Data and code from: Data integration advances reproductive phenology research across temporal, spatial, and taxonomic scales

Climate change is altering plant reproductive phenology; however, a scarcity of long-term, systematic monitoring hinders our ability to quantify and predict these responses in many parts of the world. We addressed this gap by demonstrating how data integration can be used to produce a synthesised record of reproductive phenology observations (flowering and fruiting) that spans longer time periods, larger spatial scales, and includes more species than any single source alone. Using Australian subtropical rainforest trees as a case study, we integrated reproductive phenology observations from both common data sources—published datasets, herbarium specimens, and citizen science records—and previously untapped expert botanical knowledge, including private photographic collections, field notes, and seed collections. Data integration yielded 110,657 records of flowers or fruits from 915 species (representing half of all subtropical rainforest tree species) spanning 255 years (1770-2025). We f..., , # Data and code from: Data integration advances reproductive phenology research across temporal, spatial, and taxonomic scales

Ella Cathcart van Weeren

## Dataset overview

This dataset contains reproductive phenology data (observations of flowering and fruiting events) and code to replicate analysis in Cathcart-van Weeren et al (2026), testing the hypothesis that different sources of reproductive phenological data provide complementary, rather than redundant, observations of plant reproductive phenology.

The dataset integrates multiple data sources (published datasets, herbarium specimens, iNaturalist observations, expert botanist field notes, photo collections, and seed collection records) representing 915 species of Australian subtropical rainforest trees spanning 255 years (1770-2025). It provides a comprehensive temporal and spatial coverage of (mostly) presence-only reproductive observations.

The data support analyses of a variety of phenological patterns across many spatial a...,