Adaptations in a hierarchical food web of southeastern Lake Michigan

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more non-overlapping distributions in food web properties was the subsystem that contained primarily benthic taxa, contrary to expectations that the identified major perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research should employ rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt.     

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.     

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.     

The effects of seston food quality on planktonic food web patterns

In planktonic food webs, the conversion rate of plant material to herbivore biomass is determined by a variety of factors such as seston biochemical/elemental composition, phytoplankton cell morphology, and colony architecture. Despite the overwhelming heterogeneity characterizing the plant–animal interface, plankton population models usually misrepresent the food quality constraints imposed on zooplankton growth. In this study, we reformulate the zooplankton grazing term to include seston food quality effects on zooplankton assimilation efficiency and examine its ramifications on system stability. Using different phytoplankton parameterizations with regards to growth strategies, light requirements, sinking rates, and food quality, we examined the dynamics induced in planktonic systems under varying zooplankton mortality/fish predation, light conditions, nutrient availability, and detritus food quality levels. In general, our analysis suggests that high food quality tends to stabilize the planktonic systems, whereas unforced oscillations (limit cycles) emerge with lower seston food quality. For a given phytoplankton specification and resource availability, the amplitude of the plankton oscillations is primarily modulated from zooplankton mortality and secondarily from the nutritional quality of the alternative food source (i.e., detritus). When the phytoplankton community is parameterized as a cyanobacterium-like species, conditions of high nutrient availability combined with high zooplankton mortality led to phytoplankton biomass accumulation, whereas a diatom-like parameterization resulted in relatively low phytoplankton to zooplankton biomass ratios highlighting the notion that high phytoplankton food quality allows the zooplankton community to sustain relatively high biomass and to suppress phytoplankton biomass to low levels. During nutrient and light enrichment conditions, both phytoplankton and detritus food quality determine the extent of the limit cycle region, whereas high algal food quality increases system resilience by shifting the oscillatory region towards lower light attenuation levels. Detritus food quality seems to regulate the amplitude of the dynamic oscillations following enrichment, when algal food quality is low. These results highlight the profitability of the alternative food sources for the grazer as an important predictor for the dynamic behavior of primary producer–grazer interactions in nature.     

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.     

Quantitative approaches to the analysis of stable isotope food web data

Ecologists use stable isotopes (delta13C, delta15N) to better understand food webs and explore trophic interactions in ecosystems. Traditionally, delta13C vs. delta15N bi-plots have been used to describe food web structure for a single time period or ecosystem. Comparisons of food webs across time and space are increasing, but development of statistical approaches for testing hypotheses regarding food web change has lagged behind. Here we present statistical methodologies for quantitatively comparing stable isotope food web data. We demonstrate the utility of circular statistics and hypothesis tests for quantifying directional food web differences using two case studies: an arthropod salt marsh community across a habitat gradient and a freshwater fish community from Lake Tahoe, USA, over a 120-year time period. We calculated magnitude and mean angle of change (theta) for each species in food web space using mean delta13C and delta15N of each species as the x, y coordinates. In the coastal salt marsh, arthropod consumers exhibited a significant shift toward dependence on Spartina, progressing from a habitat invaded by Phragmites to a restored Spartina habitat. In Lake Tahoe, we found that all species from the freshwater fish community shifted in the same direction in food web space toward more pelagic-based production with the introduction of nonnative Mysis relicta and onset of cultural eutrophication. Using circular statistics to quantitatively analyze stable isotope food web data, we were able to gain significant insight into patterns and changes in food web structure that were not evident from qualitative comparisons. As more ecologists incorporate a food web perspective into ecosystem analysis, these statistical tools can provide a basis for quantifying directional food web differences from standard isotope data.     

An inverse model for the analysis of the Venice lagoon food web

A steady-state model of the Venice lagoon food web was constructed, based on a comprehensive set of data, which were collected in the years 2001-2005. Energy flows were estimated by means of an inverse methodology of constrained optimization based on the Minimum Norm criterion, i.e. on the minimization of both the sum of squares of the residuals and of the sum of squares of energy flows. The solution was constrained by a set inequalities, which were derived from general eco-physiological knowledge and site specific data on energy flows. The trophic network was represented by thirty-two nodes, including single-species compartments for the species of high economical or ecological relevance. Mass balance equations were weighted, in order to obtain meaningful results in presence of large differences, up to 5 orders of magnitude, among biomasses. A perturbation technique was applied, with the purpose of reducing the risk of finding solutions heavily affected by the set of constraints and of obtaining a more robust representation of the energy flows. The main patterns of energy flow are consistent with those obtained in previous attempts at modelling the Venice lagoon food web. Micro- and macro-phytobenthos account for the largest fraction of the primary production. Energy is then transferred towards higher trophic levels by means of two main pathways: the recycling of dead biomass through the detritus compartment and the direct consumption by grazers. The first pathway is the most important and accounts for approximately two/thirds of the energy transferred to the second trophic level.     

A simulation model to explore the response of the Gulf of Maine food web to large-scale environmental and ecological changes

A dynamic simulation model was constructed using outputs from a balanced Gulf of Maine (GOM) energy budget model as the initial parameter set. The model was structured to provide a recipient control set of dynamics, largely based off of flows to and from different biological groups. The model was used to produce Monte Carlo simulations that were compared (percent change in biomass) with basecase simulations for a variety of scenarios. Changes in primary production, large increases in pelagic and demersal fish biomass, increases in fishing mortality, and large increases in top predators such as baleen whales and pinnepids were simulated. These scenarios roughly simulated the potential impacts of climate change, altered fishing pressure, additional protected species mitigations, and combinations thereof. Results suggest that the GOM system is primarily influenced by bottom-up processes involving phytoplankton, zooplankton, and bacterial biomass. Pelagic and demersal fish were important in determining trends in some of the scenarios. Marine mammals, large pelagic fish, and seabirds have a minor role in the GOM system in terms of biomass flows among the ecosystem components. The system is resilient to large-scale change due, in part to many predator–prey linkages. However, major alterations could occur from sustained climate change, high fishing rates, and by combinations of these types of external forcing mechanisms.     

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.     

Dealing with uncertainty in qualitative models with a semi-quantitative approach based on simulations. Application to the Gironde estuarine food web (France)

In the context of ecosystem approach to fisheries, it is a critical issue to build management tools able to predict the possible trajectories of ecosystems under various human pressure or environmental variations, but also capable to point out influent and sensitive components.     

Valuation of small and multiple health risks: A critical analysis of SP data applied to food and water safety

This study elicits individual risk preferences in the context of an infectious disease using choice experiments. A main objective is to examine scope sensitivity using a novel approach. Our results suggest that the value of a mortality risk reduction (VSL) is highly sensitive to the survey design. Our results cast doubt on the standard scope sensitivity tests in choice experiments, but also on the validity and reliability of VSL estimates based on stated-preference studies in general. This is important due to the large empirical literature on non-market evaluation and the elicited values’ central role in policy making.     

Relationships between dissolved and particulate carbohydrate temporal patterns and mucilaginous aggregates formation: evidences from time series analysis and biochemical composition of aggregates

A 3-year monitoring of dissolved and particulate carbohydrate concentrations in four transects located in the Adriatic and Tyrrhenian Seas was performed in order to get information on the role played by carbohydrates in the mucilage formation in these areas. The application of time series analysis pointed out that the concentration of dissolved carbohydrates does not vary significantly in coincidence of the mucilage appearance showing an almost constant state with respect to time. In contrast, wider temporal variations of carbohydrate amounts, either increase or decrease, were observed when mucilages were lacking or reduced. This almost constant state of carbohydrate amounts observed in presence of mucilages that we define 'steady state' could be associated to an alteration of the complex chemical equilibrium between synthesis and degradation (either hydrolysis or oxidation) reactions of the organic polymers which are typical of the humification processes in the marine environment. The results of this study suggest that the monitoring of carbohydrates can represent an useful tool for the comprehension of the most relevant phenomena of mucilage appearance in the Northern Adriatic Sea.     

The application of artificial neural networks to flow and phosphorus dynamics in small streams on the Boreal Plain,with emphasis on the role of wetlands

Historically, management strategies in Canada's boreal forest have focused on forest polygons and terrestrial biodiversity to address ecological considerations in forest management. The Forest Watershed and Riparian Disturbance (FORWARD) project examines the problem from a watershed perspective rather than a forest polygon viewpoint. The main objective of this study was to devise an artificial neural network (ANN) modeling tool that can predict flow and total phosphorus (TP) concentration for ungauged watersheds (where daily flow is not monitored). This dictates that all inputs should be easily accessed via a public domain database, like the Environment Canada weather database, without the need to install flow gauges in each modeled watershed. Daily flow and TP concentration for two of the project watersheds were modeled using ANNs. The two watersheds (1A Creek, 5.1 km² and Willow Creek, 15.6 km²) were chosen to reflect variations in wetland area and composition in the study area. Flow was modeled with a feed-forward multilayer perceptron ANN trained with the error back-propagation algorithm. Simulated values for flow were then used, as inputs, to model TP concentration using the same neural networks algorithm. One hidden layer with three slabs; each operating with a different activation function was utilized to simulate the conceptual differences between base flow, snowmelt, and storm events. Time domain analysis was conducted to identify possible model time-lagged inputs reflecting the time dependency of the modeled variables. Spectral analysis was used to address data hystereses. Our results highlight the capabilities of ANN in modeling complex ecosystems and highly correlated variables. Results also indicated that more research towards the phosphorus dynamics in wetlands is required to better represent the impact of wetland area and composition on the water-phase phosphorus in ANN modeling.     

Using citizen science data to identify the sensitivity of species to human land use

Conservation practitioners must contend with an increasing array of threats that affect biodiversity. Citizen scientists can provide timely and expansive information for addressing these threats across large scales, but their data may contain sampling biases. We used randomization procedures to account for possible sampling biases in opportunistically reported citizen science data to identify species’ sensitivities to human land use. We analyzed 21,044 records of 143 native reptile and amphibian species reported to the Carolina Herp Atlas from North Carolina and South Carolina between 1 January 1990 and 12 July 2014. Sensitive species significantly associated with natural landscapes were 3.4 times more likely to be legally protected or treated as of conservation concern by state resource agencies than less sensitive species significantly associated with human‐dominated landscapes. Many of the species significantly associated with natural landscapes occurred primarily in habitats that had been nearly eradicated or otherwise altered in the Carolinas, including isolated wetlands, longleaf pine savannas, and Appalachian forests. Rare species with few reports were more likely to be associated with natural landscapes and 3.2 times more likely to be legally protected or treated as of conservation concern than species with at least 20 reported occurrences. Our results suggest that opportunistically reported citizen science data can be used to identify sensitive species and that species currently restricted primarily to natural landscapes are likely at greatest risk of decline from future losses of natural habitat. Our approach demonstrates the usefulness of citizen science data in prioritizing conservation and in helping practitioners address species declines and extinctions at large extents.     

The role of lipids in fermentative propionate production from the co-fermentation of lipid and food waste

● Lipid can promote PA production on a target from food waste. ● PA productivity reached 6.23 g/(L∙d) from co-fermentation of lipid and food waste. ● Lipid promoted the hydrolysis and utilization of protein in food waste. ● Prevotella , Veillonella and norank _f _Propioni bacteriaceae were enriched. ● Main pathway of PA production was the succinate pathway. Food waste (FW) is a promising renewable low-cost biomass substrate for enhancing the economic feasibility of fermentative propionate production. Although lipids, a common component of food waste, can be used as a carbon source to enhance the production of volatile fatty acids (VFAs) during co-fermentation, few studies have evaluated the potential for directional propionate production from the co-fermentation of lipids and FW. In this study, co-fermentation experiments were conducted using different combinations of lipids and FW for VFA production. The contributions of lipids and FW to propionate production, hydrolysis of substrates, and microbial composition during co-fermentation were evaluated. The results revealed that lipids shifted the fermentation type of FW from butyric to propionic acid fermentation. Based on the estimated propionate production kinetic parameters, the maximum propionate productivity increased significantly with an increase in lipid content, reaching 6.23 g propionate/(L∙d) at a lipid content of 50%. Propionate-producing bacteria Prevotella, Veillonella, and norank_f_Propionibacteriaceae were enriched in the presence of lipids, and the succinate pathway was identified as a prominent fermentation route for propionate production. Moreover, the Kyoto Encyclopedia of Genes and Genomes functional annotation revealed that the expression of functional genes associated with amino acid metabolism was enhanced by the presence of lipids. Collectively, these findings will contribute to gaining a better understanding of targeted propionate production from FW.     

Bridging biogeochemical and food web models for an End-to-End representation of marine ecosystem dynamics: The Venice lagoon case study

The simultaneous accounting of effects of natural and anthropogenic changes within a common framework calls for the development of new comprehensive tools capable of integrating biological processes that span a huge range of scales, from viruses to fishes, in addition to their interactions with physical–chemical environmental properties, i.e. End-to-End models.     

Preferential allocation of food by magpies Pica pica to great spotted cuckoo Clamator glandarius chicks

Adult magpies Pica pica provide parasitic great spotted cuckoo Clamator glandarius nestlings with a diet very similar to that fed to their own chicks. In both naturally and experimentally parasitized nests, great spotted cuckoo chicks were fed at a higher rate than magpie chicks in the same nest. This preferential allocation of food by magpie parents to great spotted cuckoo chicks is consistent with the supernormal stimulus hypothesis, because this result implies that cuckoo chicks provide stronger stimuli for parental care than host chicks. Great spotted cuckoo chicks receive most of the food brought to the nest by the foster parents, because they exploit a series of stimuli which jointly (or sometimes individually) operate as a supernormal stimulus. This hypothesis predicts that if any stimulus is masked, the efficiency of the cuckoo in eliciting parental care will decrease. Here, we analyze experimentally the effects of two of these stimuli, preferential feeding of large nestlings and of nestlings with conspicuous palatal papillae. Firstly, when we experimentally introduced one medium-sized (7–9 days) cuckoo chick into an unparasitized magpie nest where the largest magpie chick was 12–15 days old, the cuckoo did not receive significantly more food than the average or the largest magpie chick. Secondly, when unparasitized nests were experimentally parasitized with a cuckoo chick that had its gape painted to mimic that of magpie chicks, the parasitic cuckoo received less food than the average magpie chick.     

Application of a ‘bio-engineering’ technique to protect ghoramara island (Bay of Bengal) from severe erosion

Ghoramara Island is located ca. 150 km south of Kolkata, Bay of Bengal, India, in the Sundarban Delta complex. This sparsely populated island is suffering from severe coastal erosion and areal reduction for the last three decades, which results in the loss of major areas on the northwest coast. Both numerous households and a significant area of agricultural land and coastal stretches for fish drying have been lost. This has rendered thousands of people homeless as ‘environmental refugess’. In the present paper an attempt is made to study the erosion and accretion process through time series analysis using a GIS technique. Also, a study of remedial measures to protect the island using a ‘bio-engineering’ technique is reported in this paper. It has been shown that, in the absence of protection measures, the eastern shore will merge with the Indian mainland during the next 25 years, while the western part will be completely washed off.