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Understanding phenological responses of tropical forest plant communities is crucial for identifying climate-induced changes in ecosystem dynamics. Monitoring phenology across diverse species in natural habitats provides cost-effective insights for conserving both species and forests. We studied tree phenology in a lowland evergreen dipterocarp forest in the Western Ghats, India. About 719 tree individuals representing 95 species were monitored for their vegetative and reproductive phenology from April 2021 to September 2023. Circular statistics detected seasonality in phenological events and Generalized Linear Mixed Modelling (GLMM) identified influence of climate variables on the phenological responses of the tree community. We also assessed how the activity and intensity of phenophases vary over the study period. Our results showed that leaf flushing and flowering peaked during the dry season, with mass flowering observed in two dominant dipterocarps. Fruit production peaked before the monsoon. We also observed diversity in vegetative and reproductive phenodynamics across species groups (forest strata, sexual system, and seed size). Leaf flushing was positively correlated with maximum relative humidity and negatively correlated with maximum temperature and the number of rainy days. Flowering had negative correlations with maximum relative humidity, rainfall days, and maximum temperature but showed a positive correlation with minimum temperature. Fruiting was positively correlated with maximum temperature and negatively correlated with rainy days. This detailed phenological information provides critical knowledge on resource availability and insights into how climate and seasonal changes affect plant growth cycles thereby aiding reforestation and biodiversity conservation strategies in vulnerable forest areas., (© 2024. The Author(s) under exclusive licence to International Society of Biometeorology.)

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research-from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology-from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene., Main Types of Variables Included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record., Spatial Location and Grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 )., Time Period and Grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year., Major Taxa and Level of Measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates., Software Format: .csv and .SQL.