Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning

Spatially explicit predictions of food web structure from regional-level data

Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated spatial data for species interactions. Yet, recent developments in metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to using the current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large-scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from global databases. We investigated how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Species richness and interactions followed a similar latitudinal gradient across ecoregions but simultaneously identified contrasting diversity hotspots. Network motifs revealed additional areas of variation in network structure compared with species richness and number of links. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Spatial food webs in the Barents Sea: atlantification and the reorganization of the trophic structure

Climate change affects ecosystems at several levels: by altering the spatial distribution of individual species, by locally rewiring interspecific interactions, and by reorganizing trophic networks at larger scales. The dynamics of marine food webs are becoming more and more sensitive to spatial processes and connections in the seascape. As a case study, we study the atlantification of the Barents Sea: we compare spatio-temporal subsystems at three levels: the identity of key organisms, critically important interactions and the entire food web. Network analysis offers quantitative measurements, including centrality indices, trophic similarity indices, a topological measure of interaction asymmetry and network-level measures. We found that atlantification alters the identity of key species (boreal demersals becoming hubs), results in strongly asymmetric interactions (dominated by haddock), changes the dominant regulation regime (from bottom-up to wasp-waist control) and makes the food web less modular. Since the results of food web analysis may be quite sensitive to network construction, the aggregation of food web data was explicitly studied to increase the robustness of food web analysis. We found that an alternative, mathematical aggregation algorithm better preserves some network properties (e.g. density) of the original, unaggregated network than the biologically inspired aggregation into functional groups. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Linking biodiversity, ecosystem function, and Nature's contributions to people: a macroecological energy flux perspective

At macroecological scales, the provision of Nature's contributions to people (NCP) is mostly estimated with biophysical information, ignoring the ecological processes underlying them. This hinders our ability to properly quantify the impact of declining biodiversity and the provision of NCP. Here, we propose a framework that combines local-scale food web energy flux approaches and large-scale biodiversity models to evaluate ecosystem functions and flux-related NCP at extensive spatiotemporal scales. Importantly, this approach has the potential to upscale ecosystem functions, assess the vulnerability of flux-related NCP to the climate crisis, and support the development of multiscale mitigation policies.

Invasive Spartina alterniflora habitat forms high energy fluxes but low food web stability compared to adjacent native vegetated habitats

Invasive Spartina spp. mostly colonizes a bare tidal flat and then establishes a new vegetated habitat, where it promotes the productivity of local ecosystems. However, it was unclear whether the invasive habitat could well exhibit ecosystem functioning, e.g. how its high productivity propagates throughout the food web and whether it thereby develops a high food web stability relative to native vegetated habitats. By developing quantitative food webs for a long-established invasive Spartina alterniflora habitat and adjacent native salt marsh (Suaeda salsa) and seagrass (Zostera japonica) habitats in China's Yellow River Delta, we investigated the distributions of energy fluxes, assessed the stability of food webs, and investigated the net trophic effects between trophic groups by combining all direct and indirect trophic interactions. Results showed that the total energy flux in the invasive S. alterniflora habitat was comparable to that in the Z. japonica habitat, whereas 4.5 times higher than that in the S. salsa habitat. While, the invasive habitat had the lowest trophic transfer efficiencies. Food web stability in the invasive habitat was about 3 and 40 times lower than that in the S. salsa and Z. japonica habitats, respectively. Additionally, there were strong net effects caused by intermediate invertebrate species in the invasive habitat rather than by fish species in both native habitats. This study revealed the contradiction between the promotion of energy fluxes and the decrease of food web stability resulting from the invasion of S. alterniflora, which provides new insights into the community-based management of plant invasions.

Impacts of extreme climatic events on trophic network complexity and multidimensional stability

Untangling the relationship between network complexity and ecological stability under climate change is an arduous challenge for theoretical and empirical ecology. Even more so, when considering extreme climatic events. Here, we studied the effects of extreme climatic events (heatwaves) on the complexity of realistic freshwater ecosystems using topological and quantitative trophic network metrics. Next, we linked changes in network complexity with the investigation of four stability components (temporal stability, resistance, resilience, and recovery) of community's functional, compositional, and energy flux stability. We found reduction in topological network complexity to be correlated with reduction of functional and compositional resistance. However, temperature-driven increase in link-weighted network complexity increased functional and energy flux recovery and resilience, but at the cost of increased compositional instability. Overall, we propose an overarching approach to elucidate the effects of climate change on multidimensional stability through the lens of network complexity, providing helpful insights for preserving ecosystems stability under climate change.

Why are biodiversity-ecosystem functioning relationships so elusive? Trophic interactions may amplify ecosystem function variability

The relationship between biodiversity and ecosystem functions (BEFs) has attracted great interest. Studies on BEF have so far focused on the average trend of ecosystem function as species diversity increases. A tantalizing but rarely addressed question is why large variations in ecosystem functions are often observed across systems with similar species diversity, likely obscuring observed BEFs. Here we use a multi-trophic food web model in combination with empirical data to examine the relationships between species richness and the variation in ecosystem functions (VEFs) including biomass, metabolism, decomposition, and primary and secondary production. We then probe the mechanisms underlying these relationships, focusing on the role of trophic interactions. While our results reinforce the previously documented positive BEF relationships, we found that ecosystem functions exhibit significant variation within each level of species richness and the magnitude of this variation displays a hump-shaped relationship with species richness. Our analyses demonstrate that VEFs is reduced when consumer diversity increases through elevated nonlinearity in trophic interactions, and/or when the diversity of basal species such as producers and decomposers decreases. This explanation is supported by a 34-year empirical food web time series from the Gulf of Riga ecosystem. Our work suggests that biodiversity loss may not only result in ecosystem function decline, but also reduce the predictability of functions by generating greater function variability among ecosystems. It thus helps to reconcile the debate on the generality of positive BEF relationships and to disentangle the drivers of ecosystem stability. The role of trophic interactions and the variation in their strengths mediated by functional responses in shaping ecosystem function variation warrants further investigations and better incorporation into biodiversity-ecosystem functioning research.

Food web assessments in the Baltic Sea: Models bridging the gap between indicators and policy needs

Ecosystem-based management requires understanding of food webs. Consequently, assessment of food web status is mandatory according to the European Union's Marine Strategy Framework Directive (MSFD) for EU Member States. However, how to best monitor and assess food webs in practise has proven a challenging question. Here, we review and assess the current status of food web indicators and food web models, and discuss whether the models can help addressing current shortcomings of indicator-based food web assessments, using the Baltic Sea as an example region. We show that although the MSFD food web assessment was designed to use food web indicators alone, they are currently poorly fit for the purpose, because they lack interconnectivity of trophic guilds. We then argue that the multiple food web models published for this region have a high potential to provide additional coherence to the definition of good environmental status, the evaluation of uncertainties, and estimates for unsampled indicator values, but we also identify current limitations that stand in the way of more formal implementation of this approach. We close with a discussion of which current models have the best capacity for this purpose in the Baltic Sea, and of the way forward towards the combination of measurable indicators and modelling approaches in food web assessments.

Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient

Species interactions underlie most ecosystem functions and are important for understanding ecosystem changes. Representing one type of species interaction, trophic networks were constructed from biodiversity monitoring data and known trophic links to assess how ecosystems have changed over time. The Baltic Sea is subject to many anthropogenic pressures, and low species diversity makes it an ideal candidate for determining how pressures change food webs. In this study, we used benthic monitoring data for 20 years (1980-1989 and 2010-2019) from the Swedish coast of the Baltic Sea and Skagerrak to investigate changes in benthic invertebrate trophic interactions. We constructed food webs and calculated fundamental food web metrics evaluating network horizontal and vertical diversity, as well as stability that were compared over space and time. Our results show that the west coast of Sweden (Skagerrak) suffered a reduction in benthic invertebrate biodiversity by 32% between the 1980s and 2010s, and that the number of links, generality of predators, and vulnerability of prey have been significantly reduced. The other basins (Bothnian Sea, Baltic Proper, and Bornholm Basin) do not show any significant changes in species richness or consistent significant trends in any food web metrics investigated, demonstrating resilience at a lower species diversity. The decreased complexity of the Skagerrak food webs indicates vulnerability to further perturbations and pressures should be limited as much as possible to ensure continued ecosystem functions.

Network analysis suggests changes in food web stability produced by bottom trawl fishery in Patagonia

Demersal fisheries are one of the top anthropic stressors in marine environments. In the long term, some species are more vulnerable to fishery impacts than others, which can lead to permanent changes on the food web. The trophic relationships between predator and prey constitute the food web and it represents a network of the energy channels in an ecosystem. In turn, the network structure influences ecosystem diversity and stability. The first aim of this study was to describe for the first time the food web of the San Jorge Gulf (Patagonia Argentina) with high resolution, i.e. to the species level when information is available. The San Jorge Gulf was subject to intense fisheries thus our second aim is to analyse the food web structure with and without fishery to evaluate if the bottom-trawl industrial fishery altered the network structure and stability. We used several network metrics like: mean trophic level, omnivory, modularity and quasi-sign stability. We included these metrics because they are related to stability and can be evaluated using predator diets that can weight the links between predators and prey. The network presented 165 species organized in almost five trophic levels. The inclusion of a fishery node adds 69 new trophic links. All weighted and unweighted metrics showed differences between the two networks, reflecting a decrease in stability when fishery was included in the system. Thus, our results suggested a probable change of state of the system. The observed changes in species abundances since the fishery was established, could represent the state change predicted by network analysis. Our results suggests that changes in the stability of food webs can be used to evaluate the impacts of human activity on ecosystems.

Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level

Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs a longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food-web analysis to assess the influence of species interactions on community recovery. We found species-interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species-interaction strength and food-web architecture change significantly.

Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community-composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrient enrichment, and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified postdisturbance interaction-strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticide interactions to be significant in the long term only when both interaction strength and food-web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery.

EcoDiet: A hierarchical Bayesian model to combine stomach, biotracer, and literature data into diet matrix estimation

Although quantifying trophic interactions is a critical path to understanding and forecasting ecosystem functioning, fitting trophic models to field data remains challenging. It requires flexible statistical tools to combine different sources of information from the literature and fieldwork samples. We present EcoDiet, a hierarchical Bayesian modeling framework to simultaneously estimate food-web topology and diet composition of all consumers in the food web, by combining (1) a priori knowledge from the literature on both food-web topology and diet proportions; (2) stomach content analyses, with frequencies of prey occurrence used as the primary source of data to update the prior knowledge on the topological food-web structure; (3) and biotracers data through a mixing model (MM). Inferences are derived in a Bayesian probabilistic rationale that provides a formal way to incorporate prior information and quantifies uncertainty around both the topological structure of the food web and the dietary proportions. EcoDiet was implemented as an open-source R package, providing a user-friendly interface to execute the model, as well as examples and guidelines to familiarize with its use. We used simulated data to demonstrate the benefits of EcoDiet and how the framework can improve inferences on diet matrix by comparison with classical network MM. We applied EcoDiet to the Celtic Sea ecosystem, and showed how combining multiple data types within an integrated approach provides a more robust and holistic picture of the food-web topology and diet matrices than the literature or classical MM approach alone. EcoDiet has the potential to become a reference method for building diet matrices as a preliminary step of ecosystem modeling and to improve our understanding of prey-predator interactions.

DNA metabarcoding reveals trophic niche diversity of micro and mesozooplankton species

Alternative pathways of energy transfer guarantee the functionality and productivity in marine food webs that experience strong seasonality. Nevertheless, the complexity of zooplankton interactions is rarely considered in trophic studies because of the lack of detailed information about feeding interactions in nature. In this study, we used DNA metabarcoding to highlight the diversity of trophic niches in a wide range of micro- and mesozooplankton, including ciliates, rotifers, cladocerans, copepods and their prey, by sequencing 16- and 18S rRNA genes. Our study demonstrates that the zooplankton trophic niche partitioning goes beyond both phylogeny and size and reinforces the importance of diversity in resource use for stabilizing food web efficiency by allowing for several different pathways of energy transfer. We further highlight that small, rarely studied zooplankton (rotifers and ciliates) fill an important role in the Baltic Sea pelagic primary production pathways and the potential of ciliates, rotifers and crustaceans in the utilization of filamentous and picocyanobacteria within the pelagic food web. The approach used in this study is a suitable entry point to ecosystem-wide food web modelling considering species-specific resource use of key consumers.