A global meta-analysis of the impacts of tree plantations on biodiversity
Wang, Chao (2022), A global meta-analysis of the impacts of tree plantations on biodiversity, Dryad, Dataset, https://doi.org/10.5061/dryad.zcrjdfnd4
Aim: Planted forests are becoming increasingly common worldwide for a variety of reasons including water conservation and carbon sequestration, whereas the effects of tree plantations on biodiversity are unclear as to whether planted ecosystems are ‘green deserts’ or valuable habitats for biodiversity.
Time period: 1980–2020.
Taxa studied: Flora, fauna, and microorganisms.
Methods: By conducting a meta-analysis of 361 observations from 138 sites worldwide, we explored the global patterns and associated drivers of biodiversity responding to tree plantations by comparing biodiversity levels in plantations and adjacent habitats (primary or secondary forests).
Results: Overall, the biodiversity (species richness) and abundance across multi-trophic levels in tree plantations was lower than that in primary forests, reached similar values to secondary succession, but varied with plantation and management regimes. Specifically, the biodiversity across multi-trophic levels in reforestation was higher than that in afforestation; the biodiversity in mixture, native species, and unmanaged plantations was higher than that in monoculture, exotic species, and managed plantations. The diversity of vertebrates, invertebrates, and plants in reforestation was lower than that in primary forests, while belowground biodiversity in reforestation showed no difference with primary forests. Invertebrate diversity in reforestation was lower than that in secondary succession, whereas plant diversity was higher than that in secondary succession. Moreover, the biodiversity in reforestation increased with reforestation age. Furthermore, structural equation models showed that aboveground faunal diversity in reforestation was driven by canopy coverage and plant diversity, reforestation affected belowground biodiversity mainly by changing soil organic carbon.
Main conclusions: Our findings suggesting that reforestation by planting mixed native species will be more beneficial to biodiversity, revealing that biodiversity in intensive managed plantations was significantly lower than restoration-oriented plantations, and highlighting that primary forests are not replaceable, but planted forests may be a reliable way to rapidly restore biodiversity.
To investigate the effects of tree plantations on biodiversity through evaluating differences in biodiversity between tree plantations and adjacent habitats, we searched for all peer-reviewed publications using ISI Web of Science (isiknowledge.com) and China National Knowledge Infrastructure (CNKI, www.cnki.net) between 1980 and 2020. The keywords and terms used were (“planting” OR “tree plant*” OR “plantation*” OR “afforestation” OR “reforestation”) AND (“diversity” OR “richness” OR “abundance”). The following criteria were applied to select studies: 1) experiments conducted in the field that reported the effects of tree plantations on biodiversity and 2) experiments that had at least one pair of data points comparing tree plantations vs. adjacent ecosystem types (e.g., primary and secondary forests) and that reported standard deviations/errors or numbers of replicates (Fig. S1). Means, standard deviations/errors, and sample sizes were extracted from tables or digitized graphs using GetData Graph Digitizer (ver. 2.24, www.getdata-graph-digitizer.com/). The Worldclim database at http://worldclim.org was used to extract mean annual precipitation (MAP) and temperature (MAT) using the location information (latitude and longitude). Since some publications investigated more than one site within a study, the number of study sites (138, Fig. S2) was higher than that of publications (110, Table S1). Overall, a total of 138 sites, reporting 26 Family belong to 11 Class/Phyla (Table S2), and 361 observations were selected in our meta-analysis (Fig. S3).
Beijing Academy of Agricultural and Forestry Sciences, Award: KJCX20200431
Natural Science Foundation of Beijing Municipality, Award: 5204030
National Natural Science Foundation of China, Award: 31901173
Beijing Academy of Agricultural and Forestry Sciences, Award: KJCX20200301