Summary

湖トラウトのPCB同族体の正味栄養の導入効率の実験室推定(<em>イワナnamaycush</em>)獲物から

Published: August 29, 2014
doi:

Summary

獲物から魚食性魚類のポリ塩化ビフェニル(PCB)同族体の正味の栄養転送効率の研究室推定のための技術が提供される。フィールドに検査結果の適用可能性を最大にするために、魚食性の魚​​は、一般的にフィールドに食べられている獲物の魚を供給する必要があります。

Abstract

獲物から魚食性魚類のポリ塩化ビフェニル(PCB)同族体の正味の栄養転送効率(γ)の研究室で推定するための技術は、本明細書に記載されている。 135日間の室内実験中、当社は8実験室の水槽に保管ブローターレイクトラウト( イワナのnamaycush)にミシガン湖で捕獲されていた(Coregonus hoyi)を供給した。ブローターはレイクトラウトのための自然な獲物である。タンク4内に、比較的高い流量が低流量が低いレイクトラウトの活性を可能にする、他の4つのタンクに使用したのに対し、レイクトラウト比較的高い活性を保証するために使用した。タンク·バイ·タンクベースでは、実験のそれぞれの日にレイクトラウトが食べた食物の量を記録した。各レイクトラウト、実験の開始時と終了時に秤量した。 8各タンクからの4〜9個のレイクトラウトは、実験の開始時に屠殺し、各タンクに残っているすべての10レイクトラウトはeuthanあった実験の終了時化された。私たちは、実験の最後にレイクトラウトに、実験開始時にレイクトラウト75 PCB同族体の濃度を決定し、bloatersで実験中レイクトラウトに供給。これらの測定に基づいて、γは、8つのタンクのそれぞれに75 PCB同族体のそれぞれについて計算した。 γは、アクティブおよび非アクティブの両方のレイクトラウト75 PCB同族体毎に算出された平均。実験は8タンク内に複製されたため、約標準誤差はγを推定することができたわけで。この種の実験の結果は、環境汚染のさまざまなシナリオの下で汚染された魚を食べた人間や野生生物への将来のリスクを予測するために、リスク評価モデルにおいて有用である。

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室内実験実験中に捕食魚に供給される獲物の魚を入手します。好ましくは、これらの獲物の魚は、フィールドに入力されてい凍結し、約-30°Cで保存してください。獲物の魚のための潜在的な供給源としての商業漁業を考えてみましょう。 実験室タンクに捕食魚を導入する実験に使用する。 15捕食魚まで870リットルのタンクのそれぞれに導入し、最大30捕食魚されてきたこれま?…

Representative Results

最後のレイクトラウトの平均重量は853から1566グラム( 表1)の範囲であった間に、最初のレイクトラウトの平均重量は694〜907グラムの範囲であったようにレイクトラウトは、実験中に成長のかなりの量を示した。 135日間の実験中レイクトラウトによって消費された食物の平均量は641から2649グラムの範囲であった。平均のPCB同族体濃度はによって0.03から29.31の範囲であった間に、…

Discussion

γの最も正確な推定値では、実験者は正確に実験中のタンクやタンクのそれぞれに食べ残しの量のそれぞれに配置された食物の量の両方を追跡することができなければならない。これを実現するために、実験者はタンクから食べ残しをすべて削除し、正確に重量を測定することができなければならない。実際に捕食魚に食べられ、食物の正確なトラッキングに加えて、γの正確な推定はまた?…

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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