Weighting and indirect effects identify keystone species in food webs

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.

Quantifying stability and resilience of eco-social keystone species complexes for coastal marine ecosystems of the Caribbean Sea and eastern Pacific: applications in conservation and monitoring programmes

The local stability and resilience of 13 eco-social keystone species complexes (eco-social KSCs)-considered as conservation and monitoring units-were quantified in coastal marine ecosystems located in the Caribbean and eastern Pacific. Based on Routh-Hurwitz's criterion and Levins' criteria, the eco-social KSCs corresponding to Islas Marietas National Park (Mexico) emerged as the most locally stable and resilient ecosystem. To the contrary, the eco-social KSCs determined for Guala Guala Bay (Chile) and Xcalak Reef National Park (Caribbean) were the least stable and resilient, respectively. In terms of sensitivity, the eco-social KSCs corresponding to El Cobre Bay (Chile) presented the greatest number of sensitive components. The ecological section of the KSCs is formed by a tri-trophic network, dominating self-negative feedbacks. In the case of the socio-economic section, the fisher could exhibit the three types of self-feedbacks, and instead, the demand should be controlled. The identification of eco-social KSCs and the quantification of their stabilities and resiliences allow us to approach ecosystem-based fisheries management under a climate change context. Therefore, we suggest assessing and monitoring the persistence of the eco-social KSCs herein analysed over time, as a way to conserve the fundamental network structure of these ecosystems intervened by fishing.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'.

Identification of keystone taxa in rhizosphere microbial communities using different methods and their effects on compounds of the host Cinnamomum migao

Exploring keystone taxa affecting microbial community stability and host function is crucial for understanding ecosystem functions. However, identifying keystone taxa from humongous microbial communities remains challenging. We collected 344 rhizosphere and bulk soil samples from the endangered plant C. migao for 2 years consecutively. Used high-throughput sequencing 16S rDNA and ITS to obtain the composition of bacterial and fungal communities. We explored keystone taxa and the applicability and limitations of five methods (SPEC-OCCU, Zi-Pi, Subnetwork, Betweenness, and Module), as well as the impact of microbial community domain, time series, and rhizosphere boundary on the identification of keystone taxa in the communities. Our results showed that the five methods, identified abundant keystone taxa in rhizosphere and bulk soil microbial communities. However, the keystone taxa shared by the rhizosphere and bulk soil microbial communities over time decreased rapidly decrease in the five methods. Among five methods on the identification of keystone taxa in the rhizosphere community, Module identified 113 taxa, SPEC-OCCU identified 17 taxa, Betweenness identified 3 taxa, Subnetwork identified 3 taxa, and Zi-Pi identified 4 taxa. The keystone taxa are mainly conditionally rare taxa, and their ecological functions include chemoheterotrophy, aerobic chemoheterotrophy, nitrate reduction, and anaerobic photoautotrophy. The results of the random forest model and structural equation model predict that keystone taxa Mortierella and Ellin6513 may have an effects on the accumulation of 1, 4, 7, - Cycloundecatriene, 1, 5, 9, 9-tetramethyl-, Z, Z, Z-, beta-copaene, bicyclogermacrene, 1,8-Cineole in C. migao fruits, but their effects still need further evidence. Our study evidence an unstable microbial community in the bulk soil, and the definition of microbial boundary and ecologically functional affected the identification of keystone taxa in the community. Subnetwork and Module are more in line with the definition of keystone taxa in microbial ecosystems in terms of maintaining community stability and hosting function.

Establishing riverine nutrient criteria using individual taxa thresholds

Nutrient enrichment is one of the most pervasive impacts on aquatic ecosystems globally. Approaches to establish nutrient criteria that safeguard aquatic ecosystem health are highly variable and, in many instances, criteria are derived from correlations between in-situ nutrient concentrations and biological indices. Summarising entire assemblages with a single index can result in a substantial loss of information and potentially weaker relationships. In this study, we compared the derivation of nutrient criteria using biological indices and those from individual taxa for rivers and streams in New Zealand. Random forest models, including nutrient concentrations, were built to predict two biological indices and individual taxa across New Zealand's river monitoring network. For all acceptable models, the response of the biological indices and individual taxa to increasing Dissolved Inorganic Nitrogen (DIN) and Dissolved Reactive Phosphorus (DRP) were then predicted for every river reach across the nation, and nutrient concentrations that protected 80% of taxa were then identified. Models for the biological indices were poor but were good for most of the taxa, with nutrient concentrations almost always being the most influential factor. To ensure persistence of at least 80% of the taxa within a river reach, we estimated that DIN (Dissolved Inorganic Nitrogen) concentrations would need to be below 0.57-1.32 mg/L, and DRP (Dissolved Reactive Phosphorus) concentrations below 0.019-0.033 mg/L, depending on the river type. In general, high order, low slope rivers and streams required more stringent nutrient criteria than steep, low order streams. The link between nutrient concentrations and biological indices were weak and likely suffer from the loss of information from summarising an entire assemblage into a single numeric. We consider that the derivation of nutrient criteria for waterways should also examine the individual relationships with the taxa in a river system to establish protection for a desired proportion of taxa.

Efficient keystone species identification strategy based on tabu search

As species extinction accelerates globally and biodiversity declines dramatically, identifying keystone species becomes an effective way to conserve biodiversity. In traditional approaches, it is considered that the extinction of species with high centrality poses the greatest threat to secondary extinction. However, the indirect effect, which is equally important as the local and direct effects, is not included. Here, we propose an optimized disintegration strategy model for quantitative food webs and introduced tabu search, a metaheuristic optimization algorithm, to identify keystone species. Topological simulations are used to record secondary extinctions during species removal and secondary extinction areas, as well as to evaluate food web robustness. The effectiveness of the proposed strategy is also validated by comparing it with traditional methods. Results of our experiments demonstrate that our strategy can optimize the effect of food web disintegration and identify the species whose extinction is most destructive to the food web through global search. The algorithm provides an innovative and efficient way for further development of keystone species identification in the ecosystem.

How predictable are mass extinction events?

Many modern extinction drivers are shared with past mass extinction events, such as rapid climate warming, habitat loss, pollution and invasive species. This commonality presents a key question: can the extinction risk of species during past mass extinction events inform our predictions for a modern biodiversity crisis? To investigate if it is possible to establish which species were more likely to go extinct during mass extinctions, we applied a functional trait-based model of extinction risk using a machine learning algorithm to datasets of marine fossils for the end-Permian, end-Triassic and end-Cretaceous mass extinctions. Extinction selectivity was inferred across each individual mass extinction event, before testing whether the selectivity patterns obtained could be used to 'predict' the extinction selectivity exhibited during the other mass extinctions. Our analyses show that, despite some similarities in extinction selectivity patterns between ancient crises, the selectivity of mass extinction events is inconsistent, which leads to a poor predictive performance. This lack of predictability is attributed to evolution in marine ecosystems, particularly during the Mesozoic Marine Revolution, associated with shifts in community structure alongside coincident Earth system changes. Our results suggest that past extinctions are unlikely to be informative for predicting extinction risk during a projected mass extinction.

Disentangling the effects of phosphorus loading on food web stability in a large shallow lake

Excessive nutrient loads reduce ecosystem resilience, resulting in fundamental changes in ecosystem structure and function when exceeding a certain threshold. However, quantitative analysis of the processes by which nutrient loading affects ecosystem resilience requires further exploration. Food web stability is at the heart of ecosystem resilience. In this study, we simulated the dynamics of the food web under different phosphorus loads for Lake Baiyangdian using the PCLake model and calculated the food web stability. Our results showed that there was a good correspondence between the food web stability and ecosystem state response to phosphorus loads. This relationship confirmed that food web stability could be regarded as a signal for the state transition in a real lake ecosystem. Moreover, our estimates suggested that food web stability was influenced only by several functional groups and their interaction strength. Diatoms and zooplankton were the key functional groups that affected food web stability. Phosphorus loads alter the distribution of functional group biomass, which in turn affects energy delivery and, ultimately, the stability of the food web. Corresponding to functional groups, the interactions among zooplankton, diatoms and detritus had the greatest impact, and the interaction strength of the three was positively correlated with food web stability. Overall, our study explained that food-web stability was critical to characterize ecosystem resilience response to external disturbances and can be turned into a scientific tool for lake ecosystem management.

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.

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.

Pollution and cardiovascular health: A contemporary review of morbidity and implications for planetary health

Pollution is a leading cause of premature morbidity and mortality and an important risk factor for cardiovascular disease. Convincing data predict increased rates of cardiovascular morbidity and mortality with current and projected pollution burden trends. Multiple classes of pollutants - including criteria air pollutants, secondhand smoke, toxic steel pollutants, and manufactured chemical pollutants - are associated with varied cardiovascular disease risk profiles. To reduce the future risk of cardiovascular disease from anthropogenic pollution, mitigation strategies, both at the individual level and population level, must be thoughtfully and intentionally employed. The literature supporting individual level interventions to protect against cardiovascular disease is growing but lacks large clinical trials. Population level interventions are crucial to larger societal change and rely upon policy and governmental support. While these mitigation strategies can play a major role in maintaining the health of individuals, planetary health - the impact on human health because of anthropogenic perturbation of natural ecosystems - must also be acknowledged. Future research is needed to further delineate the planetary health implications of current and projected pollutant burden as well as the mitigation strategies employed to attenuate future pollutant burden.

Machine learning ecological networks

Deep-learning tools can help to construct historical, modern-day, and future food webs.

Dynamic Responses of Ammonia-Oxidizing Archaea and Bacteria Populations to Organic Material Amendments Affect Soil Nitrification and Nitrogen Use Efficiency

Organic material amendments have been proposed as an effective strategy to promote soil health by enhancing soil fertility and promoting nitrogen (N) cycling and N use efficiency (NUE). Thus, it is important to investigate the extent to which the structure and function of ammonia-oxidizing archaea (AOA) and bacteria (AOB) differentially respond to the organic material amendments in field settings. Here, we conducted a 9-year field experiment to track the responses of AOA and AOB populations to the organic material amendments and measured the potential nitrification activity (PNA), plant productivity, and NUE in the plant rhizosphere interface. Our results revealed that the organic material amendments significantly enhanced the abundance and diversity of AOA and AOB populations. Further, significant differences were observed in the composition and co-occurrence network of AOA and AOB. A higher occurrence of potential competitive interactions between taxa and enumerated potential keystone taxa was observed in the AOA-AOB network. Moreover, we found that AOA was more important than AOB for PNA under the organic material amendments. Structural equation modeling suggested that the diversity of AOA and AOB populations induced by the potential competitive interactions with keystone taxa dynamically accelerated the rate of PNA, and positively affected plant productivity and NUE under the organic material amendments. Collectively, our study offers new insights into the ecology and functioning of ammonia oxidizers and highlights the positive effects of organic material amendments on nitrogen cycling dynamics.

Nematode Predation and Competitive Interactions Affect Microbe-Mediated Phosphorus Dynamics

Nematode predation plays an essential role in determining changes in the rhizosphere microbiome. These changes affect the local nutrient balance and cycling of essential nutrients by selectively structuring interactions across functional taxa in the system. Currently, it is largely unknown to what extent nematode predation induces shifts in the microbiome associated with different rates of soil phosphorous (P) mineralization. Here, we performed an 7-year field experiment to investigate the importance of nematode predation influencing P availability and cycling. These were tracked via the changes in the alkaline phosphomonoesterase (ALP)-producing bacterial community and ALP activity in the rhizosphere of rapeseed. Here, we found that the nematode addition led to high predation pressure and thereby caused shifts in the abundance and composition of the ALP-producing bacterial community. Further analyses based on cooccurrence networks and metabolomics consistently showed that nematode addition induced competitive interactions between potentially keystone ALP-producing bacteria and other members within the community. Structural equation modeling revealed that the outcome of this competition induced by stronger predation pressure of nematodes was significantly associated with higher diversity of ALP-producing bacteria, thereby enhancing ALP activity and P availability. Taken together, our results provide evidence for the importance of predator-prey and competitive interactions in soil biology and their direct influences on nutrient cycling dynamics.

Reinterpreting the relationship between number of species and number of links connects community structure and stability

For 50 years, ecologists have examined how the number of interactions (links) scales with the number of species in ecological networks. Here, we show that the way the number of links varies when species are sequentially removed from a community is fully defined by a single parameter identifiable from empirical data. We mathematically demonstrate that this parameter is network-specific and connects local stability and robustness, establishing a formal connection between community structure and two prime stability concepts. Importantly, this connection highlights a local stability-robustness trade-off, which is stronger in mutualistic than in trophic networks. Analysis of 435 empirical networks confirmed these results. We finally show how our network-specific approach relates to the classical across-network approach found in literature. Taken together, our results elucidate one of the intricate relationships between network structure and stability in community networks.

Drastic Effects on the Microbiome of a Young Rower Engaged in High-Endurance Exercise After a Month Usage of a Dietary Fiber Supplement

Food supplements are increasingly used worldwide. However, research on the efficacy of such supplements on athlete's well-being and optimal sports performance is very limited. This study performed in junior academic rowing explores the effects of nutritional supplements to aid to the high energy requirements at periods of intense exercise. Herein, the effects of prebiotic fibers on the intestinal microbiome composition of an 18-year-old athlete exercising at high loads during an 8-month period in a “real-life” setting were examined using next-generation sequencing analysis. Results demonstrated that although the alpha diversity of the subject's microbiome drastically decreased [from 2.11 precompetition to 1.67 (p < 0.05)] upon fiber consumption, the Firmicutes/Bacteroidetes ratio increased significantly [from 3.11 to 4.55, as compared with population average (p < 0.05)]. Underlying these macrolevel microbial alterations were demonstrable shifts from acetate- to butyrate-producing bacteria, although with stable effects on the Veillonella species. To our knowledge, this a unique study that shows pronounced changes in the gut microbiome of the young athlete at the competition season and their favorable compensation by the dietary fiber intake. The data here expand the overall understanding of how the high energy needs in high-intensity sports like academic rowing could be supported by dietary fiber supplement consumption.

Construct social-behavioral association network to study management impact on waterbirds community ecology using digital video recording cameras

Studying social-behavior and species associations in ecological communities is challenging because it is difficult to observe the interactions in the field. Animal behavior is especially difficult to observe when selection of habitat and activities are linked to energy costs of long-distance movement. Migrating communities tend to be resource specific and prefer environments that offer more suitability for coexisting in a shared space and time. Given the recent advances in digital technologies, digital video recording systems are gaining popularity in wildlife research and management. We used digital video recording cameras to study social interactions and species-habitat linkages for wintering waterbirds communities in shared habitats. Examining over 8,640 hr of video footages, we built tetrapartite social-behavioral association network of wintering waterbirds over habitat (n = 5) selection events in sites with distinct management regimes. We analyzed these networks to identify hub species and species role in activity persistence, and to explore the effects of hydrological regime on these network characteristics. Although the differences in network attributes were not significant at treatment level (p = .297) in terms of network composition and keystone species composition, our results indicated that network attributes were significantly different (p = .000, r 2 = .278) at habitat level. There were evidences suggesting that the habitat quality was better at the managed sites, where the formed networks had more species, more network nodes and edges, higher edge density, and stronger intra- and inter-species interactions. In addition, we also calculated the species interaction preference scores (SIPS) and behavioral interaction preference scores (BIPS) of each network. The results showed that species synchronize activities in shared space for temporal niche partitioning in order to avoid or minimize any potential competition for shared space. Our social network analysis (SNA) approach is likely to provide a practical use for ecosystem management and biodiversity conservation.

The influence of nutrient enrichment on riverine food web function and stability

Nutrient enrichment of rivers and lakes has been increasing rapidly over the past few decades, primarily because of agricultural intensification. Although nutrient enrichment is known to drive excessive algal and microbial growth, which can directly and indirectly change the ecological community composition, the resulting changes in food web emergent properties are poorly understood. We used ecological network analysis (ENA) to examine the emergent properties of 12 riverine food webs across a nutrient enrichment gradient in the Manawatu, New Zealand. We also derive Keystone Sensitivity Indices to explore whether nutrients change the trophic importance of species in a way that alters the resilience of the communities to further nutrient enrichment or floods. Nutrient enrichment resulted in communities composed of energy inefficient species with high community (excluding microbes) respiration. Community respiration was several times greater in enriched communities, and this may drive hypoxic conditions even without concomitant changes in microbial respiration. Enriched communities exhibited weaker trophic cascades, which may yield greater robustness to energy flow loss. Interestingly, enriched communities were also more structurally and functionally affected by species sensitive to flow disturbance making these communities more vulnerable to floods.

Bacterial networks mediate pentachlorophenol dechlorination across land-use types with citrate addition

Soil microorganisms play a crucial role in the bioremediation of pentachlorophenol (PCP)-contaminated soils. However, whether and how soil bacterial networks with keystone taxa affect PCP dechlorination is not well understood. The present study investigated the effects of citrate on soil bacterial networks mediating PCP dechlorination by direct and indirect transformation in iron-rich upland and paddy soils. The rates of PCP dechlorination and Fe(II) generation were accelerated by citrate addition, particularly in the paddy soils. Network analysis revealed that the topological properties of bacterial networks were changed by citrate addition; more modules and keystone taxa were significantly correlated with PCP dechlorination and Fe(II) generation in the networks. Random forest modeling indicated that Clostridiales was the most important bacterial order; it was significantly involved in both the direct and indirect pathways of PCP dechlorination. Citrate addition had less influence on the balance between the direct and indirect pathways of PCP dechlorination in the upland soils, whereas it enhanced biological PCP dechlorination more directly and efficiently in the paddy soils. Our results suggested that land-use type and citrate addition play a critical role in controlling the biogeochemical mechanisms of PCP dechlorination.

Spatial trophic cascades in communities connected by dispersal and foraging

Pairwise interactions between species have both direct and indirect consequences that reverberate throughout the whole ecosystem. In particular, interaction effects may propagate in a spatial dimension, to localities connected by organismal movement. Here we study the propagation of interaction effects with a spatially explicit metacommunity model, where local sites are connected by dispersal, foraging, or by both types of movement. We show that indirect pairwise effects are, in most cases, of the same sign as direct effects if localities are connected by dispersing species. However, if foraging is prevalent, this correspondence is broken, and indirect effects between species often have a different sign than direct effects. This highlights the importance of indirect interactions across space and their inherent unpredictability in complex settings with species foraging across local patches. Further, the effect of a species over another in a local patch does not necessarily correspond to its effect at the metacommunity scale; this correspondence is again mediated by the type of movement across localities. Every species, despite their trophic position or spatial range, displays a non-zero net effect over every other species in our model metacommunities. Thus we show that local dynamics and local interactions between species can trigger indirect effects all across the set of connected patches, and these effects have a distinct signature depending on whether the prevalent connection between patches is via dispersal or via foraging. However, the magnitude of this effect between any two species strongly decays with the distance between them. These theoretical results strengthen the importance of considering indirect effects across species at both the community and metacommunity levels, highlight the differences between types of movement across locations, and thus open novel avenues for the study of interaction effects in spatially explicit settings.

Interaction modifications lead to greater robustness than pairwise non-trophic effects in food webs

Considerable emphasis has been placed recently on the importance of incorporating non-trophic effects into our understanding of ecological networks. Interaction modifications are well-established as generating strong non-trophic impacts by modulating the strength of interspecific interactions. For simplicity and comparison with direct interactions within a network context, the consequences of interaction modifications have often been described as direct pairwise interactions. The consequences of this assumption have not been examined in non-equilibrium settings where unexpected consequences of interaction modifications are most likely. To test the distinct dynamic nature of these "higher-order" effects, we directly compare, using dynamic simulations, the robustness to extinctions under perturbation of systems where interaction modifications are either explicitly modelled or represented by corresponding equivalent pairwise non-trophic interactions. Full, multi-species representations of interaction modifications resulted in a greater robustness to extinctions compared to equivalent pairwise effects. Explanations for this increased stability despite apparent greater dynamic complexity can be found in additional routes for dynamic feedbacks. Furthermore, interaction modifications changed the relative vulnerability of species to extinction from those trophically connected close to the perturbed species towards those receiving a large number of modifications. Future empirical and theoretical research into non-trophic effects should distinguish interaction modifications from direct pairwise effects in order to maximize information about the system dynamics. Interaction modifications have the potential to shift expectations of species vulnerability based exclusively on trophic networks.

Competitive interaction with keystone taxa induced negative priming under biochar amendments

BACKGROUND

Biochar amendments have been widely proposed as a conventional and efficient strategy to promote soil organic carbon (SOC) sequestration via negative priming. Unfortunately, the extent and biological mechanisms responsible for biochar-induced negative priming are still not fully understood. Despite traditional explanations focused on the environmental filtering mechanisms of biochar amendments on microbial biomass and community composition underlying the priming effect on SOC dynamics, whether and how a biochar-induced competitive interaction with keystone taxa determines SOC mineralization in natural ecosystems has been minimally explored.

RESULTS

Here, we paid particular attention to the relationships between the diversity and network structure of soil bacterial and fungal communities and SOC mineralization. A 3-year field experiment was conducted comprising five treatments: no fertilization, conventional fertilization, and conventional fertilization with three rates of biochar amendments. Biochar amendments considerably increased soil moisture capacity and pH and subsequently shaped the composition and co-occurrence networks of soil bacterial and fungal communities. Importantly, network analysis revealed that the biochar amendments triggered the competitive interaction with putative keystone taxa in the bacterial and fungal networks. Structural equation modeling suggested that the competitive interaction with keystone taxa promoted bacterial and fungal diversity and consequently reduced carbohydrate catabolism and soil metabolic quotient. Stable isotope probing incubations further provided consistent evidence of competition by keystone taxa with the increases in bacterial and fungal diversity under the biochar amendments.

CONCLUSIONS

We found that biochar-induced competition with keystone taxa stimulated the bacterial and fungal diversity and consequently decreased SOC mineralization. The comprehensive understanding of the unexplored biological mechanisms underlying the biochar-induced negative priming may provide crucial implications for enabling SOC sequestration.

Identifying compartments in ecological networks based on energy channels

It has been confirmed in many food webs that the interactions between species are divided into “compartments,” that is, subgroups of highly interacting taxa with few weak interactions between the subgroups. Many of the current methods for detecting compartments in food webs are borrowed from network theory, which do little to improve our understanding of the mechanisms underpinning them. Therefore, a method based on ecological context is needed. Here, we develop a new method for detecting compartments in food webs based on the reliance of each node on energy derived from basal resources (i.e., producers or decomposers). Additional Monte Carlo simulations were conducted to test the significance of the compartmentalization. Further, we applied a food web dynamics model to test whether the effects of permutation would be retained within a single compartment. The proposed method identified significant compartments in 23 of the 28 empirical food webs that were investigated. We further demonstrated that the effects of node removal were significantly higher within compartments than between compartments. Our methods and results emphasize the importance of energy channels in forming food web structures, which sheds light on the mechanisms of self‐organization within food webs.

Plant survival and keystone pollinator species in stochastic coextinction models: role of intrinsic dependence on animal-pollination

Coextinction models are useful to understand community robustness to species loss and resilience to disturbances. We simulated pollinator extinctions in pollination networks by using a hybrid model that combined a recently developed stochastic coextinction model (SCM) for plant extinctions and a topological model (TCM) for animal extinctions. Our model accounted for variation in interaction strengths and included empirical estimates of plant dependence on pollinators to set seeds. The stochastic nature of such model allowed us determining plant survival to single (and multiple) extinction events, and identifying which pollinators (keystone species) were more likely to trigger secondary extinctions. Consistently across three different pollinator removal sequences, plant robustness was lower than in a pure TCM, and plant survival was more determined by dependence on the mutualism than by interaction strength. As expected, highly connected and dependent plants were the most sensitive to pollinator loss and collapsed faster in extinction cascades. We predict that the relationship between dependence and plant connectivity is crucial to determine network robustness to interaction loss. Finally, we showed that honeybees and several beetles were keystone species in our communities. This information is of great value to foresee consequences of pollinator losses facing current global change and to identify target species for effective conservation.

Phytoplankton Diversity Effects on Community Biomass and Stability along Nutrient Gradients in a Eutrophic Lake

The relationship between biodiversity and ecosystem functioning is a central issue in ecology, but how this relationship is affected by nutrient stress is still unknown. In this study, we analyzed the phytoplankton diversity effects on community biomass and stability along nutrient gradients in an artificial eutrophic lake. Four nutrient gradients, varying from slightly eutrophic to highly eutrophic states, were designed by adjusting the amount of polluted water that flowed into the lake. Mean phytoplankton biomass, species richness, and Shannon diversity index all showed significant differences among the four nutrient gradients. Phytoplankton community biomass was correlated with diversity (both species richness and Shannon diversity index), varying from positive to negative along the nutrient gradients. The influence of phytoplankton species richness on resource use efficiency (RUE) also changed from positive to negative along the nutrient gradients. However, the influence of phytoplankton Shannon diversity on RUE was not significant. Both phytoplankton species richness and Shannon diversity had a negative influence on community turnover (measured as community dissimilarity), i.e., a positive diversity-stability relationship. Furthermore, phytoplankton spatial stability decreased along the nutrient gradients in the lake. With increasing nutrient concentrations, the variability (standard deviation) of phytoplankton community biomass increased more rapidly than the average total biomass. Results in this study will be helpful in understanding the phytoplankton diversity effects on ecosystem functioning and how these effects are influenced by nutrient conditions in aquatic ecosystems.

Viewing the effects of species loss in complex ecological networks

Species loss is becoming a major threat to ecosystems. An urgent task in ecology is to predict the consequence of species loss which requires an extending of our traditional study of the topology of network structure to the population dynamic analyses in complex food webs. Here, via numerical simulations of the model combining structural networks with nonlinear bioenergetic models of population dynamics, we analyzed the secondary effects of species removal on biomass distribution and population stability, as well as the factors influencing these effects. We found that the biomass of target species, the nutrient supply, and the trophic level of target species were the three most significant determiners for the effects of species loss. Species loss had large negative effect on the biomass of the species with small biomass or intermediate trophic levels, especially in infertile environment. The population stability of the species with large biomass or low trophic level is easily to be influenced especially in nutrient-rich environment. Our findings indicate the species which are easily to be affected by species loss in food webs, which may help ecologists to outline a better conservation policy.