were permitted to remain relatively inactive by subjecting them to relatively low flow rates. Finally, the specific details of our laboratory procedure that need to be carefully followed to ensure the highest degree of accuracy in the γ estimates and to make the laboratory results applicable to the field are discussed, as well as future directions for research building on our laboratory technique. Net trophic transfer efficiency can be estimated both in the laboratory and in the field, and advantages and disadvantages are associated with both approaches. Accuracy in the estimate of γ depends on the accuracy of the estimate of food consumption. The amount of food eaten by fish in the laboratory can be accurately determined when proper protocols are followed, whereas the amount of food eaten by fish in the field is typically estimated via bioenergetics modeling. Use of bioenergetics modeling to derive the amount of food eaten has the potential to introduce a substantial amount of uncertainty into the estimates of food consumption. Fish bioenergetics models have been shown to estimate food consumption with no detectable bias for the case of lake trout14,15, but considerable bias in bioenergetics model estimates of food consumption has been detected for the case of lake whitefish15,16. On the other hand, estimates of net trophic transfer efficiency estimated in the laboratory may not be applicable to the field due to a difference in feeding rates between the laboratory and the field17. Evidence from both the laboratory and the field suggest that feeding rate can influence γ14,17.

The methodology used in the present study for estimating γ in the laboratory is applicable to situations where the predator fish is fed prey fish, and the amount of prey fish eaten by the predator can be accurately tracked. To accomplish this, the experimenter must weigh all of the food before placement in the tank; and the experimenter must be able to remove all of the uneaten food from the tank, and then weigh the uneaten food. In addition, an adequate suite of mixers and blenders should be available to obtain a sufficient degree of homogenization of the samples of both predator and prey fish. Finally, the gas chromatography – mass spectrometry instrumentation used to determine the PCB congener concentrations must be capable of detecting and quantifying individual PCB congeners at relatively low concentrations.

Protocol

1,实验室实验得到的猎物鱼在实验过程中,以被馈送到捕食鱼。优选这些捕食鱼应该被捕获在该领域,冷冻,并储存于约-30℃。考虑商业捕鱼作业的猎物鱼的潜在来源。 捕食鱼引入到实验室罐被用于实验。高达15捕食鱼已经被引入每一个870-L罐,和多达30个捕食鱼已经被引入到每一个2380-L罐中之前的研究16,18。 适应捕食鱼饮食选择猎物的鱼。一旦适应,捕食鱼应该在?…

Representative Results

湖鳟鱼呈增长的大量实验过程中,作为初始湖鳟意味着重量介于694至907克而最后的湖鳟意味着权重介于853 1566克( 表1)。食品135天的实验过程中消耗的湖鳟的平均金额介于641至2649克。由实验期间平均的PCB同源物的浓度在湖鳟增加,平均的PCB同源物浓度范围为0.01至7.14纳克/克(湿重)在实验开始时的平均PCB同源物的浓度从0.03范围到29.31结论实验( 表2)。整个九月,抓bloat…

Discussion

为γ的最准确的估计,实验者必须能够准确地跟踪食品的两个实验的过程中,放置在每一个容器并在每个罐的食物残渣的量的量。为了实现这一点,实验者必须能够从罐取出所有的食物残渣和准确地确定其重量。除了由捕食鱼实际上吃过的食物的准确的跟踪,γ的精确估计也可能依赖于实验的足够持续时间。鉴于广泛引用的实验室研究专门设计来估计多氯联苯营养转移效率对鱼类从他们的食物从105…

Divulgazioni

The authors have nothing to disclose.

Acknowledgements

This work was funded, in part, by the Great Lakes Fishery Commission and the Annis Water Resources Institute. Use of trade, product, or firm names does not imply endorsement by the U. S. Government. This article is Contribution 1867 of the U. S. Geological Survey Great Lakes Science Center.

Materials

Name  Company Catalog Number Comments
870-L fiberglass tanks Frigid Units RT-430-1
2,380-L fiberglass tanks Frigid Units RT-630-1
Tricaine methanesulfonate (Finquel) Argent Chemical Laboratories, Inc. C-FINQ-UE-100G Eugenol could also be used as an anesthetic.
Ashland chef knife Chicago Cutlery SKU 1106336
Cutting board Williams-Sonoma 3863586
Hobart verical mixer (40 quart) Hobart Corporation
1.9-L food processor Robot Coupe, Inc. RSI 2Y1 
Polyethylene bags (various sizes) Arcan Inc.
I-Chem jars I-Chem 220-0125
Top-load electronic balance Mettler Toledo Mettler PM 6000 
Sodium sulfate, anhydrous – granular EMD SX0760E-3
Glass extraction thimbles (45 mm x 130 mm) Wilmad-Lab Glass LG-7070-114
Teflon boiling chips Chemware 919120
Rapid Vap nitrogen sample concentrator Labconco 7910000
N-Vap nitrogen concentrator Organomation 112
Soxhlet extraction glassware (500 mL) Wilmad-Lab Glass  LG-6900-104
Hexane Burdick & Jackson  Cat. 211-4
Dichloromethane Burdick & Jackson  Cat. 300-4
Silica gel BDH Cat. BDH9004-1KG
Labl Line 5000 mult-unit extraction heater Lab Line Instruments
Agilent 5973 GC/MS with chemical ionization Agilent 5973N
Internal standard solution  Cambridge Isotope Laboratories EC-1410-1.2
PCB congener calibration standards Accustandard C-CSQ-SET
DB-XLB column (60m x 0.25mm, 0.25 micron) Agilent/ J&W 122-1262

Riferimenti

  1. Madenjian, C. P., Carpenter, S. R., Rand, P. S. Why are the PCB concentrations of salmonine individuals from the same lake so highly variable?. Canadian Journal of Fisheries and Aquatic Sciences. 51 (4), 800-807 (1994).
  2. Madenjian, C. P., et al. Net trophic transfer efficiency of PCBs to Lake Michigan coho salmon from their prey. Environmental Science and Technology. 32 (20), 3063-3067 (1998).
  3. Thomann, R. V. Bioaccumulation model of organic chemical distribution in aquatic food chains. Environmental Science and Technology. 23 (6), 699-707 (1989).
  4. Calabrese, E. J., Baldwin, L. A. . Performing ecological risk assessments. , (1993).
  5. Madenjian, C. P., et al. Variation in net trophic transfer efficiencies among 21 PCB congeners. Environmental Science and Technology. 33 (21), 3768-3773 (1999).
  6. Jackson, L. J., Schindler, D. E. Field estimates of net trophic transfer of PCBs from prey fishes to Lake Michigan salmonids. Environmental Science and Technology. 30 (6), 1861-1865 (1996).
  7. Gobas, F. A. P. C., Muir, D. C. G., Mackay, D. Dynamics of dietary bioaccumulation and faecal elimination of hydrophobic organic chemicals in fish. Chemosphere. 17 (5), 943-962 (1988).
  8. Madenjian, C. P., O’Connor, D. V., Rediske, R. R., O’Keefe, J. P., Pothoven, S. A. Net trophic transfer efficiencies of polychlorinated biphenyl congeners to lake whitefish (Coregonus clupeaformis) from their food. Environmental Toxicology and Chemistry. 27 (3), 631-636 (2008).
  9. Isosaarl, P., Kiviranta, H., Lie, &. #. 2. 1. 6. ;., Lundebye, A. K., Ritchie, G., Vartiainen, T. Accumulation and distribution of polychlorinated dibenzo-p-dioxin, dibenzofuran, and polychlorinated biphenyl congeners in Atlantic salmon (Salmo salar). Environmental Toxicology and Chemistry. 23 (7), 1672-1679 (2004).
  10. Buckman, A. H., Brown, S. B., Hoekstra, P. F., Solomon, K. R., Fisk, A. T. Toxicokinetics of three polychlorinated biphenyl technical mixtures in rainbow trout (Oncorhynchus mykiss). Environmental Toxicology and Chemistry. 23 (7), 1725-1736 (2004).
  11. Burreau, S., Axelman, J., Broman, D., Jakobsson, E. Dietary uptake in pike (Esox lucius) of some polychlorinated biphenyls, polychlorinated naphthalenes and polybrominated diphenyl ethers administered in natural diet. Environmental Toxicology and Chemistry. 16 (12), 2508-2513 (1997).
  12. Madenjian, C. P., DeSorcie, T. J., Stedman, R. M. Ontogenic and spatial patterns in diet and growth of lake trout in Lake Michigan. Transactions of the American Fisheries Society. 127 (2), 236-252 (1998).
  13. Paterson, G., Whittle, D. M., Drouillard, K. G., Haffner, G. D. Declining lake trout (Salvelinus namaycush) energy density: are there too many salmonid predators in the Great Lakes?. Canadian Journal of Fisheries and Aquatic Sciences. 66 (6), 919-932 (2009).
  14. Madenjian, C. P., O’Connor, D. V., Nortrup, D. A. A new approach toward evaluation of fish bioenergetics models. Canadian Journal of Fisheries and Aquatic Sciences. 57 (5), 1025-1032 (2000).
  15. Madenjian, C. P., Pothoven, S. A., Kao, Y. C. Reevaluation of lake trout and lake whitefish bioenergetics models. Journal of Great Lakes Research. 39 (2), 358-364 (2013).
  16. Madenjian, C. P., et al. Evaluation of a lake whitefish bioenergetics model. Transactions of the American Fisheries Society. 135 (1), 61-75 (2006).
  17. Madenjian, C. P., O’Connor, D. V., Chernyak, S. M., Rediske, R. R., O’Keefe, J. P. Evaluation of a chinook salmon (Oncorhynchus tshawytscha) bioenergetics model. Canadian Journal of Fisheries and Aquatic Sciences. 61 (4), 627-635 (2004).
  18. Madenjian, C. P., David, S. R., Rediske, R. R., O’Keefe, J. P. Net trophic transfer efficiencies of polychlorinated biphenyl congeners to lake trout (Salvelinus namaycush) from its prey. Environmental Toxicology and Chemistry. 31 (12), 2821-2827 (2012).
  19. Madenjian, C. P., O’Connor, D. V. Laboratory evaluation of a lake trout bioenergetics model. Transactions of the American Fisheries Society. 128 (5), 802-814 (1999).
  20. Ballschmiter, K., Bacher, R., Mennel, A., Fischer, R., Riehle, U., Swerev, M. The determination of chlorinated biphenyls, chlorinated dibenzodioxins, and chlorinated dibenzofurans by GC-MS. HRC Journal of High Resolution Chromatography. 15 (4), 260-270 (1992).
  21. Madenjian, C. P., David, S. R., Pothoven, S. A. Effects of activity and energy budget balancing algorithm on laboratory performance of a fish bioenergetics model. Transactions of the American Fisheries Society. 141 (5), 1328-1337 (2012).
  22. Lieb, A. J., Bills, D. D., Sinnhuber, R. O. Accumulation of dietary polychlorinated biphenyls (Aroclor 1254) by rainbow trout. Journal of Agricultural and Food Chemistry. 22 (4), 638-642 (1974).
  23. Niimi, A. J., Oliver, B. G. Biological half-lives of polychlorinated biphenyl (PCB) congeners in whole fish and muscle of rainbow trout (Salmo gairdneri). Canadian Journal of Fisheries and Aquatic Sciences. 40 (9), 1388-1394 (1983).
  24. Gobas, F. A. P. C., Wilcockson, J. B., Russell, R. W., Haffner, G. D. Mechanism of biomagnification in fish under laboratory and field conditions. Environmental Science and Technology. 33 (1), 133-141 (1999).
  25. Dmitrovic, J., Chan, S. C. Determination of polychlorinated biphenyl congeners in human milk by gas chromatography – negative chemical ionization mass spectrometry after sample clean-up by solid-phase extraction. Journal of Chromatography B. 778 (1-2), 147-155 (2002).
  26. Zorn, M. E., Gibbons, R. D., Sonzogni, W. C. Weighted least-squares approach to calculating limits of detection and quantification by modeling variability as a function of concentration. Analytical Chemistry. 69 (15), 3069-3075 (1997).
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Citazione di questo articolo
Madenjian, C. P., Rediske, R. R., O’Keefe, J. P., David, S. R. Laboratory Estimation of Net Trophic Transfer Efficiencies of PCB Congeners to Lake Trout (Salvelinus namaycush) from Its Prey. J. Vis. Exp. (90), e51496, doi:10.3791/51496 (2014).

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