PLANTS, PEOPLE, PLANET

Understanding crop genetic diversity is essential for conservation and breeding, yet farmer-maintained germplasm remains largely underrepresented in genomic studies. Theobroma cacao L. has a complex domestication history and extensive global diversity, and cacao currently cultivated in Central America, particularly in Costa Rica, has been understudied compared to South American and Mexican cultivars despite cultural and historical importance. In this study, we investigate the genetic diversity of cacao from farmer-managed systems across Costa Rica to search for Criollo germplasm and identify and characterize any unique local genetic groups. Ninety-four trees were sampled from 17 farms across four regions of the country and sequenced using whole genome resequencing. Farmer materials were analyzed alongside 166 previously characterized reference accessions representing major cacao genetic groups. Population structure analyses, phylogenetic reconstruction, and network approaches revealed that Costa Rican cacao encompasses multiple known genetic groups, including Criollo-derived lineages, while also harboring locally distinct diversity not fully represented in current global reference collections. Analyses revealed close kinship between many accessions with no clear geographic patterns corresponding to the observed population differentiation, reflecting the effects of farmers in creating dominant patterns of gene flow through seed-saving, clonal propagation, and sharing genotypes among farms. Heterozygosity levels varied substantially among individuals, consistent with a mixture of highly inbred Criollo trees and more heterozygous, admixed genotypes. We find that farmer-managed cacao systems are reservoirs of genetic diversity, including possibly rare or historically important lineages, underscoring the value of these farming systems for effective conservation and management of genomic resources for cacao resilience and improvement.

PremiseHerbarium specimens are increasingly used to extract morphological traits for ecological and evolutionary studies, yet the effects of tissue desiccation on trait measurements remain poorly understood. Here, we tested whether higher tissue water content leads to greater measurement changes after herborization (H1) and whether fresh trait values can be reliably predicted from herbarium measurements (H2). MethodsWe evaluated the reliability of herbarium-based measurements by comparing fresh and dried traits of leaves, flowers, fleshy fruits, and seeds across 262 individuals representing 133 Neotropical Myrtaceae species. Phylogenetic least square models and machine-learning regressions were used to test H1 and H2. ResultsLeaves and flowers generally shrank after herborization, fruits size metrics tended to increase, and seeds were largely unaffected. Water content was significantly associated with the magnitude of herborization effects in flowers and some leaf and seed traits. Fresh trait values were accurately predicted from herbarium measurements. Prediction errors were lowest for leaf traits, followed by fruits, flowers, and seeds. DiscussionThese results partially support H1 and support H2, indicating that herbarium specimens can be reliably used for trait analyses when organ-specific responses are considered, providing a practical framework to account for potential desiccation bias in functional trait research.

If youve ever complained about a species name thats a mouthful--say, the soldier fly Parastratiosphecomyia stratiosphecomyioides or the myxobacterium Myxococcus llanfairpwllgwyngyllgogerychwyrndrobwllllantysiliogogogochensis--youre in very good company. But could the readability of binomial scientific names cause more than complaints? Could it influence how much species are studied and talked about? We examined a random sample of 3,019 species names spanning 29 phyla/divisions. We tested whether name length and reading difficulty are associated with species representation in the scientific literature (measured via literature mentions) and their visibility to the public (measured via Wikipedia pageviews). Both species name traits showed significant negative relationships with literature mentions and Wikipedia reads. Increasing name length from 10 to 30 characters is associated with a 66% decrease in expected mentions and a 65% decrease in Wikipedia reads, while shifting from the most to the least readable name in the dataset corresponds to 53% and 76% decreases. These patterns are consistent with something familiar: the fickleness of human attention, responding to features of the world that are far from rational. While creativity in naming is a cherished part of taxonomy, a touch of orthographic restraint may ultimately benefit both science and the species themselves--especially among understudied uncharismatic taxa.

We present here FennoTraits, which is a dataset of plant functional trait and community composition data which we collected from Fennoscandia across northern Finland, Norway, and Sweden in 2016-2025. This dataset has 42 049 abundance estimations and 155 794 functional trait observations from 10 traits representing 373 vascular plant species collected from 1 235 study sites within seven study areas. The trait measurements consist of size-structural, leaf economic, leaf spectral, and reproductive traits. The species represent the majority of the native vascular plant species that occur at the seven study areas, and many of the species occur in all seven areas across the two biomes and their ecotone: tundra and boreal forests. Each study area has distinct characteristics and a range of habitats: tundra, meadows, wetlands, shrublands, and boreal forests. These areas are under low anthropogenic influence, and many of the sites are within protected areas that are reserved for nature conservation and scientific research. Finally, we provide with this dataset a general description of the main trait patterns and profiles of the northern European flora.

Climate change increasingly threatens global Capsicum (pepper) production. Accelerating the deployment of climate-resilient cultivars requires effective use of genetic diversity conserved in genebanks. We implement a "turbocharging" strategy in Capsicum by integrating genome-wide association studies and genomic prediction in a core collection (n = 423), followed by genomic prediction across the global collection (n = 10,250) using the core as a training population. We generated genomic estimated breeding values (GEBVs) for 31 high-accuracy traits (r > 0.5) encompassing hyperspectral phenotypes (heat/control), agronomic performance (heat/control) and fruit quality. To enhance accessibility and decision-making, we developed a large language model (LLM) integrated application that enables flexible, preference-based selection of candidates. By narrowing the parental decision space, this framework streamlines screening of large germplasm collections while balancing climate resilience, quality attributes and market demands. Our approach provides a scalable decision-support system to accelerate climate-resilient Capsicum breeding and maximize global genetic resources.

AimHuman land-use has dramatically altered the amount, quality, and connectivity of habitat for species worldwide. Understanding how these changes affect individual species is essential for predicting the overall consequences of land-use change for biodiversity. LocationThe Caribbean island of Puerto Rico. Forest cover on the island increased from about 18 to 45% from the late 1940s to the early 2000s. MethodsUsing data on geographic distributions and functional traits for 454 tree species, we evaluated how gain of potential habitat was related to species-specific climatic associations and life-history strategies. We estimated species-specific potential habitat (climatically suitable and forested) with species distribution models and data on forest cover. We characterized each species niche breadth (the range of environmental conditions it occupies) and niche position (the environmental conditions it prefers) to compare with the conditions in reforested areas. ResultsSpecies with relatively more potential habitat in 1951 (climatically suitable and forested) also had relatively larger gains in potential habitat from 1951 to 2000. Species that tend to occupy conditions different from those common in reforested areas (i.e., more marginal habitats) gained relatively less potential habitat and species with broad environmental niches gained more potential habitat. Additionally, species with relatively acquisitive functional traits gained more suitable habitat than those with relatively conservative traits. Main conclusionsOur results show that Puerto Ricos reforestation preferentially increased habitat for species that (1) already had suitable habitat in the landscape, (2) tolerate a wide range of climatic conditions, and (3) exhibit fast, acquisitive functional strategies. These findings illustrate how land-use change in heterogeneous tropical landscapes can generate non-uniform habitat gains across species, potentially favoring generalist over specialist species and reshaping community composition.

ObjectivesEffective communication about genetics concepts is essential for collaborative anthropological genetics research. However, communication can be challenging because many ideas are abstract and may be especially unfamiliar to communities with limited access to formal education. Indeed, there are no widely adopted models for communicating such information, nor a clear understanding of the social factors that may shape participant engagement. Here, we conducted a qualitative and quantitative, community-driven study to understand how illustrations can be useful to support concept sharing with two Indigenous groups--the Orang Asli of Peninsular Malaysia and the Turkana of Kenya. MethodsWe used a two phase approach to create and evaluate how illustrations can bolster communication about genetics concepts. First, we created images illustrating answers to frequently asked questions about genetics, iteratively updating the illustrations based on participant feedback. Second, we conducted 92 interviews to evaluate the finalized illustrations effectiveness. Finally, we analyzed the interview data using thematic analyses, multivariable modeling, and multiple correspondence analyses to identify patterns in participant understanding and feedback, including age, sex, market integration, and schooling. ResultsParticipants reported high interest in genetics research (92%) and broadly positive perceptions of the illustrations. Familiar, locally-grounded imagery was preferred and associated with greater perceived clarity, while more technical illustrations were more frequently reported as confusing. Quantitative analyses showed strong internal consistency across measures of engagement and understanding, with modest variation by degree of market-integration, schooling, and sex. DiscussionOur findings demonstrate that community-specific visualizations, co-developed through iterative feedback, can effectively support engagement with genetics research in participant communities.

Global biodiversity is declining at an unprecedented rate due to rapid environmental change and increasing human pressures. Ongoing urban expansion fragments natural systems, while urban design increasingly seeks to mitigate these impacts through the integration of blue-green infrastructure. Effective biodiversity monitoring is therefore essential to evaluate ecological conditions within these novel socio-ecological systems. Although urban biodiversity monitoring is challenged by its high landscape heterogeneity, dense human populations provide opportunities for large-scale data collection through public participation in citizen science. Using data from 25 City Nature Challenge (CNC) projects across the United Kingdom (2020-2025), we assessed the effects of the four-day bioblitz on species inventories, participation in biological recording, and spatial patterns of recording effort. CNC events doubled public participation in iNaturalist recording relative to baseline activity, leading to the documentation of numerous previously unrecorded species through increased observer effort and broader use of urban blue-green spaces. These results show that CNC events enhance urban biodiversity datasets by increasing the number of observers and reducing spatial and observer biases, providing a cost-effective tool for enriching urban biodiversity data. In addition to generating ecological data, CNC events could have public health benefits through increased exposure to urban blue-green spaces.

The narrow genetic base of cultivated tomato (Solanum lycopersicum L.) represents a major constraint on crop improvement, necessitating the exploitation of wild relatives to broaden allelic diversity. Here we present SABER (Solanum lycopersicum Allele Biodiversity Enriched Resources), a novel eight-founder Multiparent Advanced Generation Intercross (MAGIC) population that, for the first time, incorporates the Galapagos wild relative Solanum cheesmaniae as a founder alongside seven elite S. lycopersicum lines. Following a structured crossing scheme and Single Seed Descent advancement, F6 recombinant inbred lines were genotyped at 5,850 high-confidence SNP markers using Single Primer Enrichment Technology (SPET). Population structure analyses confirmed low residual heterozygosity, limited substructure among offspring, and successful introgression of S. cheesmaniae alleles across all twelve chromosomes. Mapping performance was validated through three Mendelian traits with known genetic determinants, all of which resolved to genomic positions consistent with the literature. QTL mapping for quantitative agronomic traits identified known loci for fruit epicarp and flesh color, and two novel QTL for days to flowering, number of leaves before flowering, and soluble solids content. Together, these results demonstrate that SABER is a powerful and reliable platform for high-resolution QTL mapping and candidate gene discovery, and establish a replicable framework for integrating wild germplasm into multiparental tomato breeding resources

CoverCress is a new winter annual oilseed crop developed from field pennycress within the past 20 years. Field pennycress is commonly considered to be self-pollinated but little basic research has been published and there is some misalignment of conclusions. Our experience working with pennycress plant growth in greenhouse and field conditions over the past 13 years suggests that outcrossing is uncommon. We conducted lab, greenhouse, and field experiments to strengthen the body of work. Pollen viability kinetics analysis showed that longevity of pollen viability is negatively impacted by increasing temperatures and by direct exposure to light. Samples treated at 4C declined to 50% viability in 12 hours while it took just 2.5 hrs at 37C, and 1.6 hrs in full sunlight on a cool early April day. Cross-pollination was absent among greenhouse-grown plants flowering inside an agitated plastic pollen-containment covering. Across greenhouse tests, high rates of cross-pollination occurred only in an emasculation treatment that rendered flowers male sterile and opened the pistil to cross-fertilization. Field trials designed to measure pollen flow distance using a trackable fae1 knockout reporter gene failed to show detectable movement of pollen under field conditions in two locations. This data strongly suggests that domesticated field pennycress may be considered a self-pollinated crop and managed as such.

While most plant lineages are pigmented by anthocyanins, several families in the Caryophyllales represent a major exception by showing a replacement of anthocyanin pigmentation by betalain pigmentation. The mutual exclusion of anthocyanins and betalains at the family level has been well established for over 50 years and has been mechanistically explained. Chenopodiaceae are a betalain-pigmented lineage lacking a key anthocyanin biosynthesis gene and lacking the key activating transcription factor of the anthocyanin biosynthesis. A publication by Zhang et al., 2024 claims that anthocyanins would be responsible for the red pigmentation in leaves of Chenopodium quinoa. Here, we assessed this study and reanalyzed the RNA-seq datasets generated in this study to demonstrate that there is no evidence for anthocyanin biosynthesis, but activity of the betalain and carotenoid biosynthesis could explain the observed pigmentation of quinoa leaves.

Gene flow shapes the demographic stability and evolutionary potential of tropical forest trees, yet its dynamics may differ depending on the temporal scale at which it is assessed. We combined spatial genetic structure (SGS), parentage analyses, and reproductive success metrics to investigate historical and contemporary gene dispersal in four populations of Dicorynia guianensis across French Guiana, encompassing sites differing in environment and management history. A total of 1,528 individuals were genotyped using 66 nuclear and 23 plastid microsatellite markers, enabling high-resolution inference of biparental and maternal gene dispersal. Historical mating and dispersal parameters inferred from SGS revealed marked contrasts among populations. Some populations exhibited high historical gene dispersal distances and weak spatial genetic structure, whereas others showed stronger SGS and long-term aggregative dispersal patterns. Contemporary parentage analyses further highlighted differences in seed and pollen dispersal distances, parent assignment rates, and reproductive skew. In certain populations, pronounced reproductive inequality and reduced effective connectivity were observed, while others displayed more balanced reproductive contributions. By jointly evaluating long-term dispersal legacies and present-day reproductive patterns, our study demonstrates the value of combining indirect and direct genetic approaches to assess population dynamics and conservation status in tropical forest trees. This multi-temporal perspective provides a comprehensive basis for long-term monitoring and sustainable management in heterogeneous tropical landscapes.

Within the framework of the European Adaptive BREEDING for Better FORESTs project (B4EST, https://b4est.eu/), we have developed genotyping tools for Poplar, Ash, and Pine forest tree species. SNP arrays are attractive genotyping tools because of the user-friendly genotype calling system and the robust transferability among laboratories. Here we describe the development of an Axiom SNP array for Pinus pinaster (13,407 SNPs), Pinus pinea (5,671 SNPs), Poplar spp. (13,408 SNPs), and Fraxinus spp. (13,407 SNPs) based on a two-step process. We first assembled a high-density (>100,000 SNPs/species) screening array that served to test a large panel of candidate SNPs on a diversity panel involving at least 120 individual trees per species or species group. In the second step, we selected and combined the most informative SNPs to build the final 50,000 SNP 4TREE array. This approach resulted in high genotyping success rates, including for species lacking previously validated high-quality SNP resources. The 4TREE SNP array provides a valuable and transferable genomic tool to support genomic prediction, breeding, and adaptive management of forest tree species.

Premise of studyUnder increasingly frequent pollinator-limited environments, plants need to rely on modes of reproductive assurance such as selfing and cloning. However, few studies investigate the interplay between selfing and cloning in plants that can do both. Here, we explore mechanisms determining the relative expression of selfing and cloning throughout the European distribution of the wild woodland strawberry (Fragaria vesca) under a pollinator-free environment. MethodsWe established an outdoor common garden with 121 woodland strawberry genotypes from across Europe and excluded them from pollinators. For each genotype, we recorded reproductive traits and performed hand-pollination treatments. Key ResultsWe found a weak trade-off between cloning and selfing, driven by increased seed and fruit provisioning rather than flower production. The capacity to autonomously self-fertilize was determined by the lateral proximity of the anthers to the pistils (lateral herkogamy), but not by early inbreeding depression. Genotypes sampled at lower latitudes and altitudes were better at self-fertilizing and had smaller petals. The propensity to clone increased towards the east, where genotypes also had smaller petals, particularly at higher latitudes. ConclusionAt the species level, we detected a trade-off between the propensity for clonal reproduction and the capacity for self-fertilization. At a continental scale, the capacity to self-fertilize varied along a north-south gradient, whereas clonal propensity varied along an east-west gradient. Our results suggest that these two modes of reproductive assurance may compensate for reduced pollinator attractiveness (smaller petals) in regions where each mode is most strongly expressed.

Natural history collections underpin our understanding of species distributions, yet some historical records remain embedded in modern avifaunal checklists despite limited documentation and no independent verification. One such case concerns the Dusky Parrot Pionus fuscus in Colombia: although reported from specimens collected by Melbourne A. Carriker Jr. in 1942 in the Serrania de Perija, the species has not been observed in the country for nearly eight decades yet continues to be included in national checklists and conservation assessments. We reassessed the validity of this record by applying a multi-evidence framework integrating historic archival reconstruction, specimen-based morphological comparisons, climatic niche analyses, biogeographic limit assessment and contemporary survey-effort data. Historical documentation and morphological evidence based on high-resolution specimen images and associated curatorial records demonstrate that the Carriker specimens correspond to Pionus chalcopterus, not P. fuscus. Climatic niche analyses reveal minimal environmental overlap between P. chalcopterus and P. fuscus, and place the Perija locality within the climatic niche of P. chalcopterus, while regional biogeography and extensive modern birdwatching coverage provide no support for the occurrence of P. fuscus in Perija. Together, these concordant lines of evidence demonstrate that P. fuscus does not occur in Colombia. Our findings support its removal from national bird lists and conservation assessments and highlight how integrated, multi-evidence reassessments of historical records strengthen ornithological baselines, improve biogeographic inference and ensure that conservation priorities rest on verifiable evidence.

Grapevine cluster architecture is a key selection target in breeding programs because it influences disease susceptibility, yield stability and juice quality. High-throughput phenotyping offers a rapid and non-destructive approach to capture biochemical and structural variation in these traits, yet the influence of plant organ reflectance and data partitioning strategies on trait prediction remains poorly understood. In this study, we evaluated how hyperspectral reflectance from different grapevine organs contributes to the prediction of cluster architecture and juice quality traits in two clonal populations of Riesling and Pinot. Using partial least squares regression (PLSR), we assessed the prediction accuracy of eight cluster architecture and six juice quality traits under two data partitioning strategies. Models based on cluster reflectance outperformed those using dry leaf reflectance for most traits, except for pH. Partitioning the dataset by cluster type increased trait variance and improved predictions for number of berries (R{superscript 2} = 0.53), berry diameter (R{superscript 2} = 0.79), and total acidity (R{superscript 2} = 0.48). Visible, red-edge and NIR spectra were most informative regions to predict the traits studied. Together, our results highlight the importance of organ-specific data and appropriate calibration strategies to improve phenomic models for the development of scalable proxies for grapevine improvement. HighlightSpectral phenomics reveals that prediction accuracy in grapevine depends on organ spectral signatures and traits, with cluster reflectance outperforming leaves, informing new phenotyping strategies for breeding improvement.

Grapevine Trunk diseases (GTDs) represent a major threat for the wine industry. Despite several break-through, their etiology remains unclear and no curative treatment is currently available. Wood anatomy and water transport contribute to the symptoms of young plant decline. This study investigates wood anatomical alterations in two Alsatian grapevine cultivars presenting different susceptibility to GTDs, focusing on wood structure over six months of vegetative growth and in response to infection. Using a validated FasGa staining protocol, wood sections from transverse, tangential, and radial directions were stained to differentiate lignified and cellulosic tissues. Microscopic analysis was performed at x4, x10, and x40 magnifications, yielding a dataset of 4771 images. To support this high-throughput quantitative analysis of microscopy images, a computational model was developed, enabling reliable and efficient assessment of anatomical traits. Pre-established woody tissues presented higher xylem vessels diameter in Gewurztraminer than Riesling, with a dorsoventral arrangement whereas the number of vessels remained the same all over the cross section. No significant anatomical changes were observed in established woody tissues, whereas newly formed xylem anatomy showed a possible rearrangement during infection, especially in Gewurztraminer cultivar. Furthermore, colorimetric analysis quantified the lignification of woody tissues in response to wounding damage compared to un-treated plants. While definitive conclusions remain limited due to the experimental timeframe and sample variability, the findings highlight the need for longer-term studies and broader cultivar evaluation. Code and microscopy images have been made publicly available, providing a scalable digital tool for future research in plant vascular systems.

Potato (Solanum tuberosum L.) is a staple crop crucial to global food security, yet its production is severely threatened by late blight (LB), caused by Phytophthora infestans, one of the most destructive plant diseases worldwide. Breeding programs for LB resistance have traditionally relied on labor-intensive and subjective visual assessments, which limit scalability and consistency, particularly in early-generation trials. Unmanned aerial vehicle (UAV)-based remote sensing combined with machine learning (ML) offers a promising alternative for objective, high-throughput disease phenotyping. This study evaluated the potential of UAV-derived multispectral imagery and ML techniques to estimate LB severity across large and genetically diverse potato breeding populations, comprising 2,745 clones in one trial and 492 accessions in another, conducted in Oxapampa, Pasco, Peru. We compared vegetation index-based approaches with a machine learning framework that integrates K-means clustering and Kernel Ridge Regression (KRR) and assessed their ability to capture genotypic variation and support selection decisions. NDVI consistently showed a strong correlation with visually assessed LB severity, particularly at advanced stages of disease development, enabling objective discrimination between healthy and diseased canopy tissues. However, the KRR-based approach outperformed linear NDVI-based models by capturing nonlinear relationships between spectral responses and disease progression. Estimates of LB severity derived from NDVI and KRR models, expressed as best linear unbiased estimates (BLUEs), showed strong and biologically consistent relationships with the area under the disease progress curve (AUDPC), particularly during later UAV acquisitions. Selection coincidence between UAV-derived estimates and AUDPC-based rankings was substantially higher at intermediate to advanced stages of disease progression, suggesting that UAV assessments at these stages may capture sufficient phenotypic variation to distinguish genotypes. These findings indicate that UAV-based multispectral phenotyping, especially when integrated with ML, provides a practical and scalable approach for assessing LB severity in potato breeding programs while reducing the need for time-consuming field evaluations.

Lodging in sorghum presents a significant challenge for plant breeders due to the trade-off between lodging resistance and grain yield. Manually measuring lodging across thousands of plots is time-consuming, expensive, and error-prone, making selection for lodging resistance challenging in breeding programs. Unmanned Aerial Vehicle (UAV) derived metrics offer a potential high-throughput, cost-effective alternative for lodging phenotyping. This study developed a framework for predicting plot-level lodging from UAV imagery across 2,675 sorghum breeding plots. Multi-temporal canopy height data were collected at two critical time points: maximum crop height and at manual lodging assessment. Height percentiles were extracted from UAV derived point clouds generated using photogrammetric algorithms. These data were used to develop parametric, non-parametric, and ensemble prediction models, which were evaluated using three statistical metrics. The ensemble model, averaging predictions from all models, achieved the highest accuracy with Pearson correlations of r = 0.80-0.84 and lowest residual mean square error (RMSE=16-18), explaining 64-70% of variation in manual lodging counts. Model diagnostics and iterative refinement, including inspection of UAV imagery and dataset curation, had minimal impact on model performance, demonstrating the robustness of the approach. Model performance was consistent across sites, with minimal effects of stratified sampling on accuracy, confirming the ensemble approach as optimal for plot-level lodging assessment. This study demonstrates that integrated multi-temporal UAV imagery offers a practical alternative to labor-intensive manual evaluation methods by enabling high-throughput lodging assessment suitable for implementation in sorghum breeding programs.

Potato common scab (Streptomyces sp.) is an economically important disease that reduces the quality and market value of tubers. A key aspect in developing management strategies involves accurately quantifying the disease. Due to the three-dimensional nature of the tuber and the heterogeneous distribution of lesions across its surface, visual estimates of severity can be challenging. Therefore, the objectives of this study were to develop and validate a standard area diagram (SAD) for estimating common scab severity on potato tubers and to compare validation outcomes obtained using real tubers and digital images. A SAD comprising six severity levels (from 1.3 to 66.8%) was developed based on image analysis of naturally infected tubers. Validation was conducted using two complementary approaches in which inexperienced raters evaluated either real potato tubers or digital images of the same tubers under unaided and aided conditions. Accuracy, bias components, and inter-rater reliability were quantified using absolute error metrics, Lins concordance correlation coefficient, intraclass correlation coefficients, and overall concordance correlation coefficients. Use of the SAD significantly improved accuracy, reduced systematic bias, and increased inter-rater reliability across both validation approaches. No significant differences were detected between assessments conducted on real tubers and images, although image-based evaluations showed a slight, non-significant tendency toward reduced scale and location bias under aided conditions. These results demonstrate that a dimension-aware SAD integrating information across the full tuber surface enhances the reliability and reproducibility of visual severity assessments and supports the use of image-based evaluations for training, large-scale surveys, and remote or collaborative applications involving three-dimensional plant organs.