Advancing the network theory of mental disorders: A computational model of panic disorder.

The network theory of psychopathology posits that mental disorders are systems of mutually reinforcing symptoms. This framework has proven highly generative but does not specify precisely how any specific mental disorder operates as such a system. Cognitive behavioral theories of mental disorders provide considerable insight into how these systems may operate.

Transformation starts at the periphery of networks where pushback is less.

Complex systems ranging from societies to ecological communities and power grids may be viewed as networks of connected elements. Such systems can go through critical transitions driven by an avalanche of contagious change. Here we ask, where in a complex network such a systemic shift is most likely to start.

A tiny fraction of all species forms most of nature: Rarity as a sticky state.

Using data from a wide range of natural communities including the human microbiome, plants, fish, mushrooms, rodents, beetles, and trees, we show that universally just a few percent of the species account for most of the biomass. This is in line with the classical observation that the vast bulk of biodiversity is very rare. Attempts to find traits allowing the tiny fraction of abundant species to escape rarity have remained unsuccessful.

Toxicokinetic-Toxicodynamic Model to Assess Thermal Stress.

Temperature is a crucial environmental factor affecting the distribution and performance of ectothermic organisms. This study introduces a new temperature damage model to interpret their thermal stress. Inspired by the ecotoxicological damage model in the General Unified Threshold model for Survival (GUTS) framework, the temperature damage model assumes that damage depends on the balance between temperature-dependent accumulation and constant repair.

The vulnerability of aging states: A survival analysis across premodern societies.

How states and great powers rise and fall is an intriguing enigma of human history. Are there any patterns? Do polities become more vulnerable over time as they age? We analyze longevity in hundreds of premodern states using survival analysis to help provide initial insights into these questions. This approach is commonly used to study the risk of death in biological organisms or failure in mechanical systems.

The Potential for Alternative Stable States in Food Webs Depends on Feedback Mechanism and Trait Diversity.

AbstractAlternative stable ecosystem states are possible under the same environmental conditions in models of two or three interacting species and an array of feedback loops. However, multispecies food webs might weaken the feedbacks loops that can create alternative stable states. To test how this potential depends on food web properties, we develop a many-species model where consumer Allee effects emerge from consumer-resource interactions.

Five fundamental ways in which complex food webs may spiral out of control.

Theory suggests that increasingly long, negative feedback loops of many interacting species may destabilize food webs as complexity increases. Less attention has, however, been paid to the specific ways in which these 'delayed negative feedbacks' may affect the response of complex ecosystems to global environmental change. Here, we describe five fundamental ways in which these feedbacks might pave the way for abrupt, large-scale transitions and species losses.

Northern expansion is not compensating for southern declines in North American boreal forests.

Climate change is expected to shift the boreal biome northward through expansion at the northern and contraction at the southern boundary respectively. However, biome-scale evidence of such a shift is rare. Here, we used remotely-sensed tree cover data to quantify temporal changes across the North American boreal biome from 2000 to 2019.

Loss of Earth system resilience during early Eocene transient global warming events.

Superimposed on long-term late Paleocene-early Eocene warming (~59 to 52 million years ago), Earth's climate experienced a series of abrupt perturbations, characterized by massive carbon input into the ocean-atmosphere system and global warming. Here, we examine the three most punctuated events of this period, the Paleocene-Eocene Thermal Maximum and Eocene Thermal Maximum 2 and 3, to probe whether they were initiated by climate-driven carbon cycle tipping points. Specifically, we analyze the dynamics of climate and carbon cycle indicators acquired from marine sediments to detect changes in Earth system resilience and to identify positive feedbacks.

Anticipating the occurrence and type of critical transitions.

Critical transition can occur in many real-world systems. The ability to forecast the occurrence of transition is of major interest in a range of contexts. Various early warning signals (EWSs) have been developed to anticipate the coming critical transition or distinguish types of transition.

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in .

In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic-toxicodynamic (TK-TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General Unified Threshold model for Survival (GUTS).

Species abundance correlations carry limited information about microbial network interactions.

Unraveling the network of interactions in ecological communities is a daunting task. Common methods to infer interspecific interactions from cross-sectional data are based on co-occurrence measures. For instance, interactions in the human microbiome are often inferred from correlations between the abundances of bacterial phylogenetic groups across subjects.

Understanding the critical rate of environmental change for ecosystems, cyanobacteria as an example.

Recently it has been show that in some ecosystems fast rates of change of environmental drivers may trigger a critical transition, whereas change of the same magnitude but at slower rates would not. So far, few studies describe this phenomenon of rate-induced tipping, while it is important to understand this phenomenon in the light of the ongoing rapid environmental change. Here, we demonstrate rate-induced tipping in a simple model of cyanobacteria with realistic parameter settings.

Evaluating the performance of multivariate indicators of resilience loss.

Various complex systems, such as the climate, ecosystems, and physical and mental health can show large shifts in response to small changes in their environment. These 'tipping points' are notoriously hard to predict based on trends. However, in the past 20 years several indicators pointing to a loss of resilience have been developed.

Loss of resilience preceded transformations of pre-Hispanic Pueblo societies.

Climate extremes are thought to have triggered large-scale transformations of various ancient societies, but they rarely seem to be the sole cause. It has been hypothesized that slow internal developments often made societies less resilient over time, setting them up for collapse. Here, we provide quantitative evidence for this idea.

Global inequality remotely sensed.

Economic inequality is notoriously difficult to quantify as reliable data on household incomes are missing for most of the world. Here, we show that a proxy for inequality based on remotely sensed nighttime light data may help fill this gap. Individual households cannot be remotely sensed.

No warning for slow transitions.

A rise in fragility as a system approaches a tipping point may be sometimes estimated using dynamical indicators of resilience (DIORs) that measure the characteristic slowing down of recovery rates before a tipping point. A change in DIORs could be interpreted as an early warning signal for an upcoming critical transition. However, in order to be able to estimate the DIORs, observational records need to be long enough to capture the response rate of the system.

Hysteresis of tropical forests in the 21st century.

Tropical forests modify the conditions they depend on through feedbacks at different spatial scales. These feedbacks shape the hysteresis (history-dependence) of tropical forests, thus controlling their resilience to deforestation and response to climate change. Here, we determine the emergent hysteresis from local-scale tipping points and regional-scale forest-rainfall feedbacks across the tropics under the recent climate and a severe climate-change scenario.

Neutral competition boosts cycles and chaos in simulated food webs.

Similarity of competitors has been proposed to facilitate coexistence of species because it slows down competitive exclusion, thus making it easier for equalizing mechanisms to maintain diverse communities. On the other hand, previous studies suggest that chaotic ecosystems can have a higher biodiversity. Here, we link these two previously unrelated findings, by analysing the dynamics of food web models.

Climbing Escher's stairs: A way to approximate stability landscapes in multidimensional systems.

Stability landscapes are useful for understanding the properties of dynamical systems. These landscapes can be calculated from the system's dynamical equations using the physical concept of scalar potential. Unfortunately, it is well known that for most systems with two or more state variables such potentials do not exist.

Foreseeing the future of mutualistic communities beyond collapse.

Changing conditions may lead to sudden shifts in the state of ecosystems when critical thresholds are passed. Some well-studied drivers of such transitions lead to predictable outcomes such as a turbid lake or a degraded landscape. Many ecosystems are, however, complex systems of many interacting species.

Finding the direction of lowest resilience in multivariate complex systems.

The dynamics of complex systems, such as ecosystems, financial markets and the human brain, emerge from the interactions of numerous components. We often lack the knowledge to build reliable models for the behaviour of such network systems. This makes it difficult to predict potential instabilities.