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Summary Leaf dark respiration (R_dark), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (V_cmax), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed.Here, we analyzedR_darkvariability and its associations withV_cmaxand other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative.We found that leaf magnesium and calcium concentrations were more significant in explaining cross‐siteR_darkthan commonly used traits like LMA, N and P concentrations, but univariate trait–R_darkrelationships were always weak (r² ≤ 0.15) and forest‐specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait–R_darkrelationships, accurately predicted cross‐siteR_dark(r² = 0.65) and pinpointed the factors contributing toR_darkvariability.Our findings reveal a few novel traits with greater cross‐site scalability regardingR_dark, challenging the use of empirical trait–R_darkrelationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimatingR_dark, which could ultimately improve process modeling of terrestrial plant respiration. 

Abstract Tropical tree communities are among the most diverse in the world. A small number of genera often disproportionately contribute to this diversity. How so many species from a single genus can co‐occur represents a major outstanding question in biology. Niche differences are likely to play a major role in promoting congeneric diversity, but the mechanisms of interest are often not well‐characterized by the set of functional traits generally measured by ecologists.To address this knowledge gap, we used a functional genomic approach to investigate the mechanisms of co‐occurrence in the hyper‐diverse genusFicus. Our study focused on over 800 genes related to drought and defence, providing detailed information on how these genes may contribute to the diversity ofFicusspecies.We find widespread and consistent evidence of the importance of defence gene dissimilarity in co‐occurring species, providing genetic support for what would be expected under the Janzen‐Connell mechanism. We also find that drought‐related gene sequence similarity is related toFicusco‐occurrence, indicating that similar responses to drought promote co‐occurrence.Synthesis. We provide the first detailed functional genomic evidence of how drought‐ and defence‐related genes simultaneously contribute to the local co‐occurrence in a hyper‐diverse genus. Our results demonstrate the potential of community transcriptomics to identify the drivers of species co‐occurrence in hyper‐diverse tropical tree genera. 

The ecology of forest ecosystems depends on the composition of trees. Capturing fine-grained information on individual trees at broad scales provides a unique perspective on forest ecosystems, forest restoration, and responses to disturbance. Individual tree data at wide extents promises to increase the scale of forest analysis, biogeographic research, and ecosystem monitoring without losing details on individual species composition and abundance. Computer vision using deep neural networks can convert raw sensor data into predictions of individual canopy tree species through labeled data collected by field researchers. Using over 40,000 individual tree stems as training data, we create landscape-level species predictions for over 100 million individual trees across 24 sites in the National Ecological Observatory Network (NEON). Using hierarchical multi-temporal models fine-tuned for each geographic area, we produce open-source data available as 1 km²shapefiles with individual tree species prediction, as well as crown location, crown area, and height of 81 canopy tree species. Site-specific models had an average performance of 79% accuracy covering an average of 6 species per site, ranging from 3 to 15 species per site. All predictions are openly archived and have been uploaded to Google Earth Engine to benefit the ecology community and overlay with other remote sensing assets. We outline the potential utility and limitations of these data in ecology and computer vision research, as well as strategies for improving predictions using targeted data sampling. 

Abstract Forest trees provide critical ecosystem services for humanity that are under threat due to ongoing global change. Measuring and characterizing genetic diversity are key to understanding adaptive potential and developing strategies to mitigate negative consequences arising from climate change. In the area of forest genetic diversity, genetic divergence caused by large-scale changes at the chromosomal level has been largely understudied. In this study, we used the RNA-seq data of 20 co-occurring forest trees species from genera including Acer, Alnus, Amelanchier, Betula, Cornus, Corylus, Dirca, Fraxinus, Ostrya, Populus, Prunus, Quercus, Ribes, Tilia, and Ulmus sampled from Upper Peninsula of Michigan. These data were used to infer the origin and maintenance of gene family variation, species divergence time, as well as gene family expansion and contraction. We identified a signal of common whole genome duplication events shared by core eudicots. We also found rapid evolution, namely fast expansion or fast contraction of gene families, in plant–pathogen interaction genes amongst the studied diploid species. Finally, the results lay the foundation for further research on the genetic diversity and adaptive capacity of forest trees, which will inform forest management and conservation policies. 

Abstract Metabolomics provides an unprecedented window into diverse plant secondary metabolites that represent a potentially critical niche dimension in tropical forests underlying species coexistence. Here, we used untargeted metabolomics to evaluate chemical composition of 358 tree species and its relationship with phylogeny and variation in light environment, soil nutrients, and insect herbivore leaf damage in a tropical rainforest plot. We report no phylogenetic signal in most compound classes, indicating rapid diversification in tree metabolomes. We found that locally co‐occurring species were more chemically dissimilar than random and that local chemical dispersion and metabolite diversity were associated with lower herbivory, especially that of specialist insect herbivores. Our results highlight the role of secondary metabolites in mediating plant–herbivore interactions and their potential to facilitate niche differentiation in a manner that contributes to species coexistence. Furthermore, our findings suggest that specialist herbivore pressure is an important mechanism promoting phytochemical diversity in tropical forests. 

Abstract Background and AimsUnderstanding shifts in the demographic and functional composition of forests after major natural disturbances has become increasingly relevant given the accelerating rates of climate change and elevated frequency of natural disturbances. Although plant demographic strategies are often described across a slow–fast continuum, severe and frequent disturbance events influencing demographic processes may alter the demographic trade-offs and the functional composition of forests. We examined demographic trade-offs and the shifts in functional traits in a hurricane-disturbed forest using long-term data from the Luquillo Forest Dynamics Plot (LFPD) in Puerto Rico. MethodsWe analysed information on growth, survival, seed rain and seedling recruitment for 30 woody species in the LFDP. In addition, we compiled data on leaf, seed and wood functional traits that capture the main ecological strategies for plants. We used this information to identify the main axes of demographic variation for this forest community and evaluate shifts in community-weighted means for traits from 2000 to 2016. Key ResultsThe previously identified growth–survival trade-off was not observed. Instead, we identified a fecundity–growth trade-off and an axis representing seedling-to-adult survival. Both axes formed dimensions independent of resprouting ability. Also, changes in tree species composition during the post-hurricane period reflected a directional shift from seedling and tree communities dominated by acquisitive towards conservative leaf economics traits and large seed mass. Wood specific gravity, however, did not show significant directional changes over time. ConclusionsOur study demonstrates that tree demographic strategies coping with frequent storms and hurricane disturbances deviate from strategies typically observed in undisturbed forests, yet the shifts in functional composition still conform to the expected changes from acquisitive to conservative resource-uptake strategies expected over succession. In the face of increased rates of natural and anthropogenic disturbance in tropical regions, our results anticipate shifts in species demographic trade-offs and different functional dimensions. 

ABSTRACT Lianas, climbing woody plants, influence the structure and function of tropical forests. Climbing traits have evolved multiple times, including ancestral groups such as gymnosperms and pteridophytes, but the genetic basis of the liana strategy is largely unknown. Here, we use a comparative transcriptomic approach for 47 tropical plant species, including ten lianas of diverse taxonomic origins, to identify genes that are consistently expressed or downregulated only in lianas. Our comparative analysis of full-length transcripts enabled the identification of a core interactomic network common to lianas. Sets of transcripts identified from our analysis reveal features related to functional traits pertinent to leaf economics spectrum in lianas, include upregulation of genes controlling epidermal cuticular properties, cell wall remodeling, carbon concentrating mechanism, cell cycle progression, DNA repair and a large suit of downregulated transcription factors and enzymes involved in ABA-mediated stress response as well as lignin and suberin synthesis. All together, these genes are known to be significant in shaping plant morphologies through responses such as gravitropism, phyllotaxy and shade avoidance.