scholarly journals Assessing the Reliability of Quantitative Fatty Acid Signature Analysis and Compound-Specific Isotope Analysis-Based Mixing Models for Trophic Studies

Biomolecules ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1590
Author(s):  
Igor Prokopkin ◽  
Olesia Makhutova ◽  
Elena Kravchuk ◽  
Nadezhda Sushchik ◽  
Olesia Anishchenko ◽  
...  

The study of the trophic relationships of aquatic animals requires correct estimates of their diets. We compared the quantitative fatty acid signature analysis (QFASA) and the isotope-mixing model IsoError, based on the compound-specific isotope analysis of fatty acids (CSIA-FA), which are potentially effective models for quantitative diet estimations. In a 21-day experiment, Daphnia was fed a mixture of two food items, Chlorella and Cryptomonas, which were supplied in nearly equal proportions. The percentages and isotope values of the FAs of the algal species and Daphnia were measured. The IsoError based on CSIA-FA gave an estimation of algae consumption using only one FA, 18:3n-3. According to this model, the proportion of consumption of Chlorella decreased while the proportion of consumption of Cryptomonas increased during the experiment. The QFASA model was used for two FA subsets—the extended-dietary subset, which included sixteen FAs, and the dietary one, which included nine FAs. According to both subsets, the portion of consumed Chlorella decreased from Day 5 to 10 and then increased at Day 21. The comparison of the two model approaches showed that the QFASA model is a more reliable method to determine the contribution of different food sources to the diet of zooplankton than the CSIA-based mixing model.

2020 ◽  
Vol 8 (12) ◽  
pp. 1030
Author(s):  
Junbo Zhang ◽  
Chonglan Ren ◽  
Hu Zhang ◽  
Fang Yin ◽  
Shuo Zhang ◽  
...  

The dynamic predator–prey relations in the food web are vital for understanding the function and structure of ecosystems. Dietary estimation is a research hotspot of quantitative ecology, providing key insights into predator–prey relationships. One of the most promising approaches is quantitative fatty acid signature analysis (QFASA), which is the first generation of statistical tools to estimate the quantitative trophic predator–prey relationships by comparing the fatty acid (FA) signatures among predators and their prey. QFASA has been continuously widely applied, refined and extended since its introduction. This article reviewed the research progress of QFASA from development and application. QFASA reflects the long-term diet of predator, and provides the quantitative dietary composition of predator, but it is sensitive to the metabolism of predator. The calibration coefficients (CCs) and the FA subset are two crucial parameters to explain the metabolism of predators, but the incorrect construction or improper use of CCs and the FA subset may cause bias in dietary estimation. Further study and refinement of the QFASA approach is needed to identify recommendations for which CCs and subsets of FA work best for different taxa and systems.


2004 ◽  
Vol 74 (2) ◽  
pp. 211-235 ◽  
Author(s):  
Sara J. Iverson ◽  
Chris Field ◽  
W. Don Bowen ◽  
Wade Blanchard

2021 ◽  
pp. 102141
Author(s):  
Quan Xie ◽  
Xi Ning ◽  
Xiaoxiao He ◽  
Lixia Deng ◽  
Zhenger Wu ◽  
...  

2020 ◽  
Author(s):  
Pranav Hirave ◽  
Miriam Glendell ◽  
Axel Birkholz ◽  
Christine Alewell

<p>The River Dee is one of the major river systems in Scotland, renowned for its economically important Atlantic salmon (<em>Salmo salar</em>) population. The Tarland Burn (70 km<sup>2</sup>), an intensively managed catchment, is a significant source of nutrients and suspended sediments (SS) to the River Dee, causing degradation of its water quality. To trace the SS sources in the Tarland Burn catchment, we used compound-specific isotope analysis (CSIA) fingerprinting technique. The CSIA fingerprinting technique applied in this study involved (i) carbon isotope ratio (δ<sup>13</sup>C) measurements of plant derived long-chain fatty acids (LCFAs) extracted from source soils and from river SS as a mixture signal as input tracer values, and (ii) computation of source proportions in the mixture using an end member mixing model ‘MixSIAR’ which is based on the Bayesian approach.</p><p>Source soils were sampled from the land-use types observed in a headwater catchment (10 km<sup>2</sup>) i.e. arable, temporary grassland under arable rotation, permanent grassland, coniferous forest, heather moorland and riparian zone. SS samples were collected from the headwaters, second order streams, and also from the outlet of the Tarland Burn catchment, representing a nested sampling approach. A comparison of the two common suspended sediment collection techniques to understand the role of sampling technique and associated particle sizes resulted in no substantial difference in the tracer values. SS were sampled once every two months over a period of 14 months between May 2017 and June 2018. δ<sup>13</sup>C values of LCFAs (even homologues between C<sub>22:0</sub> - C<sub>30:0</sub>) of the SS (mixture) were within the range of source soils corresponding tracer values, confirming their conservative behaviour during transport.</p><p>Quantification of source proportions using mixing model suggested that headwater streams SS originated predominantly from permanent grasslands. They are largely located on steep topography, leading to higher hydrological connectivity and possible increased pressure from livestock. Although plantation forestry and heather moorland are prominent land-uses in the catchment, their contribution as SS sources is marginal. More intensive arable land use in the lowland areas of Tarland catchment was reflected by their high contribution to SS at the downstream locations. More intensive rainfall events during winter likely led to higher sediment fluxes from the normally less connected permanent grasslands at the catchment outlets during high flow.</p><p>Our attempt of gathering source soil information from a headwater region of a catchment and upscaling this information to model the source proportions in downstream mixtures integrating the whole catchment was successful, however uncertainties increased for the downstream results</p>


2015 ◽  
Vol 5 (6) ◽  
pp. 1249-1262 ◽  
Author(s):  
Jeffrey F. Bromaghin ◽  
Karyn D. Rode ◽  
Suzanne M. Budge ◽  
Gregory W. Thiemann

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