Accounting for activity respiration results in realistic trophic transfer efficiencies in allometric trophic network (ATN) models

Body Mass-Biomass Scaling Modulates Species Keystone-Ness to Press Perturbations

Identifying species with disproportionate effects on other species under press perturbations is essential, yet how species traits and community context drive their 'keystone-ness' remain unclear. We quantified keystone-ness as linearly approximated per capita net effect derived from normalised inverse community matrices and as non-linear per capita community biomass change from simulated perturbations in food webs with varying biomass structure. In bottom-heavy webs (negative relationship between species' body mass and their biomass within the web), larger species at higher trophic levels tended to be keystone species, whereas in top-heavy webs (positive body mass to biomass relationship), the opposite was true and the relationships between species' energetic traits and keystone-ness were weakened or reversed compared to bottom-heavy webs. Linear approximations aligned well with non-linear responses in bottom-heavy webs, but were less consistent in top-heavy webs. These findings highlight the importance of community context in shaping species' keystone-ness and informing effective conservation actions.

Assessing impacts of bycatch policies and fishers' heterogeneous information on food webs and fishery sustainability

Ecosystem-based fisheries management (EBFM) has emerged as a promising framework for understanding and managing the long-term interactions between fisheries and the larger marine ecosystems in which they are nested. However, successful implementation of EBFM has been elusive because we still lack a comprehensive understanding of the network of interacting species in marine ecosystems (the food web) and the dynamic relationship between the food web and the humans who harvest those ecosystems. Here, we advance such understanding by developing a network framework that integrates the complexity of food webs with the economic dynamics of different management policies. Specifically, we generate hundreds of different food web models with 20-30 species, each harvested by five different fishers extracting the biomass of a target and a bycatch species, subject to two different management scenarios and exhibiting different information in terms of avoiding bycatch when harvesting the target species. We assess the different ecological and economic consequences of these policy alternatives as species extinctions and profit from sustaining the fishery. We present the results of different policies relative to a benchmark open access scenario where there are no management policies in place. The framework of our network model would allow policymakers to evaluate different management approaches without compromising on the ecological complexities of a fishery.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Food-web complexity, consumer behavior, and diet specialism: impacts on ecosystem stability

Ecological stability is a fundamental aspect of food web dynamics. In this study, we explore the factors influencing stability in complex ecological networks, characterizing it through biomass oscillations and species persistence. Using an Extended Niche model, we generate diverse food web structures and investigate the effects of intraspecific consumer interference, network size, connectance, and diet specialism on stability. Our findings reveal that intraspecific consumer interference plays a pivotal role in shaping stability. Higher interference results in stable dynamics, reducing oscillations and extinctions. Additionally, differences emerge between food webs comprised of invertebrate consumers and those of ectotherm vertebrates, with the latter showing higher oscillations. Network size and connectance also influence stability, where larger and more connected webs tend to exhibit reduced oscillations. Overall, our study sheds light on the complex interplay of factors affecting ecological stability in food webs. Understanding these dynamics is crucial for biodiversity conservation and ecosystem management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12080-024-00580-w.

Effects of temporal abiotic drivers on the dynamics of an allometric trophic network model

Current ecological research and ecosystem management call for improved understanding of the abiotic drivers of community dynamics, including temperature effects on species interactions and biomass accumulation. Allometric trophic network (ATN) models, which simulate material (carbon) transfer in trophic networks from producers to consumers based on mass‐specific metabolic rates, provide an attractive framework to study consumer–resource interactions from organisms to ecosystems. However, the developed ATN models rarely consider temporal changes in some key abiotic drivers that affect, for example, consumer metabolism and producer growth. Here, we evaluate how temporal changes in carrying capacity and light‐dependent growth rate of producers and in temperature‐dependent mass‐specific metabolic rate of consumers affect ATN model dynamics, namely seasonal biomass accumulation, productivity, and standing stock biomass of different trophic guilds, including age‐structured fish communities. Our simulations of the pelagic Lake Constance food web indicated marked effects of temporally changing abiotic parameters on seasonal biomass accumulation of different guild groups, particularly among the lowest trophic levels (primary producers and invertebrates). While the adjustment of average irradiance had minor effect, increasing metabolic rate associated with 1–2°C temperature increase led to a marked decline of larval (0‐year age) fish biomass, but to a substantial biomass increase of 2‐ and 3‐year‐old fish that were not predated by ≥4‐year‐old top predator fish, European perch (Perca fluviatilis). However, when averaged across the 100 simulation years, the inclusion of seasonality in abiotic drivers caused only minor changes in standing stock biomasses and productivity of different trophic guilds. Our results demonstrate the potential of introducing seasonality in and adjusting the average values of abiotic ATN model parameters to simulate temporal fluctuations in food‐web dynamics, which is an important step in ATN model development aiming to, for example, assess potential future community‐level responses to ongoing environmental changes.

Analysis on the stability of plankton in a food web with empirical organism body mass distribution

The mechanism supporting the stability of complex food webs is an important, yet still controversial issue in ecology. Integrating the bioenergetic model with a natural plankton food web with empirical organism body mass distribution, we studied the effects of taxa diversity, nutrient enrichment simulation and connectance on the stability of plankton, and the underlying mechanisms. The behavior and functions of plankton with different body masses in the system were also explored. The results showed that genus richness promoted the temporal stability of community but reduced that of population. Meanwhile, the effects of taxon extinction on community biomass and temporal stability depended on the body masses of those lost taxa. Enrichment decreased phytoplankton and zooplankton community stability directly by increasing the temporal variability of biomass and indirectly by reducing taxa diversity. Enrichment preferentially caused phytoplankton taxa with the highest individual biomass to go extinct and the ones with smaller to increase in biomass. The effects, as well as the underlying mechanisms of connectance on phytoplankton and zooplankton stability were different. High connectance promoted the persistence and biomasses of both zooplankton and small-bodied phytoplankton but reduced those of larger-bodied phytoplankton. The results and methodology in this research will be helpful in understanding and analyzing the stability of plankton communities.

Trophic Transfer Efficiency in Lakes

Trophic transfer efficiency (TTE) is usually calculated as the ratio of production rates between two consecutive trophic levels. Although seemingly simple, TTE estimates from lakes are rare. In our review, we explore the processes and structures that must be understood for a proper lake TTE estimate. We briefly discuss measurements of production rates and trophic positions and mention how ecological efficiencies, nutrients (N, P) and other compounds (fatty acids) affect energy transfer between trophic levels and hence TTE. Furthermore, we elucidate how TTE estimates are linked with size-based approaches according to the Metabolic Theory of Ecology, and how food-web models can be applied to study TTE in lakes. Subsequently, we explore temporal and spatial heterogeneity of production and TTE in lakes, with a particular focus on the links between benthic and pelagic habitats and between the lake and the terrestrial environment. We provide an overview of TTE estimates from lakes found in the published literature. Finally, we present two alternative approaches to estimating TTE. First, TTE can be seen as a mechanistic quantity informing about the energy and matter flow between producer and consumer groups. This approach is informative with respect to food-web structure, but requires enormous amounts of data. The greatest uncertainty comes from the proper consideration of basal production to estimate TTE of omnivorous organisms. An alternative approach is estimating food-chain and food-web efficiencies, by comparing the heterotrophic production of single consumer levels or the total sum of all heterotrophic production including that of heterotrophic bacteria to the total sum of primary production. We close the review by pointing to a few research questions that would benefit from more frequent and standardized estimates of TTE in lakes.

Top predators govern multitrophic diversity effects in tritrophic food webs

It is well known that functional diversity strongly affects ecosystem functioning. However, even in rather simple model communities consisting of only two or, at best, three trophic levels, the relationship between multitrophic functional diversity and ecosystem functioning appears difficult to generalize, because of its high contextuality. In this study, we considered several differently structured tritrophic food webs, in which the amount of functional diversity was varied independently on each trophic level. To achieve generalizable results, largely independent of parametrization, we examined the outcomes of 128,000 parameter combinations sampled from ecologically plausible intervals, with each tested for 200 randomly sampled initial conditions. Analysis of our data was done by training a random forest model. This method enables the identification of complex patterns in the data through partial dependence graphs, and the comparison of the relative influence of model parameters, including the degree of diversity, on food-web properties. We found that bottom-up and top-down effects cascade simultaneously throughout the food web, intimately linking the effects of functional diversity of any trophic level to the amount of diversity of other trophic levels, which may explain the difficulty in unifying results from previous studies. Strikingly, only with high diversity throughout the whole food web, different interactions synergize to ensure efficient exploitation of the available nutrients and efficient biomass transfer to higher trophic levels, ultimately leading to a high biomass and production on the top level. The temporal variation of biomass showed a more complex pattern with increasing multitrophic diversity: while the system initially became less variable, eventually the temporal variation rose again because of the increasingly complex dynamical patterns. Importantly, top predator diversity and food-web parameters affecting the top trophic level were of highest importance to determine the biomass and temporal variability of any trophic level. Overall, our study reveals that the mechanisms by which diversity influences ecosystem functioning are affected by every part of the food web, hampering the extrapolation of insights from simple monotrophic or bitrophic systems to complex natural food webs.

Integrating economic dynamics into ecological networks: The case of fishery sustainability

Understanding anthropogenic impacts on ecosystems requires investigating feedback processes between ecological and economic dynamics. While network ecology has advanced our understanding of large-scale communities, it has not robustly coupled economic drivers of anthropogenic impact to ecological outcomes. Leveraging allometric trophic network models, we study such integrated economic-ecological dynamics in the case of fishery sustainability. We incorporate economic drivers of fishing effort into food-web network models, evaluating the dynamics of thousands of single-species fisheries across hundreds of simulated food webs under fixed-effort and open-access management strategies. Analyzing simulation results reveals that harvesting species with high population biomass can initially support fishery persistence but threatens long-term economic and ecological sustainability by indirectly inducing extinction cascades in non-harvested species. This dynamic is exacerbated in open-access fisheries where profit-driven growth in fishing effort increases perturbation strength. Our results demonstrate how network theory provides necessary ecological context when considering the sustainability of economically dynamic fishing effort.

Mutualism increases diversity, stability, and function of multiplex networks that integrate pollinators into food webs

Ecosystems are composed of complex networks of many species interacting in different ways. While ecologists have long studied food webs of feeding interactions, recent studies increasingly focus on mutualistic networks including plants that exchange food for reproductive services provided by animals such as pollinators. Here, we synthesize both types of consumer-resource interactions to better understand the controversial effects of mutualism on ecosystems at the species, guild, and whole-community levels. We find that consumer-resource mechanisms underlying plant-pollinator mutualisms can increase persistence, productivity, abundance, and temporal stability of both mutualists and non-mutualists in food webs. These effects strongly increase with floral reward productivity and are qualitatively robust to variation in the prevalence of mutualism and pollinators feeding upon resources in addition to rewards. This work advances the ability of mechanistic network theory to synthesize different types of interactions and illustrates how mutualism can enhance the diversity, stability, and function of complex ecosystems.