Biology subjects

Erickson, A.

Publications and source records attributed to Erickson, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Palmitate-activated IRE1-XBP1 signaling limits DNA damage and is associated with H2A.X-linked DNA damage response transcripts in triple-negative breast cancer cells

Palmitate-associated lipotoxic stress activates the endoplasmic-reticulum stress sensor protein IRE1, but how IRE1 signaling influences genotoxic-stress responses in triple-negative breast cancer remains unclear. Here, we investigated IRE1 and XBP1 signaling in MDA-MB-231 cells exposed to palmitate and etoposide. Under combined lipotoxic and genotoxic stress, XBP1 depletion increased DNA-damage accumulation in IRE1 wild-type cells but not in IRE1-deficient cells, whereas IRE1 re-expression reduced DNA damage. Pharmacologic IRE1 RNase inhibition also increased etoposide-associated DNA damage, supporting a protective role for IRE1 RNase-dependent signaling. IRE1 status and XBP1 manipulation differentially affected H2A.X and {gamma}H2A.X abundance, indicating context-dependent regulation of chromatin-associated DNA-damage signaling. At the RNA level, H2A.X was enriched in IRE1 immunoprecipitates, and the H2A.X-linked DNA-damage-response transcripts HUWE1 and BRCA2 also associated with IRE1 under combined stress. These findings link palmitate-activated IRE1-XBP1 signaling to genome-protective responses during genotoxic stress and identify a network of IRE1-associated DNA-damage-response transcripts in triple-negative breast cancer cells. Direct IRE1-mediated cleavage of these transcripts remains to be established.

cancer biology↗

bioRxiv2026

A Framework for NGN1-Induced Sensory Neuron Differentiation for Disease Modelling and Drug Screening

Background: Neuropathic pain is a burdensome, difficult-to-treat, and highly heterogeneous condition with limited therapeutic options, underscoring the need for robust and reproducible human disease models. Human induced pluripotent stem cell (iPSC)-derived sensory neurons provide a promising platform for patient specific disease modelling and drug screening; however, their translational use is hampered by variability in differentiation efficiency, cellular composition, and functional maturation across protocols and cell lines. Methods: Here, we present a standardized and potentially scalable framework for NGN1 driven differentiation of human iPSCs into sensory neurons. Building on a previously published two step protocol (1), we systematically deconstructed and optimized each stage of differentiation across a large panel of genetically diverse iPSC lines. Results: We identified robust parameters for neural crest like cell (NCLC) generation, established a flow cytometry-based quality control strategy for NCLCs, and defined optimal combinations of seeding density and lentiviral multiplicity of infection to maximize sensory neuron progenitor yield. To improve culture homogeneity, we compared antimitotic selection strategies and demonstrated that tightly timed Ara-C treatment combined with low progenitor seeding density yields consistently pure sensory neuron cultures. We further evaluated maturation under physiologically relevant glucose conditions and performed a systematic review of media compositions to derive two defined maturation media. Morphological, immunocytochemical, transcriptomic, and electrophysiological analyses revealed that time in culture is a major determinant of maturation, while specific supplements such as prostaglandin E2; (PGE2) selectively enhance transcriptional signatures associated with nociceptor identity without substantially altering global network activity. Bulk RNA sequencing demonstrated broad expression of sensory neuron and pain related markers and gene programs across conditions, with long term maturation and PGE2; treatment showing the highest similarity to human dorsal root ganglion reference data. Functional assessment using multi electrode arrays enabled the detection of donor specific electrophysiological phenotypes, including reproducible hyperexcitability in small fiber neuropathy patient derived lines. Conclusions: This study establishes a modular, reproducible NGN1 based differentiation workflow with integrated quality checkpoints that accommodates iPSC line to line variability. The framework provides a practical foundation for translational sensory neuron research, patient specific disease modelling, and scalable drug screening applications.

neuroscience↗

bioRxiv2026

Highly resolved tumor architecture via matched spatial and nucleus transcriptomics from a single tissue section

Spatial transcriptomics often relies on reference-based deconvolution to infer cell types in a tissue context; however, public single-cell datasets can miss patient-specific biology. Here we introduce SIMPlex, a method that generates matched spatial and single-nucleus gene-expression profiles from the same 5 um FFPE section. We demonstrate context-matched profiles across mouse brain, breast cancer and prostate cancer tissues, resolving fine-grained cell-states with distinct spatial signatures. By extracting both spatial and nuclear layers, SIMPlex maximises the information recovered from a single tissue section, an advantage for scarce archival and clinical specimens.

molecular biology↗

bioRxiv2026

Spatial mapping of pediatric brain tumors across diagnoses and relapses

We present a spatial transcriptomic atlas of 19 pediatric brain tumor patients spanning nine major and rare diagnoses, including seven relapses, revealing their spatial cellular and molecular organization. Each tumor section resolves into 2 - 4 recurrent spatial archetypes across 11 biological themes, with some mirroring developmental lineage patterns - for example, oligodendrocyte-lineage programs in pilocytic astrocytomas. Spatially inferred copy-number analysis identifies relapse-associated putative clones. In one rare embryonal tumor, spatial niches in the primary tumor harboring putative clones colocalized with an archetype enriched for nervous system development and glioblast-lineage programs. In one ependymoma and one pilocytic astrocytoma, relapse-associated putative clones preferentially localized to the vasculature, suggesting regrowth during relapse may be seeded by clonal selection of residual tumor cells within specialized microenvironmental niches. This resource provides an open-access spatially resolved map via an interactive viewer to inform research on pediatric brain tumor ecosystems, relapse biology, and therapeutic strategies.

cancer biology↗

bioRxiv2026

RISOP, a Reference-Assisted Approach for Enhanced Identification of Oxidized Phospholipids

Oxidized phospholipids (OxPLs) play critical roles in inflammation, ferroptosis, and other oxidative stress-associated processes, yet their systematic characterization in biological systems remains a major analytical challenge owing to their low abundance and vast structural diversity. Here we report RISOP (Reference-Assisted Identification of Sample-specific Oxidized Phospholipids), an untargeted LC-MS/MS workflow that leverages chemically enriched OxPL reference pools to substantially improve OxPL annotation. Reference pools encompassing diverse oxidative modifications and a wide abundance range were experimentally generated using Fenton reaction and H2O2 treatment, providing broad coverage of OxPLs. Reference-assisted integrative analysis yielded a more than twofold increase in identified OxPL species in biological samples under elevated oxidative stress, as demonstrated in ML210-treated cells, a model of ferroptotic stress. We further show that the widely used BODIPY C11 lipid peroxidation probe captures cellular oxidative burden in only a subset of OxPLs identified by RISOP, highlighting the importance of untargeted, comprehensive OxPL profiling. Overall, RISOP provides a versatile platform readily applicable to other classes of oxidized complex lipids for comprehensive characterization in physiological and pathological contexts. Abstract Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/728773v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@482111org.highwire.dtl.DTLVardef@173126corg.highwire.dtl.DTLVardef@1be7238org.highwire.dtl.DTLVardef@3cf7f2_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

Clinical cure of chronic hepatitis B is dependent on activation and perpetuation of robust CD4+ T cell responses

Chronic infection with hepatitis B virus (HBV), a major global pathogen, often leads to immune-mediated progressive liver injury and liver cancer. While seroclearance of the surface antigen (HBsAg) defines clinical cure and reduces disease-associated risks, HBsAg clearance is rarely observed and remains therapeutically elusive. Here we overcome some of the challenges to studying immune mechanisms of HBsAg clearance in chronic hepatitis B (CHB) using our mouse model of age-dependent HBsAg clearance and persistence, and samples from our BeNEG-DO clinical trial that provided longitudinal PBMCs from patients who either cleared HBsAg or retained stable HBsAg levels after stopping nucleos(t)ide analog therapy. We show that young mice fail to clear HBsAg and have impaired ability to efficiently initiate and sustain HBV-specific CD4+ T cell responses. We also demonstrate a role for CD4+ T cells in hepatic leukocyte organization and cytotoxicity, and in HBV-specific CD8+ T cell cytotoxicity and HBsAg clearance. Upstream of the CD4+ T cell response, we reveal that hepatic dendritic cells, particularly cDC2s, direct effective CD4+ T cell activation and differentiation. Studies in CHB patients identified immune features of HBsAg clearance that overlap with the mouse model, including TH1 and cytotoxic CD4+ T cell activation and CD8+ T cell cytotoxic effector function. These findings identify an essential role for potent CD4+ T cell activation in the clinical cure of CHB and illuminate potential immunotherapeutic targets for enhancing CD4+ T cell responses to achieve greater HBsAg clearance rates. One Sentence SummaryUsing a mouse model of hepatitis B and longitudinal PBMCs from patients with chronic hepatitis B, we identify shared mechanisms of HBsAg seroclearance.

immunology↗

bioRxiv2024

The pseudoknot structure of a viral RNA reveals a conserved mechanism for programmed exoribonuclease resistance

Exoribonuclease-resistant RNAs (xrRNAs) are viral RNA structures that block degradation by cellular 5'-3' exoribonucleases to produce subgenomic viral RNAs during infection. Initially discovered in flaviviruses, xrRNAs have since been identified in wide range of RNA viruses, including those that infect plants. High sequence variability among viral xrRNAs raises questions about the shared molecular features that characterize this functional RNA class. Here, we present the first structure of a plant-virus xrRNA in its active exoribonuclease-resistant conformation. The xrRNA forms a 9 base pair pseudoknot that creates a knot-like topology similar to that of flavivirus xrRNAs, despite lacking sequence similarity. Biophysical assays confirm a compact pseudoknot structure in solution, and functional studies validate its relevance both in vitro and during infection. Our study reveals how viral RNAs achieve a common functional outcome through highly divergent sequences and identifies the knot-like topology as a defining feature of xrRNAs.

biochemistry↗

bioRxiv2023

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of heterogeneity on genomic signature scoring

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx(R), Decipher(R), Prostadiag(R)) using a step-wise approach increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses. Patient summaryProstate cancers are very variable, including within a single tumour. Current genetic scoring systems, which are sometimes used to make decisions for how to treat patients with prostate cancer, are based on sampling methods which do not reflect these variations. We found, using state-of-the-art spatial genetic technology to simulate accurate assessment of variation in biopsies, that the current approaches miss important details which could negatively impact clinical decisions. Take home messageVirtual biopsies from spatial transcriptomic analysis of a whole prostate reveal that current genomic risk scores potentially deliver misleading results as they are based on bulk analysis of prostate biopsies and ignore tumour heterogeneity.

genomics↗

bioRxiv2023

Clonal phylogenies inferred from bulk, single cell, and spatial transcriptomic analysis of cancer

Epithelial cancers are typically heterogeneous with primary prostate cancer being a typical example of histological and genomic variation. Prostate cancer is the second most common male cancer in western industrialized countries. Prior studies of primary prostate cancer tumor genetics revealed extensive inter and intra-patient tumor heterogeneity. Recent advances have enabled extensive single-cell and spatial transcriptomic profiling of tissue specimens. The ability to resolve accurate prostate cancer tumor phylogenies at high spatial resolution would provide tools to address questions in tumorigenesis, disease progression, and metastasis. Recent advances in machine learning have enabled the inference of ground-truth genomic single-nucleotide and copy number variant status from transcript data. The inferred SNV and CNV states can be used to resolve clonal phylogenies, however, it is still unknown how faithfully transcript-based tumor phylogenies reconstruct ground truth DNA-based tumor phylogenies. We sought to study the accuracy of inferred-transcript to recapitulate DNA-based tumor phylogenies. We first performed in-silico comparisons of inferred and directly resolved SNV and CNV status, from single cancer cells, from three different cell lines. We found that inferred SNV phylogenies accurately recapitulate DNA phylogenies (entanglement = 0.097). We observed similar results in iCNV and CNV based phylogenies (entanglement = 0.11). Analysis of published prostate cancer DNA phylogenies and inferred CNV, SNV and transcript based phylogenies demonstrated phylogenetic concordance. Finally, a comparison of pseudo-bulked spatial transcriptomic data to adjacent sections with WGS data also demonstrated recapitulation of ground truth (entanglement = 0.35). These results suggest that transcript-based inferred phylogenies recapitulate conventional genomic phylogenies. Further work will need to be done to increase accuracy, genomic, and spatial resolution.

bioinformatics↗

bioRxiv2022

IRF7 impacts on prostate cancer cell survival in response to radiation

Understanding the impact of radiotherapy on the evolution of treatment resistant prostate cancer is critical for selecting effective treatment combinations. Whilst activation of Type 1 interferon signalling is a hallmark of how cells respond to viral infection, in cancer cells, multiple stresses are known to activate this same response. In this study we have evaluated for the first time the changes in the interferon response induced by culturing prostate cancer cells under sphere- forming conditions and following irradiation. We report a conserved upregulated transcript profile for both conditions that is strongly associated with therapeutic resistance and cell survival in vitro and in vivo. The profile includes and is regulated by the Type 1 interferon master regulator IRF7 which, when depleted, delays tumour re-growth following irradiation. We immuno-stained two independent prostate cohorts for IRF7 and found that increased expression, particularly in cases with low PTEN expression, correlated with poor prognosis. To more comprehensively characterise the impact of IRF7 and radiation on cells, RNA-Seq was performed on IRF7 knockdown cells at different radiation doses. We identified a number of biological processes that were IRF7-dependent, including the formation of stem-like cell populations and also therapeutic vulnerabilities. For example, irradiation sensitised surviving cells to either a combination of an IKK{varepsilon}/TBK1 and a MEK inhibitor or treatment with an inhibitor of IDO1, an IRF7- dependent gene. Translationally our work suggests that IRF7 expression can be used to stratify patients who may not benefit from receiving radiotherapy alone but rather may benefit from treatment combinations. In two cohorts treated with radical intent, strong IRF7 staining was associated with disease-specific death implicating this pathway as a convergence point for therapeutic resistance in prostate and potentially other cancer types.

cancer biology↗

bioRxiv2022

A branching model of cell fate decisions in the enteric nervous system

How neurogenesis and gliogenesis are coordinated during development and why mature glial cells often share properties with neuroectodermal progenitors remains unclear. Here, we have used single cell RNA sequencing to map the regulatory landscape of neuronal and glial differentiation in the mammalian enteric nervous system (ENS). Our analysis indicates that neurogenic trajectories branch directly from a linear gliogenic axis defined by autonomic neural crest cells adopting sequential states as they progressively lose their strong neurogenic bias and acquire properties of adult enteric glia. We identify gene modules associated with transcriptional programs driving enteric neurogenesis and cell state transitions along the gliogenic axis. By comparing the chromatin accessibility profile of autonomic neural crest and adult enteric glia we provide evidence that the latter maintain an epigenetic memory of their neurogenic past. Finally, we demonstrate that adult enteric glia maintain neurogenic potential and are capable of generating enteric neurons in certain contexts by activating transcriptional programs employed by early ENS progenitors. Our studies uncover a novel configuration of enteric neurogenesis and gliogenesis that enables the coordinate development of ENS lineages and provides a mechanistic explanation for the ability of enteric glia to be functionally integrated into the adult intestine and simultaneously maintain attributes of early ENS progenitors.

neuroscience↗

bioRxiv2022

Proteomics profiling reveals regulation of immune response to Salmonella Typhimurium infection in mice

Regulation of the immune response to Salmonella typhimurium (S. Typhimurium) infection is a complex process, influenced by genetic and environmental factors. Different inbred mouse strains show distinct levels of resistance to S. Typhimurium infection, ranging from susceptible (e.g., C57BL/6J) to resistant (e.g., DBA/2J) strains. However, the underlying molecular mechanisms contributing to the host response remain elusive. In this study, we present a comprehensive proteomics profiling of the spleen tissue from C57BL/6J and DBA/2J strains with different doses of S. Typhimurium infection by tandem tag mass coupled with two-dimensional liquid chromatography-tandem mass spectrometry. We identified and quantified 3,986 proteins, resulting in 475 differentially expressed proteins between C57BL/6J and DBA/2J strains. Functional enrichment analysis revealed that the mechanisms of innate immune responses to S. Typhimurium infection are associated with several signaling pathways, including the interferon signaling pathway. Our proteomic data also discovered a plausible gene in a genomic region that control different levels of resistance to S. Typhimurium infection. We further revealed the roles of macrophage cells and pro-inflammatory cytokines in the mechanisms under the natural resistance to S. Typhimurium. In summary, our results provide new insights into the genetic regulation of the immune response to S. Typhimurium infection in mice. Author SummarySalmonella infection (salmonellosis) is a common zoonotic disease that mainly propagates through contaminated food and drink. Various mouse strains display prominent disparities in responses to Salmonella invasion. Elucidating the heterogeneous immune reactions between different mouse strains can shed light on the fundamental molecular mechanisms of the innate immune system. Here, we employed a combination of proteomics and systems biology approaches to provide an unprecedented panorama of the inextricably interlaced immune signaling pathways in response to Salmonella infection in mice. Our results revealed the dynamics of cell signaling molecules elicited by inflammation and established new connections among them. We also identified a new candidate gene involved in the combat with pathogens. Our proteomic data and results contribute to understanding the intricate interactions of immune responses to Salmonella infection from molecular to systemic levels.

immunology↗

bioRxiv2021

SMAP: A pipeline for sample matching in proteogenomics

Integration of genomics and proteomics (proteogenomics) offers unprecedented promise for in-depth understanding of human diseases. However, sample mix-up is a pervasive, recurring problem, due to complex sample processing in proteogenomics. Here we present a pipeline for Sample Matching in Proteogenomics (SMAP) for verifying sample identity to ensure data integrity. SMAP infers sample-dependent protein-coding variants from quantitative mass spectrometry (MS), and aligns the MS-based proteomic samples with genomic samples by two discriminant scores. Theoretical analysis with simulation data indicates that SMAP is capable of uniquely match proteomic and genomic samples, when [≥]20% genotypes of individual samples are available. When SMAP was applied to a large-scale proteomics dataset from 288 biological samples generated by the PsychENCODE BrainGVEX project, we identified and corrected 18.8% (54/288) mismatched samples. The correction was further confirmed by ribosome profiling and assay for transposase-accessible chromatin sequencing data from the same set of samples. Thus our results demonstrate that SMAP is an effective tool for sample verification in a large-scale MS-based proteogenomics study. The source code, manual, and sample data of the SMAP are publicly available at https://github.com/UND-Wanglab/SMAP, and a web-based SMAP can be accessed at https://smap.shinyapps.io/smap/.

bioinformatics↗

bioRxiv2021

Liver Organoid and T Cell Coculture Models Cytotoxic T Cell Responses against Hepatitis C Virus

Hepatitis C virus (HCV) remains a global public health challenge with an estimated 71 million people chronically infected, with surges in new cases and no effective vaccine. New methods are needed to study the human immune response to HCV since in vivo animal models are limited and in vitro cancer cell models often show dysregulated immune and proliferative responses. Here we developed a CD8+ T cell and adult stem cell liver organoid system using a microfluidic chip to coculture 3D human liver organoids embedded in extracellular matrix with HLA-matched primary human T cells in suspension. We then employed automated phase contrast and immunofluorescence imaging to monitor T cell invasion and morphological changes in the liver organoids. This microfluidic coculture system supports targeted killing of liver organoids when pulsed with a peptide specific for HCV nonstructural protein 3 (NS3) (KLVALGINAV) in the presence of patient-derived CD8+ T cells specific for KLVALGINAV. This demonstrates the novel potential of the coculture system to molecularly study adaptive immune responses to HCV in an in vitro setting using primary human cells.

immunology↗

bioRxiv2021

The spatial landscape of clonal somatic mutations in benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

genomics↗

bioRxiv2019

Time resolved quantitative phosphoproteomics reveals distinct patterns of SHP2 dependence in EGFR signaling

SHP2 is a protein tyrosine phosphatase that normally potentiates intracellular signaling by growth factors, antigen receptors, and some cytokines; it is frequently mutated in childhood leukemias and other cancers. Here, we examine the role of SHP2 in the responses of breast cancer cells to EGF by monitoring phosphoproteome dynamics when SHP2 is allosterically inhibited by the small molecule SHP099. Data on phosphotyrosine abundance at more than 400 tyrosine residues reveals six distinct response signatures following SHP099 treatment and washout. These include putative substrate sites with increased phosphotyrosine abundance at early or late timepoints, and another class of sites that shows reduced phosphotyrosine abundance when SHP099 is present. Sites of decreased phospho-abundance are enriched on proteins with two nearby phosphotyrosine residues, which can be directly protected from dephosphorylation by the paired SH2 domains of SHP2 itself. These findings highlight how analysis of phosphoproteomic dynamics can provide insight into transmembrane signaling responses.

cell biology↗

bioRxiv2019

PP2A inhibitor PME-1 suppresses anoikis, and is associated with therapy relapse of PTEN-deficient prostate cancers

While organ-confined PCa is mostly therapeutically manageable, metastatic progression of PCa remains an unmet clinical challenge. Resistance to anoikis, a form of cell death initiated by cell detachment from the surrounding extracellular matrix, is one of the cellular processes critical for PCa progression towards aggressive disease. Therefore, further understanding of anoikis regulation in PCa might provide therapeutic opportunities. Here, we discover that PCa tumors with concomitantly compromised function of two tumor suppressor phosphatases, PP2A and PTEN, are particularly aggressive, having less than 50% 5-year secondary-therapy free patient survival. Functionally, overexpression of PME-1, a PP2A inhibitor protein, inhibits anoikis in PTEN-deficient PCa cells. In vivo, PME-1 inhibition increased apoptosis in in ovo PCa tumor xenografts, and attenuated PCa cell survival in zebrafish circulation. Molecularly, PME-1 deficient PCa cells display increased trimethylation at lysines 9 and 27 of histone H3 (H3K9me3 and H3K27me3), a phenotype corresponding to increased apoptosis sensitivity. In summary, we discover that PME-1 overexpression supports anoikis resistance in PTEN-deficient PCa cells. Clinically, the results identify PME-1 as a candidate biomarker for a subset of particularly aggressive PTEN-deficient PCa.

cancer biology↗

bioRxiv2018

Implementation of the Perfect Plasticity Approximation with biogeochemical compartments in R

Modeling forest ecosystems is a landmark challenge in science, due to the complexity of the processes involved and their importance in predicting future planetary conditions. While there are a number of open-source forest biogeochemistry models, few papers exist detailing the software development approach used to develop these models. This has left many forest biogeochemistry models large, opaque, and/or difficult to use, typically implemented in compiled languages for speed. Here, we present a forest biogeochemistry model from the SORTIE-PPA class of models, PPA-SiBGC. Our model is based on the Perfect Plasticity Approximation with simple biogeochemistry compartments and uses empirical vegetation dynamics rather than detailed prognostic processes to drive the estimation of carbon and nitrogen fluxes. This allows our model to be used with traditional forest inventory data, making it widely applicable and simple to parameterize. We detail the conceptual design of the model as well as the software implementation in the R language for statistical computing. Our aim is to provide a useful tool for the biogeochemistry modeling community that demonstrates the importance of vegetation dynamics in biogeochemical models.

ecology↗