Quan-Xing Liu

Self-organization theory predicts that ecosystem functioning and resilience can emerge from feedbacks that generate spatial patterns. These emergent properties have commonly been explained by local positive feedbacks that concentrate limiting resources within productive patches. Here, we identify a stress-redistribution feedback underlying self-organized hummock-hollow patterning. Through this feedback, salinity stress is partitioned across the patterned landscape, maintaining vegetated hummocks as low-salinity refugia alongside salt-rich hollows and thereby sustaining ecosystem functioning under climate-related salinization. A spatially explicit model predicts that rain-driven salt redistribution lowers hummocks salinity, increases productivity, and enhances resilience to a salt pulse. Field and remote-sensing data support these predictions: Patterned hummocks have lower soil salinity, higher biomass, greater reproductive output, and prolonged phenological activity compared with adjacent homogeneous vegetation. Together, these results reveal that spatial self-organization can support ecosystem functioning and resilience under climate stress through an underappreciated mechanism: the spatial redistribution of environmental stress. Restoring such self-organized patterning may offer a promising strategy for sustaining ecosystems in a changing climate.

Tidal creeks impose strong hydrological and geomorphic gradients that shape plant traits and sediment dynamics in salt marshes. However, how creek‐imposed gradients reorganize plant allometric strategies and how these trait shifts regulate sediment retention remain poorly quantified. We conducted field surveys and sediment measurements along cross‐creek transects in the Chongming Dongtan salt marshes (Yangtze River Estuary) to examine spatial variation in vegetation traits, environmental conditions, and sediment processes. Using generalized linear models (GLMs), non‐parametric local regression (LOESS), and Gaussian nonlinear fitting, we quantified relationships between plant allometry, vegetation density, and suspended sediment concentration, net sediment deposition, and sediment retention rate. Plant traits varied systematically with distance from tidal creeks: aboveground biomass of the pioneer species Scirpus mariqueter near creek edges was approximately 2.6‐fold higher than at 30 m inland, while stem height–diameter relationships shifted from structural reinforcement near creeks to height investment farther from creeks, reflecting allometric trade‐offs along hydrodynamic stress gradients. Sediment retention exhibited a clear nonlinear response to vegetation density, peaking at intermediate densities (~1000–1500 shoots/m ² ). These results demonstrate that tidal creeks act as trait‐based filters that generate emergent, nonlinear sediment retention patterns, providing mechanistic insight into biogeomorphic self‐organization and quantitative guidance for nature‐based salt marsh conservation and restoration.

On Mars, fields of sand dunes contrast with the generally cratered, rocky terrain commonly seen from orbit. Near the equator, in Gale Crater, images from the rover Curiosity also reveal order on smaller scales: ripples on dunes, and ground patterns in scattered sites. The patterns include relatively inconspicuous forms: evenly spaced pebble‐size rocks (here termed clasts) on meter‐scale domains of wind‐blown sand. Here, we examine quantitatively several such domains on both Mars and Earth. The clasts are significantly more orderly than expected by chance. Moreover, many are “hyperuniform,” a self‐organized state recently recognized in diverse active materials and biological systems but that appears novel for planetary surfaces. We use numerical simulations to examine how diverse clast distributions, ranging from random and hyperuniform dispersions to distinct alignments, can emerge spontaneously from clast displacements induced by gravity combined with the wind‐driven evolution of the surface, sand transport, and ripple migration. This paper highlights clast arrangements, often‐overlooked relative to more obvious ground patterns. Moreover, our methods and findings may have quantitative implications for issues of global significance on Earth and other planets, including dust emission from vast areas into the atmosphere, and planetary energy budgets.

Self-organization of individual organisms at a very small scale may result in recognizable functional ecosystem structures at a larger spatial scale. Drylands, which cover almost half of emerged lands, host some of the most remarkable vegetation patterns on Earth, including “disordered hyperuniformity,” a recently defined class of such emergent self-organization structures. Yet, the extent, causes, and consequences of disordered hyperuniform vegetation patterns in drylands remain virtually unknown. Here, we analyzed high-resolution remote sensing images of 425 spot-like drylands across the globe and found that disordered hyperuniformity shapes vegetation patterns in about one out of ten drylands, with the distribution of plants appearing to be “disordered” to the naked eye, but supporting highly recognizable (uniform) patterns at larger scales ( ca. 50 to 500 m). Using mathematical models, we identify three potential mechanisms that can generate disordered hyperuniform vegetation patterns. These mechanisms are not limited to the well-studied Turing patterns and represent key general processes with respect to plant–plant or plant–sediment interactions. Further modeling indicates that disordered hyperuniformity enhances ecosystem functioning in terms of water retention use, and expands the range of aridity conditions under which the system can maintain itself, but may slow recovery of vegetation structure from disturbances. In a wider context, we also show that disordered hyperuniformity is likely to pertain to diverse dryland systems, such as termite-mound or fairy-circle landscapes. Our findings highlight that exploring disordered hyperuniformity of vegetation pattern of drylands (and potentially other large-scale systems) offers insights into the organization and resilience of ecosystems globally.

Microalgae play a crucial role in aquatic ecosystems by contributing to global primary production and nutrient cycling. At high cell densities, these microorganisms trigger a phenomenon known as bioconvection, where their collective swimming behavior generates self-organized flow patterns within the surrounding fluid. In this study, we investigate the bioconvection mixing in the marine algae Effrenium voratum through controlled experiments and numerical simulations based on a continuum model. We employ particle image velocimetry to quantify both cell migration and the dynamics of fluid flow. Our results demonstrate that bioconvection enhances vertical transport and mixing, particularly when cell density exceeds normal population levels. Our findings reveal two significant phenomena: First, the energy spectra of velocity in a laminar bioconvection system exhibit an exponential decay of −5/3, reminiscent of Kolmogorov scaling and indicative of turbulence. Second, we directly capture the temporal switching of upward and downward fluxes, highlighting their role in promoting nutrient exchange between water layers. Cells accumulate at the air–water interface, leading to rapid sinking of the surrounding fluid and the formation of plumes, resembling Rayleigh–Taylor instability. Additionally, our minimal model effectively reproduces these dynamics, confirming that aggregation-driven bioconvection enhances vertical mixing. These findings provide new insights into how aggregation-induced bioconvection affects nutrient distribution and light transmission in aquatic systems.

The adaptive capacity of ecosystems, or their ability to function despite altered environmental conditions, is crucial for resilience to climate change. However, the role of landscape complexity or species traits on adaptive capacity remains unclear. Here, we combine field experiments and morphodynamic modelling to investigate how ecosystem complexity shapes the adaptive capacity of intertidal salt marshes. We focus on the importance of tidal channel network complexity for sediment accumulation, allowing vertical accretion to keep pace with sea-level rise. The model showed that landscape-scale ecosystem complexity, more than species traits, explained higher sediment accumulation rates, despite complexity arising from these traits. Landscape complexity, reflected in creek network morphology, also improved resilience to rising water levels. Comparing model outcomes with real-world tidal networks confirmed that flow concentration, sediment transport and deposition increase with drainage complexity. These findings emphasize that natural pattern development and persistence are crucial to preserve resilience to climate change.

Phase separation is crucial in biological processes and ecological resilience, yet experimental evidence supporting validity of mass-conserving reaction-diffusion (MCRD) models in describing phase separation remains rare. Here, we identified one type of biomolecular condensates – double-stranded DNA (dsDNA) and the human transcription factor p53 as forming dsDNA-protein interactive co-condensates (DPICs) as an experimental model, where dynamic DPICs evolve into droplet-like patterns through reversible autocatalytic biochemical reactions. Thus, we can use the MCRD model to describe this experimental system. The pattern formation depends on concentration of protein and dsDNA and their local nonlinear interactions, which were experimentally tested at meso-scale and integrated into an MCRD model. Our results provide direct evidence that the experimental data-driven MCRD models can reproduce the observed phase diagram and scaling-invariance coarsening patterns, thus, providing a compelling mechanism for phase-separation pattern in other systems.