Unraveling emergent network indeterminacy in complex ecosystems: A random matrix approach.

Indeterminacy of ecological networks-the unpredictability of ecosystem responses to persistent perturbations-is an emergent property of indirect effects a species has on another through interaction chains. Thus, numerous indirect pathways in large, complex ecological communities could make forecasting the long-term outcomes of environmental changes challenging. However, a comprehensive understanding of ecological structures causing indeterminacy has not yet been reached. Here, using random matrix theory (RMT), we provide mathematical criteria determining whether network indeterminacy emerges across various ecological communities. Our analytical and simulation results show that indeterminacy intricately depends on the characteristics of species interaction. Specifically, contrary to conventional wisdom, network indeterminacy is unlikely to emerge in large competitive and mutualistic communities, while it is a common feature in top-down regulated food webs. Furthermore, we found that predictable and unpredictable perturbations can coexist in the same community and that indeterminate responses to environmental changes arise more frequently in networks where predator-prey relationships predominate than competitive and mutualistic ones. These findings highlight the importance of elucidating direct species relationships and analyzing them with an RMT perspective on two fronts: It aids in 1) determining whether the network's responses to environmental changes are ultimately indeterminate and 2) identifying the types of perturbations causing less predictable outcomes in a complex ecosystem. In addition, our framework should apply to the inverse problem of network identification, i.e., determining whether observed responses to sustained perturbations can reconstruct their proximate causalities, potentially impacting other fields such as microbial and medical sciences.

The generality of cryptic dietary niche differences in diverse large-herbivore assemblages.

Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth forms but are agnostic toward food plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing ∼4,000 fecal samples of 30 species from 10 sites in seven countries over 6 y. We detected 893 food plant taxa from 124 families, but just two families-grasses and legumes-accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (nongrass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food plant partitioning is driven by species interactions, and was stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: Grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.

Ecologic, Geoclimatic, and Genomic Factors Modulating Plague Epidemics in Primary Natural Focus, Brazil.

Plague is a deadly zoonosis that still poses a threat in many regions of the world. We combined epidemiologic, host, and vector surveillance data collected during 1961-1980 from the Araripe Plateau focus in northeastern Brazil with ecologic, geoclimatic, and Yersinia pestis genomic information to elucidate how these factors interplay in plague activity. We identified well-delimited plague hotspots showing elevated plague risk in low-altitude areas near the foothills of the plateau's concave sectors. Those locations exhibited distinct precipitation and vegetation coverage patterns compared with the surrounding areas. We noted a seasonal effect on plague activity, and human cases linearly correlated with precipitation and rodent and flea Y. pestis positivity rates. Genomic characterization of Y. pestis strains revealed a foundational strain capable of evolving into distinct genetic variants, each linked to temporally and spatially constrained plague outbreaks. These data could identify risk areas and improve surveillance in other plague foci within the Caatinga biome.

Generalized synchronization in a tritrophic food web metacommunity.

Complete synchronization among the metacommunity is known to elevate the risk of their extinction due to stochasticity and other environmental perturbations. Owing to the inherent heterogeneous nature of the metacommunity, we demonstrate the emergence of generalized synchronization among the patches of dispersally connected tritrophic food web using the framework of an auxiliary system approach and the mutual false nearest neighbor. We find that the critical value of the dispersal rate increases significantly with the size of the metacommunity for both unidirectional and bidirectional dispersals, which in turn corroborates that larger metacommunities are more stable than smaller ones. Further, we find that the critical value of the dispersal for the onset of generalized synchronization is smaller(larger) for bidirectional dispersal than that for unidirectional dispersal for smaller(larger) metacommunities. Most importantly, complete synchronization error remains finite even after the onset of generalized synchronization in a wider range of dispersal rate elucidating that the latter can serve as an early warning signal for the extinction of the metacommunity.

Environmental DNA metabarcoding reveals the influence of environmental heterogeneity on microeukaryotic plankton in the offshore waters of East China Sea.

Microeukaryotic plankton are essential to marine food webs and biogeochemical cycles, with coastal seas playing a critical role in aquatic ecosystems. Understanding the diversity of microeukaryotic plankton, deciphering their community structure and succession patterns, and identifying the key factors influencing these dynamics remain central challenges in coastal ecology. In this study, we examine patterns of biodiversity, community structure, and co-occurrence using environmental DNA (eDNA)-based methods. Our results show a linear correlation between α-diversity and distance from the shore, with nutrient-related factors, especially inorganic nitrogen, being the primary determinants of the spatial distribution of plankton communities. Alternation of coastal habitat have shifted the succession patterns of coastal eukaryotic plankton communities from stochastic to deterministic processes. Additionally, our observations indicate that the topology and structure of eukaryotic plankton symbiotic patterns and networks are significantly influenced by environmental heterogeneity such as nutrients, which increase the vulnerability and decrease the stability of offshore ecological networks. Overall, our study demonstrates that the distribution of microeukaryotic plankton communities is influenced by factors related to environmental heterogeneity.

Ocean acidification alters microeukaryotic and bacterial food web interactions in a eutrophic subtropical mesocosm.

Ocean acidification (OA) is known to influence biological and ecological processes, mainly focusing on its impacts on single species, but little has been documented on how OA may alter plankton community interactions. Here, we conducted a mesocosm experiment with ambient (∼410 ppmv) and high (1000 ppmv) CO2 concentrations in a subtropical eutrophic region of the East China Sea and examined the community dynamics of microeukaryotes, bacterioplankton and microeukaryote-attached bacteria in the enclosed coastal seawater. The OA treatment with elevated CO2 affected taxa as the phytoplankton bloom stages progressed, with a 72.89% decrease in relative abundance of the protist Cercozoa on day 10 and a 322% increase in relative abundance of Stramenopile dominated by diatoms, accompanied by a 29.54% decrease in relative abundance of attached Alphaproteobacteria on day 28. Our study revealed that protozoans with different prey preferences had differing sensitivity to high CO2, and attached bacteria were more significantly affected by high CO2 compared to bacterioplankton. Our findings indicate that high CO2 changed the co-occurrence network complexity and stability of microeukaryotes more than those of bacteria. Furthermore, high CO2 was found to alter the proportions of potential interactions between phytoplankton and their predators, as well as microeukaryotes and their attached bacteria in the networks. The changes in the relative abundances and interactions of microeukaryotes between their predators in response to high CO2 revealed in our study suggest that high CO2 may have profound impacts on marine food webs.

The persistence of bipartite ecological communities with Lotka-Volterra dynamics.

The assembly and persistence of ecological communities can be understood as the result of the interaction and migration of species. Here we study a single community subject to migration from a species pool in which inter-specific interactions are organised according to a bipartite network. Considering the dynamics of species abundances to be governed by generalised Lotka-Volterra equations, we extend work on unipartite networks to we derive exact results for the phase diagram of this model. Focusing on antagonistic interactions, we describe factors that influence the persistence of the two guilds, locate transitions to multiple-attractor and unbounded phases, as well as identifying a region of parameter space in which consumers are essentially absent in the local community.

The non-negligible contribution of foundation species to artificial reef construction revealed by Ecopath models.

The seabed desertification has increasingly highlighted the importance of benthic habitat restoration. Strategically engineered artificial reefs emerges as pivotal in achieving restoration objectives. However, the significant influence of foundation species on biotic components and ecosystem attributes within diverse artificial reefs has been underrecognized. This study collated twenty Ecopath models of artificial reefs and their corresponding natural control ecosystems along the coasts of the Yellow Sea and Bohai Sea, China, categorizing them into five distinct system types predicated on the biomass and productivity of foundational species. Our results suggest that dimensionless indices, rather than actual system values, were posited to facilitate inter-comparative analysis. The comparative analysis revealed differences in biomass distribution, energy utilization, and trophic structure across the five ecosystem types. All the artificial reef systems collectively enhanced the utilization of primary production. Foundation species components formed the cornerstone of system functionality, significantly impacting ecosystem stability through modulation of energy flow dynamics. Distinct impacts were observed from shellfish and macroalgae; the former augmenting the detrital food chain, while the latter bolstering the grazing food chain. Consequently, the model-based integrated analysis enabled a robust comparison among various types of artificial reef ecosystems and confirmed that promoting the colonization of foundation species was a non-negligible factor in the design and deployment of artificial reefs.

The role of phenotypic plasticity in shaping ecological networks.

Plasticity-mediated changes in interaction dynamics and structure may scale up and affect the ecological network in which the plastic species are embedded. Despite their potential relevance for understanding the effects of plasticity on ecological communities, these effects have seldom been analysed. We argue here that, by boosting the magnitude of intra-individual phenotypic variation, plasticity may have three possible direct effects on the interactions that the plastic species maintains with other species in the community: may expand the interaction niche, may cause a shift from one interaction niche to another or may even cause the colonization of a new niche. The combined action of these three factors can scale to the community level and eventually expresses itself as a modification in the topology and functionality of the entire ecological network. We propose that this causal pathway can be more widespread than previously thought and may explain how interaction niches evolve quickly in response to rapid changes in environmental conditions. The implication of this idea is not solely eco-evolutionary but may also help to understand how ecological interactions rewire and evolve in response to global change.

Haptophyte communities along the Kuroshio current reveal their geographical sources and ecological traits.

Haptophytes are one of the most ecologically successful phytoplankton groups in the modern ocean and tend to maintain balanced and stable communities across various environments. However, little is known about the mechanisms that enable community stability and ecological success. To reveal the community characteristics and interactions among haptophytes, we conducted comprehensive observations from the upstream to downstream regions of the Kuroshio Current. Haptophyte abundance and taxonomy were assessed using quantitative polymerase chain reaction and metabarcoding of 18S rRNA sequences, respectively. The haptophyte community structure changed abruptly at sites on the shelf-slope of the East China Sea, indicating the strong influence of shelf waters with high phytoplankton biomass on downstream communities. Correlation network analysis combined with the phylogeny suggested that haptophytes can coexist with their close relatives, possibly owing to their nutritional flexibility, thereby escaping from resource competition. Consistently, some noncalcifying haptophyte genera with high mixotrophic capacities such as Chrysochromulina constituted a major component of the co-occurrence network, whereas coccolithophores such as Emiliania/Gephyrocapsa were rarely observed. Our study findings suggest that noncalcifying haptophytes play crucial roles in community diversity and stability, and in sustaining the food web structure in the Kuroshio ecosystems.

Estimating co-extinction threats in terrestrial ecosystems.

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change-such as predicting which species will breach their thermal limits under different warming scenarios-with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.

The role of the core microorganisms in the microbial interactions in activated sludge.

In order to gain a deeper understanding of the microbial interactions in wastewater treatment plants (WWTPs) in China and clarify the role of the core community in the microbial interactions in activated sludge (AS), this study used a molecular ecological network approach based on random matrix theory to construct co-occurrence networks of the core microorganisms (CoreN), the whole AS community (WholeN) and the microbial communities without the core microorganisms (OtherN), respectively. It was shown that the WholeN had more complex and tighter connections compared with the OtherN, because of its higher total number of nodes, higher average clustering coefficient, and shorter average geodesic distance. The proportions of positive links in the CoreN, WholeN and OtherN were gradually decreased, indicating that the core microorganisms promoted cooperation between AS microorganisms. Moreover, higher robustness after random removal of 50% of the nodes of the WholeN (0.2836 ± 0.0311) was observed than the robustness of the OtherN (0.1152 ± 0.0263). In addition, the vulnerability of OtherN (0.0514) is significantly higher than WholeN (0.0225). Meanwhile, the average ratio of negative/positive cohesion, was significantly decreased when the core microorganisms were removed. These results demonstrated that core community could strengthen the stability of the ecological network in AS. By discerning the key factors affecting ecological network, AS temperature was observed to have a strong correlation with all three networks. Moreover, pollutants in wastewater shown stronger correlations with the CoreN and WholeN, supporting the point that core community play a critical role in pollutant removal in WWTPs to a certain extent.

Inoculation with thermophiles enhanced the food waste bio-drying and complicated interdomain ecological networks between bacterial and fungal communities.

Bio-drying is a practical approach for treating food waste (FW). However, microbial ecological processes during treatment are essential for improving the dry efficiency, and have not been stressed enough. This study analyzed the microbial community succession and two critical periods of interdomain ecological networks (IDENs) during FW bio-drying inoculated with thermophiles (TB), to determine how TB affects FW bio-drying efficiency. The results showed that TB could rapidly colonize in the FW bio-drying, with the highest relative abundance of 5.13%. Inoculating TB increased the maximum temperature, temperature integrated index and moisture removal rate of FW bio-drying (55.7 °C, 219.5 °C, and 86.11% vs. 52.1 °C, 159.1 °C, and 56.02%), thereby accelerating the FW bio-drying efficiency by altering the succession of microbial communities. The structural equation model and IDEN analysis demonstrated that TB inoculation complicated the IDENs between bacterial and fungal communities by significantly and positively affecting bacterial communities (b = 0.39, p < 0.001) and fungal communities (b = 0.32, p < 0.01), thereby enhancing interdomain interactions between bacteria and fungi. Additionally, inoculation TB significantly increased the relative abundance of keystone taxa, including Clostridium sensu stricto, Ochrobactrum, Phenylobacterium, Microvirga and Candida. In conclusion, the inoculation of TB could effectively improve FW bio-drying, which is a promising technology for rapidly reducing FW with high moisture content and recovering resources from it.

Natural restoration exhibits better soil bacterial network complexity and stability than artificial restoration on the Loess Plateau, China.

Natural restoration (NR, e.g., secondary succession) and artificial restoration (AR, e.g., afforestation) are key approaches for rehabilitating degraded land; however, a comparative assessment of microbial network between these approaches is lacking. We compared bacterial networks under NR and AR in two different watersheds on the Loess Plateau. Our findings revealed significantly heightened network complexity under NR compared to AR, including metrics such as node, edge, modularity, degree, centrality, and keystone nodes. NR's network robustness exceeded AR by 19.45-35.9% and 7.79-17.74% in the two watersheds, aligning with the ecological principle that complexity begets stability. The significantly higher negative/positive cohesion and natural connectivity under NR also support its better network stability than AR. Integrated analysis of paired sequencing data from five Loess Plateau studies conducted on the Loess Plateau further confirmed the higher complexity and stability of bacterial networks under NR. Further analysis unveiled "biological interactions" as primary drivers of bacterial co-occurrence (on average 84.21% of links), surpassing the influence of environmental filtering (5.17%) or dispersal limitation (4.2%). Importantly, networked communities under NR exhibited generally stronger linkages with various ecosystem function than AR. Overall, our study provides insights into vegetation restoration strategies from the perspective of microbial network, underscoring natural regeneration's potential as a superior remedy for degraded-land restoration.

Identifying and optimizing ecological spatial patterns based on the bird distribution in the Yellow River Basin, China.

In the Yellow River Basin (YRB), there exists a rich biodiversity of species that has been shaped by its unique geography, climate, and human activities. However, the high speed of economic development has resulted in the fragmentation and loss of habitats that are crucial for the survival of these species. To address this problem, constructing ecological networks has emerged as a promising approach for biodiversity preservation. In the study, we centered on the YRB and employed bird communities as an indicator species to identify ecological sources by combining bioclimatic variables and land use data with the Maximum Entropy (MaxEnt) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models. We generated a resistance surface using various data such as Digital Elevation Model (DEM), the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), nighttime light, road density, railway density, and waterway density. So, we then simulated ecological corridors applying the Minimum Cumulative Resistance (MCR) model and constructed a bird diversity protection network. The results we found suggested that bird hotspots were predominantly clustered upstream and downstream in the YRB. We identified 475 sources covering a total area of 65,088 km2, 681 corridors with a total length of 11,495.05 km. This network served as a critical ecological facility to sustain and protect biodiversity. The bird ecological corridors in the YRB showed that a dense east-west pattern in the central area, with a short length in the west and east and a long length in the central area. Although the central region lacked ecological sources, the east and west were still connected as a tight whole. Two scenarios showed adding ecological stepping stones had a better optimization effect than enhancing ecological connectivity.

A multilevel social-ecological network approach for reconciling coastal saltmarsh conservation and development.

In a large-scale region, governance for connectivity in an ecological system often conflicts with management boundaries, causing inefficiencies. Collaboration among management organizations in different areas can help overcome this problem. However, few studies quantified the collaborations' practical relationship with connectivity, considering that some potentially connected paths are easy to neglect by managers. In this paper, collaborations among government agencies in project application process were analyzed, and a multilevel social-ecological network analysis (SENA) approach was developed to identify the collaboration's effect on genetically connected coastal areas. The network framework and methods were shown in a case of coastal saltmarsh conservation and development in the Yellow River Delta, China. Collaboration patterns in conservation and development networks were analyzed and compared among local, subregional, and regional government agencies working in genetically connected coastal areas. Project information flow, reflecting communication frequency and decision-making chances among government agencies was quantified and correlated with ecological connectivity to inform governance effects. Results showed areas with the potential to realize social-ecological alignment, where collaborative networks were measured by network density (percentage of connected network edges). The current reveals that development has more significant potential than conservation at most levels to overcome the misalignment of the social-ecological system, also known as scale mismatch. Empirical evidence also showed a correlation between communication capacity in development networks and improved ecological conditions. The multilevel SENA advanced in this paper can be used for natural resource management when connectivity plays a major role.

Interconnected versus unconnected microorganisms: Does it matter in anaerobic digestion functioning.

Microorganisms in anaerobic digestion (AD) are essential for wastes/pollutants treatment and energy recovery. Due to microbial enormous diversity, developing effective perspectives to understand microbial roles therein is urgent. This study conducted AD of swine manure, used an ensemble-based network analysis to distinguish interconnected, unconnected, copresence (positively interconnected) and mutual-exclusion (negatively interconnected) microorganisms within microbial communities, and explored their importance towards AD performances, using amplicon sequencing of 16S rRNA and 16S rRNA gene. Our analyses revealed greater importance of interconnected than unconnected microorganisms towards CH4 production and AD multifunctionality, which was attributed to higher niche breadth, deterministic community assembly, community stability and phylogenetic conservatism. The diversity was higher in unconnected than interconnected microorganisms, but was not linked to AD performances. Compared to copresence microorganisms, mutual-exclusion microorganisms showed greater and equal importance towards CH4 production and AD multifunctionality, which was attributed to their roles in stabilizing microbial communities. The increased feedstock biodegradability, by replacing part of manure with fructose or apple waste, hardly affected the relative importance of interconnected versus unconnected microorganisms towards CH4 production or AD multifunctionality. Our findings develop a new framework to understand microbial roles, and have important implications in targeted manipulation of critical microorganisms in waste-treatment systems.

Cross-media transfer of nitrogen pollution in the fast-urbanized Greater Bay Area of China: Trends and essential control paths.

For urban agglomerations in the bay area, which concentrate multiple environmental elements and intense anthropogenic activities, comprehensive control of nitrogen pollution is particularly challenging due to diverse cross-media migration and transformation forms of nitrogen pollutants. Existing studies on urban nitrogen metabolism mainly focused on quantification of nitrogen flux, without systematic consideration of physiochemical changes of nitrogen between environmental media. This study conducted a dynamic simulation of nitrogen cross-media metabolism in urban agglomeration over 30 consecutive years, and recognized the types, quantities, and trends of cross-media transfer of nitrogen pollution as well as pollution control paths based on ecological network analysis and scenario analysis. Taking the Guangdong-Hong Kong-Macao Greater Bay Area as the case, results show that during its fast-urbanized stage in 1989-2018, more than 25% of the total nitrogen pollution emissions were transferred from other media. The higher degree of imbalance between the socioeconomic system and the soil in the nitrogen metabolic network emphasizes the increased pressure and necessity of pollution control of nitrogen in the solid state with urban development. Promoting fertilizer reduction and sludge land use are priority paths for collaborative control of cross-media nitrogen pollution. The study provides methods to systematically analyze the features of cross-media transfer of nitrogen pollution at the city level, and accordingly propose paths aiming at sustainable urban nitrogen management with multi-media integrity and synergy.

Untangling microbiota diversity and assembly patterns in the world's longest underground culvert water diversion canal.

The long-distance underground box culvert water transport system (LUBWT) is a crucial link between the source of drinking water and the consumers. It must ensure the stability of water quality during transportation. However, uncontrollable microbial growth can develop in the water delivery system during the long delivery process, posing a risk to health and safety. Therefore, we applied 16 s and 18 s gene sequence analysis in order to study microbial communities in box culvert waters sampled in 2021, as well as a molecular ecological network-based approach to decipher microbial interactions and stability. Our findings revealed that, in contrast to natural freshwater ecosystems, micro-eukaryotes in LUBWT have complex interactions such as predation, parasitism, and symbiosis due to their semi-enclosed box culvert environment. Total nitrogen may be the primary factor affecting bacterial community interactions in addition to temperature. Moreover, employing stability indicators such as robustness and vulnerability, we also found that microbial stability varied significantly from season to season, with summer having the higher stability of microbial communities. Not only that but also the stability of the micronuclei also varied greatly during water transport, which might also be related to the complex interactions among the micro-eukaryotes. To summarize, our study reveals the microbial interactions and stability in LUBWT, providing essential ecological knowledge to ensure the safety of LUBWT's water quality.

Molecular ecological networks reveal the spatial-temporal variation of microbial communities in drinking water distribution systems.

Microbial activity and regrowth in drinking water distribution systems is a major concern for water service companies. However, previous studies have focused on the microbial composition and diversity of the drinking water distribution systems (DWDSs), with little discussion on microbial molecular ecological networks (MENs) in different water supply networks. MEN analysis explores the potential microbial interaction and the impact of environmental stress, to explain the characteristics of microbial community structures. In this study, the random matrix theory-based network analysis was employed to investigate the impact of seasonal variation including water source switching on the networks of three DWDSs that used different disinfection methods. The results showed that microbial interaction varied slightly with the seasons but was significantly influenced by different DWDSs. Proteobacteria, identified as key species, play an important role in the network. Combined UV-chlorine disinfection can effectively reduce the size and complexity of the network compared to chlorine disinfection alone, ignoring seasonal variations, which may affect microbial activity or control microbial regrowth in DWDSs. This study provides new insights for analyzing the dynamics of microbial interactions in DWDSs.