Marine reserves promote cycles in fish populations on ecological and evolutionary time scales.

Marine reserves are considered essential for sustainable fisheries, although their effectiveness compared to traditional fisheries management is debated. The effect of marine reserves is mostly studied on short ecological time scales, whereas fisheries-induced evolution is a well-established consequence of harvesting. Using a size-structured population model for an exploited fish population of which individuals spend their early life stages in a nursery habitat, we show that marine reserves will shift the mode of population regulation from low size-selective survival late in life to low, early-life survival due to strong resource competition. This shift promotes the occurrence of rapid ecological cycles driven by density-dependent recruitment as well as much slower evolutionary cycles driven by selection for the optimal body to leave the nursery grounds, especially with larger marine reserves. The evolutionary changes increase harvesting yields in terms of total biomass but cause disproportionately large decreases in yields of larger, adult fish. Our findings highlight the importance of carefully considering the size of marine reserves and the individual life history of fish when managing eco-evolutionary marine systems to ensure both population persistence as well as stable fisheries yields.

Phase-separation physics underlies new theory for the resilience of patchy ecosystems.

Spatial self-organization of ecosystems into large-scale (from micron to meters) patterns is an important phenomenon in ecology, enabling organisms to cope with harsh environmental conditions and buffering ecosystem degradation. Scale-dependent feedbacks provide the predominant conceptual framework for self-organized spatial patterns, explaining regular patterns observed in, e.g., arid ecosystems or mussel beds. Here, we highlight an alternative mechanism for self-organized patterns, based on the aggregation of a biotic or abiotic species, such as herbivores, sediment, or nutrients. Using a generalized mathematical model, we demonstrate that ecosystems with aggregation-driven patterns have fundamentally different dynamics and resilience properties than ecosystems with patterns that formed through scale-dependent feedbacks. Building on the physics theory for phase-separation dynamics, we show that patchy ecosystems with aggregation patterns are more vulnerable than systems with patterns formed through scale-dependent feedbacks, especially at small spatial scales. This is because local disturbances can trigger large-scale redistribution of resources, amplifying local degradation. Finally, we show that insights from physics, by providing mechanistic understanding of the initiation of aggregation patterns and their tendency to coarsen, provide a new indicator framework to signal proximity to ecological tipping points and subsequent ecosystem degradation for this class of patchy ecosystems.

Long-distance facilitation of coastal ecosystem structure and resilience.

Biotic interactions that hierarchically organize ecosystems by driving ecological and evolutionary processes across spatial scales are ubiquitous in our biosphere. Biotic interactions have been extensively studied at local and global scales, but how long-distance, cross-ecosystem interactions at intermediate landscape scales influence the structure, function, and resilience of ecological systems remains poorly understood. We used remote sensing, modeling, and field data to test the hypothesis that the long-distance impact of an invasive species dramatically affects one of the largest tidal flat ecosystems in East Asia. We found that the invasion of exotic cordgrass Spartina alterniflora can produce long-distance effects on native species up to 10 km away, driving decadal coastal ecosystem transitions. The invasive cordgrass at low elevations facilitated the expansion of the native reed Phragmites australis at high elevations, leading to the massive loss and reduced resilience of the iconic Suaeda salsa "Red Beach" marshes at intermediate elevations, largely as a consequence of reduced soil salinity across the landscape. Our results illustrate the complex role that long-distance interactions can play in shaping landscape structure and ecosystem resilience and in bridging the gap between local and global biotic interactions.

Circular swimming motility and disordered hyperuniform state in an algae system.

Active matter comprises individually driven units that convert locally stored energy into mechanical motion. Interactions between driven units lead to a variety of nonequilibrium collective phenomena in active matter. One of such phenomena is anomalously large density fluctuations, which have been observed in both experiments and theories. Here we show that, on the contrary, density fluctuations in active matter can also be greatly suppressed. Our experiments are carried out with marine algae ([Formula: see text]), which swim in circles at the air-liquid interfaces with two different eukaryotic flagella. Cell swimming generates fluid flow that leads to effective repulsions between cells in the far field. The long-range nature of such repulsive interactions suppresses density fluctuations and generates disordered hyperuniform states under a wide range of density conditions. Emergence of hyperuniformity and associated scaling exponent are quantitatively reproduced in a numerical model whose main ingredients are effective hydrodynamic interactions and uncorrelated random cell motion. Our results demonstrate the existence of disordered hyperuniform states in active matter and suggest the possibility of using hydrodynamic flow for self-assembly in active matter.

Ice needles weave patterns of stones in freezing landscapes.

Patterned ground, defined by the segregation of stones in soil according to size, is one of the most strikingly self-organized characteristics of polar and high-alpine landscapes. The presence of such patterns on Mars has been proposed as evidence for the past presence of surface liquid water. Despite their ubiquity, the dearth of quantitative field data on the patterns and their slow dynamics have hindered fundamental understanding of the pattern formation mechanisms. Here, we use laboratory experiments to show that stone transport is strongly dependent on local stone concentration and the height of ice needles, leading effectively to pattern formation driven by needle ice activity. Through numerical simulations, theory, and experiments, we show that the nonlinear amplification of long wavelength instabilities leads to self-similar dynamics that resemble phase separation patterns in binary alloys, characterized by scaling laws and spatial structure formation. Our results illustrate insights to be gained into patterns in landscapes by viewing the pattern formation through the lens of phase separation. Moreover, they may help interpret spatial structures that arise on diverse planetary landscapes, including ground patterns recently examined using the rover Curiosity on Mars.

Foraging behaviours lead to spatiotemporal self-similar dynamics in grazing ecosystems.

Biological behaviour-driven self-organized patterns have recently been confirmed to play a key role in ecosystem functioning. Here, we develop a theoretical phase-separation model to describe spatiotemporal self-similar dynamics, which is a consequence of behaviour-driven trophic interactions in short-time scales. Our framework integrates scale-dependent feedback and density-dependent movement into grazing ecosystems. This model derives six types of selective foraging behaviours that trigger pattern formation for top-down grazing ecosystems, and one of which is consistent with existing foraging theories. Self-organized patterns nucleate under moderate grazing intensity and are destroyed by overgrazing, which suggests ecosystem degradation. Theoretical results qualitatively agree with observed grazing ecosystems that display spatial heterogeneities under variable grazing intensity. Our findings potentially provide new insights into self-organized patterns as an indicator of ecosystem transitions under a stressful environment.

Crack Patterns of Environmental Plastic Fragments.

Secondary microplastics usually come from the breakdown of larger plastics due to weathering and environmental stress cracking of plastic wastes. In the present study, 5013 plastic fragments were collected from coastal beaches, estuary dikes, and lake banks in China. The fragment sizes ranged from 0.2 to 17.1 cm, and the dominant polymers were polypropylene and polyethylene. Cracks were observed on the surfaces of 49-56% of the fragments. Based on the extracted crack images, we proposed a general crack pattern system including four crack types with specific definitions, abbreviations, and symbols. The two-dimensional spectral analysis of the cracks suggests that the first three patterns showed good regularity and supported the rationality of the pattern system. Some crack metrics (e.g., line density) were closely correlated with the carbonyl index and additives (e.g., phthalate esters) of fragments. For crack investigation in field, we proposed a succinct protocol, in which five crack ranks were established to directly characterize the degree of cracking based on the line density values. The system was successfully applied to distinguish the differences in crack features at two representative sites, which indicates that crack pattern is a useful tool to describe the morphological changes of plastic surfaces in the environment.

Utility of whole exome sequencing analysis in differentiating intrapulmonary metastatic multiple ground-glass nodules (GGNs) from multiple primary GGNs.

PURPOSE: Clinical evidence of metastasis with ground-glass nodules (GGNs) has been reported, including pulmonary metastasis and distant metastasis. However, the clonal relationships of multiple GGNs at the genetic level remain unclear. EXPERIMENTAL DESIGN: Sixty tissue specimens were obtained from 19 patients with multiple GGN lung cancer who underwent surgery in 2019. Whole exome sequencing (WES) was performed on tissue samples, and genomic profiling and clone evolution analysis were conducted to investigate the genetic characteristics and clonality of multiple GGNs. RESULTS: A total of 15,435 nonsynonymous mutations were identified by WES, and GGNs with shared nonsynonymous mutations were observed in seven patients. Copy number variant (CNV) analysis showed that GGNs in ten patients had at least one shared arm-level CNV. Mutational spectrum analysis showed that GGNs in three patients had similar six substitution profiles and GGNs in fou patients had similar 96 substitution profiles. According to the clone evolution analysis, we found that GGNs in five patients had shared clonal driver gene mutations. Taken together, we identified that 5 patients may have multiple primary GGNs without any similar genetic features, 2 patients may have intrapulmonary metastatic GGNs with ≥ 3 similar genetic features, and the other 12 patients cannot be determined due to insufficient evidences in our cohort. CONCLUSIONS: Our findings suggest that the intrapulmonary metastasis exist in multiple GGNs, but the number of GGNs was not associated with the probability of metastasis. Application of genomic profiling may prove to be important to precise management of patients with multiple GGNs.

Fish Ingest Microplastics Unintentionally.

Microplastics (size of plastic debris <5 mm) occur in various environments worldwide these days and cause detrimental effects on biota. However, the behavioral responses of fish to microplastics in feeding processes are not well understood. In the present study, juveniles from four fish species and two common shapes of microplastics were used to explore fish feeding responses. We found swallowing-feeding fish ingested more pellets than filtering- and sucking-feeding fish. With high-definition and high-speed observational experiments, we found that all species did not actively capture microfibers; instead, they passively sucked in microfibers while breathing. Surprisingly, fish showed a rejective behavior, which was spontaneously coughing up microfibers mixed with mucus. Nevertheless, some of the microfibers were still found in the gastrointestinal tracts and gills of fish, while abundances of ingested microfibers were increased in the presence of food. Our findings reveal a common phenomenon that fish ingest microplastics inadvertently rather than intentionally. We also provide insights into the pathways via which microplastics enter fish and potential strategies to assess future ecological risk and food safety related to microplastics.

A Comparison of the "Reduced Losses" and "Increased Production" Models for Mussel Bed Dynamics.

Self-organised regular pattern formation is one of the foremost examples of the development of complexity in ecosystems. Despite the wide array of mechanistic models that have been proposed to understand pattern formation, there is limited general understanding of the feedback processes causing pattern formation in ecosystems, and how these affect ecosystem patterning and functioning. Here we propose a generalised model for pattern formation that integrates two types of within-patch feedback: amplification of growth and reduction of losses. Both of these mechanisms have been proposed as causing pattern formation in mussel beds in intertidal regions, where dense clusters of mussels form, separated by regions of bare sediment. We investigate how a relative change from one feedback to the other affects the stability of uniform steady states and the existence of spatial patterns. We conclude that there are important differences between the patterns generated by the two mechanisms, concerning both biomass distribution in the patterns and the resilience of the ecosystems to disturbances.

Moesin as a prognostic indicator of lung adenocarcinoma improves prognosis by enhancing immune lymphocyte infiltration.

BACKGROUND: Ezrin-radixin-moesin (ERM) have been explored in many cancer processes. Moesin, as its component, has also been found to play an important role in the prognosis of cancer patients, tumor metastasis, drug resistance, and others. Especially in regulating the immunity, but most results came from direct studies on immune cells, there is no clear conclusion on whether moesin has similar effects in tumor cells. And moesin has certain research results in many cancers in other aspects, but there are few about moesin in lung adenocarcinoma (LUAD). METHODS: We detect the expression of moesin in 82 LUAD and matched normal tissue samples by immunohistochemistry. Besides, for the pathological feature, we did a detailed statistical analysis. And with the help of various databases, we have done in-depth exploration of moesin's ability to enhance the extent of immune lymphocyte infiltration. RESULTS: Moesin is a poor expression in lung cancer tissues than the corresponding normal samples. And this phenomenon had a strongly associated with the prognosis and TNM stage of these LUAD patients. Moesin can enhance the infiltration of multiple immune lymphocytes in lung cancer. And this may be related to the interaction between moesin and various inflammatory molecules. CONCLUSIONS: Moesin is a newly index for the prognosis of LUAD and improves the prognosis of LUAD patients by regulating a variety of inflammation-related molecules to enhance immune lymphocytes infiltration.

REPORT- Clinical outcomes of using second - versus first-Generation EGFR-tkis for the First-Line treatment of advanced NSCLC patients with EGFR mutations: A meta-analysis.

First-generation EGFR-TKIs (gefitinib/erlotinib) and second-generation EGFR-TKI (afatinib) have become the current first-line treatments for EGFR-mutated non-small cell lung cancer (NSCLC), however, the effects of using second-generation EGFR-TKIs compared to those of using first-generation EGFR-TKIs as a first-line treatment for NSCLC patients with EGFR mutations remain unknown. We conducted this meta-analysis based on 4 retrospective and 2 randomized controlled studies published between 2016 and 2018. We surveyed the effectiveness of afatinib/dacomitinib and gefitinib/erlotinib as first-line treatments for stage III-IV EGFR-mutated NSCLC patients. The combined hazard ratio (HR) for the progression free survival (PFS) of second-generation EGFR-TKI group versus that first-generation drug group was 0.64 [95% confidence interval (95% CI) 0.55-0.74; P<0.001], demonstrating a superior PFS in the second-generation group. This outcome coincided with the subgroup analyses comparing the PFS of patients with EGFR exon 19 deletion (HR = 0.68 [95% CI 0.55-0.83; P = 0.0002]) or L858R mutation (HR = 0.64 [95% CI 0.51-0.81; p=0.0002]). Meanwhile, second-generation drugs could to significantly improve the time to progression (TTFs) compared to first-generation drugs (HR = 0.81 [95% CI 0.67-0.89; P = 0.03]). Afatinib and dacomitinib may be the superior first-line treatment for advanced NSCLC patients with EGFR mutations.

The shaping role of self-organization: linking vegetation patterning, plant traits and ecosystem functioning.

Self-organized spatial patterns are increasingly recognized for their contribution to ecosystem functioning, in terms of enhanced productivity, ecosystem stability, and species diversity in terrestrial as well as marine ecosystems. Most studies on the impact of spatial self-organization have focused on systems that exhibit regular patterns. However, there is an abundance of patterns in many ecosystems which are not strictly regular. Understanding of how these patterns are formed and how they affect ecosystem function is crucial for the broad acceptance of self-organization as a keystone process in ecological theory. Here, using transplantation experiments in salt marsh ecosystems dominated by Scirpus mariqueter, we demonstrate that scale-dependent feedback is driving irregular spatial pattern formation of vegetation. Field observations and experiments have revealed that this self-organization process affects a range of plant traits, including shoot-to-root ratio, rhizome orientation, rhizome node number, and rhizome length, and enhances vegetation productivity. Moreover, patchiness in self-organized salt marsh vegetation can support a better microhabitat for macrobenthos, promoting their total abundance and spatial heterogeneity of species richness. Our results extend existing concepts of self-organization and its effects on productivity and biodiversity to the spatial irregular patterns that are observed in many systems. Our work also helps to link between the so-far largely unconnected fields of self-organization theory and trait-based, functional ecology.

Enhanced transport of nutrients powered by microscale flows of the self-spinning dinoflagellate Symbiodinium sp.

The metabolism of a living organism (e.g. bacteria, algae, zooplankton) requires a continuous uptake of nutrients from the surrounding environment. However, within local spatial scales, nutrients are quickly used up under dense concentrations of organisms. Here, we report that self-spinning dinoflagellates Symbiodinium sp. (clade E) generate a microscale flow that mitigates competition and enhances the uptake of nutrients from the surrounding environment. Our experimental and theoretical results reveal that this incessant active behavior enhances transport by approximately 80-fold when compared with Brownian motion in living fluids. We found that the tracer ensemble probability density function for displacement is time-dependent, but consists of a Gaussian core and robust exponential tails (so-called non-Gaussian diffusion). This can be explained by interactions of far-field Brownian motions and a near-field entrainment effect along with microscale flows. The contribution of exponential tails sharply increases with algal density, and saturates at a critical density, implying a trade-off between aggregated benefit and negative competition for the spatially self-organized cells. Our work thus shows that active motion and migration of aquatic algae play key roles in diffusive transport and should be included in theoretical and numerical models of physical and biogeochemical ecosystems.

SGEF is a potential prognostic and therapeutic target for lung adenocarcinoma.

BACKGROUND: SH3-containing guanine nucleotide exchange factor (SGEF), a RhoG-specific guanine nucleotide exchange factor (GEF), was consider as a key signal that determines cancer cell invasion. Although SGEF has been considered to highly express in glioma and prostate cancer. However, it is not well illustrated in LAC. METHODS: In this experiment, expression of SGEF was detected in 92 LAC and corresponding normal tissue samples by immunohistochemistry. In addition, we evaluated the invasion and migration of lung adenocarcinoma cells by the gain and loss of SGEF expression. Furthermore, RhoG activity was measured by GST pull-down assay. RESULTS: SGEF is highly expressed in LAC tissues than in normal lung tissues and was associated with the TNM stage. Lung adenocarcinoma patients with low SGEF subgroup had longer overall survival compared to those with high expression. Furthermore, univariate analysis showed that SGEF expression was an independent prognostic factor for overall survival in lung adenocarcinoma. Silencing of SGEF effectively suppressed the invasion and migration of human lung adenocarcinoma cells in vitro by inhibiting RhoG activity, and over-expression of SGEF could reverse this phenomena. CONCLUSION: SGEF is a novel prognostic target in human lung adenocarcinoma.

Phase separation explains a new class of self-organized spatial patterns in ecological systems.

The origin of regular spatial patterns in ecological systems has long fascinated researchers. Turing's activator-inhibitor principle is considered the central paradigm to explain such patterns. According to this principle, local activation combined with long-range inhibition of growth and survival is an essential prerequisite for pattern formation. Here, we show that the physical principle of phase separation, solely based on density-dependent movement by organisms, represents an alternative class of self-organized pattern formation in ecology. Using experiments with self-organizing mussel beds, we derive an empirical relation between the speed of animal movement and local animal density. By incorporating this relation in a partial differential equation, we demonstrate that this model corresponds mathematically to the well-known Cahn-Hilliard equation for phase separation in physics. Finally, we show that the predicted patterns match those found both in field observations and in our experiments. Our results reveal a principle for ecological self-organization, where phase separation rather than activation and inhibition processes drives spatial pattern formation.

Status of the Parkinson's disease gene family expression in non-small-cell lung cancer.

BACKGROUND: The purpose of this study is to detect the Parkinson's disease gene family mRNA relative expression in the non-small-cell lung cancer (NSCLC) tumor tissue and analyze the association between tumor characteristics and the Parkinson's disease gene family. METHODS: Tumor tissue and tumor-adjacent tissue of 114 NSCLC patients were collected and SYBR quantitative analysis was used to detect the relative expression level of nine Parkinson's disease gene mRNAs. Then, paired sample test, two-sided Student's t-test, or two-sided Wilcoxon rank sum test was performed to analyze the mRNA relative expression level of nine Parkinson's disease gene mRNAs in different gender, tumor histology, and tumor stage. RESULTS: Overexpression in the tumors was detected in 46/114 (40.35%) PARK1/4, 74/114 (64.91%) PARK2, 104/114 (91.23%) PARK5, 95/114 (83.33%) PARK6, 80/114 (70.18%) PARK7, 55/114 (48.25%) PARK8, 100/114 (87.72%) PARK9, 55/114 (48.25%) PARK15, and 99/114 (86.84%) glucocerebrosidase (GBA). Five genes PARK5 (91.23%), PARK6 (83.33%), PARK7 (70.18%), PARK9 (87.72%), and GBA (86.84%) were supposed to be overexpressed in the lung tumor tissues compared with tumor-adjacent tissues. There was no significant difference in PARK1/4, PARK2, PARK5, PARK9, and GBA mRNA expression by different tumor stage, whereas, PARK6, PARK7, PARK8, and PARK15 mRNA expression were found to have significant difference in the comparison of different tumor stages. The expression of PARK6 (P=0.01, P=0.03) and PARK15 (P<0.001, P<0.001) were significantly higher in stages I and II when compared with stage III, respectively. NSCLC patients in stage I showed the higher expression PARK7 compared to the patients in stage II (P=0.003). CONCLUSIONS: The high expression of PARK6, PARK7, and PARK15 might lead to the occurrence of a primary NSCLC tumor, and the tumor with a decreasing expression of these three genes tends to be stages II and III. The results of our study indicate that the Parkinson's disease gene family may be a potential marker for the prediction of NSCLC.

Ivermectin induces nonprotective autophagy by downregulating PAK1 and apoptosis in lung adenocarcinoma cells.

INTRODUCTION: LUAD (Lung adenocarcinoma), the most common subtype of lung carcinoma and one of the highest incidences and mortality cancers in the world remains still a substantial treatment challenge. Ivermectin, an avermectin derivative, has been traditionally used as an antiparasitic agent in human and veterinary medicine practice during the last few decades. Though ivermectin has been shown to be effective against a variety of cancers, however, there is few available data reporting the antitumor effects of ivermectin in LUAD. METHODS: The effect of ivermectin on cell viability and proliferative ability of LUAD cells was evaluated using CCK-8 and colony formation assay. Apoptosis rate and autophagy flux were detected using flow cytometry based on PI/Annexin V staining and confocal laser scanning microscope based on LC3-GFP/RFP puncta, respectively. Western blotting experiment was conducted to verify the results of changes in apoptosis and autophagy. LUAD-TCGA and GEO databases were used to analyse the expression and predictive value of PAK1 in LUAD patients. Xenograft model and immumohistochemical staining were used for verification of the inhibitor effect of ivermectin in vivo. RESULTS: Ivermectin treatment strikingly impeded the colony formation, and the viability of the cell, along with cell proliferation, and caused the apoptosis and enhanced autophagy flux in LUAD cells. In addition, ivermectin-induced nonprotective autophagy was confirmed by treating LUAD cells with 3-MA, an autophagy inhibitor. Mechanistically, we found that ivermectin inhibited PAK1 protein expression in LUAD cells and we confirmed that overexpression of PAK1 substantially inhibited ivermectin-induced autophagy in LUAD cells. Based on TCGA and GEO databases, PAK1 was highly expressed in LUAD tissues as compared with normal tissues. Furthermore, LUAD patients with high PAK1 level have poor overall survival. Finally, in vivo experiments revealed that ivermectin efficiently suppressed the cellular growth of LUAD among nude mice. CONCLUSION: This study not only revealed the mechanism of ivermectin inhibited the growth of LUAD but also supported an important theoretical basis for the development of ivermectin during the therapy for LUAD.

Integrated whole-exome and bulk transcriptome sequencing delineates the dynamic evolution from preneoplasia to invasive lung adenocarcinoma featured with ground-glass nodules.

OBJECTIVE: The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC. METHODS: Thirty-five patients with ground-glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole-exome sequencing (WES) and transcriptome sequencing (RNA-Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA-Seq were subsequently analyzed. RESULTS: The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co-mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD. CONCLUSIONS: Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC.

Self-organized mud cracking amplifies the resilience of an iconic "Red Beach" salt marsh.

Self-organized patterning, resulting from the interplay of biological and physical processes, is widespread in nature. Studies have suggested that biologically triggered self-organization can amplify ecosystem resilience. However, if purely physical forms of self-organization play a similar role remains unknown. Desiccation soil cracking is a typical physical form of self-organization in coastal salt marshes and other ecosystems. Here, we show that physically self-organized mud cracking was an important facilitating process for the establishment of seepweeds in a "Red Beach" salt marsh in China. Transient mud cracks can promote plant survivorship by trapping seeds, and enhance germination and growth by increasing water infiltration in the soil, thus facilitating the formation of a persistent salt marsh landscape. Cracks can help the salt marsh withstand more intense droughts, leading to postponed collapse and faster recovery. These are indications of enhanced resilience. Our work highlights that self-organized landscapes sculpted by physical agents can play a critical role in ecosystem dynamics and resilience to climate change.