Model Ecosystem Research Articles

Diagnosing phosphorus limitations in natural terrestrial ecosystems in carbon cycle models.

Most of the Earth System Models (ESMs) project increases in net primary productivity (NPP) and terrestrial carbon (C) storage during the 21st century. Despite empirical evidence that limited availability of phosphorus (P) may limit the response of NPP to increasing atmospheric CO2, none of the ESMs used in the previous Intergovernmental Panel on Climate Change assessment accounted for P limitation. We diagnosed from ESM simulations the amount of P need to support increases in carbon uptake by natural ecosystems using two approaches: the demand derived from (1) changes in C stocks and (2) changes in NPP. The C stock‐based additional P demand was estimated to range between −31 and 193 Tg P and between −89 and 262 Tg P for Representative Concentration Pathway (RCP) 2.6 and RCP8.5, respectively, with negative values indicating a P surplus. The NPP‐based demand, which takes ecosystem P recycling into account, results in a significantly higher P demand of 648–1606 Tg P for RCP2.6 and 924–2110 Tg P for RCP8.5. We found that the P demand is sensitive to the turnover of P in decomposing plant material, explaining the large differences between the NPP‐based demand and C stock‐based demand. The discrepancy between diagnosed P demand and actual P availability (potential P deficit) depends mainly on the assumptions about availability of the different soil P forms. Overall, future P limitation strongly depends on both soil P availability and P recycling on ecosystem scale.

Regenerating eutrophic aquatic ecosystem through hydrophytes

As the world facing the problem of eutrophication and it is decreasing the life of lakes, this will produce the shortage of freshwater. Hydrophytes are one of the cheaper and best options for regenerating eutrophic lake. Model eutrophic aquatic ecosystems was designed for bioremediation purpose, for use of hydrophytes, a freshwater static model ecosystem was established. Glass aquarium measuring 180 x 45x 45 cm was used as an ecosystem chamber. Fifteen kg of black soil from Wadali Lake was added to make a 4 cm bed in the aquarium. Different hydrophytic plants like Ecchornia, Pistia, Chara, Vallisneria, Hydrilla, Naja were introduced in the aquarium. Then it was filled with 200 L of water. Afterwards certain species of zooplankton and phytoplankton, snails, Chironomous larvae, Rasbora fishes were introduced in the aquarium. Water sample was analyzed for one month at one day interval. In a simulated experimental eutrophic model aquatic ecosystem, the BOD was depleted and the nutrients like phosphates, sulphates and nitrates were reduced significantly.

The evolution of ecosystem ascendency in a complex systems based model

General patterns in ecosystem development can shed light on driving forces behind ecosystem formation and recovery and have been of long interest. In recent years, the need for integrative and process oriented approaches to capture ecosystem growth, development and organisation, as well as the scope of information theory as a descriptive tool has been addressed from various sides. However data collection of ecological network flows is difficult and tedious and comprehensive models are lacking. We use a hierarchical version of the Tangled Nature Model of evolutionary ecology to study the relationship between structure, flow and organisation in model ecosystems, their development over evolutionary time scales and their relation to ecosystem stability. Our findings support the validity of ecosystem ascendency as a meaningful measure of ecosystem organisation, which increases over evolutionary time scales and significantly drops during periods of disturbance. The results suggest a general trend towards both higher integrity and increased stability driven by functional and structural ecosystem coadaptation.

Insight into climate change from the carbon exchange of biocrusts utilizing non-rainfall water

Biocrusts are model ecosystems of global change studies. However, light and non-rainfall water (NRW) were previously few considered. Different biocrust types further aggravated the inconsistence. So carbon-exchange of biocrusts (cyanobacteria crusts-AC1/AC2; cyanolichen crust-LC1; chlorolichen crust-LC2; moss crust-MC) utilizing NRW at various temperatures and light-intensities were determined under simulated and insitu mesocosm experiments. Carbon input of all biocrusts were negatively correlated with experimental temperature under all light-intensity with saturated water and stronger light with equivalent NRW, but positively correlated with temperature under weak light with equivalent NRW. LCPs and R/Pg of AC1 were lowest, followed in turn by AC2, LC2 and MC. Thus AC1 had most opportunities to use NRW, and 2.5 °C warming did cause significant changes of carbon exchange. Structural equation models further revealed that air-temperature was most important for carbon-exchange of ACs, but equally important as NRW for LC2 and MC; positive influence of warming on carbon-input in ACs was much stronger than the latter. Therefore, temperature effect on biocrust carbon-input depends on both moisture and light. Meanwhile, the role of NRW, transitional states between ACs, and obvious carbon-fixation differences between lichen crusts should be fully considered in the future study of biocrusts responding to climate change.

Combining high-resolution images and LiDAR data to model ecosystem services perception in compact urban systems

In this study, we aim to understand how the provision of ecosystem services (ESS) is spatially distributed within a compact urban system considering the structure and spatial arrangement of green spaces in relation to built-up areas and other infrastructures. For this purpose, we devised an approach to assess the ESS provided by urban green spaces through the integration of social data (i.e., stakeholders’ perception of the multiple benefits of green spaces) with remotely sensed data, such as high-resolution satellite images and Laser Imaging Detection and Ranging (LiDAR) point-cloud. We developed a spatially explicit indicator (or metric) called Normalized Difference Green-Building Volume (NDGB), derived from remote sensing, that can be used to predict the way people perceive the ESS conveyed by green spaces in cities. We designed the NDGB metric using the city of Bari, Southern Italy, as a case example by involving four groups of stakeholders (n=202) to assess ten urban green spaces. Our results show a strong positive relationship between the NDGB and the way stakeholders perceive the ESS provided by these urban green spaces. Thus, our indicator accurately expresses the relationship between stakeholders’ perceptions of ESS provided by green spaces and the physical data (i.e., green space structure) produced by remote sensing technology. The green space most highly evaluated by the NDGB indicator, the periurban park “Lama Balice”, was also the one on which all stakeholder group responses converged, including the group of NGOs and associations, which assigned average low scores for perceived ESS across all the green spaces presented in the study. The study was developed using the city of Bari in Southern Italy as testbed. There is a need to further extend and replicate our approach to other urban systems across different regions (e.g., Northern Europe, North America, Asia), especially those which are in the process of pursuing more sustainable green infrastructure planning and development, as they could be inclined to adopt our approach in ongoing decision making processes. We believe our approach can inform planners and decision makers on ESS provision and supply them with evidence of the local co-benefits of green spaces as well as of the spatial distribution of ESS within compact urban systems.

Integrated cellular framework for modeling ecosystems: Theory and applications

We introduce an integrated framework for modeling and simulation of ecosystems based on cellular models. The framework integrates cellular modeling, web-based simulation, and geographic information systems (GISs) for data collection and visualization. In this framework, data extraction from GISs is automated; we use the Cell-DEVS formalism for modeling the ecosystem and the CD++ cellular modeling tool within the RISE (RESTful Interoperability Simulation Environment) middleware for web-based simulation. The simulation results are easily integrated with Google Earth data for visualization. We discuss the design, implementation, and benefits of the integrated approach for modeling and simulation in spatial analysis of ecosystem services. We show different case studies in the area of ecological systems, demonstrating how to apply the framework, its usability, and flexibility. We focus on the use of models available in remote servers, their integration with GIS data for inputs, and georeferenced visualization of the results. We show how the modeling methods based on DEVS and their modular interfaces make it easy to build such an architecture and we discuss its application to the field of environmental systems.

Metal toxicity affects predatory stream invertebrates less than other functional feeding groups

Ecosystem effects of heavy metals need to be identified for a retrospective risk assessment, and potential impacts need to be predicted for a prospective risk assessment. In this study, we established a strong correlation between the toxic pressure of dissolved metals and invertebrate species. We compiled available data from a wide geographical range of Australian streams that were contaminated with heavy metals [mainly copper (Cu) and zinc (Zn)] and the corresponding invertebrate communities. Heavy metal toxicity is positively related to the proportion of predators within the invertebrate community, represented by the predatorratio, with an effect threshold range of 2.6 μg/L - 26 μg/L for Cu and 62 μg/L - 617 μg/L for Zn. These effect concentrations are in the ranges of the concentrations identified in model ecosystems and other field investigations and are just above the existing guideline limits. Heavy metals also affects the taxa richness negatively. Other community measures, such as the evenness, number of EPT (Ephemeroptera, Plecoptera, and Trichoptera) taxa, SPEcies At Risk (SPEAR)pesticides or SPEARsalinity were relatively poorly correlated with heavy metal toxicity in the streams. Therefore, we suggest applying the predatorratio within the community as a starting point for an indicator of the dissolved metal toxicity, the SPEARmetals.

Toxicity of environmentally realistic concentrations of chlorpyrifos and terbuthylazine in indoor microcosms

Few studies have been conducted into the evaluation of environmentally realistic pesticide mixtures using model ecosystems. In the present study, the effects of single and combined environmentally realistic concentrations of the herbicide terbuthylazine and the insecticide chlorpyrifos were evaluated using laboratory microcosms. Direct toxic effects of chlorpyrifos were noted on copepod nauplii and cladocerans and the recovery of the latter was likely related with the decrease observed in rotifer abundances. Terbuthylazine potentiated the effect of chlorpyrifos on feeding rates of Daphnia magna, presumably by triggering the transformation of chlorpyrifos to more toxic oxon-analogs. Possible food-web interactions resulting from multiple chemical (and other) stressors likely to be present in edge-of-field water bodies need to be further evaluated.

A value-oriented approach to business process specialization: Principles, proof-of-concept, and validation

A question-based method to specialize business processes is proposed.The method relies on REA business pattern.The process specialization is automated through model transformations.Empirical studies carried out both with practitioners and graduated students.The validation suggests that the models were correct from a business point of view. Organizations build information systems to support their business processes. Precise modeling of an organizations processes is a prerequisite for building information systems that support those processes. Our goal is to help business analysts produce detailed models of the business processes that best reflect the needs of their organizations. To this end, we propose to a) leverage the best practices in terms of a kernel of generic business processes, and b) provide analysts with tools to customize those processes by generating new process variants. We use business patterns from the Resource Event Agent ontology to identify variation points, and to codify the transformations inherent in the generation of the process variants. We developed a prototype process specialization tool using the Eclipse modeling ecosystem. We tested our approach on a set of processes from the Enterprise Resource Planning literature, and a set of variation points to assess the extent to which: 1) the identified variation points made sense, and 2) whether the generated variants made sense, from a business point of view. The results showed that 94.12% of the variation points made sense, and that 80.6% of the generated process variants corresponded to what the business process management specialists expected.

Much of Model Risk Does Not Come from Any Model

The use of financial models leads to model risk. Some of that risk comes from places in the “model ecosystem” other than the individual model itself. This article points out a few of those extra sources of model risk. Because financial models are always used as part of some financial business, even when each model has been validated successfully, there remain model risks coming from interactions with other parts of the business environment. The article discusses ecosystem risk, governance risk, data source risk, data integrity risk, new version risk, suitability risk, jurisdictional regulatory risk, assumption and override risk, multiple version risk, calibration risk, and model/nonmodel classification risk, with examples of each.

Coastal Ecosystem Effects of Increased Summer Temperature and Contamination by the Flame Retardant HBCDD

The combined effects of ocean warming and contaminants on marine ecosystems are poorly understood. In this study, we exposed model ecosystems comprising typical shallow coastal Baltic Sea communities to elevated temperature (+5 °C) and the flame retardant hexabromocyclododecane (HBCDD), both singly and in combination, for 13 days. Higher temperatures caused the release of PO4 from the sediment, which in turn stimulated the growth of the cyanobacteria Dolichospermum sp. This in turn led to an increase in the copepod Acartia bifilosa and other indirect effects in the plankton, interpreted as being caused by changes in predation, grazing, and competition. Elevated temperatures also stimulated benthic primary production and increased production of benthic mollusk larvae. Although increased temperature was the dominant driver of effects in these systems, HBCDD also appeared to have some effects, mainly in the zooplankton (both direct and indirect effects) and benthic meiofauna (an interactive effect with temperature). Although the study used model ecosystems, which are an approximation of field conditions, it highlights that interactive ecosystem effects between two stressors are possible and demonstrates the ecological and temporal complexity of such responses. Such unpredictable responses to warming and contaminants are a major challenge for ecosystem management to deal with multistressor situations in the Baltic Sea.

Limiting similarity of competitive species and demographic stochasticity

The limiting similarity of competitive species and its relationship with the competitive exclusion principle is still one of the most important concepts in ecology. In the 1970s, May [R. M. May, Stability and Complexity in Model Ecosystems (Princeton University, Princeton, NJ, 1973)] developed a concise theoretical framework to investigate the limiting similarity of competitive species. His theoretical results show that no limiting similarity threshold of competitive species can be identified in the deterministic model system whereby species more similar than this threshold never coexist. Theoretically, for competitive species coexisting in an unvarying environment, deterministic interspecific interactions and demographic stochasticity can be considered two sides of a coin. To investigate how the "tension" between these two forces affects the coexistence of competing species, a simple two-species competitive system based only on May's model system is transformed into an equivalent replicator equation. The effect of demographic stochasticity on the system stability is measured by the expected drift of the Lyapunov function. Our main results show that the limiting similarity of competitive species should not be considered to be an absolute measure. Specifically, very similar competitive species should be able to coexist in an environment with a high productivity level but big differences between competitive species should be necessary in an ecosystem with a low productivity level.

Habitat and Density of Oviposition Opportunity Influences Aedes aegypti (Diptera: Culicidae) Flight Distance.

Understanding the dispersal of Aedes (aegypti (L.) Diptera: Culicidae) after consuming a potentially infectious bloodmeal is an important part of controlling the spread of the arboviruses it transmits. Because of the impact on abundance, removal of oviposition sites is a key component of vector control. However, source reduction around a case may encourage dispersal of potentially infected vectors. We compare the effect of oviposition site availability on Ae. aegypti dispersal behavior within 30-m linear cages in three model ecosystems at the University of Arizona's Biosphere 2 research facility. We found a significant interaction effect in which, when oviposition site density was sparse, dispersal was greater in the highly vegetated humid rainforest and limited in the low vegetation, arid desert model ecosystem. When oviposition site density was dense, no significant effect on dispersal was observed. These analyses support the idea that source reduction has an important influence on the distance that gravid, potentially infected, females will travel.

Organismal and spatial partitioning of energy and macronutrient transformations within a hypersaline mat

Phototrophic mat communities are model ecosystems for studying energy cycling and elemental transformations because complete biogeochemical cycles occur over millimeter-to-centimeter scales. Characterization of energy and nutrient capture within hypersaline phototrophic mats has focused on specific processes and organisms; however, little is known about community-wide distribution of and linkages between these processes. To investigate energy and macronutrient capture and flow through a structured community, the spatial and organismal distribution of metabolic functions within a compact hypersaline mat community from Hot Lake have been broadly elucidated through species-resolved metagenomics and geochemical, microbial diversity and metabolic gradient measurements. Draft reconstructed genomes of 34 abundant organisms revealed three dominant cyanobacterial populations differentially distributed across the top layers of the mat suggesting niche separation along light and oxygen gradients. Many organisms contained diverse functional profiles, allowing for metabolic response to changing conditions within the mat. Organisms with partial nitrogen and sulfur metabolisms were widespread indicating dependence on metabolite exchange. In addition, changes in community spatial structure were observed over the diel. These results indicate that organisms within the mat community have adapted to the temporally dynamic environmental gradients in this hypersaline mat through metabolic flexibility and fluid syntrophic interactions, including shifts in spatial arrangements.

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes.

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual roots to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.

Characterization of phase transitions in a model ecosystem of sessile species.

We consider a model ecosystem of sessile species competing for space. In particular, we consider the system introduced by Mathiesen etal. [J. Mathiesen, N. Mitarai, K. Sneppen, and A. Trusina, Phys. Rev. Lett. 107, 188101 (2011)PRLTAO0031-900710.1103/PhysRevLett.107.188101] where species compete according to a fixed interaction network with links determined by a Bernoulli process. In the limit of a small introduction rate of new species, the model exhibits a discontinuous transition from a high-diversity state to a low-diversity state as the interaction probability between species, γ, is increased from zero. Here we explore the effects of finite introduction rates and system size on the phase transition by utilizing efficient parallel computing. We find that the low state appears for γ>γ_{c}. As γ is increased further, the high state approaches the low state, suggesting the possibility that the two states merge at a high γ. We find that the fraction of time spent in the high state becomes longer with higher introduction rates, but the availability of the two states is rather insensitive to the value of the introduction rate. Furthermore, we establish a relation between the introduction rate and the system size, which preserves the probability for the system to remain in the high-diversity state.

Simplified and representative bacterial community of maize roots

Plant-associated microbes are important for the growth and health of their hosts. As a result of numerous prior studies, we know that host genotypes and abiotic factors influence the composition of plant microbiomes. However, the high complexity of these communities challenges detailed studies to define experimentally the mechanisms underlying the dynamics of community assembly and the beneficial effects of such microbiomes on plant hosts. In this work, from the distinctive microbiota assembled by maize roots, through host-mediated selection, we obtained a greatly simplified synthetic bacterial community consisting of seven strains (Enterobacter cloacae, Stenotrophomonas maltophilia, Ochrobactrum pituitosum, Herbaspirillum frisingense, Pseudomonas putida, Curtobacterium pusillum, and Chryseobacterium indologenes) representing three of the four most dominant phyla found in maize roots. By using a selective culture-dependent method to track the abundance of each strain, we investigated the role that each plays in community assembly on roots of axenic maize seedlings. Only the removal of E. cloacae led to the complete loss of the community, and C. pusillum took over. This result suggests that E. cloacae plays the role of keystone species in this model ecosystem. In planta and in vitro, this model community inhibited the phytopathogenic fungus Fusarium verticillioides, indicating a clear benefit to the host. Thus, combined with the selective culture-dependent quantification method, our synthetic seven-species community representing the root microbiome has the potential to serve as a useful system to explore how bacterial interspecies interactions affect root microbiome assembly and to dissect the beneficial effects of the root microbiota on hosts under laboratory conditions in the future.

Invasive red swamp crayfish (Procambarus clarkii) and native noble crayfish (Astacus astacus) similarly reduce oligochaetes, epipelic algae, and meiofauna biomass: a microcosm study

AbstractHuman activities have led to the decline of native crayfish and promoted dispersion of invasive species in European freshwater ecosystems. Crayfish are well-known predators of benthic macroinvertebrates, but benthic communities in aquatic ecosystems also include an abundant and functionally important meiofaunal component. For these organisms, the effects of invasive and native crayfish species are poorly understood. In this study, the effects of predation by the invasive red swamp crayfish (Procambarus clarkii) and the native noble crayfish (Astacus astacus) on the density, biomass, and secondary production of meiofaunal assemblages were compared in a model ecosystem experiment. Both crayfish species reduced the overall density of oligochaetes; the biomasses of total meiofauna, oligochaetes, and microcrustaceans; and secondary production by total meiofauna and oligochaetes. Nematodes and rotifers were unaffected by either crayfish species. An analysis of the gut contents of P. clarkii and A. astac...

The application of satellite-based model and bi-stable ecosystem balance concept to monitor desertification in arid lands, a case study of Sinai Peninsula

Desertification is responsible for depleting natural resources in arid lands, which is globally happening in an alarming rate. It is considered as the major environmental threat that affects about 40% of the world dry lands, which are populated by approximately one billion humans. In this paper the main objective is to discuss the recent and past research in monitoring and assessing desertification and land degradation using remote sensing technology and data. Recently, the Bi-stable ecosystem balance becomes a promising framework theory to detect the spatial extent of prime land degradation in arid and semi-arid environments; it is also a potential methodology to recognize the difference between the natural variability and instantaneous/non-instantaneous desertification symptoms in dry lands. The satellite-based models are the future tools for monitoring very precisely desertification development, MODerate resolution Imaging Spectroradiometer (MODIS) satellite images are becoming the best datasets for building regional desertification monitoring algorithms because of its temporal scales (8–16 days). The MODIS Based Disturbance Index (MBDI) algorithm provide accurate information at six different study sites in Sinai Peninsula and showed the seasonal and yearly changes. This application can be used for monitoring decades of desertification development in North Africa, South Europe, and the Middle East, and can be linked to several fields such as agriculture sustainability, environmental conservations, rural development, and economics.

Special issue: Leveraging modeling and simulation as a service for the future modeling and simulation eco-system

Special issue: Leveraging modeling and simulation as a service for the future modeling and simulation eco-system