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Summary After a period of heavy emphasis on negative interactions, such as predation and competition, the past two decades have seen an explosion of literature on the role of positive interactions in ecological communities. Such positive interactions can take many forms. One possibility is that amelioration of environmental stress by plants or sessile animals enhances growth, reproduction and survival of others, but many more intricate patterns exist. Importantly such positive interactions may contribute to creating a positive feedback. For instance, biomass can lead to improved environmental conditions causing better growth and therefore leading to more biomass. A positive feedback is a necessary (but not sufficient) condition for the emergence of alternative stable states at the community scale. However, the literature on positive interactions in plant and animal communities rarely addresses this connection. Here, we address this gap, asking the question of when positive interactions may lead to alternative stable states, and hence set the stage for catastrophic transitions at tipping points in ecosystems. We argue that, although there are a number of now classical examples in the literature for which positive interactions are clearly the main actors of positive feedback loops, more empirical and theoretical research scaling up from the individual‐level interactions to the community and the ecosystem scale processes is needed to further understand under which conditions positive interactions can trigger positive feedback loops, and thereby alternative stable states. Lay Summary

Type I interferons (IFN) induce powerful antiviral and innate immune responses via the transcription factor, IFN‐stimulated gene factor (ISGF3). However, in some pathological contexts, type I IFNs are responsible for exacerbating inflammation. Here, we show that a high dose of IFN‐β also activates an inflammatory gene expression program in contrast to IFN‐λ3, a type III IFN, which elicits only the common antiviral gene program. We show that the inflammatory gene program depends on a second, potentiated phase in ISGF3 activation. Iterating between mathematical modeling and experimental analysis, we show that the ISGF3 activation network may engage a positive feedback loop with its subunits IRF9 and STAT2. This network motif mediates stimulus‐specific ISGF3 dynamics that are dependent on ligand, dose, and duration of exposure, and when engaged activates the inflammatory gene expression program. Our results reveal a previously underappreciated dynamical control of the JAK–STAT/IRF signaling network that may produce distinct biological responses and suggest that studies of type I IFN dysregulation, and in turn therapeutic remedies, may focus on feedback regulators within it. Synopsis The dose and duration of type I interferon exposure is interpreted by a signaling module that contains a stimulus‐contingent positive feedback loop to specify ISGF3 activation dynamics. A secondary, potentiated phase of ISGF3 activates a pro‐inflammatory gene expression program. High‐dose IFN‐β activates a pro‐inflammatory gene program in epithelial cells. IFN‐β, but not IFN‐λ3, induces a second, potentiated phase in ISGF3 activity. ISGF3 induces its subunits to form a stimulus‐contingent positive feedback loop. The positive feedback motif is required for the pro‐inflammatory gene program. Graphical Abstract The dose and duration of type I interferon exposure is interpreted by a signaling module that contains a stimulus‐contingent positive feedback loop to specify ISGF3 activation dynamics. A secondary, potentiated phase of ISGF3 activates a pro‐inflammatory gene expression program.

In coastal and estuarine systems, foundation species like seagrasses, mangroves, saltmarshes or corals provide important ecosystem services. Seagrasses are globally declining and their reintroduction has been shown to restore ecosystem functions. However, seagrass restoration is often challenging, given the dynamic and stressful environment that seagrasses often grow in. From our world‐wide meta‐analysis of seagrass restoration trials (1786 trials), we describe general features and best practice for seagrass restoration. We confirm that removal of threats is important prior to replanting. Reduced water quality (mainly eutrophication), and construction activities led to poorer restoration success than, for instance, dredging, local direct impact and natural causes. Proximity to and recovery of donor beds were positively correlated with trial performance. Planting techniques can influence restoration success. The meta‐analysis shows that both trial survival and seagrass population growth rate in trials that survived are positively affected by the number of plants or seeds initially transplanted. This relationship between restoration scale and restoration success was not related to trial characteristics of the initial restoration. The majority of the seagrass restoration trials have been very small, which may explain the low overall trial survival rate (i.e. estimated 37%). Successful regrowth of the foundation seagrass species appears to require crossing a minimum threshold of reintroduced individuals. Our study provides the first global field evidence for the requirement of a critical mass for recovery, which may also hold for other foundation species showing strong positive feedback to a dynamic environment. Synthesis and applications. For effective restoration of seagrass foundation species in its typically dynamic, stressful environment, introduction of large numbers is seen to be beneficial and probably serves two purposes. First, a large‐scale planting increases trial survival – large numbers ensure the spread of risks, which is needed to overcome high natural variability. Secondly, a large‐scale trial increases population growth rate by enhancing self‐sustaining feedback, which is generally found in foundation species in stressful environments such as seagrass beds. Thus, by careful site selection and applying appropriate techniques, spreading of risks and enhancing self‐sustaining feedback in concert increase success of seagrass restoration.

Identified as essential mechanisms promoting alternative stable states, positive feedbacks have been the focus of most former studies on the potential for catastrophic shifts in drylands. Conversely, little is known about how negative feedbacks could counterbalance the effects of positive feedbacks. A decrease in vegetation cover increases the connectivity of bare-soil areas and entails a global loss of runoff-driven resources from the ecosystem but also a local increase in runoff transferred from bare-soil areas to vegetation patches. In turn, these global resource losses and local resource gains decrease and increase vegetation cover, respectively, resulting in a global positive and a local negative feedback loop. We propose that the interplay of these two interconnected ecohydrological feedbacks of opposite sign determines the vulnerability of dryland ecosystems to catastrophic shifts. To test this hypothesis, we developed a spatially explicit model and assessed the effects of varying combinations of feedback strengths on the dynamics, resilience, recovery potential, and spatial structure of the system. Increasing strengths of the local negative feedback relative to the global positive feedback decreased the risk of catastrophic shifts, facilitated recovery from a degraded state, and promoted the formation of banded vegetation patterns. Both feedbacks were most relevant at low vegetation cover due to the nonlinear increase in hydrological connectivity with decreasing vegetation. Our modelling results suggest that catastrophic shifts to degraded states are less likely in drylands with strong source–sink dynamics and/or strong response of vegetation growth to resource redistribution and that feedback manipulation can be useful to enhance dryland restoration.

Many governments and organisations are currently aligning many aspects of their policies and practices to the sustainable development goals (SDGs). Achieving the SDGs should increase social-ecological resilience to shocks like climate change and its impacts. Here, we consider the relationship amongst the three elements—the SDGs, social-ecological resilience and climate change—as a positive feedback loop. We argue that long-term memory encoded in historical, archaeological and related ‘palaeo-data’ is central to understanding each of these elements of the feedback loop, especially when long-term fluctuations are inherent in social-ecological systems and their responses to abrupt change. Yet, there is scant reference to the valuable contribution that can be made by these data from the past in the SDGs or their targets and indicators. The historical and archaeological records emphasise the importance of some key themes running through the SDGs including how diversity, inclusion, learning and innovation can reduce vulnerability to abrupt change, and the role of connectivity. Using paleo-data, we demonstrate how changes in the extent of water-related ecosystems as measured by indicator 6.6.1 may simply be related to natural hydroclimate variability, rather than reflecting actual progress towards Target 6.6. This highlights issues associated with using SDG indicator baselines predicated on short-term and very recent data only. Within the context of the contributions from long-term data to inform the positive feedback loop, we ask whether our current inability to substantively combat anthropogenic climate change threatens achieving both the SDGS and enhanced resilience to climate change itself. We argue that long-term records are central to understanding how and what will improve resilience and enhance our ability to both mitigate and adapt to climate change. However, for uptake of these data to occur, improved understanding of their quality and potential by policymakers and managers is required.

The resilience of forests is compromised by human-induced environmental influences pushing them towards tipping points and resulting in major shifts in ecosystem state that might be difficult to reverse, are difficult to predict and manage, and can have vast ecological, economic and social consequences. The literature on tipping points has grown rapidly, but almost exclusively based on aquatic and aboveground systems. So far little effort has been made to make links to soil systems, where change is not as drastically apparent, timescales may differ and recovery may be slower. Predicting belowground ecosystem state transitions and recovery, and their impacts on aboveground systems, remains a major scientific, practical and policy challenge. Recently observed major changes in aboveground tree condition across European forests are probably causally linked to ectomycorrhizal (EM) fungal changes belowground. Based on recent breakthroughs in data collection and analysis, we apply tipping point theory to forests, including their belowground component, focusing on EM fungi; link environmental thresholds for EM fungi with nutrient imbalances in forest trees; explore the role of phenotypic plasticity in EM fungal adaptation to, and recovery from, environmental change; and propose major positive feedback mechanisms to understand, address and predict forest ecosystem tipping points.

Positive feedback driven by transcriptional regulation has long been considered a key mechanism underlying cell lineage segregation during embryogenesis. Using the developing spinal cord as a paradigm, we found that canonical, transcription‐driven feedback cannot explain robust lineage segregation of motor neuron subtypes marked by two cardinal factors, Hoxa5 and Hoxc8. We propose a feedback mechanism involving elementary microRNA–mRNA reaction circuits that differ from known feedback loop‐like structures. Strikingly, we show that a wide range of biologically plausible post‐transcriptional regulatory parameters are sufficient to generate bistable switches, a hallmark of positive feedback. Through mathematical analysis, we explain intuitively the hidden source of this feedback. Using embryonic stem cell differentiation and mouse genetics, we corroborate that microRNA–mRNA circuits govern tissue boundaries and hysteresis upon motor neuron differentiation with respect to transient morphogen signals. Our findings reveal a previously underappreciated feedback mechanism that may have widespread functions in cell fate decisions and tissue patterning. SYNOPSIS Robust cell fate decision and precise tissue boundary formation are critical for development. This study reports a feedback mechanism involving mRNA‐microRNA interactions during cell lineage segregation in mouse spinal cord development. Robust lineage segregation of mouse Hoxa5 + and Hoxc8 + motor neurons does not require canonical transcriptional feedback loops. Mathematical modeling derives a wide range of biologically plausible parameters that allow bistability to arise from post‐transcriptional networks. An intuitive interpretation of the mathematical analysis reveals a hidden feedback mechanism involving mRNA‐microRNA interactions. In vitro and in vivo experiments validate the critical roles of two microRNAs in lineage segregation and tissue boundary formation. Graphical Abstract Robust cell fate decision and precise tissue boundary formation are critical for development. This study reports a feedback mechanism involving mRNA‐microRNA interactions during cell lineage segregation in mouse spinal cord development.

The Alzheimer’s disease (AD) is a neurodegenerative disease, which is caused by the aggregation of beta-amyloid peptide ( A β ) in the patient’s brain and the disorder of Ca 2 + homeostasis in neurons. Caluwé and Dupont (Theor Biol 331:12–18, 2013) proposed a deterministic AD model to explore the effect of Ca 2 + on AD. They demonstrated the positive feedback loop between A β and Ca 2 + : and the occurrence of bistability. Based on their results, we further discuss the bistable behaviors. We present two periodically feasible drug strategies to alleviate the AD and screen out more effective one. In this paper, we also formulate a stochastic AD model, analyze the existence and uniqueness of global positive solutions and establish sufficient conditions for the existence of ergodic stationary distribution. Furthermore, the confidence ellipses describing the configurational arrangement of stochastic coexistence equilibria are constructed by stochastic sensitivity function technique, and tipping threshold is estimated as well. Noise-induced stochastic switching between two coexistence equilibria is observed in bistability region. Our results provide a new idea to control noise to alleviate AD through physical therapy.

To improve the performance of a whole-cell biosensor for lead detection, we designed six gene circuits by re-configuring the regulatory elements and incorporating positive feedback loops to the circuits. The lead resistance operon pbr encodes six genes with pbrRT on one side of the promoter and pbrABCD on the other side. PbrR, the divergent promoter it regulates, and GFP were used to design the lead biosensors. One has pbrR and gfp on opposite sides of the promoter mimicking the native operon. We re-configured it by placing pbrR and gfp on the same side or under two separate promoters. The one with pbrR and gfp on the same side demonstrated lead sensitivity 10 times higher than the others. Positive feedback loop was introduced to these circuits. The strength of the output signal from the designs with positive feedback loop was 1.5-2 times stronger than those without positive feedback. This study demonstrates the importance of configuration and positive feedback as effective strategies to improve the performance of lead biosensors and they can be extended to the design of other whole-cell biosensors.

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes – self-activation, toggle switch, and double activation loops – are the commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. What happens to the bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings? In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that the most frequent states in coupled networks follow the ‘rules’ within a motif (double activation, toggle switch) and those across the two motifs in terms of how the two motifs have been coupled. Moreover, ‘hybrid’ states can be observed, too, where one of the above-mentioned ‘rules’ can be compromised, leading to a more diverse phenotypic repertoire. Furthermore, adding direct and indirect self-activations to these coupled networks can increase the frequency of multistability. Thus, our observations revealed specific dynamical traits exhibited by various coupled bistable motifs.