Bonan, G. B. Forests and climate change: Forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449. https://doi.org/10.1126/science.1155121 (2008).
Google Scholar
Le Quere, C. et al. Global carbon budget 2016. Earth Syst. Sci. Data 8, 605–649. https://doi.org/10.5194/essd-8-605-2016 (2016).
Google Scholar
DavidMorales-Hidalgo, D., Oswalt, S. N. & Somanathan, E. Status and trends in global primary forest, protected areas, and areas designated for conservation of biodiversity from the Global Forest Resources Assessment 2015. Forest Ecol. Manag. 352, 68–77. https://doi.org/10.1016/j.foreco.2015.06.011 (2015).
Google Scholar
Kauppi, P. E., Sandstrom, V. & Lipponen, A. Forest resources of nations in relation to human well-being. PLoS One 13, e0196248. https://doi.org/10.1371/journal.pone.0196248 (2018).
Google Scholar
Anderegg, W. R. L. et al. Climate-driven risks to the climate mitigation potential of forests. Science 368, 1327. https://doi.org/10.1126/science.aaz7005 (2020).
Google Scholar
Wilson, M. C. et al. Habitat fragmentation and biodiversity conservation: Key findings and future challenges. Landsc. Ecol. 31, 219–227. https://doi.org/10.1007/s10980-015-0312-3 (2016).
Google Scholar
Haddad, N. M. et al. Habitat fragmentation and its lasting impact on earth’s ecosystems. Sci. Adv. 1, e1500052. https://doi.org/10.1126/sciadv.1500052 (2015).
Google Scholar
Holl, K. D. Restoring tropical forests from the bottom up. Science 355, 455–456. https://doi.org/10.1126/science.aam5432 (2017).
Google Scholar
Audino, L. D., Murphy, S. J., Zambaldi, L., Louzada, J. & Comita, L. S. Drivers of community assembly in tropical forest restoration sites: Role of local environment, landscape, and space. Ecol. Appl. 27, 1731–1745. https://doi.org/10.1002/eap.1562 (2017).
Google Scholar
Temperton, V. M., Hobbs, R. J., Nuttle, T. & Halle, S. in Assembly Rules and Restoration Ecology: Bridging the Gap Between Theory and Practice [Science and Practice of Ecological Restoration]. i–xv, 1–439 (2004).
Young, T. P., Chase, J. M. & Huddleston, R. T. Community succession and assembly: Comparing, contrasting and combining paradigms in the context of ecological restoration. Ecol. Restor. 19, 5–18 (2001).
Google Scholar
Vellend, M. The Theory of Ecological Communities (Princeton University Press, 2016).
HilleRisLambers, J., Adler, P. B., Harpole, W. S., Levine, J. M. & Mayfield, M. M. Rethinking community assembly through the lens of coexistence theory. Annu. Rev. Ecol. Evol. Syst. 43(43), 227–248. https://doi.org/10.1146/annurev-ecolsys-110411-160411 (2012).
Google Scholar
Connell, J. H. On the role of natural enemies in preventing competitive exclusion in some marine animals and in rain forest trees. In Dynamics of Populations (eds Den Boer, P. J. & Gradwell, G. R.) (Centre for Agricultural Publishing and Documentation, 1971).
Janzen, D. H. Herbivores and the number of tree species in tropical forests. Am. Nat. 104, 501. https://doi.org/10.1086/282687 (1970).
Google Scholar
Schmid, J. S., Taubert, F., Wiegand, T., Sun, I. F. & Huth, A. Network science applied to forest megaplots: Tropical tree species coexist in small-world networks. Sci. Rep. https://doi.org/10.1038/s41598-020-70052-8 (2020).
Google Scholar
Wang, H. X. et al. Prevalence of inter-tree competition and its role in shaping the community structure of a natural Mongolian scots pine (Pinus sylvestris var. mongolica) forest. Forests https://doi.org/10.3390/f8030084 (2017).
Google Scholar
Hubbell, S. P. et al. Light-gap disturbances, recruitment limitation, and tree diversity in a neotropical forest. Science 283, 554–557. https://doi.org/10.1126/science.283.5401.554 (1999).
Google Scholar
Janik, D. et al. Breaking through beech: A three-decade rise of sycamore in old-growth European forest. Forest Ecol. Manag. 366, 106–117. https://doi.org/10.1016/j.foreco.2016.02.003 (2016).
Google Scholar
Svatek, M., Rejzek, M., Kvasnica, J., Repka, R. & Matula, R. Frequent fires control tree spatial pattern, mortality and regeneration in argentine open woodlands. Forest Ecol. Manag. 408, 129–136. https://doi.org/10.1016/j.foreco.2017.10.048 (2018).
Google Scholar
Giammarchi, F. et al. Effects of the lack of forest management on spatiotemporal dynamics of a subalpine Pinus cembra forest. Scand. J. Forest Res. 32, 142–153. https://doi.org/10.1080/02827581.2016.1207802 (2017).
Google Scholar
Janik, D. et al. Patterns of Fraxinus angustifolia in an alluvial old-growth forest after declines in flooding events. Eur. J. Forest Res. 135, 215–228. https://doi.org/10.1007/s10342-015-0925-8 (2016).
Google Scholar
Bagchi, R. et al. Defaunation increases the spatial clustering of lowland western amazonian tree communities. J. Ecol. 106, 1470–1482. https://doi.org/10.1111/1365-2745.12929 (2018).
Google Scholar
Zhang, L. Y., Dong, L. B., Liu, Q. & Liu, Z. G. Spatial patterns and interspecific associations during natural regeneration in three types of secondary forest in the central part of the greater Khingan mountains, Heilongjiang province, China. Forests https://doi.org/10.3390/f11020152 (2020).
Google Scholar
Obiang, N. L. E. et al. Determinants of spatial patterns of canopy tree species in a tropical evergreen forest in Gabon. J. Veg. Sci. 30, 929–939. https://doi.org/10.1111/jvs.12778 (2019).
Google Scholar
Wiegand, T. et al. Spatially explicit metrics of species diversity, functional diversity, and phylogenetic diversity: Insights into plant community assembly processes. Annu. Rev. Ecol. Evol. Syst. 48(48), 329–351. https://doi.org/10.1146/annurev-ecolsys-110316-022936 (2017).
Google Scholar
Gabriel, E. Spatial point patterns: Methodology and applications with R. Math. Geosci. 49, 815–817. https://doi.org/10.1007/s11004-016-9670-x (2017).
Google Scholar
Baddeley, A., Rubak, R. & Turner, R. Spatial Point Patterns, Methodology and Applications with R (CRC Press, 2016).
Google Scholar
Wiegand, T. & Moloney, K. A. Rings, circles, and null-models for point pattern analysis in ecology. Oikos 104, 209–229. https://doi.org/10.1111/j.0030-1299.2004.12497.x (2004).
Google Scholar
Plotkin, J. B., Chave, J. M. & Ashton, P. S. Cluster analysis of spatial patterns in Malaysian tree species. Am. Nat. 160, 629–644. https://doi.org/10.1086/342823 (2002).
Google Scholar
Ripley, B. D. Modeling spatial patterns. J. R. Stat. Soc. B 39, 172–212 (1977).
He, F. L. & Gaston, K. J. Estimating species abundance from occurrence. Am. Nat. 156, 553–559. https://doi.org/10.1086/303403 (2000).
Google Scholar
Diggle, P. Statistical Analysis of Spatial Point Patterns (Academic Press, 1983).
Google Scholar
Pielou, E. C. The use of point-to-plant distances in the study of the pattern of plant-populations. J. Ecol. 47, 607–613. https://doi.org/10.2307/2257293 (1959).
Google Scholar
Losapio, G., Montesinos-Navarro, A. & Saiz, H. Perspectives for ecological networks in plant ecology. Plant Ecol. Divers. 12, 87–102. https://doi.org/10.1080/17550874.2019.1626509 (2019).
Google Scholar
Fuller, M. M., Wagner, A. & Enquist, B. J. Using network analysis to characterize forest structure. Nat. Resour. Model. 21, 225–247. https://doi.org/10.1111/j.1939-7445.2008.00004.x (2008).
Google Scholar
Montoya, J. M., Pimm, S. L. & Sole, R. V. Ecological networks and their fragility. Nature 442, 259–264. https://doi.org/10.1038/nature04927 (2006).
Google Scholar
Proulx, S. R., Promislow, D. E. L. & Phillips, P. C. Network thinking in ecology and evolution. Trends Ecol. Evol. 20, 345–353. https://doi.org/10.1016/j.tree.2005.04.004 (2005).
Google Scholar
Nakagawa, Y., Yokozaw, M. & Hara, T. Complex network analysis reveals novel essential properties of competition among individuals in an even-aged plant population. Ecol. Complex 26, 95–116. https://doi.org/10.1016/j.ecocom.2016.03.005 (2016).
Google Scholar
Wiegand, T. & Moloney, K. A. Handbook of Spatial Point Pattern Analysis in Ecology (CRC Press, 2013).
Google Scholar
Barthelemy, M. Spatial networks. Phys. Rep. Rev. Sect. Phys. Lett. 499, 1–101. https://doi.org/10.1016/j.physrep.2010.11.002 (2011).
Google Scholar
Keren, S. Modeling tree species count data in the understory and canopy layer of two mixed old-growth forests in the Dinaric region. Forests https://doi.org/10.3390/f11050531 (2020).
Google Scholar
Podlaski, R. Models of the fine-scale spatial distributions of trees in managed and unmanaged forest patches with Abies alba Mill. and Fagus sylvatica L. Forest Ecol. Manag. 439, 1–8 (2019).
Google Scholar
Levin, S. A. Theoretical ecology—Principles and applications, 3rd edition. Science 316, 1699–1700. https://doi.org/10.1126/science.1141870 (2007).
Google Scholar
Martinez-Lopez, V., Garcia, C., Zapata, V., Robledano, F. & De la Rua, P. Intercontinental long-distance seed dispersal across the Mediterranean basin explains population genetic structure of a bird-dispersed shrub. Mol. Ecol. 29, 1408–1420. https://doi.org/10.1111/mec.15413 (2020).
Google Scholar
Dale, M. R. T. & Fortin, M. J. From graphs to spatial graphs. Annu. Rev. Ecol. Evol. Syst. 41, 21–38. https://doi.org/10.1146/annurev-ecolsys-102209-144718 (2010).
Google Scholar
Silva, C. A. et al. Treetop: A shiny-based application and R package for extracting forest information from LiDAR data for ecologists and conservationists. Methods Ecol. Evol. 13, 1164–1176. https://doi.org/10.1111/2041-210x.13830 (2022).
Google Scholar
Tatsumi, S., Yamaguchi, K. & Furuya, N. Forestscanner: A mobile application for measuring and mapping trees with LiDAR-equipped iPhone and iPad. Methods Ecol. Evol. https://doi.org/10.1111/2041-210x.13900 (2022).
Google Scholar
Ferraz, A., Saatchi, S. S., Longo, M. & Clark, D. B. Tropical tree size-frequency distributions from airborne LiDAR. Ecol. Appl. 30, e02154. https://doi.org/10.1002/eap.2154 (2020).
Google Scholar
Bianchi, E., Bugmann, H., Hobi, M. L. & Bigler, C. Spatial patterns of living and dead small trees in subalpine Norway spruce forest reserves in Switzerland. Forest Ecol. Manag. 494, 119315. https://doi.org/10.1016/j.foreco.2021.119315 (2021).
Google Scholar
Tatsumi, S., Owari, T., Yin, M. F. & Ning, L. Z. Neighborhood analysis of underplanted Korean pine demography in larch plantations: Implications for uneven-aged management in northeast china. Forest Ecol. Manag. 322, 10–18. https://doi.org/10.1016/j.foreco.2014.03.022 (2014).
Google Scholar
Cornett, M. W., Reich, P. B. & Puettmann, K. J. Canopy feedbacks and microtopography regulate conifer seedling distribution in two Minnesota conifer-deciduous forests. Ecoscience 4, 353–364. https://doi.org/10.1080/11956860.1997.11682414 (1997).
Google Scholar
Wang, X. F., Zheng, G., Yun, Z. X. & Moskal, L. M. Characterizing tree spatial distribution patterns using discrete aerial LiDAR data. Remote Sens. Basel 12, 712. https://doi.org/10.3390/rs12040712 (2020).
Google Scholar
Matérn, B. Spatial variation: Stochastic models and their application to some problems in forest surveys and other sampling investigations. Meddelanden från Statens Skogsforskningsinstitut 49, 1–144 (1960).
Google Scholar
Matérn, B. Spatial Variation. Lecture Notes in Statistics Vol. 36 (Springer, 1986).
Google Scholar
Thomas, M. A generalisation of Poisson’s binomial limit for use in ecology. Biometrika 36, 18–25 (1949).
Google Scholar
Lotwick, H. W. Simulation of some spatial hard core models, and the complete packing problem. J. Stat. Comput. Simul. 15, 295–314 (1982).
Google Scholar
Strauss, D. J. A model for clustering. Biometrika 62, 467–475 (1975).
Google Scholar
Cressie Noel, A. C. Statistics for Spatial Data (Wiley-Interscience, 1993).
Google Scholar
Besag, J. E. Contribution to the discussion of the paper by Ripley. J. R. Stat. Soc. 39, 193–195 (1977).
Google Scholar
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