147 research outputs found
Parameterising competing zooplankton for survival in plankton functional type models
No full textMarine plankton ecosystems are an important component of biogeochemical cycling in the oceans. Operational plankton functional type (PFT) models, that group plankton according to their biogeochemical properties, are currently being developed to resolve biogenic gas exchange between the ocean and atmosphere, and to model the lowest trophic levels in fisheries models. A fundamental problem with these models is that PFTs often go extinct in computer simulations, effectively removing the biogeochemical processes from the models. Cropp and Norbury [Cropp, R., Norbury, J., 2009a. Parameterizing plankton functional type models: insights from a dynamical systems perspective. J. Plankton Res. 31, 939-963] demonstrated that parameter combinations that allowed all PFTs to stay extant for all time in stable, homogeneous environments were rare in a PFT model with two competing phytoplankton and one zooplankton (NP1P2Z). In this paper, we examine the dynamical properties of a generic predator-predator-prey PFT model, and apply the analysis techniques developed by Cropp and Norbury to a simple example PFT model with one phytoplankton and two zooplankton (NPZ1Z2) in order to explore its properties and parameter space. We find that the properties of predator-predator-prey PFT systems are fundamentally different from those of predator-prey-prey PFT systems. The likelihood of parameter combinations for which all PFTs stay extant for all time in predator-predator-prey PFT systems depends critically on the process formulations used, and the properties of co-existing zooplankton (as defined by their parameter values) are quite different to those of co-existing phytoplankton.Griffith Sciences, Griffith School of EnvironmentFull Tex
Is maximizing resilience compatible with established ecological goal functions?
No full textCropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] used a simple phytoplanktonzooplankton-nutrient model and a genetic algorithm to determine the parameter values that would maximize the value of certain goal functions. These goal functions were to maximize biomass, maximize flux, maximize flux to biomass ratio, and maximize resilience. It was found that maximizing goal functions maximized resilience. The objective of this study was to investigate whether the Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] result was indicative of a general ecosystem principle, or peculiar to the model and parameter ranges used. This study successfully replicated the Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] experiment for a number of different model types, however, a different interpretation of the results is made. A new metric, concordance, was devised to describe the agreement between goal functions. It was found that resilience has the highest concordance of all goal functions trialled. for most model types. This implies that resilience offers a compromise between the established ecological goal functions. The parameter value range used is found to affect the parameter versus goal function relationships. Local maxima and minima affected the relationship between parameters and goal functions, and between goal functions. (C) 2003 Elsevier B.V. All rights reserved
Correction to: An eco-evolutionary system with naturally bounded traits
No full textCorrection to: Theoretical Ecology
https://doi.org/10.1007/s12080-019-0407-6
The original version of this article unfortunately contains an incorrect panel (b) in Fig. 1 introduced during the production process. The correct Fig. 1 is shown next page:
Ecospace diagrams illustrating the initial conditions (blue dots) and stable invasion outcomes (black dots) under ecological theory used for the four scenarios: a competitive exclusion—either x1 or x2 could survive depending on initial conditions, but for this initial condition x1 will survive and x2 will fail to invade; b competitive exclusion—R∗ theory predicts that x1 will win and x2 will go extinct; c competitive exclusion—R∗ theory predicts that x2 will win and x1 will go extinct; d competitive coexistence—both populations survive but x1 will dominate in non-adaptive scenarios. The lines are zero isoclines, the dots are stable (black) or unstable (white) equilibriums or initial conditions (blue). The vector field (blue arrows) show how the system changes in time. The initial population values have x1 set to its carrying capacity (i.e. x∗1=K1=r1/a11) and x∗2=0.05. Technically, R∗ is only relevant to panels b and c, but we will use the term generically to mean the outcome of non-evolutionary competition. (See Table 1 for parameter values)No Full Tex
Modelling the evolution of naturally bounded traits in a population
No full textEco-evolutionary models commonly assume that traits are normally distributed in a population, and that the trait bounds do not influence the adaptation of traits. However, recent empirical evidence suggests that at least some traits are not normally distributed, and there is theoretical support for the view that trait bounds can be fundamental to trait adaptation. These attributes suggest that a beta distribution, which can accommodate unbounded (i.e. normal), singly bounded (i.e. gamma) or doubly bounded (beta) trait distributions, may be an appropriate alternative assumption for eco-evolutionary models. We develop an evolutionary model that represents how the mean values of a population’s traits change. Implementation of the model requires assumptions to be made regarding the relative fitness of the individuals in the population, and how their traits are distributed within natural bounds. We compare the numerical results of “population” models that evolve a plant population and the means of its two traits using our eco-evolutionary equations with those of “phenotype” models that evolve 10,000 phenotypes, each defined by a pair of trait values, of a plant population. The phenotype models do not assume any particular trait distribution or fitness, and allow phenotypes to wax and wane according to their ability to compete with other phenotypes in the population for a finite resource. Comparison of the trait distributions obtained by solving 3 coupled population odes with those obtained by solving 10,000 coupled phenotype odes reveals very good agreement between the approaches for each of four mortality functions. Further, it supports the ubiquity of the beta distribution in describing evolutionary processes in populations. An advantage of the simple population model is that it provides insights into why particular results are obtained, which augments the predictive power of the modelling, suggesting that in fact a simplified, abstracted modelling approach is sometimes preferable to the detailed, complicated alternative.Full Tex
A Biogeochemical Modelling Analysis of the Potential For Marine Ecosystems to Regulate Climate By the Production of Dimethylsulphide
No full textThe potential for life to control its environment was first suggested by Lovelock (1972). Charlson et al (1987) proposed a role for marine planktonic ecosystems in global climate regulation via the production and ventilation to the atmosphere of dimethylsulphide (DMS), a by-product of phytoplankton metabolism. Once in the atmosphere DMS contributes to the formation of cloud condensation nuclei, and increases the amount and brightness of cloud. This affects the albedo of the planet, reflecting more incident sunlight back into space, and cooling the earth. In common with many other 'hypotheses' regarding complex adaptive systems, the hypothesis proposed by Charlson et al (1987) is not experimentally testable. The production and ventilation to the atmosphere of DMS is the result of complex interactions between biological, chemical and physical processes. Consequently, increasing use is being made of mathematical models that simulate these processes to advance understanding of it (Archer et al. 2002). This study examines one of the fundamental mechanisms proposed by the Charlson et al (1987) hypothesis, that increasing global temperatures will lead to increased ventilation of DMS from the ocean to the atmosphere. The study develops one-dimensional biogeochemical models of DMS production by upper ocean ecosystems, based on the model proposed by Gabric et al. (1993b). The models are examined to elucidate their fundamental mathematical properties, and are subjected to sensitivity analysis to identify important processes and parameters. These investigations identify a simpler model that can reproduce the predictions of the Gabric et al. (1993b) model. Predictions derived from model simulations forced by climatologies of measured physical data are compared to a global database of measurements of sea surface DMS concentrations, and to observed depth profiles of DMS in the upper ocean. These comparisons confirm that all models are in good qualitative agreement with measured data. The fifteen global climate prediction models currently in use around the globe all predict substantial warming effects from the ventilation of anthropogenic carbon dioxide to the atmosphere. A simplified DMS model is calibrated to climatologies of Antarctic chlorophyll and DMS data and reproduces the data with great precision. The calibrated model is applied in global warming scenarios to 'test' the efficacy of the mechanism proposed by the Charlson et al (1987) hypothesis. This simulation provides evidence that the response predicted by the hypothesis is indeed feasible, and that substantial increases (up to 45%) in the ventilation of DMS to the atmosphere could be possible in some circumstances. The results of the modelling study provide impetus for further examination of field data. If couplings between marine biota and atmosphere are feasible, then they may be operating contemporarily, and may be detectable. Atmospheric DMS is oxidised to form aerosols (Miller et al. 2002) that influence the aerosol optical depth of the atmosphere. Archives of remote sensed ocean chlorophyll a concentration and aerosol optical depth are examined for evidence of the biologically mediated couplings. A clear coupling between aeolian dust and marine phytoplankton is evident from this analysis, suggesting that the deposition of dust from the atmosphere is a major factor controlling phytoplankton growth in many parts of the ocean. A second coupling between marine phytoplankton and atmospheric aerosols is also detected. This coupling is apparently not related to dust and is symmetrical about the equator, despite the substantial differences in the atmospheres and oceans of each hemisphere. It is speculated that this coupling may reflect the influence of the ventilation of DMS produced by marine phytoplankton on the atmosphere. This thesis provides new evidence supporting the important role of marine ecosystems in global climate regulation by the production of DMS. This evidence is principally obtained from a biogeochemical modelling approach, but is supported by analyses of empirical data. The concordance of results obtained from different approaches suggests that the contribution of marine ecosystems to global climate regulation is real, important and currently active.Thesis (PhD Doctorate)Doctor of Philosophy (PhD)Australian School of Environmental StudiesFull Tex
The dynamics of evolutionary branching in an ecological model
No full textEco-evolutionary modelling involves the coupling of ecological equations to evolutionary ones. The interaction between ecological dynamics and evolutionary processes is essential to simulating evolutionary branching, a precursor to speciation. The creation and maintenance of biodiversity in models depends upon their ability to capture the dynamics of evolutionary branching. Understanding these systems requires low-dimension models that are amenable to analysis. The rapid reproduction rates of marine plankton ecosystems and their importance in determining the fluxes of climatically important gases between the ocean and atmosphere suggest that the next generation of global climate models needs to incorporate eco-evolutionary models in the ocean. This requires simple population-level models, that can represent such eco-evolutionary processes with orders of magnitude fewer equations than models that follow the dynamics of individual phenotypes. We present a general framework for developing eco-evolutionary models and consider its general properties. This framework defines a fitness function and assumes a beta distribution of phenotype abundances within each population. It simulates the change in total population size, the mean trait value, and the trait differentiation, from which the variance of trait values in the population may be calculated. We test the efficacy of the eco-evolutionary modelling framework by comparing the dynamics of evolutionary branching in a six-equation eco-evolutionary model that has evolutionary branching, with that of an equivalent one-hundred equation model that simulates the dynamics of every phenotype in the population. The latter model does not involve a population fitness function, nor does it assume a distribution of phenotype abundance across trait values. The eco-evolutionary population model and the phenotype model produce similar evolutionary branching, both qualitatively and quantitatively, in both symmetric and asymmetric fitness landscapes. In order to better understand the six-equation model, we develop a heuristic three-equation eco-evolutionary model. We use the density-independent mortality parameter as a convenient bifurcation parameter, so that differences in evolutionary branching dynamics in symmetric and asymmetric fitness landscapes may be investigated. This model shows that evolutionary branching of a stable population is flagged by a zero in the local trait curvature; the trait curvature then changes sign from negative to positive and back to negative, along the solution. It suggests that evolutionary branching points may be generated differently, with different dynamical properties, depending upon, in this case, the symmetry of the system. It also suggests that a changing environment, that may change attributes such as mortality, could have profound effects on an ecosystem’s ability to adapt. Our results suggest that the properties of the three-dimensional model can provide useful insights into the properties of the higher-dimension models. In particular, the bifurcation properties of the simple model predict the processes by which the more complicated models produce evolutionary branching points. The corresponding bifurcation properties of the phenotype and population models, evident in the dynamics of the phenotype distributions they predict, suggest that our eco-evolutionary modelling framework captures the essential properties that underlie the evolution of phenotypes in populations
The potential for coral reefs to adapt to a changing climate - an eco-evolutionary modelling perspective
No full textCoral reef systems are under increasing pressure to adapt to rapidly varying environmental conditions, in particular increasing ocean temperatures. A question of major concern is whether coral reefs can adapt to and survive the predicted increases in global temperatures over the remainder of this century. A simple model of a coral reef ecosystem is developed to include adaptation of key growth and mortality parameters for a coral polyp population and its symbiotic algae population. Interacting populations of pelagic phytoplankton and zooplankton are also simulated. The model simulates a stable coral reef ecosystem in the absence of climate change, but predicts the extinction of the coral population under global warming if the populations do not adapt. However, when the coral and symbiont populations adapt to climate change, a stable coral reef ecosystem is predicted. The model allows identification of processes and parameters to inform attempts to measure the key attributes of adapting coral reef ecosystems
Predator–Prey Evolution from an Eco-evolutionary Trade-off Model: The Role of Trait Differentiation
No full textWe develop a novel eco-evolutionary modelling framework and demonstrate its efficacy by simulating the evolution of trait distributions in predator and prey populations. The eco-evolutionary modelling framework assumes that population traits have beta distributions and defines canonical equations for the dynamics of each total population size, the population’s average trait value, and a measure of the population’s trait differentiation. The trait differentiation is included in the modelling framework as a phenotype analogue, Q, of Wright’s fixation index FST, which is inversely related to the sum of the beta distribution shape parameters. The canonical equations may be used as templates to describe the evolution of population trait distributions in many ecosystems that are subject to stabilising selection. The solutions of the “population model” are compared with those of a “phenotype model” that simulates the growth of each phenotype as it interacts with every other phenotype under the same trade-offs. The models assume no sources of new phenotypic variance, such as mutation or gene flow. We examine a predator–prey system in which each population trades off growth against mortality: the prey optimises devoting resources to growth or defence against predation; and the predator trades off increasing its attack rate against increased mortality. Computer solutions with stabilising selection reveal very close agreement between the phenotype and population model results, which both predict that evolution operates to stabilise an initially oscillatory system. The population model reduces the number of equations required to simulate the eco-evolutionary system by several orders of magnitude, without losing verisimilitude for the overarching population properties. The population model also allows insights into the properties of the system that are not available from the equivalent phenotype model.Full Tex
The Role of Contracts in the Organic Supply Chain: 2004 and 2007
No full textOrganic food products are excellent candidates for contract production and marketing because they are produced using a distinct process and are in high demand. This report summarizes survey data on contracting in the organic sector, addressing the extent of contracting, the rationale for using contracts, and contract design for select commodities. The central survey data were collected from certified organic handlers (intermediaries)in the United States who marketed and procured organic products in 2004 and 2007. Contracting is widespread in the organic sector, and, in 2007, firms used contracts most frequently to secure organic products essential to their business and to source products in short supply. Large firms were more likely to use contracts for procurement, and these firms contracted for a larger share of their procurement needs. Nearly all contracts required suppliers to provide evidence of organic certification. Firms using contracts rarely assisted suppliers with obtaining organic certification or the transition to organic. Most contracts include provisions regarding quality, and quality verification was an essential component of these contracts. Prices were determined in a variety of ways and, in some cases, depended on delivered quality.Organic supply chain, contracts, organic marketing, organic procurement, intermediaries, certified organic handlers, contract design, certified organic, Agribusiness, Marketing,
Ecosystem model parameter set for a near-shore Antarctic food web
No full textProgress Code: completedStatement: The dates provided in temporal coverage represent the start and end dates of the AAS project. The coordinates provided in spatial coverage are generic Antarctic coastline coordinates.This parameter set was developed to provide a plausible implementation for the ecological model described in Bates, M., S Bengtson Nash, D.W. Hawker, J. Norbury, J.S. Stark and R. A. Cropp. 2015. Construction of a trophically complex near-shore Antarctic food web model using the Conservative Normal framework with structural coexistence. Journal of Marine Systems. 145: 1-14. The ecosystem model used in this paper was designed to have the property of structural coexistence. This means that the functional forms used to describe population interactions in the equations were chosen to ensure that the boundary eigenvalues of every population were all always positive, ensuring that no population in the model can ever become extinct. This property is appropriate for models such as this that are implemented to model typical seasonal variations rather than changes over time. The actual parameter values were determined by searching a parameter space for parameter sets that resulted in a plausible distribution of biomass among the trophic levels. The search was implemented using the Boundary Eigenvalue Nudging - Genetic Algorithm (BENGA) method and was constrained by measured values where these were available.<br/><br/>This parameter set is provided as an indicative set that is appropriate for studying the partitioning of Persistent Organic Pollutants in coastal Antarctic ecosystems. It should not be used for predictive population modelling without independent calibration and validation
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