Variation Partitioning Research Articles

Metabolic Characterization and Geochemical Drivers of Active Hydrocarbon‐Degrading Microorganisms

AbstractUnderstanding the metabolic characteristics and controlled geochemical factors of functional microorganisms in petroleum‐contaminated areas at different locations is pivotal for enhancing pollutant removal strategies. To address the existing research gap in this domain, we employed stable‐isotope‐probing (SIP) with multi‐isotope labeling substrates, combined with 16S amplicon sequencing, metagenomic sequencing, and geochemical factor analysis. Utilizing n‐hexadecane and phenanthrene as model compounds, our study revealed location‐specific differences in the composition of functional microorganisms. Despite these variances, key players such as Pseudomonas, Marinobacter, Alcanivorax, Ochrobactrum, and Sphingomonas consistently emerged as active degraders of n‐hexadecane and/or phenanthrene. Several genera, including Pseudomonas, Ochrobactrum, Alcanivorax, Nitriliruptoraceae, and Sphingobacterium, demonstrated versatility by effectively degrading both contaminants. SIP‐metagenomic binning facilitated the acquisition of genomes from key active degraders, such as Pseudomonas sp., Ochrobactrum sp., Sphingomonas sp., and Shinella sp. This enabled a comprehensive analysis of petroleum hydrocarbon degradation pathways and genes, encompassing PAH dioxygenase genes, alkB genes, phthalate, and salicylate‐related pathways. Environmental factor and variation partitioning analysis revealed that oil pollution significantly influences the functional microbial community (12%), followed by available potassium and available nitrogen. Geochemical parameters and geographic location independently explained 14% and 21% of total variations, respectively. Intriguingly, more than half (51%) of the variation in functional microbial community structure remains unexplained, possibly due to unmeasured environmental variables. Our study contributes valuable insights into the in situ bioremediation mechanism for petroleum‐contaminated soil, elucidating factors influencing functional microbial structures across locations. These findings provide a vital theoretical reference for in situ regulation and bioremediation of petroleum hydrocarbon pollution in diverse environmental contexts.

Plant beta-turnover rather than nestedness shapes overall taxonomic and phylogenetic beta-diversity triggered by favorable spatial-environmental conditions in large-scale Chinese grasslands.

Although it is widely acknowledged that biodiversity maintains plant community assembly processes, exploring the patterns and drivers of beta-diversity (β-diversity; species variation among local plant communities) has received much less attention compared to alpha-diversity (α-diversity; species variation within a local plant community). Here, we aim to examine the patterns and spatial-environmental drivers of taxonomic and phylogenetic β-diversity, and their components such as species turnover and nestedness, in large-scale Leymus chinensis grassland communities. We collected plant community data from 166 sites across widely distributed L. chinensis communities in northern China, and then calculated the taxonomic and phylogenetic β-diversity indices (overall, turnover and nestedness) using a pairwise dissimilarity approach. To assess the effects and to explain the variation in the patterns of β-diversity, we collected data on geospatial, climate and soil conditions. We applied descriptive statistics, Mental correlations, and multiple linear regression models to assess the patterns and spatial-environmental drivers of β-diversity. The β-turnover, as compared to β-nestedness, exhibited a predominant influence, constituting 92.6% of the taxonomic β-diversity and 80.4% of the phylogenetic β-diversity. Most of the spatial-environmental variables were significantly positively correlated with the overall taxonomic and phylogenetic β-diversity and β-turnover, but not with β-nestedness. Climatic factors such as MAP and MAT were the strongest predictors of both taxonomic and phylogenetic β-diversity and β-turnover. The variance partitioning analysis showed that the combined effects of spatial and environmental factors accounted for 19% and 16% of the variation in the taxonomic and phylogenetic β-diversity (overall), 17% and 12% of the variation in the β-turnover, and 7% and 1% of the variation in the β-nestedness, respectively, which were higher than independent effects of either spatial or environmental factors. At larger spatial scales, the turnover component of β-diversity may be associated with the species complementarity effect, but dominant or functionally important species can vary among communities due to the species selection effect. By incorporating β-diversity into grassland management strategies, we can enhance the provision of vital ecosystem services that bolster human welfare, serving as a resilient barrier against the adverse effects of climate change at regional and global scales.

Multidimensional primate niche space sheds light on interspecific competition in primate evolution

Characterising how the totality of primate diversity is distributed across the order, and how it evolved, is challenging because diversity in individual traits often show opposing phylogenetic patterns. A species’ combination of traits can be conceptualised as its ‘niche’. Here, we describe and analyse seven-dimensional niche space, comprising 11 traits, for 191 primate species. Multifaceted diversity is distributed unequally among taxonomic groups. Cercopithecoidea and Hominidae occupy the largest areas of niche space, and are the most diverse families; platyrrhine families occupy small areas, and this space overlaps with strepsirrhines. The evolution of species’ locations in niche space is regulated by selection for adaptive optima in trait combinations. Given that niche similarity results in interspecific competition, we quantify two measures of species’ niche locations relative to others. We find that omnivores, frugivores, and species tolerating higher temperatures experience stronger interspecific competition. Hominidae occupation of niche space suggests competitive exclusion from niches by Cercopithecoidea over evolutionary time; but living great apes experience the lowest levels of interspecific competition. Callitrichids experience the highest levels of interspecific competition. Our results provide a standardised measure of primate niches that sheds light on the partitioning and evolution of primate diversity, and how this is driven by interspecific competition.

Spatial patterns and climatic drivers of phylogenetic structure of regional liverwort assemblages in China.

Latitudinal diversity gradients have been intimately linked to the tropical niche conservatism hypothesis, which posits that there has been a strong filter due to the challenges faced by ancestral tropical lineages to adapt to low temperatures and colonize extra-tropical regions. In liverworts, species richness is higher towards the tropics, but the centres of diversity of the basal lineages are distributed across extra-tropical regions, pointing to the colonization of tropical regions by phylogenetically clustered assemblages of species of temperate origin. Here, we test this hypothesis through analyses of the relationship between macroclimatic variation and phylogenetic diversity in Chinese liverworts. Phylogenetic diversity metrics and their standardized effect sizes for liverworts in each of the 28 regional floras at the province level in China were related to latitude and six climate variables using regression analysis. We conducted variation partitioning analyses to determine the relative importance of each group of climatic variables. We find that the number of species decreases with latitude, whereas phylogenetic diversity shows the reverse pattern, and that phylogenetic diversity is more strongly correlated with temperature-related variables compared with precipitation-related variables. We interpret the opposite patterns observed in phylogenetic diversity and species richness in terms of a more recent origin of tropical diversity coupled with higher extinctions in temperate regions.

Coupling physiochemical adsorption with biodegradation for enhanced removal of microcystin-LR in water

To innovate the design of water treatment technology for algal toxin removal, this research investigated the mechanisms of cyanotoxin microcystin-LR (MC-LR) removal by a coupled adsorption-biodegradation. Eight types of woody carbonaceous adsorbents with and without Sphingopyxis sp. m6, a MC-LR degrading bacterium, were tested for MC-LR removal in water. All adsorbents showed good adsorption capability, removing 40 % to almost 100 % of the MC-LR (4.5 mg/L) within 48 h in batch experiments. Adding Sphingopyxis sp. m6 continuously promoted MC-LR biological removal, and successfully broke the barrier of adsorption capacity of tested adsorbents, removing >90 % of the MC-LR in most of the coupled adsorption-biodegradation tests, especially for those adsorbents had low physiochemical adsorption capacity. Variance partitioning analysis indicated that mesopore was the dominant contributor to adsorption capacity of MC-LR in pure adsorption treatments, which acted synergistically with electrical conductivity, polarity and total functional groups on the absorbent. Pore structure was the key factor beneficial for the growth of Sphingopyxis sp. m6 (51% contribution) and subsequent MC-LR biological removal rate (80 % contribution). Overall, pinewood-based carbonaceous adsorbents (especially pinewood activated carbon) exhibited the highest adsorption capacity towards MC-LR and provided the most favorable conditions for biological removal of MC-LR, largely because of their high mesopore volume, total functional groups and electric conductivity. The research outcomes not only deepened the quantitative understanding of mechanisms for MC-LR removal by the coupled process, but also provided theoretical basis for future materials' selection and modification during the practical application of coupled process.

Near-natural streams: Spatial factors are key in shaping multiple facets of zooplankton α and β diversity

In near-natural basins, zooplankton are key hubs for maintaining aquatic food webs and organic matter cycles. However, the spatial patterns and drivers of zooplankton in streams are poorly understood. This study registered 165 species of zooplankton from 147 sampling sites (Protozoa, Rotifers, Cladocera and Copepods), integrating multiple dimensions (i.e., taxonomic, functional, and phylogenetic) and components (i.e., total, turnover, and nestedness) of α and β diversity. This study aims to reveal spatial patterns, mechanisms, correlations, and relative contribution of abiotic factors (i.e., local environment, geo-climatic, land use, and spatial factors) through spatial interpolation (ordinary kriging), mantel test, and variance partitioning analysis (VPA). The study found that α diversity is concentrated in the north, while β diversity is more in the west, which may be affected by typical habitat, hydrological dynamics and underlying mechanisms. Taxonomic and phylogenetic β diversity is dominated by turnover, and metacommunity heterogeneity is the result of substitution of species and phylogeny along environmental spatial gradients. Taxonomic and phylogenetic β diversity were strongly correlated (r from 0.91 to 0.95), mainly explained by historical/spatial isolation processes, community composition, generation time, and reproductive characteristics, and this correlation provides surrogate information for freshwater conservation priorities. In addition, spatial factors affect functional and phylogenetic α diversity (26%, 28%), and environmental filtering and spatial processes combine to drive taxonomic α diversity (10%) and phylogenetic β diversity (11%). Studies suggest that spatial factors are key to controlling the community structure of zooplankton assemblages in near-natural streams, and that the relative role of local environments may depend on the dispersal capacity of species. In terms of diversity conservation, sites with high variation in uniqueness should be protected (i) with a focus on the western part of the thousand islands lake catchment and (ii) increasing effective dispersal between communities to facilitate genetic and food chain transmission.

How Do Zooplankton Communities Respond to Environmental Factors across the Subsidence Wetlands Created by Underground Coal Mining in the North China Plain?

The degradation and loss of natural wetlands has caused severe crises for wetland taxa. Meanwhile, constructed wetlands are expanding significantly and facing dramatic environmental changes. Exploring the responses of wetland organisms, particularly zooplankton, may have important implications for the management of wetlands. Environmental and zooplankton samples were collected from 34 subsidence wetlands created by underground coal mining across the North China Plain in August 2021. We used generalized linear models and redundancy analysis to test zooplankton responses to environmental variables, with the relative importance quantified by variation partitioning. We identified 91 species, divided into 7 functional groups, with the highest density of rotifer filter feeders (RF, 2243.4 ± 499.4 ind./L). Zooplankton species richness was negatively correlated with electrical conductivity (EC), chlorophyll-a, total phosphorus, and pH. The Shannon–Weiner and Pielou evenness indices were positively correlated with transparency and negatively correlated with the photovoltaic panel area (AS). Rotifer predators (RCs) and RF densities were positively correlated with cropland area and dissolved oxygen, but negatively correlated with AS. Small crustacean filter feeders positively correlated with AS, whereas medium crustacean feeders (MCFs) positively correlated with EC. AS was the most critical variable affecting the zooplankton community. Our study showed that the spatial pattern of zooplankton communities was shaped by environmental heterogeneity across the subsidence wetlands, providing implications for the management and conservation of these constructed wetlands.

Beyond beta: diversity partitioning reveals different underlying patterns in ant assemblages along two small scale gradients in a Brazilian neotropical forest

Beyond beta: diversity partitioning reveals different underlying patterns in ant assemblages along two small scale gradients in a Brazilian neotropical forest

The spatial variation and drivers of soil δ13C in an alpine-gorge region on the eastern Qinghai-Tibetan Plateau

Soil stable carbon isotope (soil δ13C) can reflect soil carbon metabolic processes and record environmental and vegetation change information, so mapping the spatial distribution of soil δ13C (isoscapes of soil δ13C) can help us better understand the spatial variability of ecosystem carbon cycles. However, efficient approaches for obtaining the isoscapes of soil δ13C remain challenging, especially in mountainous areas with complex terrain. A total of 150 soil samples were collected and their soil δ13C was measured to investigate the spatial variation of soil δ13C in an alpine-gorge region on the eastern Qinghai-Tibetan Plateau which is characterized by complex terrain. Four prediction methods included ordinary kriging interpolation, multiple linear regression, random forest regression, and geographically weighted regression (GWR) were selected and compared to find the best prediction model for mapping the isoscapes of soil δ13C. The pathways of vegetation, topography, soil, and spatial factors influencing the spatial variability of soil δ13C were explored using variance partitioning analysis and structural equation model. The soil δ13C was significantly different among vegetation types, and ranged from −27.155‰ to −9.647‰. The spatial heterogeneity of soil δ13C showed moderate variation, and was dominated by spatial structural factors. The GWR model had higher prediction accuracy in the modeling soil δ13C in comparison to other models. Soil carbon to nitrogen ratio and normalized difference vegetation index were the main factors determining the spatial variability of soil δ13C, and other topographic and soil factors indirectly regulated the spatial distribution of soil δ13C by influencing these two factors. Our results provided a useful tool (GWR model) for mapping the isoscapes of soil δ13C and explored the factors controlling the spatial variability of soil δ13C in the alpine-gorge region on the eastern Qinghai-Tibetan Plateau, which are important for an in-depth understanding of soil carbon cycling in mountain ecosystems.

Major axes of variation in tree demography across global forests

The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatio‐temporal patterns in tree population dynamics. While previous research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach to overcome these limitations is to group mechanisms according to their shared effects on the variability of tree vital rates and quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions – categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28–33% of demographic variance alone, and 14–17% in interaction with space, totalling 40–43%. Our results support the hypothesis that the range of vital rates is similar across global forests. However, the average variability among species declined with species richness, indicating that diverse forests featured smaller interspecific differences in vital rates. Moreover, decomposing the variance in vital rates into the proposed OPs showed the importance of unexplained variability, which includes individual variation, in tree demography. A focus on how demographic variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems.

Wright's Hierarchical F-Statistics.

This perspective article offers a meditation on FST and other quantities developed by Sewall Wright to describe the population structure, defined as any departure from reproduction through random union of gametes. Concepts related to the F-statistics draw from studies of the partitioning of variation, identity coefficients, and diversity measures. Relationships between the first two approaches have recently been clarified and unified. This essay addresses the third pillar of the discussion: Nei's GST and related measures. A hierarchy of probabilities of identity-by-state provides a description of the relationships among levels of a structured population with respect to genetic diversity. Explicit expressions for the identity-by-state probabilities are determined for models of structured populations undergoing regular inbreeding and recurrent mutation. Levels of genetic diversity within and between subpopulations reflect mutation as well as migration. Accordingly, indices of the population structure are inherently locus-specific, contrary to the intentions of Wright. Some implications of this locus-specificity are explored.

Spectral fusion-based machine learning classifiers for discriminating membrane breakage in multiple scenarios

Membrane breakage can lead to filtration failure, which allows harmful substances to enter the effluent, posing potential hazards to human health and the environment. This study is an innovative combination of fluorescence and ultraviolet-visible (UV–Vis) spectroscopy to identify membrane breakage. It aims to unravel more comprehensive information, improve detection sensitivity and selectivity, and enable real-time monitoring capabilities. Fluorescence and UV–Vis data are extracted through variance partitioning analysis (VPA) and integrated through a decision tree algorithm to form a superior system with enhanced discrimination capabilities. VPA improves discrimination efficiency by extracting key information from spectral data and eliminating redundancy. The decision tree algorithm, on the other hand, can process large amounts of data simultaneously. In addition, the method has a wide range of applications and can be used in various scenarios accurately. The scenarios include domestic sewage, micropollutant water, aquaculture wastewater, and secondary treated sewage. The experimental results validate the application of machine learning classifiers in membrane breakage detection with an accuracy rate of 96.8 % to 97.4 %.

Parasite infestation patterns differ between ticks and chigger mites on two rodent host species in Taiwan.

Parasites are typically concentrated on a few host individuals, and identifying the mechanisms underlying aggregated distribution can facilitate a more targeted control of parasites. We investigated the infestation patterns of hard ticks and chigger mites on two rodent species, the striped field mouse, Apodemus agrarius, and the lesser ricefield rat, Rattus losea, in Taiwan. We also explored abiotic and biotic factors that were important in explaining variation in the abundance of ticks and chiggers on rodent hosts. Ticks were more aggregated than chiggers on both rodent species. Factors important for the variation in parasitic loads, especially biotic factors, largely differed between ticks and chiggers. Variation partitioning analyses revealed that a larger proportion of variation in chiggers than in ticks can be explained, especially by abiotic factors. If, as proposed, the higher number of parasites in males is due to a larger range area or immunity being suppressed by testosterone, when A. agrarius males host more ticks, they are expected to also host more chiggers, given that chiggers adopt a similar host finding approach to that of ticks. Instead, the similar abundance of chiggers in male and female A. agrarius implies that a large home range or suppressed immunity does not predispose males to inevitably host more parasites. More variations were explained by abiotic than biotic factors, suggesting that controlling practices are more likely to be successful by focusing on factors related to the environment instead of host traits. Our study indicated that the extent of parasitism is rarely determined by a sole factor, but is an outcome of complex interactions among animal physiology, animal behavior, characteristics of parasites, and the environments.

Adaptation of Wind Drag Coefficient Parameterization: Improvement of Hydrodynamic Modeling by a Wave‐Dependent Cd in Large Shallow Lakes

AbstractWind is a critical driving force in hydrodynamic and water quality modeling of large shallow lakes, and is characterized by the wind drag coefficient Cd, representing the momentum transfer at the air‐water interface. Contemporary empirical formulae for Cd estimation were derived over oceans and some of which are solely wind velocity U10 dependent. These formulae were previously found to be inadequate in inland lake models often resulting in the water velocity underestimation. To address this problem, a physical scale experiment was designed, in which Cd was measured using a wind profile and eddy covariance methodology. A new wind‐induced wave‐dependent Cd parameterization was also established and validated in two lake studies. The driving force was modified by the wave‐dependent Cd formula in a hydrodynamic model of the shallow Upper Klamath Lake (UKL), OR, USA. The experimental Cd was negatively correlated to the wind velocity up until the critical U10 = 1.6 m s−1 which was 1.0~3.1 times previous empirical extrapolations at light winds. The variation partitioning results showed that wave parameters contributed to more than 30% of Cd variation combined with wind parameters. The modified wind stress field was spatially heterogeneous and the modeled water velocity was closer to the observations at two sites. Significant main circulation and outer bank circulation were modeled accompanied by higher surface vorticity, compared to the original UKL model. Overall, the wave‐dependent Cd formula provided an improvement of the surface flow field in the UKL model and will improve the management of the lake ecosystems.

Plant and soil microbial community assembly processes across urban vacant lots

AbstractQuestionsNumerous studies on community assembly processes have been conducted in natural ecosystems. However, we know little about community assembly processes in human‐dominated urban ecosystems. Here, we asked: (1) how are the composition and functional diversity of native and exotic plant species shaped by local environment and landscape factors across urban vacant lots; and (2) how is microbial (bacterial and fungal) community composition influenced by the local environment, landscape factors, and plant species composition across urban vacant lots?LocationWe investigated 69 urban vacant lots in Yokohama, Japan.MethodsBy using a variation partitioning approach, we examined the relative importance of local environmental and landscape factors (including land use and spatial structure) in explaining variation in plant species composition and functional diversity of native or exotic species. We also explored the relative importance of local environmental and landscape factors, and plant species composition in explaining variation in microbial community composition.ResultsThe spatial structure of vacant lots determined the species composition and functional diversity of plant communities, suggesting that plant community assembly is determined by dispersal limitation. However, the functional diversity of the exotic species varied randomly, which reduced the relative importance of the spatial structure of vacant lots. Plant species composition as well as the spatial structure of vacant lots were the important drivers of the composition of soil microbial communities, despite a higher proportion of unexplained variation in their composition. Finally, we found an essential contribution of earthmoving methods in explaining the variations in both plant and microbial community composition.ConclusionPlant and microbial community composition would be largely determined by dispersal limitation across urban vacant lots. Understanding urban community assembly is critical for predicting plant and microbial communities that play an essential role in regulating urban ecosystem functioning and services.

MPH: fast REML for large-scale genome partitioning of quantitative genetic variation.

Genome partitioning of quantitative genetic variation is useful for dissecting the genetic architecture of complex traits. However, existing methods, such as Haseman-Elston regression and linkage disequilibrium score regression, often face limitations when handling extensive farm animal datasets, as demonstrated in this study. To overcome this challenge, we present MPH, a novel software tool designed for efficient genome partitioning analyses using restricted maximum likelihood. The computational efficiency of MPH primarily stems from two key factors: the utilization of stochastic trace estimators and the comprehensive implementation of parallel computation. Evaluations with simulated and real datasets demonstrate that MPH achieves comparable accuracy and significantly enhances convergence, speed, and memory efficiency compared to widely used tools like GCTA and LDAK. These advancements facilitate large-scale, comprehensive analyses of complex genetic architectures in farm animals. The MPH software is available at https://jiang18.github.io/mph/.

Dynamic evolution of ultrafiltration membrane fouling affected by S(IV)–Fe(II)-activated permanganate pretreatment during a long-term operation

ABSTRACT The S(IV)–Fe(II)/PM pretreatment has demonstrated preliminary potential as an effective ultrafiltration (UF) pretreatment technology. However, a comprehensive understanding of its impact on UF membrane fouling control and the dynamic evolution of membrane fouling during prolonged operation is still lacking. In this study, a relatively prolonged fouling experiment was conducted. Results revealed that the S(IV)–Fe(II)/PM pretreatment exhibited superior performance over Al(III) coagulation pretreatment in mitigating the transmembrane pressure difference and addressing both reversible and irreversible membrane fouling. The application of a cluster analysis method to classify membrane fouling evolution stages further confirmed that S(IV)–Fe(II)/PM pretreatment effectively decelerated the rate of membrane fouling evolution. The surface cake layer of UF membranes pretreated with S(IV)–Fe(II)/PM exhibited greater looseness and smoothness. It also showed better results than Al(III) coagulation pretreatment in reducing the accumulation of organic foulants, controlling the Si content and reducing the total microorganisms and live microorganisms in the UF feed water. Variance Partitioning Analysis indicated that the combined contribution of organic, inorganic, and biological foulants was the most significant for UF membranes after S(IV)–Fe(II)/PM pretreatment (50.4%) and UF membranes after Al(III) coagulation pretreatment (70.2%). These findings underscore the efficacy of S(IV)–Fe(II)/PM pretreatment in controlling UF membrane fouling under prolonged operation.

Rootstock influences on growth and bearing precocity in juvenile cocoa

Within the cocoa germplasm used for variety development in West Africa, knowledge of varieties that are suitable as rootstocks to promote growth and precocity of clones is lacking. Six cocoa varieties were used to generate 36 clones for evaluation. For each of the six scions selected as ortets from previous progeny trials, the corresponding seed-derived family was regenerated through manual pollinations. The scions were grafted in a full diallel fashion on each of the six seed-derived family, and field evaluated in four replications following a randomized complete block design. Also, seed-derived varieties were evaluated in the nursery for vigour characteristics, and under similar conditions as the 36 clones in the field. Genotype heterozygosity at 72 SNP loci was significantly correlated with vigour characteristics of the six varieties. Seed-derived varieties of high vigour benefited clone performance for vigour, and dry bean yield when used as rootstocks but not as scion. The maximum photochemical efficiency of photosystem II (Fv/Fm) was different among seed-derived varieties and clones in the dry season but not the rainy season. Among clones, higher Fv/Fm values were associated with higher-vigour rootstock varieties. Diallel grafting model enabled partitioning of total variance into several sub-components. The variance due to specific compatibility ability was not significant for any of the measured traits. Decomposition of the reciprocal variance revealed that significant reciprocal effects were mainly due to significant maternal (rootstock) effects. The key finding is that, for any scion, the most precocious clone is obtained by grafting on high vigour rootstock varieties.

Clarifications on the intersectional MAIHDA approach: A conceptual guide and response to Wilkes and Karimi (2024)

Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) has been welcomed as a new gold standard for quantitative evaluation of intersectional inequalities, and it is being rapidly adopted across the health and social sciences. In their commentary “What does the MAIHDA method explain?”, Wilkes and Karimi (2024) raise methodological concerns with this approach, leading them to advocate for the continued use of conventional single-level linear regression models with fixed-effects interaction parameters for quantitative intersectional analysis.In this response, we systematically address these concerns, and ultimately find them to be unfounded, arising from a series of subtle but important misunderstandings of the MAIHDA approach and literature. Since readers new to MAIHDA may share confusion on these points, we take this opportunity to provide clarifications. Our response is organized around four important clarifications: (1) At what level are the additive main effect variables defined in intersectional MAIHDA models? (2) Do MAIHDA models have problems with collinearity? (3) Why does the Variance Partitioning Coefficient (VPC) tend to be small, and the Proportional Change in Variance (PCV) tend to be large in MAIHDA? and (4) What are the goals of MAIHDA analysis?

Environmental heterogeneity caused by large-scale cultivation of Pyropia haitanensis shapes multi-group biodiversity distribution in coastal areas

The response of marine biodiversity to mariculture has long been a research focus in marine ecology. However, the effects of seaweed cultivation on biological community assembly are poorly understood, especially in diverse communities with distinct ecological characteristics. In this study, we used environmental DNA metabarcoding to investigate the spatial distribution patterns of bacterial, protistan, and metazoan diversity, aiming to reveal the mechanisms of community assembly in the Pyropia haitanensis cultivation zone along the Fujian coast, China. We found that, compared with the biological communities in control zones, those in P. haitanensis cultivation zones exhibited stronger geographic distance-decay patterns and displayed more complex and stable network structures. Deterministic processes (environmental selection) played a more important role in the assembly of bacterial, protistan, and metazoan communities in P. haitanensis cultivation zones, especially metazoan communities. Variance partitioning analysis showed that environmental variables made greater contributions to the diversity of the three types of communities within the P. haitanensis cultivation zones than in the control zones. Partial least squares path modeling analysis identified nitrate‑nitrogen (NO3-N), pH, particulate organic carbon (POC), and dissolved organic carbon (DOC) as the key environmental variables affecting biodiversity. Overall, the environmental heterogeneity caused by the large-scale cultivation of P. haitanensis could be the crucial factor influencing the composition and structure of various biological communities. Our results highlight the importance of the responses of multi-group organisms to the cultivation of seaweed, and provide insights into the coexistence patterns of biodiversity at the spatial scale.