scholarly journals Uncertainties associated with trophic discrimination factor and body size complicate calculation of δ 15 N‐derived trophic positions in Arapaima sp.

2020 ◽  
Vol 29 (4) ◽  
pp. 779-789 ◽  
Author(s):  
Cristina Mariana Jacobi ◽  
Francisco Villamarín ◽  
Timothy D. Jardine ◽  
William Ernest Magnusson
2016 ◽  
Author(s):  
Kevin Healy ◽  
Seán B.A Kelly ◽  
Thomas Guillerme ◽  
Richard Inger ◽  
Stuart Bearhop ◽  
...  

1. Stable isotope analysis is a widely used tool for the reconstruction and interpretation of animal diets and trophic relationships. Analytical tools have improved the robustness of inferring the relative contribution of different prey sources to an animal’s diet by accounting for many of the sources of variation in isotopic data. One major source of uncertainty is Trophic Discrimination Factor (TDF), the change in isotopic signatures between consumers’ tissues and their food sources. This parameter can have a profound impact on model predictions, but often, it is not feasible to estimate a species’ TDF value and so researchers often use aggregated or taxon level estimates, an assumption that in turn has major implications for the interpretation of subsequent analyses. 2. We collected extensive carbon (δ13C) and nitrogen (δ15N) TDF data on mammals and birds from published literature. We then used a Bayesian linear modelling approach to determine if, and to what extent, variation in TDF values can be attributed to a species’ ecology, physiology, phylogenetic relationships and experimental variation. Finally, we developed a Bayesian imputation approach to estimate unknown TDF values and compared the accuracy of this tool using a series of cross-validation tests. 3. Our results show that, for birds and mammals, TDF values are influenced by phylogeny, tissue type sampled, diet of consumer, isotopic signature of food source, and the error associated with the measurement of TDF within a species. Furthermore, our cross-validation tests determined that, our tool can (i) produce accurate estimates of TDF values with a mean distance of 0.2 ‰ from observed TDF values, and (ii) provide an estimate of the precision associated with these estimates, with species presence in the data allowing for a reduced level of uncertainty. 4. By incorporating various sources of variation and reflecting the levels of uncertainty associated with TDF estimates our novel tool will contribute to more accurate and honest reconstructions and interpretations of animal diets and trophic interactions. This tool can be extended readily to include other taxa and sources of variation as data becomes available. To facilitate this, we provide a step-by-step guide and code for this tool: Discrimination Estimation in R (DEsiR)


2017 ◽  
Author(s):  
Kevin Healy ◽  
Seán B.A Kelly ◽  
Thomas Guillerme ◽  
Richard Inger ◽  
Stuart Bearhop ◽  
...  

1. Stable isotope analysis is a widely used tool for the reconstruction and interpretation of animal diets and trophic relationships. Analytical tools have improved the robustness of inferring the relative contribution of different prey sources to an animal’s diet by accounting for many of the sources of variation in isotopic data. One major source of uncertainty is Trophic Discrimination Factor (TDF), the change in isotopic signatures between consumers’ tissues and their food sources. This parameter can have a profound impact on model predictions, but often, it is not feasible to estimate a species’ TDF value and so researchers often use aggregated or taxon level estimates, an assumption that in turn has major implications for the interpretation of subsequent analyses. 2. We collected extensive carbon (δ13C) and nitrogen (δ15N) TDF data on mammals and birds from published literature. We then used a Bayesian linear modelling approach to determine if, and to what extent, variation in TDF values can be attributed to a species’ ecology, physiology, phylogenetic relationships and experimental variation. Finally, we developed a Bayesian imputation approach to estimate unknown TDF values and compared the accuracy of this tool using a series of cross-validation tests. 3. Our results show that, for birds and mammals, TDF values are influenced by phylogeny, tissue type sampled, diet of consumer, isotopic signature of food source, and the error associated with the measurement of TDF within a species. Furthermore, our cross-validation tests determined that, our tool can (i) produce accurate estimates of TDF values with a mean distance of 0.2 ‰ from observed TDF values, and (ii) provide an estimate of the precision associated with these estimates, with species presence in the data allowing for a reduced level of uncertainty. 4. By incorporating various sources of variation and reflecting the levels of uncertainty associated with TDF estimates our novel tool will contribute to more accurate and honest reconstructions and interpretations of animal diets and trophic interactions. This tool can be extended readily to include other taxa and sources of variation as data becomes available. To facilitate this, we provide a step-by-step guide and code for this tool: Discrimination Estimation in R (DEsiR)


2020 ◽  
Author(s):  
Yuko Takizawa ◽  
Yoshinori Takano ◽  
Bohyung Choi ◽  
Prarthana Dharampal ◽  
Shawn Steffan ◽  
...  

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3436 ◽  
Author(s):  
Shaena Montanari

Stable isotope analysis of feces can provide a non-invasive method for tracking the dietary habits of nearly any mammalian species. While fecal samples are often collected for macroscopic and genetic study, stable isotope analysis can also be applied to expand the knowledge of species-specific dietary ecology. It is somewhat unclear how digestion changes the isotope ratios of animals’ diets, so more controlled diet studies are needed. To date, most diet-to-feces controlled stable isotope experiments have been performed on herbivores, so in this study I analyzed the carbon and nitrogen stable isotope ratios in the diet and feces of the meerkat (Suricata suricatta), a small omnivorous mammal. The carbon trophic discrimination factor between diet and feces (Δ13Cfeces) is calculated to be 0.1 ± 1.5‰, which is not significantly different from zero, and in turn, not different than the dietary input. On the other hand, the nitrogen trophic discrimination factor (Δ15Nfeces) is 1.5 ± 1.1‰, which is significantly different from zero, meaning it is different than the average dietary input. Based on data generated in this experiment and a review of the published literature, carbon isotopes of feces characterize diet, while nitrogen isotope ratios of feces are consistently higher than dietary inputs, meaning a discrimination factor needs to be taken into account. The carbon and nitrogen stable isotope values of feces are an excellent snapshot of diet that can be used in concert with other analytical methods to better understand ecology, diets, and habitat use of mammals.


Author(s):  
Kevin Healy ◽  
Seán B.A Kelly ◽  
Thomas Guillerme ◽  
Richard Inger ◽  
Stuart Bearhop ◽  
...  

1. Stable isotope analysis is a widely used tool for the reconstruction and interpretation of animal diets and trophic relationships. Analytical tools have improved the robustness of inferring the relative contribution of different prey sources to an animal’s diet by accounting for many of the sources of variation in isotopic data. One major source of uncertainty is Trophic Discrimination Factor (TDF), the change in isotopic signatures between consumers’ tissues and their food sources. This parameter can have a profound impact on model predictions, but often, it is not feasible to estimate a species’ TDF value and so researchers often use aggregated or taxon level estimates, an assumption that in turn has major implications for the interpretation of subsequent analyses. 2. We collected extensive carbon (δ13C) and nitrogen (δ15N) TDF data on mammals and birds from published literature. We then used a Bayesian linear modelling approach to determine if, and to what extent, variation in TDF values can be attributed to a species’ ecology, physiology, phylogenetic relationships and experimental variation. Finally, we developed a Bayesian imputation approach to estimate unknown TDF values and compared the accuracy of this tool using a series of cross-validation tests. 3. Our results show that, for birds and mammals, TDF values are influenced by phylogeny, tissue type sampled, diet of consumer, isotopic signature of food source, and the error associated with the measurement of TDF within a species. Furthermore, our cross-validation tests determined that, our tool can (i) produce accurate estimates of TDF values with a mean distance of 0.2 ‰ from observed TDF values, and (ii) provide an estimate of the precision associated with these estimates, with species presence in the data allowing for a reduced level of uncertainty. 4. By incorporating various sources of variation and reflecting the levels of uncertainty associated with TDF estimates our novel tool will contribute to more accurate and honest reconstructions and interpretations of animal diets and trophic interactions. This tool can be extended readily to include other taxa and sources of variation as data becomes available. To facilitate this, we provide a step-by-step guide and code for this tool: Discrimination Estimation in R (DEsiR)


Author(s):  
Kevin Healy ◽  
Seán B.A Kelly ◽  
Thomas Guillerme ◽  
Richard Inger ◽  
Stuart Bearhop ◽  
...  

1. Stable isotope analysis is a widely used tool for the reconstruction and interpretation of animal diets and trophic relationships. Analytical tools have improved the robustness of inferring the relative contribution of different prey sources to an animal’s diet by accounting for many of the sources of variation in isotopic data. One major source of uncertainty is Trophic Discrimination Factor (TDF), the change in isotopic signatures between consumers’ tissues and their food sources. This parameter can have a profound impact on model predictions, but often, it is not feasible to estimate a species’ TDF value and so researchers often use aggregated or taxon level estimates, an assumption that in turn has major implications for the interpretation of subsequent analyses. 2. We collected extensive carbon (δ13C) and nitrogen (δ15N) TDF data on mammals and birds from published literature. We then used a Bayesian linear modelling approach to determine if, and to what extent, variation in TDF values can be attributed to a species’ ecology, physiology, phylogenetic relationships and experimental variation. Finally, we developed a Bayesian imputation approach to estimate unknown TDF values and compared the accuracy of this tool using a series of cross-validation tests. 3. Our results show that, for birds and mammals, TDF values are influenced by phylogeny, tissue type sampled, diet of consumer, isotopic signature of food source, and the error associated with the measurement of TDF within a species. Furthermore, our cross-validation tests determined that, our tool can (i) produce accurate estimates of TDF values with a mean distance of 0.2 ‰ from observed TDF values, and (ii) provide an estimate of the precision associated with these estimates, with species presence in the data allowing for a reduced level of uncertainty. 4. By incorporating various sources of variation and reflecting the levels of uncertainty associated with TDF estimates our novel tool will contribute to more accurate and honest reconstructions and interpretations of animal diets and trophic interactions. This tool can be extended readily to include other taxa and sources of variation as data becomes available. To facilitate this, we provide a step-by-step guide and code for this tool: Discrimination Estimation in R (DEsiR)


Sign in / Sign up

Export Citation Format

Share Document