Search Results (45)

Mutualistic interactions are crucial to the structure and functioning of ecological communities, playing a vital role in maintaining biodiversity amidst environmental perturbations. In studies of meta-networks, which are groups of local networks connected by dispersal, most research has focused on the effect of dispersal on interaction networks of competition and predation, without much attention given to mutualistic interactions. Consequently, the role of different dispersal rates (between local networks and across species) in stability and network structures is not well understood. We present a competition–mutualism model for meta-networks where mutualistic interactions follow a type II functional response, to investigate stability and species abundance dynamics under varying dispersal scenarios. We specifically assess the impact of mutualism and dispersal heterogeneity, both between local networks and across species, on the structure and stability of meta-networks. We find that mutualistic meta-networks exhibit greater stability, higher total abundance, lower species unevenness, and greater nestedness compared to meta-networks with only competition interactions. Although dispersal heterogeneity across species exerts some influence, dispersal heterogeneity between local networks mainly drives the patterns observed: it reduces total abundance, increases unevenness, and diminishes compositional similarity across the meta-network. These results highlight the pivotal role of both mutualism and spatial dispersal structure in shaping ecological networks. Our work advances understanding of how mutualistic interactions and dispersal dynamics interact to influence biodiversity and stability in complex ecosystems. Full article

Extreme drought events, intensified by climate change, critically threaten aquatic ecosystem stability by restructuring phytoplankton communities. However, the mechanisms underlying drought-driven community assembly remain poorly understood. This study investigated the impacts of extreme drought on phytoplankton community dynamics in the aquatic reserves of Jiujiang City, China, a critical ecotone of the Yangtze River and Poyang Lake. Through multi-temporal sampling (2022–2023) across 12 sites, we integrated taxonomic, functional group, and co-occurrence network analyses with environmental driver assessments. The results revealed that extreme drought significantly reduced phytoplankton species diversity and triggered a functional shift from disturbance-adapted (e.g., MP group) to pollution-tolerant taxa (e.g., W1 group). Deterministic processes dominated community assembly, driven by drought-induced environmental filtering through water temperature, dissolved oxygen, and nutrient fluctuations. Copper emerged as a key stressor, correlating with the abundance of Cryptophyta. Co-occurrence networks, cohesion, and robustness exhibited heightened complexity and stability under extreme drought, emphasizing stress-induced mutualistic interactions. Our findings elucidate how drought reshapes phytoplankton communities via nutrient dynamics and deterministic species interactions, offering critical insights for managing aquatic ecosystems under escalating climatic extremes. Full article

Identifying the relation between biodiversity and mutualistic ecosystem function has been a longstanding concern. In this study, we present an interpretive model to evaluate the impact of each species on mutualistic ecosystem functions. By analyzing network resilience, we derive the average abundance and tipping point of the ecosystem to represent ecosystem functions. Based on the order of species collapse, each species is classified according to the F-core. The model quantitatively evaluates the influence of species on mutualistic ecosystem functions in scenarios where species are removed from ecosystems. We propose a criterion for identifying redundant species: a species is considered redundant if its removal negatively impacts average abundance without affecting the tipping point. To validate the model, we introduce twenty-four mutualistic ecosystems. Our numerical simulations and analytical analyses reveal two distinct patterns: one indicating the presence of redundancy and the other suggesting that each species is essential. Additionally, in mutualistic ecosystems characterized by redundancy, specialist species are more likely to be identified as redundant. Full article

Arbuscular mycorrhizal (AM) fungi play a crucial role in maintaining sustainable agroecosystems by forming mutualistic relationships with plant roots, improving soil health, facilitating nutrient uptake, and enhancing resilience to abiotic stresses. The mutualistic relationship between AM fungi and plants promotes a balanced microbial community and improves soil structure by forming stable soil aggregates. Additionally, AM fungi can lower the adverse effects of high soil phosphorus (P) while also enhancing plant tolerance to drought, salinity, and heavy metal toxicity through osmotic regulation and antioxidant production. Arbuscular mycorrhizal fungi also support beneficial microorganisms, such as potassium (K)-solubilizing microbes and nitrogen (N)-transforming bacteria, which enhance the nutrient dynamics in soil. However, intensive agricultural practices, including heavy tillage and continuous monoculture, disrupt AM fungal networks and reduce microbial diversity, impairing their effectiveness. Adopting conservation practices such as reduced tillage, crop rotation, and organic amendments supports AM fungal growth. Incorporating mycorrhizal crops and utilizing native fungal inoculants can enhance AM fungal colonization and plant growth. These strategies collectively bolster soil health, crop productivity, and resilience, offering a promising solution to the environmental and agricultural challenges posed by intensive farming. By promoting AM fungi growth and colonization, agroecosystems can achieve long-term productivity and increased sustainability. Full article

Background: Bees rely on plants for nutrition and reproduction, making the preservation of natural areas crucial as pollinator reservoirs. Seasonal tropical dry forests are among the richest habitats for bees, but only 27% of their original extent remains in Mexico. In contrast, temperate forests harbor fewer bee species and face high deforestation rates, with 40% of their area converted to other land uses. This study aimed to estimate the α and β diversities of wild bees and compare bee–plant interaction networks between these two vegetation types. Methods: Wild bees and their interactions with plants were monitored for one year in four sites within the Área de Protección de Flora y Fauna Sierra de Quila. Two sites corresponded to seasonal tropical dry forest and two to temperate forest. α and β diversity, connectance, nestedness, web asymmetry, and niche overlap were analyzed. Results: Sierra de Quila harbors high bee diversity, with 155 species in tropical dry forest and 103 in temperate forest. Species turnover between vegetation types was high, although nine species used floral resources in both forests, connecting the interaction networks. Conclusions: Sierra de Quila diverse habitats promote high bee diversity, with niche partitioning and low connectance facilitating coexistence across different vegetation types. Full article

Biologists, philosophers, and mathematicians building upon Robert Rosen’s non-algorithmic theories of life using Relational Biology and Category Theory have continued to develop his theory and modeling approaches. There has been general agreement that the impredicative, self-referential, and complex nature of living systems negates an algorithmic approach. Rosen’s main goal was to answer, “What is Life?”. Many believe he provided the best but minimum answer using a cellular, metabolism–repair or (M, R)-system as a category-theoretic model. It has been challenging, however, to incorporate his theory to develop a fully non-algorithmic methodology that retains the essence of his thinking while creating more operational models of living systems that can be used to explore other facets of life and answer different questions. Living systems do more than the minimum in the real world beyond the confines of definition alone. For example, ecologists ask how living systems inherently mitigate existential risk from climate change and biodiversity loss through their complex self-organization. Loop Analysis, a signed graph technique, is discussed as a hybrid algorithmic/non-algorithmic methodology in Relational Biology. This methodology can be used at the ecosystem level with standard non-algorithmic field data as per McAllister’s description of the algorithmic incompressibility of empirical data of this type. An example is described showing how the North Atlantic Carbon Pump, an important planetary life support system, is situated in the plankton community and functions as a mutualistic ecosystem chimera. It captures carbon from the atmosphere as an extended (M, R)-system and processes it until it is sequestered in the marine sediments. This is an important process to alleviate climate change in magnitude equal to or larger than the sequestration of carbon on land with forests. It is suggested that the ecosystem level should replace the cellular and organismic levels as the main system unit in biology and evolution since all life exists and evolves with full functional potential in ecosystem networks and not laboratory test tubes. The plankton ecosystem is the largest after the total biosphere and consists of evolutionary links and relationships that have existed for eons of time. If there was ever a genuine robust, highly self-organized ecosystem, it would be planktonic. Severing the links in these thermodynamically open networks by focusing on lower levels of the biological hierarchy loses the critical organization of how life exists on this planet. There is no theory to regain this crucial ‘omitted’ ecological relational causality at the cell or organismal levels. At the end of the paper, some future directions are outlined. Full article

Nitrogen (N) deposition from human activities leads to an imbalance in the N and phosphorus (P) ratios of natural ecosystems, which has a series of negative impacts on ecosystems. In this study, we used 16s rRNA sequencing technology to investigate the effect of the N-P supply ratio on the bulk soil (BS) and rhizosphere soil (RS) bacterial community of halophytes in coastal wetlands through manipulated field experiments. The response of soil bacterial communities to changing N and P ratios was influenced by plants. The N:P ratio increased the α-diversity of the RS bacterial community and changed the structure of the BS bacterial community. P addition may increase the threshold, causing decreased α-diversity of the bacterial community. The co-occurrence network of the RS community is more complex, but it is more fragile than that of BS. The co-occurrence network in BS has more modules and fewer network hubs. The increased N:P ratio can increase chemoheterotrophy and denitrification processes in the RS bacterial community, while the N:P ratio can decrease the N-fixing processes and increase the nitration processes. The response of the BS and the RS bacterial community to the N:P ratio differed, as influenced by soil organic carbon (SOC) content in terms of diversity, community composition, mutualistic networks, and functional composition. This study demonstrates that the effect of the N:P ratio on soil bacterial community is different for plant roots and emphasizes the role of plant roots in shaping soil bacterial community during environmental change. Full article

Current methods for studying the effects of climate change on plants and pollinators can be grouped into two main categories. The first category involves using species distribution models (SDMs) to generate habitat suitability maps, followed by applying climate change scenarios to predict the future distribution of plants and pollinators separately. The second category involves constructing interaction matrices between plants and pollinators and then either randomly removing species or selectively removing generalist or specialist species, as a way to estimate how climate change might affect the plant–pollinator network. The primary limitation of the first approach is that it examines plant and pollinator distributions separately, without considering their interactions within the context of a pollination network. The main weakness of the second approach is that it does not accurately predict climate change impacts, as it arbitrarily selects species to remove without knowing which species will truly shift, decline, or increase in distribution due to climate change. Therefore, a new approach is needed to bridge the gap between these two methods while avoiding their specific limitations. In this context, we introduced an innovative approach that first requires the creation of binary climate suitability maps for plants and pollinators, based on SDMs, for both the current and future periods. This step aligns with the first category of methods mentioned earlier. To assess the effects of climate change within a network framework, we consider species co-overlapping in a geographic matrix. For this purpose, we developed a Python program that overlays the binary distribution maps of plants and pollinators, generating interaction matrices. These matrices represent potential plant–pollinator interactions, with a ‘0’ indicating no overlap and a ‘1’ where both species coincide in the same cell. As a result, for each cell within the study area, we can construct interaction matrices for both the present and future periods. This means that for each cell, we can analyze at least two pollination networks based on species co-overlap. By comparing the topology of these matrices over time, we can infer how climate change might affect plant–pollinator interactions at a fine spatial scale. We applied our methodology to Chile as a case study, generating climate suitability maps for 187 plant species and 171 pollinator species, resulting in 2906 pollination networks. We then evaluated how climate change could affect the network topology across Chile on a cell-by-cell basis. Our findings indicated that the primary effect of climate change on pollination networks is likely to manifest more significantly through network extinctions, rather than major changes in network topology. Full article

Reducing nitrogen fertilizer application highlights its role in optimizing soil bacterial communities to achieve sustainable agriculture. However, the specific mechanisms of bacterial community change under these conditions are not yet clear. In this study, we employed long-term field experiments and high-throughput sequencing to analyze how varying levels of nitrogen application influence the soil bacterial community structure and co-occurrence networks. The results show that reducing the nitrogen inputs significantly enhances the diversity and evenness of the soil bacterial communities, possibly due to the diminished dominance of nitrogen-sensitive taxa, which in turn liberates the ecological niches for less competitive species. Furthermore, changes in the complexity and stability of the bacterial co-occurrence networks suggest increased community resilience and a shift toward more mutualistic interactions. These findings underline the potential of reduced nitrogen application to alleviate competitive pressures among bacterial species, thereby promoting a more diverse and stable microbial ecosystem, highlighting the role of competitive release in fostering microbial diversity. This research contributes to our understanding of how nitrogen management can influence soil health and offers insights into sustainable agricultural practices. Full article

The planning for the scale of the urban rail transit network (URTN) is one of the key tasks of URTN planning. The scale should match the urban development (UD). A reasonable scale can improve travel efficiency, increase economic activities, and promote UD, while an unreasonable scale may consume more urban resources, fail to meet urban transportation demands, and even inhibit UD. Currently, the URTN scale is primarily determined by qualitative analyses and static indicators, which leads to the scale does not match UD perfectly. To determine a reasonable scale, a System Dynamics–Lotka–Volterra (SD-LV) model is constructed. The SD model is adopted to simulate the dynamic interaction between the URT and UD. The LV (Lotka–Volterra) model is employed to calculate the scale, in which the mutualism coefficients are proposed to characterize the mutualistic relationships between the URT and UD. The model is validated by using a dataset of the Beijing URTN from 2017 to 2021. The simulation errors of the URTN scale range from −4.3% to 1.32%, which demonstrates the robustness and effectiveness of the proposed model. The study offers quantitative theoretical insights for determining the reasonable scale of the URTN. Full article

The Diannong River, a valuable river and lake resource of the northern Ningxia Yellow River Irrigation Area, plays an instrumental role in regional flood control, drought resistance, climate regulation, and biodiversity conservation. Phytoplankton and zooplankton, as crucial elements of the aquatic ecosystem, have their distribution patterns evaluated and potential influencing factors identified, thereby enhancing the understanding of community distribution patterns. Nested structures and interspecies interaction relationships bear significant implications for community distribution patterns, functions, and stability. The upstream section of the Diannong River in Yinchuan City was chosen as the study object. Water samples were collected in January, April, July, and October 2021, and the community composition of phytoplankton and zooplankton was analyzed using relative abundance, density, and biomass. The distribution matrix temperature and bipartite network methodologies were deployed to investigate their nested pattern and interaction network seasonal characteristics. The findings indicate that the water environment of the Diannong River’s upstream section displays pronounced spatiotemporal heterogeneity, characterized by weak alkalinity and high fluoride content. The plankton community composition and relative abundance showed marked differences among the distinct sampling periods. The temperature of the random distribution matrix shows a significant difference compared to the zero-sum model, revealing a notable nested pattern in plankton in the Diannong River’s upstream section. The bipartite network suggests that the plankton composition was the simplest in January and the most complex in July, with the fiercest species competition observed in January and the lowest levels of species specificity, vulnerability, and generality. Water temperature (WT), dissolved oxygen (DO), total phosphorus (TP), available phosphorus (AP), COD_Cr, F⁻, and Cl⁻ constitute the environmental parameters influencing the overall structure of the phytoplankton community in the Diannong River’s upstream section, whereas zooplankton did not present a significant correlation with water environmental factors. Full article

Legumes represent an important source of food protein for human nutrition and animal feed. Therefore, sustainable production of legume crops is an issue of global importance. It is well-known that legume-rhizobia symbiosis allows an increase in the productivity and resilience of legume crops. The efficiency of this mutualistic association strongly depends on precise regulation of the complex interactions between plant and rhizobia. Their molecular dialogue represents a complex multi-staged process, each step of which is critically important for the overall success of the symbiosis. In particular, understanding the details of the molecular mechanisms behind the nodule formation and functioning might give access to new legume cultivars with improved crop productivity. Therefore, here we provide a comprehensive literature overview on the dynamics of the signaling network underlying the development of the legume-rhizobia symbiosis. Thereby, we pay special attention to the new findings in the field, as well as the principal directions of the current and prospective research. For this, here we comprehensively address the principal signaling events involved in the nodule inception, development, functioning, and senescence. Full article

Diatom–bacteria interactions evolved during more than 200 million years of coexistence in the same environment. In this time frame, they established complex and heterogeneous cohorts and consortia, creating networks of multiple cell-to-cell mutualistic or antagonistic interactions for nutrient exchanges, communication, and defence. The most diffused type of interaction between diatoms and bacteria is based on a win-win relationship in which bacteria benefit from the organic matter and nutrients released by diatoms, while these last rely on bacteria for the supply of nutrients they are not able to produce, such as vitamins and nitrogen. Despite the importance of diatom–bacteria interactions in the evolutionary history of diatoms, especially in structuring the marine food web and controlling algal blooms, the molecular mechanisms underlying them remain poorly studied. This review aims to present a comprehensive report on diatom–bacteria interactions, illustrating the different interplays described until now and the chemical cues involved in the communication and exchange between the two groups of organisms. We also discuss the potential biotechnological applications of molecules and processes involved in those fascinating marine microbial networks and provide information on novel approaches to unveiling the molecular mechanisms underlying diatom–bacteria interactions. Full article

Plants, the cornerstone of life on Earth, are constantly struggling with a number of challenges arising from both biotic and abiotic stressors. To overcome these adverse factors, plants have evolved complex defense mechanisms involving both a number of cell signaling pathways and a complex network of interactions with microorganisms. Among these interactions, the relationship between symbiotic arbuscular mycorrhizal fungi (AMF) and strigolactones (SLs) stands as an important interplay that has a significant impact on increased resistance to environmental stresses and improved nutrient uptake and the subsequent enhanced plant growth. AMF establishes mutualistic partnerships with plants by colonizing root systems, and offers a range of benefits, such as increased nutrient absorption, improved water uptake and increased resistance to both biotic and abiotic stresses. SLs play a fundamental role in shaping root architecture, promoting the growth of lateral roots and regulating plant defense responses. AMF can promote the production and release of SLs by plants, which in turn promote symbiotic interactions due to their role as signaling molecules with the ability to attract beneficial microbes. The complete knowledge of this synergy has the potential to develop applications to optimize agricultural practices, improve nutrient use efficiency and ultimately increase crop yields. This review explores the roles played by AMF and SLs in plant development and stress tolerance, highlighting their individual contributions and the synergistic nature of their interaction. Full article

Global food systems are a central issue for personal and planetary health in the Anthropocene. One aspect of major concern is the dramatic global spread of ultra-processed convenience foods in the last 75 years, which is linked with the rising human burden of disease and growing sustainability and environmental health challenges. However, there are also calls to radically transform global food systems, from animal to plant-derived protein sources, which may have unintended consequences. Commercial entities have moved toward this “great plant transition” with vigor. Whether motivated by profit or genuine environmental concern, this effort has facilitated the emergence of novel ultra-processed “plant-based” commercial products devoid of nutrients and fiber, and sometimes inclusive of high sugar, industrial fats, and synthetic additives. These and other ingredients combined into “plant-based” foods are often assumed to be healthy and lower in calorie content. However, the available evidence indicates that many of these products can potentially compromise health at all scales—of people, places, and planet. In this viewpoint, we summarize and reflect on the evidence and discussions presented at the Nova Network planetary health meeting on the “Future of Food”, which had a particular focus on the encroachment of ultra-processed foods into the global food supply, including the plant-sourced animal protein alternatives (and the collective of ingredients therein) that are finding their way into global fast-food chains. We contend that while there has been much uncritical media attention given to the environmental impact of protein and macronutrient sources—meat vs. novel soy/pea protein burgers, etc.—the impact of the heavy industrial processing on both human and environmental health is significant but often overlooked, including effects on cognition and mental health. This calls for a more nuanced discourse that considers these complexities and refocuses priorities and value systems towards mutualistic solutions, with co-benefits for individuals, local communities, and global ecology. Full article