Complexity Thoughts: Issue #12
Unraveling complexity: building knowledge, one paper at a time
In a nutshell…
In this issue we have a paper demonstrating that accounting for multiple information pathways in a complex network allows one to better predict perturbation patterns, with applications from cellular dynamics to epidemic spreading.
Another study addresses the expansion of climate change risks for species globally. It reveals that the area of each species' geographical range at risk of thermal exposure will expand abruptly, primarily due to rapid warming and limited available habitats at the warm end of thermal gradients. The study emphasizes the urgent need for mitigation and adaptation actions to protect vulnerable species.
In the field of ecology, a paper explores the transition from niche to dispersal assembly in local communities. It challenges the classic theory that niches dictate the maximum number of coexisting species, proposing instead that niches dictate the minimum number and that immigration plays a significant role in maintaining species richness. Experimental evidence supports this alternative theory.
Examining epidemic processes and global flows, a study investigates the dispersal patterns of SARS-CoV-2 variants of concern (VOCs). It finds that different VOCs exhibit varying source-sink dynamics, with certain countries acting as global and regional hubs of dissemination. Another paper, indeed, discusses how to enhance global preparedness during an ongoing pandemic using partial and noisy data. By integrating genomic surveillance, global human mobility data, and epidemic modeling, the paper quantifies the pandemic potential of emerging variants.
The evolution of a pathogen is the subject of another study, where the authors explore the impact of antigenic escape on the evolution of pathogen virulence. Non-equilibrium dynamics resulting from antigenic drift and escape select for more acute pathogens with higher virulence. The study sheds light on the timing and outcomes of antigenic shifts and their implications for epidemic behavior, endemic behavior, and control strategies.
We finish with a perspective on the neuroconnectionist research program. Artificial neural networks (ANNs) inspired by biology are seen as a promising computational language for understanding brain computation. Rather than focusing solely on the successes and failures of current ANNs, the program emphasizes its capacity to generate novel insights into brain function and computation, contributing to a deeper understanding of the brain.
Network theory
Multi pathways temporal distance unravels the hidden geometry of network-driven processes
Network-based interactions allow one to model many technological and natural systems, where understanding information flow between nodes is important to predict their functioning. The complex interplay between network connectivity and dynamics can be captured by scaling laws overcoming the paradigm of information spread being solely dependent on network structure. Here, we capitalize on this paradigm to identify the relevant paths for perturbation propagation. We introduce a multi-pathways temporal distance between nodes that overcomes the limitation of focussing only on the shortest path. This metric predicts the latent geometry induced by the dynamics in which the signal propagation resembles the traveling wave solution of reaction-diffusion systems. We validate the framework on a set of synthetic dynamical models, showing that it outperforms existing approaches in predicting arrival times. On a set of empirical contact-based social systems, we show that it can be reliably used also for models of infectious diseases spread - such as the Susceptible-Infected-Susceptible - with remarkable accuracy in predicting the observed timing of infections. Our framework naturally encodes the concerted behavior of the ensemble of paths connecting two nodes in conveying perturbations, with applications ranging from regulatory dynamics within cells to epidemic spreading in social networks.
Climate system
Abrupt expansion of climate change risks for species globally
Climate change is already exposing species to dangerous temperatures driving widespread population and geographical contractions. However, little is known about how these risks of thermal exposure will expand across species’ existing geographical ranges over time as climate change continues. Here, using geographical data for approximately 36,000 marine and terrestrial species and climate projections to 2100, we show that the area of each species’ geographical range at risk of thermal exposure will expand abruptly. On average, more than 50% of the increase in exposure projected for a species will occur in a single decade. This abruptness is partly due to the rapid pace of future projected warming but also because the greater area available at the warm end of thermal gradients constrains species to disproportionately occupy sites close to their upper thermal limit. These geographical constraints on the structure of species ranges operate both on land and in the ocean and mean that, even in the absence of amplifying ecological feedbacks, thermally sensitive species may be inherently vulnerable to sudden warming-driven collapse. With higher levels of warming, the number of species passing these thermal thresholds, and at risk of abrupt and widespread thermal exposure, increases, doubling from less than 15% to more than 30% between 1.5 °C and 2.5 °C of global warming. These results indicate that climate threats to thousands of species are expected to expand abruptly in the coming decades, thereby highlighting the urgency of mitigation and adaptation actions.
Ecological systems
Unveiling the transition from niche to dispersal assembly in ecology
A central goal in ecology is to understand what maintains species diversity in local communities. Classic ecological theory1,2 posits that niches dictate the maximum number of species that can coexist in a community and that the richness of observed species will be below this maximum only where immigration is very low. A new alternative theory3,4 is that niches, instead, dictate the minimum number of coexisting species and that the richness of observed species will usually be well above this because of ongoing immigration. We conducted an experimental test to discriminate between these two unified theories using a manipulative field experiment with tropical intertidal communities. We found, consistent with the new theory, that the relationship of species richness to immigration rate stabilized at a low value at low immigration rates and did not saturate at high immigration rates. Our results suggest that tropical intertidal communities have low niche diversity and are typically in a dispersal-assembled regime where immigration is high enough to overfill the niches. Observational data from other studies3,5 suggest that these conclusions may generalize to other ecological systems. Our new experimental approach can be adapted for other systems and be used as a ‘niche detector’ and a tool for assessing when communities are niche versus dispersal assembled.
Epidemic processes and global flows
The Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated globally during 2020-21, fueling waves of infections. They were displaced by Delta during a third wave worldwide in 2021, in turn displaced by Omicron in late 2021. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of VOCs worldwide. We find that source-sink dynamics varied substantially by VOC, and identify countries that acted as global and regional hubs of dissemination. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal, estimating that India contributed <15% of Delta exports and South Africa <1-2% of Omicron dispersal. We estimate that >80 countries had received introductions of Omicron within 100 days of emergence, associated with accelerating passenger air travel and higher transmissibility. Our study highlights the rapid dispersal of highly transmissible variants with implications for genomic surveillance along the hierarchical airline network.
Enhancing global preparedness during an ongoing pandemic from partial and noisy data
As the coronavirus disease 2019 (COVID-19) spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5, BA.2.75 and other sub- and lineages. We combine the different sources of information in a simple estimate of the pandemic delay and show that only in combination, the pandemic potentials of the lineages are correctly assessed relative to each other. Compared to a country-level epidemic intelligence, our scalable integrated approach, i.e. pandemic intelligence, permits to enhance global preparedness to contrast the pandemic of respiratory pathogens such as SARS-CoV-2.
Population and evolutionary dynamics
Antigenic escape selects for the evolution of higher pathogen transmission and virulence
Despite the propensity for complex and non-equilibrium dynamics in nature, eco-evolutionary analytical theory typically assumes that populations are at equilibria. In particular, pathogens often show antigenic escape from host immune defences, leading to repeated epidemics, fluctuating selection and diversification, but we do not understand how this impacts the evolution of virulence. We model the impact of antigenic drift and escape on the evolution of virulence in a generalized pathogen and apply a recently introduced oligomorphic methodology that captures the dynamics of the mean and variance of traits, to show analytically that these non-equilibrium dynamics select for the long-term persistence of more acute pathogens with higher virulence. Our analysis predicts both the timings and outcomes of antigenic shifts leading to repeated epidemics and predicts the increase in variation in both antigenicity and virulence before antigenic escape. There is considerable variation in the degree of antigenic escape that occurs across pathogens and our results may help to explain the difference in virulence between related pathogens including, potentially, human influenzas. Furthermore, it follows that these pathogens will have a lower R0, with clear implications for epidemic behaviour, endemic behaviour and control. More generally, our results show the importance of examining the evolutionary consequences of non-equilibrium dynamics.
Network neuroscience and bio-inspired computing
The neuroconnectionist research programme
Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call ‘neuroconnectionism’. ANNs have been not only lauded as the current best models of information processing in the brain but also criticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.
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