Biology subjects

Cao, M.

Publications and source records attributed to Cao, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Conserved Untranslated Regions of Multipartite Viruses: Natural Markers of Novel Viral Genomic Components and Tags of Viral Evolution

Viruses with split genomes are categorized as being either segmented or multipartite according to whether their genomic segments occur in single or different virions. Some complexity will exist, in that inherited "core" vital segments viruses may renew the others once host and environmental alterations keep driving viral evolution. Despite this uncertainty, empirical observations have been made across the split genomes in the untranslated regions (UTRs) on the short or long stretches of conserved or identical sequences. In this study, we describe a methodology that combines RNA and small RNA sequencing, conventional BLASTx, and iterative BLASTn of UTRs to detect viral genomic components even if they encode orphan genes (ORFans). Within the phylum Kitrinoviricota, novel putative multipartite viruses and viral genomic components were annotated using data obtained from our sampling or publicly available sources. The novel viruses, as extensions or intermediate nodes, enriched the information of the evolutionary networks. Furthermore, the diversity of novel genomic components emphasized the evolutionary roles of reassortment and recombination, as well as genetic deletion, strongly supporting the genomic complexity. These data also suggest insufficient knowledge of these genomic components for categorizing some extant viral taxa. The relative conservation of UTRs at the genome level may explain the relationships between monopartite and multipartite viruses and how the multipartite viruses can have a life strategy involving multiple host cells. Author summaryThe current workflows for virus identification are largely based on high-throughput sequencing and coupled protein sequence homology-dependent analysis methods and tools. However, for viruses with split genomes, the identification of genomic components whose deduced protein sequences are not homologous to known sequences is inadequate. Furthermore, many plant-infecting multipartite viruses contain conserved UTRs across their genomic components. Based on this, we propose a practical method of UTR-backed iterative BLASTn (UTR-iBLASTn) to explore the components with ORFans and study virus evolution using the UTRs as signals. These shed light on viral "dark matter"--unknown/omitted genomic components of segmented/multipartite viruses from different kingdoms and hosts, and the origins of these components.

microbiology↗

bioRxiv2021

SARS-CoV-2 diverges from other betacoronaviruses in only partially activating the IRE1α/XBP1 ER stress pathway in human lung-derived cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed over 6 million individuals worldwide and continues to spread in countries where vaccines are not yet widely available, or its citizens are hesitant to become vaccinated. Therefore, it is critical to unravel the molecular mechanisms that allow SARS-CoV-2 and other coronaviruses to infect and overtake the host machinery of human cells. Coronavirus replication triggers endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR), a key host cell pathway widely believed essential for viral replication. We examined the master UPR sensor IRE1 kinase/RNase and its downstream transcription factor effector XBP1s, which is processed through an IRE1-mediated mRNA splicing event, in human lung-derived cells infected with betacoronaviruses. We found human respiratory coronavirus OC43 (HCoV-OC43), Middle East respiratory syndrome coronavirus (MERS-CoV), and murine coronavirus (MHV) all induce ER stress and strongly trigger the kinase and RNase activities of IRE1 as well as XBP1 splicing. In contrast, SARS-CoV-2 only partially activates IRE1 through autophosphorylation, but its RNase activity fails to splice XBP1. Moreover, while IRE1 was dispensable for replication in human cells for all coronaviruses tested, it was required for maximal expression of genes associated with several key cellular functions, including the interferon signaling pathway, during SARS-CoV-2 infection. Our data suggest that SARS-CoV-2 actively inhibits the RNase of autophosphorylated IRE1, perhaps as a strategy to eliminate detection by the host immune system. IMPORTANCESARS-CoV-2 is the third lethal respiratory coronavirus after MERS-CoV and SARS-CoV to emerge this century, causing millions of deaths world-wide. Other common coronaviruses such as HCoV-OC43 cause less severe respiratory disease. Thus, it is imperative to understand the similarities and differences among these viruses in how each interacts with host cells. We focused here on the inositol-requiring enzyme 1 (IRE1) pathway, part of the host unfolded protein response to virus-induced stress. We found that while MERS-CoV and HCoV-OC43 fully activate the IRE1 kinase and RNase activities, SARS-CoV-2 only partially activates IRE1, promoting its kinase activity but not RNase activity. Based on IRE1-dependent gene expression changes during infection, we propose that SARS-CoV-2 prevents IRE1 RNase activation as a strategy to limit detection by the host immune system.

microbiology↗

bioRxiv2021

Connectome-wide association analysis identified significant brain functional alteration in adults with attention-deficit/hyperactivity disorder

Adults with attention-deficit/hyperactivity disorder (ADHD), as an extreme-phenotype of ADHD, is still facing problems of inconsistency and undeciphered mechanisms for its neuropathology. To address this matter, our present study performed connecotome-wide voxel-based analyses with the resting-state fMRI data of 84 adults with ADHD and 89 healthy controls. We found that functional connectivity patterns of the left precuneus and the left middle temporal significantly altered in ADHD populations serving as potential neural biomarkers to distinguish ADHD with healthy controls, with subsequent seed-based analysis revealing the dysfunction of functional connections both intra- and inter-default mode and attention networks, among which middle temporal gyrus plays the key role of bridge linking the default mode and attention networks. After cognitive behavioral therapy, two of these ADHD-altered functional connections ameliorated accompanied with improvement of ADHD core symptoms. Additionally, imaging genetic analyses also revealed close relationships between the observed brain functional alterations and ADHD-risk genes. Taken together, our findings suggested the interference of default mode on attention networks in adults with ADHD, which would be severing as a potential biomarker for both ADHD pathogenesis and treatment effects.

neuroscience↗

bioRxiv2021

Regional Topological Aberrances of White Matter- and Gray Matter-based Functional Networks for Attention Processing may Foster Traumatic Brain Injury-Related Attention Deficits in Adults

Traumatic brain injury (TBI) is highly prevalent in adults. TBI-related functional brain alterations have been linked with common post-TBI neurobehavioral sequelae, with unknown neural sub-strates. This study examined the systems-level functional brain alterations in white matter (WM) and gray matter (GM) for visual sustained attention processing, their interactions, and contribution to post-TBI attention deficits. Task-based functional MRI data were collected from 42 adults with TBI and 43 group-matched normal controls (NCs), and analyzed using the graph theoretic tech-nique. Global and nodal topological properties were calculated and compared between the two groups. Correlation analyses were conducted between the neuroimaging measures that showed significant between-group differences and the behavioral symptom measures in attention domain in the groups of TBI and NCs, respectively. Significantly altered nodal efficiency and/or degree in several WM and GM nodes were reported in the TBI group, including the posterior corona radiata (PCR), posterior thalamic radiation (PTR), postcentral gyrus (PoG), and superior temporal sulcus (STS). Subjects with TBI also demonstrated abnormal systems-level functional synchronization between the PTR and STS in the right hemisphere, hypo-interaction between PCR and PoG in the left hemisphere; as well as the involvement of systems-level functional aberrances in PCR in TBI-related behavioral impairments in the attention domain. Findings of the current study suggest that TBI-related systems-level functional alterations associated with these two major association WM tracts and their anatomically connected GM regions may play critical role in TBI-related behavioral deficits in attention domain.

neuroscience↗

bioRxiv2021

Divergence and convergence of cortical encoding during word reading in bilinguals

Word reading includes a series of cognitive processes that convert low-level visual characteristics to neural representations. However, the consistency of the neural mechanisms for processing these cognitive components across different writing systems in bilinguals remains inconclusive. Here, we explored this question by employing representational similarity analysis with a semantic access task involving Chinese words, English words and Chinese pinyin. Distinct anatomical distribution patterns were detected for each type of brain representation across ideographic and alphabetic languages, resulting in 100% classification accuracy. Meanwhile, convergent cognitive components processing was found in the core language-related regions in left hemisphere, including the inferior frontal gyrus, temporal pole, superior and middle temporal gyrus, precentral gyrus and supplementary motor areas. Broadly, our findings indicated that the neural basis for word recognition of different writing systems in bilinguals was divergent in anatomical locations of neural representations for specialized processing but convergent in cognitive domains, which supported and enriched the assimilation-accommodation hypothesis. TeaserCortical encoding linguistic processing across languages was support by parallel interdigitated distributed networks but convergent in cognitive domains.

neuroscience↗

bioRxiv2021

Thalamic bursts modulate cortical synchrony locally to switch between states of global functional connectivity in a cognitive task

Performing a cognitive task requires going through a sequence of functionally diverse stages. Although it is typically assumed that these stages are characterized by distinct states of cortical synchrony that are triggered by sub-cortical events, little reported evidence supports this hypothesis. To test this hypothesis, we first identified cognitive stages in single-trial MEG data of an associative recognition task, showing with a novel method that each stage begins with local modulations of synchrony followed by a state of directed functional connectivity. Second, we developed the first whole-brain model that can simulate cortical synchrony throughout a task. The model suggests that the observed synchrony is caused by thalamocortical bursts at the onset of each stage, targeted at cortical synapses and interacting with the structural anatomical connectivity. These findings confirm that cognitive stages are defined by distinct states of cortical synchrony and explains the network-level mechanisms necessary for reaching stage-dependent synchrony states. Author summaryA novel machine-learning method was applied to unveil the dynamics of local and cortex-wide neural coordination underlying the fundamental cognitive processes involved in a memory task. To explain how neural activity - and ultimately behavior - was coordinated throughout the task, we developed a whole-brain model that incorporates cognitive mechanisms, anatomy, and neural biophysics. Similar models are used with resting state data, however, simulating a cognitive task remained elusive. The model showed that sub-cortical pulses at the onset of cognitive processes - as hypothesized by cognitive and neurophysiological theories - were sufficient to switch between the states of neural coordination observed. These findings have implications to understand goal-directed cognitive processing and the mechanisms to reach states of neural coordination.

neuroscience↗

bioRxiv2021

The Need for Transfer Learning in CRISPR-Cas Off-Target Scoring

MotivationThe scalable design of safe guide RNA sequences for CRISPR gene editing depends on the computational "scoring" of DNA locations that may be edited. As there is no widely accepted benchmark dataset to compare scoring models, we present a curated "TrueOT" dataset that contains thoroughly validated datapoints to best reflect the properties of in vivo editing. Many existing models are trained on data from high throughput assays. We hypothesize that such models may suboptimally transfer to the low throughput data in TrueOT due to fundamental biological differences between proxy assays and in vivo behavior. We developed new Siamese convolutional neural networks, trained them on a proxy dataset, and compared their performance against existing models on TrueOT. ResultsOur simplest model with a single convolutional and pooling layer surprisingly exhibits state-of-the-art performance on TrueOT. Adding subsequent layers improved performance on a proxy dataset while compromising performance on TrueOT. We demonstrate improved generalization on TrueOT with a Siamese model of higher complexity when we apply transfer learning techniques. These results suggest an urgent need for the CRISPR community to agree upon a benchmark dataset such as TrueOT and highlight that various sources of CRISPR data cannot be assumed to be equivalent. Availability and ImplementationOur code base and datasets are available on GitHub at github.com/baolab-rice/CRISPR_OT_scoring.

bioinformatics↗

bioRxiv2021

The entomopathogenic nematode Steinernema hermaphroditum is a self-fertilizing hermaphrodite and a genetically tractable system for the study of parasitic and mutualistic symbiosis

Entomopathogenic nematodes, including Heterorhabditis and Steinernema, are parasitic to insects and contain mutualistically symbiotic bacteria in their intestines (Photorhabdus and Xenorhabdus, respectively) and therefore offer opportunities to study both mutualistic and parasitic symbiosis. The establishment of genetic tools in entomopathogenic nematodes has been impeded by limited genetic tractability, inconsistent growth in vitro, variable cryopreservation, and low mating efficiency. We obtained the recently described Steinernema hermaphroditum strain CS34 and optimized its in vitro growth, with a rapid generation time on a lawn of its native symbiotic bacteria Xenorhabdus griffiniae. We developed a simple and efficient cryopreservation method. Previously, S. hermaphroditum isolated from insect hosts was described as first-generation hermaphroditic and second-generation gonochoristic. We discovered that CS34, when grown in vitro, produced consecutive generations of autonomously reproducing hermaphrodites accompanied by rare males. We performed mutagenesis screens in S. hermaphroditum that produced mutant lines with visible and heritable phenotypes. Genetic analysis of the mutants demonstrated that this species reproduces by self-fertilization rather than parthenogenesis and that its sex is determined chromosomally. Genetic mapping has thus far identified markers on the X chromosome and three of four autosomes. We report that S. hermaphroditum CS34 is the first consistently hermaphroditic entomopathogenic nematode and is suitable for genetic model development to study naturally occurring mutualistic symbiosis and insect parasitism.

genetics↗

bioRxiv2021

Abnormal Neurite Density and Orientation Dispersion in Frontal Lobe Link to Elevated Hyperactive/Impulsive Behaviors in Young Adults with Traumatic Brain Injury

Traumatic brain injury is a major public health concern. A significant proportion of individuals experience post-traumatic brain injury behavioral impairments, especially in attention and inhibitory control domains. Traditional diffusion-weighted MRI techniques, such as diffusion tensor imaging, have provided tools to assess white matter structural disruptions reflecting the long-term brain tissue alterations associated with traumatic brain injury. The recently developed neurite orientation dispersion and density imaging is a more advanced diffusion-weighted MRI modality, which provides more refined characterization of brain tissue microstructures by assessing the neurite orientation dispersion and neurite density properties. In this study, we investigated the morphometrical and microstructural alterations at chronic brain injury stage and their relationships with the functional outcomes. Neurite orientation dispersion and density imaging data from 44 young adults with chronic traumatic brain injury (ranging from 18 27 years of age; 23 males/21 females) who had no prior-traumatic brain injury history of attention deficits and/or hyperactivity and 45 group-matched normal controls (23 males /22 females) were collected. Maps of fractional anisotropy, neurite orientation dispersion index, and neurite density index were calculated. Vertex-wise and voxel-wise analyses were conducted for gray matter and white matter, respectively. Post-hoc region of interest-based analyses were also performed. Compared to the controls, the group of traumatic brain injury showed significantly increased orientation dispersion index in various gray matter regions and significantly decreased orientation dispersion index in several white matter regions. Brain-behavioral association analyses indicated that the reduced neurite density index of left precentral gyrus and the reduced orientation dispersion index of left superior longitudinal fasciculus were significantly associated with elevated hyperactive/impulsive symptoms in the patients with traumatic brain injury. These findings suggest that traumatic brain injury-induced chronic neurite orientation dispersion alterations of left superior longitudinal fasciculus and left precentral may significantly contribute to post-traumatic brain injury hyperactive/impulsive behaviors in young adults with traumatic brain injury.

neuroscience↗

bioRxiv2021

Deep Learning-Based Phenotyping of Breast Cancer Cells Using Lens-free Digital In-line Holography

Lens-free digital in-line holography (LDIH) offers a wide field of view at micrometer-scale resolution, surpassing the capabilities of lens-based microscopes, making it a promising diagnostic tool for high-throughput cellular analysis. However, the complex nature of holograms renders them challenging for human interpretation, necessitating time- consuming computational processing to reconstruct object images. To address this, we present HoloNet, a novel deep learning architecture specifically designed for direct analysis of holographic images from LDIH in cellular phenotyping. HoloNet extracts both global features from diffraction patterns and local features from convolutional layers, achieving superior performance and interpretability compared to other deep learning methods. By leveraging raw holograms of breast cancer cells stained with well-known markers ER/PR and HER2, HoloNet demonstrates its effectiveness in classifying breast cancer cell types and quantifying molecular marker intensities. Furthermore, we introduce the feature-fusion HoloNet model, which extracts diffraction features associated with breast cancer cell types and their marker intensities. This hologram embedding approach allows for the identification of previously unknown subtypes of breast cancer cells, facilitating a comprehensive analysis of cell phenotype heterogeneity, leading to precise breast cancer diagnosis.

bioinformatics↗

bioRxiv2021

The receptor kinase SRF3 coordinates iron-level and flagellin dependent defense and growth responses in plants

Iron is critical for host-pathogen interactions. While pathogens seek to scavenge iron to spread, the host aims at decreasing iron availability to reduce pathogen virulence. Thus, iron sensing and homeostasis are of particular importance to prevent host infection and part of nutritional immunity. While the link between iron homeostasis and immunity pathways is well established in plants, how iron levels are sensed and integrated with immune response pathways remain unknown. We identified a receptor kinase, SRF3 coordinating root growth, iron homeostasis and immunity pathways via regulation of callose synthase activity. These processes are modulated by iron levels and rely on SRF3 extracellular and kinase domain which tune its accumulation and partitioning at the cell surface. Mimicking bacterial elicitation with the flagellin peptide flg22 phenocopies SRF3 regulation upon low iron levels and subsequent SRF3-dependent responses. We propose that SRF3 is part of nutritional immunity responses involved in sensing external iron levels.

plant biology↗

bioRxiv2021

GAT-FD: An Integrated MATLAB Toolbox for Graph Theoretical Analysis of Task-Related Functional Dynamics

Functional connectivity (FC) has been demonstrated to be varying over time during sensory and cognitive processes. Quantitative examinations of such variations can significantly advance our understanding on large-scale functional organizations and their topological dynamics that support normal brain functional connectome and can be altered in individuals with brain disorders. However, toolboxes that integrate the complete functions for analyzing task-related brain FC, functional network topological properties, and their dynamics, are still lacking. The current study has developed a MATLAB toolbox, the Graph Theoretical Analysis of Task-Related Functional Dynamics (GAT-FD), which consists of four modules for sliding-window analyses, temporal mask generation, estimations of network properties and dynamics, and result display, respectively. All the involved functions have been tested and validated using fMRI data collected from human subjects when performing a block-designed task. The results demonstrated that the GAT-FD allows for effective and quantitative evaluations of the functional network properties and their dynamics during the task period. As an open-source and user-friendly package, the GAT-FD and its detailed user manual are freely available at https://www.nitrc.org/projects/gat_fd and https://centers.njit.edu/cnnl/gat_fd/.

neuroscience↗

bioRxiv2021

Chemical ecology of a tripartite symbiosis

Microbial symbiotic interactions, mediated by small molecule signaling, drive physiological processes of higher order systems. Metabolic analytic technologies advancements provide new avenues to examine how chemical ecology, or conversion of existing biomass to new forms, changes over a symbiotic lifecycle. We examine such processes using the tripartite relationship between nematode host Steinernema carpocapsae, its obligate mutualist bacterium, Xenorhabdus nematophila, and the insects they infect together. We integrate trophic, metabolomics, and gene regulation analyses to understand insect biomass conversion to nematode or bacterium biomass. Trophic analysis established bacteria as the primary insect consumers, with nematodes at trophic position 4.37, indicating consumption of bacteria and likely other nematodes. Significant, discrete metabolic phases were distinguishable from each other, indicating the insect chemical environment changes reproducibly during bioconversion. Tricarboxylic acid cycle components and amino acids were significantly affected throughout infection. These findings contribute to an ongoing understanding of how symbiont associations shape chemical environments. TeaserEntomopathogenic nematodes act as an apex predator in some ecosystems through altering chemical environments of their prey.

microbiology↗

bioRxiv2021

Modulations of local synchrony over time lead to resting-state functional connectivity in a parsimonious large-scale brain model

Biophysical models of large-scale brain activity are a fundamental tool for understanding the mechanisms underlying the patterns observed with neuroimaging. These models combine a macroscopic description of the within- and between-ensemble dynamics of neurons within a single architecture. A challenge for these models is accounting for modulations of within-ensemble synchrony over time. Such modulations in local synchrony are fundamental for modeling behavioral tasks and resting-state activity. Another challenge comes from the difficulty in parametrizing large scale brain models which hinders researching principles related with between-ensembles differences. Here we derive a parsimonious large scale brain model that can describe fluctuations of local synchrony. Crucially, we do not reduce within-ensemble dynamics to macroscopic variables first, instead we consider within and between-ensemble interactions similarly while preserving their physiological differences. The dynamics of within-ensemble synchrony can be tuned with a parameter which manipulates local connectivity strength. We simulated resting-state static and time-resolved functional connectivity of alpha band envelopes in models with identical and dissimilar local connectivities. We show that functional connectivity emerges when there are high fluctuations of local and global synchrony simultaneously (i.e. metastable dynamics). We also show that for most ensembles, leaning towards local asynchrony or synchrony correlates with the functional connectivity with other ensembles, with the exception of some regions belonging to the default-mode network. Author summaryHere we present and evaluate a parsimonious model of large-scale brain activity. The model represents the brain as a network-of-networks structure. The sub-networks describe the neural activity within a brain region, and the global network encodes interactions between brain regions. Unlike other models, it capture progressive changes of local synchrony and local dynamics can be tuned with one parameter. Therefore the model could be used not only to model resting-state, but also behavioural tasks. Furthermore, we describe a simple framework that can deal with the arduous task of identifying global and local parameters.

neuroscience↗

bioRxiv2021

A multimodal metabolomics approach to elucidate the trigger components of rumen fluid for larval exsheathment in a model gastrointestinal parasitic nematode, Haemonchus contortus.

From an animal production and health perspective, our understanding of the metabolites in ruminant biofluids, particularly rumen fluid across different host species is poorly understood. Metabolomics is a powerful and sensitive approach for investigating low molecular weight metabolite profiles present in rumen biofluids. It can be used to identify potential roles of metabolites in the rumen microbiome and provide and understanding of host-level regulatory mechanisms associated with animal production. The rumen is a strictly anaerobic environment enriched with a complex community of bacteria, protozoa, fungi, archaea and bacteriophages. Here, we present a metabolomic dataset generated using hydrophilic interaction liquid chromatography (HILIC) and semi-polar (C18) chromatography methods coupled to high resolution mass spectrometry (MS), collected in both positive and negative ionization modes, of ovine rumen samples that were fractionated based on molecular weight (20 kDa, 8-10 kDa and 100 Da). This study highlights the potential of HILIC and C18 chromatography combined with non-targeted mass spectrometric methods to detect the polar and semi-polar metabolite species of the ruminal fluid metabolome.

molecular biology↗

bioRxiv2020

Presynaptic autophagy is coupled to the synaptic vesicle cycle via ATG-9

Autophagy is a cellular degradation pathway essential for neuronal health and function. Autophagosome biogenesis occurs at synapses, is locally regulated and increases in response to neuronal activity. The mechanisms that couple autophagosome biogenesis to synaptic activity remain unknown. In this study we determine that trafficking of ATG-9, the only transmembrane protein in the core autophagy pathway, links the synaptic vesicle cycle with autophagy. ATG-9 positive vesicles in C. elegans are generated from the trans-Golgi network via AP3-dependent budding, and delivered to presynaptic sites. At presynaptic sites, ATG-9 undergoes exo-endocytosis in an activity-dependent manner. Mutations that disrupt endocytosis, including one associated with Parkinsons disease, result in abnormal ATG-9 accumulation at clathrin-rich synaptic foci and defects in activity-dependent presynaptic autophagy. Our findings uncover regulated key steps of ATG-9 trafficking at presynaptic sites, and provide evidence that ATG-9 exo-endocytosis couples autophagosome biogenesis at presynaptic sites with the activity-dependent synaptic vesicle cycle. HighlightsO_LIIn C. elegans, ATG-9 is delivered to presynaptic sites in vesicles generated from the trans-Golgi network via AP-3-dependent budding C_LIO_LIATG-9 vesicles undergo activity-dependent exo-endocytosis at presynaptic sites C_LIO_LIMutations in endocytic proteins, including a mutation associated with Parkinsons disease, result in abnormal ATG-9 accumulation at clathrin-rich foci C_LIO_LIAbnormal accumulation of ATG-9 at clathrin-rich foci is associated with defects in activity-dependent presynaptic autophagy C_LI

neuroscience↗

bioRxiv2020

Temporal trait plasticity and neighborhood crowding predict the growth of tropical trees

Functional traits and neighborhood composition have been used to predict tree growth dynamics. Temporal changes in trait values (temporal trait plasticity) is one of the mechanisms for adaptive plastic response to environmental change. However, the consequence of temporal change in trait values and neighborhoods on the growth performance of individuals has rarely been investigated. We, therefore tested the effect of temporal changes in trait values and neighborhood crowding on the growth rate of individuals in a tropical forest using a dataset containing individual level growth and functional trait data for Ficus individuals. We collected trait and size data at two time points (2010 and 2017) for 472 individuals of 15 Ficus species in Xishuangbanna tropical forest dynamics plot, southwest China. We used linear mixed effect model to predict the effect of temporal trait plasticity and neighborhood crowding on the relative growth rate of individuals using these data. We found significant temporal changes in individuals functional traits suggesting a shift in ecological strategies from being functionally acquisitive to conservative. We also found differences in neighborhood crowding between the two census years indicating that the strength of individual interactions might change over time. The temporal changes in trait values and neighborhood crowding were found to predict better the relative growth rate of individuals, compared to static trait or crowding values in the initial and final censuses. We also found major axes of tree functional strategies in a principal component analysis, highlighting potentially adaptive trait differences. Our results in general highlight to consider the temporal dimension of functional traits and biotic interactions, as our result suggest that growth-trait relationships may vary between time points, allowing us to understand the demographic response of species to temporal environmental change.

ecology↗

bioRxiv2020

Species packing and the latitudinal gradient in local beta-diversity

The decline in species richness at higher latitudes is among the most fundamental patterns in ecology. Whether changes in species composition across space (beta-diversity) contribute to this gradient of overall species richness (gamma-diversity) remains hotly debated. Previous studies that failed to resolve the issue suffered from a well-known tendency for small samples in areas with high gamma-diversity to have inflated measures of beta-diversity. Here, we provide here a novel analytical test, using beta-diversity metrics that correct the gamma-diversity and sampling biases, to compare beta-diversity and species packing across a latitudinal gradient in tree species richness of 21 large forest plots along a large environmental gradient in East Asia. We demonstrate that after accounting for topography and correcting the gamma-diversity bias, tropical forests still have higher beta-diversity than temperate analogs. This suggests that beta-diversity contributes to the latitudinal species richness gradient as a component of gamma-diversity. Moreover, both niche specialization and niche marginality (a measure of niche spacing along an environmental gradient) also increase towards the equator, after controlling for the effect of topographic heterogeneity. This supports the joint importance of tighter species packing and larger niche space in tropical forests while also demonstrating the importance of local processes in controlling beta-diversity.

ecology↗