Food webs may be affected by evolutionary processes, and effective evolutionary time ultimately affects the probability of species evolving to fill the niche space. Thus, ecosystem history may set important evolutionary constraints on community composition and food web structure. Food chain length (FCL) has long been recognized as a fundamental ecosystem attribute. We examined historical effects on FCL in large lakes spanning >6 orders of magnitude in age. We found that food chains in the world’s ancient lakes (n = 8) were significantly shorter than in recently formed lakes (n = 10) and reservoirs (n = 3), despite the fact that ancient lakes harbored much higher species richness, including many endemic species. One potential factor leading to shorter FCL in ancient lakes is an increasing diversity of trophic omnivores and herbivores. Speciation could simply broaden the number of species within a trophic group, particularly at lower trophic levels and could also lead to a greater degree of trophic omnivory. Our results highlight a counter-intuitive and poorly-understood role of evolutionary history in shaping key food web properties such as FCL.
Citation: Doi H, Vander Zanden MJ, Hillebrand H (2012) Shorter Food Chain Length in Ancient Lakes: Evidence from a Global Synthesis. PLoS ONE 7(6): e37856. https://doi.org/10.1371/journal.pone.0037856
Editor: Tamara Natasha Romanuk, Dalhousie University, Canada
Received: January 29, 2012; Accepted: April 27, 2012; Published: June 6, 2012
Copyright: © 2012 Doi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Funding provided by the Japanese Society for the Promotion of Science. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Food chain length (FCL), which is a measure of the number of trophic levels in an ecosystem between primary producers and the top predator, has been recognized as a fundamental ecosystem attribute. FCL influences community structure, species diversity, and population stability by altering the organization of trophic interactions –. Defining the factors that determine FCL has been an important research focus for ecologists. Numerous widely cited hypotheses have been proposed. The productivity hypothesis predicts that energy availability limits FCL –, due to limited efficiency in energy transfer up the food chain, such that the available energy diminishes at higher trophic levels. The ecosystem size hypothesis predicts that FCL increases with increasing ecosystem size, such as lake volume and island area . The productive-space hypothesis  is a combination of the productivity and the ecosystem size hypotheses. This argues that total ecosystem production (per-unit-area productivity × ecosystem size) reflects the productive capacity of the ecosystem to support higher trophic levels. The dynamic stability hypothesis argues that long food chains tend to be dynamically unstable in the face of disturbance, such that food webs should be shorter in more highly-disturbed systems –.
Ecosystem history may set important evolutionary constraints on ecological processes and properties of ecosystems –. Food webs are affected by evolutionary processes such as speciation, and effective evolutionary time ultimately affects the probability of species evolving to fill the available niche space . In addition, a long evolutionary history may provide more opportunities for food web disturbances. Previous studies have shown that FCL varies greatly among systems , –. However, the role of ecosystem age and the historical signal on FCL has not been examined.
How might FCL vary as a function of ecosystem age? First, older ecosystems might be expected to have longer food chains, as speciation and colonization should increase overall biodiversity, and thus the increase the potential to assemble longer food chains . On the other hand, speciation could lead to an increase in herbivores and other low trophic position species. This might be expected since shorter food chains are expected to be more dynamically stable . There are numerous examples of evolutionary adaptations towards lower trophic position, for example, the filter feeding apparatus of baleen whales, which evolved from the teeth of toothed whales . If speciation simply increases the number of herbivorous species or increases the frequency of intraguild predation , older ecosystems could end up with shorter, not longer, food chains.
Here we investigate patterns of FCL using a global lake dataset. Lakes in our data set vary in size by >5 orders of magnitude, and in age from a few to 107 years, depending on whether they are tectonic, glacial or impounded lakes. Ancient lakes (typically >1 million year) have a long evolutionary history and consequently higher species diversity, often with a large number of endemic species. In the present study, we used stable nitrogen isotope-based estimates of FCL from reservoirs, glacial, and ancient lakes. Our data set includes 68% of all freshwater ancient lakes >1 million years in age. Since some empirical studies suggest that ecosystem size is a driver of FCL , we compared FCL in ancient lakes to more recent lakes within a similar range of lake volumes.
A) Boxplot for food-chain length in lakes of different origins. Symbols represent the median FCL, boxes = inter-quartiles, and bars = maximum and minimum values. Different letters indicate significant differences by multiple comparison using ANOVA (p<0.001). B) Correlation between age of lake and food-chain length. Different symbols are for reservoir, glacial and ancient lakes (see A). Lake Victoria and Lake Kyoga are originally from 400,000 years ago, but are thought to have dried up 14,600 years ago.
Materials and Methods
We searched for stable isotope datasets from published papers using ISI Web of Science and Google Scholar. We used “isotope”, “lake” and lake and reservoir names such as "Baikal" as keywords. Lakes and reservoirs were selected using the published literature  and the World Lake Database, which includes the large lakes of the world (http://www.ilec.or.jp/database/database.html, and LakeNet; http://www.worldlakes.org/searchlakes.asp). We selected papers that report nitrogen stable isotope values of top predator fishes (seal in Lake Baikal) and invertebrate primary consumers such as zooplankton, mussels, and aquatic benthic invertebrates. We found suitable nitrogen isotope data for 21 large lakes and reservoirs from 23 published and unpublished papers. A list of lakes and reservoirs included in this analysis, and the relevant lake attribute data and literature references are in Table 1. A strong relationship between FCL and ecosystem size has been found among temperate lakes . To avoid confounding effects of ecosystem size, we only included recent lakes and reservoirs larger than 3.2 km3, which was the volume of the smallest ancient lake included in the present study (Table 1).
Estimation of FCL
FCL for a given lake is defined as the trophic position of the fish species with the highest mean δ15N value. We assumed a trophic fractionation of 3.4‰ to calculate FCL as in previous studies , . For each food web, we estimated FCL using stable nitrogen isotope as follows , :where the mean δ15N of invertebrate primary consumers (zooplankton, mollusks, and other benthic invertebrates) were used as the isotopic baseline. As in , we used stable isotope information from all primary consumers from both pelagic and benthic habitats for the δ15Nbaseline. The observed variation in δ15Nbaseline did not significantly affect the estimation of FCL in lakes .
We tested for differences among the three lake types using analysis of variance (ANOVA, α = 0.05). We performed the Bonferroni adjustment for multiple comparisons as a post-hoc test in ANOVA among the three lake types (α = 0.05). To compare factors that are correlated with FCL, we used Pearson's correlation coefficients (α = 0.05). We included Lake Kyoga and Victoria as ancient lakes, because the lake basins have a long history (>400,000 years) and many endemic species, although they are suspected to have dried up 14,600 years ago . All statistical tests and graphics were performed by R ver. 2.13.0 software .
We found that FCL in ancient lakes was significantly shorter than glacial lakes and reservoirs (ANOVA, p<0.001, multiple comparison, p<0.001, Fig. 1A). The shortest food chains were consistently in the oldest lakes (Fig. 1B). FCL of reservoirs tended to be shorter than that of glacial lakes, although the difference was not significant (Fig. 1A). FCL was not correlated with lake area, lake volume, or mean depth (Pearson's correlation coefficient, |r| <0.35, p>0.16, Fig. 2), but increased with latitude, as many ancient lakes are tropical (r = 0.60, p<0.05, Fig. 2). There was a strong positive relationship between lake age and number of endemic species (r = 0.81, p<0.001).
Lake Victoria and Lake Kyoga are located in ancient lake basins, but are suspected to have dried up 14,600 years ago (Table 1), though notably they have approximately 700 and 100 endemic Cichlid fish species, respectively. Five of the eight ancient lakes contain an endemic top predator (Table 1). Despite the fact that the long evolutionary history has led to the evolution of new and endemic top predators in many of these lakes, FCL in ancient lakes is still short relative to lakes of more modern origin.
We found that FCL in ancient lakes was significantly shorter than glacial lakes and reserviors, even though these ancient lakes tend to have much higher fish species richness and endemism than their more recent counterparts. Though we cannot resolve the causal mechanism as to why ancient lakes have shorter food chains, there are several potential ways in which this could occur. For example, speciation could simply broaden the number of species within a trophic group, particularly at lower trophic levels. Additional species richness does not necessarily lead to longer food chains. Furthermore, speciation could lead to a greater degree of trophic omnivory, such that FCL would naturally decline with increasing species richness. Longer time for speciation in ancient lakes may increase the number of trophic omnivores and trophic specialists relative to recent lakes. A theoretical study by Loeuille and Loreau  predicted that long evolutionary history would tend to decrease FCL when competition intensity is low. A high diversity of ecological specialists might decrease competition intensity, and consequently FCL of the system . The other hypothesis to explain shorter FCL in ancient lakes is that speciation simply leads to more herbivores in the ecosystem . In fact, African ancient lakes tend to have many herbivorous cichlid species. This is the case even in Lake Victoria and Kyoga, which are thought to have dried up 14,600 years ago –. Similarly, Lake Baikal has many species of zooplankton-feeding pelagic sculpins (e.g., Cottocomephorus inermis and grewingki) which evolved from benthic invertebrate-feeding sculpins . To mechanistically test the above hypotheses, a potential approach could involve rapid diversification in experimental systems, e.g. involving bacteria and microbial food webs.
Cohen and Newman’s cascade model  predicts that increasing species richness would tend to increase FCL by increasing the total number of both nodes and links, and thus the mean path length leading to the top predator. In fact, most of the ancient lakes have high species richness and many endemic species, including endemic top predators. However, higher species richness does not correspond with elevated FCL. The dynamic constraints hypothesis predicts that more frequent or more intense disturbance would tend to shorten FCL based on simple theoretical models suggest that longer chains are less resilient, and thus unlikely to persist in the face of disturbance . If ancient lakes have been more frequently disturbed relative to recent lakes, this could result in shorter food chains. Though ancient lakes have been around longer, the ecosystems tend to be large, deep and located in the tropics. Such factors may mediate or buffer the effects of disturbance on these lakes. A number of food web studies in both the laboratory and field did not find an effect of disturbance on FCL –, possibly suggesting a limited role for disturbance history in affecting FCL.
Though it is perhaps impossible to measure the FCL of a single lake over a long time period, our comparative results suggest that lake food chains lengthen over time periods of hundreds to thousands of years as a stable biological community assembles. In contrast, over time periods of thousands to millions of years, food chains actually become shorter as species diversity rises and endemic species emerge. Because our findings are observational and comparative in nature, we ultimately cannot infer mechanisms that underlie this pattern. Nevertheless, the relationship between FCL and ecosystem age is striking. Our study is a first step towards understanding the role of historical and evolutionary factors in determining fundamental food web properties such as FCL.
We sincerely thank M. Kondoh, G. Takimoto, and K. Yoshida for their comments on the early draft of the manuscript.
Conceived and designed the experiments: HD MJV HH. Performed the experiments: HD MJV HH. Analyzed the data: HD. Wrote the paper: HD MJV HH.
- 1. Elton C (1927) Animal Ecology, Sidgwick and Jackson, London, UK. C. Elton1927Animal Ecology, Sidgwick and Jackson, London, UK
- 2. Pimm SL (1982) Food Web, Chapman and Hall, London, UK. SL Pimm1982Food Web, Chapman and Hall, London, UK
- 3. Post DM, Pace ML, Hairston NG (2000) Ecosystem size determines food-chain length in lakes. Nature 405: 1047–1049.DM PostML PaceNG Hairston2000Ecosystem size determines food-chain length in lakes.Nature40510471049
- 4. Schoener TW (1989) Food webs from the small to the large. Ecology 70: 1559–1589.TW Schoener1989Food webs from the small to the large.Ecology7015591589
- 5. Pimm SL, Lawton JH (1977) The number of trophic levels in ecological communities. Nature 275: 542–544.SL PimmJH Lawton1977The number of trophic levels in ecological communities.Nature275542544
- 6. Jenkins B, Kitching RL, Pimm SL (1992) Productivity, disturbance and food web structure at a local spatial scale in experimental container habitats. Oikos 65: 249–255.B. JenkinsRL KitchingSL Pimm1992Productivity, disturbance and food web structure at a local spatial scale in experimental container habitats.Oikos65249255
- 7. Lennon JT, Martiny JBH (2008) Rapid evolution buffers ecosystem impacts of viruses in a microbial food web. Ecol Let 11: 1178–1188.JT LennonJBH Martiny2008Rapid evolution buffers ecosystem impacts of viruses in a microbial food web.Ecol Let1111781188
- 8. Fukami T, Morin PJ (2003) Productivity-biodiversity relationships depend on the history of community assembly. Nature 424: 423–426.T. FukamiPJ Morin2003Productivity-biodiversity relationships depend on the history of community assembly.Nature424423426
- 9. Loeuille N, Loreau M (2005) Evolutionary emergence of size-structured food webs Proc Natl Acad Sci USA 102: 5761–5766.N. LoeuilleM. Loreau2005Evolutionary emergence of size-structured food webs Proc Natl Acad Sci USA10257615766
- 10. Vander Zanden MJ, Lester NP, Shuter BJ, Rasmussen JB (1999) Patterns of food chain length in lakes: a stable isotope study. Ame Nat 154: 406–416.MJ Vander ZandenNP LesterBJ ShuterJB Rasmussen1999Patterns of food chain length in lakes: a stable isotope study.Ame Nat154406416
- 11. Vander Zanden MJ, Fetzer WW (2007) Global patterns of aquatic food chain length. Oikos 116: 1378–1388.MJ Vander ZandenWW Fetzer2007Global patterns of aquatic food chain length.Oikos11613781388
- 12. Doi H, Chang KH, Ando T, Imai H, Ninomiya I, et al. (2009) Resource availability and ecosystem size predict food-chain lengths in pond ecosystems. Oikos 118: 138–144.H. DoiKH ChangT. AndoH. ImaiI. Ninomiya2009Resource availability and ecosystem size predict food-chain lengths in pond ecosystems.Oikos118138144
- 13. Thompson RM, Townsend CR (2005) Energy availability, spatial heterogeneity and ecosystem size predict food-web structure in streams. Oikos 108: 137–148.RM ThompsonCR Townsend2005Energy availability, spatial heterogeneity and ecosystem size predict food-web structure in streams.Oikos108137148
- 14. May RM (2001) Stability and complexity in model ecosystems. Princeton University Press, Princeton, USA. RM May2001Stability and complexity in model ecosystems.Princeton University Press, Princeton, USA
- 15. Fordyce RE, Barnes LG (1994) The evolutionary history of whales and dolphins. Ann Rev Earth Planet Sci 22: 419–455.RE FordyceLG Barnes1994The evolutionary history of whales and dolphins.Ann Rev Earth Planet Sci22419455
- 16. Post DM, Takimoto G (2007) Proximate structural mechanisms for variation in food-chain length. Oikos. 116: 775–782.DM PostG. Takimoto2007Proximate structural mechanisms for variation in food-chain length. Oikos.116775782
- 17. Chao BF, Wu YH, Li YS (2008) Impact of artificial reservoir water impoundment on global sea level. Science. 320: 212–214.BF ChaoYH WuYS Li2008Impact of artificial reservoir water impoundment on global sea level. Science.320212214
- 18. Johnson TC, Scholz CA, Talbot MR, Kelts K, Ricketts RD, et al. (1996) Late pleistocene desiccation of Lake Victoria and rapid evolution of cichlid fishes. Science 273: 1091–1093.TC JohnsonCA ScholzMR TalbotK. KeltsRD Ricketts1996Late pleistocene desiccation of Lake Victoria and rapid evolution of cichlid fishes.Science27310911093
- 19. R Development Core Team (2011) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. R Development Core Team2011R: A language and environment for statistical computing.R Foundation for Statistical Computing, Vienna, Austria
- 20. Albertson RC, Koche TD (2006) Genetic and developmental basis of cichlid trophic diversity. Heredity 97: 211–221.RC AlbertsonTD Koche2006Genetic and developmental basis of cichlid trophic diversity.Heredity97211221
- 21. Campbell LM, Wandera SB, Thacker RJ, Dixon DG, Hecky RE (2005) Trophic niche segregation in the Nilotic ichthyofauna of Lake Albert (Uganda, Africa) Environ Biol Fish 74: 247–260.LM CampbellSB WanderaRJ ThackerDG DixonRE Hecky2005Trophic niche segregation in the Nilotic ichthyofauna of Lake Albert (Uganda, Africa) Environ Biol Fish74247260
- 22. Hunt DM, Fitzgibbon J, Slobodyanyuk SJ, Bowmaker JK, Dulai KS (1997) Molecular evolution of the cottoid fish endemic to Lake Baikal deduced from nulear DNA evidence. Mol Phylogenet Evol 8: 415–422.DM HuntJ. FitzgibbonSJ SlobodyanyukJK BowmakerKS Dulai1997Molecular evolution of the cottoid fish endemic to Lake Baikal deduced from nulear DNA evidence.Mol Phylogenet Evol8415422
- 23. Cohen JE, Newman CM (1992) Community area and food-chain length: theoretical predictions. Am Nat 138: 1542–1554.JE CohenCM Newman1992Community area and food-chain length: theoretical predictions.Am Nat13815421554
- 24. Jenkins B, Kitching RL, Pimm SL (1992) Productivity, disturbance and food web structure at a local spatial scale in experimental container habitats. Oikos 65: 249–255.B. JenkinsRL KitchingSL Pimm1992Productivity, disturbance and food web structure at a local spatial scale in experimental container habitats.Oikos65249255
- 25. Takimoto G, Spiller DA, Post DM (2008) Ecosystem size, but not disturbance, determines food-chain length on islands in the Bahamas. Ecology 89: 3001–3007.G. TakimotoDA SpillerDM Post2008Ecosystem size, but not disturbance, determines food-chain length on islands in the Bahamas.Ecology8930013007
- 26. Campbell LM, Wandera SB, Thacker RJ, Dixon DG, Hecky RE (2005) Trophic niche segregation in the Nilotic ichthyofauna of Lake Albert (Uganda, Africa) Environ Biol Fish 74: 247–260.LM CampbellSB WanderaRJ ThackerDG DixonRE Hecky2005Trophic niche segregation in the Nilotic ichthyofauna of Lake Albert (Uganda, Africa) Environ Biol Fish74247260
- 27. Yoshii K, Melnik NG, Timoshkin OA, Bondarenko NA, Anoshko PN, et al. (1999) Stable isotope analyses of the pelagic food web in Lake Baikal. Limnol Oceanogr 44: 502–511.K. YoshiiNG MelnikOA TimoshkinNA BondarenkoPN Anoshko1999Stable isotope analyses of the pelagic food web in Lake Baikal.Limnol Oceanogr44502511
- 28. Yoshii K (1999) Stable isotope analyses of benthic organisms in Lake Baikal 29. Hydrobiologia 411: 145–159.K. Yoshii1999Stable isotope analyses of benthic organisms in Lake Baikal 29.Hydrobiologia411145159
- 29. Takai N, Sakamoto W (1999) Identification of local populations of Lake Biwa catfish Silurus biwaensis in Japan on the basis of δ13C and δ15N analyses. Can J Zool 77: 258–266.N. TakaiW. Sakamoto1999Identification of local populations of Lake Biwa catfish Silurus biwaensis in Japan on the basis of δ13C and δ15N analyses.Can J Zool77258266
- 30. Hecky RE, Hesslein RH (1995) Contributions of benthic algae to lake food webs as revealed by stable isotope analysis. J N Am Benthol Soc 14: 631–653.RE HeckyRH Hesslein1995Contributions of benthic algae to lake food webs as revealed by stable isotope analysis.J N Am Benthol Soc14631653
- 31. Kidd KA, Bootsma HA, Hecky RE, Hesslein RH (2003) Mercury Concentrations in the Food Web of Lake Malawi, East Africa. J Great Lakes Res 29: 258–266.KA KiddHA BootsmaRE HeckyRH Hesslein2003Mercury Concentrations in the Food Web of Lake Malawi, East Africa.J Great Lakes Res29258266
- 32. Vander Zanden MJ, Chandra S, Allen BC, Reuter JE, Goldman CR (2003) Historical food web structure and restoration of native aquatic communities in the Lake Tahoe (California–Nevada) Basin. Ecosystems 6: 274–288.MJ Vander ZandenS. ChandraBC AllenJE ReuterCR Goldman2003Historical food web structure and restoration of native aquatic communities in the Lake Tahoe (California–Nevada) Basin.Ecosystems6274288
- 33. Campbell LM, Verburg P, Dixon DG, Hecky RE (2008) Mercury biomagnification in the food web of Lake Tanganyika (Tanzania, East Africa). Sci Total Environ 402: 184–191.LM CampbellP. VerburgDG DixonRE Hecky2008Mercury biomagnification in the food web of Lake Tanganyika (Tanzania, East Africa).Sci Total Environ402184191
- 34. Campbell LM, Hecky RE, Wandera SB (2003) Stable isotope analyses of food web structure and fish diet in Napoleon and Winam Gulfs, Lake Victoria, East Africa. J Great Lakes Res 29: 243–257.LM CampbellRE HeckySB Wandera2003Stable isotope analyses of food web structure and fish diet in Napoleon and Winam Gulfs, Lake Victoria, East Africa.J Great Lakes Res29243257
- 35. Kikuchi E, Doi H, Shikano S, Yurlova N, Yadrenkina E, et al. (2004) Preliminary studies on carbon and nitrogen stable isotope ratios analysis of food web in Lake Chany of Western Siberia. Research Report of the Research and Education Center for Inlandwater Environment Shinshu University 2: 21–244.E. KikuchiH. DoiS. ShikanoN. YurlovaE. Yadrenkina2004Preliminary studies on carbon and nitrogen stable isotope ratios analysis of food web in Lake Chany of Western Siberia.Research Report of the Research and Education Center for Inlandwater Environment Shinshu University221244
- 36. Doi H, Kikuchi E, Mizota C, Satoh N, Shikano S, et al. (2004) Carbon, nitrogen, and sulfur isotope changes and hydro-geological processes in a saline lake chain. Hydrobiologia 529: 225–235.H. DoiE. KikuchiC. MizotaN. SatohS. Shikano2004Carbon, nitrogen, and sulfur isotope changes and hydro-geological processes in a saline lake chain.Hydrobiologia529225235
- 37. Power M, O’Connell MF, Dempson JB (2005) Ecological segregation within and among Arctic char morphotypes in Gander Lake, Newfoundland. Environ Biol Fish 73: 263–274.M. PowerMF O’ConnellJB Dempson2005Ecological segregation within and among Arctic char morphotypes in Gander Lake, Newfoundland.Environ Biol Fish73263274
- 38. Zimmerman MS, Schmidt SN, Krueger CC, Vander Zanden MJ, Eshenroder RL (2009) Ontogenetic niche shifts and resource partitioning of lake trout morphotypes Can J Aquat Fish Sci 66: 1007–1018.MS ZimmermanSN SchmidtCC KruegerMJ Vander ZandenRL Eshenroder2009Ontogenetic niche shifts and resource partitioning of lake trout morphotypes Can J Aquat Fish Sci6610071018
- 39. Stapleton HM, Letcher RJ, Baker JE (2001) Accumulation of atmospheric and sedimentary PCBs and toxaphene in a Lake Michigan food web. Environ Sci Technol 35: 3287–3293.HM StapletonRJ LetcherJE Baker2001Accumulation of atmospheric and sedimentary PCBs and toxaphene in a Lake Michigan food web.Environ Sci Technol3532873293
- 40. Clarke LR, Vidergar DT, Bennettm DH (2005) Stable isotopes and gut content show diet overlap among native and introduced piscivores in a large oligotrophic lake. Ecol Freshw Fish 14: 267–277.LR ClarkeDT VidergarDH Bennettm2005Stable isotopes and gut content show diet overlap among native and introduced piscivores in a large oligotrophic lake.Ecol Freshw Fish14267277
- 41. Keough JR, Sierszen ME, Hagley CA (1996) Analysis of a Lake Superior coastal food web with stable isotope techniques. Limnol Oceanogr 41: 136–146.JR KeoughME SierszenCA Hagley1996Analysis of a Lake Superior coastal food web with stable isotope techniques.Limnol Oceanogr41136146
- 42. Gewurtz SB, Gandhi N, Stern GA, Franzin WG, Rosenberg B, et al. (2006) Dynamics of PCBs in the Food Web of Lake Winnipeg. J Great Lakes Res 32: 712–727.SB GewurtzN. GandhiGA SternWG FranzinB. Rosenberg2006Dynamics of PCBs in the Food Web of Lake Winnipeg.J Great Lakes Res32712727
- 43. Iacumin P, Bocherens H, Chaix L, Marioth A (1998) Stable carbon and nitrogen isotopes as dietary indicators of ancient nubian populations (Northern Sudan) J Archaeol Sci 25: 293–301.P. IacuminH. BocherensL. ChaixA. Marioth1998Stable carbon and nitrogen isotopes as dietary indicators of ancient nubian populations (Northern Sudan) J Archaeol Sci25293301
- 44. Black AR, Barlow GW, Scholz AT (2003) Carbon and nitrogen stable isotope assessment of the Lake Roosevelt aquatic food web. Northwest Sci 77: 1–11.AR BlackGW BarlowAT Scholz2003Carbon and nitrogen stable isotope assessment of the Lake Roosevelt aquatic food web.Northwest Sci77111
- 45. Saito L, Johnson BM, Bartholow J, Hanna RB (2001) Assessing ecosystem effects of reservoir operations using food web-energy transfer and water quality models. Ecosystems 4: 105–125.L. SaitoBM JohnsonJ. BartholowRB Hanna2001Assessing ecosystem effects of reservoir operations using food web-energy transfer and water quality models.Ecosystems4105125