Ecological Archives E096-183-A1
Jeffrey P. Stephens, Keith A. Berven, Scott D. Tiegs, and Thomas R. Raffel. 2015. Ecological stoichiometry quantitatively predicts responses of tadpoles to a food quality gradient. Ecology 96:2070–2076. http://dx.doi.org/10.1890/14-2439.1
Appendix A. Supplementary discussion of ecological stoichiometry and the “minimal model”, tadpole trophic ecology and resource use, alternative explanations for toad results, and dissolved polyphenolic effects on tadpoles.
Ecological stoichiometry and consumer growth
Ecological stoichiometry (ES) provides a powerful tool for understanding how imbalances in nutrients between consumers and their food influence growth (Stelzer and Lamberti 2002, Sterner and Elser 2002, Elser and Hamilton 2007, Sardans et al. 2012, Hessen et al. 2013, Penczykowski et al. 2014, Fuller et al. 2014, Prado et al. 2014, Tao et al. 2014). Studies of invertebrate stoichiometry have shown that ES theory can explain relative stoichiometric ratios in consumer body tissues based on their taxon, feeding strategy, or trophic position (Cross et al. 2003, Liess and Hillebrand 2005, Evans-White et al. 2005, Lauridsen et al. 2012), and that these stoichiometric ratios can influence community- and ecosystem-level characteristics like rates of carbon and nutrient cycling (Frost et al. 2006, Liess 2014). For vertebrates including tadpoles, prior studies have tested the qualitative prediction of ES theory that consumer growth should be faster when fed a high-quality diet, i.e., with lower C:N or C:P ratios (Kupferberg 1997, Maerz et al. 2010, Venesky et al. 2012, Liess et al. 2013, Stephens et al. 2013, Benstead et al. 2014). However, to our knowledge no prior study has generated quantitative predictions for vertebrate growth rates based purely on stoichiometric ratios of consumers and their food, possibly because there have been relatively few studies to even measure stoichiometric ratios in vertebrate body tissues (Sterner and George 2000, Vanni 2002, Vanni et al. 2002, McIntyre et al. 2008, Capps et al. 2014, Sterrett et al. 2014). In this study, we take these findings a step further by using ES theory to generate quantitative predictions of tadpole growth.
The “minimal model” created by Sterner and Elser (2002) integrates consumer stoichiometry and ecology, and allows us to make quantitative predictions about how the consumer will respond in terms of excretion, growth efficiency, and growth rates across a limiting nutrient gradient. This model allows calculation of threshold elemental ratios (TER) for consumers, which indicates the precise resource nutrient ratio where the organism shifts from carbon limited to nutrient limited (Frost et al. 2006). Some of the classic work on ES theory focused on predicting differences in TER of C:P among aquatic consumer taxa and feeding strategies, showing that maximum growth rates were negatively correlated with the TER of C:P across 41 aquatic consumer taxa (Frost et al. 2006). Other studies have used mass-balance models (similar to the minimal model) to a priori calculate growth efficiencies and excretion rates of consumers (Mather et al. 1995, Sterner and Elser 2002, Anderson et al. 2005).
ES model assumptions
Like any reductionist model, the ES minimal model includes simplifying assumptions (Allen and Gillooly 2009). For example, the minimal model ignores temperature, which we know influences growth rates via its effects on metabolism (Berven 1982, Ratkowsky et al. 1982, Brown et al. 2004, Clarke 2006). The minimal model also assumes that the consumer is limited by one nutrient at a time, and that the C:nutrient ratio represents an organism’s overall energy:nutrient ratio despite evidence that energy and nutrients are divided between metabolic and structural compartments (Allen and Gillooly 2009). Also, this model assumes that the consumer is not limited by the total biomass of food available, as is the case for many primary consumers and detritivores. However, plant structural and secondary compounds contained within plant tissue and detritus [such as lignin, cellulose and phenolic acids (Campbell and Fuchshuber 1995, Graça et al. 2005, Ferreira et al. 2010)] could lead to food quantity or C limitation for some consumers (Hessen et al. 2004). Combining ES theory with predictions of temperature-dependent growth or development from metabolic theory might be a fruitful area of future research as suggested by Allen and Gillooly (2009).
Another important simplifying assumption of the ES minimal model is that it ignores the potential for consumers to compensate for low resource quality via phenotypic plasticity. Tadpoles are known to have a variety of plastic responses to environmental variation, including alterations in morphology and behavior in response to low food quantity and quality (Pfennig 1992, Stoler and Relyea 2013a, Jefferson et al. 2014b, Jefferson et al. 2014a). Based on these previous studies, it is possible that wood frogs in our low-quality litter treatments compensated by developing longer GI tracts, thereby increasing their assimilation efficiencies (Stoler and Relyea 2013a). Alternatively, tadpoles in the low-quality treatments might have compensated by increasing their consumption rates [i.e., use compensatory feeding (Liess 2014)]. Wood frogs have also been known to switch to consumption of animal protein (e.g., dead conspecifics or invertebrates) to compensate for low food quality (Schiesari et al. 2009, Jefferson et al. 2014b). However, in this study, we restricted our mesocosms from being colonized by invertebrates. Thus in this experiment there should have been few sources of animal protein for tadpoles to consume, making it unlikely that tadpoles could have compensated for low litter quality using this strategy. Furthermore, the ES minimal model provided good predictions of wood frog growth rates in our study despite ignoring plastic responses, suggesting that phenotypic plasticity played a relatively minor role in mediating resource quality effects in this experiment.
Leaf-litter quality (C:nutrient ratios) and tadpole performance
Previous studies have shown that amphibian larval performance can be affected by the abundance and species identity of leaf litter resources, and that different tadpole species respond differently to litter abundance and quality (Rubbo and Kiesecker 2004, Brown et al. 2006, Stoler and Relyea 2011, Earl et al. 2011, Cohen et al. 2012a, Earl et al. 2012, Earl and Semlitsch 2012). Litter species with more nitrogen (N) have been shown to increase rates of growth, development, and survival of wood frogs Lithobates sylvaticus, pickerel frogs Rana palustris, American toads Bufo americanus, spring peepers Hyla crucifer, and green frogs Rana clamitans (Maerz et al. 2010, Cohen et al. 2012b, Stephens et al. 2013, Stoler and Relyea 2013a, Cohen et al. 2014, Earl et al. 2014, Martin et al. 2015). Together, these studies suggest that larval amphibian growth rates are frequently N-limited. Phosphorus is also known to limit aquatic consumer growth (Sterner and Elser 2002), but fewer studies have explored the relationship between tadpole growth and the P content of litter, and litter N was a better predictor of tadpole performance in prior studies (Cohen et al. 2012b, Stephens et al. 2013). However, P might also be important to tadpole development during periods of bone ossification (Capps et al. 2014). The extent of N and P co-limitation for larval amphibians is an important outstanding question that could be addressed by independently manipulating the N and P content of their food.
It is clear that wood frog tadpoles consume leaf-litter detritus, as evident from the gut content analysis in our study and results from previous field and mesocosm studies (Schiesari 2004, Schiesari et al. 2009, Schriever and Williams 2013, Stephens et al. 2013). We have also visually witnessed wood frog tadpoles eating unconditioned leaf litter in the lab (Stephens, personal observation). However, an important outstanding question is what fraction of nutrients and carbon assimilated by these tadpoles came from the litter tissue itself, relative to nutrients and carbon derived from litter-associated microbes. These biofilms contain an assortment of fungi, bacteria, and algae, and their quantity and quality can co-vary with litter nutrient quality (Tuchman et al. 2002, Das et al. 2007, Danger et al. 2013). Based on stable isotope analysis of 44 tadpoles, Schriver et al. (2013) concluded that wood frog biomass was mostly derived directly from litter detritus and aquatic plants. However, Schiesari et al. (2009) concluded that wood frog tadpole biomass in closed canopy ponds was supported in part by microbes, based on stable isotope analysis of 8 tadpoles. Our study contributes to the literature on this topic by providing an additional line of evidence that litter-consuming tadpoles likely derive at least some of their nutrients directly from litter. We parameterized our predictive model based on the stoichiometric ratios of tadpoles and their litter resource, making the implicit assumption that the litter itself was the primary source of nutrients. If this assumption had been wrong, and most of their nutrients actually came from litter-associated microbes, it is unlikely that the model would have generated such accurate predictions.
The forest canopy and tadpole trophic ecology
In freshwater systems, gradients in forest canopy cover explain much of the variation in the composition of amphibian and invertebrate communities (Werner and Glennemeier 1999, Skelly et al. 2005). For example some species of amphibian, such as wood frogs and salamanders (e.g., Ambyostoma maculatum) often deposit eggs in closed canopy ponds [i.e., those with abundant overhanging trees (Petranka 1998, Skelly et al. 2002)], whereas other species, such as leopard frogs (Rana pipiens) and American toads (Anaxyrus americanus), typically avoid areas of high canopy cover (Werner and Glennemeier 1999).
Observed differences in amphibian usage between open and closed canopy ponds might be driven by interspecific differences in the ability to utilize the resources available in each habitat type (Williams et al. 2008). Contrary to past assertions that most tadpole species have generalist trophic morphologies and diverse diets (Altig 1999), different tadpole species often have very different mouthpart and digestive morphologies, foraging behaviors, and food preferences (Altig 1999, Schiesari 2006, Altig et al. 2007, Schiesari et al. 2009, Schriever and Williams 2013).
The results of our study and others (Schiesari 2004, Schiesari 2006) provide evidence that wood frogs might be specially adapted to closed canopy ponds and the relatively low quality resources they contain. Wood frogs respond strongly to variation in litter quality and perform better than other amphibian species in closed-canopy conditions (Werner and Glennemeier 1999, Maerz et al. 2010, Stephens et al. 2013, Stoler and Relyea 2013a). Wood frog tadpoles also appear to be better at selectively foraging for higher-quality etritus, at least relative to leopard frog tadpoles (Schiesari et al. 2006), and they possess two more tooth rows and higher assimilation efficiencies than leopard frogs (Altig 1970, Schiesari 2004).
Conversely, species that breed in the warmer summer months like green frogs and bull frogs Rana catesbeiana tend to breed in permanent open canopy ponds dominated by primary producers (Werner and Glennemeier 1999, Schiesari 2004). American toads represent a species intermediate between spring and summer breeders. Toads are primarily restricted to open canopy ponds (like summer breeders), but can also use ephemeral ponds (Werner and Glennemeier 1999, Skelly et al. 2002, Skelly et al. 2005, Werner et al. 2007)). The preference of toads for open canopy ponds is suggested by our study and others showing that toads perform better under open canopy conditions with abundant primary producers (Werner and Glennemeier 1999).
American toad alternative hypotheses
The lack of evidence for a direct effect of leaf litter on toad tadpoles in the high light treatment most likely indicates American toads rely on algae for growth instead of litter, and the fact that toad growth was generally slower than predicted by the ES minimal model suggests that toads were limited by resource quantity rather than quality. These findings are consistent with previous transplant studies showing higher performance of American toad tadpoles in open- than in closed-canopy ponds (Werner and Glennemeier 1999). However, alternative mechanisms could also have influenced toad performance in our experiment. For example, the poorer performance of toads in the low light or low N mesocosms might also have been in response to presumably lower levels of dissolved oxygen in mesocosms with less algae. American toad tadpoles develop lungs late in larval development relative to wood frogs, making them unable to gulp air when dissolved oxygen is low (Wassersug and Seibert 1975, Feder 1984). Toad species also undergo very rapid development relative to other anurans (Richter-Boix et al. 2006) which can trade off with growth (Skelly 1997), such that variation in American toad size at metamorphosis might be constrained by their need to develop rapidly. However, data from an outlier mesocosm that experienced a bloom of filamentous algae seems to contradict this interpretation, as toads metamorphosed in a similar amount of time relative to other mesocosms from the same treatment, but at a much larger size. Interestingly, these toads grew at almost precisely the rate predicted by the ES minimal model, as one might expect if algal abundance was no longer the limiting factor in this replicate.
Effects of plant secondary compounds (i.e., phenolics) on tadpoles
In addition to nutrients, leaf litter contains secondary compounds that can influence larval amphibian performance (i.e., growth, development, survival), with effects depending on the species of source plant, the dissolved concentration, and amphibian investigated (Maerz et al. 2005, Earl et al. 2012, Martin and Blossey 2013, Stephens et al. 2013, Stoler and Relyea 2013b, Earl and Semlitsch 2015). An abundant type of secondary compound are polyphenolics, which includes a variety of chemicals including tannins, saponins, and lignin, an important structural chemical in plant cell walls. Previous studies have found negative effects of polyphenolic compounds on larval amphibian growth, development, and survival (Maerz et al. 2005, Brown et al. 2006, Stephens et al. 2013, Earl et al. 2012). However, other studies have found no effects of polyphenolics on survival and development (Maerz et al. 2005, Earl and Semlitsch 2015) or weak positive effects on larval growth (Martin and Blossey 2013, Earl and Semlitsch 2015). In the present study, the path analysis detected negative direct effects of polyphenolics concentration on growth of both tadpole species in the high-light treatment, but there was no apparent effect of phenolics in the low-light treatment. Thus, the observation by Stephens et al. (2013) that polyphenolics did not alter wood frog growth missed an element of complexity, as all of their mesocosms had lids similar to the high-light treatments in this study. One possible explanation of this context dependency is that high intensity light degrades the polyphenolics over time, reducing direct toxicity (Scully et al. 2004). However, polyphenolics indirectly influenced growth at high light for American toads via negative effects on algal production (i.e., chl. a). Previous studies have shown that leaf-derived polyphenolics can limit periphyton growth (Stephens et al. 2013); however, the mechanism remains uncertain. Polyphenolics might be directly toxic to the algae, fungi, and/or bacteria that comprise periphyton (Herrera-Silveira and Ramirez-Ramirez 1996, Ervin and Wetzel 2003, Maerz et al. 2005). Our path analysis indicated that litter-derived phenolics had stronger effects on the autotrophic component of biofilm (chl. a) than on the remaining heterotrophic component, at least at high light (Fig. 3). These results suggest that any toxic effects might have been greater for algae than for bacteria and fungi, or perhaps that bacteria and algae each respond differently to different phenolic compounds (Bakowska et al. 2003, Scully et al. 2004). Alternatively, darkening of the water by polyphenolics might have reduced light availability to algae, thereby reducing primary production (Bledsoe et al. 2004).
Allen, A. P., and J. F. Gillooly. 2009. Towards an integration of ecological stoichiometry and the metabolic theory of ecology to better understand nutrient cycling. Ecology Letters 12:369384.
Altig, R. 1999. Tadpoles: the biology of anuran larvae. University of Chicago Press, Chicago, Illinois, USA.
Altig, R. 1970. A key to the tadpoles of the continental United States and Canada. Herpetologica 26:180207.
Altig, R., M. Whiles, and C. Taylor. 2007. What do tadpoles really eat? Assessing the trophic status of an understudied and imperiled group of consumers in freshwater habitats. Freshwater Biology 52:386395.
Anderson, T. R., D. O. Hessen, J. J. Elser, and J. Urabe. 2005. Metabolic stoichiometry and the fate of excess carbon and nutrients in consumers. The American Naturalist 165:115.
Bakowska, A., A. Z. Kucharska, and J. Oszmiański. 2003. The effects of heating, UV irradiation, and storage on stability of the anthocyanin–polyphenol copigment complex. Food Chemistry 81:349355.
Benstead, J. P., J. M. Hood, N. V. Whelan, M. R. Kendrick, D. Nelson, A. F. Hanninen, and L. M. Demi. 2014. Coupling of dietary phosphorus and growth across diverse fish taxa: a meta-analysis of experimental aquaculture studies. Ecology 95:27682777.
Berven, K. A. 1982. The genetic basis of altitudinal variation in the wood frog Rana sylvatica II. An experimental analysis of larval development. Oecologia 52:360369.
Bledsoe, E. L., E. J. Phlips, C. E. Jett, and K. A. Donnelly. 2004. The relationships among phytoplankton biomass, nutrient loading and hydrodynamics in an inner-shelf estuary. Ophelia 58:2947.
Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage, and G. B. West. 2004. Toward a metabolic theory of ecology. Ecology 85:17711789.
Brown, C. J., B. Blossey, J. C. Maerz, and S. J. Joule. 2006. Invasive plant and experimental venue affect tadpole performance. Biological Invasions 8:327338.
Campbell, I. C., and L. Fuchshuber. 1995. Polyphenols, condensed tannins, and processing rates of tropical and temperate leaves in an Australian stream. Journal of the North American Benthological Society 14:174182.
Capps, K. A., K. A. Berven, and S. D. Tiegs. 2014. Modelling nutrient transport and transformation by pool-breeding amphibians in forested landscapes using a 21-year dataset. Freshwater Biology 60:500511.
Clarke, A. 2006. Temperature and the metabolic theory of ecology. Functional Ecology 20:405412.
Cohen, J. S., S. Ng, and B. Blossey. 2012a. Quantity Counts: Amount of Litter Determines Tadpole Performance in Experimental Microcosms. Journal of Herpetology 46:8590.
Cohen, J. S., J. C. Maerz, and B. Blossey. 2012b. Traits, not origin, explain impacts of plants on larval amphibians. Ecological Applications 22:218228.
Cohen, J., S. D. Rainford, and B. Blossey. 2014. Community-weighted mean functional effect traits determine larval amphibian responses to litter mixtures. Oecologia 174:13591366.
Cross, W. F., J. P. Benstead, A. D. Rosemond, and J. Bruce Wallace. 2003. Consumer-resource stoichiometry in detritus-based streams. Ecology Letters 6:721732.
Danger, M., J. Cornut, E. Chauvet, P. Chavez, A. Elger, and A. Lecerf. 2013. Benthic algae stimulate leaf litter decomposition in detritus-based headwater streams: a case of aquatic priming effect? Ecology 94:16041613.
Das, M., T. V. Royer, and L. G. Leff. 2007. Diversity of fungi, bacteria, and actinomycetes on leaves decomposing in a stream. Applied and Environmental Microbiology 73:756767.
Earl, J. E., and R. D. Semlitsch. 2012. Reciprocal subsidies in ponds: does leaf input increase frog biomass export? Oecologia 170:111.
Earl, J. E., K. E. Cohagen, and R. D. Semlitsch. 2012. Effects of leachate from tree leaves and grass litter on tadpoles. Environmental Toxicology and Chemistry 31:15111517.
Earl, J. E., T. M. Luhring, B. K. Williams, and R. D. Semlitsch. 2011. Biomass export of salamanders and anurans from ponds is affected differentially by changes in canopy cover. Freshwater Biology 56:24732482.
Earl, J. E., and R. D. Semlitsch. 2015. Effects of tannin source and concentration from tree leaves on two species of tadpoles. Environmental Toxicology and Chemistry 34:120126.
Earl, J. E., P. O. Castello, K. E. Cohagen, and R. D. Semlitsch. 2014. Effects of subsidy quality on reciprocal subsidies: how leaf litter species changes frog biomass export. Oecologia 175:209218.
Elser, J. J., and A. Hamilton. 2007. Stoichiometry and the new biology: the future is now. PLoS biology 5:e181.
Ervin, G. N., and R. G. Wetzel. 2003. An ecological perspective of allelochemical interference in land–water interface communities. Plant and Soil 256:1328.
Evans-White, M. A., R. S. Stelzer, and G. A. Lamberti. 2005. Taxonomic and regional patterns in benthic macroinvertebrate elemental composition in streams. Freshwater Biology 50:17861799.
Feder, M. E. 1984. Consequences of aerial respiration for amphibian larvae. Pages 7186 In Seymour, R., editor. Respiration and metabolism of embryonic vertebrates, Springer, Netherlands.
Ferreira, V., A. L. Goncalves, D. L. Godbold, and C. Canhoto. 2010. Effect of increased atmospheric CO2 on the performance of an aquatic detritivore through changes in water temperature and litter quality. Global Change Biology 16:32843296.
Frost, P. C., J. P. Benstead, W. F. Cross, H. Hillebrand, J. H. Larson, M. A. Xenopoulos, and T. Yoshida. 2006. Threshold elemental ratios of carbon and phosphorus in aquatic consumers. Ecology Letters 9:774779.
Fuller, C. L., M. A. Evans-White, and S. A. Entrekin. 2014. Growth and stoichiometry of a common aquatic detritivore respond to changes in resource stoichiometry. Oecologia 177:112.
Graça, M. A., F. Bärlocher, and M. O. Gessner. 2005. Methods to study litter decomposition: a practical guide. Springer, Netherlands.
Herrera-Silveira, J. A., and J. Ramirez-Ramirez. 1996. Effects of natural phenolic material (tannin) on phytoplankton growth. Limnology and Oceanography 41:10181023.
Hessen, D. O., G. I. Ågren, T. R. Anderson, J. J. Elser, and P. C. de Ruiter. 2004. Carbon sequestration in ecosystems: the role of stoichiometry. Ecology 85:11791192.
Hessen, D. O., J. J. Elser, R. W. Sterner, and J. Urabe. 2013. Ecological stoichiometry: An elementary approach using basic principles. Limnology and Oceanography 58:22192236.
Jefferson, D. M., K. A. Hobson, and D. P. Chivers. 2014a. Time to feed: how diet, competition, and experience may influence the feeding behaviour and cannibalism of wood frog tadpoles (Lithobates sylvaticus). Curr Zool 60:571580.
Jefferson, D. M., K. A. Hobson, B. S. Demuth, M. C. Ferrari, and D. P. Chivers. 2014b. Frugal cannibals: how consuming conspecific tissues can provide conditional benefits to wood frog tadpoles (Lithobates sylvaticus). Naturwissenschaften 101:291303.
Kupferberg, S. J. 1997. The role of larval diet in anuran metamorphosis. American Zoologist 37:146-159.
Lauridsen, R. B., F. K. Edwards, M. J. Bowes, G. Woodward, A. G. Hildrew, A. T. Ibbotson, and J. I. Jones. 2012. Consumer-resource elemental imbalances in a nutrient-rich stream. Freshwater Science 31:408422.
Liess, A., and H. Hillebrand. 2005. Stoichiometric variation in C: N, C: P, and N: P ratios of littoral benthic invertebrates. Journal of the North American Benthological Society 24:256269.
Liess, A. 2014. Compensatory feeding and low nutrient assimilation efficiencies lead to high nutrient turnover in nitrogen-limited snails. Freshwater Science 33:425434.
Liess, A., O. Rowe, J. Guo, G. Thomsson, and M. I. Lind. 2013. Hot tadpoles from cold environments need more nutrients–life history and stoichiometry reflects latitudinal adaptation. Journal of Animal Ecology 82:13161325.
Maerz, J. C., C. J. Brown, C. T. Chapin, and B. Blossey. 2005. Can secondary compounds of an invasive plant affect larval amphibians? Functional Ecology 19:970975.
Maerz, J. C., J. S. Cohen, and B. Blossey. 2010. Does detritus quality predict the effect of native and non-native plants on the performance of larval amphibians? Freshwater Biology 55:16941704.
Martin, L. J., and B. Blossey. 2013. Intraspecific variation overrides origin effects in impacts of litter-derived secondary compounds on larval amphibians. Oecologia 173:449459.
Martin, L. J., S. Rainford, and B. Blossey. 2015. Effects of plant litter diversity, species, origin and traits on larval toad performance. Oikos in press:.
Mather, M. E., M. J. Vanni, T. E. Wissing, S. A. Davis, and M. H. Schaus. 1995. Regeneration of nitrogen and phosphorus by bluegill and gizzard shad: effect of feeding history. Canadian Journal of Fisheries and Aquatic Sciences 52:23272338.
McIntyre, P. B., A. S. Flecker, M. J. Vanni, J. M. Hood, B. W. Taylor, and S. A. Thomas. 2008. Fish distributions and nutrient cycling in streams: can fish create biogeochemical hotspots. Ecology 89:23352346.
Penczykowski, R. M., B. C. Lemanski, R. D. Sieg, S. R. Hall, J. Housley Ochs, J. Kubanek, and M. A. Duffy. 2014. Poor resource quality lowers transmission potential by changing foraging behaviour. Functional Ecology 28:12451255.
Petranka, J. W. 1998. Salamanders of the United States and Canada. Smithsonian Institution Press, Washington, DC, USA.
Pfennig, D. W. 1992. Proximate and functional causes of polyphenism in an anuran tadpole. Functional Ecology 6:167174.
Prado, P., K. L. Heck Jr, and J. Cebrian. 2014. Moderate stoichiometric homeostasis in the sea urchin Lytechinus variegatus: effects of diet and growth on C: N: P ratios. Marine Biology 161:28692883.
Ratkowsky, D. A., J. Olley, T. A. McMeekin, and A. Ball. 1982. Relationship between temperature and growth rate of bacterial cultures. Journal of Bacteriology 149:15.
Richter-Boix, A., G. A. Llorente, and A. Montori. 2006. A comparative analysis of the adaptive developmental plasticity hypothesis in six Mediterranean anuran species along a pond permanency gradient. Evolutionary Ecology Research 8:11391154.
Rubbo, M. J., and J. M. Kiesecker. 2004. Leaf litter composition and community structure: Translating regional species changes into local dynamics. Ecology 85:25192525.
Sardans, J., A. Rivas-Ubach, and J. Penuelas. 2012. The elemental stoichiometry of aquatic and terrestrial ecosystems and its relationships with organismic lifestyle and ecosystem structure and function: a review and perspectives. Biogeochemistry 111:139.
Schiesari, L. 2006. Pond canopy cover: a resource gradient for anuran larvae. Freshwater Biology 51:412423.
Schiesari, L., E. E. Werner, and G. W. Kling. 2009. Carnivory and resource‐based niche differentiation in anuran larvae: implications for food web and experimental ecology. Freshwater Biology 54:572586.
Schiesari, L. C. 2004. Performance tradeoffs across resource gradients in anuran larvae. University of Michigan., Ann Arbor, Michigan, USA.
Schriever, T., and D. Williams. 2013. Ontogenetic and individual diet variation in amphibian larvae across an environmental gradient. Freshwater Biology 58:223236.
Scully, N. M., N. Maie, S. K. Dailey, J. N. Boyer, R. D. Jones, and R. Jaffé. 2004. Early diagenesis of plant-derived dissolved organic matter along a wetland, mangrove, estuary ecotone. Limnology and Oceanography 49:16671678.
Skelly, D. K. 1997. Tadpole communities: pond permanence and predation are powerful forces shaping the structure of tadpole communities. American Scientist 85:3645.
Skelly, D. K., M. A. Halverson, L. K. Freidenburg, and M. C. Urban. 2005. Canopy closure and amphibian diversity in forested wetlands. Wetlands Ecology and Management 13:261268.
Skelly, D., L. Freidenburg, and J. Kiesecker. 2002. Forest canopy and the performance of larval amphibians. Ecology 83:983992.
Stelzer, R. S., and G. A. Lamberti. 2002. Ecological stoichiometry in running waters: periphyton chemical composition and snail growth. Ecology 83:10391051.
Stephens, J. P., K. A. Berven, and S. D. Tiegs. 2013. Anthropogenic changes to litter input affect the fitness of a larval amphibian. Freshwater Biology 58:16311646.
Sterner, R. W., and J. J. Elser. 2002. Ecological stoichiometry: the biology of elements from molecules to the biosphere. Princeton University Press, New Jersey, USA.
Sterner, R. W., and N. B. George. 2000. Carbon, nitrogen, and phosphorus stoichiometry of cyprinid fishes. Ecology 81:127140.
Sterrett, S. C., J. C. Maerz, and R. A. Katz. 2014. What can turtles teach us about the theory of ecological stoichiometry? Freshwater Biology 60:443455.
Stoler, A. B., and R. A. Relyea. 2011. Living in the litter: the influence of tree leaf litter on wetland communities. Oikos 120:862872.
Stoler, A. B., and R. A. Relyea. 2013a. Leaf litter quality induces morphological and developmental changes in larval amphibians. Ecology 94:15951603.
Stoler, A. B., and R. A. Relyea. 2013b. Bottom-up meets top-down: leaf litter inputs influence predator–prey interactions in wetlands. Oecologia 173:249257.
Tao, L., A. R. Berns, and M. D. Hunter. 2014. Why does a good thing become too much? Interactions between foliar nutrients and toxins determine performance of an insect herbivore. Functional Ecology 28:190196.
Tuchman, N. C., R. G. Wetzel, S. T. Rier, K. A. Wahtera, and J. A. Teeri. 2002. Elevated atmospheric CO2 lowers leaf litter nutritional quality for stream ecosystem food webs. Global Change Biology 8:163170.
Vanni, M. J., A. S. Flecker, J. M. Hood, and J. L. Headworth. 2002. Stoichiometry of nutrient recycling by vertebrates in a tropical stream: linking species identity and ecosystem processes. Ecology Letters 5:285293.
Vanni, M. J. 2002. Nutrient cycling by animals in freshwater ecosystems. Annual Review of Ecology and Systematics 33:341370.
Venesky, M. D., T. E. Wilcoxen, M. A. Rensel, L. Rollins-Smith, J. L. Kerby, and M. J. Parris. 2012. Dietary protein restriction impairs growth, immunity, and disease resistance in southern leopard frog tadpoles. Oecologia 169:2331.
Wassersug, R. J., and E. A. Seibert. 1975. Behavioral responses of amphibian larvae to variation in dissolved oxygen. Copeia 1:86103.
Werner, E. E., and K. S. Glennemeier. 1999. Influence of forest canopy cover on the breeding pond distributions of several amphibian species. Copeia 1:112.
Werner, E. E., D. K. Skelly, R. A. Relyea, and K. L. Yurewicz. 2007. Amphibian species richness across environmental gradients. Oikos 116:16971712.
Williams, B. K., T. A. G. Rittenhouse, and R. D. Semlitsch. 2008. Leaf litter input mediates tadpole performance across forest canopy treatments. Oecologia 155:377384.
[Back to E096-183]