Biology subjects

Chu, C.

Publications and source records attributed to Chu, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Mapping the coupling between tract reachability and cortical geometry of the human brain

The study of cortical geometry and connectivity is prevalent in research on the human brain. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brains folding patterns and white matter connectivity unexplored. In this study, we aimed to elucidate fundamental links between cortical geometry and white matter tract connectivity. We developed the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. Specifically, spectral analyses of the cortical surface yielded a set of geometrical eigenmodes, which were then used to explain the locations on the cortical surface reached by specific white matter tracts, referred to as tract reachability. In two independent datasets, we confirmed that tract reachability was well characterized by cortical geometry. We further observed that TGC had high test-retest ability and was specific to each individual. Interestingly, low-frequency TGC was found to be heritable and more informative than the high-frequency components in behavior prediction. Finally, we found that TGC could reproduce task-evoked cortical activation patterns. Collectively, our study provides a new approach to mapping coupling between cortical geometry and connectivity, highlighting how these two aspects jointly shape the connected brain.

neuroscience↗

bioRxiv2025

Physical Activity and Depressive Mood Shared the Structural Connectivity between Motor and Reward Network: a population-based study from the UK Biobank

BackgroundExercise has been revealed to leave a positive effect on alleviating depressive symptoms by various existing studies. However, the neural basis behind this phenomenon remains unknown, as well as its underlying biological mechanism.AimsUsing a large neuroimaging cohort from UK Biobank, this study aimed to identify structural connectivity (SC) patterns simultaneously linked with physical activity and depression, as well as its biological interpretation.Method492 participants with major depression disorder (MDD) and 535 healthy controls (HC) were extracted from the UK Biobank dataset. Partial least squares regression was first utilized to explore a replicable SC pattern simultaneously associated with physical activity and depressive mood. The neuromaps toolbox was applied to interpret the biological ontologies of the identified SC pattern. Neuroimaging-transcriptome association and enrichment analyses were conducted to explore its underlying genetic basis, pathways and cell types. The reproducibility and generalizability were tested on another independent MDD dataset (N=3,496) and bipolar disorder (BD) dataset (N=81).ResultsA SC pattern linked with exercise was identified to be both significantly correlated with depressive mood and group discriminative between MDDs and HCs, which primarily located between the motor-related regions and reward-related regions. This pattern was associated with multiple neurotransmitter receptors, such as serotonin and GABA receptors, and enriched in pathways like synaptic signaling and astrocytes cell type. The SC pattern and genetic results were also replicated in another independent MDD dataset and present commonalities with BD.ConclusionsThis study not only initially identified a reproducible shared SC pattern between physical activity and depressive mood, but also elucidated the underlying biological mechanisms, which enhanced our understanding of how exercise helps alleviate depression and may inform the development of novel neuromodulation targets.

neuroscience↗

bioRxiv2025

Single-cell RNA sequencing of peripheral blood defines two immunological subtypes of Sjögren's disease

Sjogrens disease (SjD) is a heterogeneous autoimmune disorder with significant clinical and molecular diversity. While anti-SSA antibodies serve as a hallmark serological biomarker, nearly half of patients lack them, raising fundamental questions about distinct pathogenic mechanisms. To address this, we performed single-cell RNA sequencing with surface protein profiling on 1.5 million PBMCs from 333 participants in the Sjogrens International Collaborative Clinical Alliance cohort, comparing those with and without SjD and stratifying them by anti-SSA status. Our analysis identified two immunologically distinct subtypes of SjD, with SSA-positive patients exhibiting a dominant and persistent IFN-I signature, profoundly impacting immune cell maturation. Notably, transitional B cells were disproportionately affected, displaying signs of premature maturation, reduced BCR diversity, and shorter CDR3 regions, reinforced interactions with proinflammatory cells, thereby fostering an environment conducive to autoreactivity. By contrast, SSA-negative SjD participants lacked an upregulated IFN-I signature, challenging prevailing pathogenic models and suggesting alternative immune dysregulation pathways. These findings support a two-disease model of SjD and highlight transitional B cells as both a key biomarker and a potential therapeutic target. Targeting IFN-I signaling and transitional B cell maturation may represent a novel therapeutic avenue to modulate immune dysregulation and prevent autoreactivity in SjD.

genomics↗

bioRxiv2025

Accounting for Edge Uncertainty in Stochastic Actor-Oriented Models for Dynamic Network Analysis

Stochastic Actor-Oriented Models (SAOMs) were designed in the social network setting to capture network dynamics representing a variety of influences on network change. The standard framework assumes the observed networks are free of false positive and false negative edges, which may be an unrealistic assumption. We propose a hidden Markov model (HMM) extension to these models, consisting of two components: 1) a latent model, which assumes that the unobserved, true networks evolve according to a Markov process as they do in the SAOM framework; and 2) a measurement model, which describes the conditional distribution of the observed networks given the true networks. An expectation-maximization algorithm is developed for parameter estimation. We address the computational challenge posed by a massive discrete state space, of a size exponentially increasing in the number of vertices, through the use of the missing information principle and particle filtering. We present results from a simulation study, demonstrating our approach offers improvement in accuracy of estimation, in contrast to the standard SAOM, when the underlying networks are observed with noise. We apply our method to functional brain networks inferred from electroencephalogram data, revealing larger effect sizes when compared to the naive approach of fitting the standard SAOM.

neuroscience↗

bioRxiv2025

Mapping Early Brain Maturation: Anatomical Substrates of Cortical Connectivity Shifts in Neonates

Understanding the early development of brain connectivity is essential for unraveling the mechanisms of brain maturation. In this study, we utilized diffusion MRI data from 242 term neonates to chart the developmental trajectory of cortical connectivity in infants. We quantified interareal variations in connectivity and identified three distinct global connectopies (GCs) along the rostrocaudal, dorsoventral, and mediolateral axes by using gradient mapping techniques. A pivotal age-dependent shift between the dorsoventral and mediolateral GCs occurred at 40 postmenstrual weeks. This shift was diminished by virtual thalamic fiber lesions, underscoring the critical role of thalamic projections. A longitudinal analysis disclosed a delayed structural connectivity pattern development in preterm infants who failed to exhibit the anticipated shift. This research helps to clarify the topographic principles that shape infant brain organization and emphasizes the influence of thalamic connectivity on early brain development. Our findings elucidate the anatomical underpinnings of early brain development, providing critical insights into the formation of cortical hierarchies and highlighting the influence of thalamic connectivity on developmental trajectories. These findings are essential for understanding typical brain growth and the pathogenesis of neurodevelopmental disorders.

neuroscience↗

bioRxiv2024

Natural variations of TaMYB7-A1 regulate PHS resistance and specify wheat geographic adaptation

Crop domestication tended to select against seed dormancy for uniform germination--raising risks of undesirable pre-harvest sprouting (PHS) -- but regulation of seed dormancy and PHS in wheat are grossly under-characterized. Here, we identified wheat PHS resistance loci by GWAS. TaMYB7-A1 confers PHS resistance by elevating ABA signaling and seed dormancy in grains. Three TaMYB7-A1 haplotypes (Hap-1/2/3) contrast in PHS resistance, with Gly23 and Gly92 crucial for binding to and activating TaABI5 in Hap-1/3. A MITE transposon in the TaMYB7-A1Hap-1 promoter likely recruited the TaAZF1-TaABI4 module to boost expression, resulting in strong PHS resistance. TaMYB7-A1Hap-1 originated from wild einkorn and was integrated into hexaploid wheat through introgression into wild emmer. Different haplotypes of TaMYB7-A1, in conjunction with alleles of other major PHS resistance genes, is pivotal in shaping wheats adaptability to rainfall conditions in China, US and Europe during the harvest season. Introduction of TaMYB7-A1Hap-1 into elite cultivars confers PHS resistance without yield defects. Thus, artificial and natural selection across diverse climates regions have collectively shaped wheat adaptation and enabled rational delivery of improved lines tailored to local cropping needs.

plant biology↗

bioRxiv2024

YY1 Enhances the Stability of HIF-1α Protein by Interacting with NUSAP1 in Macrophages within the Prostate Cancer Microenvironment

Immune checkpoint therapy for prostate cancer (PCa) has failed in clinical trials; however, the precise underlying mechanisms involved remain elusive. PCa, a classic "immune-cold" tumor, is characterized by an immunosuppressive tumor microenvironment. Within this milieu, macrophages, the predominant immune cell population, have a propensity to infiltrate the hypoxic zones of tumors. In a previous study, we showed that Yin Yang 1 (YY1) is highly expressed in macrophages in PCa tissues. Here, through multiplexed imaging mass cytometry (IMC) of a PCa tissue microarray, we further demonstrate that YY1+ macrophages aggregate in hypoxic areas of tumors and that hypoxia promotes the phase separation of YY1 in the nucleus by increasing YY1 tyrosine phosphorylation in macrophages. Furthermore, YY1 binds to NUSAP1 and promotes the SUMOylation of HIF-1, which promotes phase separation and stabilization of the HIF-1 protein. We also demonstrated that either treatment with a small molecule inhibitor (tenapanor) to decrease the YY1-NUSAP1-HIF-1 interaction or myeloid-specific YY1 gene knockout impairs subcutaneous PCa tumor formation. Furthermore, we present a first-generation tetrahedral DNA nanostructure (TDN) based on the proteolysis targeting chimera (PROTAC) technique, named YY1-DcTAC, which targets and degrades YY1 in tumor-associated macrophages. In a PCa mouse model, YY1-DcTAC exhibited prolonged drug efficacy, robust macrophage-specific responsiveness, potent antitumor effects, and increased CD8+ T cell tumor infiltration. In summary, our findings underscore the pivotal role of YY1 within the hypoxia/HIF-1 pathway in tumor-associated macrophages and affirm the therapeutic potential of targeting YY1 for treating PCa.

cancer biology↗

bioRxiv2024

Uncovering Individualized Cerebellar Atrophy Pattern and Behavioral Links in Children with Brainstem Tumor

Background and PurposeBrainstem tumors are rare but cause enduring behavioral issues, challenging patients and surgeons. Research on cerebellar changes in these patients limited, despite symptoms similar to cerebellar injuries. This study aims to investigate cerebellar damage pattern resulting from brainstem tumors and its association with behavioral disorders. MethodsIn this study, a U-Net-based segmentation algorithm was used to divide the cerebellum into 26 lobules, which were then used to build a normative model for assessing individual structural deviations. Furthermore, a behavior prediction model was developed using the total outlier count (tOC) index and brain volume as predictive features. ResultsMost patients were found to have negative deviations in cerebellar regions, particularly in anterior lobules like Left V. Higher tOC was significantly associated with severe social problems (r = 0.31, p = 0.001) and withdrawal behavior (r = 0.28, p = 0.001). Smaller size of cerebellar regions strongly correlated with more pronounced social problems (r = 0.27, p = 0.007) and withdrawal behavior (r = 0.25, p = 0.015). Notably, lobules Right X, V, IV, VIIB, Left IX, VIII, and X influenced social problems, while Left V, Right IV, Vermis VI, and VIII impacted withdrawal behavior. ConclusionsOur study revealed cerebellar damage patterns in patients with brainstem tumors, emphasizing the role of both anterior and posterior cerebellar lobes in social problems and withdrawal behavior. This research sheds light on the brain mechanisms underlying complex behavioral disorders in brainstem tumor patients.

neuroscience↗

bioRxiv2024

Normative Growth Modeling of Cortical Thickness Identify Neuroanatomical Variability and Distinct Subtypes in Brainstem Tumor Patients

BackgroundBrainstem tumors can cause structural brain changes, but the resulting heterogeneity within wholebrain structure is not well-studied. This study examines cortical thickness to identify patterns of structural alterations and explore underlying biological subtypes and their associations with clinical factors. Materials and MethodsThis study involved 124 pediatric brainstem tumor patients, aged 4-18 years. Cortical thickness was measured using CAT12 segmentation of 3D T1-weighted structural MRI. A normative model was established using data from 849 healthy children. Deviations in cortical thickness were estimated, and patients were classified into two subtypes using spectral clustering. Clinical statistical analyses were conducted with SPSS 26.0. ResultsThe normative model revealed significant heterogeneity in cortical thickness deviations, which correlated with tumor size and growth patterns. Focal tumors primarily caused negative deviations (t = 3.14, p = 0.02). There was a significant positive correlation between extreme positive deviations and tumor volume (r = 0.214, p = 0.010), and between extreme negative deviations and progression-free survival (r = 0.39, p = 0.008). Two subtypes were identified: Subtype 1, consisting of diffuse tumors with extreme positive deviations, and Subtype 2, consisting of focal tumors with extreme negative deviations. Subtype and tumor growth pattern significantly influenced duration (p < 0.01). The Kaplan-Meier survival curves for Subtype 1 and Subtype 2 demonstrated a significant difference in survival probabilities over time (p = 0.03). ConclusionOverall, this study identifies two major patterns of cortical thickness changes in brainstem tumor patients, enhancing our understanding of their relationship with cortical morphology. The findings suggest that cortical thickness alterations could serve as valuable biomarkers for predicting progression-free survival, which is crucial for clinical assessment and personalized treatment strategies. This research provides new insights into the physiological mechanisms by which brainstem tumors affect brain structure, supporting more precise clinical interventions and efficacy monitoring in the future.

neuroscience↗

bioRxiv2024

Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Underpinnings

Chimpanzees (Pan troglodytes) are humans closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.

neuroscience↗

bioRxiv2024

An epilepsy-associated CILK1 variant compromises KATNIP regulation and impairs primary cilia and Hedgehog signaling

Mutations in human CILK1 (ciliogenesis associated kinase 1) are linked to ciliopathies and epilepsy. Homozygous point and nonsense mutations that extinguish kinase activity impair primary cilia function, whereas mutations outside the kinase domain are not well understood. Here, we produced a knock-in mouse equivalent of the human CILK1 A615T variant identified in juvenile myoclonic epilepsy (JME). This residue is in the C-terminal region of CILK1 separate from the kinase domain. Mouse embryo fibroblasts (MEF) with either heterozygous or homozygous A612T mutant alleles exhibited a higher ciliation rate, shorter individual cilia and up-regulation of ciliary Hedgehog signaling. Thus, a single A612T mutant allele was sufficient to impair primary cilia and ciliary signaling in MEFs. Gene expression profiles of wild type versus mutant MEFs revealed profound changes in cilia-related molecular functions and biological processes. CILK1 A615T mutant protein was not increased to the same level as the wild type protein when co-expressed with scaffold protein KATNIP (katanin-interacting protein). Our data show that KATNIP regulation of a JME-associated single residue variant of CILK1 is compromised and this impairs the maintenance of primary cilia and Hedgehog signaling.

cell biology↗

bioRxiv2024

Single-cell profiling reveals the intratumor heterogeneity and immunosuppressive microenvironment in cervical adenocarcinoma

BackgroundCervical adenocarcinoma (ADC) is more aggressive compared to other types of cervical cancer (CC), such as squamous cell carcinoma (SCC). The tumor immune microenvironment (TIME) and tumor heterogeneity are recognized as pivotal factors in cancer progression and therapy. However, the disparities in TIME and heterogeneity between ADC and SCC are poorly understood. MethodsWe performed single-cell RNA sequencing on 11 samples of ADC tumor tissues, with other 4 SCC samples served as controls. The immunochemistry and multiplexed immunofluorescence were conducted to validate our findings. ResultsCompared to SCC, ADC exhibited unique enrichments in several sub-clusters of epithelial cells with elevated stemness and hyper-malignant features, including the Epi_10_CYSTM1 cluster. ADC displayed a highly immunosuppressive environment characterized by the enrichment of regulatory T cells (Tregs) and tumor-promoting neutrophils. The Epi_10_CYSTM1 cluster recruits Tregs via ALCAM-CD6 signaling, while Tregs reciprocally induce stemness in the Epi_10_CYSTM1 cluster through TGF{beta} signaling. Importantly, our study revealed that the Epi_10_CYSTM1 cluster could serve as a valuable predictor of lymph node metastasis for CC patients. ConclusionsThis study highlights the significance of ADC-specific cell clusters in establishing a highly immunosuppressive microenvironment, ultimately contributing to the heightened aggressiveness and poorer prognosis of ADC compared to SCC.

cancer biology↗

bioRxiv2024

Cross-species alignment along the chronological axis reveals evolutionary effect on structural development of human brain

Disentangling evolution mysteries of human brain has always been an imperative endeavor in neuroscience. On the one hand, by spatially aligning the brains between human and nonhuman primates (NHPs), previous efforts in comparative studies revealed both correspondence and difference in brain anatomy, e.g., the morphological and the connectomic patterns. On the other hand, brain anatomical development along the temporal axis is evident for both human and NHPs in early life. However, it remains largely unknown whether we can conjugate the brain development phases between human and NHPs, and, especially, what the role played by the brain anatomy in the conjugation will be. Here, we proposed to embed the brain anatomy of human and macaque in the chronological axis for enabling the cross-species comparison on brain development. Specifically, we separately established the prediction models by using the brain anatomical features in gray matter and white matter tracts to predict the chronological age in the human and macaque samples with brain development. We observed that applying the trained models within-species could well predict the chronological age. Interestingly, by conducting the cross-species application of the trained models, e.g., applying the model trained in humans to the data of macaques, we found a significant cross-species imbalance regarding to the model performance, in which the model trained in macaque showed a higher accuracy in predicting the chronological age of human than the model trained in human in predicting the chronological age of macaque. The cross application of the trained model introduced the brain cross-species age gap (BCAP) as an individual index to quantify the cross-species discrepancy along the temporal axis of brain development for each participant. We further showed that BCAP was associated with the behavioral performance in both visual sensitivity test and picture vocabulary test in the human samples. Taken together, our study situated the cross-species brain development along the chronological axis, which highlighted the disproportionately anatomical development in the human brain to extend our understanding of the potential evolutionary effects.

neuroscience↗

bioRxiv2024

Identifying Reproducible Transcription Regulator Coexpression Patterns with Single Cell Transcriptomics

The proliferation of single cell transcriptomics has potentiated our ability to unveil patterns that reflect dynamic cellular processes such as the regulation of gene transcription. In this study, we leverage a broad collection of single cell RNA-seq data to identify the gene partners whose expression is most coordinated with each human and mouse transcription regulator (TR). We assembled 120 human and 103 mouse scRNA-seq datasets from the literature (>28 million cells), constructing a single cell coexpression network for each. We aimed to understand the consistency of TR coexpression profiles across a broad sampling of biological contexts, rather than examine the preservation of context-specific signals. Our workflow therefore explicitly prioritizes the patterns that are most reproducible across cell types. Towards this goal, we characterize the similarity of each TRs coexpression within and across species. We create single cell coexpression rankings for each TR, demonstrating that this aggregated information recovers literature curated targets on par with ChIP-seq data. We then combine the coexpression and ChIP-seq information to identify candidate regulatory interactions supported across methods and species. Finally, we highlight interactions for the important neural TR ASCL1 to demonstrate how our compiled information can be adopted for community use. Author SummaryA common way to analyze gene expression (transcriptomics) data is to correlate gene transcript levels across samples for every pair of genes (coexpression). Coordinated expression between genes may imply a shared biological function, though this warrants cautious interpretation given assumptions about cellular processes inferred from RNA abundances alone. Still, coexpression inference is often used to nominate genes whose expression may be controlled by transcription regulators (TRs). The rapid generation of diverse single cell transcriptomics data has unlocked our ability to discover coexpression patterns across individual cells -- though these signals are often noisy. Reproducible patterns across studies can help distinguish meaningful biological relationships from spurious correlations. We used this study to analyze a broad collection of single cell data spanning numerous tissues in human and mouse to infer global TR coexpression patterns. We aimed to learn which interactions were generally observable, to better potentiate future examinations of reproducible coexpression in specific contexts. We evaluate the predictive performance of these global single cell coexpression rankings using independent gene regulation evidence, and highlight TR-gene pairs that are supported across data modalities as well as species. By disseminating these rankings, we hope that other researchers can extract insight for their own TRs of interest.

bioinformatics↗

bioRxiv2024

Capturing G protein-coupled receptors into native lipid-bilayer nanodiscs using new diisobutylene/maleic acid (DIBMA) copolymers

Many membrane proteins, including G-protein-coupled receptors (GPCRs), are susceptible to denaturation when extracted from their native membrane by detergents. Therefore, alternative methods have been developed, including amphiphilic copolymers that enable the direct extraction of functional membrane proteins along with their surrounding lipids, leading to the formation of native lipid-bilayer nanodiscs. Among these amphiphilic copolymers, styrene/maleic acid (SMA) and diisobutylene/maleic acid (DIBMA) polymers have been extensively studied and successfully utilized to isolate various types of membrane proteins, including GPCRs. Despite their many benefits, SMA and DIBMA polymers also have significant drawbacks that limit their application. Most notably, both SMA and DIBMA carry high negative charge densities, which can interfere with protein-protein and protein-lipid interactions through unspecific Coulombic attraction or repulsion. Herein, we describe a series of new amphiphilic copolymers derived from DIBMA via partial amidation of the carboxylate pendant groups with various biocompatible amines. The nanodisc-forming properties of the new polymers were assessed using model membranes as well as in the context of extracting the melanocortin 4 receptor (MC4R), a prototypical class A GPCR. While each new DIBMA variant displays distinct features that may be favorable for selected applications, we identified a new PEGylated DIBMA variant called mPEG4-DIBMA as particularly promising for the studied purpose. On the one hand, mPEG4-DIBMA abolishes unspecific interactions with the tested peptide ligand, a prerequisite for reliably characterizing GPCR-ligand interactions. On the other hand, mPEG4-DIBMA outperforms other polymers such as SMA and DIBMA by achieving higher extraction efficiencies of MC4R from Sf9 insect cell membranes. Thus, this new nanodisc-forming polymer combines two key advantages that are crucial for investigating GPCRs in a well-defined but still native lipid-bilayer environment, thus paving the way for manifold future applications.

biochemistry↗

bioRxiv2023

Integrated-omics profiling unveils the disparities of host defense to ECM scaffolds during wound healing in aged individuals.

Extracellular matrix (ECM) scaffold membranes have exhibited promising potential to better the outcomes of wound healing by creating a regenerative microenvironment around. However, when compared to the application in younger individuals, the performance of the same scaffold membrane in promoting re-epithelialization and collagen deposition was observed dissatisfying in aged mice. To comprehensively elucidate the mechanisms underlying this age-related disparity, we conducted an integrated analysis, combing single-cell RNA sequencing (scRNA-Seq) with spatial transcriptomics, to explore the complex cellular niches surrounding the ECM scaffolds. Through intergroup comparative analysis and cell-cell communication, we identified and characterized the senescent SPP1+ macrophages may impede the activation of the type L immune response, thus inhibiting the repair ability of epidermal cells and fibroblasts around the ECM scaffolds. These findings contribute to a deeper understanding of biomaterial applications in varied physiological contexts, thereby paving the way for the development of precision-based biomaterials tailored specifically for aged individuals in future therapeutic strategies.

immunology↗

bioRxiv2023

Climate change decreases the likelihood of tropical forest community persistence with a strong mediation of plant-plant network structures

Climate change is known to negatively impact tropical forests; yet how climate change impacts tree community persistence at local scales remains less clear. Using data from a long-term tropical forest census plot over 25 years, we constructed plant- plant interaction networks based on tree growth. We then quantified community persistence as feasibility domain of constituent species using recently developed frameworks of structural stability. We found a decrease in structural stability under warming and precipitation changes over time as evidenced by both direct environmental effects and indirect effects via network structure; and indirect effects were stronger than direct effects. Among these structures, facilitation:competition degree ratio and competitive transitivity were most positively related with structural stability. Our study highlights how the lens of plant-plant interaction networks can identify novel details about risk to tropical forest diversity under climate change at local scales. Insights from this work will be helpful for aligning forest management activities with areas under the greatest risk of species loss.

ecology↗

bioRxiv2023

Forest demography and biomass accumulation rates are associated with transient mean tree size vs density scaling relations

Linking individual and stand-level dynamics during forest development reveals a scaling relationship between mean tree size and tree density in forest stands, which integrates forest structure and function. However, the nature of this so-called scaling law and its variation across broad spatial scales remains unquantified and its linkage with forest demographic processes and carbon dynamics remains elusive. Here we develop a theoretical framework and compile a broad-scale dataset of long-term sample forest stands (n = 1433) from largely undisturbed forests to examine the association of temporal mean tree size vs density scaling trajectories (slopes) with biomass accumulation rates and the sensitivity of scaling slopes to environmental and demographic drivers. The results empirically demonstrate a large variation of scaling slopes, ranging from -4 to -0.2, across forest stands in tropical, temperate and boreal forest biomes. Steeper scaling slopes are associated with higher rates of biomass accumulation, resulting from a lower offset of forest growth by biomass loss from mortality. In North America, scaling slopes are positively correlated with forest stand age and rainfall seasonality, thus suggesting a higher rate of biomass accumulation in younger forests with lower rainfall seasonality. These results demonstrate the strong association of the transient mean tree size vs density scaling trajectories with forest demography and biomass accumulation rates, thus highlighting the promise of leveraging forest structure properties to predict forest demography, carbon fluxes and dynamics at broad spatial scales. Significance StatementMean tree size vs density scaling relationships are thought to predict forest function at broad spatial scales. Here we develop a theoretical framework based upon demographic processes and empirical evidence from forest inventory data to demonstrate a strong association of the transient mean tree size and density scaling trajectories (slopes) with forest demography and biomass accumulation rates. This strong association is pervasive across forest biomes and suggests a negative relationship between scaling slope and biomass accumulation rate (resource availability). Our results highlight the promise of leveraging forest structure (i.e., inferred from high resolution remote sensing data or fused into size-structured demographic models) to evaluate forest demography, carbon fluxes and dynamics at broad spatial scales.

ecology↗