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.     

Comparative network analysis toward characterization of systemic organization for human–environmental sustainability

A preliminary study in comparative ecological network analysis was conducted to identify key assumptions and methodological challenges, test initial hypotheses and explore systemic and network structural characteristics for environmentally sustainable ecosystems. A nitrogen network for the U.S. beef supply chain – a small sub-network of the industrial food system analyzed as a pilot study – was constructed and compared to four non-human carbon and nitrogen trophic networks for the Chesapeake Bay and the Florida Everglades. These non-human food webs served as sustainable reference systems. Contrary to the main original hypothesis, the “window of vitality” and the number of network roles did not clearly differentiate between a human sub-network and the more complete non-human networks. The effective trophic level of humans (a partial estimate of trophic level based on the single food source of beef) was much higher (8.1) than any non-human species (maximum of 4.88). Network connectance, entropy, total dependency coefficients, trophic efficiencies and the ascendency to capacity ratio also indicated differences that serve as hypotheses for future tests on more comprehensive human food webs. The study elucidated important issues related to (1) the steady state assumption, which is more problematic for industrial human systems, (2) the absence or dearth of data on contributions of dead humans and human wastes to feed other species in an integrated food web, (3) the ambiguity of defining some industrial compartments as living versus non-living, and (4) challenges with constructing compartments and trophic transfers in industrial versus non-human food webs. The two main novel results are (1) the progress made toward adapting ecological network analysis (ENA) methodology for analysis of human food networks in industrial cultures and (2) characterizing the critical aspects of comparative ENA for understanding potential causes of the problems, and providing avenues for solutions, for environmental sustainability. Based on this work, construction and comparative network analysis of a more comprehensive industrial human food network seems warranted and likely to provide valuable insights for modifying structures of industrial food networks to be more like natural networks and more sustainable.     

What is hidden behind the concept of ecosystem efficiency in energy transformation?

The number of energy transformation levels in trophic webs is usually below five, but can be extended up to ten when parasites and hyper-parasites are included. Research on the structure and function of food webs is relevant to the complexity–stability–productivity debate. The aim of this theoretical analysis is to link energetic and connectional aspects of ecosystems with information theory. Updating an energetic model reported by Ricklefs [Ecologia, Zanichelli Editore S.p.A., Bologna, Italy, 1993, p. 896], our approach is integrated with a static analysis of food webs. The length of food webs is theoretically associated with the average ecological efficiency which can be empirically correlated with the effective connectance between species. Furthermore, the advantage of greater complexity when applied to a signalling network is qualitatively addressed.The overall efficiency of energy transformation into biomass throughout a trophic web, in an ecosystem with a given number of species, is the resultant of the various ecological efficiencies, η, at the transitions between the trophic levels. However, we propose that an increment in effective connectance and interspecies connectivity based on a superimposed signalling web may increase the η values, despite the fact that signalling per se has an energetic cost. According to this hypothesis, ecosystem stability would not be necessarily reduced by increasing the number of trophic levels, N, whenever stability in terms of persistence is improved by a cost-efficient regulatory network.     

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.     

Origin of compartmentalization in food webs

The response of an ecosystem to perturbations is mediated by both antagonistic and facilitative interactions between species. It is thought that a community's resilience depends crucially on the food web--the network of trophic interactions--and on the food web's degree of compartmentalization. Despite its ecological importance, compartmentalization and the mechanisms that give rise to it remain poorly understood. Here we investigate several definitions of compartments, propose ways to understand the ecological meaning of these definitions, and quantify the degree of compartmentalization of empirical food webs. We find that the compartmentalization observed in empirical food webs can be accounted for solely by the niche organization of species and their diets. By uncovering connections between compartmentalization and species' diet contiguity, our findings help us understand which perturbations can result in fragmentation of the food web and which can lead to catastrophic effects. Additionally, we show that the composition of compartments can be used to address the long-standing question of what determines the ecological niche of a species.     

Invasive species impacts on ecosystem structure and function: A comparison of the Bay of Quinte, Canada, and Oneida Lake, USA, before and after zebra mussel invasion

As invasion rates of exotic species increase, an ecosystem level understanding of their impacts is imperative for predicting future spread and consequences. We have previously shown that network analyses are powerful tools for understanding the effects of exotic species perturbation on ecosystems. We now use the network analysis approach to compare how the same perturbation affects another ecosystem of similar trophic status. We compared food web characteristics of the Bay of Quinte, Lake Ontario (Canada), to previous research on Oneida Lake, New York (USA) before and after zebra mussel (Dreissena polymorpha) invasion. We used ecological network analysis (ENA) to rigorously quantify ecosystem function through an analysis of direct and indirect food web transfers. We used a social network analysis method, cohesion analysis (CA), to assess ecosystem structure by organizing food web members into subgroups of strongly interacting predators and prey. Together, ENA and CA allowed us to understand how food web structure and function respond simultaneously to perturbation. In general, zebra mussel effects on the Bay of Quinte, when compared to Oneida Lake, were similar in direction, but greater in magnitude. Both systems underwent functional changes involving focused flow through a small number of taxa and increased use of benthic sources of production; additionally, both systems structurally changed with subgroup membership changing considerably (33% in Oneida Lake) or being disrupted entirely (in the Bay of Quinte). However, the response of total ecosystem activity (as measured by carbon flow) differed between both systems, with increasing activity in the Bay of Quinte, and decreasing activity in Oneida Lake. Thus, these analyses revealed parallel effects of zebra mussel invasion in ecosystems of similar trophic status, yet they also suggested that important differences may exist. As exotic species continue to disrupt the structure and function of our native ecosystems, food web network analyses will be useful for understanding their far-reaching effects.     

Do microbial processes regulate the stability of a coral atoll's enclosed pelagic ecosystem?

Complex marine ecosystems contain multiple feedback cycles that can cause unexpected responses to perturbations. To better predict these responses, complicated models are increasingly being developed to enable the study of feedback cycles. However, the sparseness of ecological data often limits the direct empirical parameterization of all model parameters. Here we use a Bayesian inverse analysis approach to synthesize empirical data and ecological theory derived from published studies of a coral atoll's enclosed pelagic ecosystem (Takapoto Atoll, French Polynesia). We then use the estimates of flux magnitudes to parameterize probabilistic compartment models with two forms of heterotrophic consumption: (1) “bottom-up” donor-controlled heterotrophic consumption and (2) “top-down” mass-action heterotrophic consumption. We explore how the flux magnitudes affect the ecosystem's stability properties of resilience, reactivity, and resistance under both assumptions for heterotrophic consumption. The models suggest that the microbial uptake of dissolved organic carbon (DOC) regulates the long term rate of return to steady state following a temporary or pulse perturbation (resilience), and the cycling of carbon between abiotic pools and heterotrophic compartments regulates the short-term response (reactivity). In the bottom-up process model, the sensitivity of steady state masses following a sustained or press perturbation (resistance) is highest for the DOC pool following a sustained change to the microbial uptake rate of DOC. Further, a change in the microbial uptake of DOC propagates through the ecosystem and affects the steady state values of zooplankton. The analysis suggests that the food web is highly dependent on the recycling between the abiotic and biotic carbon pools, particularly as mediated by the microbial consumption of DOC, and this recycling determines how the ecosystem responds to perturbations.     

Trophic food web and ecosystem attributes of a water reservoir of the Ria Formosa (south Portugal)

Using a top-down modelling approach, a balanced trophic food web model of a water reservoir of the Ria Formosa lagoonal system was constructed. Few adjustments of input data were necessary to run the model since most of the parameters were estimated at the study site and the characteristics of the water reservoir allowed a high degree of control and precision in terms of sampling and data collection. Trophic levels of the 14 compartments included in the model varied between 1.0 for primary producers and detritus to 3.4 for carnivorous fish and the 14 groups were aggregated in a food chain with six trophic levels. The water reservoir has a detritus based food chain, with the majority of the biomass concentrated in the first two levels, the producers level and the herbivore/detritivore level (97.6%). The transfer efficiencies were low, and decreased with increasing level number, varying between 6.0 and 0.2%. The degree of “ecosystem maturity” was difficult to establish, but several parameters indicate that it could be high. The water reservoir studied, which has similar environmental and ecological characteristics as the Ria Formosa lagoon, is near its carrying capacity.     

Implications of network particle tracking (NPT) for ecological model interpretation

Network particle tracking (NPT), building on the foundation of network environ analysis (NEA), is a new development in the definition of coherence relations within and between connected systems. This paper evaluates three ecosystem models in a comparison of throughflow- and storage-based NEA and NPT. Compartments in models with high indirect effects and Finn cycling showed low correlation of NEA storage and throughflow with particle repeat visits and numbers of particles in compartments at steady state. Conversely, the correlation between NEA and NPT results was high with two models having lower indirect effects and Finn cycling. Analysis of ecological orientors associated with NEA showed NPT to fully support conventional NEA results when the common conditions of donor control and steady state are satisfied. Particle trajectories are recorded in the new concept of a particle “passport”. Ability to track and record particle in-system histories enables views of multiple scales and opens the possibility of making pathway-dependent modeling decisions. NPT may also enable modeling of time, allowing integration of Newtonian, organismal and stochastic modeling perspectives in a single comprehensive analysis.     

Response of balanced network models to large-scale perturbation: Implications for evaluating the role of small pelagics in the Gulf of Maine

Exploring the response of an ecosystem, and subsequent tradeoffs among its biological community, to human perturbations remains a key challenge for the implementation of an ecosystem approaches to fisheries (EAF). To address this and related issues, we developed two network (or energy budget) models, Ecopath and Econetwrk, for the Gulf of Maine ecosystem. These models included 31 network “nodes” or biomass state variables across a broad range of trophic levels, with the present emphasis to particularly elucidate the role of small pelagics. After initial network balancing, various perturbation scenarios were evaluated to explore how potential changes to different fish, fisheries and lower trophic levels can affect model outputs. Categorically across all scenarios and interpretations thereof, there was minimal change at the second trophic levels and most of the “rebalancing” after a perturbation occurred via alteration of the diet matrix. Yet the model results from perturbations to a balanced energy budget fall into one of three categories. First, some model results were intuitive and in obvious agreement with established ecological and fishing theory. Second, some model results were counter-intuitive upon initial observation, seemingly contradictory to known ecological and fishing theory; but upon further examination the results were explainable given the constraints of an equilibrium energy budget. Finally, some results were counter-intuitive and difficult to reconcile with theory or further examination of equilibrium constraints. A detailed accounting of biomass flows for example scenarios explores some of the non-intuitive results more rigorously. Collectively these results imply a need to carefully track biomass flows and results of any given perturbation and to critically evaluate the conditions under which a new equilibrium is obtained for these types of models, which has implications for dynamic simulations based off of them. Given these caveats, the role of small pelagics as a prominent component of this ecosystem remains a robust conclusion. We discuss how one might use this approach in the context of further developing an EAF, recognizing that a more holistic, integrated perspective will be required as we continue to evaluate tradeoffs among marine biological communities.     

Invasive species impacts on ecosystem structure and function: A comparison of Oneida Lake, New York, USA, before and after zebra mussel invasion

Exotic species invasion is widely considered to affect ecosystem structure and function. Yet, few contemporary approaches can assess the effects of exotic species invasion at such an inclusive level. Our research presents one of the first attempts to examine the effects of an exotic species at the ecosystem level in a quantifiable manner. We used ecological network analysis (ENA) and a social network analysis (SNA) method called cohesion analysis to examine the effect of zebra mussel (Dreissena polymorpha) invasion on the Oneida Lake, New York, USA, food web. We used ENA to quantify ecosystem function through an analysis of food web carbon transfer that explicitly incorporated flow over all food web paths (direct and indirect). The cohesion analysis assessed ecosystem structure through an organization of food web members into subgroups of strongly interacting predators and prey. Our analysis detected effects of zebra mussel invasion throughout the entire Oneida Lake food web, including changes in trophic flow efficiency (i.e., carbon flow among trophic levels) and alterations of food web organization (i.e., paths of carbon flow) and ecosystem activity (i.e., total carbon flow). ENA indicated that zebra mussels altered food web function by shunting carbon from pelagic to benthic pathways, increasing dissipative flow loss, and decreasing ecosystem activity. SNA revealed the strength of zebra mussel perturbation as evidenced by a reorganization of food web subgroup structure, with a decrease in importance of pelagic pathways, a concomitant rise of benthic pathways, and a reorganization of interactions between top predator fish. Together, these analyses allowed for a holistic understanding of the effects of zebra mussel invasion on the Oneida Lake food web.     

Ecological network determination of sectoral linkages, utility relations and structural characteristics on urban ecological economic system

Analyzing the structure and functioning of the urban system revealed ways to optimize its structure by adjusting the relationships among compartments, thereby demonstrating how ecological network analysis can be used in urban system research. Based on the account of the extended exergy utilization in the sector of urban socio-economic system, which is considered as the composition of extraction (Ex), conversion (Co), agriculture (Ag), industry (In), transportation (Tr), tertiary (Te) and households (Do) sectors, an urban ecological network model is constructed to gain insights into the economic processes oriented to sustainable urban development. Taking Beijing city as the case, the network accounting and related ecological evaluation of a practical urban economy are carried out in this study in the light of flux, efficiency, utility and structure analysis. The results showed that a large quantity of energy and resources have to be consumed to maintain the structure and function of a city. The thermodynamic efficiencies of individual sector in Beijing remain at a low level. The social system in Beijing is a highly competitive network, and there are 8 competitive relations and only two mutualistic ones. The Domestic and Agricultural sector are the major controlling factors of the system. Moreover, the assessment results of Beijing are compared with the other three socio-economic systems, Norway, UK and Italy, and the ecological network function and structure comparisons are correspondingly illuminated and discussed. The conclusions indicate that the exergy-based network analysis can be refined to become an integrative tool for evaluation, policy-making and regulation for urban socio-economic system management concerning structure and efficiency at urban levels.     

Identifying key species in ecosystems with stochastic sensitivity analysis

The development of approaches to estimate the vulnerability of biological communities and ecosystems to extirpations and reductions of species is a central challenge of conservation biology. One key aim of this challenge is to develop quantitative approaches to estimate and rank interaction strengths and keystoneness of species and functional groups, i.e. to quantify the relative importance of species. Network analysis can be a powerful tool for this because certain structural aspects of ecological networks are good indicators of the mechanisms that maintain co-evolved, biotic interactions. A static view of ecological networks would lead us to focus research on highly-central species in food webs (topological key players in ecosystems). There are a variety of centrality indices, developed for several types of ecological networks (e.g. for weighted and un-weighted webs). However, truly understanding extinction and its community-wide effects requires the use of dynamic models. Deterministic dynamic models are feasible when population sizes are sufficiently large to minimize noise in the overall system. In models with small population sizes, stochasticity can be modelled explicitly. We present a stochastic simulation-based ecosystem model for identification of “dynamic key species” in situations where stochastic models are appropriate. To demonstrate this approach, we simulated ecosystem dynamics and performed sensitivity analysis using data from the Prince William Sound, Alaska ecosystem model. We then compare these results to those of purely topological analyses and deterministic dynamic (Ecosim) studies. We present the relationships between various topological and dynamic indices and discuss their biological relevance. The trophic group with the largest effect on others is nearshore demersals, the species mostly sensitive to others is halibut, and the group of both considerable effect on and sensitivity to others is juvenile herring. The most important trophic groups in our dynamical simulations appear to have intermediate trophic levels.     

Food web model of the Upper Paraná River Floodplain: description and aggregation effects

To describe the Upper Paraná River Floodplain (the last non-dammed stretch of the Paraná River, Brazil) a food web model was quantified using ECOPATH. The modeled ecosystem showed maturity because of the total primary production/total respiration ratio (close to 2), Finn’s cycling index (7%) and overhead (65%). The first model elaborated had 40 compartments/groups, but its transfer efficiencies among trophic levels did not reduce in despite the trophic level increasing. To solve this, the effect of two grouping methods on system-level information and other ecosystem attributes was investigated. The first series tested, named “classic” (researcher intuitive way and by food preferences) also did not reduce transfer efficiencies. In the second series, named “by pathways”, the first species grouping were those with higher number of input pathways and longest mean length of pathways. Thereby, the news groups from aggregation decreased the number of components and system’s richness, but stability (measured by overhead) did not change, including the model with only eight compartments. The great number of the ten compartments that showed these characteristics was piscivores, increasing the redundancy within highest trophic level. The use of pathways (number and length) can be useful to lumping species since it reduces compartments and do compromise neither maturity nor stability, diminishing grouping subjectivity.     

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.     

The Reynolds transport theorem: Application to ecological compartment modeling and case study of ecosystem energetics

The Reynolds transport theorem (RTT) from mathematics and engineering has a rich history of success in mass transport dynamics and traditional thermodynamics. This paper introduces RTT as a complementary approach to traditional compartmental methods used in ecological modeling and network analysis. A universal system equation for a generic flow quantity is developed into a generic open-system differential expression for conservation of energy. Nonadiabatic systems are defined and incorporated into control volume (CV) and control surface (CS) perspectives of RTT where reductive assumptions in empirical data are then formally introduced, reviewed, and appropriately implemented. Compartment models are abstract, time-dependent systems of simultaneous differential equations describing storage and flow of conservative quantities between interconnected entities (the compartments). As such, they represent a set of flexible and somewhat informal, assumptions, definitions, algebraic manipulations, and graphical depictions subject to influence and selectively parsed expression by the modeler. In comparison, RTT compartment models are more rigorous and formal integro-differential equations and graphics initiated by the RTT universal system equation, forcing an ordered identification of simplifying assumptions, ending with clearly identified depictions of the transfer and transport of conservative substances in physical space and time. They are less abstract in the rigor of their equation development leaving less ambiguity to modeler discretion. They achieve greater consistency with other RTT compartment style models while possibly generating greater conformity with physical reality. Characteristics of the RTT approach are compared with those of a traditional compartment model of energy flow in an intertidal oyster-reef community.     

A concise review of ecological risk assessment for urban ecosystem application associated with rapid urbanization processes

ABSTRACT

Urban ecological risk (UER) caused by rapid urbanization means potential threat to urban ecosystem structure, pattern and services. The scales of ecological risk assessment (ERA) have been expanded from individual organisms to watersheds and regions. The types of stressor range from chemical to physical, biological and natural events. However, the application of ERA in urban ecosystems is relatively new. Here, we summarize the progress of urban ERA and propose an explicit framework to illumine future ERA based on UER identification, analysis, characterization, modeling, projection and early warning and management. The summary includes six urban ERA-relevant methods: weight-of-evidence (WoE), procedure for ecological tiered assessment of risks (PETAR), relative risk model (RRM), multimedia, multi-pathway, multi-receptor risk assessment (3MRA), landscape analysis and ecological models. Furthermore, we review critical cases of urban ERA in landscape ecology, soil, air, water and solid waste. Based on the Internet of Things (IoT) and cloud computing, an urban ERA management platform integrates various urban ERA methodologies that can be developed to provide better implementation strategies of UER for urban ecosystem managers and stakeholders. We develop a conceptual model of urban ERA based on the urban characteristics in China. The future applications of urban ERA include uncertainty analysis using Monte Carlo techniques on the basis of geospatial techniques and comprehensive urban ERA using nonlinear models or process models.     

Ecosystem Management and the Arrogance of Humanism

The ecosystem management paradigm has gained wide acceptance among land resource managers. The definition of ecosystem management remains fuzzy, however, and two fundamentally different views of ecosystem management prevail The first view is biocentric and considers human use of resources to be constrained by the primary goal of maintaining ecological integrity. The second view is anthropocentric and retains the importance of human use of resources, but it includes ecological and social considerations. In the 1981 book The Arrogance of Humanism , David Ehrenfeld examines the central tenets and assumptions of humanism. He provides several examples of human activities in which humanist assumptions are manifest and applies end-product analysis to these to demonstrate the arrogance and failure of humanist assumptions. In this essay, the anthropocentric view of ecosystem management (hereafter just ecosystem management) is discussed in the context of The Arrogance of Humanism , and it is shown that ecosystem management is ultimately humanistic. The underlying assumptions of ecosystem management are also discussed and are examined using end-product analysis. This analysis suggests that the belief in our ability to meet the assumptions of ecosystem management is unwarranted and that ecosystem management is yet another example of the arrogance of humanism. Solution of our land- and resource-management problems must begin with rejection of humanism's doctrine of final causes.     

Ecological role of stomatopods (mantis shrimps) and potential impacts of trawling in a marine ecosystem of the southeast coast of India

Ecosystems are balanced by nature and each component in the system has a role in the sustenance of other components. A change in one component would invariably have an effect on others. Stomatopods (mantis shrimps) are common and ecologically important predatory crustaceans in tropical marine waters. The ecological role of mantis shrimps and potential impacts of trawling in a marine ecosystem were estimated using Ecopath with Ecosim (EwE) Version 5.0 software, by constructing a mass balanced Ecopath model of Parangipettai (Porto Novo) ecosystem. Based on fisheries information from the region, 17 ecological groups were defined including stomatopods. Both primary and secondary data on biomass, P/B, Q/B and diet composition were used as basic inputs. The mass balanced model gave a total system throughput of 14,756 t km⁻² year⁻¹. The gross efficiency of 0.000942 indicated higher contribution of lower food chain groups in the fishery though the mean trophic level was 3.08. The immature and developing stage of the ecosystem was indicated by the ratio of total primary production and total respiration (1.832) and the net system production (2643.30 t km⁻² year⁻¹). Key indices (flow to detritus, net efficiency and omnivory index), split mortality rates and mixed trophic impact of different ecological groups were obtained from the model. A flow diagram was constructed to illustrate the trophic interactions, which explained the biomass flows in the ecosystem with reference to stomatopods. Two temporal simulations were made, with 10 year durations in the mass balanced Ecopath model by using ecosim routine incorporated in EwE software. The effect of decrease in biomass of stomatopods in the ecosystem was well defined, in the first run with increase in stomatopod fishing mortality, and the group showed a high positive impact on benthopelagic fish biomass increase (129%). The simulation with increase in trawling efforts resulted in the biomass decline of different ecological groups as elasmobranchs to 1%, stomatopods to 2%, crabs and lobsters to 36%, cephalopods to 63%, mackerel to 78%, and shrimps to 89%. Present study warns stomatopod discards and further increase in trawling efforts in the region and it explained the need for ecosystem based fisheries management practices for the sustainability of marine fisheries.