Göl Alabalık PCB kongenerinin Net Trofik Transferi Etkinliklerinin Laboratuvarı Tahmini (<em> Salvelinus namaycush</em>) Onun Prey dan
Summary
Onların yırtıcı balıkçıl balık poliklorlanmış bifenil (PCB) Petkim'de net trofik transfer verimi laboratuar tahmini için bir tekniği sunulmuştur. Alanına laboratuvar sonuçlarının uygulanabilirliğini en üst düzeye çıkarmak için, balıkçıl balık tipik alanda yenir av balık beslenen edilmelidir.
Abstract
Avlarını ikinci balıkçıl balık poliklorlanmış bifenil (PCB) konjenerlerinin net trofik aktarım etkinliği (γ) laboratuar tahmin etmek için bir teknik tarif edilmektedir. 135 gün laboratuar deney sırasında, biz sekiz laboratuar tanklarda muhafaza bloater göl alabalığı (Salvelinus namaycush) Lake Michigan yakalanmıştı (Coregonus hoyi) beslenir. Bloater göl alabalık için doğal bir av. Tankların dördünde, nispeten yüksek bir akış hızı, bir düşük akış hızı, diğer dört tank kullanılmıştır Ancak düşük göl alabalığı aktivitesi için izin göl alabalık nispeten yüksek aktivite için kullanılmıştır. Bir tank-ile-tank temelinde, deneyin her bir günü göl alabalık yenen gıda miktarı kaydedildi. Her bir göl alabalığı deneyin başlangıcında ve sonunda tartıldı. Sekiz tankların her birinden dört ila dokuz göl alabalığı Deneyin başlangıcında öldürülür ve tankların her kalan 10 göl alabalığı euthan edildiDeneyin sonunda ize. Bu deney sonunda göl alabalığı Deneyin başlangıcında göl alabalığı 75 PCB konjenerlerinin konsantrasyonu belirlenir ve bloaters olarak, deney sırasında göl alabalığı beslenir. Bu ölçümlere dayanarak, γ sekiz tankların her 75 PCB konjenerlerinin her biri için hesaplandı. Γ aktif ve inaktif hem göl alabalık için 75 PCB Petkim'de her biri için hesaplanan idi. Deney sekiz tanklarda çoğaltılmış çünkü, yaklaşık standart hata γ tahmin edilebilir demek. Bu tür denemelerde sonuçları çevresel kirlenme, çeşitli senaryolar altında kirlenmiş balık yeme insanlar ve yaban hayatı gelecekteki riskini tahmin etmek için risk değerlendirme modelleri yararlıdır.
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
Representative Results
Discussion
Γ en doğru tahminleri için doğru deneyi Deney sırasında tank ve tank her meyvelerin gıda miktarı her yerleştirilen gıda miktarını hem de takip etmek mümkün olmalıdır. Bunu gerçekleştirmek için, deneyci tanklarından meyvelerin gıda kaldırmak ve doğru ağırlığını belirlemek mümkün olmalıdır. Aslında yırtıcı balıklar tarafından yenen gıda doğru izlemeye ek olarak, γ doğru tahmin de deney yeterli süresine bağlı olabilir. Yaygın olarak anılan laboratuar çalışmaları özellikl…
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 |
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