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Abstract Terrestrial plant communities show great variation in their annual rhythms of growth, or seasonal phenology^1,2. The geographical patterns resulting from this variation, known as land surface phenology (LSP)³, contain valuable information for the study of ecosystem function^4,5, plant ecophysiology^6–8, landscape ecology^9,10and evolutionary biogeography^11–13. Yet globally consistent LSP mapping has been hampered by methods that struggle to represent the full range of seasonal phenologies occurring across terrestrial biomes¹⁴, especially the subtle and complex phenologies of many arid and tropical ecosystems^1,15,16. Here, using a data-driven analysis of satellite imagery to map LSP worldwide, we provide insights into Earth’s phenological diversity, documenting both intercontinental convergence between similar climates and regional heterogeneity associated with topoclimate, ecohydrology and vegetation structure. We then map spatial phenological asynchrony and the modes of asynchronous seasonality that control it, identifying hotspots of asynchrony in tropical mountains and Mediterranean climate regions and reporting evidence for the hypothesis that climatically similar sites exhibit greater phenological asynchrony within the tropics. Finally, we find that our global LSP map predicts complex geographical discontinuities in flowering phenology, genetic divergence and even harvest seasonality across a range of taxa, establishing remote sensing as a crucial tool for understanding the ecological and evolutionary consequences of allochrony by allopatry. 

ABSTRACT Landscape genomic approaches for detecting genotype‐environment associations (GEA), isolation by distance (IBD) and isolation by environment (IBE) have seen a dramatic increase in use, but there have been few thorough analyses of the influence of sampling strategy on their performance under realistic genomic and environmental conditions. We simulated 24,000 datasets across a range of scenarios with complex population dynamics and realistic landscape structure to evaluate the effects of the spatial distribution and number of samples on common landscape genomics methods. Our results show that common analyses are relatively robust to sampling scheme as long as sampling covers enough environmental and geographic space. We found that for detecting adaptive loci and estimatingIBE, sampling schemes that were explicitly designed to increase coverage of available environmental space matched or outperformed sampling schemes that only considered geographic space. When sampling does not cover adequate geographic and environmental space, such as with transect‐based sampling, we detected fewer adaptive loci and had higher error when estimatingIBDandIBE. We found thatIBDcould be detected with as few as nine sampling sites, while large sample sizes (e.g., greater than 100 individuals) were crucial for detecting adaptive loci andIBE. We also demonstrate that, even with optimal sampling strategies, landscape genomic analyses are highly sensitive to landscape structure and migration—when spatial autocorrelation and migration are weak, commonGEAmethods fail to detect adaptive loci. 

Abstract Reforestation is a prominent climate change mitigation strategy, but available global maps of reforestation potential are widely criticized and highly variable, which limits their ability to provide robust estimates of both the locations and total area of opportunity. Here we develop global maps that address common critiques, build on a review of 89 reforestation maps created at multiple scales, and present eight reforestation scenarios with varying objectives, including providing ecosystem services, minimizing social conflicts, and delivering government policies. Across scenarios, we find up to 195 Mha (million hectares) are available (2225 TgCO₂e (teragrams of carbon dioxide equivalent) per year total net mitigation potential), which is 71–92% smaller than previous estimates because of conservative modeling choices, incorporation of safeguards, and use of recent, high-resolution datasets. This area drops as low as 6 Mha (53 TgCO₂e per year total net mitigation potential) if only statutorily protected areas are targeted. Few locations simultaneously achieve multiple objectives, suggesting that a mix of lands and restoration motivations will be needed to capitalize on the many potential benefits of reforestation.