Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long‐lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time‐series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population‐level time‐series from 974 species in 66 countries. The mean and median time‐series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well‐studied species, MASTREE+ includes extensive replication of time‐series across geographical and climatic gradients. Here we describe the open‐access data set, available as a.csv file, and we introduce an associated web‐based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long‐lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics.

Patagonian forests are the southernmost temperate forests in the world, andNothofagus pumiliois one of their most ecologically important tree species (i.e., a foundation species). It presents great adaptability and a wide distribution range, making it a suitable model for predicting the performance of trees facing global climate change.N. pumilioforests are increasingly threatened by extreme climatic events and anthropogenic activities. This study aims to identify priority conservation areas and Genetic Zones (GZs) forN. pumilio, promoting the implementation of specific practices to ensure its management and long-term preservation. Thirty-five populations (965 trees) sampled across its distribution (more than 2200 km latitudinally) were genotyped with SSRs, and geographical patterns of genetic variation were identified using Bayesian approaches. The phylogeographic patterns of the species and geomorphological history of the region were also considered. Six priority conservation areas were identified, which hold high allelic richness and/or exclusive allelic variants. Eighteen GZs were delineated based on the genetic structure of this species, and maps showing their distributional range were drawn up. Overall, this study defines management units based on genetic data forN. pumiliofor the first time, which will facilitate the establishment of sustainable practices and highlight priorities for investment of conservation funding.