Diversity begets stability: Sublinear growth and competitive coexistence across ecosystems

Geography and availability of natural habitat determine whether cropland intensification or expansion is more detrimental to biodiversity

To mitigate biodiversity loss from agriculture, intensification is often promoted as an alternative to farmland expansion. However, its local impacts remain debated. We assess globally the responses of three biodiversity metrics-species richness, total abundance and relative community abundance-weighted average range size (RCAR), a proxy for biotic homogenization-to land conversion and yield increases. Our models predict a median species loss of 11% in primary vegetation in modified landscapes, and of 25% and 40% in cropland within natural and modified landscapes, respectively. Land conversion also reduces abundance and increases biotic homogenization, with impacts varying by geographic region and history of human modification. However, increasing yields changes biodiversity as well, including in adjacent primary vegetation, with effects dependent on crop, region, biodiversity metric and natural habitat cover. Ultimately, neither expansion nor intensification consistently benefits biodiversity. Intensification has better species richness outcomes in 29%, 83%, 64% and 57% of maize, soybean, wheat and rice landscapes, respectively, whereas expansion performs better in the remaining areas. In terms of abundance and RCAR, both expansion and intensification can outperform the other depending on landscape. Therefore, minimizing local biodiversity loss requires a context-dependent balance between expansion and intensification, while avoiding expansion in unmodified landscapes.

Lactobacillus murinus ZNL-13 Modulates Intestinal Barrier Damage and Gut Microbiota in Cyclophosphamide-Induced Immunosuppressed Mice

Cyclophosphamide (CTX) is a widely used anticancer drug in clinical practice; however, its administration can lead to gastrointestinal damage and immune suppression. Lactobacillus murinus (L. murinus) has been shown to regulate immune cell activity and protect the gastrointestinal system, showing potential application as a functional food. The objective of this study was to investigate the effects of L. murinus ZNL-13 on CTX-induced intestinal mucosal injury and gut microbiota in mice. The results demonstrated that L. murinus ZNL-13 significantly alleviated weight loss and intestinal pathological damage. Moreover, in CTX-induced intestinal injury mice, L. murinus ZNL-13 enhanced the release of immune factors, suppressed cell apoptosis, and protected the intestinal mucosal barrier. Additionally, it activated the TLR4/NF-κB pathway, thereby promoting immune cell activity. Furthermore, L. murinus ZNL-13 contributed to the restoration of gut microbial homeostasis by increasing the relative abundance of short-chain fatty acid-producing bacteria. Taken together, this investigation highlights the potential of L. murinus ZNL-13 in protecting the intestinal barrier and enhancing immune function while laying the groundwork for its development as a novel probiotic and functional food.

Microbial populations hardly ever grow logistically and never sublinearly

We investigate the growth dynamics of microbial populations, challenging the conventional logistic model. By analyzing empirical data from various biomes, we demonstrate that microbial growth is better described by a generalized logistic model, the θ-logistic model. This accounts for different growth mechanisms and environmental fluctuations, leading to a generalized gamma distribution of abundance fluctuations. Our findings reveal that microbial growth is never sublinear, so they cannot endorse-at least in the microbial world-the recent proposal of this mechanism as a stability enhancer of highly diverse communities. These results have significant implications for understanding macroecological patterns and the stability of microbial ecosystems.

Will a large complex model ecosystem be viable? The essential role of positive interactions

Ecologists have documented many characteristics of natural systems that foster ecosystem persistence, and it might be deduced that such strategies are essential for counteracting the negative effect of complexity on local stability that was suggested by R.M. May in his influential work of the 1970s. However, we show that the loss of local stability does not necessarily imply total ecosystem extinction. A more general criterion of ecosystem viability is the long-term persistence of any number of surviving species-not necessarily all of them. With this approach, we show that persistence increases with complexity, contrary to previous theoretical findings. In particular, positive interactions (mutualistic or prey-to-predator) play a crucial role in creating ecological niches, which sustain biodiversity with increasing complexity.

Climb forest, climb: diverse disperser communities are key to assist plants tracking climate change on altitudinal gradients

Climate change is forcing species to shift their distribution ranges. Animal seed dispersers might be particularly important in assisting plants tracking suitable climates to higher elevations. However, this role is still poorly understood due to a lack of comprehensive multi-guild datasets along elevational gradients. We compiled seed dispersal networks for the five altitudinal vegetation belts of the Tenerife Island (0-3718 m above sea level) to explore how plant and animal species might facilitate the mutual colonisation of uphill habitats under climate change. The overall network comprised 283 distinct interactions between 73 plant and 27 animal species, with seed dispersers offering viable pathways for plants to colonise upper vegetation belts. A pivotal role is played by a lizard as island-level hub, while four birds and one introduced mammal (rabbit) are also important connectors between belts. Eleven plant species were empirically found to be actively dispersed to elevations beyond their current known range, with observed vertical dispersal distances largely surpassing those required to escape climate change. Furthermore, over half of the plants arriving at higher elevations were exotic. Functionally diverse disperser communities are crucial for enabling plants tracking climate change on mountains, but exotic plants might particularly benefit from this upward lift.

Behavior of simple closed ecological systems; lower nutrient concentrations allow longer persistence of grazer populations

We expect to develop self-sustaining extraterrestrial colonies, and they will approach being closed ecological systems. Using simple closed ecosystems containing Daphnia magna, three species of algae, and microbes, we tested multiple conditions to study long-term organism survival, which is only possible with adequate nutrient recycling. Closed and open systems behaved differently from one another at high nitrate concentrations; in closed systems, the animals were dead by day 14; in open systems, the Daphnia populations persisted beyond 273 days. Daphnia deaths were associated with increased pH and O2 caused by greater algal photosynthesis and the lack of exchange with the atmosphere. Replicate variability that used small Daphnia suggested that inadequate grazing capability allowed algae to create conditions unfavorable to Daphnia survival. Over months, algal and Daphnia abundance decreased, presumably because of inadequate nutrient recycling; these populations increased temporarily after the addition of nutrients. The addition of natural lake organisms did not increase the nutrient-recycling capabilities of the systems. Understanding the mechanisms of closed systems will be useful in implementing biological processes in managing life support systems.

Uncovering the multi-fencing effects: Changes in plant diversity across dimensions and spatio, and the relationship between diversity and stability

Plant diversity is fundamental to maintaining grassland ecosystem function. Rangeland managers use fencing as a strategy to enhance plant diversity in degraded grasslands. However, the effects of this natural management approach on grasslands across a wide range of environmental gradients and its spatial pattern remain unclear. This study investigated 37 pairs of fencing and grazing sites along an 1800 km transect of alpine grasslands on the Tibetan Plateau to evaluate the effects of fencing on plant species, functional, and phylogenetic alpha and beta diversity. Fencing increased plant functional and species alpha-diversity, as well as phylogenetic and functional beta-diversity by 0.20%-26.18%, but decreased species beta-diversity by 0.70%. The sensitivity of functional diversity to fencing was higher in alpine meadows than in alpine steppes and alpine desert steppes. Fencing resulted in spatial heterogeneity in plant alpha and beta diversity in alpine grasslands. The beta-diversity of plant communities in the three dimensions across all the alpine grasslands was dominated by turnover components. The response of plant diversity to fencing increased with longitude but declined with latitude and elevation. Consequently, the effects of fencing on plant diversity in Tibetan alpine grasslands are associated with grassland types and climatic conditions. Notably, fencing did not consistently yield positive outcomes for plant diversity, indicating it should be applied selectively for biodiversity restoration. Given the nonlinear relationship between diversity and ecosystem stability, it is recommended that restoration of degraded grasslands should consider not only species selection but also a balanced composition of species with varied functional and phylogenetic traits.

Stable Soil Biota Network Enhances Soil Multifunctionality in Agroecosystems

Unraveling how agricultural management practices affect soil biota network complexity and stability and how these changes relate to soil processes and functions is critical for the development of sustainable agriculture. However, our understanding of these knowledge still remains unclear. Here, we explored the effects of soil management intensity on soil biota network complexity, stability, and soil multifunctionality, as well as the relationships among these factors. Four typical land use types representing a gradient of disturbance intensity were selected in calcareous and red soils in southwest China. The four land use types with increasing disturbance intensity included pasture, sugarcane farmland, rice paddy fields, and maize cropland. The network cohesion, the network topological features (e.g., average degree, average clustering coefficient, average path length, network diameter, graph density, and modularity), and the average variation degree were used to evaluate the strength of interactions between species, soil biota network complexity, and the network stability, respectively. The results showed that intensive soil management increased species competition and soil biota network complexity but decreased soil biota network stability. Soil microfauna (e.g., nematode, protozoa, and arthropoda) stabilized the entire soil biota network through top-down control. Soil biota network stability rather than soil biota network complexity or soil biodiversity predicted the dynamics of soil multifunctionality. Specifically, stable soil communities, in both the entire soil biota network and selected soil organism groups (e.g., archaea, bacteria, fungi, arthropoda, nematode, protozoa, viridiplantae, and viruses), support high soil multifunctionality. In particular, soil microfauna stability had more contributions to soil multifunctionality than the stability of soil microbial communities. This result was further supported by network analysis, which showed that modules 1 and 4 had greater numbers of soil microfauna species and explained more variation of soil multifunctionality. Our study highlights that soil biota network stability should be considered a key factor in improving agricultural sustainability and crop productivity in the context of increasing global agricultural intensification.

Calibrated Ecosystem Models Cannot Predict the Consequences of Conservation Management Decisions

Ecosystem models are often used to predict the consequences of management interventions in applied ecology and conservation. These models are often high-dimensional and nonlinear, yet limited data are available to calibrate or validate them. Consequently, their utility as decision-support tools is unclear. In this paper, we calibrate ecosystem models to time series data from 110 different experimental microcosm ecosystems, each containing three to five interacting species. Then, we assess their ability to predict the consequences of management interventions. Our results show that for each time series dataset, multiple divergent parameter sets offer equivalent, good fits. However, these models have poor predictive accuracy when forecasting future dynamics or when predicting how the ecosystem will respond to management intervention. Closer inspection reveals that the models fail because calibration cannot determine the nature of the interspecific interactions. Our findings question whether ecosystem models can support applied ecological decision-making when calibrated against real-world datasets.

Ecosystem stability relies on diversity difference between trophic levels

The stability of ecological communities has a profound impact on humans, ranging from individual health influenced by the microbiome to ecosystem services provided by fisheries. A long-standing goal of ecology is the elucidation of the interplay between biodiversity and ecosystem stability, with some ecologists warning of instability due to loss of species diversity while others arguing that greater diversity will instead lead to instability. Here, by considering a minimal two-level ecosystem with multiple predator and prey species, we show that stability does not depend on absolute diversity but rather on diversity differences between levels. We found that increasing diversity in either level first destabilizes but then stabilizes the community (i.e., a reentrant stability transition). We therefore find that it is the diversity difference between levels that is the key to stability, with the least stable communities having similar diversities in different levels. An analytical stability criterion is derived, demonstrating quantitatively that the critical diversity difference is determined by the correlation between how one level affects another and how it is affected in turn. Our stability criterion also applies to consumer-resource models with other forms of interaction such as cross-feeding. Finally, we show that stability depends on diversity differences in ecosystems with three trophic levels. Our finding of a nonmonotonic dependence of stability on diversity provides a natural explanation for the variety of diversity-stability relationships reported in the literature, and emphasizes the significance of level structure in predicting complex community behaviors.

Biomass competition connects individual and community scaling patterns

Both metabolism and growth scale sublinearly with body mass across species. Ecosystems show the same sublinear scaling between production and total biomass, but ecological theory cannot reconcile the existence of these nearly identical scalings at different levels of biological organization. We attempt to solve this paradox using marine phytoplankton, connecting individual and ecosystem scalings across three orders of magnitude in body size and biomass. We find that competitive interactions determined by biomass slow metabolism in a consistent fashion across species of different sizes. These effects dominate over species-specific peculiarities, explaining why community composition does not affect respiration and production patterns. The sublinear scaling of ecosystem production thus emerges from this metabolic density-dependence that operates across species, independently of the equilibrium state or resource regime. Our findings demonstrate the connection between individual and ecosystem scalings, unifying aspects of physiology and ecology to explain why growth patterns are so strikingly similar across scales.

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

Complexity-stability relationships in competitive disordered dynamical systems

Robert May famously used random matrix theory to predict that large, complex systems cannot admit stable fixed points. However, this general conclusion is not always supported by empirical observation: from cells to biomes, biological systems are large, complex, and often stable. In this paper, we revisit May's argument in light of recent developments in both ecology and random matrix theory. We focus on competitive systems, and, using a nonlinear generalization of the competitive Lotka-Volterra model, we show that there are, in fact, two kinds of complexity-stability relationships in disordered dynamical systems: if self-interactions grow faster with density than cross-interactions, complexity is destabilizing; but if cross-interactions grow faster than self-interactions, complexity is stabilizing.

CSR strategies seasonal cycling: A new mechanism for coexistence among seaweeds

The stable maintenance of high biological diversity remains a major puzzle in biology. We propose a new mechanism involving the cyclical use of Competitive, Stress-tolerant, and Ruderal (CSR) strategies to explain high biodiversity maintenance. This study examines the interactions among three morphs of the cosmopolitan and commercially important seaweed Ulva Linnaeus. We measured biomass productivity, effective quantum yield, carbohydrate concentration, and nutrient competition across all seasons for one year and matched trait value combinations to CSR strategies. Our findings reveal that the Ulva morphs exhibited significant competitive interactions under eutrophic conditions, in a scramble competition dynamic. However, competition did not significantly affect their functional traits under naturally prevalent oligotrophic conditions. Season-by-season analysis revealed that each morph employed temporal niche partitioning by cyclically adopting different CSR strategies, thereby avoiding direct competition. This cyclical strategy, akin to a rock-paper-scissors game, prevents any single strategy from dominating year-round, maintaining the three-morph polymorphism. Our study further highlights the importance of year-long functional trait measurements to encompass seasonal changes in functional responses. Our CSR cycling conceptual model offers new insights useful for monitoring and conservation efforts.

Modeling tumors as complex ecosystems

Many cancers resist therapeutic intervention. This is fundamentally related to intratumor heterogeneity: multiple cell populations, each with different phenotypic signatures, coexist within a tumor and its metastases. Like species in an ecosystem, cancer populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity or predict its consequences. Here, we propose that the generalized Lotka-Volterra model (GLV), a standard tool to describe species-rich ecological communities, provides a suitable framework to model the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties provide a new understanding of the disease. We discuss potential extensions of the model and their application to phenotypic plasticity, cancer-immune interactions, and metastatic growth. Our work outlines a set of questions and a road map for further research in cancer ecology.

Leaf isotopes reveal tree diversity effects on the functional responses to the pan-European 2018 summer drought

Recent droughts have strongly impacted forest ecosystems and are projected to increase in frequency, intensity, and duration in the future together with continued warming. While evidence suggests that tree diversity can regulate drought impacts in natural forests, few studies examine whether mixed tree plantations are more resistant to the impacts of severe droughts. Using natural variations in leaf carbon (C) and nitrogen (N) isotopic ratios, that is δ13C and δ15N, as proxies for drought response, we analyzed the effects of tree species richness on the functional responses of tree plantations to the pan-European 2018 summer drought in seven European tree diversity experiments. We found that leaf δ13C decreased with increasing tree species richness, indicating less drought stress. This effect was not related to drought intensity, nor desiccation tolerance of the tree species. Leaf δ15N increased with drought intensity, indicating a shift toward more open N cycling as water availability diminishes. Additionally, drought intensity was observed to alter the influence of tree species richness on leaf δ15N from weakly negative under low drought intensity to weakly positive under high drought intensity. Overall, our findings suggest that dual leaf isotope analysis helps understand the interaction between drought, nutrients, and species richness.

Untangling the complex food webs of tropical rainforest streams

Food webs depict the tangled web of trophic interactions associated with the functioning of an ecosystem. Understanding the mechanisms providing stability to these food webs is therefore vital for conservation efforts and the management of natural systems. Here, we first characterised a tropical stream meta-food web and five individual food webs using a Bayesian Hierarchical approach unifying three sources of information (gut content analysis, literature compilation and stable isotope data). With data on population-level biomass and individually measured body mass, we applied a bioenergetic model and assessed food web stability using a Lotka-Volterra system of equations. We then assessed the resilience of the system to individual species extinctions using simulations and investigated the network patterns associated with systems with higher stability. The model resulted in a stable meta-food web with 307 links among the 61 components. At the regional scale, 70% of the total energy flow occurred through a set of 10 taxa with large variation in body masses. The remaining 30% of total energy flow relied on 48 different taxa, supporting a significant dependency on a diverse community. The meta-food web was stable against individual species extinctions, with a higher resilience in food webs harbouring omnivorous fish species able to connect multiple food web compartments via weak, non-specialised interactions. Moreover, these fish species contributed largely to the spatial variation among individual food webs, suggesting that these species could operate as mobile predators connecting different streams and stabilising variability at the regional scale. Our results outline two key mechanisms of food web stability operating in tropical streams: (i) the diversity of species and body masses buffering against random and size-dependent disturbances and (ii) high regional diversity and weak omnivorous interactions of predators buffering against local stochastic variation in species composition. These mechanisms rely on high local and regional biodiversity in tropical streams, which is known to be strongly affected by human impacts. Therefore, an urgent challenge is to understand how the ongoing systematic loss of diversity jeopardises the stability of stream food webs in human-impacted landscapes.

Impacts of oxbow lake evolution on sediment microbial community structure in the Yellow River source region

Oxbow lake formation and evolution have significant impacts on the fragile Yellow River Basin ecosystem. However, the effects of different oxbow lake evolutionary stages on sediment microbial community structure are not yet understood comprehensively. Therefore, microbial community structure in three stages of oxbow lake succession, namely, lotic lake (early stage), semi-lotic lake (middle stage), and lentic lake (late stage), was investigated in the present study in the Yellow River Basin on the Qinghai-Tibet Plateau. Amplicon sequencing was employed to reveal differences in microbial community diversity and composition. The bacterial and fungal communities in sediment were significantly different among the three succession stages and were driven by different environmental factors. In particular, bacterial community structure was influenced primarily by nitrate-nitrogen (N), microbial biomass phosphorus, and total carbon (C) and organic C in the early, middle, and late stages, respectively. Conversely, fungal community structure was influenced primarily by ammonium-N in the early stage and by moisture content in the middle and late stages. However, the predicted functions of the microbial communities did not exhibit significant differences across the three succession stages. Both bacteria and fungi were influenced significantly by stochastic factors. Homogeneous selection had a high relative contribution to bacteria community assembly in the middle stage, whereas the relative contributions of heterogeneous selection processes to fungal community assembly increased through the three stages. As succession time increased, the total number of keystone species increased gradually, and the late succession stage had high network complexity and the highest network stability. The findings could facilitate further elucidation of the evolution mechanisms of oxbow lake source area, high-altitude river evolution dynamics, in addition to aiding a deeper understanding of the long-term ecological evolution patterns of source river ecosystems.

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

Effects of biodiversity on functional stability of freshwater wetlands: a systematic review

Freshwater wetlands are the wetland ecosystems surrounded by freshwater, which are at the interface of terrestrial and freshwater ecosystems, and are rich in ecological composition and function. Biodiversity in freshwater wetlands plays a key role in maintaining the stability of their habitat functions. Due to anthropogenic interference and global change, the biodiversity of freshwater wetlands decreases, which in turn destroys the habitat function of freshwater wetlands and leads to serious degradation of wetlands. An in-depth understanding of the effects of biodiversity on the stability of habitat function and its regulation in freshwater wetlands is crucial for wetland conservation. Therefore, this paper reviews the environmental drivers of habitat function stability in freshwater wetlands, explores the effects of plant diversity and microbial diversity on habitat function stability, reveals the impacts and mechanisms of habitat changes on biodiversity, and further proposes an outlook for freshwater wetland research. This paper provides an important reference for freshwater wetland conservation and its habitat function enhancement.