Site-based climate-smart tree species selection for forestation under climate change

Abstract

Global climate change threatens ecosystem functions and resilience, prompting large-scale planting initiatives to mitigate its impacts. To ensure new plantations are adaptive to future climates, it is crucial to consider climate mismatches resulting from climate change when selecting tree species. However, current research is all species-based, which is not effective for species selection across species at specific plantation sites. Our research developed a novel site-based approach that can identify optimal tree species for specific planting sites under projected future climates. We evaluated the feasibility and effectiveness of this method across 10 representative sites in diverse climatic zones in China based on climate niche projections for 100 key tree species. Our findings demonstrated the necessity and effectiveness of this approach, which can select a suit of suitable tree species tailored for any potential planting site across China under different climate change scenarios. For instance, at Tibet Dongjiu Forest farm, Aibes densa and Quercus pannosa currently showed high suitability scores above 0.8 (on a scale of 0–1). However, by the 2080s, Aibes densa's suitability was projected to drop to 0.25, while Quercus pannosa was expected to maintain its suitability. Conversely, Quercus aquifolioides currently had a low suitability of 0.08, but it was projected to increase to 0.74 by the 2080s. These findings demonstrate the importance of using this approach to avoid selecting the wrong species or overlooking potentially suitable species. In addition, our simulation analysis suggests that a dataset of 40–50 species is necessary to ensure that most planting sites can identify 2–3 suitable species. This advancement significantly enhances the precision and effectiveness of tree species selection strategies for local practitioners, offering vital insights for forestry, conservation, and ecological restoration projects. These results highlight the tremendous potential and practical applicability of our site-based approach in enhancing forestry adaptation and ecological functions in response to global climate change.