Recent advances in ecological stoichiometry: insights for population and community ecology

Conventional theories of population and community dynamics are based on a single currency such as number of individuals, biomass, carbon or energy. However, organisms are constructed of multiple elements and often require them (in particular carbon, phosphorus and nitrogen) in different ratios than provided by their resources; this mismatch may constrain the net transfer of energy and elements through trophic levels. Ecological stoichiometry, the study of the balance of elements in ecological processes, offers a framework for exploring ecological effects of such constraints. We review recent theoretical and empirical studies that have considered how stoichiometry may affect population and community dynamics. These studies show that stoichiometric constraints can affect several properties of populations (e.g. stability, oscillations, consumer extinction) and communities (e.g. coexistence of competitors, competitive interactions between different guilds). We highlight gaps in general knowledge and focus on areas of population and community ecology where incorporation of stoichiometric constraints may be particularly fruitful, such as studies of demographic bottlenecks, spatial processes, and multi-species interactions. Finally, we suggest promising directions for new research by recommending potential study systems (terrestrial insects, detritivory-based webs, soil communities) to improve our understanding of populations and communities. Our conclusion is that a better integration of stoichiometric principles and other theoretical approaches in ecology may allow for a richer understanding of both population and community structure and dynamics.     

Towards an integration of ecological stoichiometry and the metabolic theory of ecology to better understand nutrient cycling

Ecologists have long recognized that species are sustained by the flux, storage and turnover of two biological currencies: energy, which fuels biological metabolism and materials (i.e. chemical elements), which are used to construct biomass. Ecological theories often describe the dynamics of populations, communities and ecosystems in terms of either energy (e.g. population-dynamics theory) or materials (e.g. resource-competition theory). These two classes of theory have been formulated using different assumptions, and yield distinct, but often complementary predictions for the same or similar phenomena. For example, the energy-based equation of von Bertalanffy and the nutrient-based equation of Droop both describe growth. Yet, there is relatively little theoretical understanding of how these two distinct classes of theory, and the currencies they use, are interrelated. Here, we begin to address this issue by integrating models and concepts from two rapidly developing theories, the metabolic theory of ecology and ecological stoichiometry theory. We show how combining these theories, using recently published theory and data along with new theoretical formulations, leads to novel predictions on the flux, storage and turnover of energy and materials that apply to animals, plants and unicells. The theory and results presented here highlight the potential for developing a more general ecological theory that explicitly relates the energetics and stoichiometry of individuals, communities and ecosystems to subcellular structures and processes. We conclude by discussing the basic and applied implications of such a theory, and the prospects and challenges for further development.     

Herbivore metabolism and stoichiometry each constrain herbivory at different organizational scales across ecosystems

Plant-herbivore interactions mediate the trophic structure of ecosystems. We use a comprehensive data set extracted from the literature to test the relative explanatory power of two contrasting bodies of ecological theory, the metabolic theory of ecology (MTE) and ecological stoichiometry (ES), for per-capita and population-level rates of herbivory across ecosystems. We found that ambient temperature and herbivore body size (MTE) as well as stoichiometric mismatch (ES) both constrained herbivory, but at different scales of biological organization. Herbivore body size, which varied over 11 orders of magnitude, was the primary factor explaining variation in per-capita rates of herbivory. Stoichiometric mismatch explained more variation in population-level herbivory rates and also in per-capita rates when we examined data from within functionally similar trophic groups (e.g. zooplankton). Thus, predictions from metabolic and stoichiometric theories offer complementary explanations for patterns of herbivory that operate at different scales of biological organization.     

Integrating models with data in ecology and palaeoecology: advances towards a model-data fusion approach

It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process-based ecological models and data in cohesive, systematic ways. Model-data fusion (MDF) is an emerging area of research in ecology and palaeoecology. It provides a new quantitative approach that offers a high level of empirical constraint over model predictions based on observations using inverse modelling and data assimilation (DA) techniques. Increasing demands to integrate model and data methods in the past decade has led to MDF utilization in palaeoecology, ecology and earth system sciences. This paper reviews key features and principles of MDF and highlights different approaches with regards to DA. After providing a critical evaluation of the numerous benefits of MDF and its current applications in palaeoecology (i.e., palaeoclimatic reconstruction, palaeovegetation and palaeocarbon storage) and ecology (i.e. parameter and uncertainty estimation, model error identification, remote sensing and ecological forecasting), the paper discusses method limitations, current challenges and future research direction. In the ongoing data-rich era of today's world, MDF could become an important diagnostic and prognostic tool in which to improve our understanding of ecological processes while testing ecological theory and hypotheses and forecasting changes in ecosystem structure, function and services.     

Pyramids and cascades: a synthesis of food chain functioning and stability

Food chain theory is one of the cornerstones of ecology, providing many of its basic predictions, such as biomass pyramids, trophic cascades and predator–prey oscillations. Yet, ninety years into this theory, the conditions under which these patterns may occur and persist in nature remain subject to debate. Rather than address each pattern in isolation, we propose that they must be understood together, calling for synthesis in a fragmented landscape of theoretical and empirical results. As a first step, we propose a minimal theory that combines the long‐standing energetic and dynamical approaches of food chains. We chart theoretical predictions on a concise map, where two main regimes emerge: across various functioning and stability metrics, one regime is characterised by pyramidal patterns and the other by cascade patterns. The axes of this map combine key physiological and ecological variables, such as metabolic rates and self‐regulation. A quantitative comparison with data sheds light on conflicting theoretical predictions and empirical puzzles, from size spectra to causes of trophic cascade strength. We conclude that drawing systematic connections between various existing approaches to food chains, and between their predictions on functioning and stability, is a crucial step in confronting this theory to real ecosystems.     

Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110.

Flux balance models of metabolism use stoichiometry of metabolic pathways, metabolic demands of growth, and optimality principles to predict metabolic flux distribution and cellular growth under specified environmental conditions. These models have provided a mechanistic interpretation of systemic metabolic physiology, and they are also useful as a quantitative tool for metabolic pathway design. Quantitative predictions of cell growth and metabolic by-product secretion that are experimentally testable can be obtained from these models. In the present report, we used independent measurements to determine the model parameters for the wild-type Escherichia coli strain W3110. We experimentally determined the maximum oxygen utilization rate (15 mmol of O2 per g [dry weight] per h), the maximum aerobic glucose utilization rate (10.5 mmol of Glc per g [dry weight] per h), the maximum anaerobic glucose utilization rate (18.5 mmol of Glc per g [dry weight] per h), the non-growth-associated maintenance requirements (7.6 mmol of ATP per g [dry weight] per h), and the growth-associated maintenance requirements (13 mmol of ATP per g of biomass). The flux balance model specified by these parameters was found to quantitatively predict glucose and oxygen uptake rates as well as acetate secretion rates observed in chemostat experiments. We have formulated a predictive algorithm in order to apply the flux balance model to describe unsteady-state growth and by-product secretion in aerobic batch, fed-batch, and anaerobic batch cultures. In aerobic experiments we observed acetate secretion, accumulation in the culture medium, and reutilization from the culture medium. In fed-batch cultures acetate is cometabolized with glucose during the later part of the culture period.(ABSTRACT TRUNCATED AT 250 WORDS)     

Statistical mechanics unifies different ecological patterns

Recently there has been growing interest in the use of maximum relative entropy (MaxREnt) as a tool for statistical inference in ecology. In contrast, here we propose MaxREnt as a tool for applying statistical mechanics to ecology. We use MaxREnt to explain and predict species abundance patterns in ecological communities in terms of the most probable behaviour under given environmental constraints, in the same way that statistical mechanics explains and predicts the behaviour of thermodynamic systems. We show that MaxREnt unifies a number of different ecological patterns: (i) at relatively local scales a unimodal biodiversity-productivity relationship is predicted in good agreement with published data on grassland communities, (ii) the predicted relative frequency of rare vs. abundant species is very similar to the empirical lognormal distribution, (iii) both neutral and non-neutral species abundance patterns are explained, (iv) on larger scales a monotonic biodiversity-productivity relationship is predicted in agreement with the species-energy law, (v) energetic equivalence and power law self-thinning behaviour are predicted in resource-rich communities. We identify mathematical similarities between these ecological patterns and the behaviour of thermodynamic systems, and conclude that the explanation of ecological patterns is not unique to ecology but rather reflects the generic statistical behaviour of complex systems with many degrees of freedom under very general types of environmental constraints.     

A thermodynamic perspective on food webs: quantifying entropy production within detrital-based ecosystems

Because ecosystems fit so nicely the framework of a "dissipative system", a better integration of thermodynamic and ecological perspectives could benefit the quantitative analysis of ecosystems. One obstacle is that traditional food web models are solely based upon the principles of mass and energy conservation, while the theory of non-equilibrium thermodynamics principally focuses on the concept of entropy. To properly cast classical food web models within a thermodynamic framework, one requires a proper quantification of the entropy production that accompanies resource processing of the food web. Here we present such a procedure, which emphasizes a rigorous definition of thermodynamic concepts (e.g. thermodynamic gradient, disequilibrium distance, entropy production, physical environment) and their correct translation into ecological terms. Our analysis provides a generic way to assess the thermodynamic operation of a food web: all information on resource processing is condensed into a single resource processing constant. By varying this constant, one can investigate the range of possible food web behavior within a given fixed physical environment. To illustrate the concepts and methods, we apply our analysis to a very simple example ecosystem: the detrital-based food web of marine sediments. We examine whether entropy production maximization has any ecological relevance in terms of food web functioning.     

The scaling of abundance in consumers and their resources: implications for the energy equivalence rule

The negative scaling of plant and animal abundance with body mass is one of the most fundamental relationships in ecology. However, theoretical approaches to explain this phenomenon make the unrealistic assumption that species share a homogeneous resource. Here we present a simple model linking mass and metabolism with density that includes the effects of consumer size on resource characteristics (particle size, density, and distribution). We predict patterns consistent with the energy equivalence rule (EER) under some scenarios. However, deviations from EER occur as a result of variation in resource distribution and productivity (e.g., due to the clumping of prey or variation in food particle size selection). We also predict that abundance scaling exponents change with the dimensionality of the foraging habitat. Our model predictions explain several inconsistencies in the observed scaling of vertebrate abundance among ecological and taxonomic groups and provide a broad framework for understanding variation in abundance.     

Integrating microbial ecology into ecosystem models: challenges and priorities

Microbial communities can potentially mediate feedbacks between global change and ecosystem function, owing to their sensitivity to environmental change and their control over critical biogeochemical processes. Numerous ecosystem models have been developed to predict global change effects, but most do not consider microbial mechanisms in detail. In this idea paper, we examine the extent to which incorporation of microbial ecology into ecosystem models improves predictions of carbon (C) dynamics under warming, changes in precipitation regime, and anthropogenic nitrogen (N) enrichment. We focus on three cases in which this approach might be especially valuable: temporal dynamics in microbial responses to environmental change, variation in ecological function within microbial communities, and N effects on microbial activity. Four microbially-based models have addressed these scenarios. In each case, predictions of the microbial-based models differ—sometimes substantially—from comparable conventional models. However, validation and parameterization of model performance is challenging. We recommend that the development of microbial-based models must occur in conjunction with the development of theoretical frameworks that predict the temporal responses of microbial communities, the phylogenetic distribution of microbial functions, and the response of microbes to N enrichment.     

Tree size distributions in an old-growth temperate forest

Despite the wide variation in the structural characteristics in natural forests, tree size distribution show fundamental similarities that suggest general underlying principles. The metabolic ecology theory predicts the number of individual scales as the −2 power of tree diameter. The demographic equilibrium theory predicts tree size distribution starting from the relationship of size distributions with growth and mortality at demographic equilibrium. Several analytic predictions for tree size distributions are derived from the demographic equilibrium theory, based on different growth and mortality functions. In addition, some purely phenomenological functions, such as polynomial function, have been used to describe the tree size distributions. In this paper, we use the metabolic ecology theory, the demographic equilibrium theory and the polynomial function to predict the tree size distribution for both the whole community and each species in an old-growth temperate forest in northeastern China. The results show that metabolic ecology theory predictions for the scaling of tree abundance with diameter were unequivocally rejected in the studied forest. Although these predictions of demographic theory are the best models for most of the species in the temperate forest, the best models for some species ( Tilia amurensis , Quercus mongolica and Fraxinus mandshurica ) are compound curves (i.e. rotated sigmoid curves), best predicted by the polynomial function. Hence, the size distributions of natural forests were unlikely to be invariant and the predictive ability of general models was limited. As a result, developing a more sophisticated theory to predict tree size distributions remains a complex, yet tantalizing, challenge.     

The role of expert systems in vegetation science

An area of artificial intelligence known as experts systems (or knowledge-based systems) is being applied in many areas of science, technology and commerce. It is likely that the techniques will have an impact on vegetation science and ecology in general. This paper discusses some of those impacts and concludes that the main effects will be in areas of applied ecology especially where ecological expertise is needed either quickly (e.g. disaster management) or across a wide range of ecological disciplines (e.g. land management decisions). Expert systems will provide ecologists with valuable tools for managing data and interacting with other fields of expertise. The impact of expert systems on ecological theory will depend on the degree to which deep knowledge (i.e. knowledge based on first principles rather than on more empirical rules) is used in formulating knowledge bases.     

Predicting shifts in dynamics of cannibalistic field populations using individual-based models

The occurrence of qualitative shifts in population dynamical regimes has long been the focus of population biologists. Nonlinear ecological models predict that these shifts in dynamical regimes may occur as a result of parameter shifts, but unambiguous empirical evidence is largely restricted to laboratory populations. We used an individual-based modelling approach to predict dynamical shifts in field fish populations where the capacity to cannibalize differed between species. Model-generated individual growth trajectories that reflect different population dynamics were confronted with empirically observed growth trajectories, showing that our ordering and quantitative estimates of the different cannibalistic species in terms of life-history characteristics led to correct qualitative predictions of their dynamics.     

The unified neutral theory of biodiversity and biogeography at age ten

A decade has now passed since Hubbell published The Unified Neutral Theory of Biodiversity and Biogeography. Neutral theory highlights the importance of dispersal limitation, speciation and ecological drift in the natural world and provides quantitative null models for assessing the role of adaptation and natural selection. Significant advances have been made in providing methods for understanding neutral predictions and comparing them with empirical data. In this review, we describe the current state-of-the-art techniques and ideas in neutral theory and how these are of relevance to ecology. The future of neutral theory is promising, but its concepts must be applied more broadly beyond the current focus on species-abundance distributions.     

Can metabolic traits explain animal community assembly and functioning?

All animals on Earth compete for free energy, which is acquired, assimilated, and ultimately allocated to growth and reproduction. Competition is strongest within communities of sympatric, ecologically similar animals of roughly equal size (i.e. horizontal communities), which are often the focus of traditional community ecology. The replacement of taxonomic identities with functional traits has improved our ability to decipher the ecological dynamics that govern the assembly and functioning of animal communities. Yet, the use of low-resolution and taxonomically idiosyncratic traits in animals may have hampered progress to date. An animal's metabolic rate (MR) determines the costs of basic organismal processes and activities, thus linking major aspects of the multifaceted constructs of ecological niches (where, when, and how energy is obtained) and ecological fitness (how much energy is accumulated and passed on to future generations). We review evidence from organismal physiology to large-scale analyses across the tree of life to propose that MR gives rise to a group of meaningful functional traits – resting metabolic rate (RMR), maximum metabolic rate (MMR), and aerobic scope (AS) – that may permit an improved quantification of the energetic basis of species coexistence and, ultimately, the assembly and functioning of animal communities. Specifically, metabolic traits integrate across a variety of typical trait proxies for energy acquisition and allocation in animals (e.g. body size, diet, mobility, life history, habitat use), to yield a smaller suite of continuous quantities that: (1) can be precisely measured for individuals in a standardized fashion; and (2) apply to all animals regardless of their body plan, habitat, or taxonomic affiliation. While integrating metabolic traits into animal community ecology is neither a panacea to disentangling the nuanced effects of biological differences on animal community structure and functioning, nor without challenges, a small number of studies across different taxa suggest that MR may serve as a useful proxy for the energetic basis of competition in animals. Thus, the application of MR traits for animal communities can lead to a more general understanding of community assembly and functioning, enhance our ability to trace eco-evolutionary dynamics from genotypes to phenotypes (and vice versa), and help predict the responses of animal communities to environmental change. While trait-based ecology has improved our knowledge of animal communities to date, a more explicit energetic lens via the integration of metabolic traits may further strengthen the existing framework.     

Using prior information to build probabilistic invasive species risk assessments

Understanding why some introduced species become naturalized and invasive whereas others do not is a major focus of invasion ecology. Invasive species risk assessments address this same question, but are not typically based on the results from recent ecological studies. Applying results from the ecological literature to risk assessment is difficult, in part because there are no general explanations of invasion likelihood across taxa. Most ecological studies are also specific to a particular region and it is unclear whether outcomes in one region will necessarily apply to another. Here we show how a hierarchical Bayesian statistical framework can make better use of ecological studies for applied risk assessments. We focus on three key opportunities afforded by these models: (1) the ability to leverage information from one region to form prior expectations for other regions about which little is known, (2) the ability to quantify uncertainty of predictions, and (3) flexibility to incorporate within-group heterogeneities in probabilities of naturalization. We illustrate these principles using a case study where we predict the probability of plant taxa naturalizing in New Zealand and Australia, showing how prior information can be particularly valuable when data are limited. As more studies document invasion patterns around the world, a framework that can formally incorporate prior information will help link the accumulating data on species introductions to risk assessments.     

Woodstoich III: Integrating tools of nutritional geometry and ecological stoichiometry to advance nutrient budgeting and the prediction of consumer‐driven nutrient recycling

Within the last two decades, ecological stoichiometry (ES) and nutritional geometry (NG, also known as geometric framework for nutrition) have delivered novel insights into core questions of nutritional ecology. These two nutritionally explicit frameworks differ in the ‘nutrient currency’ used and the focus of their past research; behavioural feeding strategies in NG, mainly investigating terrestrial organisms, and trophic ecology in ES, mainly in aquatic settings. However, both NG and ES have developed in explaining patterns across various scales of biological organization. Integrating specific tools of these frameworks could advance the field of nutritional ecology by unifying theoretical and empirical approaches from the organismal to ecosystem level processes. Toward this integration, we identified 1) nutrient/element budgets as a shared concept of both frameworks that encompass nutrient intake, retention, and release, 2) response surface plots of NG as powerful tools to illustrate processes at the organismal level and 3) the concept of consumer‐driven nutrient recycling (CNR) of ES as a useful tool bridging organism and ecosystem scales. We applied response surface plots to element budget data from an ES study to show how this approach can deliver new insights at the organismal level, e.g. by showing the interplay between egestion and excretion depending simultaneously on the consumed amount of carbon and phosphorus based on variation across individuals. By integrating concepts of ES and NG to model microbial uptake and mineralization of nitrogenous wastes reported in a NG study, we also demonstrate that considering biochemically explicit mineralization rates of organic wastes can improve predictions of CNR by reducing over‐ or underestimation of mineralization depending on the quality of the consumer's diet. Our presented tools and approaches can help to bridge the organismal and ecosystem level, advancing the predictive power of studies in nutritional ecology at multiple ecological scales.     

Theoretical predictions for how temperature affects the dynamics of interacting herbivores and plants

Concern about climate change has spurred experimental tests of how warming affects species' abundance and performance. As this body of research grows, interpretation and extrapolation to other species and systems have been limited by a lack of theory. To address the need for theory for how warming affects species interactions, we used consumer-prey models and the metabolic theory of ecology to develop quantitative predictions for how systematic differences between the temperature dependence of heterotrophic and autotrophic population growth lead to temperature-dependent herbivory. We found that herbivore and plant abundances change with temperature in proportion to the ratio of autotrophic to heterotrophic metabolic temperature dependences. This result is consistent across five different formulations of consumer-prey models and over varying resource supply rates. Two models predict that temperature-dependent herbivory causes primary producer abundance to be independent of temperature. This finding contradicts simpler extensions of metabolic theory to abundance that ignore trophic interactions, and is consistent with patterns in terrestrial ecosystems. When applied to experimental data, the model explained 77% and 66% of the variation in phytoplankton and zooplankton abundances, respectively. We suggest that metabolic theory provides a foundation for understanding the effects of temperature change on multitrophic ecological communities.