Topological analysis of the ecological importance of elasmobranch fishes: A food web study on the Gulf of Tortugas, Colombia

We built a trophic network based on a matrix of interspecific trophic relationships to assess the role of elasmobranch fishes in shaping community structure of the Gulf of Tortugas in the Colombian Pacific Ocean. We analyzed diet similarities to define trophic components (nodes) - rather than taxonomical groups - in the network. We evaluated the ecological function of species or trophic entities through topological analysis of their structural importance in trophic networks by applying one local and several mesoscale network indices. We found that top predatory elasmobranchs play an important ecological role in top-down control and in propagating indirect effects through the system owing to high values of the node degree, centrality and topological importance indices. However, invertebrates and teleost fishes had higher connectivity and topological importance than other elasmobranchs in the network before and after removal of top predators from the system. Results from our study thus suggest that elasmobranchs at intermediate trophic levels - commonly referred to as “mesopredators” - are not so important in all complex coastal ecosystems as previously reported.     

Chaos and pattern formation in a spatial tritrophic food chain

The model of Hastings and Powell describes a tritrophic food chain that exhibits chaotic dynamics. The model assumes that the populations are homogeneously mixed, so that the probability that any two individuals interact is uniform and space can be ignored. In this paper we propose a spatial version of the Hastings and Powell model in which predators seek their preys only in a finite neighborhood of their home location, breaking the mixing hypothesis. Treating both space and time as discrete variables we derive a set of coupled equations that describe the evolution of the populations at each site of the spatial domain. We show that the introduction of local predator–prey interactions result in qualitatively distinct dynamics of predator and prey populations. The evolution equations for the predators involve averages over the local density of preys, whereas the equations for the preys involve double averages, where the local density of both preys and predators appear. Our numerical simulations show that local predation also leads to spontaneous pattern formation and to qualitative changes in the global dynamics of the system. In particular, depending on the size of the predation neighborhoods, the chaotic strange attractor present in the original model of Hastings and Powell can be replaced by a stable fixed point or by an attractor of simpler topology.     

Food web structure affects the extinction risk of species in ecological communities

This paper studies the effect of food web structure on the extinction risk of species. We examine 793 different six-species food web structures with different number, position and strength of trophic links and expose them to stochasticity in a model with Lotka–Volterra predator–prey dynamics. The characteristics of species (intrinsic rates of increase as well as intraspecific density dependence) are held constant, but the interactions with other species and characteristics of the food web are varied.     

Carbon-based balanced trophic structure and flows in the offshore Lake Ontario food web before (1987-1991) and after (2001-2005) invasion-induced ecosystem change

Replicate mass-balanced solutions to Ecopath models describing carbon-based trophic structures and flows were developed for the Lake Ontario offshore food web before and after invasion-induced disruption. The food webs link two pathways of energy and matter flow: the grazing chain (phytoplankton-zooplankton-fish) and the microbial loop (bacteria-protozoans) and include 19 species-groups and three detrital groups. Mass-balance was achieved by using constrained optimization techniques to randomly vary initial estimates of biomass and diet composition. After the invasion, production declined for all trophic levels and species-groups except Chinook salmon. The trophic level (TL) increased for smelt, adult sculpin, adult alewife and Chinook salmon. Changes to ecotrophic efficiencies indicate a reduction in phytoplankton grazing, increased predation pressure on Mysis, adult smelt and alewife and decreased predation pressure on protozoans. Specific resource to consumer TTE changed; increasing for protozoans (8.0-11.5%), Mysis (0.6-1.0%), and Chinook salmon (1.0-2.3%) and other salmonines (0.4-0.5%) and decreasing for zooplankton (20.2-15.1%), prey-fish (9.7-8.8%), and benthos (1.7-0.6%). Direct trophic influences of recent invasive species were low. The synchrony of the decline in PP and species-group production indicates strong bottom-up influence. Mass balance required an increase of two to threefold in lower trophic level biomass and production, confirming a previously observed paradoxical deficit in lower trophic level production. Analysis of food web changes suggest hypotheses that may apply to other similar large pelagic systems including, (1) as pelagic primary productivity declines, overgrazing of zooplankton results in an increase in protozoan production and a loss of trophic transfer efficiency, (2) habitat and food web changes increased Mysis predation on Diporeia and contributed to their recent decline, and (3) production of Chinook salmon, the primary piscivore, was uncoupled from pelagic production processes. This study demonstrates the value of food web models to better understand the impact of invasive species and to develop novel hypotheses concerning trophic influences.     

Influence of groundwater recharge and well characteristics on dissolved arsenic concentrations in southeastern Michigan groundwater

Arsenic concentrations exceeding 10 μg/l, the United States maximum contaminant level and the World Health Organization guideline value, are frequently reported in groundwater from bedrock and unconsolidated aquifers of southeastern Michigan. Although arsenic-bearing minerals (including arsenian pyrite and oxide/hydroxide phases) have been identified in Marshall Sandstone bedrock of the Mississippian aquifer system and in tills of the unconsolidated aquifer system, mechanisms responsible for arsenic mobilization and subsequent transport in groundwater are equivocal. Recent evidence has begun to suggest that groundwater recharge and characteristics of well construction may affect arsenic mobilization and transport. Therefore, we investigated the relationship between dissolved arsenic concentrations, reported groundwater recharge rates, well construction characteristics, and geology in unconsolidated and bedrock aquifers. Results of multiple linear regression analyses indicate that arsenic contamination is more prevalent in bedrock wells that are cased in proximity to the bedrock-unconsolidated interface; no other factors were associated with arsenic contamination in water drawn from bedrock or unconsolidated aquifers. Conditions appropriate for arsenic mobilization may be found along the bedrock-unconsolidated interface, including changes in reduction/oxidation potential and enhanced biogeochemical activity because of differences between geologic strata. These results are valuable for understanding arsenic mobilization and guiding well construction practices in southeastern Michigan, and may also provide insights for other regions faced with groundwater arsenic contamination.     

Simulation of aquatic food web and species interactions by adaptive agents embodied with evolutionary computation: a conceptual framework

Individual-based and state variable-based adaptive agents (AA) are discussed regarding their relevance to different types of ecosystems. Individual-based AA proved applicable to a spatially explicit simulation of highly simplified terrestrial food webs. State variable-based AA with evolutionary computation (EC) embodied are suggested for the simulation of aquatic food webs and plankton species interactions. Embodiment of EC in AA can be achieved by evolving predictive rules (ER), differential equations (EDE) or artificial neural networks (ANN) derived from a diverse lake database. In order to provide ecosystem simulation with resilience to environmental change, agent banks can be created containing alternative agents for same species or functional groups from different lakes. State variable-based AA are currently tested for aquatic ecosytem simulation by means of a diverse lake database. It promises to overcome constraints by the rigidity of traditional lake ecosystem models.     

A physical-microbial food web coupled model to study the evolution of the ecological functioning of a new reservoir after its flooding (Sep,Puy de Dôme)

The aim of this paper is to understand the temporal changes in planktonic populations and to highlight some important factors that control the biological functioning and evolution of a recently flooded reservoir, the Sep reservoir (Massif Central, France). To achieve this objective, a 1D vertical coupled physical–biological model was used and developed. It couples relevant physical processes (dispersion, advection and convection) with biological processes taking into account the complexity of interactions within the microbial food web, including the conventional grazing food chain with a microbial loop.     

Estimating an homogeneous series of a population abundance indicator despite changes in data collection procedure: A hierarchical Bayesian modelling approach

Abundance indicators are required both to assess and to manage wild populations. As new techniques are developed and teams in charge of gathering the data change, data collection procedures (DCPs) can evolve in space and time. How to estimate an homogeneous series of abundance indicator despite changes in DCP? To tackle this question a hierarchical Bayesian modelling (HBM) approach is proposed. It integrates multiple DCPs in order to derive a single abundance indicator that can be compared over space and time irrespective of the DCP used. Compared to single DCP models, it takes further advantage for abundance estimation of the joint treatment of a larger set of spatio-temporal units. After presenting the general formulation of our HBM approach, it is applied to the juvenile Atlantic salmon (Salmo salar L.) population of the River Nivelle (France). Posterior model checking, using χ² discrepancy measure, do not reveal any inadequacy between the model and the data. Despite a change in the DCP used (successive removals to catch-per-unit of effort), a unique abundance indicator for the 425 spatio-temporal units (site × year) sampled over twenty-four years (1985-2008) is estimated. The HBM approach allows the assessment of precision of the abundance estimates and shows variation between DCPs: a reduction in precision is observed during the most recent years (2005-2008) when only the catch-per-unit of effort DCP was used. The merits and generality of our HBM approach are discussed. We contend it extends previous single DCP models or inter-calibration of two DCPs, and it could be applied to a wide range of specific situations (taxon and DCPs).     

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.     

A Numerical Study of the Dynamics of the Riverine Thermal Bar in a Deep Lake

A numerical model based on a Finite Volume formulation of the Navier–Stokes equations is used to simulate a range of scenarios leading to a thermal bar formed by a river inflow to an idealised deep lake. The results presented here show that small riverine salinity increases have a profound effect on the dynamics of the thermal bar, suppressing horizontal propagation of the plume and raising the possibility of a thermal bar which is capable of sinking to great depths. This finding is particularly relevant to Lake Baikal in Siberia, where the vigorous deep-water renewal is still not fully understood. An analysis of the buoyancy forces governing the depth of penetration of the thermal bar plume shows that realistic salinity gradients are an important factor in determining the circulation of Baikal waters. Observations of the saline curtailment of the thermal bar's horizontal propagation also reveal a potential for reduced productivity in the ecosystem of any temperate river delta during the Spring renewal period.     

Ecosystem network analysis indicators are generally robust to parameter uncertainty in a phosphorus model of Lake Sidney Lanier, USA

Understanding how data uncertainty influences ecosystem analysis is critical as we move toward ecosystem-based management. Here, we investigate how 18 Ecological Network Analysis (ENA) indicators that characterize ecosystem growth, development, and condition are affected by uncertainty in an ecosystem model of Lake Sidney Lanier (USA). We applied ENA to 122 plausible parameterizations of the ecosystem developed by Borrett and Osidele (2007, Ecological Modelling 200, 371-387), and then used the coefficient of variation (CV) to compare system indicator variability. We considered Total System Throughput (TST) as a measure of the underlying model uncertainty and tested three hypotheses. First, we hypothesized that non-ratio indicators whose calculation includes the TST would be at least as variable as TST if not more variable. Second, we postulated that indicators calculated as ratios, with TST in the numerator and denominator would tend to be less variable than TST because its influence will cancel. Last, we expected the Average Mutual Information (AMI) to be less variable than TST because it is a bounded function. Our work shows that the 18 indicators grouped into four categories. The first group has significantly larger CVs than the CV for TST. In this group, model uncertainty is amplified rendering these three indicators less useful. The second group of four indicators shows no significant difference in variability with respect to TST. Finally, there are two groups whose CV values are significantly lower than that for TST. The least variable group includes the ratio-based indicators and Average Mutual Information. Due to their low variability, we conclude that these indicators are the most robust to the parameter uncertainty and most useful for ecosystem assessment and comparative ecosystem analysis. In summary, this work suggests that we can be as certain, or more certain, in most of the selected ENA indicators as we are in the parameters of the model analyzed.     

Assessment of impacts of invasive fishes on the food web structure and ecosystem properties of a tropical reservoir in India

A network model of trophic interactions in a tropical reservoir in India was developed with the objective to quantify matter and energy flows between system components and to study the impact of invasive fishes on the ecosystem. Structure of flows and their distribution within and between trophic levels were analysed by aggregating single flows into combined flows for discrete trophic levels. The trophic flows primarily occurred in the first four trophic level (TL) and the food web structure in this reservoir ecosystem was characterized by the dominance of low TL organisms, with the highest TL of only 3.57 for the top predator. Highest system omnivory index (SOI) was observed for indigenous catfishes (0.422), followed by the exotic fish Mozambique Tilapia (0.402). Nile Tilapia and Pearl spots show the highest niche overlap which suggests high competition for similar resources. The mixed trophic impact routine reveals that an increase in the abundance of the African catfish would negatively impact almost all fish groups such as Indian major carps, Pearl spots, indigenous catfishes and Tilapines. The other invasive fish Mozambique Tilapia adversely affects the indigenous catfishes. The most interesting observation in this study is that the most dominant invasive fish in this reservoir, the Nile Tilapia does not negatively impact any of the fish groups. In fact it positively impacts the Indian major carps. The direct and indirect effects of predation between system components (i.e. fish, invertebrates, phytoplankton and detritus) are quantitatively described and the possible influence and role in the ecosystem's functioning of the invasive fish species are discussed.     

Biomagnification of trace elements in a benthic food web: the case study of Deer Island (Northern Yellow Sea)

In this study, we investigated the concentrations of ten trace elements (Cu, Zn, Mn, Se, Ni, Cd, Cr, Pb, Hg, and As) and their trophodynamics in a benthic food chain of Deer Island, Northern Yellow Sea. The concentrations of Cu, Zn, Mn, Se, Ni, Cd, Cr, Pb, Hg, and As in the food chain ranged from 3.2 to 23.2, from 71 to 227, from 7.4 to 45.6, from 0.44 to 5.80, from 0.73 to 7.60, from 0.14 to 1.65, from 0.68 to 6.70, from 0.08 to 1.86, from 0.08 to 1.18, and from 0.24 to 3.92 mg kg^?1 dry weight, respectively. Among these trace elements, the linear regression between the log-transformed concentrations of Hg and Cd and δ¹⁵N values showed statistically significant increase (p<0.05) with the slopes of 0.134 and 0.144, indicating biomagnification of Hg and Cd occurred in the benthic food chain of Deer Island. While the linear regression for other eight trace elements (Cu, Zn, Mn, Se, Ni, Cr, Pb and As) were characterised by extensive scatter with non-significant correlation coefficients (R ²=0.002–0.235) and slopes (p=0.079–0.875), indicating there were not biomagnified or biodiluted of these trace elements.     

太湖典型河网区地表水与沉积物氮、磷和重金属含量空间分异

将无锡城乡交错区河网分为城镇生活区水巷、工业区主河道、农业区主河道、农业区支流和鱼塘5种类型区.通过秋季(旱季)和夏季(雨季)2次采样,研究氮、磷和Cu、Zn、Pb、Cr、Cd在地表水和沉积物中的含量及其空间变化.结果表明:(1)城乡交错区地表水氮、磷来源于生活污染和工业污染的比例大于农田,同时具有来源分散、污染面广的特征.(2)由于城镇地表径流和工业活动影响,各类型区地表水重金属含量均有不同程度提高.但地表水重金属主要沿主河道迁移,旱季和雨季主河道重金属含量均大于农业区支流,而且随着与城镇距离增加,主河道沉积物重金属含量迅速降低,重金属污染影响范围较小.(3)与重金属相比,地表水氮、磷污染仍是太湖水网区主要的环境问题.但城镇及其周围河流沉积物中富集的重金属含量很高,其潜在环境风险不容忽视.