Old trees have many ecological and socio-cultural values. However, knowledge of the factors influencing their long-term persistence in human-dominated landscapes is limited. Here, using an extensive database (nearly 1.8 million individual old trees belonging to 1,580 species) from China, we identified which species were most likely to persist as old trees in human-dominated landscapes and where they were most likely to occur. We found that species with greater potential height, smaller leaf size and diverse human utilization attributes had the highest probability of long-term persistence. The persistence probabilities of human-associated species (taxa with diverse human utilization attributes) were relatively high in intensively cultivated areas. Conversely, the persistence probabilities of spontaneous species (taxa with no human utilization attributes and which are not cultivated) were relatively high in mountainous areas or regions inhabited by ethnic minorities. The distinctly different geographic patterns of persistence probabilities of the two groups of species were related to their dissimilar responses to heterogeneous human activities and site conditions. A small number of human-associated species dominated the current cohort of old trees, while most spontaneous species were rare and endemic. Our study revealed the potential impacts of human activities on the long-term persistence of trees and the associated shifts in species composition in human-dominated landscapes.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
The distribution data of old-tree species are available in Atlas of Woody Plants in China: Distribution and Climate38 and the National Specimen Information Infrastructure (www.nsii.org.cn/). The main source of old-tree species biological traits data is accessible through the ‘Flora of China’ (https://www.plantplus.cn/foc). The species list and tree abundance data of old trees in China are available in Figshare (https://doi.org/10.6084/m9.figshare.22545844).
Lindenmayer, D. B. Conserving large old trees as small natural features. Biol. Conserv. 211, 51–59 (2017).
Lindenmayer, D. B. & Laurance, W. F. The ecology, distribution, conservation and management of large old trees. Biol. Rev. 92, 1434–1458 (2017).
Blicharska, M. & Mikusiński, G. Incorporating social and cultural significance of large old trees in conservation policy. Conserv. Biol. 28, 1558–1567 (2014).
Cannon, C. H., Piovesan, G. & Munné-Bosch, S. Old and ancient trees are life history lottery winners and vital evolutionary resources for long-term adaptive capacity. Nat. Plants 8, 136–145 (2022).
Liu, J. et al. Age and spatial distribution of the world’s oldest trees. Conserv. Biol. 36, e1390 (2022).
Lindenmayer, D. B., Laurance, W. F. & Franklin, J. F. Global decline in large old trees. Science 338, 1305–1306 (2012).
Patrut, A. et al. The demise of the largest and oldest African baobabs. Nat. Plants 4, 423–426 (2018).
Liu, J., Yang, B. & Lindenmayer, D. B. The oldest trees in China and where to find them. Front. Ecol. Environ. 17, 319–322 (2019).
Huang, L. et al. Biogeographic and anthropogenic factors shaping the distribution and species assemblage of heritage trees in China. Urban For. Urban Green. 50, 126652 (2020).
Jin, C. et al. Co-existence between humans and nature: heritage trees in China’s Yangtze River region. Urban For. Urban Green. 54, 126748 (2020).
Locosselli, G. M. et al. Global tree-ring analysis reveals rapid decrease in tropical tree longevity with temperature. Proc. Natl Acad. Sci. USA 117, 33358–33364 (2020).
Liu, J. et al. Diversity and density patterns of large old trees in China. Sci. Total Environ. 655, 255–262 (2019).
Lindenmayer, D. B. & Laurance, W. F. The unique challenges of conserving large old trees. Trends Ecol. Evol. 31, 416–418 (2016).
Huang, L. et al. Local cultural beliefs and practices promote conservation of large old trees in an ethnic minority region in southwestern China. Urban For. Urban Green. 49, 126584 (2020).
Zhou, L. et al. Fengshui forests as a conservation paradigm of the golden larch in China. For. Ecol. Manage. 520, 120358 (2022).
Tang, C. Q. et al. Evidence for the persistence of wild Ginkgo biloba (Ginkgoaceae) populations in the Dalou Mountains, southwestern China. Am. J. Bot. 99, 1408–1414 (2012).
Frascaroli, F., Bhagwat, S., Guarino, R., Chiarucci, A. & Schmid, B. Shrines in Central Italy conserve plant diversity and large trees. Ambio 45, 468–479 (2016).
Choat, B. et al. Triggers of tree mortality under drought. Nature 558, 531–539 (2018).
Bennett, A. C., McDowell, N. G., Allen, C. D. & Anderson-Teixeira, K. J. Larger trees suffer most during drought in forests worldwide. Nat. Plants 1, 1–5 (2015).
Laanisto, L., Sammul, M., Kull, T., Macek, P. & Hutchings, M. J. Trait‐based analysis of decline in plant species ranges during the 20th century: a regional comparison between the UK and Estonia. Glob. Change Biol. 21, 2726–2738 (2015).
Osborne, C. P. et al. Human impacts in African savannas are mediated by plant functional traits. New Phytol. 220, 10–24 (2018).
Xu, W.-B. et al. Human activities have opposing effects on distributions of narrow-ranged and widespread plant species in China. Proc. Natl Acad. Sci. USA 116, 26674–26681 (2019).
Cámara-Leret, R. et al. Fundamental species traits explain provisioning services of tropical American palms. Nat. Plants 3, 1–7 (2017).
Purugganan, M. D. & Fuller, D. Q. The nature of selection during plant domestication. Nature 457, 843–848 (2009).
Lu, M. & He, F. Estimating regional species richness: the case of China’s vascular plant species. Glob. Ecol. Biogeogr. 26, 835–845 (2017).
Zhang, H., Lai, P. Y. & Jim, C. Y. Species diversity and spatial pattern of old and precious trees in Macau. Landsc. Urban Plan. 162, 56–67 (2017).
Qian, S. et al. Biotic homogenization of China’s urban greening: a meta-analysis on woody species. Urban For. Urban Green. 18, 25–33 (2016).
Tang, C. Q. et al. Identifying long-term stable refugia for relict plant species in East Asia. Nat. Commun. 9, 1–14 (2018).
Tang, C. Q. et al. Survival of a tertiary relict species, Liriodendron chinense (Magnoliaceae), in southern China, with special reference to village fengshui forests. Am. J. Bot. 100, 2112–2119 (2013).
Coggins, C. & Minor, J. Fengshui forests as a socio-natural reservoir in the face of climate change and environmental transformation. Asia Pac. Perspect. 15, 4–29 (2018).
Yuan, J. & Liu, J. Fengshui forest management by the Buyi ethnic minority in China. For. Ecol. Manage. 257, 2002–2009 (2009).
Tang, C. Q. et al. Population structure of relict Metasequoia glyptostroboides and its habitat fragmentation and degradation in south-central China. Biol. Conserv. 144, 279–289 (2011).
Lôbo, D., Leao, T., Melo, F. P., Santos, A. M. & Tabarelli, M. Forest fragmentation drives Atlantic forest of northeastern Brazil to biotic homogenization. Divers. Distrib. 17, 287–296 (2011).
Zhao, Y.-P. et al. Resequencing 545 ginkgo genomes across the world reveals the evolutionary history of the living fossil. Nat. Commun. 10, 1–10 (2019).
Cubino, J. P. et al. Taxonomic, phylogenetic, and functional composition and homogenization of residential yard vegetation with contrasting management. Landsc. Urban Plan. 202, 103877 (2020).
Piovesan, G., Cannon, C. H., Liu, J. & Munné-Bosch, S. Ancient trees: irreplaceable conservation resource for ecosystem restoration. Trends Ecol. Evol. 37, 1025–1028 (2022).
Lu, L.-M. et al. Evolutionary history of the angiosperm flora of China. Nature 554, 234–238 (2018).
Fang, J., Wang, Z. & Tang, Z. Atlas of Woody Plants in China: Distribution and Climate Vol. 1 (Springer, 2011).
Wang, Z., Fang, J., Tang, Z. & Lin, X. Patterns, determinants and models of woody plant diversity in China. Proc. R. Soc. B 278, 2122–2132 (2011).
Li, Y. et al. Leaf size of woody dicots predicts ecosystem primary productivity. Ecol. Lett. 23, 1003–1013 (2020).
Peng, S. et al. Preserving the woody plant tree of life in China under future climate and land-cover changes. Proc. R. Soc. B 289, 20221497 (2022).
Moles, A. T. et al. Global patterns in plant height. J. Ecol. 97, 923–932 (2009).
Wang, Y. et al. Drivers of large‐scale geographical variation in sexual systems of woody plants. Glob. Ecol. Biogeogr. 29, 546–557 (2020).
Molina-Venegas, R., Rodríguez, M. Á., Pardo-de-Santayana, M., Ronquillo, C. & Mabberley, D. J. Maximum levels of global phylogenetic diversity efficiently capture plant services for humankind. Nat. Ecol. Evol. 5, 583–588 (2021).
ArcGIS v.10.1 (ESRI, 2010).
Kissling, W. D. & Carl, G. Spatial autocorrelation and the selection of simultaneous autoregressive models. Glob. Ecol. Biogeogr. 17, 59–71 (2008).
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference. A Practical Information-Theoretic Approach (Springer, 2002).
Bivand, R. et al. spatialreg: Spatial Regression Analysis. The R Project for Statistical Computing (2019) https://r-spatial.github.io/spatialreg/
Jin, Y. & Qian, H. V. PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).
Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).
Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
Wood, S. Package ‘mgcv’. The R Project for Statistical Computing (2015) https://cran.r-project.org/src/contrib/Archive/mgcv/mgcv_1.8–38.tar.gz
We thank M. Zheng, J. Wang, R. Liao and L. Tian for help in data collection; our colleagues and local forestry departments that generously provided the original data of old trees; J. Liu for disccussing many sections of the paper; and G. Wheeler for assistance with the English language and grammatical editing of the paper. This study was supported by the Chongqing Technology Innovation and Application Demonstration Major Theme Special Project (cstc2018jszxzdyfxmX0007) to Y.Y., the National Natural Science Foundation of China (32071652, 32025025 and 31988102) to Y.Y and Z.T. and the China Postdoctoral Science Foundation (2022M720254) to L.H.
The authors declare no competing interests.
Peer review information
Nature Plants thanks Charles Cannon, Grzegorz Mikusiński and Fangliang He for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Comparison of species richness and individual counts among the three groups of old trees.
a, Comparison of species richness for the three groups of old trees at the national scale. b, Comparison of individual counts for the three groups of old trees at the national scale. HS, human-associated species; SS, semi-spontaneous species; S, spontaneous species.
Extended Data Fig. 2 Ordering of old tree species by tree abundance and species observed range size.
a, Ordering of old tree species by tree abundance. b, Ordering of old tree species by species observed range size (number of study grids in which a species occurred).
Extended Data Fig. 3 Comparison of potential and observed range size for the three groups of old trees.
The observed range size refers to the number of grid cells in which a species has been observed to occur. Boxplots in show the median (centre line), 25th and 75th quartiles (hinges), 1.5 times the interquartile range from the hinges (whiskers) and values outside 1.5 times the interquartile range (points).
Comparison of the mean RFR between the families with more than ten species. Data are presented as mean values +/− SE.
Extended Data Fig. 5 Difference of spatial recruitment rate (SRR) between human-associated species and spontaneous species.
a, Histogram of SRR of human-associated species and spontaneous species. b, Comparison of the SRR of human-associated species (n = 206) and spontaneous species (n = 931) at the grid scale. In (B), boxplots in show the median (centre line), 25th and 75th quartiles (hinges), 1.5 times the interquartile range from the hinges (whiskers) and values outside 1.5 times the interquartile range (points). Significance test was performed using the Wilcoxon rank-sum test.
a, China’s administrative provinces. b, Topography with annotations of key landform features of China.
Counties (round dots) with species-abundance data of old trees in our database. The red line indicates the Hu Huanyong Line, which separates China into the northwestern and southeastern halves based on human population density. Background data show the distribution of vegetation types in China.
a, Methods for calculating the range filling rate. b, Methods for calculating the spatial recruitment rate.
Ordering of old tree species by human utilization index. Red vertical dashed line represents the 75th quartile.
Spearman’s rank correlation coefficients among the explanatory variables.
About this article
Cite this article
Huang, L., Jin, C., Pan, Y. et al. Human activities and species biological traits drive the long-term persistence of old trees in human-dominated landscapes. Nat. Plants 9, 898–907 (2023). https://doi.org/10.1038/s41477-023-01412-1