Fusarium head blight (FHB) is a major threat for wheat production worldwide. Most reviews focus on Fusarium graminearum as a main causal agent of FHB. However, different Fusarium species are involved in this disease complex. These species differ in their geographic adaptation and mycotoxin profile. The incidence of FHB epidemics is highly correlated with weather conditions, especially rainy days with warm temperatures at anthesis and an abundance of primary inoculum. Yield losses due to the disease can reach up to 80% of the crop. This review summarizes the Fusarium species involved in the FHB disease complex with the corresponding mycotoxin profiles, disease cycle, diagnostic methods, the history of FHB epidemics, and the management strategy of the disease. In addition, it discusses the role of remote sensing technology in the integrated management of the disease. This technology can accelerate the phenotyping process in the breeding programs aiming at FHB-resistant varieties. Moreover, it can support the decision-making strategies to apply fungicides via monitoring and early detection of the diseases under field conditions. It can also be used for selective harvest to avoid mycotoxin-contaminated plots in the field. Triticum L. 1753) is a member of the grass family Poaceae with different cultivated species, mainly the tetraploid durum wheat Triticum durum 2n = 28 with the genome set AABB and the hexaploid wheat Triticum aestivum 2n = 42 with the genome set AABBDD  asodochium . The maicotoxins .Fusarium mycotoxins and the effect of Fusarium head blight on wheat yield, it is important to integrate plant protection practices such as crop rotation, resistant varieties, and cultural practices up to the application of fungicide within the management strategy. To safeguard wheat yield and to produce products with high quality especially, the application of fungicides is necessary under certain environmental conditions. To increase knowledge about the relevant parameters of the epidemiology and to perform knowledge-based plant protection measures, it is important to investigate and develop new methods to predict and detect FHB epidemics early on cereals [Because of the high toxicity of  cereals . This isFusarium spp. and wheat plants. It was efficiently used in quantifying wheat resistance to FHB [Fusarium infection and mycotoxin contamination of wheat kernels and flour [Besides direct control, a highly effective strategy to control FHB is breeding varieties with appropriate resistance against this disease complex. Effective cultivar development needs interdisciplinary research, integrating plant breeding, phytopathology, and informatics. It also needs precise and innovative methods for identifying and characterizing disease symptoms at an early stage of pathogenicity . Becausee to FHB , the assnd flour , and, cond flour .Fusarium graminearum as the main causal agent of FHB on wheat; therefore, this review summarizes the Fusarium species involved in the FHB disease complex with the corresponding mycotoxin profiles, disease cycle, and diagnostic methods. In addition, it displays the history of FHB epidemics, and the management strategy of the disease. Moreover, it discusses the role of remote sensing technology in diagnosing and phenotyping the disease symptoms on wheat spikes.Most available reviews focus on Fusarium mycotoxin contamination in European wheat during the years 2010–2019; however, there is a lack of data on FHB incidence in Europe [The frequency of FHB epidemics has increased in the last decades due to the changes in agricultural practices, mainly the zero tillage regime in wheat fields, in addition to the increase in the area of wheat cultivation and the frequency of wheat in the crop rotation ,18. The n Europe . Seven sn Europe . In Canan Europe . In the n Europe . In the n Europe . In Latin Europe . Furthern Europe . InformaFusarium was recognized as a unique name for all species including teleomorphs, which means that the name Gibberella and other names are not accepted anymore to indicate the sexual stage of these pathogens [Microdochium were elevated to species in 2005 and have become the accepted taxonomy. The following scheme shows the taxonomical position of the genus Fusarium and Microdochium according to the MycoBank database, 2022 [Since 2013, and after the changes in the International Code of Nomenclature for fungi, the name athogens . In addise, 2022   at C8 of trichothecenes backbone in trichothecenes B while it is absent in trichothecenes A [in Animalia compared with trichothecenes B; however, in Planta, trichothecenes B are more toxic [F. acuminatum, F. equiseti, F. graminearum, F. poae, F. sambucinum, and F. sporotrichioides. Trichothecenes B include nivalenol (NIV), 4-acetyl-nivalenol (4-ANIV), deoxynivalenol (DON), 3-acetyl-deoxynivalenol (3-ADON) and 15-acetyl-deoxynivalenol (15-ADON). Fusarium species that produce trichothecenes B are F. acuminatum, F. crookwellense, F. culmorum, F. equiseti, F. graminearum, F. poae, F. sambucinum, F. semitectum, and F. sporotrichioides  in α- and β- derivatives [in Planta or in Animalia compared with trichothecenes [Fusaria involved in zearalenone production are F. crookwellense, F. culmorum, F. equiseti, F. graminearum, F. semitectum, and F. sporotrichioides  and matrix-associated mycotoxins . The maiThere are different methods to diagnose the fungal pathogens involved in FHB on wheat. The classical method is pathogen re-isolation on selective media and identifying the fungus based on the morphological characteristics of the spores or the colony. The immunological method uses specific antibodies against a specific protein or protein complex produced by the fungus. However, the most specific method is the molecular method using specific primers that target a specific region in the DNA of the fungus.Fusarium species can be diagnosed based on the visual and microscopical characteristics of the colony and the spores after re-isolating the fungus on selective medium. Different media showed selectivity to Fusarium spp., e.g., Czapek Dox iprodione dichloran agar (CZID), dichloran-chloramphenicol peptone agar (DCPA), malachite green agar (MGA 2.5), modified Czapek Dox agar (MCz), Nash and Snyder medium (NS), and potato dextrose iprodione dichloran agar (PDID). However, MGA 2.5 was recommended as a selective medium for Fusarium re-isolation from naturally infected kernels [Fusarium species was possible based on their pigmentation on CZID [Burkholderia glumae showed selectivity to Fusarium species [ kernels . Further on CZID . Recentl species . HoweverFusarium using poly- or monoclonal antibodies. These antibodies are obtained after immunization of animals or cell lines by exoantigens secreted by Fusarium [Enzyme-linked immunosorbent assay (ELISA) is used as a diagnostic method for Fusarium ,103. HowFusarium .Thermus aquaticus in 1988. This allowed automated thermal cycling and abolished the need for enzyme refreshment after each cycle [Fusarium species involved in FHB (F. lateritium and F. semitectum showed cross-hybridization with other Fusarium species [The polymerase chain reaction (PCR) was invented in 1984 and became widely used in plant pathogen detection and quantification with high sensitivity and specificity ,106. Thech cycle . The PCRch cycle . Differed in FHB . However species .Fusarium species, which serves as a source of the inoculum, and reduced tillage helps to keep this source available during wheat vegetation. In addition, wheat comes very often after maize in the crop rotation, which increases the disease incidence during the availability of the inoculum. Secondly, the visible FHB symptoms appear on wheat spikes at a later stage of pathogenicity, and during this stage, it is too late for fungicide application because the kernels have been contaminated with Fusarium mycotoxins. In addition, traditional disease control using fungicides involves different disadvantages mainly costs, bio- and eco-hazards, relatively short lifetime due to fungicide resistance, and low availability for smallholder farmers. Moreover, the environment and health protection measures lead to continuous regulatory changes regarding the availability and applicability of fungicides [The effective management of FHB is challenging due to several factors. Firstly, maize intensification and reduced tillage increased the frequency of FHB epidemics during the last decades. This is because maize is the main host of ngicides . This shFusarium species, such as maize and barley. This practice prohibits perithecia formation and ascospore discharge during wheat spike development [Adopting moderately resistant varieties combined with variety rotation and using varieties with different maturities in addition to spreading anthesis times by disseminating planting dates showed efficiency in FHB control ,124. In elopment ,125. Anoelopment .Components of wheat resistance to FHB include passive resistance represented by morphological and phenological features and active resistance represented by physiological features . MorpholWheat resistance to FHB is a quantitative trait, which means that many genes with cumulative effects are involved in this trait. Environmental conditions have a significant effect on this trait resulting in various resistance levels in different environments . Durum wFusarium species or biological secondary metabolites to control FHB on wheat. These microorganisms can be applied to the residues of the previous crop to inhibit perithecia development or directly to wheat spikes. For example, bacteria from Bacillus spp., Lysobacter enzymogenes, Pseudomonas spp. and Streptomyces spp., and fungi from Aureobasidium pullulans, Clonostachys rosea, and Trichoderma spp. showed effectivity against Fusarium [Clonostachys rosea was applied on wheat residues infected with different Fusarium species under field conditions. Fusarium growth measured as fungal DNA reduced between 68 and 98% after 90 days of treatment and was undetectable after 180 days [Aureobasidium proteae, Phoma glomerate, and Sarocladium kiliense, with a high protection ratio between 75 and 100% on detached wheat spikelets. The basidiomycetous yeast Cryptococcus nodaensis OH 182.9 was isolated from wheat anthers [F. graminearum on detached wheat spikes. Six isolates were shown to inhibit F. graminearum growth while the strain XS-2 of Bacillus amyloliquefaciens reduced disease severity on detached wheat spikes significantly. In vitro, B. subtilis SG6 inhibited F. graminearum growth, sporulation, and DON concentration with ratios of 88, 96, and 100%, respectively, while in the field, the same strain significantly reduced disease incidence, FHB index, and kernel DON contamination when it was applied from anthesis until soft dough [Sinapis alba) and Chinese galls (Rhus chinensis) against F. graminearum in vitro. All these compounds fully inhibited mycelium growth, conidial, and ascospore germination. Moreover, they reduced perithecia formation and ascospore discharge up to 50 and 6%, respectively.Biological control uses microorganisms antagonistic to Fusarium . The fun180 days . Comby e180 days  reported anthers . This is anthers ,144. Zha anthers  isolatedft dough . The usaft dough . It alsoft dough . Drakopoft dough  tested bEffective chemical control of FHB should be combined with other management practices ,150. TheFusarium species, inoculum availability, resistance degree of the cultivated wheat variety, anthesis period, and the previous crops in the surrounding area. In addition, information about favorable weather conditions  for FHB incidence during wheat vegetation are required as input data for these models. These two practices could be effective tools to prevent quantity and quality losses in wheat yield caused by FHB. These models can be supported or improved by innovative digital technology and remote sensing data to realize knowledge-based plant protection management.One of the prediction practices is risk assessment using disease prediction models based on weather conditions and the history of FHB epidemics in the growing region . In addiOptical sensors are among the remote sensing technologies that have been widely investigated in monitoring plant diseases as well as in plant phenotyping . These sSpectral sensors acquire the spectral reflectance of the object. Based on the number of recorded wavebands, these sensors are classified as multispectral sensors and hyperspectral sensors. Multispectral sensors record the spectral reflectance of individual wavebands  , while hThe main flaw of using hyperspectral imaging sensors in plant-disease detection is data complexity. To reduce data complexity, spectral vegetation indices (SVIs) can be derived from the spectral data based on a ratio between individual wavebands. Each of these indices can be used as an indicator of a specific compound of the plant which might be affected during the pathogenicity . This data can be utilized in plant-disease detection using supervised or unsupervised machine learning methods. Reducing data complexity reduces calculation time and improves the accuracy of the machine learning approach in plant-disease detection .Fusarium-infected wheat spikes based on the mean spectral signature and the SVIs derived from the mean spectral signature of the spikes. They reached an accuracy of >93% in the period 8–17 days after inoculation. In addition, it was possible to rank wheat varieties automatically according to their resistance to FHB using a non-metric multidimensional scaling approach based on the SVIs of the spikes [Fusarium infection and mycotoxin contamination on the kernel and flour scale. This can accelerate the kernel sorting procedure by replacing the laborious and cost-effective chemical methods [Bauriegel et al.  investige spikes . Moreove methods ,159.2 = 0.97.Under field conditions, Ma et al.  used the2 = 0.88 were also developed based on UAV hyperspectral images to detect FHB under field conditions [Unmanned aerial vehicles (UAVs) are an effective and flexible tool for acquiring high resolution images of a large acreage in a short time and with low costs. Zhang et al.  used UAVnditions ,166.Infrared thermography determines the plant temperature which reflects the water status of the plant. Plant pathogens influence the water balance in the plant tissue and this effect can be indirectly measured and visualized as a false-color image by IRT . Maximum0) is the minimum value of fluorescence for dark-adapted PSII after excitation with low-intensity light but not enough for electron transport through PSII. The maximum fluorescence (Fm) is the maximum value of fluorescence for dark-adapted PSII after excitation with a saturating pulse. The variable fluorescence (Fv) represents the difference between Fm and F0, while the ratio Fv/Fm represents the maximum quantum yield of PSII photochemistry with a constant value of ≈0.83 for healthy plants [Chlorophyll fluorescence imaging assesses the status of photosystem II (PSII) of the plant . The basy plants . FHB infy plants ,170,171.The damage caused by FHB includes yield losses and contamination of wheat kernels with mycotoxins. Therefore, applying fungicides at an early stage of pathogenicity should be considered in the management strategy of the disease . This, iFormer studies successfully implemented HSI and CFI to detect and discriminate healthy and FHB-infected spikes ,170. MahFusarium species [Based on the SVIs of wheat spikes, it was also possible to discriminate between healthy and FHB-infected spikes as well as spikes infected with different  species . Using SHigh yielding varieties with sufficient resistance to FHB are required to reduce yield losses and the use of plant protection chemicals substantially. Besides yield and disease resistance, different plant traits  have to be assessed simultaneously. from this point of view, using optical sensors, especially multi- and hyperspectral imaging sensors in phenotyping, can provide an objective assessment for plant traits in addition to reducing time and labor in the field .Alisaac et al.  designedFusarium DNA and mycotoxin content in wheat kernels. However, the quantification methods are destructive, time-consuming, laborious, and expensive [Fusarium species [Fusarium DNA contents. Moreover, this technology will reduce the costs, labor, and time required for wheat kernel phenotyping against FHB.Another factor to be considered in the breeding programs is kernel phenotyping for infection and mycotoxin contamination. This needs the quantification of xpensive . HSI pro species . ApplyinIn summary, combining different control measures has been shown to be an effective tool in the integrated disease management of FHB. These control measures must be considered before and after planting wheat. Before planting, applying suitable cultural practices and planting resistant varieties play a significant role in reducing disease incidence and severity. However, predicting and monitoring the disease will help in the decision making to apply biological and chemical control products during the growing season. In addition, selective harvesting by avoiding mycotoxin-contaminated plots is a useful tool to reduce mycotoxin contamination in harvested kernels. From this point of view, optical sensors, mainly IRT and HSI, are promising tools to monitor FHB infection on wheat.


In a mainstreaming pathway, nongenetic healthcare professionals, such as surgeons and nurses, provide pre-test genetic counseling.2 For a pathway to be sustainable, it is important that these nongenetic healthcare professionals feel confident and capable to provide pre-test genetic counseling themselves. Thus far, experiences have been evaluated primarily for healthcare professionals working in ovarian cancer care.Germline genetic testing of patients with breast cancer provides valuable information for patients and family members; however, currently not all patients eligible for genetic testing are being tested.3 The results of this study show that these healthcare professionals have a positive attitude, and feel confident and capable to provide pre-test genetic counseling themselves with an acceptable time investment (< 15 min per patient). Moreover, they appreciated the online training. Thus, this study shows that healthcare professionals, working in a surgical department in particular, are well suited to provide pre-test genetic counseling themselves after completing concise training.We implemented a mainstream genetic testing pathway for breast cancer, including online training for healthcare professionals, and evaluated the attitudes and experiences of 70 surgical oncologists, nurse specialists, and nurses both before and after implementation.4 the need for genetic testing by medical oncologists is also expected to increase and future studies should focus on their experiences. Taking into account the various barriers and facilitators,5 mainstreaming initiatives may be a valuable adaptation in making germline genetic testing accessible to all eligible breast cancer patients. In addition, the experiences from these healthcare professionals provide valuable insights for mainstream genetic testing for other types of cancer. Future research should investigate whether mainstream genetic testing leads to higher testing rates.This study shows that mainstream genetic testing can be successfully implemented in breast cancer care and especially in surgical departments. As poly(ADP-ribose) polymerase (PARP) inhibitors are expected to be used more frequently in the future,


The Chengdu–Chongqing urban agglomeration (CCUA), as the only national-level city cluster in southwestern China, serves as a strategic support for the Yangtze River Economic Belt and an important demonstration area for promoting new urbanization in the country. The study of the networked characteristics of the CCUA contributes to a systematic understanding of its spatial connectivity patterns, optimization of spatial structure and layout, and promotion of high-quality regional development. In this study, we constructed models for traffic flow, information flow, migration flow, and composite flow to calculate the strength of connections between cities and the total flow of various elements in the CCUA. ArcGIS spatial visualization tools were used to depict the spatial connectivity patterns of the element flows within the CCUA. Additionally, social network analysis methods, including network density, centrality, and cohesive subgroups analysis, were employed to reveal the spatial network structure characteristics of the CCUA. The findings are as follows: (1) The overall structure of the cities within the CCUA is relatively loose, with significant differences in connectivity strength. It exhibits a west-strong and east-weak pattern, with Chengdu-Chongqing, Chengdu-Deyang, Chengdu-Mianyang, and Chengdu-Meishan occupying the top tier, while Zigong and Ya'an have relatively weak connections with other cities. Chengdu and Chongqing have prominent positions in the CCUA, with Chengdu having a more prominent core position compared to Chongqing, resulting in an overall hierarchical distribution of “1 + 1+7 + 7”. (2) The network density of the element flows in the CCUA is relatively low, indicating a generally weak element connectivity. The centrality of cities other than Chengdu and Chongqing is at a moderate to lower level, suggesting a weak overall resource connectivity capacity in the CCUA. (3) Most cities tend to form cohesive subgroups based on geographic proximity, while the cohesive subgroup in Chongqing is still in its early stages of development due to administrative boundaries. The research results quantitatively depict the spatial network structure characteristics of the CCUA, providing theoretical references for its development. They consist of core cities and some affiliated cities and have a profound impact on urban planning, economic geography, and regional economics . The CheAs urbanization progress, the flow of elements between cities intensifies, resulting in increasingly intricate and interconnected city network . PreviouExisting studies on the CCUA have analyzed it using single or multi-dimensional element flows. For example, Zhao et al.  and WangThe coordinated development among cities within urban agglomerations or provincial regions remains an unresolved issue. Currently, there are three main knowledge gaps: 1) Most studies on urban network spatial structures focus on single flow elements and do not utilize composite flow analysis; 2) Existing research predominantly relies on statistical yearbook data to analyze the economic connectivity patterns within urban agglomerations, neglecting the use of flow spatial data; 3) There is limited research that simultaneously considers traffic flow and migration flow to study the spatial structure characteristics of urban agglomerations, which encompasses both population mobility and traffic volume. To address these gaps, this paper conducts a literature review to analyze existing research achievements on urban spatial structures, the progress and frontier issues of studying urban spatial structures from the perspective of element flows were identified. Furthermore, the research perspectives, methods, tools, and approaches used by previous researchers were understood, serving valuable references and insights for further research, expanding ideas and methods.In this paper, CCUA is selected as the research area, building upon existing studies . Three fThe fifth part concludes the paper and offers discussions. Analyzing the spatial network structure of the CCUA from a flow perspective holds significant important for deepening our understanding of the urban connectivity pattern in the CCUA. It contributes to optimizing the spatial structure and layout of the Chengdu-Chongqing Economic Circle, promoting high-quality and coordinated regional development, and servers as reference for studying the urban network structure of other urban agglomerations.2World-class urban agglomerations thrive due to the radiation of core cities and the establishment of a “multi-polar support” system for coordinated development among cities of different sizes . PromineChengdu and Chongqing, as the core cities of the CCUA, have faced challenges due to their predominant competition rather than cooperation, resulting in a development setback. Their capacity to attract resources outweighs their ability to distribute them, leading to an imbalanced pattern known as “dual core dominance” and a subsequent “central collapse” within the CCUA . However33.1The comprises 15 cities in Sichuan and 27 districts and counties in Chongqing. Chengdu and Chongqing, as the core cities, share similarities in population, economy, and transportation facilities . However3.2http://index.baidu.com) provided the information used to represent the information connection between the two cities, using search index data up to August 21, 2019. Data on bus frequency were obtained from the bus network (http://checi.cn/), while ordinary train and high-speed rail passenger frequency data were sourced from the Shengming Timetable. Population migration data were acquired from the Tencent location big data platform (https://heat.qq.com/). It is important to note that the Tencent platform only publishes the top 10 move-in and move-out records for each city, but additional data can be supplemented using move-out and move-in records from other cities beyongd the top 10. For this analysis, data on residents' migration between the 16 cities within the CCUA were collected from January 1, 2019, to August 21, 2019.The data used were sourced from various platforms. The baidu index data analysis platform AHP. It is a subjective weighting analysis method utilized to address the challenges of determining the relative importance of multiple objectives. It quantifies the weights by assessing the relative importance of each objective and employs these weight values to effectively compare their importance. A hierarchical structure model is established, judgment matrices are constructed, and hierarchical single ranking and consistency tests are conducted to ultimately determine the weight .(2)CRITIC method. It is an objective weighting method employed when multiple targets face challenges in effectively measuring the relative importance due to data differences. This method derives the importance of target data bythoroughly exploring and utilizing its own attributes, assigning corresponding weight values to compare the order of importance among various targets. The final weight are determined through dimensionless processing of indicators, calculation of index variability, index conflict, and information amount .(3)Game theory empowerment. The weights obtained through different weighting methods may exhibit significant differences or even conflicts. Therefore, a consistency test of weights is conducted prior to the weighting of game theory combinations. The distance function used for this purpose is as follows:This paper employs the game theory combination weighting method ,34, incoTo minimize the deviation between the combined weight w and the two types of weights Qij is the composite connection strength of city i and city j; Qi is the total amount of composite flow of city i; and Tij’, Cij’, and Lij’ represent the result of normalized connection strength of traffic, information, and migration flow between city i and city j.The formula for calculating the connection strength and total amount of composite flow is as follows:3.3.5Social network analysis is widely utilized to study urban spatial network structures. In the article “Vital Nodes Identification in Complex Networks” , the ideIt is important to note that traditional centrality indices were chosen in this study due to their effectiveness in addressing our specific research question. Centrality indices are widely acknowledged as valuable tools for assessing the significance of nodes in various flows and the dissemination of influence throughout a network. By employing these indices, we can gain insights into the relative importance and interconnectedness of nodes in urban networks, thereby illuminating the spatial structure and functional distribution of cities. While network analysis continues to evolve, the selection of traditional centrality indices aligns well with the objectives of this study.44.1The ArcGIS spatial analysis function was utilized to visualize the connection strengths between cities in the CCUA. Employing the natural breakpoint classification method, the connection strengths of the cities in the CCUA were categorized into four levels. The results show that the spatial network structure of the CCUA revolves around Chengdu and Chongqing as the core cities, with notable variations in connection strengths among the cities, indicating significant spatial differentiation .Fig. 3Sp4.1.1The traffic flow is determined using 4.1.2The calculation of information flow is carried out employing 4.1.3The migration flow within the CCUA is quantified using 4.1.4Using the game theory combination weighting method as prescribed by 4.24.2.1The network densities of traffic flow, information flow, migration flow, and composite flow are 0.25, 0.262, 0.246, and 0.258, respectively. Theses relatively low densities suggest that the flow space network within the CCUA is in its early stage of development, and the connections between cities are relatively loose.Cities play a crucial role as nodes in the formation and development of the urban network. They determines the direction and strength of element flows and influence the overall development and trends of the city network . In Fig.4.2.2Centrality is a measure of an individual's influence within a network. In directed networks, a high in-degree indicates strong agglomeration ability, rendering the actor more “important”. Conversely, a high out-degree signifies greater radiation capability, making the actor more “influential” .The point-in degree measures node agglomeration ability. Notably, as depicted in The point-out degree quantifies node radiation capability. Chengdu and Chongqing possesses relatively high point-out degrees, suggesting that their transportation, information flow and population migration exert a substantial influence on other cities, thereby enhancing the overall levels of urban traffic, information, and population migration within the CCUA. On the other hand, Zigong, Deyang, Leshan, Yibin, Meishan, Dazhou, Ya'an and Ziyang exhibit relatively low point-out degrees, indicating that these cities have limited impact on other cities in terms of traffic, information flow, and population migration. Due to their smaller economic size and weaker radiation capacities, their contributions to the overall improvement of urban transportation, information, and population migration levels within the CCUA are minimal.4.2.3In a network, each node has a unique betweenness centrality, with the node possessing the highest betweenness centrality occupying a core position. As indicated in 4.2.4Closeness centrality measures the extent to which a city operates independently of others. As illustrated in 4.3Cohesive subgroups represent cities that are closely interconnected within the city network, revealing clustering patterns within the network. Based on the analysis results shown in In the traffic flow network, subgroup 1 , subgroup 2 , and subgroup 3  consist of 3 or 4 cities, highlighting close connections within each subgroup that contribute to the development of the CCUA. Subgroup 4  comprises only two cities, exhibiting a simpler network structure and sparse connections. Chengdu and Chongqing, being the two core cities, enjoy better transportation accessibility and do not form cohesive subgroups with other cities. The connections between Ya'an and other cities are weak and require improvement.In the information flow network, subgroup 1 , subgroup 2 , and subgroup 3  consist of 3 or 4 cities, indicating strong connections within each subgroup. Subgroup 4  comprises only 2 cities with a simpler network structure. Chengdu and Chongqing have closely connections with other cities and receive significant attention, not forming cohesive subgroups. Yibin receives relatively little attention and has limited connections with other cities, resulting in relative isolation within the subgroup.In the migration flow network, subgroup 1 consists 5 cities, namely Nanchong, Guang'an, Dazhou, Suining, and Ziyang, indicating closely connections and high network density. Subgroup 2 , Subgroup 3 , Subgroup 4 , subgroup 5 , and subgroup 6  each contain 2 cities, suggesting relative sparse network connections. Chongqing, as a core city of the CCUA, has close connections with other cities and does not form a cohesive subgroup. Chengdu forms a cohesive subgroup with Ya'an, highlighting Chengdu's radiating and driving effect on Ya'an.In the composite flow network, subgroup 1 comprises 4 cities . Subgroups 2  and 3  consist of 3 cities, showcasing close interconnections. Subgroups 4 (Meishan and Leshan) and 5 (Chengdu and Ya'an) contain two cities, with sparse connections between them. Chongqing and Deyang did not form cohesive subgroups.Cities tend to form cohesive subgroups with nearby cities, and cities within a subgroup exhibit closer relationships than those outside the subgroup. Cohesive subgroups do not typically cross administrative boundaries, indicating limited cohesion between cities in Sichuan and Chongqing. In the CCUA, there are few core cities with strong spatial correlations, and isolated cities still exist. The subgroups are in the early stage of development with relatively simple structures. Therefore, it is crucial to strengthen cooperation between cities in the CCUA, leverage the leadership roles of Chongqing and Chengdu, and promote accelerated development in densely populated areas such as Zigong, Neijiang, Luzhou, Yibin, Nanchong, Suining, and Guang'an. Additionally, the cohesive subgroup structure within the CCUA should be optimized, enhancing connectivity, stability, narrowing the gaps between cities, and promoting balanced developmentd.55.1(1)The composite flow network in the CCUA aligns closely with individual element flow network, particularly traffic flow. Each city exhibits varying connectivity levels with others at different element flow levels. The urban agglomeration demonstrates significant polarization, with Chengdu and Chongqing occupying dominant positions. Chengdu's influence surpasses that of Chongqing, reflecting a hierarchical distribution of “1 + 1+7 + 7". Connection strength varies spatial, with stronger connections in the west compared to the east. Besides Chengdu–Chongqing, other notable connections include Chengdu–deyang, Chengdu–Mianyang and Chengdu–Meishan, forming the primary level of connections. Overall, the urban spatial connections within the CCUA is relatively loose. Administrative boundaries constrain Chongqing's connections, limiting strong cross-regional ties.(2)Element flow networks within the CCUA exhibit low density, indicating a loose overall structure and weak element connections. The flow space network of the CCUA is still in its early developmental stage. Chengdu demonstrates the highest connectivity, followed by Chongqing, while Ya'an exhibits the weakest connectivity. Chengdu and Chongqing exert significant influences and possess strong agglomeration capacities. Conversely, Deyang, Leshan, Meishan and Ya'an have limited connections and weaker agglomeration capacities. Chengdu and Chongqing have substantial impacts and strong radiation capacities, while Zigong, Deyang, Leshan, Yibin, Meishan, Dazhou, Ya'an and Ziyang have minimal influence and weak radiation capacities. For cities beyond Chengdu and Chongqing in the CCUA, centrality is at a lower-middle level, and the overall resource connectivity of the CCUA is weak.(3)The CCUA consists of five cohesive subgroups: two subgroups with two cities, two subgroups with three cities, and one subgroup with four cities. The network density is low, and connections between cities are sparse. Cities tend to form cohesive subgroups with closer geographic proximity, leading to stronger connections within subgroups. Cohesion subgroups do not cross administrative boundaries, and Chongqing dose not form a cohesive subgroup with cities in Sichuan province. The CCUA lacks there core cities with high spatial correlations, and isolated cities persist. The subgroups are in the early stage of development, exhibiting a simple structural composition.This study explores the urban network spatial structure in the CCUA from a multi-dimensional element flow perspective, yielding the following key findings:5.2Research on the spatial network structure of the CCUA has primarily focused on single-element flow analysis, emphasizing information flow, population migration flow and traffic flow. However, there is a lack of studies using a composite flow model to analyze the network connection patterns of the CCUA. Previous research based on information flow, using multi-year data to analyze changes in the spatial structure of the CCUA ,23, has Due to constraints in administrative boundaries and the unavailability of district-level data for Chongqing, our study focuses solely on Chongqing as a research unit, neglecting connections between districts and counties within Chongqing and weakening the strength of connections in the eastern part of the Chengdu-Chongqing region. However, previous studies analyzing the spatial structure of the CCUA have yielded similar conclusions, indicating strong connections between Chengdu and the main urban area of Chongqing and weaker connections with other districts and counties in Chongqing ,24,25,41Since Tencent's migration data are not public available, and complete data for the year 2019 is unattainable, we utilize 233 days of data. Most previous studies use average values over a specific time period to reflect city connections, while our study employs the sum of the 233-day data from 2019, providing a more representative approach to represent the spatial structure of the CCUA. Population migration network connections typically accompany traffic network connections since population movement requires transportation. Additionally, traffic network connections are often accompanied by information network connections, as individuals generally seek destination information before traveling. Therefore, information network connections have a certain supportive effect on transportation network connections. Future research should consider the overlapping nature of these three types of connection. Network connections between cities are influenced not only by information networks but also by traffic networks, population migration networks, and other factors. A comprehensive analysis of various networks can more accurately depict the spatial structure of an urban agglomeration.Utilizing Baidu Index to represent the intensity of information flow between cities has limitations as it primarily reflect users’ online interest in cities. However, it still offers a visually intuitive representation of city network connections and aligns with the current trends of utilizing big data in research. On one hand, it is indeed worth noting that numerous studies have effectively utilized Baidu Index to analyze the spatial network structure characteristics of city clusters. These studies highlight the value and maturity of this approach in understanding urban connections ,20. On tThe Chengdu Metropolitan Circle, centered around Chengdu and comprising Deyang, Meishan, and Ziyang, plays a crucial role in the development of the CCUA. Promoting the integration of Cheng-De-Mei-Zi is beneficial for the progress of the CCUA. From the perspective of composite flow connection strength, Chengdu-deyang and Chengdu-Meishan from the first level of connections, while Chengdu-Ziyang constitutes the second level, all exhibiting strong connections. In the future, it is essential to enhance Chengdu's role as a central city in terms of radiation and leadership, leverage the advantages of Deyang, Meishan, and Ziyang, and achieve coordinated development between large and small cities within the metropolitan circle. The spatial distribution of network connections between cities in the CCUA is unbalanced, yet a certain degree of spatial network structure has already formed. This study emphasizes that cities in the CCUA should not overlook the disparities among them while pursuing their individual development. For cities with weak element flow connections, it is crucial to more effectively embrace the radiation from core cities, consider their objective reality, make full use of their own advantages, and gradually narrow the gap with core cities. Chengdu and Chongqing still possess ample development space, and they should extend their radiation and influence to other cities enhancing their own growth and advancement.Data will be made available on request.Xiaohui Zhang: Writing – original draft, Visualization, Methodology, Formal analysis, Data curation. Jifei Zhang: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Ningaui timealeyi, and two native rodents, Pseudomys chapmani and P. hermannsburgensis. SNPs resolved subtle genetic structuring not detected by microsatellites, particularly for N. timealeyi where two genetic clusters were identified. Furthermore, stronger signatures of isolation‐by‐distance and isolation‐by‐resistance were detected when using SNPs, and model selection based on SNPs tended to identify more complex resistance surfaces  in the best‐performing models. While we found limited evidence for physical barriers to dispersal across the Pilbara for all species, we found that topography, substrate, and soil moisture were the main environmental drivers shaping functional connectivity. Our study demonstrates that new analytical and genetic tools can provide novel ecological insights into arid landscapes, with potential application to conservation management through identifying dispersal corridors to mediate the impacts of ongoing habitat fragmentation in the region.Landscape genetics is increasingly transitioning away from microsatellites, with single nucleotide polymorphisms (SNPs) providing increased resolution for detecting patterns of spatial‐genetic structure. This is particularly pertinent for research in arid‐zone mammals due to challenges associated with unique life history traits, such as boom‐bust population dynamics and long‐distance dispersal capacities. Here, we provide a case study comparing SNPs versus microsatellites for testing three explicit landscape genetic hypotheses  in a suite of small, arid‐zone mammals in the Pilbara region of Western Australia. Using clustering algorithms, Mantel tests, and linear mixed effects models, we compare functional connectivity between genetic marker types and across species, including one marsupial,  We evaluate landscape connectivity using two different genetic marker types across arid‐zone mammals, which are underrepresented in the landscape genetics literature. We find that topography, substrate, and soil moisture are the main environmental drivers shaping connectivity and that single nucleotide polymorphism (SNP) markers provide finer‐detailed ecological insight. To our knowledge, our study is the first to compare SNPs and microsatellites to empirically test isolation‐by‐resistance hypotheses. IncorpoLandscape genetics aims to determine how realized dispersal is influenced by the surrounding environment. It operates by examining genetic variation within heterogenous landscapes to explicitly quantify the effect of landscape composition and/or matrix quality (the space separating habitat patches) on an organism's dispersal, gene flow and/or spatial‐genetic structure  adapted to arid environments, including a carnivorous dasyurid marsupial: A previous study found limited evidence that the Pilbara landscape influenced patterns of genetic structure in these species , P. chapmani (Pc) and P. hermannsburgensis (Ph) were obtained from Levy et al. , 94 individuals for P. chapmani (Pc) and 179 individuals for P. hermannsburgensis (Ph). A total of 100–500 ng of genomic DNA was sent to DArT for library preparation and sequencing. Library preparation by DArTseq™ follows a reduced representation method with enzyme digestion (here PstI and SphI) followed by sequencing on an Illumina Hiseq 2500   were filtered in R version 4.1.2 , and two P. hermannsburgensis individuals . Locus quality filters were then applied to each data set based on thresholds for missing data , average total read depth , repeatability average (95%), and minimum minor allele frequency . Multiple SNPs per sequence were removed followed by linkage disequilibrium pruning. We calculated pairwise relatedness  to avoid biasing the genetic analyses with closely related individuals   identified through IBB analysis, described below.The raw SNP data sets  Wang, . We incl2.3dartr to identify natural genetic clusters in the data (based on Euclidean genetic distances). As a preliminary step, we visualized temporal patterns to ensure genetic structure was not related to sample collection year  when using the TESS3 algorithm in the R package tess3r  methods  taking geographic information into account   was presented, with the best value for K decided based on the presence of a plateau or change in slope in the cross‐entropy criterion.We tested 2.4P. hermannsburgensis individuals located on islands from IBD analysis and summary statistics, given the low likelihood that mainland and island individuals are randomly mating. IBD was investigated with Mantel tests in GenAlEx 6.5 . Summary statistics were then calculated in GenAlEx 6.5 within each genetic cluster, including the number of alleles (Na), observed heterozygosity (Ho), expected heterozygosity (He) and the fixation index (F). When more than one genetic cluster was detected, we also calculated FIS and FST.We performed tests for IBD and calculated population genetic summary statistics for each genetic cluster identified in the IBB analysis for both microsatellite and SNP data sets. Individuals were assigned to a genetic cluster if the corresponding admixture coefficient proportion was ≥0.7, while individuals were excluded from IBD and summary statistics if they fell below this threshold. We chose this somewhat arbitrary threshold to enable the representation of discrete populations for comparison and these individuals were not excluded from any other analyses. We also removed three 2.52 resolution due to the long‐range dispersal capacities of the focal species. For example, both Pseudomys species have displayed long‐range movements of several kilometers, with P. chapmani individuals found up to 2 km from neighboring mounds and P. hermannsburgensis recorded moving up to 14 km in a 2‐week period  with missing date information from this analysis. We also removed individuals located on islands (Ph = 3) from the analysis, as our aim was to explore how terrestrial landscape attributes influence gene flow . Shirk et al.   , 4925 (Pc) and 3638 (Ph). Microsatellite data sets included the same individuals to exactly match the individuals from the SNP data sets.After filtering, the final SNP data sets included 180 3.2N. timealeyi, SNPs resolved two genetic clusters that were not detected when using microsatellite markers , although with admixture between the two clusters , showing no obvious plateau or change in slope of the cross‐entropy criterion for increasing values of K  for both Pseudomys species  for the N. timealeyi SNP data set identified in IBB analyses, excluding the 23 admixed individuals that did not assign to either population. For the Pseudomys SNP data sets, and the microsatellite data sets for all three species, analyses included all individuals as a single genetic population (K = 1).Mantel tests and summary statistics were calculated across the total data set, as well as within the two genetic clusters  within almost all populations identified in IBB analysis for each marker type for all three species , the magnitude differed by a factor of approximately 1.5–3 between marker types for N. timealeyi  and P. chapmani , suggesting SNPs were better able to resolve patterns of IBD , potentially providing additional evidence for IBB.We detected significant IBD , followed by the other two species . Where population genetic structure was detected, genetic differentiation was low , terrain ruggedness (VRM) and a vegetation element , followed by soil moisture , and a minimal contribution by the vegetation element . For both models, landscape resistance decreased with increasing ruggedness and soil moisture, and increased as the specific vegetation cover/density (FOR vs. SPIN) increased  and weathering intensity  in a suite of small arid‐zone mammals possessing high dispersal capacities. In general, SNP markers provided additional resolution in detecting subtle genetic structuring in IBB analyses, particularly for the dasyurid, and resulted in stronger patterns of IBD and IBR in both rodent and dasyurid species. However, the large dispersal capacity and the dynamic nature of arid landscapes present specific challenges for IBR analyses, which we discuss below.4.1N. timealeyi, that was not detected with microsatellite data using the same individuals . The weak clusters detected in the SNP P. chapmani data set may reflect the accumulation of positive spatial‐genetic structure driven by the sociality of the species   than microsatellites, potentially reflecting the increased power of large SNP panels to detect subtle and complex patterns of functional connectivity. SNP models also revealed a stronger effect of landscape resistance on genetic distance and tended to better differentiate between the top models and the alternate IBD hypothesis, adding to the body of evidence arguing that SNPs provide better resolution for questions that require individual‐level genetic information, such as relatedness, individual identification and fine‐scale genetic structure . Simulation tools such as CDPOP , an arboreal mammal, will readily cross non‐forested habitat during dispersal and mating movements despite having home ranges tightly linked to forested areas. In the case of N. timealeyi, the increased complexity of rocky, rugged habitat and dense vegetation  may provide protection from predators during dispersal  models, this difference was slightly less pronounced for P. chapmani (particularly using the microsatellite data set), suggesting that functional connectivity is approaching IBD for this species. Still, our results indicated that increased rocky outcrops (lower weathering—SNPs) or increased rocky substrate (coarse fragments—microsatellites), and increased soil moisture (SNPs) facilitated landscape connectivity. This is biologically plausible since this species is a rocky habitat specialist, although our results suggest that due to the fragmented nature of rocky habitat in the Pilbara ; investigation (lead); visualization ; writing – original draft (lead); writing – review and editing . Kym M. Ottewell: Conceptualization (supporting); data curation (supporting); formal analysis (supporting); funding acquisition (lead); investigation (supporting); methodology (supporting); project administration (supporting); resources ; supervision ; writing – original draft (supporting); writing – review and editing . Peter B. Spencer: Conceptualization (supporting); funding acquisition (supporting); investigation (supporting); methodology (supporting); project administration (lead); resources ; supervision ; writing – original draft (supporting); writing – review and editing . Robyn E. Shaw: Conceptualization (lead); data curation (lead); formal analysis (lead); investigation (supporting); methodology (lead); supervision (lead); visualization ; writing – original draft (supporting); writing – review and editing (lead).https://github.com/RobynSh/LandGen_AridMammals) and have been archived in a Zenodo Digital Repository (Shaw, All data and R code are available from Github (ry Shaw, .This research is part of a collaborative project across academic, government and industry partners and addresses a priority concern by testing the methods being applied to the conservation of small mammals in the broader project. Benefits from this research accrue from the sharing of our data and results on public databases as described above.Appendix S1–S9Click here for additional data file.


Direct-to-consumer (DTC) genetic tests have generated considerable scholarly attention and public intrigue. Although the current consumer genetic testing regime relies on the reporting of individual variants of interest to consumers, there has recently been interest in the possibility of integrating polygenic scores (PGS), which aggregate genetic liability for disease across the entire genome. While PGS have thus far been extensively explored as clinical and public health tools, the use of PGS in consumer genetic testing has not yet received systematic attention, even though they are already in use for some consumer genetic tests. In this narrative review, we highlight the ethical, legal, and social implications of the use of PGS in DTC genetic tests and synthesize existing solutions to these concerns. We organize these concerns into three domains: (1) industry variation; (2) privacy and commercialization; and (3) patient safety and risk. While previously expressed concerns in these domains will remain relevant, the emergence of PGS-based DTC genetic tests raises challenges that will require novel approaches. Direct-to-consumer genetic tests allow consumers to access genetic testing without the direct involvement of healthcare providers ,2. By 20In this narrative review, we highlight the ethical, legal, and social implications of the use of PGS in consumer genetic testing and review various suggestions as to how these concerns may be addressed. We focus primarily on the implications of the use of PGS in common diseases of adult-onset , though the use of PGS-based genetic testing for embryo selection and prenatal testing poses important challenges of their own, some of which may overlap with those discussed here. We organize these concerns into three domains: (1) industry variation; (2) privacy and commercialization; and (3) patient safety and risk. Instead of taking a definitive stance on the immense complexities discussed below—particularly given the ongoing academic and industry efforts being brought to bear on improving the efficacy of polygenic risk scoring—this review seeks to synthesize existing scholarship and encourage scholarly and public engagement. Many previous models of DTC genetic tests were largely confined to monogenic testing or non-health-related ancestry evaluations. In contrast, the polygenic score is the latest iteration of a series of advances in genomics that has the potential to expand prevailing understandings of the scope and role of DTC genetic testing. Although some of the literature uses “polygenic risk score” and “polygenic score” interchangeably, we follow conventions that reserve the latter term to extend to a broader array of measures that may include rare as well as common variants , and tha® unveiled a PGS-based consumer report for type 2 diabetes. Myriad Genetics and Genomics PLC have incorporated PGS into their clinical risk models .,45.® conThough there is extensive literature on the sharing of information discovered from DTC genetic tests to family members, it is far less clear how PGS-based DTCs will change dynamics around responsibility for sharing of genetic information to family members. Recent work has demonstrated that depending on specified thresholds, high polygenic scores for certain traits may be correlated across siblings . Yet, be®’s breast cancer reports explicitly state that the three BRCA1/2 pathogenic variants being tested do not include other BRCA1/2 pathogenic variants relevant for breast cancer risk [Safety is a key concern for any medical intervention, and a significant literature has developed regarding the safety profile of DTC genetic tests, though more work is needed on whether findings on previous models of genetic testing apply to newer models that incorporate PGS. There is conflicting evidence regarding the health-promoting or health-detrimental impacts of monogenic DTC genetic tests. While some studies have shown that access to genetic health information can encourage patients to take greater control of their health, particularly in the context of cancer-disposing gene mutations, other studies have shown less conclusive results ,62,63. Pcer risk , it is uPolygenic scores throw a wrench into an already complex debate regarding genetic risk comprehension. First, PGS generally explain only a fraction of the heritability of a complex condition. Accordingly, some experts deflate the utility of PGS on this basis, arguing that other conventional risk factors may be more actionable. However, this is likely disease-dependent. For example, as reviewed by Wray et al., studies have demonstrated that PGS for some conditions  may already be a powerful tool for risk assessment, and in many cases improved the utility of existing risk assessment tools based solely on conventional risk factors . Further® have stated that their PGS-based tools are already accurate for individuals of non-European genetic ancestries [® currently provides information to consumers regarding groups for whom information about a given variant is most useful. For example, for the Late-onset Alzheimer’s Disease risk report based on the APOE gene, 23andMe® states that risk estimates may not be equally accurate across all ethnic backgrounds [Crucially, many scholars have urged the lack of generalizability of PGS across ethnicities, given that many large-scale genomics studies have been performed in European populations ,69. Thercestries ,70, attrcestries . Notablykgrounds .It is unclear, however, how this kind of approach should be tailored for PGS, where a complex interplay of factors may drive differences in accuracy of PGS for various groups, including (most prominently) lack of representation in genomic databases, differing allele frequencies, and others. Secondly, PGS-based stratification of consumers’ disease risks may impact consumer behavior. Although the several studies performed thus far on the impact of communicating polygenic disease risk on patient behavior revealed that polygenic risk may help to motivate positive health-seeking behavior in the context of cardiovascular disease ,50,51, tThirdly, consumers’ and health providers’ understanding of PGS and PGS-related results may be varied. Scholars have documented that while both specialist and non-specialist healthcare providers are generally better equipped than consumers to interpret traditional DTC genetic tests, there is a lack of research regarding whether providers’ self-efficacy may be equivalent for PGS-based genetic tests, or whether they believe PGS-based tests are practically relevant ,58,72,73Regulatory solutions to these safety concerns are important to consider. Although several federal agencies in the United States have taken a role in regulating consumer genetic testing in the past, it is unclear how the regulatory landscape will change in the face of widespread PGS-based consumer genetic testing and third-party interpretation. The Federal Trade Commission (FTC), US Centers for Medicaid & Medicare Services (CMS), and FDA have all played a role in overseeing consumer genetic testing ,33. The ® [The FDA regulates some DTC genetic tests as in vitro devices, but their oversight of DTC genetic testing has been varied. The first DTC tests approved for marketing by the FDA were from 23andMe® . Industr® . ® seems to be taking an approach not completely out of line with the general wellness claims for type 2 diabetes contemplated by the FDA. According to one source, 23andMe® allows consumers to see, for an imaginary pool of 100 individuals with PGS-based profiles similar to theirs, how the addition of risk factors such as weight and frequency of fast food consumption changes the probability of developing diabetes [Consistent with this claim, 23andMediabetes . Indeed,diabetes ,47,74. Sdiabetes .In one possible scenario, the question of whether the PGS-based tests are general wellness products may depend on how these other risk categories are reported, as well as what “risk cohort” a given patient falls into based on their PGS . In the In many ways, the ambiguity around the regulation of PGS-based DTC genetic tests was anticipated, including limitations of some existing frameworks for the regulation of DTC genetic testing as the line between monogenic and polygenic disease paradigms quickly became blurred . Indeed,Further scholarship and robust dialogue are needed regarding whether/how the FDA should have oversight over these tools, given that immediate regulation may not be the answer to every problem in this space . In the Over the long-term, more expansive non-regulatory solutions should also be considered. In many ways, PGS hold immense potential as a powerful tool in the DTC setting because it is the bridge between personalized and population medicine. Common variants and their effect sizes are difficult to understand in isolation, and PGS can only sensibly be estimated by aggregating findings from population studies. If the goal of DTC testing is to empower patients and to “democratize” medicine, then it will be important to understand the role of genomic information for individuals on their own terms given their unique circumstances, values, and preferences. The use of PGS in DTC genetic testing presents novel challenges that warrant further study and public involvement. We have highlighted three domains—industry variation; privacy, and commercialization; patient safety and risk—in which PGS-based testing will pose significant challenges and deviate from consumers’ previous engagement with DTC tests. While we did not perform a systematic literature search, we have carefully reviewed the published literature related to PGS since the initial advent of DTC genetic testing in the last decade and synthesized them into these domains. Research on PGS in DTC settings is in its nascent stages, and further studies on these domains is warranted, with a specific focus on quantifiable metrics to assess effects on consumer health-related behaviors.Although it will be important to establish robust guidelines for the use of PGS in consumer genetic testing, previous scholarship will still be useful in setting standards for PGS-based tests. Therefore, though regulators and researchers need to start off on the right foot, they need not start from scratch. At the same time, PGS-based consumer genetic testing will also stretch the use of genomics by the public beyond existing thresholds, necessitating robust cross-disciplinary efforts to ensure the safety and efficacy of these technologies. Novel participatory solutions to bolster public understanding of genomic technology should also be considered to empower consumers in efforts to democratize genomic technology safely and effectively. Some have argued that in the near future, as genomic testing gains currency as consumer products for a “price conscious, genetically literate, and busy world”, a significant portion of the public will have access to their whole genome sequences in a portable and mobile format . Indeed,More broadly, if empowering the general public to have agency over their genetic information is a key value for all stakeholders, then promoting increased genetic literacy will be a key bulwark  for protecting the interests of consumers. Deliberative forums in which experts, industry leaders, and most importantly—citizens and consumers—are convened to debate and understand the purpose and function of PGS-based technologies may be critical to empower the general public to understand these tools going forward, and can help to ease the transition if they begin to be incorporated into clinical systems. For instance, deliberation in citizens’ assemblies have recently been proposed to help resolve governance questions for thorny ethical issues arising in the context of other emerging technologies such as germline genome editing . Therefo


Quantitative genetics theory postulates that genetic variance in closed populations under directional selection can considerably decrease. As genetic variance directly influences selection response, animal breeders are actively monitoring its changes over time to ensure the sustainability of their breeding programmes. Here, we evaluated three different approaches to computing variance components over a period of twenty-three years in a commercial broiler (meat-type chicken) population undergoing multi-trait selection. Our results showed that the trajectory of variance components fluctuated, but no overall decline trend was detected. In light of these findings, we discuss the implications for the long-term sustainability of broiler breeding programmes.Monitoring the genetic variance of traits is a key priority to ensure the sustainability of breeding programmes in populations under directional selection, since directional selection can decrease genetic variation over time. Studies monitoring changes in genetic variation have typically used long-term data from small experimental populations selected for a handful of traits. Here, we used a large dataset from a commercial breeding line spread over a period of twenty-three years. A total of 2,059,869 records and 2,062,112 animals in the pedigree were used for the estimations of variance components for the traits: body weight  and hen-housed egg production . Data were analysed with three estimation approaches: sliding overlapping windows, under frequentist (restricted maximum likelihood (REML)) and Bayesian (Gibbs sampling) methods; expected variances using coefficients of the full relationship matrix; and a “double trait covariances” analysis by computing correlations and covariances between the same trait in two distinct consecutive windows. The genetic variance showed marginal fluctuations in its estimation over time. Whereas genetic, maternal permanent environmental, and residual variances were similar for BWT in both the REML and Gibbs methods, variance components when using the Gibbs method for HHP were smaller than the variances estimated when using REML. Large data amounts were needed to estimate variance components and detect their changes. For Gibbs (REML), the changes in genetic variance from 1999–2001 to 2020–2022 were 82.29 to 93.75 (82.84 to 93.68) for BWT and 76.68 to 95.67 (98.42 to 109.04) for HHP. Heritability presented a similar pattern as the genetic variance estimation, changing from 0.32 to 0.36 (0.32 to 0.36) for BWT and 0.16 to 0.15 (0.21 to 0.18) for HHP. On the whole, genetic parameters tended slightly to increase over time. The expected variance estimates were lower than the estimates when using overlapping windows. That indicates the low effect of the drift-selection process on the genetic variance, or likely, the presence of genetic variation sources compensating for the loss. Double trait covariance analysis confirmed the maintenance of variances over time, presenting genetic correlations >0.86 for BWT and >0.82 for HHP. Monitoring genetic variance in broiler breeding programmes is important to sustain genetic progress. Although the genetic variances of both traits fluctuated over time, in some windows, particularly between 2003 and 2020, increasing trends were observed, which warrants further research on the impact of other factors, such as novel mutations, operating on the dynamics of genetic variance. Breeding programmes strive for sustainable genetic progress across the traits that are part of the breeding goal. This progress depends on the parameters in the breeder’s equation, namely the selection intensity, accuracy, genetic variation, and generational interval . ConsideTheory postulates that genetic variation decreases under intense directional selection ,2. BulmeA [Computing genetic variances over time was proposed by Sorensen et al. (2001) . They esA ,10. WhenA . Thus, uA . FurtherA .The estimation of genetic parameters is sensitive to sample size , and large datasets are needed to ensure the accuracy of the estimation and to accurately identify changes in the genetic parameters. Datasets from chicken breeding populations have a sufficiently large size to monitor long-term genetic variances. For broiler (meat-type) chickens, body weight (BWT) and hen-housed egg production (HHP) are part of a broad and balanced breeding goal and represent the typical antagonism between growth and reproduction through a negative genetic correlation between them ,13. In aThe population analysed in this research comes from a maternal grandsire broiler line that has not undergone any introgression process, standing for a closed population. BWT and HHP records were provided by Aviagen Ltd.  from a pedigreed line spanning 23 years (from 1999 to 2022). The selection was performed from overlapping generations . BWT was recorded at 35 days of age, whilst HHP consisted of the total number of eggs collected between the 28th and 54th weeks of age. The final dataset included 2,059,869 animals with phenotype information and 2,062,112 animals in the pedigree. The data were divided into sliding overlapping windows, with a period of 3 years and an overlap of 2 years between subsequent windows. The descriptive statistics are outlined in 1 and 2 represent the BW and HHP traits, respectively; A bivariate model was used in the analysis to estimate all variance components, as follows:Data were assumed to be conditionally distributed asThe (co)variances were assumed to beASReml [RENUMF90, GIBBS2F90, and POSTGIBBSF90 from the BLUPF90 family programs [The estimation procedure, under a frequentist method, was implemented in ASReml  and convprograms  were uset time by partitioning the elements of an entire relationship matrix A into a set of individuals belonging to the population at t time. In a nutshell, variance components come from individuals that pertain to each overlapping window in the current study. Let t be the time for an overlapping window; then, the expected variances are obtained from the following equation:A from only animals of the overlapping window, A, from only animals of the overlapping window, and PedModule” of JWAS Software v.1.2.1 [A was computed using Colleau’s Algorithm, programmed in a custom Julia script variance components of a closed population, under directional selection, pertain to the base population or the first population before the selection process starts. The same method used in the sliding overlapping windows was carried out, but under a chain length of 112,400. Expected variances were computed according to the procedure described by Legarra 2016) , in whic , in whiript see . Colleaupedigree . By decol matrix ,18), the1 and BWT2 and between HHP1 and HHP2. For instance, when we compared the window “2006” vs. “2009”, we were using the years 2006, 2007, and 2008 in “2006” (for BWT1 and HHP1), and the years 2009, 2010, and 2011 in “2009” (for BWT2 and HHP2). The only link between the two windows was their relationship (pedigree). In the current study, we used the correlation for the same trait to indirectly infer likely changes in its genetic variance in an empirical approach, given the number of data, and generations [As an alternative approach to assess the changes in genetic variance over time, we evaluated two consecutive non-overlapping windows (of 3 years) while assuming the traits of the second window to be different and computing the covariance and genetic correlation among the four traits . A total of 19 such analyses were carried out to examine the changes in the genetic parameters and particularly the genetic correlations between BWTHerein, the main results are shown graphically to reveal the trends of each variance component .95%), and the mean and confidence intervals at 95% from using REML (frequentist). The estimates of genetic variance from REML, for the first (1999–2001), half (2009–2011), and end (2020–2022) year intervals, were 82.84, 109.85, and 93.68 decagrams squared for BWT and 98.42, 152.39, and 109.04 eggs squared for HHP, respectively. The Bayesian estimates were 82.29, 109.87, and 93.75 decagrams squared for BWT, and 76.68, 129.58, and 95.67 eggs squared for HHP, respectively. Genetic (co)variances between BWT and HHP were −48.77, −79.20, and −81.52 when using REML, and −17.86, −31.69, and −43.33 in the Bayesian analysis, respectively. Note that (co)variance estimates were almost double in REML those in the Bayesian analysis; in fact, HPD95% was wider for the estimates involving HHP. Despite that, the effective size of the sample, autocorrelation lag, and Geweke diagnostic ensured the convergence of chains.In the current study, genetic variances and parameters were estimated using two methods: frequentist and Bayesian statistics, under the overlapping window approach. 95% of the latter results was wide, in accordance with most HHP estimates.The heritability estimates of BWT were practically the same when using REML and Bayesian analysis a. The esThe variance component provided by MPE effects was also analysed. Its estimates for the first (1999–2001), half (2009–2011), and end (2020–2022) year intervals when using REML were 9.52, 11.27, and 6.05 for BWT, and 3.81, 23.08, and 6.53 for HHP, respectively. With the Bayesian approach, the estimates were 9.63, 11.36, and 6.53 for BWT, and 15.88, 32.74, and 12.64 for HHP, respectively. After 2017, the MPE variance dropped, registering lower values . This agThe residual and phenotypic variances presented the same pattern in both REML and the Bayesian analysis. The Bayesian posterior means of residual variances were 163.29, 142.10, and 157.92 for BWT in the first (1999–2001), half (2009–2011), and end (2020–2022) year intervals. The residual variances for BWT were steadier, whilst they tend to increase over time for HHP with values of 375.03, 470.05, and 510.62, respectively  in decagrams squared) of genetic variance, 11.91 ± 0.39 of MPE variance, and 165.31 ± 1.25 of residual variance. For HHP, the estimated genetic variance was 100.89 ± 23.56 (in eggs squared), the MPE variance was 26.75 ± 4.49, and the residual variance was 425.24 ± 11.06. The estimated covariances between the two traits were −44.44 ± 2.81 (genetic), 1.06 ± 0.67 (MPE), and −24.40 ± 2.31 . According to expected variance method, the expected reduction after 23 years of selection was at most 20% of the genetic variance of the base population a. The inA high correlation was found between the comparisons of overlapping windows using the same trait doubled as two correlated traits. For BWT, the minimum correlation was 0.86 in the comparison of 2007 vs. 2010. Indeed, no drastic changes in BWT were detected when using double trait covariance analysis . For HHPIn animal breeding, accurate and unbiased estimates of variance components are essential for the prediction of breeding values. These estimates are transient and can fluctuate over time. Therefore, monitoring them and obtaining up-to-date estimations are important steps to ensure long-term genetic improvement .The heritability estimate for BWT in this study (0.32) is similar to those found in commercial broiler populations at 5 weeks, of 0.320 and 0.329 in males and females . These rTo our knowledge, no estimations of variance components over time for antagonistic traits have been reported in commercial broiler breeding programmes, though, to date, only one study has focused on the dynamics of genetic variance of BWT over time . In that95%, given the small number of data samples and the large number of missing values compared to the records of the BWT dataset. The HHP heritabilities over time, ranging from 0.176 to 0.351 for REML and 0.154 to 0.325 for the Bayesian approach, were in agreement with those in the literature found for cumulative egg production from 3 to 6 months of laying (0.28) [The heritability estimates for HHP tended to be lower than those for growth traits. Our estimate, using all data available, was similar to those of other studies, where egg production was recorded at 40 weeks (0.11) , until 4g (0.28)  and at 4g (0.28) . Likewisg (0.28)  and 0.31g (0.28) . None ofRegarding the genetic covariance between BWT and HHP, its trajectory over time fluctuated; it seemed to be more stable until 2015, when it dropped, becoming more negative . The samThe trajectories of genetic variance for both traits fluctuated, as expected, but no overall decreasing trend was detected. The heritabilities presented a similar pattern to the genetic variance trajectories, especially for BWT .The results of variances estimated with pedigree spreading over the whole period revealed a slight increase in genetic variance, which became relevant in the last five overlapping windows. That was a peculiar result since the quantitative genetic view is typically that the amount of genetic variance will be reduced by inbreeding ,2. HowevWhen using the overlapping windows, the changes in the variance components over time were shown. However, this approach does not identify the main causes of the changes. Estimating expected variance is a way to find out how inbreeding influences the fluctuations in genetic variance. In our dataset, annual inbreeding accumulation was lower than 1% (or 0.006 per generation), i.e., below the threshold set by the FAO . TheoretIn practice, breeding companies control the inbreeding effect by implementing optimal contribution selection or by straightforward ad hoc restrictions on the inbreeding rate in truncation selection, e.g., no cousin mating  or avoidTheory postulates that the genetic (co)variance, heritability, genetic correlation, and selection response of a trait under direct selection are reduced, especially when one or a limited number of traits are considered. However, genetic variances could be less influenced when the selection is performed for multiple traits, and the selected population undergoes different selection pressures depending on each trait ,45. MoreIn practice, nucleus populations are continuously under selection for fitness, while family sizes are regulated to reduce variation and maintain Ne. Commercial poultry breeding goals have broadened since the 1970s, typically including 40 to 50 traits now . Even, tIn multi-trait breeding programmes, several traits may have an antagonistic relationship that can affect the long-term selection response if not appropriately managed. For instance, a negative high correlation (−0.92) between the number born alive and body weight at weaning in rabbits does not enable breeders to establish a feasible line selected for both traits (instead of creating independent lines) . HoweverAlthough adverse negative genetic correlation hinders responses to selection, poultry breeding schemes using broad and balanced breeding goals (multi-trait selection) have shown that favourable selection responses in antagonistic traits can be achieved . A plausThe three proposed approaches  are feasible strategies to monitor the dynamics of genetic variance. Estimates from overlapping windows use both phenotypic and pedigree data, rendering the approach more accurate since the expected variance method and double trait covariance analysis are based mainly on the pedigree information. The latter method enables us to corroborate the magnitude of changes in the genetic variance over time. In dairy cattle, the concern about genetic variance estimations brought about a method to approach trends in genetic variances over time and their tolerance values in the breeding programme, based on the estimates within strata using breeding values and prediction error variance (PEV) of Mendelian sampling deviations ,56. ThisOn the other hand, large datasets and bias are key factors to consider when estimating variance components, and estimates seem more susceptible when the selection includes further genomic information ,59. In pMonitoring the genetic variance is a key factor to be considered in poultry breeding programmes to assess breeding sustainability. The three approaches shown in the current study can highlight changes or loss in genetic variances. Overall, the results, in agreement with other studies, suggested that little variation was lost, implying that rates of genetic improvement can be sustained in the future .Monitoring genetic variance in the broiler breeding industry is an excellent strategy to ensure positive levels of genetic progress. The methods presented in this study can be extended to other traits in the breeding goal, provided datasets are large enough. Although genetic variances fluctuate over time, they may sometimes strikingly increase. In the current study, we found this happened particularly between 2003 and 2020, indicating suitable levels of maintenance of genetic variance. A suggestion is that other factors, such as a sufficiently high rate of de novo variation , can counterbalance the loss of variation, which warrants further studies to elucidate these factors contributing to novel genetic variance.


Acer yangbiense is a critically endangered plant species with extremely small populations (PSESP). However, no information was available on its seed germination and seedling growth in populations with different genetic characteristics. In this study, we investigated seed germination and compared the performance of 566 seedlings in 10 maternal half-sib families cultivated in Kunming Botanical Garden. The results showed that A. yangbiense seeds required an average of 44 days to start germinating, with a 50% germination rate estimated to take about 47–76 days, indicating slow and irregular germination. There is a trade-off between the growth and survival in A. yangbiense seedlings, with fast growth coming at the cost of low survival. Groups that were able to recover from a recent bottleneck consistently had higher relative growth rates. High genetic diversity and low levels of inbreeding are likely to be responsible for their improved survival during drought conditions and rapid growth under optimal environmental conditions. Our results suggest that maternal genetic traits might be used as indicators for conservation and population restoration. These findings provide us with new information that could be applied to support ex situ conservation and reintroduction of threatened species.Understanding the adaptation of plant species will help us develop effective breeding programs, guide the collection of germplasm, and improve the success of population restoration projects for threatened species. Genetic features correlate with species adaptation.  Seeds or seedlings are important germplasm resources and are often used in conservation programs for endangered species and in ecological projects to restore forest vegetation . They arBy the late 21st century, the global land area affected by drought is predicted to more than double . IncreasParashorea tomentella, seedling survival increased with genetic diversity [Parashorea tomentella, genetic diversity affected seedling survival but not growth or seed germination [Sessile plants have evolved different mechanisms to cope with the threat from drought environments . High geiversity . While iiversity , promoteiversity . For exaiversity . Populativersity . Plant siversity . While tiversity , in Paramination . Seed geA. yangbiense, a maple species whose genetic features were investigated using resequencing data from a previous study [A. yangbiense seedlings could be predicted by the genetic features of the maternal plants.Despite extensive research on plant adaptation, little is known about how past population demographics, such as severe population bottlenecks, may potentially influence the ability of plants to adapt to current environmental stresses. This knowledge gap is mainly due to a lack of genetic data. In this study, we chose us study , to addrA. yangbiense. Additionally, seed mass was significantly higher in the CRR and HHO groups, and high in the LHE and HF groups  . The aveF groups .A. yangbiense required an average of 44 days to begin germination  of 41%, ranging from 11% in BDH3 to 82% in CR10  than those given water  . We compared the final survival rate (SR) among different genetic groups for the water and drought treatments, separately. In the drought treatment experiments . As expected, SR was significantly higher in maternal families with high heterozygosity rates , low numbers of homozygous deleterious mutations , and low levels of inbreeding . In the water treatment experiments , and high in maternal families of the HHE group , the HHO group , and the LF group .eriments A–D, the eriments E–H, SR wp > 0.05). The LHE group (p < 0.01), the HHO group (p < 0.01), and the HF group (p < 0.01) had significantly lower SR than did the HHE, LHO, and LF groups, respectively, in the water treatment group compared with the drought treatment.When H1 (the first height measurement) and maternal individual were included as random effects, the results of the generalized linear mixed model (GLMM) showed that S (water treatment) had a positive effect on SR A–D compaW = 18374, p = 0.51, n = 391). RGR was consistently higher in the CRR group than in the OTD group , higher in the HHE group than in the LHE group , higher in the HHO group than in the LHO group , and higher in the LF group than in the HF group , both in the drought and water treatment groups. We observed that the majority of seedlings suffered from dieback and a reduction in height as the upper stem perished from disease or weather damage [We compared the relative growth rate (RGR) among different genetic groups in the water and drought treatments, separately. Overall, the mean RGR in the water treatment group (about −0.93 mm/day) was greater than that in the drought treatment group (about −1.25 mm/day), but not significantly (r damage .p < 0.01). The LHE group (p > 0.05), the LHO group (p > 0.05), and the HF group (p > 0.05) all showed lower RGR than did the HHE, HHO, and LF groups, respectively.When H1 and maternal plants were included as random effects, water treatment had a positive effect on RGR A–D. CompInvestigations into adaptation in endangered plant species, particularly at the vulnerable seed germination and subsequent seedling stages, will provide us with valuable information and inform future conservation decisions during global climate change . To our A. yangbiense were different among maternal families, for example, the GRs in maternal families, CR5 and CR10, were 33% and 82%, respectively. The average GR across the 10 maternal families of A. yangbiense was 41%, which is consistent with the findings of Yin et al. [A. yangbiense seeds are dormant and require four months of low temperature treatment to break dormancy [A. yangbiense to reach 50% GR in our germination experiments, which is faster than A. pycnanthum, a vulnerable tree species from Japan, which took 16 weeks of cold stratification to reach a GR of 49–90% [A. mono, which took only about 21–28 days to reach 67–87% GR [A. yangbiense may represent an adaptive strategy to cope with the monsoon climate in East Asia, which is characterized by very low rainfall during a long dry season from approximately November to May of the following year [Seed germination is one of the most important phenological traits affecting subsequent seedling growth . The GRsn et al. . Previoudormancy . It tookf 49–90% , and slo7–87% GR , althouging year . Seed doA. yangbiense seedlings died after two months of growth under natural conditions with no water during the dry season at Kunming Botanical Garden, suggesting that drought has a significant effect on seedling survival (SR) in this species, which may be a factor determining its threatened status. The implementation of protection or restoration practices requires an understanding of their drought tolerance and adaptation. We therefore propose that the best time to reintroduce A. yangbiense populations would be during the rainy season, as this could increase the success rate of the restoration efforts by increasing the likelihood of seedling survival. This period corresponds to the growing season of this deciduous tree, and to the phase of the Chinese solar calendar known as “Grain in Ear”, which describes a period of markedly high temperatures, abundant rainfall, and high humidity beginning around 5 or 6 June each year. Follow the rhythm of nature and nature will reward you during the seedling reintroduction. Impacted by monsoon climatic variability, China is significantly affected by drought hazards, particularly meteorological drought . Our resA. yangbiense seedlings experienced dieback , low number of homozygous deleterious mutations (LHO group), and low level of inbreeding (LF group) are better able to withstand a drought environment than those with low genetic diversity (LHE group), high number of deleterious mutations (HHO group), and high level of inbreeding (HF group). However, maternal families with significantly higher SR in the drought treatments did not always have significantly higher SR in the water treatments, indicating that seedling performance cannot always be predicted by the genetic features, depending on the fitness indicator  and experimental treatments . Genetic diversity is essential for the adaptability of a species, though there is no general relationship between genetic diversity and various fitness components, a lower level of heterozygosity may lead to a reduction in fitness . For exaA. yangbiense may allocate more resources to survival than to growth under drought stress, representing a trade-off between growth and mortality. The CRR group, which was previously predicted to be able to recover from a severe demographic bottleneck [A. yangbiense seedlings with high genetic diversity and low levels of inbreeding grow faster under suitable conditions, and that plant species with high genetic diversity are likely to be more adaptable to increasing environmental stress than those with low diversity.Growth and survival are key characters of forest dynamics and are important for population restoration. It has been reported that for small trees, there is a trade-off between rapid growth under favorable conditions and low mortality under unfavorable conditions . In our ttleneck , consistA. yangbiense had a known mother, but an unknown father, we used only the genetic features of the mother plants to represent the genetic features of all their offspring. However, the genetic diversity, number of homozygous deleterious mutations, and level of inbreeding in plant seedlings can be affected by selection, purging, drift, recombination, and gene flow, and are therefore likely to be variable and uncertain. Future research on the genetic attributes of these offspring should be used to thoroughly address the complexity of this issue.As individuals from the same maternal lineage are more similar in genetically regulated traits than those chosen at random, the seedlings from the same mother tree are considered half siblings, and the genetic features of the mother plants were used as an indicator of their offspring . BecauseThe sample size in this study is small, with only 10 maternal plants sampled due to the fact that few females could be found in the remaining populations, which is commonly a challenge when working with a critically endangered plant species with extremely small populations. Consequently, the findings of this study are relatively limited. A. yangbiense  and is categorized as Endangered on the IUCN Red List [A. yangbiense, and the species has a very restricted distribution range in Yunnan [A. yangbiense has been reported, and the genetic parameters, including demographic history, deleterious mutations, and inbreeding coefficient, have been thoroughly investigated in 105 individuals of this species [Acer species, including A. yangbiense, prefer humid environments based on field observation. Species distribution modeling also suggested that annual precipitation contributed most to the suitability of potentially suitable habitat for most maple species [ngbiense A, which arpa Pax , is endeRed List  and CritRed List . Thorougn Yunnan . The chr species . The see species . Most Ac species .A. yangbiense is andromonoecious, with an extremely low female to male ratio, most individuals are male and unable to bear fruit leading to a low fruit set rate [A. yangbiense seedlings to drought stress, we collected mature seeds  for germination experiments on 19 January 2021, following a previous method . BrieflyGermination onset time , germination rate , germination index , and germination potential  were calculated following previous research ,44. We aTo eliminate the effect of soil heterogeneity, all seedlings were grown in the nursery with similar substrate (peat:coconut hust:perlite:kanuma = 3:1:1:1) and watered frequently using tap water. Fungicide was applied once to eliminate fungal diseases due to its susceptibility to fungal infection , and weeA. yangbiense seedlings. After the last watering (16 March 2022), we randomly divided the surviving seedlings into two groups, one group was watered frequently (about twice a week) using tap water (the water experiment group) to keep the soil moist, and the other group was not watered until the end of the experiment . South China is subject to a significant monsoon climate characterized by an arid season from November until the end of May, and the natural group was considered to be under drought stress. The final survival status (SR) of individuals at the end of the experiment (10 June 2022) was recorded as follows: survival to the end of the experiment = 1, dead at the end of the experiment = 0 [A. yangbiense.We next explored the effects of natural drought on the performance of ment = 0 . The lasAll statistical analyses were conducted in RStudio v 2022.2.3.492  using R A. yangbiense, we divided the germinated seedlings into different half-sib groups according to the genetic features of their mother trees (FROH (frequency of runs of homozygosity), calculated by dividing the number of ROHs (runs of homozygosity) by the genome size, is often used as a coefficient of genomic inbreeding . To inveer trees  using thA. yangbiense. Maternal individual (M) and the first height measurement (H1) were included as random effects within our models. We used the R software with the glmer function in the lme4 [We also used a generalized linear mixed model (GLMM) to test the effect of treatment , and the genetic characteristics and their interactions on the survival (SR) and relative growth rate (RGR) of the ten tested maternal families of the lme4  to perfothe lme4  and was A. yangbiense is vulnerable to dry weather in early summer. Under experimental conditions, A. yangbiense took an average of 44 days to begin germinating, and a 50% germination rate was reached after an estimated 47–76 days. This slow and irregular germination, along with seedling dieback, might represent a series of drought adaptation strategies that have evolved in A. yangbiense in response to dry seasons. A. yangbiense seedlings prioritize resource allocation for survival over their ability to grow under drought stress, demonstrating a trade-off between growth and survival. Maternal genetic features of A. yangbiense might be used as indicators for conservation efforts in the face of climate change. The lower mortality under drought stress and faster growth under optimal conditions of A. yangbiense seedlings may likely be explained by the mother plants with high genetic diversity and low inbreeding levels. The CRR group consistently exhibited higher RGR than the OTD group in both water and drought experiments. These findings could be used for future conservation and restoration of A. yangbiense populations.The seedling stage of