Divergence Estimates Research Articles

Robustness of Divergence Time Estimation Despite Gene Tree Estimation Error: A Case Study of Fireflies (Coleoptera: Lampyridae).

Genomic data has become ubiquitous in phylogenomic studies, including divergence time estimation, but provide new challenges. These challenges include, amongst others, biological gene tree discordance, methodological gene tree estimation error, and computational limitations on performing full Bayesian inference under complex models. In this study, we use a recently published firefly (Coleoptera: Lampyridae) anchored hybrid enrichment dataset (AHE; 436 loci for 88 Lampyridae species and 10 outgroup species) as a case study to explore gene tree estimation error and the robustness of divergence time estimation. First, we explored the amount of model violation using posterior predictive simulations because model violations are likely to bias phylogenetic inferences and produce gene tree estimation error. We specifically focused on missing data (either uniformly distributed or systematically) and the distribution of highly variable and conserved sites (either uniformly distributed or clustered). Our assessment of model adequacy showed that standard phylogenetic substitution models are not adequate for any of the 436 AHE loci. We tested if the model violations and alignment errors resulted indeed in gene tree estimation error by comparing the observed gene tree discordance to simulated gene tree discordance under the multispecies coalescent model. Thus, we show that the inferred gene tree discordance is not only due to biological mechanism but primarily due to inference errors. Lastly, we explored if divergence time estimation is robust despite the observed gene tree estimation error. We selected four subsets of the full AHE dataset, concatenated each subset and performed a Bayesian relaxed clock divergence estimation in RevBayes. The estimated divergence times overlapped for all nodes that are shared between the topologies. Thus, divergence time estimation is robust using any well selected data subset as long as the topology inference is robust.

Going digital: challenges in monitoring marine megafauna when comparing results from visual and digital aerial surveys

Since the first plans to develop offshore wind farms (OWFs), concerns have been raised about the impacts on marine megafauna. Today, it is required to assess these impacts over the whole lifecycle of the OWF. Before construction, initial assessments are often conducted by visual surveys, but subsequent monitoring over the lifecycle of the OWF has to be digital due to safety requirements, leading to challenges in data comparability. The aim of this study was to attempt to establish generalizable intercalibration factors for this transition between visual and digital monitoring methods. To this end, intercalibration surveys were conducted at five different sites and at different times of the year within a site, using both visual monitoring at low-altitude and digital monitoring at both low and high altitudes. We tested the potential for intercalibration of the results based on the ratio of abundance estimated from data collected by the different methods. We explored factors such as the species under study and site-specific conditions that may influence intercalibration. We computed more than 100 intercalibration factors and found that, on average, abundance estimates from digital methods were higher than those from visual methods and that flight altitude for digital monitoring did not significantly influence abundance estimates. Aside from divergent abundance estimates depending on monitoring method, the findings also revealed significant heterogeneity, only one-third of which was explained by contextual factors such as taxonomy or the sea conditions. This outcome presents a pessimistic outlook on the prospect for the intercalibration of results between an initial assessment carried out with visual observations and subsequent monitoring with digital methods after OWF construction and until decommissioning. The high heterogeneity prevents seamless transferability of intercalibration factors and highlights the importance of local context.

Evaluating model fit for type II censored data: a Bayesian non-parametric approach based on the Kullback-Leibler divergence estimation

Model checking evaluates the appropriateness of a statistical model based on the observed data, and it is essential to make valid statistical analyses. In this paper, a new procedure for model checking type II censored data is proposed. This procedure combines the Kullback-Leibler divergence, the Dirichlet process, and the relative belief ratio. The method is implemented via a computational algorithm and is explained through several examples.

The genus Hymenagaricus: phylogeny, time divergence estimation, and the description of three new species from Pakistan

The genus Hymenagaricus: phylogeny, time divergence estimation, and the description of three new species from Pakistan

Transcription dynamics and genome organization in the mammalian nucleus: Recent advances.

Single-molecule tracking (SMT) has emerged as the dominant technology to investigate the dynamics of chromatin-transcription factor (TF) interactions. How long a TF needs to bind to a regulatory site to elicit a transcriptional response is a fundamentally important question. However, highly divergent estimates of TF binding have been presented in the literature, stemming from differences in photobleaching correction and data analysis. TF movement is often interpreted as specific or non-specific association with chromatin, yet the dynamic nature of the chromatin polymer is often overlooked. In this perspective, we highlight how recent SMT studies have reshaped our understanding of TF dynamics, chromatin mobility, and genome organization in the mammalian nucleus, focusing on the technical details and biological implications of these approaches. In a remarkable convergence of fixed and live-cell imaging, we show how super-resolution and SMT studies of chromatin have dovetailed to provide a convincing nanoscale view of genome organization.

Divergent metabolism estimates from dissolved oxygen and inorganic carbon: Implications for river carbon cycling

AbstractRivers efficiently collect, process, and transport terrestrial‐derived carbon. River ecosystem metabolism is the primary mechanism for processing carbon. Diel cycles of dissolved oxygen (DO) have been used for decades to infer river ecosystem metabolic rates, which are routinely used to predict metabolism of carbon dioxide (CO2) with uncertainties of the assumed stoichiometry ranging by a factor of 4. Dissolved inorganic carbon (DIC) has been less used to directly infer metabolism because it is more difficult to quantify, involves the complexity of inorganic carbon speciation, and as shown in this study, likely requires a two‐station approach. Here, we developed DIC metabolism models using single‐ and two‐station approaches. We compared metabolism estimates based on simultaneous DO and DIC monitoring in the Upper Clark Fork River (USA), which also allowed us to estimate ecosystem‐level photosynthetic and respiratory quotients (PQE and RQE). We observed that metabolism estimates from DIC varied more between single‐ and two‐station approaches than estimates from DO. Due to carbonate buffering, CO2 is slower to equilibrate with the atmosphere compared to DO, likely incorporating a longer distance of upstream heterogeneity. Reach‐averaged PQE ranged from 1.5 to 2.0, while RQE ranged from 0.8 to 1.5. Gross primary production from DO was larger than that from DIC, as was net ecosystem production by . The river was autotrophic based on DO but heterotrophic based on DIC, complicating our understanding of how metabolism regulated CO2 production. We suggest future studies simultaneously model metabolism from DO and DIC to understand carbon processing in rivers.

Species delimitation within the genus Porcellana (Anomura, Galatheoidea, Porcellanidae) in the East Atlantic and systematic implications

Abstract The porcelain crab Porcellana africana was originally identified as a subspecies of Porcellana platycheles, a species widely distributed in the eastern Atlantic Ocean and the Mediterranean Sea. A study characterizing the recent invasion of P. africana in South Africa places doubts on the identification and previously reported distribution of populations of the two species of Porcellana, which could have implications for the conservation and management of the species. Here, we aimed to delineate the Porcellana species from the East Atlantic to gain a better understanding of their distribution, which will help in conservation decision-making. Molecular analyses based on two mitochondrial genes and a nuclear gene confirmed that P. africana is a well-defined species and that its distribution extends further north, including the Canary Islands. A time divergence estimation indicates the cladogenesis between P. platycheles and P. africana occurred during the Neogene, likely linked to drastic climatic and environmental changes that took place during the Pliocene. Both species are morphologically very close, but can be distinguished by the shape of the third thoracic sternite.

Affect regulation and allostatic load over time

ObjectiveEmerging work suggests that affect regulation strategies (e.g., active coping, anger expression) predict disease and mortality risk, with sometimes divergent estimates by sex or education levels. However, few studies have examined potential underlying biological mechanisms. This study assessed the longitudinal association of affect regulation with future allostatic load. MethodIn 2004–2006, 574 participants from the Midlife in the United States study completed validated scales assessing use of nine general and emotion-specific regulatory strategies (e.g., denial, anger expression). As a proxy for how flexibly participants regulate their affect, variability in the use of regulatory strategies was operationalized using a standard deviation-based algorithm and considered categorically (i.e., lower, moderate, greater variability) to assess non-linear effects. Participants also provided data on relevant covariates and 24 allostatic load biomarkers (e.g., cortisol, blood pressure). In 2017–2021, these biomarkers were again collected. Linear regressions modeled betas (β) and 95 % confidence intervals (CI) examining associations of affect regulatory constructs with future allostatic load. ResultsIn fully-adjusted models including initial allostatic load, general regulatory strategies were unrelated to future allostatic load. Yet, greater versus moderate affect regulation variability levels predicted lower allostatic load (β=−0.14; 95 %CI: −0.27, −0.01). Only among more educated participants, greater use of anger expression predicted lower allostatic load, while the reverse was noted with anger control (βexpression=−0.12; 95 %CI: −0.20, −0.05; βcontrol=0.14; 95 %CI: 0.05, 0.24). ConclusionsWhile general regulatory strategies appeared unrelated to allostatic load, greater variability in their use and anger-related strategies showed predictive value. Subsequent studies should examine these associations in larger, more diverse samples.

Identification and mapping of sex-linked markers in giant abalone (Haliotis gigantea Gmelin)

Giant abalone (Haliotis gigantea Gmelin) is an economically important species within Haliotis genus, yet the genetic basis of sex in this species is still poorly understood. Therefore, we screened and mapped sex-linked SNPs and InDels, and subsequently developed a PCR-based method for genetic sex identification in giant abalone. Based on whole-genome sequencing reads, we obtained a total 6,159,941 high-quality SNPs and 2,623,263 high-quality InDels. Among them, 1,737 SNPs and 179 InDels were detected as sexually dimorphic, assuming a male heterogametic sex determination system. The majority of these variants, 99.1 % for SNPs and 99.4 % for InDels, were clustered on Chr.4 (0.02 Mb to 23.22 Mb). Furthermore, the estimation of genetic divergence between the sexes using FST showed that the genomic windows with the top 1 % FST values were concentrated on Chr.4 (0.5 Mb to 19.0 Mb) and Chr.5 (20.0 Mb to 35.0 Mb). Based on the sexually dimorphic variants on Chr.4, three PCR-based markers were successfully developed to determine the genetic sex of giant abalone. PCR validation using a tested panel of 67 females and 67 males from a cultivated population demonstrated compliance rates for these three markers ranging from 97.7 % to 99.3 %. These results suggest that the sex determination system is male heterogametic in giant abalone. Thus, this study provides valuable insights and tools for further research on the mechanisms of sex determination and differentiation, as well as for monitoring sex ratios in wild and cultivated populations in giant abalone.

Recent secondary contact, genome-wide admixture, and asymmetric introgression of neo-sex chromosomes between two Pacific island bird species.

Secondary contact between closely related taxa represents a "moment of truth" for speciation-an opportunity to test the efficacy of reproductive isolation that evolved in allopatry and to identify the genetic, behavioral, and/or ecological barriers that separate species in sympatry. Sex chromosomes are known to rapidly accumulate differences between species, an effect that may be exacerbated for neo-sex chromosomes that are transitioning from autosomal to sex-specific inheritance. Here we report that, in the Solomon Islands, two closely related bird species in the honeyeater family-Myzomela cardinalis and Myzomela tristrami-carry neo-sex chromosomes and have come into recent secondary contact after ~1.1 my of geographic isolation. Hybrids of the two species were first observed in sympatry ~100 years ago. To determine the genetic consequences of hybridization, we use population genomic analyses of individuals sampled in allopatry and in sympatry to characterize gene flow in the contact zone. Using genome-wide estimates of diversity, differentiation, and divergence, we find that the degree and direction of introgression varies dramatically across the genome. For sympatric birds, autosomal introgression is bidirectional, with phenotypic hybrids and phenotypic parentals of both species showing admixed ancestry. In other regions of the genome, however, the story is different. While introgression on the Z/neo-Z-linked sequence is limited, introgression of W/neo-W regions and mitochondrial sequence (mtDNA) is highly asymmetric, moving only from the invading M. cardinalis to the resident M. tristrami. The recent hybridization between these species has thus enabled gene flow in some genomic regions but the interaction of admixture, asymmetric mate choice, and/or natural selection has led to the variation in the amount and direction of gene flow at sex-linked regions of the genome.

Shedding Light on the Origin of ^{204}Pb, the Heaviest s-Process-Only Isotope in the Solar System.

Asymptotic giant branch stars are responsible for the production of most of the heavy isotopes beyond Sr observed in the solar system. Among them, isotopes shielded from the r-process contribution by their stable isobars are defined as s-only nuclei. For a long time the abundance of ^{204}Pb, the heaviest s-only isotope, has been a topic of debate because state-of-the-art stellar models appeared to systematically underestimate its solar abundance. Besides the impact of uncertainties from stellar models and galactic chemical evolution simulations, this discrepancy was further obscured by rather divergent theoretical estimates for the neutron capture cross section of its radioactive precursor in the neutron-capture flow, ^{204}Tl (t_{1/2}=3.78 yr), and by the lack of experimental data on this reaction. We present the first ever neutron capture measurement on ^{204}Tl, conducted at the CERN neutron time-of-flight facility n_TOF, employing a sample of only 9mg of ^{204}Tl produced at the Institute Laue Langevin high flux reactor. By complementing our new results with semiempirical calculations we obtained, at the s-process temperatures of kT≈8 keV and kT≈30 keV, Maxwellian-averaged cross sections (MACS) of 580(168)mb and 260(90)mb, respectively. These figures are about 3% lower and 20% higher than the corresponding values widely used in astrophysical calculations, which were based only on theoretical calculations. By using the new ^{204}Tl MACS, the uncertainty arising from the ^{204}Tl(n,γ) cross section on the s-process abundance of ^{204}Pb has been reduced from ∼30% down to +8%/-6%, and the s-process calculations are in agreement with the latest solar system abundance of ^{204}Pb reported by K. Lodders in 2021.

A multi-algorithm approach for modeling coastal wetland eco-geomorphology

Coastal wetlands play an important role in the global water and biogeochemical cycles. Climate change makes it more difficult for these ecosystems to adapt to the fluctuation in sea levels and other environmental changes. Given the importance of eco-geomorphological processes for coastal wetland resilience, many eco-geomorphology models differing in complexity and numerical schemes have been developed in recent decades. However, their divergent estimates of the response of coastal wetlands to climate change indicate that substantial structural uncertainties exist in these models. To investigate the structural uncertainty of coastal wetland eco-geomorphology models, we developed a multi-algorithm model framework of eco-geomorphological processes, such as mineral accretion and organic matter accretion, within a single hydrodynamics model. The framework is designed to explore possible ways to represent coastal wetland eco-geomorphology in Earth system models and reduce the related uncertainties in global applications. We tested this model framework at three representative coastal wetland sites: two saltmarsh wetlands (Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter Estuary). Through the model–data comparison, we showed the importance of using a multi-algorithm ensemble approach for more robust predictions of the evolution of coastal wetlands. We also found that more observations of mineral and organic matter accretion at different elevations of coastal wetlands and evaluation of the coastal wetland models at different sites in diverse environments can help reduce the model uncertainty.

Biogeographic history of pigeons and doves drives the origin and diversification of their parasitic body lice.

Despite their extensive diversity and ecological importance, the history of diversification for most groups of parasitic organisms remains relatively understudied. Elucidating broad macroevolutionary patterns of parasites is challenging, often limited by the availability of samples, genetic resources, and knowledge about ecological relationships with their hosts. In this study, we explore the macroevolutionary history of parasites by focusing on parasitic body lice from doves. Building on extensive knowledge of ecological relationships and previous phylogenomic studies of their avian hosts, we tested specific questions about the evolutionary origins of the body lice of doves, leveraging whole genome data sets for phylogenomics. Specifically, we sequenced whole genomes from 68 samples of dove body lice, including representatives of all body louse genera from 51 host taxa. From these data, we assembled >2,300 nuclear genes to estimate dated phylogenetic relationships among body lice and several outgroup taxa. The resulting phylogeny of body lice was well supported, although some branches had conflicting signal across the genome. We then reconstructed ancestral biogeographic ranges of body lice and compared the body louse phylogeny to phylogeny of doves, and also to a previously published phylogeny of the wing lice of doves. Divergence estimates placed the origin of body lice in the late Oligocene. Body lice likely originated in Australasia and dispersed with their hosts during the early Miocene, with subsequent codivergence and host switching throughout the world. Notably, this evolutionary history is very similar to that of dove wing lice, despite the stronger dispersal capabilities of wing lice compared to body lice. Our results highlight the central role of the biogeographic history of host organisms in driving the evolutionary history of their parasites across time and geographic space.

BFLIDS: Blockchain-Driven Federated Learning for Intrusion Detection in IoMT Networks.

The Internet of Medical Things (IoMT) has significantly advanced healthcare, but it has also brought about critical security challenges. Traditional security solutions struggle to keep pace with the dynamic and interconnected nature of IoMT systems. Machine learning (ML)-based Intrusion Detection Systems (IDS) have been increasingly adopted to counter cyberattacks, but centralized ML approaches pose privacy risks due to the single points of failure (SPoFs). Federated Learning (FL) emerges as a promising solution, enabling model updates directly on end devices without sharing private data with a central server. This study introduces the BFLIDS, a Blockchain-empowered Federated Learning-based IDS designed to enhance security and intrusion detection in IoMT networks. Our approach leverages blockchain to secure transaction records, FL to maintain data privacy by training models locally, IPFS for decentralized storage, and MongoDB for efficient data management. Ethereum smart contracts (SCs) oversee and secure all interactions and transactions within the system. We modified the FedAvg algorithm with the Kullback-Leibler divergence estimation and adaptive weight calculation to boost model accuracy and robustness against adversarial attacks. For classification, we implemented an Adaptive Max Pooling-based Convolutional Neural Network (CNN) and a modified Bidirectional Long Short-Term Memory (BiLSTM) with attention and residual connections on Edge-IIoTSet and TON-IoT datasets. We achieved accuracies of 97.43% (for CNNs and Edge-IIoTSet), 96.02% (for BiLSTM and Edge-IIoTSet), 98.21% (for CNNs and TON-IoT), and 97.42% (for BiLSTM and TON-IoT) in FL scenarios, which are competitive with centralized methods. The proposed BFLIDS effectively detects intrusions, enhancing the security and privacy of IoMT networks.

INTEGRATE-ADHD: Comparison and Integration of Administrative and Epidemiological ADHD Diagnosis Data through Clinical Assessment - Presentation of the Project

As one of the most frequently diagnosed mental disorders in children and adolescents with sometimes serious individual, family and social consequences, attention deficit/hyperactivity disorder (ADHD) is highly relevant to society and health policy. In Germany, data from statutory health insurance companies has reported increasing ADHD diagnosis prevalence rates over years, while epidemiological data has shown constant and recently even decreasing prevalence rates. The clinical validity of diagnoses from either data sources is unknown. In the framework of the consortium project INTEGRATE-ADHD, 5461 parents of children aged 0 to 17 years with a confirmed administrative ADHD diagnosis insured with the third-largest German statutory health insurance provider (DAK-Gesundheit) in at least one quarter of 2020 were surveyed with the questionnaires from the epidemiological German Health Interview and Examination Survey (KiGGS study) and its in-depth module on child mental health (BELLA study) on their child's ADHD diagnosis and symptoms and on other topics, including comorbidity, utilisation of healthcare services, quality of care and satisfaction, psychosocial risk and protective factors and health-related quality of life. In addition, a subsample of 202 children and adolescents with a clinical diagnosis based on the AMWF S3 guideline on ADHD was analysed. An important aim of the project is to use data linkage on person-level to identify possible causes for the often divergent prevalence estimates from epidemiological and administrative data and to integrate and validate the data sources using a guideline-based clinical diagnosis, thereby contributing to a more accurate population-based prevalence estimate of ADHD in children and adolescents and clarifying actual or supposed contradictions between the data sources. The INTEGRATE-ADHD data linkage project combines administrative, epidemiological and clinical ADHD diagnosis data to create a "three-dimensional view" of the ADHD diagnosis. The results will be used to identify fields of action for healthcare policy and self-administration in the German healthcare system and to derive recommendations for the actors and stakeholders in the field of ADHD. The first results will be published in 2024.

Discovery in leaf litter: uncovering the systematics of Porcelloderes (Heteroptera: Reduviidae: Phimophorinae)

Abstract The subfamily Phimophorinae includes ~113 species of cryptic assassin bugs found in the Neotropics and Paleotropics. Presumably due to its small size, cryptic coloration, and occurrence in the remote Eastern Arc Mountains (EAM), Porcelloderes impenetrabilis Rédei, 2012 (Heteroptera: Reduviidae: Phimophorinae), was only recently described as the first representative of this subfamily from mainland Africa. Previous morphology-based phylogenetic research on Phimophorinae (then known as Physoderinae or Epiroderinae) recovered Porcelloderes as sister taxon to the remaining epiroderine-lineage of Phimophorinae. Recent fieldwork in Tanzania has resulted in 241 additional specimens of Porcelloderes from 3 EAM) ranges. We used molecular and morphological analyses for these 241 specimens to (i) determine their species identity, (ii) test the phylogenetic position of Porcelloderes within Phimophorinae, and (iii) determine if divergence within Porcelloderes coincides with periods of climate-driven forest fragmentation in the EAM. Specimens from the Kimboza and Nguru Mountains likely represent P. impenetrabilis, but we here describe Porcelloderes harles, n. sp., from the Udzungwa Mountains. Our molecular phylogeny shows Porcelloderes nested within the epiroderine-lineage of Phimophorinae and as sister taxon to a Madagascar clade. We estimate that the epiroderine-lineage diverged from other Phimophorinae ~44 MYA. The divergence estimates for the 2 Porcelloderes species is ~15 MYA, consistent with proposed dates for other EAM assassin bugs and a period of forest fragmentation.

Uncovering ghost introgression through genomic analysis of a distinct eastern Asian hickory species.

Ghost introgression, or the transfer of genetic material from extinct or unsampled lineages to sampled species, has attracted much attention. However, conclusive evidence for ghost introgression, especially in plant species, remains scarce. Here, we newly assembled chromosome-level genomes for both Carya sinensis and Carya cathayensis, and additionally re-sequenced the whole genomes of 43 C. sinensis individuals as well as 11 individuals representing 11 diploid hickory species. These genomic datasets were used to investigate the reticulation and bifurcation patterns within the genus Carya (Juglandaceae), with a particular focus on the beaked hickory C. sinensis. By combining the D-statistic and BPP methods, we obtained compelling evidence that supports the occurrence of ghost introgression in C. sinensis from an extinct ancestral hickory lineage. This conclusion was reinforced through the phylogenetic network analysis and a genome scan method VolcanoFinder, the latter of which can detect signatures of adaptive introgression from unknown donors. Our results not only dispel certain misconceptions about the phylogenetic history of C. sinensis but also further refine our understanding of Carya's biogeography via divergence estimates. Moreover, the successful integration of the D-statistic and BPP methods demonstrates their efficacy in facilitating a more precise identification of introgression types.

Advancements in Rényi entropy and divergence estimation for model assessment

Advancements in Rényi entropy and divergence estimation for model assessment

The Extended Bregman Divergence and Parametric Estimation in Continuous Models

The Extended Bregman Divergence and Parametric Estimation in Continuous Models

Developing novel ensemble models for predicting soil hydraulic properties in China’s arid region

Accurately quantifying the mass (water, nutrients, and carbon) and energy exchange processes between the Earth’s atmosphere, biosphere, and lithosphere requires the accurate parameterization of soil hydraulic properties (SHPs) and their spatial heterogeneity. Because direct measurements of SHPs are difficult, time-consuming, and impossible at larger spatial scales, various pedotransfer functions (PTFs) have been developed in the last few decades, providing divergent estimates of SHPs from readily measurable variables. However, existing PTFs are mostly developed for specific regions and may not be suitable for other pedoclimatic conditions. Here, PTFs were developed using multiple machine-learning algorithms to estimate SHPs and examined the weaknesses and strengths of each method in estimating the average and variability of SHPs across China’s arid region. The optimal PTFs were applied to a 1 × 1 km2 regional map of texture and bulk density, thus producing maps of the saturated hydraulic conductivity (Ks), the parameters of the van Genuchten (VG) formulation, field capacity (θfc), wilting point (θwp), plant available water (θpa), and soil macroporosity (ϕm) in the 0–2 m soil profile throughout the region. The results indicate that the ensemble model with the averaging method (EMA) is the most robust for estimating all SHPs. The EMA-PTFs for Ks yielded the best performance for sand textures, followed by sandy loam, loam, silty loam, silty clay loam, loamy sand, and clay loam textures. There were no significant differences in estimating soil water retention curve parameters among the different soil texture classes. Using the same observed data set, we demonstrated that the new EMA-PTFs outperformed those of existing PTFs, such as Rosetta and HYPRES, with RMSE values decreasing by 25–83 % depending on the SHPs. Furthermore, our SHP datasets exhibited significantly deeper soil profiles and higher accuracy than other available regional and global SHP products. The VG retention parameter α shows the greatest variation vertically throughout the 0–2 m soil profile, followed by ln(Ks), θr, θpa, θfc, θwp, ϕm, θs and n. All SHPs exhibit much lower variability in the desert than in other areas, likely due to the homogeneous particle size distribution of desert areas. This study provides more accurate SHP estimates in China’s arid region than the existing SHP products by developing advanced PTFs and highlights the inconsistency in SHPs among different global or regional products; the uncertainties induced by PTFs should thus be considered in future terrestrial biosphere modeling.