We decipher global patterns in seagrass growth and structure to advance seagrass science, facilitate multidisciplinary research, and promote effective management strategies and policy development for seagrass habitats. A global data set on seagrass total biomass, total NPP, shoot density, and percent cover was compiled for 11 genera. Here, we tested how these variables change across seagrass genera, life-history strategy, and geographic location, and then sought to decipher the environmental drivers of the patterns observed. The mean (±SE) total biomass of seagrasses globally was estimated at 340 ± 10 g DW m -2, and total NPP was estimated at 5.4 ± 0.4 g DW m -2 d-1. Mean shoot density across all genera was 1,780 ± 67 shoots m-2, and percent cover was 42 ± 1%. Persistent genera showed the highest total biomass, followed by opportunistic and then colonising genera, whereas shoot density was higher for colonising than for persistent, which had the highest percent cover. Latitudinal and bioregional patterns were identified for some genera, and were mostly driven by genus-specific traits, followed by localised environmental factors. Trends in seagrass meadow ecology were largely influenced by seagrass genera and their life-history strategy, with localised environmental factors, such as temperature and nutrients, also playing a role. Global estimates of seagrass biomass and NPP were 2 times higher than previously reported. Seagrass life-history strategies modulate the trade-offs between NPP and biomass to thrive in specific habitats. This study provides the most updated global synthesis of patterns in seagrass growth and structure

N.R.F. received funding from the European Union's Horizon Europe Training and mobility actions under the Marie Skłodowska Curie grant 101105307-POSIDONIArXiv. This research was supported by I + D + i projects RYC2019-027073-I and MEDCHANGE funded by MCIN/AEI/10.13039/501100011033. E.G. was supported by ‘Pla de Doctorats Industrials del Departament de Recerca i Universitats de la Generalitat de Catalunya’. U.M. was supported by the PREDOC BERRI Fellowship Program of the Basque Government. V.P. acknowledges the support received from the Beatriu de Pinós program (2022BP00112) and Grant CEX2019-000928-S funded by AEI 10.13039/501100011033. A.M.R. received the support of a fellowship from ‘la Caixa’ Foundation (LCF/BQ/PI23/11970014) and project CNS2023-145492 funded by MCIN/AEI/10.13039/501100011033 and European Union ‘NextGenerationEU’/PRTR. D.I.M. was supported by ‘Programa de Becas Externas Postdoctorales para Jóvenes Investigadores del CONICET’

Description of the data and file structure: Data file of metadata and seagrass variables extracted from studies looking at seagrass productivity and structure from 1975-2024 and environmental variable data from Bio-ORACLE v2.0 (2000-2014). Empty cells denoted that data was not available. R script for processing analysis and graphing Files and variables File: Final_code_analysis_and_plotting.R Description: Code for analysing and plotting data. This R script imports and cleans a seagrass dataset, adds biological and geographic classifications,customize the appearance of the ggplot map and counts the number of non-missing observations of total productivity per genus. File: Dataset_ecological_biomass_complete.csv Description: Seagrass ecology variable data collected from meta-analyses including informati,on on location and BIO-oracle environmental data

Peer reviewed