Foraging adaptation and the relationship between food-web complexity and stability

Environmental gradient changes shape multi-scale food web structures: Impact on antibiotics trophic transfer in a lake ecosystem

Environmental change can alter the multi-scale foodweb structure, thereby impacting the pollutants trophic transfer in aquatic ecosystems. However, a quantitative understanding of how environmental gradient changes affect pollutant trophic transfer in natural lake ecosystems remains limited. This study investigated temporal variations in environment change index (ECi), multi-scale foodweb structure, and trophic transfer of quinolones antibiotics (QNs) in Baiyangdian Lake, Northern China, from 2018 to 2023. Our results demonstrated that the interaction strength (IS) in detritus (DIS) and macrophyte (MIS) in 2023 were significantly lower than those in 2018, and diversity indices exhibited significant temporal differences between 2018 and 2023. ECi was significantly correlated with DIS/MIS between species at the population scale and with diversity indices (DH and H') at the ecosystem scale. The trophic magnification factors (TMFs) of QNs have higher values in 2023 compared to 2018, showing significant temporal differences. Through structural equation model, the results showed ECi directly impacted DIS, which in turn affected SEAc and H', while indirectly influencing TMFs. The TMFs of QNs was mainly regulated by environmental factors. These findings highlighted the influencing mechanism through multi-scale foodweb structures regulate pollutant trophic transfer under environmental change in natural lake.

Unraveling Omnivory and Community Interactions Between Primary Producers and an Apex Predator

The effects of climate and plant phenological changes on herbivorous species are widely recognized, yet less research has focused on predatory species, even though vegetative components can account for large proportions of their diet. The historical focus on predation through the lens of simple interactions between obligate carnivores and their prey oversimplifies many species' roles within ecological communities and minimizes other, equally important community functions. We used a long-term, individual-based dataset on an omnivorous species, the brown bear (Ursus arctos), to identify long-term diet patterns and factors contributing to annual variation in diet. We used carbon and nitrogen stable isotopes measured in hair and Bayesian mixing models to determine annual diet among three demographic classes and then used linear mixed models to relate diet to indices of food availability. Variation in both carbon and nitrogen values were explained by bilberry (Vaccinium myrtillus) productivity. Additionally, even as the moose population increased over time, there was no increase in the proportion of moose in the diet. The variation in the proportion of moose in the diet slightly decreased throughout the study, while the proportion of bilberry became increasingly more variable. Our results highlight that even though vegetative diet components are typically considered less important to predator ecology, brown bear diet in Sweden responded to changes in berry availability, regardless of prey availability. It will be crucial to put more emphasis on the vegetative parts of diets as we predict how species and ecological communities respond to climate change because predators serve many more functions within their community besides predation alone.

Fish Community Resource Utilization Reveals Benthic-Pelagic Trophic Coupling Along Depth Gradients in the Beibu Gulf, South China Sea

Benthic-pelagic coupling is a key approach to studying the structure and energy dynamics of shallow marine food webs. The movement and foraging patterns of consumers are major drivers of nutrient and energy distribution in ecosystems and are critical for maintaining ecosystem stability. To better understand the energy coupling of consumers between coastal marine habitats, this study employed a Bayesian mixture model using SC and SI data. By classifying functional groups based on taxonomy, morphological traits, and feeding ecology similarities, we constructed a trophic network and analyzed the changes in fish feeding patterns and the dynamics of benthic-pelagic coupling across environmental gradients. The results show that the primary carbon sources in the Beibu Gulf are phytoplankton, particulate organic matter (POM), and sediment organic matter (SOM), with phytoplankton contributing the most. Pelagic food subsidies dominate the food web. Small sized, abundant planktivorous and benthivorous fish act both as predators and important prey, transferring carbon and energy derived from both benthic and pelagic zones to higher trophic-levels. Larger, higher-trophic-level piscivorous fish serve as key energy couplers, preying on organisms from various habitats. Depth and chlorophyll-a (Chl-a) are the two key variables influencing the trophic structure of fish, with opposite gradient patterns observed for each. Along the depth gradient, fish exhibit clear adaptive foraging strategies. As water depth increases, fish tend to forage more within their specific habitat (either benthic or pelagic), with prey types continually changing, leading to a gradual reduction in the strength of benthic-pelagic trophic coupling. This study reveals the spatial resource utilization patterns and adaptive foraging strategies of fish in the Beibu Gulf, providing deeper insights into the structure and spatial variation of food webs. It also enhances our understanding of ecosystem responses to human pressures and global changes, offering valuable perspectives for predicting these responses.

Food-web dynamics of a floodplain mosaic overshadow the effects of engineered logjams for Pacific salmon and steelhead

Food webs vary in space and time. The structure and spatial arrangement of food webs are theorized to mediate temporal dynamics of energy flow, but empirical corroboration in intermediate-scale landscapes is scarce. River-floodplain landscapes encompass a mosaic of aquatic habitat patches and food webs, supporting a variety of aquatic consumers of conservation concern. How the structure and productivity of these patch-scale food webs change through time, and how floodplain restoration influences their dynamics, are unevaluated. We measured productivity and food-web dynamics across a mosaic of main-channel and side-channel habitats of the Methow River, WA, USA, during two study years (2009-2010; 2015-2016) and examined how food webs that sustained juvenile anadromous salmonids responded to habitat manipulation. By quantifying temporal variation in secondary production and organic matter flow across nontreated river-floodplain habitats and comparing that variation to a side channel treated with engineered logjams, we jointly confronted spatial food-web theory and assessed whether food-web dynamics in the treated side channel exceeded natural variation exhibited in nontreated habitats. We observed that organic matter flow through the more complex, main-channel food web was similar between study years, whereas organic matter flow through the simpler, side-channel food webs changed up to ~4-fold. In the side channel treated with engineered logjams, production of benthic invertebrates and juvenile salmonids increased between study years by 2× and 4×, respectively; however, these changes did not surpass the temporal variation observed in untreated habitats. For instance, juvenile salmonid production rose 17-fold in one untreated side-channel habitat, and natural aggregation of large wood in another coincided with a shift to community and food-web dominance by juvenile salmonids. Our findings suggest that interannual dynamism in material flux across floodplain habitat mosaics is interrelated with patchiness in food-web complexity and may overshadow the ecological responses to localized river restoration. Although this dynamism may inhibit detection of the ecological effects of river restoration, it may also act to stabilize aquatic ecosystems and buffer salmon and other species of conservation concern in the long term. As such, natural, landscape-level patchiness and dynamism in food webs should be integrated into conceptual foundations of process-based, river restoration.

Spatiotemporal patterns of trophic niche variation within and among species of tropical coastal fishes

Intraspecific niche variation shapes the structure and function of food webs, but we still know little about the magnitude and drivers of trophic variation within species in species‐rich communities. Here, we examined how intrinsic (sex and life stage) and extrinsic (locality and season) factors affect the diet composition and trophic niche width of tropical fish species. Specifically, we studied co‐occurring species with benthopelagic (Stellifer ericymba, S. melanocheir, S. zestocarus, and Larimus argenteus) and benthic feeding habits (S. strabo, Cathorops manglarensis, Notarius troschelii, and Urotrygon rogersi) on the central Pacific coast of Colombia. Overall, we observed strong spatial and seasonal effects driving variation in the consumption of (i) amphipods, copepods, and decapods for benthopelagic species and (ii) mollusks and polychaetes for benthic species. As expected, we observed little sexual diet variation; however, surprisingly, most species showed little ontogenetic diet variation. Seasonality strongly shaped the trophic niche width for most species, but effects were species‐specific, suggesting no general pattern of seasonal niche expansion across species. In turn, spatial effects on the trophic niche width were congruent across species, which might be related to differences in the diversity of available resources between bays. Our results reveal the complex interplay between intrinsic and extrinsic factors in shaping resource exploitation by coastal fish. This high level of trophic plasticity may be a critical component for both the persistence of marine populations and the stability of local food webs.

Abstract in Spanish is available with online material.

Multifaceted effects of variable biotic interactions on population stability in complex interaction webs

Recent studies have revealed that biotic interactions in ecological communities vary over time, possibly mediating community responses to anthropogenic disturbances. This study investigated the heterogeneity of such variability within a real community and its impact on population stability in the face of pesticide application, particularly focusing on density-dependence of the interaction effect. Using outdoor mesocosms with a freshwater community, we found considerable heterogeneity in density-dependent interaction variability among links in the same community. This variability mediated the stability of recipient populations, with negative density-dependent interaction variability stabilizing whereas positive density-dependence and density-independent interaction variability destabilizing populations. Unexpectedly, the mean interaction strength, which is typically considered crucial for stability, had no significant effect, suggesting that how organisms interact on average is insufficient to predict the ecological impacts of pesticides. Our findings emphasize the multifaceted role of interaction variability in predicting the ecological consequences of anthropogenic disturbances such as pesticide application.

Connected interactions: enriching food web research by spatial and social interactions

This theme issue features 18 papers exploring ecological interactions, encompassing metabolic, social, and spatial connections alongside traditional trophic networks. This integration enriches food web research, offering insights into ecological dynamics. By examining links across organisms, populations, and ecosystems, a hierarchical approach emerges, connecting horizontal effects within organizational levels vertically across biological organization levels. The inclusion of interactions involving humans is a key focus, highlighting the need for their integration into ecology given the complex interactions between human activities and ecological systems in the Anthropocene. The comprehensive exploration in this theme issue sheds light on the interconnectedness of ecological systems and the importance of considering diverse interactions in understanding ecosystem dynamics. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Predicting emergent animal biodiversity patterns across multiple scales

Restoring biodiversity-based resilience and ecosystem multi-functionality needs to be informed by more accurate predictions of animal biodiversity responses to environmental change. Ecological models make a substantial contribution to this understanding, especially when they encode the biological mechanisms and processes that give rise to emergent patterns (population, community, ecosystem properties and dynamics). Here, a distinction between 'mechanistic' and 'process-based' ecological models is established to review existing approaches. Mechanistic and process-based ecological models have made key advances to understanding the structure, function and dynamics of animal biodiversity, but are typically designed to account for specific levels of biological organisation and spatiotemporal scales. Cross-scale ecological models, which predict emergent co-occurring biodiversity patterns at interacting scales of space, time and biological organisation, is a critical next step in predictive ecology. A way forward is to first capitalise on existing models to systematically evaluate the ability of scale-explicit mechanisms and processes to predict emergent patterns at alternative scales. Such model intercomparisons will reveal mechanism to process transitions across fine to broad scales, overcome approach-specific barriers to model realism or tractability and identify gaps which necessitate the development of new fundamental principles. Key challenges surrounding model complexity and uncertainty would need to be addressed, and while opportunities from big data can streamline the integration of multiple scale-explicit biodiversity patterns, ambitious cross-scale field studies are also needed. Crucially, overcoming cross-scale ecological modelling challenges would unite disparate fields of ecology with the common goal of improving the evidence-base to safeguard biodiversity and ecosystems under novel environmental change.

Oil and gas platforms degrade benthic invertebrate diversity and food web structure

Oil and gas exploitation introduces toxic contaminants such as hydrocarbons and heavy metals to the surrounding sediment, resulting in deleterious impacts on marine benthic communities. This study combines benthic monitoring data over a 30-year period in the North Sea with dietary information on >1400 taxa to quantify the effects of active oil and gas platforms on benthic food webs using a multiple before-after control-impact experiment. Contamination from oil and gas platforms caused declines in benthic food web complexity, community abundance, and biodiversity. Fewer trophic interactions and increased connectance indicated that the community became dominated by generalists adapting to alternative resources, leading to simpler but more connected food webs in contaminated environments. Decreased mean body mass, shorter food chains, and the dominance of small detritivores such as Capitella capitata near to structures suggested a disproportionate loss of larger organisms from higher trophic levels. These patterns were associated with concentrations of hydrocarbons and heavy metals that exceed OSPAR's guideline thresholds of sediment toxicity. This study provides new evidence to better quantify and manage the environmental consequences of oil and gas exploitation at sea.

Interconnection between density-regulation and stability in competitive ecological network

In natural ecosystems, species can be characterized by the nonlinear density-dependent self-regulation of their growth profile. Species of many taxa show a substantial density-dependent reduction for low population size. Nevertheless, many show the opposite trend; density regulation is minimal for small populations and increases significantly when the population size is near the carrying capacity. The theta-logistic growth equation can portray the intraspecific density regulation in the growth profile, theta being the density regulation parameter. In this study, we examine the role of these different growth profiles on the stability of a competitive ecological community with the help of a mathematical model of competitive species interactions. This manuscript deals with the random matrix theory to understand the stability of the classical theta-logistic models of competitive interactions. Our results suggest that having more species with strong density dependence, which self-regulate at low densities, leads to more stable communities. With this, stability also depends on the complexity of the ecological network. Species network connectance (link density) shows a consistent trend of increasing stability, whereas community size (species richness) shows a context-dependent effect. We also interpret our results from the aspect of two different life history strategies: r and K-selection. Our results show that the stability of a competitive network increases with the fraction of r-selected species in the community. Our result is robust, irrespective of different network architectures.

Individual diet variability shapes the architecture of Antarctic benthic food webs

Antarctic biodiversity is affected by seasonal sea-ice dynamics driving basal resource availability. To (1) determine the role of intraspecific dietary variability in structuring benthic food webs sustaining Antarctic biodiversity, and (2) understand how food webs and the position of topologically central species vary with sea-ice cover, single benthic individuals' diets were studied by isotopic analysis before sea-ice breakup and afterwards. Isotopic trophospecies (or Isotopic Trophic Units) were investigated and food webs reconstructed using Bayesian Mixing Models. As nodes, these webs used either ITUs regardless of their taxonomic membership (ITU-webs) or ITUs assigned to species (population-webs). Both were compared to taxonomic-webs based on taxa and their mean isotopic values. Higher resource availability after sea-ice breakup led to simpler community structure, with lower connectance and linkage density. Intra-population diet variability and compartmentalisation were crucial in determining community structure, showing population-webs to be more complex, stable and robust to biodiversity loss than taxonomic-webs. The core web, representing the minimal community 'skeleton' that expands opportunistically while maintaining web stability with changing resource availability, was also identified. Central nodes included the sea-urchin Sterechinus neumayeri and the bivalve Adamussium colbecki, whose diet is described in unprecedented detail. The core web, compartmentalisation and topologically central nodes represent crucial factors underlying Antarctica's rich benthic food web persistence.

Interaction network rewiring and species' contributions to community-scale flexibility

The architecture of species interaction networks is a key factor determining the stability of ecological communities. However, the fact that ecological network architecture can change through time is often overlooked in discussions on community-level processes, despite its theoretical importance. By compiling a time-series community dataset involving 50 spider species and 974 Hexapoda prey species/strains, we quantified the extent to which the architecture of predator-prey interaction networks could shift across time points. We then developed a framework for finding species that could increase the flexibility of the interaction network architecture. Those "network coordinator" species are expected to promote the persistence of species-rich ecological communities by buffering perturbations in communities. Although spiders are often considered as generalist predators, their contributions to network flexibility vary greatly among species. We also found that detritivorous prey species can be cores of interaction rewiring, dynamically interlinking below-ground and above-ground community dynamics. We further found that the predator-prey interactions between those network coordinators differed from those highlighted in the standard network-analytical framework assuming static topology. Analyses of network coordinators will add a new dimension to our understanding of species coexistence mechanisms and provide platforms for systematically prioritizing species in terms of their potential contributions in ecosystem conservation and restoration.

Dual species interaction and ecological community stability

How diverse species coexist in nature remains a challenging issue that is not yet resolved in ecology. The traditional approach to tackling this problem uses an ecological community network comprising various biological interaction links between species, such as predator-prey, mutualism, and competition. However, in nature, the interaction between any species pair is not limited to a singular interaction; instead, various interactions occur mostly in two ways, such as competition/facilitation in plants, mutualism/antagonism in consumer-resource mutualisms, and reciprocal predation. Here, using an ecological community model, I show that such so-called dual interactions play a key role in stabilizing ecological communities. Theory predicts that dual interactions can stabilize ecological communities through the balance of positive and negative effects, which behave as if the interactions disappear. Communities with dual interactions are inherently more stable than a classical random community with multiple types of singular interactions, suggesting that dual interactions are more widespread than expected in nature and help to maintain ecological communities.

Flexible foraging behaviour increases predator vulnerability to climate change

Higher temperatures are expected to reduce species coexistence by increasing energetic demands. However, flexible foraging behaviour could balance this effect by allowing predators to target specific prey species to maximize their energy intake, according to principles of optimal foraging theory. Here we test these assumptions using a large dataset comprising 2,487 stomach contents from six fish species with different feeding strategies, sampled across environments with varying prey availability over 12 years in Kiel Bay (Baltic Sea). Our results show that foraging shifts from trait- to density-dependent prey selectivity in warmer and more productive environments. This behavioural change leads to lower consumption efficiency at higher temperature as fish select more abundant but less energetically rewarding prey, thereby undermining species persistence and biodiversity. By integrating this behaviour into dynamic food web models, our study reveals that flexible foraging leads to lower species coexistence and biodiversity in communities under global warming.

Quantitative description of six fish species' gut contents and prey abundances in the Baltic Sea (1968-1978)

The dataset presents a compilation of stomach contents from six demersal fish species from two functional groups inhabiting the Baltic Sea. It includes detailed information on prey identities, body masses, and biomasses recovered from both the fish's digestive systems and their surrounding environment. Environmental parameters, such as salinity and temperature levels, have been integrated to enrich this dataset. The juxtaposition of information on prey found in stomachs and in the environment provides an opportunity to quantify trophic interactions across different environmental contexts and investigate how fish foraging behaviour adapts to changes in their environment, such as an increase in temperature. The compilation of body mass and taxonomic information for all species allows approaching these new questions using either a taxonomic (based on species identity) or functional trait (based on body mass) approach.

Analyzing tiger interaction and home range shifts using a time-geographic approach

BACKGROUND

Interaction through movement can be used as a marker to understand and model interspecific and intraspecific species dynamics, and the collective behavior of animals sharing the same space. This research leverages the time-geography framework, commonly used in human movement research, to explore the dynamic patterns of interaction between Indochinese tigers (Panthera tigris corbeti) in the western forest complex (WEFCOM) in Thailand.

METHODS

We propose and assess ORTEGA, a time-geographic interaction analysis method, to trace spatio-temporal interactions patterns and home range shifts among tigers. Using unique GPS tracking data of tigers in WEFCOM collected over multiple years, concurrent and delayed interaction patterns of tigers are investigated. The outcomes are compared for intraspecific tiger interaction across different genders, relationships, and life stages. Additionally, the performance of ORTEGA is compared to a commonly used proximity-based approach.

RESULTS

Among the 67 tracked tigers, 42 show concurrent interactions at shared boundaries. Further investigation of five tigers with overlapping home ranges (two adult females, a male, and two young male tigers) suggests that the mother tiger and her two young mostly stay together before their dispersal but interact less post-dispersal. The male tiger increases encounters with the mother tiger while her young shift their home ranges. On another timeline, the neighbor female tiger mostly avoids the mother tiger. Through these home range dynamics and interaction patterns, we identify four types of interaction among these tigers: following, encounter, latency, and avoidance. Compared to the proximity-based approach, ORTEGA demonstrates better detects concurrent mother-young interactions during pre-dispersal, while the proximity-based approach misses many interactions among the dyads. With larger spatial buffers and temporal windows, the proximity-based approach detects more encounters but may overestimate the duration of interaction.

CONCLUSIONS

This research demonstrates the applicability and merits of ORTEGA as a time-geographic based approach to animal movement interaction analysis. We show time geography can develop valuable, data-driven insights about animal behavior and interactions. ORTEGA effectively traces frequent encounters and temporally delayed interactions between animals, without relying on specific spatial and temporal buffers. Future research should integrate contextual and behavioral information to better identify and characterize the nature of species interaction.

Model-free prediction of microbiome compositions

BACKGROUND

The recent recognition of the importance of the microbiome to the host's health and well-being has yielded efforts to develop therapies that aim to shift the microbiome from a disease-associated state to a healthier one. Direct manipulation techniques of the species' assemblage are currently available, e.g., using probiotics or narrow-spectrum antibiotics to introduce or eliminate specific taxa. However, predicting the species' abundances at the new state remains a challenge, mainly due to the difficulties of deciphering the delicate underlying network of ecological interactions or constructing a predictive model for such complex ecosystems.

RESULTS

Here, we propose a model-free method to predict the species' abundances at the new steady state based on their presence/absence configuration by utilizing a multi-dimensional k-nearest-neighbors (kNN) regression algorithm. By analyzing data from numeric simulations of ecological dynamics, we show that our predictions, which consider the presence/absence of all species holistically, outperform both the null model that uses the statistics of each species independently and a predictive neural network model. We analyze real metagenomic data of human-associated microbial communities and find that by relying on a small number of "neighboring" samples, i.e., samples with similar species assemblage, the kNN predicts the species abundance better than the whole-cohort average. By studying both real metagenomic and simulated data, we show that the predictability of our method is tightly related to the dissimilarity-overlap relationship of the training data.

CONCLUSIONS

Our results demonstrate how model-free methods can prove useful in predicting microbial communities and may facilitate the development of microbial-based therapies. Video Abstract.

Adaptive rewiring shapes structure and stability in a three-guild herbivore-plant-pollinator network

Animal species, encompassing both pollinators and herbivores, exhibit a preference for plants based on optimal foraging theory. Understanding the intricacies of these adaptive plant-animal interactions in the context of community assembly poses a main challenge in ecology. This study delves into the impact of adaptive interaction rewiring between species belonging to different guilds on the structure and stability of a 3-guild ecological network, incorporating both mutualistic and antagonistic interactions. Our findings reveal that adaptive rewiring results in sub-networks becoming more nested and compartmentalized. Furthermore, the rewiring of interactions uncovers a positive correlation between a plant's generalism concerning both pollinators and herbivores. Additionally, there is a positive correlation between a plant's degree centrality and its energy budget. Although network stability does not exhibit a clear relationship with non-random structures, it is primarily influenced by the balance of multiple interaction strengths. In summary, our results underscore the significance of adaptive interaction rewiring in shaping the structure of 3-guild networks. They emphasize the importance of considering the balance of multiple interactions for the stability of adaptive networks, providing valuable insights into the complex dynamics of ecological communities.

Robustness versus productivity during evolutionary community assembly: short-term synergies and long-term trade-offs

The realization that evolutionary feedbacks need to be considered to fully grasp ecological dynamics has sparked interest in the effect of evolution on community properties like coexistence and productivity. However, little is known about the evolution of community robustness and productivity along diversification processes in species-rich systems. We leverage the recent structural approach to coexistence together with adaptive dynamics to study such properties and their relationships in a general trait-based model of competition on a niche axis. We show that the effects of coevolution on coexistence are two-fold and contrasting depending on the time scale considered. In the short term, evolution of niche differentiation strengthens coexistence, while long-term diversification leads to niche packing and decreased robustness. Moreover, we find that coevolved communities tend to be on average more robust and more productive than non-evolutionary assemblages. We illustrate how our theoretical predictions echo in observed empirical patterns and the implications of our results for empiricists and applied ecologists. We suggest that some of our results such as the improved robustness of Evolutionarily Stable Communities could be tested experimentally in suitable model systems.

Synthetic model ecosystem of 12 cryopreservable microbial species allowing for a noninvasive approach

Simultaneous understanding of both population and ecosystem dynamics is crucial in an era marked by the degradation of ecosystem services. Experimental ecosystems are a powerful tool for understanding these dynamics; however, they often face technical challenges, typically falling into two categories: "complex but with limited replicability microcosms" and "highly replicable but overly simplistic microcosms." Herein, we present a high-throughput synthetic microcosm system comprising 12 functionally and phylogenetically diverse microbial species. These species are axenically culturable, cryopreservable, and can be measured noninvasively via microscopy, aided by machine learning. This system includes prokaryotic and eukaryotic producers and decomposers, and eukaryotic consumers to ensure functional redundancy. Our model system exhibited key features of a complex ecosystem: (i) various positive and negative interspecific interactions, (ii) higher-order interactions beyond two-species dynamics, (iii) probabilistic dynamics leading to divergent outcomes, and (iv) stable nonlinear transitions. We identified several conditions under which at least one species from each of the three functional groups-producers, consumers, and decomposers-and one functionally redundant species, persisted for over six months. These conditions set the stage for detailed investigations in the future. Given its designability and experimental replicability, our model ecosystem offers a promising platform for deeper insights integrating both population and ecosystem dynamics.

Biodiversity and Constrained Information Dynamics in Ecosystems: A Framework for Living Systems

The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex post adaptation, typically associated with natural selection, and its proactive counterpart, ex ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified ecosystem stability, (ii) identified correlations between some biodiversity indexes and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, it was suggested that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories-fluctuations, rapid environmental responses, and long-term changes-converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems.

Dynamics of species-rich predator-prey networks and seasonal alternations of core species

In nature, entangled webs of predator-prey interactions constitute the backbones of ecosystems. Uncovering the network architecture of such trophic interactions has been recognized as the essential step for exploring species with great impacts on ecosystem-level phenomena and functions. However, it has remained a major challenge to reveal how species-rich networks of predator-prey interactions are continually reshaped through time in the wild. Here, we show that dynamics of species-rich predator-prey interactions can be characterized by remarkable network structural changes and alternations of species with greatest impacts on community processes. On the basis of high-throughput detection of prey DNA from 1,556 spider individuals collected in a grassland ecosystem, we reconstructed dynamics of interaction networks involving, in total, 50 spider species and 974 prey species and strains through 8 months. The networks were compartmentalized into modules (groups) of closely interacting predators and prey in each month. Those modules differed in detritus/grazing food chain properties, forming complex fission-fusion dynamics of belowground and aboveground energy channels across the seasons. The substantial shifts of network structure entailed alternations of spider species located at the core positions within the entangled webs of interactions. These results indicate that knowledge of dynamically shifting food webs is crucial for understanding temporally varying roles of 'core species' in ecosystem processes.

Seasonal variation in activity and nearshore habitat use of Lake Trout in a subarctic lake

BACKGROUND

In lake ecosystems, predatory fish can move and forage across both nearshore and offshore habitats. This coupling of sub-habitats, which is important in stabilizing lake food webs, has largely been assessed from a dietary perspective and has not included movement data. As such, empirical estimates of the seasonal dynamics of these coupling movements by fish are rarely quantified, especially for northern lakes. Here we collect fine-scale fish movement data on Lake Trout (Salvelinus namaycush), a predatory cold-water fish known to link nearshore and offshore habitats, to test for seasonal drivers of activity, habitat use and diet in a subarctic lake.

METHODS

We used an acoustic telemetry positioning array to track the depth and spatial movements of 43 Lake Trout in a subarctic lake over two years. From these data we estimated seasonal 50% home ranges, movements rates, tail beat activity, depth use, and nearshore habitat use. Additionally, we examined stomach contents to quantify seasonal diet. Data from water temperature and light loggers were used to monitor abiotic lake conditions and compare to telemetry data.

RESULTS

Lake Trout showed repeatable seasonal patterns of nearshore habitat use that peaked each spring and fall, were lower throughout the long winter, and least in summer when this habitat was above preferred temperatures. Stomach content data showed that Lake Trout acquired the most nearshore prey during the brief spring season, followed by fall, and winter, supporting telemetry results. Activity rates were highest in spring when feeding on invertebrates and least in summer when foraging offshore, presumably on large-bodied prey fish. High rates of nearshore activity in fall were associated with spawning. Nearshore habitat use was widespread and not localized to specific regions of the lake, although there was high overlap of winter nearshore core areas between years.

CONCLUSIONS

We provide empirical demonstrations of the seasonal extent to which a mobile top predator links nearshore and offshore habitats in a subarctic lake. Our findings suggest that the nearshore is an important foraging area for Lake Trout for much of the year, and the role of this zone for feeding should be considered in addition to its traditional importance as spawning habitat.

Tapeworms detected in wolf populations in Central Italy (Umbria and Marche regions): A long-term study

Tapeworms are trophically-transmitted and multi-host parasites with a complex indirect life cycle, strictly depending on predator-prey interactions. Their presence in a free-living population, mainly definitive hosts, is arduous to study due to the complexity of collecting fecal samples. However, epidemiological studies on their frequency are crucial from a public health perspective, providing information on food habits and prey selection of predators. The present study aims to update the frequency of tapeworms detected in stool samples by molecular analysis in Italian wolf populations of Umbria and Marche regions collected from 2014 to 2022. Tapeworm's total frequency was 43.2%. In detail, Taenia serialis was detected in 27 samples (21.6%), T. hydatigena in 22 (17.6%), and Mesocestoides corti (syn. M. vogae) in 2 (1.6%). Three samples were identified as M. litteratus and E. granulosus s.s. (G3) and T. pisiformis, with a proportion of 0.8%, respectively. The low frequency of E. granulosus in a hyperendemic area is discussed. The results show for the first time a high frequency of Taenia serialis not comparable to other Italian studies conducted on wild Carnivora; thus, a new ecological niche is conceivable. These findings suggest a plausible wolf-roe deer cycle for T. serialisin the investigated area.

Colonization-competition dynamics of basal species shape food web complexity in island metacommunities

Exploring how food web complexity emerges and evolves in island ecosystems remains a major challenge in ecology. Food webs assembled from multiple islands are commonly recognized as highly complex trophic networks that are dynamic in both space and time. In the context of global climate change, it remains unclear whether food web complexity will decrease in a monotonic fashion when undergoing habitat destruction (e.g., the inundation of islands due to sea-level rise). Here, we develop a simple yet comprehensive patch-dynamic framework for complex food web metacommunities subject to the competition-colonization tradeoff between basal species. We found that oscillations in food web topological complexity (characterized by species diversity, mean food chain length and the degree of omnivory) emerge along the habitat destruction gradient. This outcome is robust to changing parameters or relaxing the assumption of a strict competitive hierarchy. Having oscillations in food web complexity indicates that small habitat changes could have disproportionate negative effects on species diversity, thus the success of conservation actions should be evaluated not only on changes in biodiversity, but also on system robustness to habitat alteration. Overall, this study provides a parsimonious mechanistic explanation for the emergence of food web complexity in island ecosystems, further enriching our understanding of metacommunity assembly.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-023-00167-0.

Empirical evidence of type III functional responses and why it remains rare

More than 70 years after its introduction, the framework of resource density-dependent consumption rates, also known as predator-prey functional responses, remains a core concept in population and food web ecology. Initially, three types of responses were defined: linear (type I), hyperbolic (type II), and sigmoid (type III). Due to its potential to stabilize consumer-resource population dynamics, the sigmoid type III functional response immediately became a “holy grail” in population ecology. However, experimentally proving that type III functional responses exist, whether in controlled laboratory systems or in nature, was challenging. While theoretical and practical advances make identifying type III responses easier today, decades of research have brought only a limited number of studies that provide empirical evidence for type III response curves. Here, we review this evidence from laboratory- and field-based studies published during the last two decades. We found 107 studies that reported type III responses, but these studies ranged across various taxa, interaction types, and ecosystems. To put these studies into context, we also discuss the various biological mechanisms that may lead to the emergence of type III responses. We summarize how three different and mutually independent intricacies bedevil the empirical documentation of type III responses: (1) challenges in statistical modeling of functional responses, (2) inadequate resource density ranges and spacing, and (3) biologically meaningful and realistic design of experimental arenas. Finally, we provide guidelines on how the field should move forward based on these considerations.

Evolutionary emergence of alternative stable states in shallow lakes

Ecosystems under stress may respond abruptly and irreversibly through tipping points. Although mechanisms leading to alternative stable states are much studied, little is known about how such ecosystems could have emerged in the first place. We investigate whether evolution by natural selection along resource gradients leads to bistability, using shallow lakes as an example. There, tipping points occur between two alternative states dominated by either submersed or floating macrophytes depending on nutrient loading. We model the evolution of macrophyte depth in the lake, identify the conditions under which the ancestor population diversifies and investigate whether alternative stable states dominated by different macrophyte phenotypes occur. We find that eco-evolutionary dynamics may lead to alternative stable states, but under restrictive conditions. Such dynamics require sufficient asymmetries in the acquisition of both light and nutrient. Our analysis suggests that competitive asymmetries along opposing resource gradients may allow bistability to emerge by natural selection.

Interpreting random forest analysis of ecological models to move from prediction to explanation

As modeling tools and approaches become more advanced, ecological models are becoming more complex. Traditional sensitivity analyses can struggle to identify the nonlinearities and interactions emergent from such complexity, especially across broad swaths of parameter space. This limits understanding of the ecological mechanisms underlying model behavior. Machine learning approaches are a potential answer to this issue, given their predictive ability when applied to complex large datasets. While perceptions that machine learning is a "black box" linger, we seek to illuminate its interpretive potential in ecological modeling. To do so, we detail our process of applying random forests to complex model dynamics to produce both high predictive accuracy and elucidate the ecological mechanisms driving our predictions. Specifically, we employ an empirically rooted ontogenetically stage-structured consumer-resource simulation model. Using simulation parameters as feature inputs and simulation output as dependent variables in our random forests, we extended feature analyses into a simple graphical analysis from which we reduced model behavior to three core ecological mechanisms. These ecological mechanisms reveal the complex interactions between internal plant demography and trophic allocation driving community dynamics while preserving the predictive accuracy achieved by our random forests.

High variation in handling times confers 35-year stability to predator feeding rates despite community change

Historical resurveys of ecological communities are important for placing the structure of modern ecosystems in context. Rarely, however, are snapshot surveys alone sufficient for providing direct insight into the rates of the ecological processes underlying community functioning, either now or in the past. In this study, I used a statistically reasoned observational approach to estimate the feeding rates of a New Zealand intertidal predator, Haustrum haustorium, using diet surveys performed at several sites by Robert Paine in 1968-1969 and by me in 2004. Comparisons between time periods reveal a remarkable consistency in the predator's prey-specific feeding rates, which contrasts with the changes I observed in prey abundances, the predator's body-size distribution, and the prey's proportional contributions to the predator's apparent diet. Although these and additional changes in the predator's per-capita attack rates seem to show adaptive changes in its prey preferences, they do not. Rather, feeding-rate stability is an inherently statistical consequence of the predator's high among-prey variation in handling times which determine the length of time that feeding events will remain detectable to observers performing diet surveys. Though understudied, similarly high among-prey variation in handling (or digestion) times is evident in many predator species throughout the animal kingdom. The resultant disconnect between a predator's apparent diet and its actual feeding rates suggests that much of the temporal, biogeographic, and seemingly context-dependent variation that is often perceived in community structure, predator diets, and food-web topology may be of less functional consequence than assumed. Qualitative changes in ecological pattern need not represent qualitative changes in ecological process.

Generalized Lotka-Volterra model with hierarchical interactions

In the analysis of complex ecosystems it is common to use random interaction coefficients, which are often assumed to be such that all species are statistically equivalent. In this work we relax this assumption by imposing hierarchical interspecies interactions. These are incorporated into a generalized Lotka-Volterra dynamical system. In a hierarchical community species benefit more, on average, from interactions with species further below them in the hierarchy than from interactions with those above. Using dynamic mean-field theory, we demonstrate that a strong hierarchical structure is stabilizing, but that it reduces the number of species in the surviving community, as well as their abundances. Additionally, we show that increased heterogeneity in the variances of the interaction coefficients across positions in the hierarchy is destabilizing. We also comment on the structure of the surviving community and demonstrate that the abundance and probability of survival of a species are dependent on its position in the hierarchy.

Trait adaptation enhances species coexistence and reduces bistability in an intraguild predation module

Disentangling how species coexist in an intraguild predation (IGP) module is a great step toward understanding biodiversity conservation in complex natural food webs. Trait variation enabling individual species to adjust to ambient conditions may facilitate coexistence. However, it is still unclear how coadaptation of all species within the IGP module, constrained by complex trophic interactions and trade-offs among species-specific traits, interactively affects species coexistence and population dynamics. We developed an adaptive IGP model allowing prey and predator species to mutually adjust their species-specific defensive and offensive strategies to each other. We investigated species persistence, the temporal variation of population dynamics, and the occurrence of bistability in IGP models without and with trait adaptation along a gradient of enrichment represented by carrying capacity of the basal prey for different widths and speeds of trait adaptation within each species. Results showed that trait adaptation within multiple species greatly enhanced the coexistence of all three species in the module. A larger width of trait adaptation facilitated species coexistence independent of the speed of trait adaptation at lower enrichment levels, while a sufficiently large and fast trait adaptation promoted species coexistence at higher enrichment levels. Within the oscillating regime, increasing the speed of trait adaptation reduced the temporal variability of biomasses of all species. Finally, species coadaptation strongly reduced the presence of bistability and promoted the attractor with all three species coexisting. These findings resolve the contradiction between the widespread occurrence of IGP in nature and the theoretical predictions that IGP should only occur under restricted conditions and lead to unstable population dynamics, which broadens the mechanisms presumably underlying the maintenance of IGP modules in nature. Generally, this study demonstrates a decisive role of mutual adaptation among complex trophic interactions, for enhancing interspecific diversity and stabilizing food web dynamics, arising, for example, from intraspecific diversity.

Metabolic responses of predators to prey density

The metabolic cost of foraging is the dark energy of ecological systems. It is much harder to observe and to measure than its beneficial counterpart, prey consumption, yet it is not inconsequential for the dynamics of prey and predator populations. Here I define the metabolic response as the change in energy expenditure of predators in response to changes in prey density. It is analogous and intrinsically linked to the functional response, which is the change in consumption rate with prey density, as they are both shaped by adjustments in foraging activity. These adjustments are adaptive, ubiquitous in nature, and are implicitly assumed by models of predator–prey dynamics that impose consumption saturation in functional responses. By ignoring the associated metabolic responses, these models violate the principle of energy conservation and likely underestimate the strength of predator–prey interactions. Using analytical and numerical approaches, I show that missing this component of interaction has broad consequences for dynamical stability and for the robustness of ecosystems to persistent environmental or anthropogenic stressors. Negative metabolic responses – those resulting from decreases in foraging activity when more prey is available, and arguably the most common – lead to lower local stability of food webs and a faster pace of change in population sizes, including higher excitability, higher frequency of oscillations, and quicker return times to equilibrium when stable. They can also buffer the effects of press perturbations, such as harvesting, on target populations and on their prey through top-down trophic cascades, but are expected to magnify bottom-up cascades, including the effects of nutrient enrichment or the effects of altering lower trophic levels that can be caused by environmental forcing and climate change. These results have implications for any resource management approach that relies on models of food web dynamics, which is the case of many applications of ecosystem-based fisheries management. Finally, besides having their own individual effects, metabolic responses have the potential to greatly alter, or even invert, functional response-stability relationships, and therefore can be critical to an integral understanding of predation and its influence on population dynamics and persistence.

Predator discrimination of prey promotes the predator-mediated coexistence of prey species

The predator discrimination of prey can affect predation intensity and the prey density dependence of predators, which has the potential to alter the coexistence of prey species. We used a predator-prey population dynamics model accounting for the predator's adaptive diet choice and predator discrimination of prey to investigate how the latter influences prey coexistence. The model revealed that (i) prey species that are perceived as belonging to the same species by a predator are attacked in the same manner, and it is more difficult for them to coexist than those that are recognized as different prey species, and (ii) prey species that are not discriminated by a predator-and therefore cannot coexist-may coexist in the presence of an alternative predator that does discriminate between them. These results suggest that prey diversity, which favours the predator discrimination of prey, and the different capabilities of predators to identify prey species both enhance prey coexistence.

Permanence via invasion graphs: incorporating community assembly into modern coexistence theory

To understand the mechanisms underlying species coexistence, ecologists often study invasion growth rates of theoretical and data-driven models. These growth rates correspond to average per-capita growth rates of one species with respect to an ergodic measure supporting other species. In the ecological literature, coexistence often is equated with the invasion growth rates being positive. Intuitively, positive invasion growth rates ensure that species recover from being rare. To provide a mathematically rigorous framework for this approach, we prove theorems that answer two questions: (i) When do the signs of the invasion growth rates determine coexistence? (ii) When signs are sufficient, which invasion growth rates need to be positive? We focus on deterministic models and equate coexistence with permanence, i.e., a global attractor bounded away from extinction. For models satisfying certain technical assumptions, we introduce invasion graphs where vertices correspond to proper subsets of species (communities) supporting an ergodic measure and directed edges correspond to potential transitions between communities due to invasions by missing species. These directed edges are determined by the signs of invasion growth rates. When the invasion graph is acyclic (i.e. there is no sequence of invasions starting and ending at the same community), we show that permanence is determined by the signs of the invasion growth rates. In this case, permanence is characterized by the invasibility of all [Formula: see text] communities, i.e., communities without species i where all other missing species have negative invasion growth rates. To illustrate the applicability of the results, we show that dissipative Lotka-Volterra models generically satisfy our technical assumptions and computing their invasion graphs reduces to solving systems of linear equations. We also apply our results to models of competing species with pulsed resources or sharing a predator that exhibits switching behavior. Open problems for both deterministic and stochastic models are discussed. Our results highlight the importance of using concepts about community assembly to study coexistence.

Solving multispecies population games in continuous space and time

Game theory has emerged as an important tool to understand interacting populations in the last 50 years. Game theory has been applied to study population dynamics with optimal behavior in simple ecosystem models, but existing methods are generally not applicable to complex systems. In order to use game-theory for population dynamics in heterogeneous habitats, habitats are usually split into patches and game-theoretic methods are used to find optimal patch distributions at every instant. However, populations in the real world interact in continuous space, and the assumption of decisions based on perfect information is a large simplification. Here, we develop a method to study population dynamics for interacting populations, distributed optimally in continuous space. A continuous setting allows us to model bounded rationality, and its impact on population dynamics. This is made possible by our numerical advances in solving multiplayer games in continuous space. Our approach hinges on reformulating the instantaneous game, applying an advanced discretization method and modern optimization software to solve it. We apply the method to an idealized case involving the population dynamics and vertical distribution of forage fish preying on copepods. Incorporating continuous space and time, we can model the seasonal variation in the migration, separating the effects of light and population numbers. We arrive at qualitative agreement with empirical findings. Including bounded rationality gives rise to spatial distributions corresponding to reality, while the population dynamics for bounded rationality and complete rationality are equivalent. Our approach is general, and can easily be used for complex ecosystems.

Functional Responses Shape Node and Network Level Properties of a Simplified Boreal Food Web

Ecological communities are fundamentally connected through a network of trophic interactions that are often complex and difficult to model. Substantial variation exists in the nature and magnitude of these interactions across various predators and prey and through time. However, the empirical data needed to characterize these relationships are difficult to obtain in natural systems, even for relatively simple food webs. Consequently, prey-dependent relationships and specifically the hyperbolic form (Holling’s Type II), in which prey consumption increases with prey density but ultimately becomes saturated or limited by the time spent handling prey, are most widely used albeit often without knowledge of their appropriateness. Here, we investigate the sensitivity of a simplified food web model for a natural, boreal system in the Kluane region of the Yukon, Canada to the type of functional response used. Intensive study of this community has permitted best-fit functional response relationships to be determined, which comprise linear (type I), hyperbolic (type II), sigmoidal (type III), prey- and ratio-dependent relationships, and inverse relationships where kill rates of alternate prey are driven by densities of the focal prey. We compare node- and network-level properties for a food web where interaction strengths are estimated using best-fit functional responses to one where interaction strengths are estimated exclusively using prey-dependent hyperbolic functional responses. We show that hyperbolic functional responses alone fail to capture important ecological interactions such as prey switching, surplus killing and caching, and predator interference, that in turn affect estimates of cumulative kill rates, vulnerability of prey, generality of predators, and connectance. Exclusive use of hyperbolic functional responses also affected trends observed in these metrics over time and underestimated annual variation in several metrics, which is important given that interaction strengths are typically estimated over relatively short time periods. Our findings highlight the need for more comprehensive research aimed at characterizing functional response relationships when modeling predator-prey interactions and food web structure and function, as we work toward a mechanistic understanding linking food web structure and community dynamics in natural systems.

Adaptive plasticity in activity modes and food web stability

Natural ecosystems are comprised of diverse species and their interspecific interactions, in contrast to an ecological theory that predicts the instability of large ecological communities. This apparent gap has led ecologists to explore the mechanisms that allow complex communities to stabilize, even via environmental changes. A standard approach to tackling this complexity-stability problem is starting with a description of the ecological network of species and their interaction links, exemplified by a food web. This traditional description is based on the view that each species is in an active state; that is, each species constantly forages and reproduces. However, in nature, species’ activities can virtually stop when hiding, resting, and diapausing or hibernating, resulting in overlooking another situation where they are inactive. Here I theoretically demonstrate that adaptive phenotypic change in active and inactive modes may be the key to understanding food web dynamics. Accurately switching activity modes can greatly stabilize otherwise unstable communities in which coexistence is impossible, further maintaining strong stabilization, even in a large complex community. I hypothesize that adaptive plastic change in activity modes may play a key role in maintaining ecological communities.

20 Years of Global Change on the Limnology and Plankton of a Tropical, High-Altitude Lake

The present long-term (1993–2013) study was aimed at identifying the effects of global change on the environmental characteristics and the plankton community of the tropical, high-altitude Lake Alchichica, Puebla, Mexico. We found no statistically significant increasing trend in air temperature, but an increase from 2002 to 2013, and interannual variability in the meteorological variables. Accordingly, the water temperature rose from 1993 to 2003 and remained similar until 2013. Nonetheless, on a longer-term (1966-2018), longer than the period considered in the present study, air and water temperatures showed an increasing trend in the range considered indicative of climate change. The lake displayed a characteristic warm monomictic thermal pattern but exhibited interannual variability. The planktonic community composition and structure remained similar. The small chlorophytes (e.g., Monoraphidium minutum) dominated the phytoplankton abundance, while the large diatom Cyclotella alchichicana dominated the biomass. The calanoid copepod Leptodiaptomus garciai dominated both the zooplankton abundance and biomass. However, as the temperature increased the large-size phytoplankton (i.e., C. alchichicana) abundance and biomass increased, but the small-size phytoplankton abundance and biomass, as well as the adult copepod abundance and biomass, decreased. The increase in temperature could have favoured the large-size over the small-size phytoplankton. In addition, the temperature increase could have negatively affected the calanoid copepods in two different ways—direct association with the negative effects of higher temperatures on the physiology of the copepods, or indirect association with the negative effects of higher temperatures on the small-size phytoplankton, which diminish the copepods’ food resource.

Riparian buffers maintain aquatic trophic structure in agricultural landscapes

Local and regional habitat conditions associated with agricultural activity can fundamentally alter aquatic ecosystems. Increased nutrient inputs, channelization and reduced riparian habitat both upstream and locally contribute to the degradation of stream ecosystems and their function. Here, we examine stream food webs in watersheds that feed into Lake Erie to determine the effects of agricultural land cover on major food web energy pathways and trophic structure. Given that higher agricultural intensity can increase nutrient runoff and reduce the riparian zone and litter in-fall into streams, we predicted that generalist fish would derive less energy from the terrestrial pathway and become more omnivorous. Consistent with these predictions, we show that both mean terrestrial energy use and trophic position of the resident top consumer, creek chub (Semotilus atromaculatus), decrease with local agricultural intensity but not with watershed-level agriculture intensity. These findings suggest that local riparian buffers can maintain trophic structure even in the face of high whole-watershed agricultural intensity.

Predator interference and complexity-stability in food webs

It is predicted that ecological communities will become unstable with increasing species numbers and subsequent interspecific interactions; however, this is contrary to how natural ecosystems with diverse species respond to changes in species numbers. This contradiction has steered ecologists toward exploring what underlying processes allow complex communities to stabilize even through varying pressures. In this study, a food web model is used to show an overlooked role of interference among multiple predator species in solving this complexity–stability problem. Predator interference in large communities weakens species interactions due to a reduction in consumption rates by prey-sharing species in the presence of predators in response to territorial and aggressive behavior, thereby playing a key stabilizing role in communities. Especially when interspecific interference is strong and a community has diverse species and dense species interactions, stabilization is likely to work and creates a positive complexity–stability relationship within a community. The clear positive effect of complexity on community stability is not reflected by/intraspecific interference, emphasizing the key role of interspecific interference among multiple predator species in maintaining larger systems.