Spatial Diversity Research Articles

Dispersal limitations and ecological adaptions shape phylogenetic diversity patterns of angiosperm woody plant communities along latitudinal and elevational gradients in East Asian islands

For centuries, ecologists have been captivated by the assembly of local communities from regional species pools, which gives rise to spatial diversity patterns. This study focused on hierarchical filtering process, which involves dispersal limitation and climatic constraint across regional to local scale, that underpins plant biodiversity patterns in East Asian islands, as one of the biodiversity hotspots with high endemicity. We used vegetation and species pool datasets of angiosperm woody plant communities collected from seven mountains across Japan to Taiwan to explore the relative contributions of local factors of individual plots, islands, latitude, elevation, and climatic variables related to the pattern of phylogenetic community assembly. Using linear regression and variation partitioning, we found that the island factor had the strongest filtering effect followed by latitude. Elevation and local factors (slope, aspect) accounted for a very small proportion of the variance in phylogenetic dispersion and community clade age between member species. Geographical factors involving islands, distance, and elevation had overriding filtering effects over climatic factors (minimum temperature of the coldest month, precipitation of the driest month) in shaping woody plant assembly patterns at the regional scale across East Asia islands. Tropical niche conservatism contributed to shaping woody plant communities in temperate region and high elevational regions on subtropical mountains as young and closely related species coexisted in those regions due to their adaptation to cold climates. This also explained the minor climate effects on species sorting in temperate mountains characterized by temperate-specific species pool which had already been filtered by cold climates. Inconsistent elevational phylogenetic diversity patterns in East Asia islands suggest a mountain-specific process that governs community assembly along elevational gradients, likely attributed to the location and climate of the mountain. These results suggest that historical factors (geohistorical isolation) related to islands and mountains contribute to in situ diversification that shaped plant diversity gradient from subtropical to temperate forests.

Metasurface loaded dual port circularly polarized dielectric resonator antenna with reduced RADAR cross section and mutual coupling features

The design of dual port radiator with a polarization diversity technique and reduced radar cross section (RCS) is described in this study. Cross slot is used to stimulate cylindrical ceramic for generating circular polarization features. Mirror orientation of aperture between port-1 and port-2 improves the isolation level by 25 dB. To suppress the antenna’s monostatic RCS, split ring resonator (SRR) based frequency selective surface is positioned between and around the dual ports. Experimental outcomes confirm the designed radiator operates from 4.11–5.24 GHz along with 3-dB axial ratio in between 4.15–4.92 GHz. The value of monostatic RCS is reduced by 15 dBsm in between the operating band. Broadsided radiation characteristics and good value of diversity parameter makes the designed radiator applicable for C-band Radar applications.

Simulation of Massive MIMO Antennas for Improved Link Throughput

Massive MIMO technology involves deploying multiple antennas on both ends of a communication link, which boosts spatial diversity and signal-to-noise ratio. By using multi-user MIMO transmission and techniques like spatial multiplexing and beamforming, it increases capacity, spectral efficiency, and data rates. Simulations conducted with tools like Octave software help engineers to optimize designs, predict system behavior, and assess the impact of antenna quantity on downlink throughput. This study addresses the increasing demand for high downlink data rates within modern communication networks. It explores the performance of Massive MIMO systems through simulations using Octave software, focusing on the quantity of antenna elements (M), and considering both spectral efficiency (SE) and data throughput. Results show higher M enhances both spectral efficiency and data rates. Efficiency dips at M=10, surges at M=40, and slowly, but steadily grows from M=50 to 100. Similar trends in data rates indicate M's impact on transmission performance. SE values range from 5.8442 bps/Hz (M = 10) to 24.1608 bps/Hz (M = 100), while data rates range from 116.8834 Mbps (M = 10) to 483.2158 Mbps (M = 100). These insights offer practical guidance for engineers and could facilitate the optimization of wireless communication setups and addressing the imperative for improved data rates. The study advances the understanding of Massive MIMO's potential, providing a roadmap for effectively leveraging its capabilities across diverse communication network scenarios.

Outage-guaranteed transmission for IRS-assisted FSO systems

Intelligent reflecting surface (IRS)-assisted free space optical (FSO) communication can overcome line-of-sight and bring spatial diversity, which is considered to be a good complement to direct FSO links. This paper is interested in understanding the role of IRS-assisted FSO links when coexisting with direct FSO links. Due to the diverse nature of existing FSO channel models and the reliability requirements of IRS-assisted FSO systems, this paper aims to investigate the transmission problems of link selection and power configuration under the quality of service guarantee for link outage, which can be applicable to different channel models. Despite the inherent complexity of the problems, transmission schemes, i.e., sum rate transmission (SRT) and rate fairness transmission (RFT) are developed, which can achieve the respective optimal performance. Also, some insights for transmission schemes are provided. The results verify the efficacy of the proposed transmission schemes. The performance of the system may be improved by 40% and 41% for SRT and RFT, respectively.

Dual band notched superwideband MIMO antenna for 5G and 6G applications

In this article, a compact super wideband multiple input multiple output (MIMO) antenna with dual band elimination feature is presented. The antenna element comprises of modified square shaped radiating element and coplanar waveguide (CPW) with asymmetric ground planes. A dual-port MIMO configuration is proposed for spatial diversity. It has compact size of dimensions 18 × 37.5 × 1.6 mm3. It has frequency band of impedance matching (VSWR < 2) from 3.9– > 150 GHz (%BW > 189.86 %). The radiator and feedline are loadedwith modified M- and U-shaped slots to achieve a band notch at 5.5 GHz (WLAN) and 7.5 GHz (X-band satellite communication), respectively. A modified staircase shaped structure is used between the two ports to achieve an intraport isolation of > 20 dB at maximum frequencies. The MIMO antenna has envelope correlation coefficient based on scattering parameters < 0.005, envelope correlation coefficient based on farfield parameters < 0.08, peak gain of 8.63dBi, Mean Effective Gain (MEG) < -3dB, multiplexing efficiency > -4.0 dB, channel capacity loss (CCL) < 0.4bits/sec/Hz to signify its suitability for MIMO applications. The measured and the simulated outcomes are found to be close to each other. The proposed antenna element and MIMO antenna structure will be suitable for Internet of Things (IoT), 5G, and 6G due to their superwideband (SWB) bandwidth, desirable radiation properties and diversity performance.

Performance implications of channel aware cooperative probing-GBN ARQ in the context of wireless body area networks

The advent of Wireless Body Area Networks (WBAN) in patient care has revolutionized the healthcare sector as patients can now be monitored continuously in real-time and as well remotely. Despite its significant advantages, WBAN encounters a notable challenge in the fading aspect, which undermines its effectiveness. Improving WBAN efficiency involves tackling signal fading, which is crucial. Cooperative communication offers a promising solution by introducing spatial diversity to counteract fading effects. We propose a scheme that uses cooperative communication and the Probing-Go Back N Automatic Repeat Request (P-GBN ARQ) technique to reduce the fading effect. The proposed method uses feedback to predict the channel's current state, and the probing interval is determined by the received signal's Average Fading Duration (AFD). The proposed scheme's performance is also assessed extensively through simulations employing various metrics. The results demonstrate a considerable improvement in throughput performance with the inclusion of knowledge about channel fading. The Bit Error Rate (BER) execution is compared with Selection Combiner (SC) and conventional Maximal Ratio Combining (MRC). At 10−3, the cooperative method achieves it at 13 dB SNR, whereas the direct approach reaches it at 24 dB SNR, requiring an additional 11 dB. The proposed approach minimizes BER, enhancing throughput and reliability in WBAN.

High resolution remote sensing for biodiversity assessment and monitoring: A case study of dominant tree species in an old-growth forest

Biodiversity assessment and monitoring in old-growth forests (OGFs) is crucial for their effective management and conservation amongst various natural and human-induced challenges. In the present study, the spatial and temporal species diversity were assessed in the mixed stands of Białowieża Forest (BF), a renowned UNESCO world heritage site recognized as an OGF. The BF has encountered challenges due to pest outbreaks peaking in 2016–2017 with adverse impacts on species composition. Utilizing airborne laser scanning (ALS) and color infrared (CIR) datasets from 2015 and 2019 (prior and following the peak, respectively), 30 variables were extracted and employed as input for the Random Forest algorithm to identify 14 species of broadleaved and coniferous individuals at plot levels (458 plots) within the BF. We calculated biodiversity indices (including α, β, and γ diversity), Importance Value Index (IVI), bivariate scale-dependent density of species, and temporal β diversity indices independently for data acquired from both field observation (FO) and species maps obtained through remote sensing analysis (RSA). The study found no significant differences in α diversity indices between the FO and RSA across the BF, however, notable discrepancies existed in species richness. Limited species detection was attributed to low species frequency and therefore, insufficient reference individuals. Average β and γ diversities from both datasets showed no significant differences. The RSA accurately identified top species and their changes in terms of IVI. Additionally, the RSA explored scale-dependent density changes of broadleaved individuals around conifers. Consistency was observed between FO and RSA in identifying dominance shifts from losses to gains within the BF communities. The comparison of diversity indices obtained from FO and RSA suggests that the RSA provided comparable results to FO in capturing the diversity of dominant tree species within the BF, providing a promising approach for advancing our understanding of forest biodiversity in OGFs.

Unleashing the potential of cheminformatic analysis for Mycobacterium tuberculosis inhibitors: Insights into chemical space and structural diversity

Mycobacterium tuberculosis (Mtb) remains a major global health concern, causing millions of infections and deaths annually. Drug-resistant tuberculosis poses significant challenges, necessitating the search for new Mtb inhibitors. In this context, a cheminformatic analysis of the currently available antimycobacterial chemical space can be performed to discover structural diversity and new scaffolds. This study conducts a comprehensive cheminformatic analysis of two datasets containing Mtb inhibitors (Mtbs and Phytochemicals), comparing them with Approved drugs and Nutraceuticals datasets. The analysis includes physicochemical properties, molecular scaffolds, structural fingerprints, and structural similarities. The analysis of physicochemical property distributions revealed that Mtb inhibitors are generally less polar or equally polar compared to approved drugs and have similar flexibility. The visual representation of the property space illustrates that the Mtbs dataset is confined to a narrower area, whereas certain compounds within the Phytochemical dataset broaden the scope of the traditional medicinal space. Scaffold analysis identifies several promising candidates in both the Mtbs and Phytochemical datasets. Additionally, employing SkelSpheres descriptors and rubber band scaling for similarity analysis reveals a limited depiction of the chemical space. The analysis of structural diversity indicates that the compounds in the Mtbs dataset exhibit less structural diversity. These findings underscore the necessity to broaden the chemical space of Mtb-targeting molecules by incorporating representative molecules from diverse scaffolds to effectively tackle the issue of drug resistance.

Polarization Diversity and Transfer Learning-Based Modulation Optimization for High-Speed Dual Channel MIMO Backscatter Communication

Polarization Diversity and Transfer Learning-Based Modulation Optimization for High-Speed Dual Channel MIMO Backscatter Communication

CULINARY GEOGRAPHY SCIENTIFIC DIRECTION NEW WORLD OF TOURISM

The article considers the importance of culinary geography in the training of specialists in the specialty 242 Tourism and recreation. Obtaining a higher education in the specified specialty in our country is directly relating ding to the activities of the departments that ensure the graduation of specialists - tourism experts for the needs of the country. The study of issues, problems and the nearest prospects of obtaining a professional higher education in tourism and recreation in Ukraine were intensifying by the authors' research due to the appearance of publications approximately since 2015. The analysis of curricula shows the introduction of culinary geography and the justification of the tourism education model at the departments of the Faculty of Geography of Ivan Franko Lviv National University, Yuri Fedkovich Chernivtsi National University, Volodymyr Hnatyuk Ternopil National Pedagogical University and other universities. As a resulting of the conducted research, new aspects of culinary geography were established. In recent years, interest in the "geography of nutrition" has grown rapidly. Reflecting the great popularity and public interest in all aspects of nutrition - from health issues, global hunger and malnutrition to climate change environmental destruction and animal welfare. The availability of a significant number of journal articles and books on various aspects of food geography creates prerequisites for teaching this subject in universities and colleges. The popularization of scientific research on the geography of food allows activating interest in the development and improvement of one's "geographic ideas" about food. Dishes and methods of their preparation are specific features of the national characteristics of each nation. Culinary geography is a systematic, multidisciplinary, integrated approach to the study of folk food as an important element of material culture. Folk food is an important element of material culture. Its composition and quality characteristics depend on many factors. These are primarily historical, socio-economic, cultural and household, geographical living conditions of the ethnic group, traditions, directions and degree of development of agriculture. Dishes and methods of their preparation are specific features of the national characteristics of each nation. A broad understanding of the study of everyday life, traditions of the material and spiritual culture of peoples, their origin (ethnogenesis) is engage ding in by a number of sciences that have their own unique research methods. In a narrow sense, culinary geography is a component of cultural geography. The geography of culture examines culture in geographic space, studies the spatial differentiation and diversity of its elements, their expression in the landscape and the connection with the geographic environment, as well as the reflection of geographic space in the culture itself. Thus, the arguments listed above for establishing the scientific direction of culinary geography allow us to outline its main definitions. First, we note that there is no single interpretation of the name of the scientific direction (academic discipline) of the problem of culinary geography. It is necessary to state that two main approaches have historically developed in the literature: 1) Food geography (quite a wide range of subjects); 2) Culinary tourism, culinary geography, nutrition in tourism, gastronomic tourism. Keywords: culinary geography, geography of food, culinary tourism, geography of tourist food.

Leveraging Spatial Diversity for Ambiguity-Free Ultranarrowband Phase-Based 3-D Localization

Leveraging Spatial Diversity for Ambiguity-Free Ultranarrowband Phase-Based 3-D Localization

A multimodal multi-objective differential evolution with series-parallel combination and dynamic neighbor strategy

Multimodal multi-objective optimization problems (MMOPs), which aim to identify as many optimal solutions as possible and exhibit multiple equivalent Pareto optimal solution sets (PSs) that correspond to the same Pareto optimal front (PF), commonly arise in a wide range of optimization problems in the real world. However, some dominated solutions that exhibit greater diversity in the decision space may be substituted by non-dominated solutions with a higher level of decision space crowding. To tackle this issue, this paper proposes a multimodal multi-objective differential evolution with series-parallel combination and dynamic neighbor strategy (MMODE_SPDN), which can balance convergence, objective space diversity and decision space diversity. Specifically, two archives are initially updated serially followed by the overall update of the parallel structure, in which the serial-first approach can enhance population diversity and the parallel structure can greatly reduce the amount of calculation. In addition, a dynamic neighbor strategy which utilizes adaptive selection among neighbors to generate difference vectors in the decision space and objective space and then adopts the main and auxiliary parent method during the mutation process is proposed. Furthermore, the utilization of an auxiliary archive and the clustering-based special crowding distance (CSCD) method are employed to facilitate the updating of the archive, thereby enhancing diversity. MMODE_SPDN is compared with other multimodal multi-objective optimization evolutionary algorithms (MMOEAs) on numerous test problems and the experimental results demonstrate that MMODE_SPDN exhibits superior performance.

Additive partitioning of multispecies distributional aggregation of local assemblages.

The distribution of species is not random in space. At the finest-resolution spatial scale, that is, field sampling locations, distributional aggregation level of different species would be determined by various factors, for example spatial autocorrelation or environmental filtering. However, few studies have quantitatively measured the importance of these factors. In this study, inspired by the statistical properties of a Markov transition model, we propose a novel additive framework to partition local multispecies distributional aggregation levels for sequential sampling-derived field biodiversity data. The framework partitions the spatial distributional aggregation of different species into two independent components: regional abundance variability and the local spatial inertia effect. Empirical studies from field amphibian surveys through line-transect sampling in southwestern China (Minya Konka) and central-southern Vietnam showed that local spatial inertia was always the dominant mechanism structuring the local occurrence and distributional aggregation of amphibians in the two regions with a latitudinal gradient from 1200 to nearly 4000 m. However, regional abundance variability is still nonnegligible in highly diverse tropical regions (i.e. Vietnam) where the altitude is not higher than 2000 m. In summary, we propose a novel framework that shows that the multispecies distributional aggregation level can be structured by two additive components. The two partitioned components could be theoretically independent. These findings are expected to deepen our understanding of the local community structure from the perspective of both spatial distribution and regional diversity patterns. The partitioning framework might have potential applications in field ecology and macroecology research.

Ecological and climatic transferability of airborne lidar-driven aboveground biomass models in Piñon-Juniper woodlands

ABSTRACT Piñon-juniper (PJ) woodlands are an expansive and dynamic dryland ecosystem in the US that encompass a wide range of spatial, temporal, and ecological diversity. The dynamism of PJ woodland extent and abundance over space and time is attributable to variability in species compositions, stand structures, climatic conditions, and disturbance patterns. PJ aboveground biomass (AGB) quantification is important for understanding its role in the global carbon cycle, for tracking climate change impacts, and for informing forest management practices. Quantifying AGB in PJ woodlands is challenging due to complex vegetation structure. Although airborne laser scanning (ALS) has proven effective in estimating PJ AGB in local scale studies, these efforts only capture a fraction of the overall PJ range leaving open an important question as to whether a broad-scale, ecosystem-wide effort to map PJ woodland AGB could be successful. This research seeks to determine whether AGB predictive models built in ecologically distinct portions of PJ’s range can be accurately applied to prediction of AGB in other portions of the range. Using a large database of 497 field plots compiled from eight sources and a random forest modeling framework, transferability between predictive models was evaluated by grouping field reference plots into two clustering categories based on PJ characteristics: one category generated with environmental variables (climate and topography) and the other using species compositions. For both clustering categories, models trained on one cluster were used to predict AGB in every other cluster within that category. Relatively distinct clusters, such as those characterized by notably higher temperatures and precipitation totals or dominated by a unique species, had high transferability when models were trained on the distinct cluster and applied to other clusters, but low transferability when other clusters were tested on the distinct cluster. High training transferability for distinct clusters is likely due to the inability of random forests to extrapolate beyond the range of training data, while the high testing transferability is likely due to ecological reasons. Therefore, it is important to capture the distinct environments and species compositions within the range of PJ woodlands when training a range-wide model to map PJ AGB. With the eventual goal of a range-wide PJ AGB map, we developed a preliminary range-wide model of PJ woodland AGB using our entire field reference dataset. The bootstrapped accuracy assessment of the range wide model (median R2 = 0.52; median rRMSE = 0.49) suggests promise for future comprehensive PJ AGB maps. However, high AGB values in the range-wide model were under-predicted, suggesting that gathering additional field plots in high AGB PJ woodlands has the potential to enhance the accuracy of the predictive model across the range of PJ AGB.

Dual port high gain frequency reconfigurable THz graphene–silicon ring ceramic antenna with polarization and pattern diversity features

Dual port high gain frequency reconfigurable THz graphene–silicon ring ceramic antenna with polarization and pattern diversity features

Design and optimization of a dual port high gain circularly polarized graphene-ceramic array antenna in a THz regime

In this paper, a dual port high gain hybrid (silicon graphene) antenna is designed and investigated. Some of the important qualities of the proposed radiating structure include the following: (1) XGBoost and Random Forest-based machine learning (ML) techniques are applied to predict the reflection coefficient (|S11|) features of the designed radiator to reduce the simulation time; (2) the use of a cross slot provides the circularly polarized waves between 4.92 and 5.38 THz; (3) a 1∗2 array structure produces the high gain, i.e., 10.0 dBi within the operating frequency range; and (4) the opposite orientation of the aperture provides a polarization diversity concept, which, in turn, improves the isolation level to more than 30 dB. After comparing the results obtained from CST and HFSS, as well as those predicted from the ML algorithm, it is confirmed that the designed radiator operates from 4.71 to 5.85 THz. The good value of far-field and diversity parameters affirms the fitness of the designed radiator for wireless power transfer in the THz regime.

A Low-Profile four-port MIMO Antenna for 5G-n79 Band with high diversity performance

This paper presents a simple design of a compact 4-port multiple-input multiple-output (MIMO) microstrip antenna using polarization diversity technique. The proposed structure consists of four monopole elements operating in the fifth generation n79 band (4800–5000 MHz). To achieve good performance with a more compact design, the four identical elements are arranged orthogonally to each other. The proposed antenna is fabricated using a Rogers RT6010 substrate with a compact size of 28 × 28mm2. The measured results of the manufactured antenna in terms of S-parameters and radiation pattern are in good agreement at the operating frequency band. Moreover, the diversity performance of the proposed MIMO antenna is evaluated through the envelope correlation coefficient (ECC), the diversity gain (DG), the total active reflection coefficient (TARC) and the channel capacity loss (CCL).

Mapping myeloid cell function: Spatial diversity in tumor and neuronal microenvironment

In this issue of Cancer Cell, Zhong etal. explore the dual role of TREM2 in glioblastoma-associated myeloid cells, demonstrating its function in promoting inflammation at the tumor-neural interface and suppression within the tumor core, influenced by the local microenvironment. These findings open up promising prospects for advancements in neuro-oncological immunotherapy.

Charting heterogeneity and spatial landscape of consensus molecular subtypes in colorectal cancer.

e15647 Background: High inter-patient heterogeneity and spatial diversity within tumors represent significant challenges to improving outcomes in colorectal cancer (CRC). Despite elucidation of consensus molecular subtypes (CMS), little progress has been made in translating this knowledge into clinical gain. Intratumoral CMS heterogeneity remains a relatively unexplored area and understanding of the interplay between subtypes holds promise for improving prognostication. We leverage spatial transcriptomics (ST) to enhance understanding of CMS heterogeneity and spatial distribution, with the goal of advancing personalized therapy through high resolution molecular sub-typing. Methods: ST using the 10x Genomics Visium platform was performed on paraffin-embedded CRC specimens for which comprehensive clinicopathological and long-term clinical outcome data were available. ST data were deconvoluted with respect to CMS single-cell RNA sequencing (scRNA-seq) data, yielding maps of CMS landscapes at a resolution of 55 microns. A pre-trained deep learning model was used to identify distinct CRC tissue classes (tumor epithelium, stroma, etc.) within H&amp;E images, enabling spatial correlation of histomorphology with CMS. Cellular composition within these CMS maps was quantified through deconvolution of six major cell types using reference scRNA-seq data. Pseudo-bulk samples were generated from the ST data to evaluate CMS behaviors and compute pathway activities. Results: 40 CRC patients were assayed using ST and H&amp;E profiling (13, 8, 14, and 5 from stages 1-4, respectively). Median follow-up was 112 months (Range 1–192). Intratumoral CMS heterogeneity was evident in all patients, with diverse CMS compositions. Using Simpson diversity index to quantify this heterogeneity, we observed significant correlation of heterogeneity with disease specific survival (DSS) (p = .03). CMS landscapes displayed spatial patterns that were distinct among tissue categories (average F1-score: testing = .92, validation = .89. Tissue categories based on deep learning from H&amp;E images). Tumors with higher levels of CMS1 or 4 were associated with worse outcome. Stratification by the composite CMS biomarker (CMS1+CMS4)/(CMS2+CMS3) yielded significant separation of the Kaplan-Meier curve for DSS (p = .018). Conclusions: This study demonstrates that CRC tumors contain significant intratumoral CMS heterogeneity that is not detectable using bulk classification methods. Spatial patterns in CMS transcriptional topographies correlate with H&amp;E-derived morphology, suggesting the potential for estimating CMS composition from histopathological features. Importantly, we show that spatially composite CMS-derived biomarkers possess strong prognostic potential. The capacity to decode CMS topographic patterns and associate these with clinical outcome offers great potential to advance personalized therapy for CRC.

Genetic diversity and population structure of a rare flowering tree endemic to Appalachia, Stewartia ovata.

Stewartia ovata (cav.) Weatherby, commonly known as mountain stewartia, is an understory tree native to the southeastern United States (U.S.). This relatively rare species occurs in isolated populations in Virginia, Kentucky, Tennessee, North Carolina, South Carolina, Georgia, Alabama, and Mississippi. As a species, S. ovata has largely been overlooked, and limited information is available regarding its ecology, which presents obstacles to conservation efforts. Stewartia ovata has vibrant, large white flowers that bloom in summer with a variety of filament colors, suggesting potential horticultural traits prized by ornamental industry. However, S. ovata is relatively slow growing and, due to long seed dormancy, propagation is challenging with limited success rates. This has created a need to assess the present genetic diversity in S. ovata populations to inform potential conservation and restoration of the species. Here, we employ a genotyping-by-sequencing (GBS) approach to characterize the spatial distribution and genetic diversity of S. ovata in the southern Appalachia region of the eastern United States. A total of 4475 single nucleotide polymorphisms (SNPs) were identified across 147 individuals from 11 collection sites. Our results indicate low genetic diversity (He = 0.216), the presence of population structure (K = 2), limited differentiation (F ST = 0.039), and high gene flow (Nm = 6.16) between our subpopulations. Principal component analysis corroborated the findings of STRUCTURE, confirming the presence of two distinct S. ovata subpopulations. One subpopulation mainly contains genotypes from the Cumberland Plateau, Tennessee, while the other consists of genotypes present in the Great Smoky Mountain ranges in Tennessee, North Carolina, and portions of Nantahala, Chattahoochee-Oconee national forests in Georgia, highlighting that elevation likely plays a major role in its distribution. Our results further suggested low inbreeding coefficient (F IS = 0.070), which is expected with an outcrossing tree species. This research further provides necessary insight into extant subpopulations and has generated valuable resources needed for conservation efforts of S. ovata.