Positive site selection bias in meta-analyses comparing natural regeneration to active forest restoration

Science Advances
J Leighton ReidRakan A Zahawi

Abstract

Several recent meta-analyses have aimed to determine whether natural regeneration is more effective at recovering tropical forests than active restoration (for example, tree planting). We reviewed this literature and found that comparisons between strategies are biased by positive site selection. Studies of natural forest regeneration are generally conducted at sites where a secondary forest was already present, whereas tree planting studies are done in a broad range of site conditions, including non-forested sites that may not have regenerated in the absence of planting. Thus, a level of success in forest regeneration is guaranteed for many studies representing natural regeneration, but not for those representing active restoration. The complexity of optimizing forest restoration is best addressed by paired experimentation at the same site, replicated across landscapes. Studies that have taken this approach reach different conclusions than those arising from meta-analyses; the results of paired experimental comparisons emphasize that natural regeneration is a highly variable process and that active restoration and natural regeneration are complementary strategies.

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Citations

Oct 29, 2018·Ecology Letters·T Trevor CaughlinCristina Martínez-Garza
Nov 10, 2018·Global Change Biology·Kristen E DybalaNathaniel E Seavy
Dec 28, 2018·PloS One·Carolina Y ShimamotoMárcia C M Marques
Jul 18, 2019·Proceedings. Biological Sciences·Holly P JonesDavid Moreno Mateos
Sep 25, 2020·Nature·Susan C Cook-PattonBronson W Griscom
Dec 22, 2020·Conservation Biology : the Journal of the Society for Conservation Biology·João P RomanelliRicardo R Rodrigues
Apr 21, 2021·Proceedings of the National Academy of Sciences of the United States of America·Lars A BrudvigJohn D Stuhler
Sep 14, 2021·Ecological Applications : a Publication of the Ecological Society of America·Luke P ShooKerrie Wilson

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