Elemental Ecology Exercise #2 (30 points) This exercise is designed to teach you how to (1) calculate trophic discrimination factors; (2) use 18 bioapatite δ O values to determine the oxygen isotope composition of meteoric water; (3) determine tissue-specific discrimination factors; and (4) use stable isotope mixing models to quantify dietary proportions. All data are provided below or in the attached Excel spreadsheet (Exercise #2.xls); both are available on the course website. This exercise is due on Tuesday, April 8th. Email your homework to Seth Newsome ([email protected]). Rename and save this workbook file by adding your last name to the filename. You can work collaboratively on this assignment, and the course instructor is available for questions and assistance. Problem #1: Leopard Shark Trophic Discrimination! One important aspect of animal isotopic ecology is determining the isotopic offset between a consumer’s tissues and its diet, which is often called a trophic discrimination or trophic enrichment factor. As part of her dissertation, Dr. Sora Kim conducted a 3+ year captive feeding experiment on leopard sharks (Triakis semifasciata) to determine trophic discrimination factors (and isotopic incorporation rates) for a variety of tissues. Over the past several weeks, you have prepared and analyzed muscle and liver from these sharks and muscle of their squid and tilapia diets. For the first part of this lab exercise, please determine the diet-to-tissue trophic discrimination factors for these leopard shark tissues. What is the equation for a trophic discrimination factor? 13 15 13 15 13 15 What are the average δ C and δ N values for muscle? C:N? What are the average δ C and δ N values for liver? C:N? What are the average δ C and δ N values for squid? C:N? What are the average trophic discrimination factors for muscle? For liver? (Propagate the error between the tissue and prey isotope values) Why do you think the discrimination factors are different between tissues? 13 Why are C:N ratios important? Now plot δ C vs. C:N. Why are the liver C:N ratios concerning? Problem #2: What Cows Drink The inorganic portion of bone is bioapatite, a biological form of hydroxyapatite [Ca5(PO4)3OH]. Within this mineral matrix, carbonate (CO3) can substitute for phosphate (PO4). Archeologists and 13 18 paleontologists analyze this CO3 for δ C and δ O values. 13 1. Compare the organic and inorganic δ C values. Are they similar? Why or why not. 18 18 2. The δ O value of an animal’s body water is dependent on the δ O value of potential sources (food and drinking water) and temperature. However, mammals keep their bodies at constant temperature, so the ambient environmental temperature is not a major factor in determining the 18 δ O value of biogenic inorganic substrates (e.g., tooth enamel). Instead, we can use mammalian 18 18 δ O values to determine the δ O value of body water that is assumed to represent local meteoric water since tooth/bone carbonate is formed in equilibrium with body water. The isotopic 18 value of body water (δ Ow) can be calculated with the equations below: 10! ln 𝛼!"!#!!! = 2.78 × 10! 𝑇 ! − 2.89 𝛼!"!#!!! = (𝛿 !" 𝑂!"!#! + 10! ) (𝛿 !" 𝑂! + 10! ) 18 where T is temperature in Kelvin and δ OCaCO3 is the oxygen isotope value of calcium carbonate. 18 These cows were raised near Columbia, Missouri. Does the δ Ow match the modeled value from isotopes.org?* Describe why or why not. 18 2 *To access the google earth add-on that gives you modeled δ O and δ H values, download the OIPC from http://wateriso.utah.edu/waterisotopes/index.html Problem #3: Thresher Shark Tissue-Specific Discrimination Tissue-specific isotopic discrimination is a poorly understood phenomenon in animal isotope 13 ecology. Our colleague, Dr. Carlos Polo, studies sharks in Ecuador and Mexico. Carlos uses δ C 15 and δ N to characterize trophic relationships, habitat use, and large-scale (i.e., ocean basin) movement within and among shark species in the eastern Tropical Pacific Ocean; as an aside, his data have some major implications for conservation and management of a ruthlessly exploited group of fish. A recent dataset from pelagic thresher sharks (Alopias pelagicus) collected off 15 coastal Ecuador showed an intriguing difference between δ N of muscle and vertebrae tissues (see below). One of the possible explanations for this dataset is tissue-specific discrimination. a. Explain what tissue-specific discrimination is and what types of data are needed to test the 15 explanation that this phenomenon is the reason why Carlos’ shark tissues differ in their δ N isotopic composition. Using the data from the literature (see papers below by Mizuta et al. 2001, Kittiphattanabawom* et al. 2010, and Popp et al. 2007), determine whether or not tissue-specific discrimination is driving the observed trend. *This is his/her real name. b. Why can we use data for tuna (Popp et al. 2007) as a surrogate for thresher sharks? c. Tissue-specific discrimination aside, what is another possible explanation for the observed 15 δ N difference between muscle and vertebrae tissue? Shark Tissue Muscle Vertebrae 13 δ C -16.0 -16.8 15 δ N 13.8 9.2 REFERENCES Kittiphattanabawon P, Soottawat B, Wonnop V, Fereidoon S (2010) Isolation and characterization of collagen from the cartilages of brownbanded bamboo (Chiloscylliumpunctatum) and black tip (Carcharhinus limbatus) shark. Food Science and Technology 43:792-800. Mizuta S, Hwang J, Yoshinaka R (2001) Molecular species of collagen from wing muscle of skate (Raja Kenojei). Food Chemistry 100(3):921-925. Popp BN, Graham BS, Olson RJ, Cecelia CSH, Lott MJ, López-Ibarra GA, Galván-Magaña F, Fry B (2007) Insight into the Trophic Ecology of Yellowfin Tuna, Thunnus albacares, from Compound-Specific Nitrogen Isotope Analysis of Proteinaceous Amino Acids. (download at: http://www.soest.hawaii.edu/GG/FACULTY/POPP/bpopp-publ.html) Problem #4: Linear and Concentration-Dependent Stable Isotope Mixing Models Mixing models are an often used but rarely understood component of many applied studies in animal isotope ecology. Briefly describe how mixing models work, the type of data required for their use, and most importantly the major assumptions that are implicit in their accurate use and interpretation. a. Using the isotopic dataset from Alaskan black and brown bears below, determine the relative proportion of the two general prey sources (salmon and berries) to each populations diet using a simple 2-source, 1-isotope linear mixing model. Be sure to write and describe the 13 15 variables in the equations for both δ C and δ N mixing models: 15 15 15 15 15 δ NM = fx(δ Nx + Δ Nx) + fy(δ Ny + Δ Ny) 1 = fx + fy b. Using the same isotopic dataset, determine the relative proportions of the three general prey sources with a concentration-dependent mixing model using the [C] and [N] data supplied below: 15 15 15 δ Nx + Δ Nx = δ N’x 15 15 15 δ Ny + Δ Ny = δ N’y 15 15 15 15 (δ N’x - δ NM)[N]xfx + (δ N’y - δ NM)[N]yfy = 0 1 = fx + fy c. What are the major physiological mechanisms that are likely driving the observed differences in the prey proportions between the model results in part A and B? d. In some instances, when you draw mixing triangle by connecting isotope values of three sources, some of the consumers (e.g., bears) have isotope values outside the mixing triangle. Give one or more reasons that consumers can have isotope values outside the mixing envelope defined by the measured sources. Consumer/Prey Brown Bear (sympatric) Black Bear (sympatric) Black Bear (allopatric) δ N 10.9 4.9 7.6 15 Δ N – – – 15 [N] – – – Salmon Berries 13.2 -0.9 2.3 4.1 12.0 1.0 Problem #5: Sandia Mountains Survivor 13 15 In this exercise you will practice interpreting carbon (δ C) and nitrogen (δ N) isotopes by analyzing data collected during a popular reality television show, produced right here in the Sandia Mountains of New Mexico (in the summer of course). You will need to make some graphs and tables for this exercise, and then we will review the answers with the entire class. We begin by gathering a few samples from the set – a few leaves on the ground, mushrooms, a worm and a centipede from the soil, spiders from the bushes and bird feathers from sparrows and hawks. o We dry the samples overnight at 60 C, grind them to a fine powder with a mortar and pestle, 13 weigh them into tin capsules, and analyze them in an isotope ratio mass spectrometer. The δ C 15 and δ N results arrive in your email inbox a month later, and now the work begins to interpret the data. Step 1. Make a table and an isotope biplot (x,y) graph with the following stable isotope data: 15 Sample ID Juniper Leaves Mushroom Worm Centipede Spider #1 Spider #2 Sparrow Feather Hawk Feather 13 δ N (‰) 2.0 3.2 4.2 8.1 5.4 10.3 8.5 12.8 δ C (‰) -27.2 -24.1 -26.3 -21.5 -24.0 -21.2 -23.7 -18.2 15 Questions: Look at your (x,y) plots – are the axes correctly labeled? Which is the x-axis, δ N 13 and δ C, and why did you choose one or the other? Can you make an initial assessment of who is eating whom? 15 Step 2. Assign trophic levels to your plot, using a 3‰ increase in δ N increase indicate an increase of one trophic level (TL). Use the plant isotope value as TL 1, and see how many consumer animal TLs beyond 1 are indicated; there are usually less than 8 TLs in natural food webs. The general formula for calculating trophic levels starting with plants at TL1 is: 15 15 TL = 1 + (δ NCONSUMER - δ NPLANT)/3 15 Note that in this formula the “3” is the per mil (‰) increment in δ N that occurs on average per each trophic level, and the “1” in the equation ensures that trophic levels start at TL = 1 at the plant level. Questions: How many trophic levels are there? Is there any sample whose trophic level does not make sense? Step 3. During the second month of the show (to insure full incorporation) we were able to 13 15 collect fingernails from all of the cast members, and prepared this tissue for δ C and δ N analysis; see attached spreadsheet. We also did a bit more “fieldwork” and found a few 13 15 smuggled items in the camp on the set, including some Frito corn chips (δ C: -13.5‰, δ N: 13 15 2‰) and a pig bone (δ C: -12.5‰, δ N: 5.5‰). Update your table and make another isotope biplot graph with the combined data. Questions: Does including these new points change your impressions of which food sources support the cast members on Wyoming Survivor? Do you think the lodgepole pines are the only primary producer of nutrition in this food web? Which food sources are most important? Which cast members appear to be cheating the most? 13 Step 4: Make corrections to the cast member δ C data, factoring out discrimination effects 13 related to TL, and leaving source inputs as the sole reason for the animal δ C variations. 13 This correction gives you the δ C value of the inferred plant diet for each consumer, needed 13 for direct comparison to the possible plant foods. The increase in δ C per trophic level 13 averages near 0.5‰, so use the following formula to calculate δ C values corrected for trophic level effects: 13 13 Corrected δ C = Measured δ C – 0.5 *(TL -1) 15 13 where TL is estimated from the δ N data in step 2 above. Add the corrected δ C values to 13 your data table. Questions: Do these TL corrections change the δ C data very much? Which food sources are most important for the overall food web? Which cast members appear to be cheating the most?