Ecosystem services as a counterpart of emergy flows to ecosystems

A generic input-state-output scheme has been used to represent ecosystem dynamics. Systemic approaches to ecosystems use functions that are based either on inputs, state or outputs of the system. Some examples of approaches that use a combination of functions have been recently proposed. For example the use of eco-exergy to emergy flow can be seen as a mixed input-state approach; more recently, to connect the state to the output of the ecosystem, the relation of eco-exergy and ecosystems services has been proposed. This paper studies the link between the useful output of an ecosystems and its input through the relation between ecosystem services and emergy flow, in a kind of grey/black box scheme (i.e., without considering the state and the structure of the ecosystem). No direct connection between the two concepts can be determined, but identifying and quantifying the emergy flows feeding an ecosystem and the services to humans coming from them facilitate the sustainable conservation of Nature and its functions. Furthermore, this input-output relation can be established in general by calculating the ratio of the value of the ecosystem services to the emergy flow that supports the system. In particular, the ratio of the world ecosystem services to the emergy flow supporting the entire biosphere has been calculated showing that, at least at the global level, Nature is more efficacious in producing “money” (in form of ecosystem services) than economic systems (e.g., national economies and their GDP).     

The free energy and information embodied in the amino acid chains of organisms

It is generally accepted as a useful and workable hypothesis that when an ecosystem receives an inflow of exergy (energy that can do work) it will utilize this flow of exergy to move as far away from thermodynamic equilibrium as possible after the exergy (energy) for maintenance has been covered. If more combinations of system components including organisms are offered, the combination of components and processes that will bring the system most away from thermodynamic equilibrium will win.The amino acid sequences of the proteins e.g. enzymes determine and control the life processes of the organisms and may be viewed as information sensu lato. The free energy of oxidation of the amino acids and the peptide bonds of the cell enzymes expresses therefore the exergy content, eco-exergy or work capacity that the information contributes to “moving further away from thermodynamic equilibrium”. In this paper eco-exergy is calculated and plotted versus the β-values (a measure of the information contained in the genome) for different organisms. The eco-exergy density was previously (see [J?rgensen et al., 1995] and [J?rgensen et al., 2005]) proposed to be calculated as the summation of the product of the β-values representing the information of the genome multiplied by the concentrations of the respective ecosystem components. This analysis shows a strong correlation between the β-values and free energy released when oxidizing the enzymes. The β-values can therefore be assumed to represent the free energy that the organisms have invested in genetic information.     

Application of eco-exergy for assessment of ecosystem health and development of structurally dynamic models

Eco-exergy has been widely used in the assessment of ecosystem health, parameter estimations, calibrations, validations and prognoses. It offers insights into the understanding of ecosystem dynamics and disturbance-driven changes. Particularly, structurally dynamic models (SDMs), which are developed using eco-exergy as the goal function, have been applied in explaining and exploring ecosystem properties and changes in community structure driven by biotic and abiotic factors. In this paper, we review the application of eco-exergy for the assessment of ecosystem health and development of structurally dynamic models (SDMs). The limitations and possible future applications of the approach are also addressed.     

Quantifying the sustainability of water use systems: Calculating the balance between network efficiency and resilience

In ecological network theory, network efficiency and resilience are two essential but complementary attributes of the network structure, and a balance between these factors is critical for an ecosystem's long-term sustainability. Our paper introduces this method and related concepts into water use systems to provide a new angle for sustainability quantification. In this paper, we investigate the meanings of network efficiency and resilience in the context of sustainable development of water use systems, and define sustainable systems based on the optimal balance between network efficiency and resilience. With the consideration of complex artificial characteristics of water use, we propose an optimal water use network and quantify its flows. By ascendency calculation, the balanced network structure can be determined. We then use the four sub-basins of China's Haihe River as a case study to illustrate how the optimal network can be constructed and how the optimal balance for each scenario can be calculated. The results show that the optimal balance for the sub-basins has ascendency values ranging from 0.5970 to 0.7161. By analyzing the contribution of each water use activity to network's balance structure, the location of the optimal balance in water use systems can be better understood. This research represents the first attempt to explore the balance between a network structure's efficiency and resilience as a way to quantify the sustainability of water use systems, and builds a foundation for future studies on the assessment, regulation, and management of water resources.     

Dynamic model of Lake Chozas (León, NW Spain)—Decrease in eco-exergy from clear to turbid phase due to introduction of exotic crayfish

We developed a dynamic model of the phosphorus cycle in Lake Chozas, a small shallow water body in León (NW Spain). The calibrated model simulated seasonal dynamics of phosphorus concentrations in major components of the lake's ecological network before and after 1997, the year when an invasive allochthonous crustacean, the Louisiana red swamp crayfish (Procambarus clarkii), was introduced into the lake. The shift from clean to turbid phase, due to grazing by crayfish on submerged vegetation, caused a gradual decrease in eco-exergy, reflecting an increase in entropy, related to breakdown of ecosystem internal equilibria. This case study verifies the hypothesis of Marchi et al. (2010) that, after an initial relatively stable state, the allochthonous species may cause an increase in entropy indicating perturbation of the ecosystem.     

Resistance and re-organization of an ecosystem in response to biological invasion: Some hypotheses

Using a dynamic model of Lake Chozas developed by Marchi et al. (2011), we tested three hypotheses about recovery of the indigenous community and water quality after radical changes caused by introduction of an invasive allochthonous crayfish, Procambarus clarkii:

1.

Can the lake resist the pressure of an invasive species, like P. clarkii, by adaptation?

2.

Can the ecosystem recover when all the crayfish are removed and low phosphorus concentrations persist in inflow water?

3.

Does the simulated recovery of submerged vegetation occur at a total phosphorus concentration below 100 mg TP m⁻³, as estimated by Scheffer et al. (1993), Scheffer (1997), Jeppesen et al. (1998) and Zhang et al. (2003)?

We obtained the following answers:

1.

Lake Chozas can at least partly resist by adaptation. A combination of possible parameter changes could lead to a significant increase in eco-exergy.

2.

Removal of the phosphorus represented by crayfish (by harvesting) implies complete recovery of the lake and its eco-exergy, albeit not necessarily with the same organisms having the same properties.

3.

The expected hysteresis created by introduction and harvesting of crayfish is observed under the following conditions: phytoplankton dominance at total phosphorus ≥ about 200-250 mg TP m⁻³ and submerged vegetation returns at total phosphorus < 100 mg TP m⁻³.

     

Ecological network analysis: network construction

Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but the additional challenge is that the data need to characterize an entire ecosystem's flows and storages. Thus, data requirements are substantial. As a result, there have, in fact, not been a significant number of network models constructed and development of the network analysis methodology has progressed largely within the purview of a few established models. In this paper, we outline the steps for one approach to construct network models. Lastly, we also provide a brief overview of the algorithmic methods used to construct food web typologies when empirical data are not available. It is our aim that such an effort aids other researchers to consider the construction of such models as well as encourages further refinement of this procedure.     

The effects of aggregation on the performance of the inverse method and indicators of network analysis

Food webs are usually aggregated into a manageable size for their interpretation and analysis. The aggregation of food web components in trophic or other guilds is often at the choice of the modeler as there is little guidance in the literature as to what biases might be introduced by aggregation decisions. We examined the impacts of the choice of the a priori model on the subsequent estimation of missing flows using the inverse method and on the indices derived from ecological network analysis of both inverse method-derived flows and on the actual values of flows, using the fully determined Sylt-Rømø Bight food web model. We used the inverse method, with the least squares minimization goal function, to estimate ‘missing’ values in the food web flows on 14 aggregation schemes varying in number of compartments and in methods of aggregation. The resultant flows were compared to known values; the performance of the inverse method improved with increasing number of compartments and with aggregation based on both habitat and feeding habits rather than diet similarity. Comparison of network analysis indices of inverse method-derived flows with that of actual flows and the original value for the unaggregated food web showed that the use of both the inverse method and the aggregation scheme affected indices derived from ecological network analysis. The inverse method tended to underestimate the size and complexity of food webs, while an aggregation scheme explained as much variability in some network indices as the difference between inverse-derived and actual flows. However, topological network indices tended to be most robust to both the method of determining flows and to the inverse method. These results suggest that a goal function other than minimization of flows should be used when applying the inverse method to food web models. Comparison of food web models should be done with extreme care when different methodologies are used to estimate unknown flows and to aggregate system components. However, we propose that indices such as relative ascendency and relative redundancy are most valuable for comparing ecosystem models constructed using different methodologies for determining missing flows or for aggregating system components.     

The role of conjugation in the gene-individual-population relationships in increasing eco-exergy

The genotypic and phenotypic processes were incorporated into one system in the gene-individual-population relationships under the framework of Individual based models (IBMs). The gene types addressing different degrees of metabolic efficiency and toxin susceptibility were provided as attributes in the individuals. Subsequently ecological processes such as food competition and movement were allowed concurrently on the 2-D space to determine the suitable species adapted to the system. The integrative gene-individual-population model accordingly responded to gene exchanges between the neighboring individuals through conjugation. At a substantially low level of gene exchange, system heterogeneity increased to produce high levels of eco-exergy, being presented by species diversity and total population size in the system. The issues related to genetic and ecological effects in the integrative gene-individual-population relationships were further discussed.     

Ecological network analysis for water use systems—A case study of the Yellow River Basin

Ecological network analysis (ENA) is introduced in this paper as a promising approach to study water use systems. Information indices from ENA involving total system throughput (TST), ascendency and overhead are calculated here. Two related aspects including organization inherent in system structures and synthesized water use intensity related with sustainable development of water use systems are analyzed. The indices of ascendency and overhead are applied for analyzing and characterizing water use network organization. For comparison of sustainability of water use systems from integrated aspects of environment, society and economy and based on TST, a new indicator termed as total system throughput intensity (TSTI) is constructed incorporating parameters of land, precipitation, population, GDP and environmental flow, which can be used as a measure of sustainability in terms of synthesized water use intensity. The Yellow River Basin in China during 1998–2006 is chosen as the case study and divided into subsystems according to the six river sections as from source to Lanzhou (S1-L1), Lanzhou to Toudaoguai (L1-T), Toudaoguai to Longmen (T-L2), Longmen to Sanmenxia (L2-S2), Sanmenxia to Huayuankou (S2-H) and Huayuankou to the mouth of Bo Sea (H-B). The results show that (i) the organization levels of L1-T and H-B are better than those of S1-L1 and T-L2, with those of L2-S2 and S2-H the worst; (ii) the synthesized water use intensity has been improving, of which T-L2, L2-S2 and S2-H are at the highest levels while H-B the lowest. In addition, the comparison between TSTI and other metrics and the relationship between ascendency and TSTI are discussed, from which the importance of TSTI is reflected and the optimization criterions for sustainable development of six subsystems are derived. It can be concluded that the application of ENA in water use systems can provide new angles for water resource management to address the challenges of assessing and optimizing options to obtain more sustainable water use.     

Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay

Ecosystem components interact in complex ways and change over time due to a variety of both internal and external influences (climate change, season cycles, human impacts). Such processes need to be modeled dynamically using appropriate statistical methods for assessing change in network structure. Here we use visualizations and statistical models of network dynamics to understand seasonal changes in the trophic network model described by Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329–364] for the Chesapeake Bay (USA). Visualizations of carbon flow networks were created for each season by using a network graphic analysis tool (NETDRAW). The structural relations of the pelagic and benthic compartments (nodes) in each seasonal network were displayed in a two-dimensional space using spring-embedder analyses with nodes color-coded for habitat associations (benthic or pelagic). The most complex network was summer, when pelagic species such as sea nettles, larval fishes, and carnivorous fishes immigrate into Chesapeake Bay and consume prey largely from the plankton and to some extent the benthos. Winter was the simplest of the seasonal networks, and exhibited the highest ascendency, with fewest nodes present and with most of the flows shifting to the benthic bacteria and sediment POC compartments. This shift in system complexity corresponds with a shift from a pelagic- to benthic-dominated system over the seasonal cycle, suggesting that winter is a mostly closed system, relying on internal cycling rather than external input. Network visualization tools are useful in assessing temporal and spatial changes in food web networks, which can be explored for patterns that can be tested using statistical approaches. A simulation-based continuous-time Markov Chain model called SIENA was used to determine the dynamic structural changes in the trophic network across phases of the annual cycle in a statistical as opposed to a visual assessment. There was a significant decrease in outdegree (prey nodes with reduced link density) and an increase in the number of transitive triples (a triad in which i chooses j and h, and j also chooses h, mostly connected via the non-living detritus nodes in position i), suggesting the Chesapeake Bay is a simpler, but structurally more efficient, ecosystem in the winter than in the summer. As in the visual analysis, this shift in system complexity corresponds with a shift from a pelagic to a more benthic-dominated system from summer to winter. Both the SIENA model and the visualization in NETDRAW support the conclusions of Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329–364] that there was an increase in the Chesapeake Bay ecosystem's ascendancy in the winter. We explain such reduced complexity in winter as a system response to lowered temperature and decreased solar energy input, which causes a decline in the production of new carbon, forcing nodes to go extinct; this causes a change in the structure of the system, making it simpler and more efficient than in summer. It appears that the seasonal dynamics of the trophic structure of Chesapeake Bay can be modeled effectively using the SIENA statistical model for network change.     

Ecological network analysis of an urban energy metabolic system: Model development, and a case study of four Chinese cities

Urban metabolism research faces difficulties defining ecological trophic levels and analyzing relationships among the metabolic system's energy components. Here, we propose a new way to perform such research. By integrating throughflow analysis with ecological network utility analysis, we used network flows to analyze the metabolic system's network structure and the ecological relationships within the system. We developed an ecological network model for the system, and used four Chinese cities as examples of how this approach provides insights into the flows within the system at both high and low levels of detail. Using the weight distribution in the network flow matrix, we determined the structure of the urban energy metabolic system and the trophic levels; using the sign distribution in the network utility matrix, we determined the relationships between each pair of the system's compartments and their degrees of mutualism. The model uses compartments based on 17 sectors (energy exploitation; coal-fired power; heat supply; washed coal; coking; oil refinery; gas generation; coal products; agricultural; industrial; construction; communication, storage, and postal service; wholesale, retail, accommodation, and catering; household; other consuming; recovery; and energy stocks). Analyzing the structure and functioning of the urban energy metabolic system revealed ways to optimize its structure by adjusting the relationships among compartments, thereby demonstrating how ecological network analysis can be used in future urban system research.     

Evaluating the dimensionality and significance of “active periods” in turbulent environmental flows defined using Lipshitz/Hölder regularity

Active periods within perturbed boundary-layer flows are considered in terms of the local roughness of measured velocity time series and defined in terms of Hölder/Lipshitz exponents. Such events are associated with the passage of energetic, coherent flow structures and are responsible for exerting high turbulent stresses because of the rapid changes in velocity that occur at such times. A method is proposed for assessing the effective dimensionality of such active periods, as well as their significance to the flow field, for a particular choice of flow metric. The method is applied to the turbulent flow through a confluence flow geometry, with velocity samples acquired close to the bed of the channel in a zone of complex mixing. The dimensionality of the active periods is consistent with the observed patterns of sediment entrainment from the bed, with the significance of the active periods decaying away from the erosional zone.     

Analytical evaluation of mesoscale fluxes and pressure field

Terrain in natural areas is never homogeneous: there may be a variety of vegetation types and patches of vegetated and unvegetated areas which can modify the mesoscale atmospheric flow. Moreover, horizontal thermal inhomogeneities in the planetary boundary layer are a well known source of mesoscale circulation systems such as land and sea breezes, mountain-valley winds, and urban heat island circulations. Since those phenomena are not resolved in regional scale numerical models, therefore an analytic procedure able to evaluate the relative importance of mesoscale and turbulent heat fluxes associated with surface thermal heterogeneities is of crucial importance in the optic of developing a parameterization of mesoscale effects generated by these heterogeneities for use in larger scale models. In the present paper we analyze how small a horizontal variation in surface heating can be and still produce a significant mesoscale circulation, how the heat and momentum fluxes associated to mesoscale flows can penetrate deeply into the mid-troposphere, and how they modify tropospheric relevant climate parameters, such as the atmospheric static stability. In addition, we evaluate the terms of the pressure gradient force, nonlinear and linear, non-hydrostatic and hydrostatic, as function of time and space scales of the mesoscale flow. The present paper is mainly a review of analytical results, the numerical comparison and verification using RAMS is in progress.     

大兴安岭南部温带山杨天然次生林不同生长阶段生物量及碳储量

基于内蒙古赛罕乌拉森林生态系统定位研究站山杨（Populus davidiana Dode）天然次生林幼龄林、中龄林、近熟林、成熟林及过熟林生物量调查,探讨了不同龄组山杨天然次生林单株木、林分、林下植被和枯落物的生物量及群落碳储量的时空变化规律。结果表明：随林龄的增大,山杨天然次生林木和各器官生物量总体呈增加趋势,树干所占比例增加,中龄林增加尤为明显;林下植被层、枯落物层生物量随林龄增大呈增加趋势。群落总碳储量的空间分布序列是：乔木层〉枯落物层〉林下植被层。幼龄林、中龄林、近熟林、成熟林和过熟林群落的碳储量分别为27.146 6、53.545 1、60.889 8、77.915 8、79.135 3t.hm-2,乔木层碳储量分别为22.206 5、47.215 7、52.056 3、68.445 3、68.773 1 t.hm-2,枯落物层和林下植被层碳储量平均值分别为5.814 4、2.172 7 t.hm-2。乔木层、枯落物层和林下植被层碳储量占总量的平均率分别为86.05%、10.39%和3.57%。研究认为山杨天然次生林群落碳储量随林龄增加的变化规律明显,碳汇潜力巨大;中龄林为碳储量增长迅速期,且持续较长一段时间,是林分管理的关键阶段;自然稀疏有利于促进林木生长,林分碳储量并未随林分密度下降而减小。     

Dynamic environ analysis of compartmental systems: A computational approach

Ecosystems are often modeled as stocks of matter or energy connected by flows. Network environ analysis (NEA) is a set of mathematical methods for using powers of matrices to trace energy and material flows through such models. NEA has revealed several interesting properties of flow–storage networks, including dominance of indirect effects and the tendency for networks to create mutually positive interactions between species. However, the applicability of NEA is greatly limited by the fact that it can only be applied to models at constant steady states. In this paper, we present a new, computationally oriented approach to environ analysis called dynamic environ approximation (DEA). As a test of DEA, we use it to compute compartment throughflow in two implementations of a model of energy flow through an oyster reef ecosystem. We use a newly derived equation to compute model throughflow and compare its output to that of DEA. We find that DEA approximates the exact results given by this equation quite closely – in this particular case, with a mean Euclidean error ranging between 0.0008 and 0.21 – which gives a sense of how closely it reproduces other NEA-related quantities that cannot be exactly computed and discuss how to reduce this error. An application to calculating indirect flows in ecosystems is also discussed and dominance of indirect effects in a nonlinear model is demonstrated.     

Near-critical free-surface flows: real fluid flow analysis

An open channel flow with a flow depth close to the critical depth is characterised by a curvilinear streamline flow field that results in steady free surface undulations. Near critical flows of practical relevance encompass the undular hydraulic jump when the flow changes from supercritical (F > 1) to subcritical (F < 1), and the undular weir flow over broad-crested weirs where the flow changes from subcritical (F < 1) to supercritical (F > 1). So far these flows were mainly studied based on ideal fluid flow computations, for which the flow is assumed irrotational and, thus, shear forces are absent. While the approach is accurate for critical flow conditions (F = 1) in weir and flumes, near-critical flows involve long distances reaches, and the effect of friction on the flow properties cannot be neglected. In the present study the characteristics of near-critical free-surface flows are reanalysed based on a model accounting for both the streamline curvature and friction effects. Based on the improved model, some better agreement with experimental results is found, thereby highlighting the main frictional features of the flow profiles.     

Environ indicator sensitivity to flux uncertainty in a phosphorus model of Lake Sidney Lanier, USA

Effective environmental impact assessment and management requires improved understanding of the organization and transformation of ecosystems in which independent agents are linked through an intricate network of energy, matter, and informational interactions. While advances have been made, we still lack a complete understanding of the processes that create, constrain, and sustain ecosystems. Network environ analysis (NEA) provides one approach for building novel ecosystem insights, but it is model dependent. As ecological modeling is an imprecise art, often complicated by inadequate empirical data, the utility of NEA may be limited by model uncertainty. Here, we investigate the sensitivity of NEA indicators of ecosystem growth and development to flow and storage uncertainty in a phosphorus model of Lake Sidney Lanier, USA. The indicators are total system throughflow (TST), total system storage (TSS), total boundary input (Boundary), Finn cycling index (FCI), ratio of indirect-to-direct flows (Indirect/Direct), indirect flow index (IFI), network aggradation (AGG), network homogenization (HMG), and network amplification (AMP). Our results make two primary contributions. First, they demonstrate that five of the indicators – FCI, Indirect/Direct, IFI, AGG and HMG – are relatively robust to the flow and storage uncertainty in the Lake Lanier model. This stability lets us draw robust conclusions about the Lake Lanier ecosystem organization (e.g., phosphorus flux in the lake is dominated by internal processes) in spite of uncertainties in the model. Second, we show that the majority of the indicators co-vary and that most of their common variation could be mapped onto two latent factors, which we interpret as (1) system integration and (2) boundary influences.     

Information indices as a tool for quantifying development of below-ground terrestrial ecosystems

Information indices from ecosystem network analysis (ENA) describe the size and organization of an ecosystem and are claimed to quantify ecosystem development [Ulanowicz, R.E., 1986, Growth and Development, Springler-Verslag, New York, 203 pp.]. To date, these indices were not used to describe a gradient of ecosystem development for a field situation. Here we used information indices to quantify soil succession with soils of different age on the island Schiermonnikoog, The Netherlands. We evaluated whether information indices describe ecosystem development as predicted by ENA.For the Island of Schiermonnikoog the biomasses of soil organisms and roots were measured on four stages of succession (0, 10, 25 and 100 years old soils). Organisms were grouped based on their feeding characteristics. With these data consumption, respiration, excretion, external input and output flows to, from and between groups were calculated. These flows, in turn, were used to calculate the information indices. Relative information indices describe the organization of an ecosystem; i.e. level of organisation (specialization of flows), diversity and evenness of flows, and disorganisation. Absolute indices describe both size (in terms of energy flow) and organisation of the system. System size is used to scale the absolute indices and will be analysed separately as well.We found that the absolute indices increased when succession processed, as predicted by theory. This pattern could have been due to the build-up of biomass, which apparently did not level off. Because the succession gradient deals mostly with young soils (0, 10 and 25 years old) and only one older field (100 years old), the gradient should include more soils of around 100 years old and older to exclude this possibility. Relative indices, on the other hand, increased initially, but then levelled off. We think that this was due to the strong aggregation of functional groups, especially at lower trophic levels, because information in some functional groups showed (expected) trends.Our results suggest that the absolute indices are able to describe ecological succession of terrestrial below-ground ecosystems. The relative indices, in contrast, appeared to be insensitive to subtle succesional changes.