Intraspecific variability modulates interspecific variability in animal organismal stoichiometry.

Interspecific differences in organismal stoichiometry (OS) have been documented in a wide range of animal taxa and are of significant interest for understanding evolutionary patterns in OS. In contrast, intraspecific variation in animal OS has generally been treated as analytical noise or random variation, even though available data suggest intraspecific variability in OS is widespread. Here, we assess how intraspecific variation in OS affects inferences about interspecific OS differences using two co-occurring Neotropical fishes: Poecilia reticulata and Rivulus hartii. A wide range of OS has been observed within both species and has been attributed to environmental differences among stream systems. We assess the contributions of species identity, stream system, and the interactions between stream and species to variability in N:P, C:P, and C:N. Because predation pressure can impact the foraging ecology and life-history traits of fishes, we compare predictors of OS between communities that include predators, and communities where predators are absent. We find that species identity is the strongest predictor of N:P, while stream or the interaction of stream and species contribute more to the overall variation in C:P and C:N. Interspecific differences in N:P, C:P, and C:N are therefore not consistent among streams. The relative contribution of stream or species to OS qualitatively changes between the two predation communities, but these differences do not have appreciable effects in interspecific patterns. We conclude that although species identity is a significant predictor of OS, intraspecific OS is sometimes sufficient to overwhelm or obfuscate interspecific differences in OS

SEED: A framework for integrating ecological stoichiometry and eco‐evolutionary dynamics

Characterising the extent and sources of intraspecific variation and their ecological consequences is a central challenge in the study of eco‐evolutionary dynamics. Ecological stoichiometry, which uses elemental variation of organisms and their environment to understand ecosystem patterns and processes, can be a powerful framework for characterising eco‐evolutionary dynamics. However, the current emphasis on the relative content of elements in the body (i.e. organismal stoichiometry) has constrained its application. Intraspecific variation in the rates at which elements are acquired, assimilated, allocated or lost is often greater than the variation in organismal stoichiometry. There is much to gain from studying these traits together as components of an ‘elemental phenotype’. Furthermore, each of these traits can have distinct ecological effects that are underappreciated in the current literature. We propose a conceptual framework that explores how microevolutionary change in the elemental phenotype occurs, how its components interact with each other and with other traits, and how its changes can affect a wide range of ecological processes. We demonstrate how the framework can be used to generate novel hypotheses and outline pathways for future research that enhance our ability to explain, analyse and predict eco‐evolutionary dynamics

Quantum Genetic Algorithm for Highly Constrained Optimization Problems

Quantum computing appears as an alternative solution for solving computationally intractable problems. This paper presents a new constrained quantum genetic algorithm designed specifically for identifying the extreme value of a highly constrained optimization problem, where the search space size _database is massive and unsorted_ cannot be handled by the currently available classical or quantum processor, called the highly constrained quantum genetic algorithm (HCQGA). To validate the efficiency of the suggested quantum method, maximizing the energy efficiency with respect to the target user bit rate of an uplink multi-cell massive multiple-input and multiple- output (MIMO) system is considered as an application. Simulation results demonstrate that the proposed HCQGA converges rapidly to the optimum solution compared with its classical benchmark

Measurement of geologic nitrogen using mass spectrometry, colorimetry, and a newly adapted fluorometry technique

Long viewed as a mostly noble, atmospheric species, recent work demonstrates that nitrogen in fact cycles throughout the Earth system, including the atmosphere, biosphere, oceans, and solid Earth. Despite this new-found behaviour, more thorough investigation of N in geologic materials is limited due to its low concentration (one to tens of parts per million) and difficulty in analysis. In addition, N can exist in multiple species (NO3−, NH4+, N2, organic N), and determining which species is actually quantified can be difficult. In rocks and minerals, NH4+ is the most stable form of N over geologic timescales. As such, techniques designed to measure NH4+ can be particularly useful.We measured a number of geochemical rock standards using three different techniques: elemental analyzer (EA) mass spectrometry, colorimetry, and fluorometry. The fluorometry approach is a novel adaptation of a technique commonly used in biologic science, applied herein to geologic NH4+. Briefly, NH4+ can be quantified by HF dissolution, neutralization, addition of a fluorescing reagent, and analysis on a standard fluorometer. We reproduce published values for several rock standards (BCR-2, BHVO-2, and G-2), especially if an additional distillation step is performed. While it is difficult to assess the quality of each method, due to lack of international geologic N standards, fluorometry appears better suited to analyzing mineral-bound NH4+ than EA mass spectrometry and is a simpler, quicker alternative to colorimetry.To demonstrate a potential application of fluorometry, we calculated a continental crust N budget based on new measurements. We used glacial tills as a proxy for upper crust and analyzed several poorly constrained rock types (volcanics, mid-crustal xenoliths) to determine that the continental crust contains  ∼  2  ×  1018 kg N. This estimate is consistent with recent budget estimates and shows that fluorometry is appropriate for large-scale questions where high sample throughput is helpful.Lastly, we report the first δ15N values of six rock standards: BCR-2 (1. 05  ±  0. 4 ‰), BHVO-2 (−0. 3  ±  0. 2 ‰), G-2 (1. 23  ±  1. 32 ‰), LKSD-4 (3. 59  ±  0. 1 ‰), Till-4 (6. 33  ±  0. 1 ‰), and SY-4 (2. 13  ±  0. 5 ‰). The need for international geologic N standards is crucial for further investigation of the Earth system N cycle, and we suggest that existing rock standards may be suited to this need

Environmental and Organismal Predictors of Intraspecific Variation in the Stoichiometry of a Neotropical Freshwater Fish

The elemental composition of animals, or their organismal stoichiometry, is thought to constrain their contribution to nutrient recycling, their interactions with other animals, and their demographic rates. Factors that affect organismal stoichiometry are generally poorly understood, but likely reflect elemental investments in morphological features and life history traits, acting in concert with the environmental availability of elements. We assessed the relative contribution of organismal traits and environmental variability to the stoichiometry of an insectivorous Neotropical stream fish, Rivulus hartii. We characterized the influence of body size, life history phenotype, stage of maturity, and environmental variability on organismal stoichiometry in 6 streams that differ in a broad suite of environmental variables. The elemental composition of R. hartii was variable, and overlapped with the wide range of elemental composition documented across freshwater fish taxa. Average %P composition was ∼3.2%(±0.6), average %N∼10.7%(±0.9), and average %C∼41.7%(±3.1). Streams were the strongest predictor of organismal stoichiometry, and explained up to 18% of the overall variance. This effect appeared to be largely explained by variability in quality of basal resources such as epilithon N∶P and benthic organic matter C∶N, along with variability in invertebrate standing stocks, an important food source for R. hartii. Organismal traits were weak predictors of organismal stoichiometry in this species, explaining when combined up to 7% of the overall variance in stoichiometry. Body size was significantly and positively correlated with %P, and negatively with N∶P, and C∶P, and life history phenotype was significantly correlated with %C, %P, C∶P and C∶N. Our study suggests that spatial variability in elemental availability is more strongly correlated with organismal stoichiometry than organismal traits, and suggests that the stoichiometry of carnivores may not be completely buffered from environmental variability. We discuss the relevance of these findings to ecological stoichiometry theory

Nutrient limitation, bioenergetics and stoichiometry: A new model to predict elemental fluxes mediated by fishes

Energy flow and nutrient cycling dictate the functional role of organisms in ecosystems. Fishes are key vectors of carbon (C), nitrogen (N) and phosphorus (P) in aquatic systems, and the quantification of elemental fluxes is often achieved by coupling bioenergetics and stoichiometry. While nutrient limitation has been accounted for in several stoichiometric models, there is no current implementation that permits its incorporation into a bioenergetics approach to predict ingestion rates. This may lead to biased estimates of elemental fluxes.Here, we introduce a theoretical framework that combines stoichiometry and bioenergetics with explicit consideration of elemental limitations. We examine varying elemental limitations across different trophic groups and life stages through a case study of three trophically distinct reef fishes. Further, we empirically validate our model using an independent database of measured excretion rates.Our model adequately predicts elemental fluxes in the examined species and reveals species‐ and size‐specific limitations of C, N and P. In line with theoretical predictions, we demonstrate that the herbivore Zebrasoma scopas is limited by N and P, and all three fish species are limited by P in early life stages. Further, we show that failing to account for nutrient limitation can result in a greater than twofold underestimation of ingestion rates, which leads to severely biased excretion rates.Our model improved predictions of ingestion, excretion and egestion rates across all life stages, especially for fishes with diets low in N and/or P. Due to its broad applicability, its reliance on many parameters that are well‐defined and widely accessible, and its straightforward implementation via the accompanying r‐package fishflux, our model provides a user‐friendly path towards a better understanding of ecosystem‐wide nutrient cycling in the aquatic biome.A free Plain Language Summary can be found within the Supporting Information of this article.A free Plain Language Summary can be found within the Supporting Information of this article.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162691/5/fec13618_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162691/4/fec13618-sup-0002-AppendixS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162691/3/fec13618-sup-0001-Summary.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162691/2/fec13618-sup-0003-AppendixS2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162691/1/fec13618.pd