Ecological network complexity scales with area.

Larger geographical areas contain more species-an observation raised to a law in ecology. Less explored is whether biodiversity changes are accompanied by a modification of interaction networks. We use data from 32 spatial interaction networks from different ecosystems to analyse how network structure changes with area. We find that basic community structure descriptors (number of species, links and links per species) increase with area following a power law. Yet, the distribution of links per species varies little with area, indicating that the fundamental organization of interactions within networks is conserved. Our null model analyses suggest that the spatial scaling of network structure is determined by factors beyond species richness and the number of links. We demonstrate that biodiversity-area relationships can be extended from species counts to higher levels of network complexity. Therefore, the consequences of anthropogenic habitat destruction may extend from species loss to wider simplification of natural communities.

Incorporating abiotic controls on animal movements in metacommunities.

Local dynamics are influenced by regional processes. Meta-ecology, or the study of spatial flows of energy, materials, and species between local systems, is becoming increasingly concerned with accurate depictions of species movements and the impacts of this movement on landscape-level ecosystem function. Indeed, incorporating diverse types of movement is a major frontier in metacommunity theory. Here, we synthesize literature to demonstrate that the movement of organisms between patches is governed by the interplay between both a species' ability to move and the combined effects of landscape structure and physical flows (termed abiotic controls), which together we refer to as abiotic-dependent species connectivity. For example, two lakes that share geographic proximity may be inaccessible for mobile fish species because they lack a river connecting them (landscape structure), but wind currents may disperse insects between them (physical flows). Empirical evidence suggests that abiotic controls, such as ocean currents, lead to abiotic-dependent species connectivity and that, in nature, this type of connectivity is the rule rather than the exception. Based on this empirical evidence, we introduce a novel mathematical framework to demonstrate how species movement capabilities and abiotic conditions, can interact to influence metacommunity stability. We apply this framework to predict how incorporating abiotic-dependent species connectivity applies to classic empirical examples of aquatic, aquatic-terrestrial, and terrestrial experimental metacommunities. We demonstrate that incorporating abiotic-dependent species connectivity into metacommunity models can lead to a much broader range of dynamics than models previously predicted, including a wider range of metacommunity stability. Our framework fills critical gaps in our basic understanding of organismal movement across landscapes and provides testable predictions for how such common natural phenomena impact landscape-level ecosystem function. Finally, we present future perspectives for further development of meta-ecological theory from questions about fragmentation to ecosystems. Anthropogenic change is not only leading to habitat loss from the damming of rivers to denuding the landscape, but altering the physical flows that have historically connected communities. Thus, recognizing the importance of these processes in tandem with species' movement abilities is critical for predicting and preserving the structure and function of ecological communities.

The multiple meanings of omnivory influence empirical, modular theory and whole food web stability relationships.

The persistence of whole communities hinges on the presence of select interactions which act to stabilize communities making the identification of these keystone interactions critical. One potential candidate is omnivory, yet theoretical research on omnivory thus far has been dominated by a modular theory approach whereby an omnivore and consumer compete for a shared resource. Empirical research, however, has highlighted the presence of a broader suite of omnivory modules. Here, we integrate empirical data analysis and mathematical models to explore the influence of both omnivory module (including classic, multi-resource, higher level, mutual predation and cannibalism) and omnivore-resource interaction type on food web stability. We use six classic empirical food webs to examine the prevalence of the different types of omnivory, a multi-species consumer-resource model to determine the stability of these different kinds of omnivory within a module context, and finally extend these models to a 50 species, whole food web model to examine the influence of omnivory on whole food web persistence. Our results challenge the concept that omnivory is broadly stabilizing. In particular, we demonstrate that the impact of omnivory depends on the type of omnivory being examined with multi-resource omnivory having the largest correlation with whole food web persistence. Moreover, our results highlight that we need to exercise caution when scaling modular theory to whole food web theory. Cannibalism, for example, was the most persistent and stable omnivory module in the modular theory analysis, but only demonstrated a weak correlation with whole food web persistence. Lastly, our results demonstrate that the frequency of omnivory modules are more important for whole food web persistence than the frequency of omnivore-resource interactions. Together, these results demonstrate that the role of omnivory often depends both on the type of omnivory being examined and the food web within which it is nested. In whole food web models, omnivory acts less as a keystone interaction, rather, specific types of omnivory, particularly multi-resource omnivory, act as keystone modules. Future work integrating module and whole food web theory is critical for resolving the role of key interactions in food webs.

Use of a Food Web Bioaccumulation Model to Uncover Spatially Integrated Polychlorinated Biphenyl Exposures in Detroit River Sport Fish.

We applied and tested a bioenergetic-based, steady-state food web bioaccumulation model to predict polychlorinated biphenyl (PCB) exposures in sport fish of the Detroit River (USA-Canada), which is a Great Lakes area of concern. The PCB concentrations in the sediment and water of the river were found to exhibit high spatial variation. The previously contained areas of high contamination may have spread to adjacent food webs as a result of fish movements. This process may cause biased predictions in single-compartment bioaccumulation models. We performed multiple simulations and contrasted model predictions against a database of 1152 fish sample records comprising 19 sport fish species. The simulations evaluated 4 spatial scales (river-wide, 2-nation, 4-zone, and 6-zone models) to reveal how the spatial heterogeneity of contamination and species-specific movements contribute to variation in fish PCB exposures. The model testing demonstrated that the 2-nation model provided the most accurate global prediction of fish contamination. However, these improvements were not equally observed across all species. The model was subsequently calibrated for poorly performing species, by allowing cross-zone exposures, demonstrating the importance of accounting for specific ecological factors, such as fish movement, to improve PCB bioaccumulation prediction, especially in highly heterogeneous water systems. Environ Toxicol Chem 2019;38:2771-2784. © 2019 SETAC.

A Multitracer Approach to Quantifying Resource Utilization Strategies in Lake Trout Populations in Lake Huron.

Lake ecosystems are threatened by an array of stressors. An understanding of how food webs and bioaccumulation dynamics respond to these challenges requires the quantification of energy flow. We present a combined, multitracer approach using both polychlorinated biphenyls (PCBs) and stable isotopes to trace energy flow, and to quantify how lake trout feeding strategies have adapted to changes in food web structure in 3 basins of Lake Huron (ON, Canada). This combined tracer approach allows the quantification of dietary proportions (using stable isotopes), which are then integrated using a novel PCB tracer approach that employs knowledge of PCB bioaccumulation pathways, to estimate consumption and quantify energy flow between age cohorts of individual fish across Lake Huron. We observed basin-specific differences in ultimate energy sources for lake trout, with Georgian Bay lake trout deriving almost 70% of their energy from benthic resources compared with 16 and 33% for Main Basin and North Channel lake trout, respectively. These differences in resource utilization are further magnified when they are contrasted with age. The dependency on pelagic energy sources in the Main Basin and North Channel suggests that these populations will be the most negatively affected by the ongoing trophic collapse in Lake Huron. Our study demonstrates the utility of a multitracer approach to quantify the consequences of food web adaptations to changes in aquatic ecosystems. Environ Toxicol Chem 2019;38:1245-1255. © 2019 SETAC.

Characterizing polychlorinated biphenyl exposure pathways from sediment and water in aquatic life using a food web bioaccumulation model.

Contaminant remediation decisions often focus on sediment-organism relationships, omitting the partitioning between sediment and water that exists across a given site. The present study highlights the importance of incorporating nonsedimentary routes of exposure into a nonequilibrium, steady-state food web bioaccumulation model for predicting polychlorinated biphenyl (PCB) concentrations in benthic invertebrates. Specifically, we examined the proportion of overlying water relative to the sediment porewater respired by benthic invertebrates, which has been used in previous studies to examine contaminant bioaccumulation. We evaluated the model accuracy using paired benthos-sediment samples and an extensive fish contamination database to ensure realistic predictions at the base of the Detroit River (Ontario, Canada, and Michigan, USA) food web. The results demonstrate that, compared with empirical regression analyses, the food web bioaccumulation model provided satisfactory estimates of PCB bioaccumulation for benthos simulations and better estimates for fish simulations. Our results showed that PCB bioaccumulation measurements are significantly affected by variations in pollutant uptake and elimination routes via the overlying water, which in turn are affected by the degree of disequilibrium of PCBs between sediments and water. Interestingly, we obtained contrasting results regarding the effectiveness of remediation strategies for reducing the contaminant burden of the aquatic biota based on different proportions of overlying water relative to porewater. These differences could consequently impact decisions about the approaches for source control and strategic sediment remediation. This study suggests that bioaccumulation assessments could be improved through better identification of chemical uptake-elimination routes in benthos and by accounting for chemical bioavailability in sediment and water components in areas with disequilibrium.Integr Environ Assess Manag 2019;00:000-000. © 2019 SETAC.

Ecological Implications of Steady State and Nonsteady State Bioaccumulation Models.

Accurate predictions on the bioaccumulation of persistent organic pollutants (POPs) are critical for hazard and ecosystem health assessments. Aquatic systems are influenced by multiple stressors including climate change and species invasions and it is important to be able to predict variability in POP concentrations in changing environments. Current steady state bioaccumulation models simplify POP bioaccumulation dynamics, assuming that pollutant uptake and elimination processes become balanced over an organism's lifespan. These models do not consider the complexity of dynamic variables such as temperature and growth rates which are known to have the potential to regulate bioaccumulation in aquatic organisms. We contrast a steady state (SS) bioaccumulation model with a dynamic nonsteady state (NSS) model and a no elimination (NE) model. We demonstrate that both the NSS and the NE models are superior at predicting both average concentrations as well as variation in POPs among individuals. This comparison demonstrates that temporal drivers, such as environmental fluctuations in temperature, growth dynamics, and modified food-web structure strongly determine contaminant concentrations and variability in a changing environment. These results support the recommendation of the future development of more dynamic, nonsteady state bioaccumulation models to predict hazard and risk assessments in the Anthropocene.

PCB Food Web Dynamics Quantify Nutrient and Energy Flow in Aquatic Ecosystems.

Measuring in situ nutrient and energy flows in spatially and temporally complex aquatic ecosystems represents a major ecological challenge. Food web structure, energy and nutrient budgets are difficult to measure, and it is becoming more important to quantify both energy and nutrient flow to determine how food web processes and structure are being modified by multiple stressors. We propose that polychlorinated biphenyl (PCB) congeners represent an ideal tracer to quantify in situ energy and nutrient flow between trophic levels. Here, we demonstrate how an understanding of PCB congener bioaccumulation dynamics provides multiple direct measurements of energy and nutrient flow in aquatic food webs. To demonstrate this novel approach, we quantified nitrogen (N), phosphorus (P) and caloric turnover rates for Lake Huron lake trout, and reveal how these processes are regulated by both growth rate and fish life history. Although minimal nutrient recycling was observed in young growing fish, slow growing, older lake trout (>5 yr) recycled an average of 482 Tonnes·yr(-1) of N, 45 Tonnes·yr(-1) of P and assimilated 22 TJ yr(-1) of energy. Compared to total P loading rates of 590 Tonnes·yr(-1), the recycling of primarily bioavailable nutrients by fish plays an important role regulating the nutrient states of oligotrophic lakes.

Synergistic interactions of biotic and abiotic environmental stressors on gene expression.

Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis - cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) - using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.

Comparative organochlorine accumulation in two ecologically similar shark species (Carcharodon carcharias and Carcharhinus obscurus) with divergent uptake based on different life history.

Trophic position and body mass are traits commonly used to predict organochlorine burdens. Sharks, however, have a variety of feeding and life history strategies and metabolize lipid uniquely. Because of this diversity, and the lipid-association of organochlorines, the dynamics of organochlorine accumulation in sharks may be predicted ineffectively by stable isotope-derived trophic position and body mass, as is typical for other taxa. The present study compared ontogenetic organochlorine profiles in the dusky shark (Carcharhinus obscurus) and white shark (Carcharodon carcharias), which differ in metabolic thermoregulation and trophic position throughout their ontogeny. Although greater organochlorine concentrations were observed in the larger bodied and higher trophic position white shark (e.g., p,p'-dichlorodiphenyldichloroethylene: 20.2 ± 2.7 ng/g vs 9.3 ± 2.2 ng/g in the dusky shark), slopes of growth-dilution corrected concentrations with age were equal to those of the dusky shark. Similar ontogenetic trophic position increases in both species, less frequent white shark seal predation than previously assumed, or inaccurate species-specific growth parameters are possible explanations. Inshore habitat use (indicated by δ(13)C values) and mass were important predictors in white and dusky sharks, respectively, of both overall compound profiles and select organochlorine concentrations. The present study clarified understanding of trophic position and body mass as reliable predictors of interspecific organochlorine accumulation in sharks, whereas regional endothermy and diet shifting were shown to have less impact on overall rates of accumulation.

Quantifying uncertainty in the trophic magnification factor related to spatial movements of organisms in a food web.

Trophic magnification factors (TMFs) provide a method of assessing chemical biomagnification in food webs and are increasingly being used by policy makers to screen emerging chemicals. Recent reviews have encouraged the use of bioaccumulation models as screening tools for assessing TMFs for emerging chemicals of concern. The present study used a food web bioaccumulation model to estimate TMFs for polychlorinated biphenyls (PCBs) in a riverine system. The uncertainty associated with model predicted TMFs was evaluated against realistic ranges for model inputs (water and sediment PCB contamination) and variation in environmental, physiological, and ecological parameters included within the model. Finally, the model was used to explore interactions between spatial heterogeneity in water and sediment contaminant concentrations and theoretical movement profiles of different fish species included in the model. The model predictions of magnitude of TMFs conformed to empirical studies. There were differences in the relationship between the TMF and the octanol-water partitioning coefficient (KOW ) depending on the modeling approach used; a parabolic relationship was predicted under deterministic scenarios, whereas a linear TMF-KOW relationship was predicted when the model was run stochastically. Incorporating spatial movements by fish had a major influence on the magnitude and variation of TMFs. Under conditions where organisms are collected exclusively from clean locations in highly heterogeneous systems, the results showed bias toward higher TMF estimates, for example the TMF for PCB 153 increased from 2.7 to 5.6 when fish movement was included. Small underestimations of TMFs were found where organisms were exclusively sampled in contaminated regions, although the model was found to be more robust to this sampling condition than the former for this system.

Ecological factors contributing to variability of persistent organic pollutant bioaccumulation within forage fish communities of the Detroit River, Ontario, Canada.

Understanding variability of contaminant bioaccumulation within and among fish populations is critical for distinguishing between the chemical and biological mechanisms that contribute to food web biomagnification and quantifying contaminant exposure risks in aquatic ecosystems. The present study examined the relative contributions of chemical hydrophobicity (octanol-water partition coefficient [KOW ]) and habitat use as factors regulating variability in polychlorinated biphenyl (PCB) congener bioaccumulation in 3 lower trophic level cyprinid species across spatial and temporal scales. Bluntnose minnows (Pimephales notatus), spottail shiners (Notropis hudsonius), and emerald shiners (Notropis atherinoides) were sampled at 3 locations in the Detroit River, Ontario, Canada. Variability in PCB concentration was evaluated with respect to several factors, including chemical hydrophobicity, site, season, species, and weight using sum of squares and Levene's test of homogeneity of variance. Individual variability in bioaccumulated congener-specific residues depended on chemical hydrophobicity with mid- and high-range KOW congeners (log KOW >6.0), demonstrating the highest amount of variance compared with low KOW congeners. Different feeding strategies also contributed to the variance observed for mid-range KOW congeners among species. In the present study, benthic feeding specialists exhibited lower variance in PCB concentrations compared with the 2 generalist species. The results indicate that chemical hydrophobicity and feeding ecology not only contribute to differences in the biomagnification potentials of fish, but also regulate between-individual variation in PCB concentrations both across and within fish species.