Deep learning models map rapid plant species changes from citizen science and remote sensing data.

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model-Deepbiosphere-not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Understanding processes underlying cross-taxon congruence in species composition along elevational gradients.

Changes in species diversity of different taxa along environmental gradients are usually correlated, resulting in a pattern called cross-taxon congruence. This pattern can be due to functional relationships between taxa, a common response to niche-related processes, or stochastic processes. However, it remains unclear the extent to which they contribute to the association among patterns of changes in species composition, (i.e., beta diversity), and whether these changes are related to species nestedness and turnover. Here we described patterns of change in the taxonomic composition of plant and orthopteran assemblages along an elevational gradient in Cordoba province, central Argentina. We assessed cross-taxon congruence and identified the main environmental variables accounting for such patterns. Mantel correlations showed congruence between the patterns of taxonomic dissimilarity of plants and orthopterans. According Generalized disiimilarity models (GDM) the main environmental variables driving the patterns were temperature for both taxa, and changes in soil nutrient content for plants, spatial effects were also found. Beta diversity was mainly due to species turnover for orthopterans and plants, indicating replacement by species adapted to elevational conditions. Niche-related process, such as environmetal filtering, along with neutral processes may have contributed to cross-taxon congruence in beta diversity.

Early Pennsylvanian Lagerstätte reveals a diverse ecosystem on a subhumid, alluvial fan.

Much of what we know about terrestrial life during the Carboniferous Period comes from Middle Pennsylvanian (~315-307 Mya) Coal Measures deposited in low-lying wetland environments1-5. We know relatively little about terrestrial ecosystems from the Early Pennsylvanian, which was a critical interval for the diversification of insects, arachnids, tetrapods, and seed plants6-10. Here we report a diverse Early Pennsylvanian trace and body fossil Lagerstätte (~320-318 Mya) from the Wamsutta Formation of eastern North America, distinct from coal-bearing deposits, preserved in clastic substrates within basin margin conglomerates. The exceptionally preserved trace fossils and body fossils document a range of vertebrates, invertebrates and plant taxa (n = 131), with 83 distinct foliage morphotypes. Plant-insect interactions include what may be the earliest evidence of insect oviposition. This site expands our knowledge of early terrestrial ecosystems and organismal interactions and provides ground truth for future phylogenetic reconstructions of key plant, arthropod, and vertebrate groups.

[Spatial Distribution Characteristics of Plant Community and the Identification of Driving Factors in Riparian Zone of the Three-River Headwaters Region, China].

The unique geographical and climatic conditions in the Three-River Headwaters Region gave birth to distinctive plant species and vegetation types. To reveal the spatial distribution of plant communities and soil habitats along the riparian zone of the Sanjiangyuan Region and their influencing mechanisms, 14 survey plots were set up （ten from the Yangtze River source, two from the Lancang River source, and two from the Yellow River source）, and the effects of soil nutrient characteristics （especially soil phosphorus morphology）, climate factors, and river topography on plant community characteristics were quantitatively analyzed. The results showed that the plant community composition in the riparian zone of the source of the three rivers was dominated by perennial herbs （72.2%）, followed by annual herbs （20.4%） and shrubs （7.4%）. The dominant plants were Stipa purpurea, Polygonum orbiculatum, Carex parvula, Potentilla anserina, and Gentiana straminea. The average plant coverage, Shannon-Wiener index, and Pielou index were （64.4% ±23.6%）, （1.31 ±0.42）, and （0.84 ±0.08）, respectively. The plant community diversity index was the highest in the Yangtze River source, followed by that in the Lancang River source, and the lowest in the Yellow River source. The soil pH of the riparian zone of the Yangtze River source was significantly higher than that of the Lancang River source, whereas the mean contents of organic matter, total nitrogen, and Fe-Al combined phosphorus were significantly lower than those of the Lancang River source. The calcium and magnesium-combined phosphorus was the main form of phosphorus in riparian soil （63.89%）. Temperature, soil organic phosphorus content, and pH had significant effects on plant composition in the riparian zone of the Three-River Headwaters Region, whereas soil calcium and magnesium-combined phosphorus content had significant effects on plant community diversities. These results may deepen the scientific understanding of the evolution trend and genetic mechanism of plant communities in the riparian zone of the Three-River Headwaters Region.

Naturalized species drive functional trait shifts in plant communities.

Despite decades of research documenting the consequences of naturalized and invasive plant species on ecosystem functions, our understanding of the functional underpinnings of these changes remains rudimentary. This is partially due to ineffective scaling of trait differences between native and naturalized species to whole plant communities. Working with data from over 75,000 plots and over 5,500 species from across the United States, we show that changes in the functional composition of communities associated with increasing abundance of naturalized species mirror the differences in traits between native and naturalized plants. We find that communities with greater abundance of naturalized species are more resource acquisitive aboveground and belowground, shorter, more shallowly rooted, and increasingly aligned with an independent strategy for belowground resource acquisition via thin fine roots with high specific root length. We observe shifts toward herbaceous-dominated communities but shifts within both woody and herbaceous functional groups follow community-level patterns for most traits. Patterns are remarkably similar across desert, grassland, and forest ecosystems. Our results demonstrate that the establishment and spread of naturalized species, likely in combination with underlying environmental shifts, leads to predictable and consistent changes in community-level traits that can alter ecosystem functions.

The impact of trait number and correlation on functional diversity metrics in real-world ecosystems.

The use of trait-based approaches to understand ecological communities has increased in the past two decades because of their promise to preserve more information about community structure than taxonomic methods and their potential to connect community responses to subsequent effects of ecosystem functioning. Though trait-based approaches are a powerful tool for describing ecological communities, many important properties of commonly-used trait metrics remain unexamined. Previous work with simulated communities and trait distributions shows sensitivity of functional diversity measures to the number and correlation of traits used to calculate them, but these relationships have yet to be studied in actual plant communities with a realistic distribution of trait values, ecologically meaningful covariation of traits, and a realistic number of traits available for analysis. To address this gap, we used data from six grassland plant communities in Minnesota and New Mexico, USA to test how the number of traits and the correlation between traits used in the calculation of eight functional diversity indices impact the magnitude of functional diversity metrics in real plant communities. We found that most metrics were sensitive to the number of traits used to calculate them, but functional dispersion (FDis), kernel density estimation dispersion (KDE dispersion), and Rao's quadratic entropy (Rao's Q) maintained consistent rankings of communities across the range of trait numbers. Despite sensitivity of metrics to trait correlation, there was no consistent pattern between communities as to how metrics were affected by the correlation of traits used to calculate them. We recommend that future use of evenness metrics include sensitivity analyses to ensure results are robust to the number of traits used to calculate them. In addition, we recommend use of FDis, KDE dispersion, and Rao's Q when ecologically applicable due to their ability to produce consistent rankings among communities across a range of the numbers of traits used to calculate them.

Niche and interspecific associations of dominant plant species in antimony mining ecological damaged site in Nandan, Guangxi, China.

In order to provide a guide for plant selection of ecological restoration at antimony (Sb) mining ecological damaged sites, species composition, importance value, niche, and interspecific associations of tree, shrub, and herb layers were examined at Sb mining site in Nandan City, Guangxi, China. The results showed that 23 vascular plant species were recorded at the Sb mining ecological damaged site, belonging to 22 genera and 13 families, primarily Gramineae, Cyperaceae, Fabaceae, and Asteraceae. The highest importance values for trees, shrubs, and herbs were observed in Rhus chinensis (56.7%), Coriaria nepalensis (56.3%), and Eremochloa ciliaris (44.0%), which were characterized by fairly large niche widths of 1.58, 1.32 and 1.57, respectively. The highest niche overlap values were found between R. chinensis and Triadica sebifera in the tree layer, and between Thysanolaena latifolia and Bidens pilosa in the herb layer, with the value of 0.68 and 0.99, respectively. Shrub layer exhibited a lower range of niche overlap (0.30-0.42), suggesting significant niche differentiation among different species. In the tree and shrub layers, most species showed insignificantly negative associations, the proportion was 83.3% and 66.7%, respectively, indicating that the plant community was not stable. Herb layer generally exhibited significantly positive correlations, with 52.4% of species pairs showing positive correlation, indicating weak resource competition among species. Overall, plant community at Sb mining ecological damaged site was unstable. In the process of ecological restoration, trees and shrubs that can adapt to the conditions and have positive associations should be prioritized in species selection, such as R. chinensis, C. lanceolata, C. nepalensis, and B. nivea. This will promote vegetation positive succession, rehabilitate the ecosystem and ensure sustainable development at Sb mining ecological damaged sites.

Predicting undetected native vascular plant diversity at a global scale.

Vascular plants are diverse and a major component of terrestrial ecosystems, yet their geographic distributions remain incomplete. Here, I present a global database of vascular plant distributions by integrating species distribution models calibrated to species' dispersal ability and natural habitats to predict native range maps for 201,681 vascular plant species into unsurveyed areas. Using these maps, I uncover unique patterns of native vascular plant diversity, endemism, and phylogenetic diversity revealing hotspots in underdocumented biodiversity-rich regions. These hotspots, based on detailed species-level maps, show a pronounced latitudinal gradient, strongly supporting the theory of increasing diversity toward the equator. I trained random forest models to extrapolate diversity patterns under unbiased global sampling and identify overlaps with modeled estimations but unveiled cryptic hotspots that were not captured by modeled estimations. Only 29% to 36% of extrapolated plant hotspots are inside protected areas, leaving more than 60% outside and vulnerable. However, the unprotected hotspots harbor species with unique attributes that make them good candidates for conservation prioritization.

Topography and soil variables drive the plant community distribution pattern and species richness in the Arjo-Diga forest in western Ethiopia.

Understanding plant community characteristics, distributions, and environmental relationships is crucial for sustainable forest management. Thus, this study examined the relationships between plant community composition and topographic and soil variables within the Arjo-Diga forest. Vegetation data were collected from 72 nested plots (30 × 30 m2 and 2 × 2 m2) systematically laid along nine transects spaced 300 to 700 m apart. Environmental variables, including soil properties and anthropogenic disturbance, were recorded within each main plot. Agglomerative hierarchical cluster analysis and canonical correspondence analysis (CCA) using R software were employed to identify distinct plant community types and examine their relationships with environmental factors. The Shannon‒Wiener diversity index was calculated to quantify and compare species diversity among the identified community types. The analysis revealed five distinct plant community types: 1: Maesa lanceolata-Ehretia cymosa, 2: Trichilia dregeana-Flacourtia indica, 3: Acacia abyssinica-Millettia ferruginea, 4: Combretum collinum-Croton macrostachyus, and 5: Terminalia macroptera-Piliostigma thonningii. The CCA results highlighted the significant influence (p < 0.05) of altitude, CEC, TN, and disturbance on species distribution and plant community formation. The findings indicate that variation in plant communities is closely associated with altitude, TN, and CEC, as well as with disturbance factors such as human interventions, with elevation being the most influential factor. Based on these findings, it is recommended that conservation plans consider the effects of human interventions to address the challenges in conserving forests in the future. Additionally, further research efforts should focus on mitigating disturbance factors and understanding the environmental variables that affect forests to improve their protection.

Unravelling large-scale patterns and drivers of biodiversity in dry rivers.

More than half of the world's rivers dry up periodically, but our understanding of the biological communities in dry riverbeds remains limited. Specifically, the roles of dispersal, environmental filtering and biotic interactions in driving biodiversity in dry rivers are poorly understood. Here, we conduct a large-scale coordinated survey of patterns and drivers of biodiversity in dry riverbeds. We focus on eight major taxa, including microorganisms, invertebrates and plants: Algae, Archaea, Bacteria, Fungi, Protozoa, Arthropods, Nematodes and Streptophyta. We use environmental DNA metabarcoding to assess biodiversity in dry sediments collected over a 1-year period from 84 non-perennial rivers across 19 countries on four continents. Both direct factors, such as nutrient and carbon availability, and indirect factors such as climate influence the local biodiversity of most taxa. Limited resource availability and prolonged dry phases favor oligotrophic microbial taxa. Co-variation among taxa, particularly Bacteria, Fungi, Algae and Protozoa, explain more spatial variation in community composition than dispersal or environmental gradients. This finding suggests that biotic interactions or unmeasured ecological and evolutionary factors may strongly influence communities during dry phases, altering biodiversity responses to global changes.

Unforeseen plant phenotypic diversity in a dry and grazed world.

Earth harbours an extraordinary plant phenotypic diversity1 that is at risk from ongoing global changes2,3. However, it remains unknown how increasing aridity and livestock grazing pressure-two major drivers of global change4-6-shape the trait covariation that underlies plant phenotypic diversity1,7. Here we assessed how covariation among 20 chemical and morphological traits responds to aridity and grazing pressure within global drylands. Our analysis involved 133,769 trait measurements spanning 1,347 observations of 301 perennial plant species surveyed across 326 plots from 6 continents. Crossing an aridity threshold of approximately 0.7 (close to the transition between semi-arid and arid zones) led to an unexpected 88% increase in trait diversity. This threshold appeared in the presence of grazers, and moved toward lower aridity levels with increasing grazing pressure. Moreover, 57% of observed trait diversity occurred only in the most arid and grazed drylands, highlighting the phenotypic uniqueness of these extreme environments. Our work indicates that drylands act as a global reservoir of plant phenotypic diversity and challenge the pervasive view that harsh environmental conditions reduce plant trait diversity8-10. They also highlight that many alternative strategies may enable plants to cope with increases in environmental stress induced by climate change and land-use intensification.

Phylogenetic evidence clarifies the history of the extrusion of Indochina.

The southeastward extrusion of Indochina along the Ailao Shan-Red River shear zone (ARSZ) is one of two of the most prominent consequences of the India-Asia collision. This plate-scale extrusion has greatly changed Southeast Asian topography and drainage patterns and effected regional climate and biotic evolution. However, little is known about how Indochina was extruded toward the southeast over time. Here, we sampled 42 plant and animal clades (together encompassing 1,721 species) that are distributed across the ARSZ and are not expected to disperse across long distances. We first assess the possible role of climate on driving the phylogenetic separations observed across the ARSZ. We then investigate the temporal dynamics of the extrusion of Indochina through a multitaxon analysis. We show that the lineage divergences across the ARSZ were most likely associated with the Indochinese extrusion rather than climatic events. The lineage divergences began at ~53 Ma and increased sharply ~35 Ma, with two peaks at ~19 Ma and ~7 Ma, and one valley at ~13 Ma. Our results suggest a two-phase model for the extrusion of Indochina, and in each phase, the extrusion was subject to periods of acceleration and decrease, in agreement with the changes of the India-Asia convergence rate and angle from the early Eocene to the late Miocene. This study highlights that a multitaxon analysis can illuminate the timing of subtle historical events that may be difficult for geological data to pinpoint and can be used to explore other tectonic events.

Relationship between soil and species diversity in typical forest stands in Xianrendong, Liaoning Province based on plant-soil feedback.

Exploring the relationship between soil properties and species diversity in typical forest stands in Liaoning Xianrendong National Nature Reserve will help maintain the stability of forest communities in the transition zone between flora in Changbai and North China. Based on the plant-soil feedback theory, community sample data from nine typical forest stands in the study area and experimental test data from 54 soil samples, we selected indexes of soil physical and chemical properties based on the minimum data set (temperature, compactness, capillary pore space, bulk weight, capillary water holding capacity, drainage capacity, soil water storage, conductivity, pH, organic matter, Ca, Fe, K, N and P). We adopt the research method of classical statistical analysis. The soil properties of nine typical stands in Xianrendong National Nature Reserve of Liaoning Province were systematically analyzed. The relationship between soil properties and forest stands' species diversity was quantified using correlation and redundancy analyses. The Pearson correlation analysis results showed significant positive correlations between the Gleason abundance index (arbors) with conductivity, pH, organic matter, Ca, N and P; Pielou's evenness index (arbors) with bulk weight and Fe. Significant negative correlations between the Gleason abundance index (arbors) with capillary pore space, bulk weight, drainage capacity, soil water storage and capillary water holding capacity; Simpson dominance index and Shannon-Wiener diversity index with capillary water holding capacity, drainage capacity and soil water storage; Pielou's evenness index (arbors) with Ca and N. The natural moisture content and clay particles are neutral feedback. The results showed that the feedback mechanism of soil physicochemical properties on stand species diversity was complex, which was conducive to species coexistence and community stability.

Woody plant species richness and productivity relationship in a subtropical forest: The predominant role of common species.

A long-standing key issue for examining the relationships between biodiversity and ecosystem functioning (BEF), such as forest productivity, is whether ecosystem functions are influenced by the total number of species or the properties of a few key species. Compared with controlled ecosystem experiments, the BEF relationships in secondary forest remain unclear, as do the effects of common species richness and rare species richness on the variation in ecosystem functions. To address this issue, we conducted field surveys at five sampling sites (1 ha each) with subtropical secondary evergreen broad-leaved forest vegetation. We found (1) a positive correlation between species richness and standing aboveground biomass (AGB); (2) that common species were primarily responsible for the distribution patterns of species abundance and dominance; although they accounted for approximately 25% of the total species richness on average, they represented 86-91% of species abundance and 88-97% of species dominance; and (3) that common species richness could explain much more of the variation in AGB than total species richness (common species plus rare species) at both the site and plot scales. Because rare species and common species were not equivalent in their ability to predict productivity in the biodiversity-ecosystem productivity model, redundant information should be eliminated to obtain more accurate results. Our study suggested that woody plant species richness and productivity relationship in subtropical forest ecosystem can be explained and predicted by a few common species.

DiasMorph: a dataset of morphological traits and images of Central European diaspores.

We present DiasMorph, a dataset of images and traits of diaspores from 1,442 taxa in 519 genera, and 96 families from Central Europe, totalling 94,214 records. The dataset was constructed following a standardised and reproducible image analysis method. The image dataset consists of diaspores against a high-contrast background, enabling a simple and efficient segmentation process. The quantitative traits records go beyond traditional morphometric measurements, and include colour and contour features, which are made available for the first time in a large dataset. These measurements correspond to individual diaspores, an input currently unavailable in traits databases, and allow for several approaches to explore the morphological traits of these species. Additionally, information regarding the presence and absence of appendages and structures both in the images and diaspores of the assessed taxa is also included. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications.

Global biogeographic regions for ants have complex relationships with those for plants and tetrapods.

On a global scale, biodiversity is geographically structured into regions of biotic similarity. Delineating these regions has been mostly targeted for tetrapods and plants, but those for hyperdiverse groups such as insects are relatively unknown. Insects may have higher biogeographic congruence with plants than tetrapods due to their tight ecological and evolutionary links with the former, but it remains untested. Here, we develop a global regionalization for a major and widespread insect group, ants, based on the most comprehensive distributional and phylogenetic information to date, and examine its similarity to regionalizations for tetrapods and vascular plants. Our ant regionalization supports the newly proposed Madagascan and Sino-Japanese realms based on tetrapod delineations, and it recovers clusters observed in plants but not in tetrapods, such as the Holarctic and Indo-Pacific realms. Quantitative comparison suggests strong associations among different groups-plants showed a higher congruence with ants than with tetrapods. These results underscore the wide congruence of diverse distribution patterns across the tree of life and the similarities shared by insects and plants that are not captured by tetrapod groups. Our analysis highlights the importance of developing global biogeographic maps for insect groups to obtain a more comprehensive geographic picture of life on Earth.

CoRRE Trait Data: A dataset of 17 categorical and continuous traits for 4079 grassland species worldwide.

In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species' responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide.

Mapping of specialized metabolite terms onto a plant phylogeny using text mining and large language models.

Plants produce a staggering array of chemicals that are the basis for organismal function and important human nutrients and medicines. However, it is poorly defined how these compounds evolved and are distributed across the plant kingdom, hindering a systematic view and understanding of plant chemical diversity. Recent advances in plant genome/transcriptome sequencing have provided a well-defined molecular phylogeny of plants, on which the presence of diverse natural products can be mapped to systematically determine their phylogenetic distribution. Here, we built a proof-of-concept workflow where previously reported diverse tyrosine-derived plant natural products were mapped onto the plant tree of life. Plant chemical-species associations were mined from literature, filtered, evaluated through manual inspection of over 2500 scientific articles, and mapped onto the plant phylogeny. The resulting "phylochemical" map confirmed several highly lineage-specific compound class distributions, such as betalain pigments and Amaryllidaceae alkaloids. The map also highlighted several lineages enriched in dopamine-derived compounds, including the orders Caryophyllales, Liliales, and Fabales. Additionally, the application of large language models, using our manually curated data as a ground truth set, showed that post-mining processing can largely be automated with a low false-positive rate, critical for generating a reliable phylochemical map. Although a high false-negative rate remains a challenge, our study demonstrates that combining text mining with language model-based processing can generate broader phylochemical maps, which will serve as a valuable community resource to uncover key evolutionary events that underlie plant chemical diversity and enable system-level views of nature's millions of years of chemical experimentation.