Natural forests loss and tree plantations: large-scale tree cover loss differentiation in a threatened biodiversity hotspot

Abstract

Distinguishing between natural forests from exotic tree plantations is essential to get an accurate picture of the world’s state of forests. Most exotic tree plantations support lower levels of biodiversity and have less potential for ecosystem services supply than natural forests, and differencing them is still a challenge using standard tools. We use a novel approach in south-central of Chile to differentiate tree cover dynamics among natural forests and exotic tree plantations. Chile has one of the world’s most competitive forestry industry and the region is a global biodiversity hotspot. Our collaborative visual interpretation method combined a global database of tree cover change, remote sensing from high-resolution satellite images and expert knowledge. By distinguishing exotic tree plantation and natural forest loss, we fit spatially explicit models to estimate tree-cover loss across 40 millions of ha between 2000 and 2016. We were able to distinguish natural forests from exotic tree plantations with an overall accuracy of 99% and predicted forest loss. Total tree cover loss was continuous over time, and the disaggregation revealed that 1 549 909 ha of tree plantations were lost (mean = 96 869 ha year−1), while 206 142 ha corresponded to natural forest loss (mean = 12 884 ha year−1). Mostly of tree plantations lost returned to be plantation (51%). Natural forests were converted mainly (75%) to transitional land covers (e.g. shrubland, bare land, grassland), and an important proportion of these may finish as tree plantation. This replacement may undermine objectives of increasedcarbon storage and biodiversity. Tree planting as a solution has gained increased attention in recen years with ambitious commitments to mitigate the effects of climate change. However, negative outcomes for the environment could result if strategies incentivize the replacement of natural forests into other land covers. Initiatives to reduce carbon emissions should encourage differentiating natural forests from exotic tree plantations and pay more attention on protecting and managing sustainably the former.

Global Forest Plantations Mapping and Biomass Carbon Estimation

“…In Malaysia, On the point scale, GSDFP Version 1.0 is highly consistent (OA = 91.69%, kappa coefficient = 0.82) with the split validation samples (20%) visually interpreted in Google Earth (Figure S11, Tables S8 and S9 in Supporting Information S1). In addition, GSDFP Version 1.0 outperformed SDPT VERSION 1.0 and the FP map generated by Schulze et al (2019) with respect to the reference samples from the previous literature (Adison et al, 2020;Koskinen et al, 2018;Wu et al, 2022). For Chile, the producer's accuracy (PA) value of GSDFP Version 1.0 reaches 0.42, whereas the values for SDPT VERSION 1.0 and Schulze et al (2019) are less than 0.19 (Figure 5c).…”

“…Except for the FP distribution generated by Schulze et al. (2019), other spatial maps or samples depicted the FP distribution in 2015 (Adison et al., 2020; Chen et al., 2017; FAO, 2015; Koskinen et al., 2018) or a period closely aligned with it (Petersen et al., 2016; Wu et al., 2022). Consequently, it is viable to validate the FP maps generated in this study by comparing them with these samples and spatial maps given the restricted availability of validation data sets for FP.…”

“…Also, we validated our FP map in typical regions (China, Chile, Malaysia, Tanzania, and the United States) with publicly accessed spatial maps and reference samples, as spatially shown in Figure S5 in Supporting Information S1. Among the selected validation areas, China and the United States have the first and second largest FPs areas (Chen et al, 2017;Wu et al, 2022), while Chile is one of the global leaders in pulp production from exotic tree plantations and is also classified as a global biodiversity hotspot (Adison et al, 2020), and Malaysia is a typical tropical country with a long history of plantation systems (Petersen et al, 2016) and Tanzania experienced rapid growth of smallholder-owned woodlots in recent decades (Koskinen et al, 2018). For China, Wu et al (2022) collected a total of 594 samples through surveying more than 600 peer-reviewed papers since 1948, while few samples was collected during the year of 2015.…”

“…The reference samples in Chile provided by Adison et al. (2020) are available at http://www.lepfor.ufro.cl/?page_id=530. The four validation samples data set in Tanzania was provided by Koskinen et al.…”

“…The reference samples in China provided by Wu et al (2022) are available at https://www.scidb.cn/en/detail?dataSetId=a857a0fb2a144168ab755fd38 89f51e6. The reference samples in Chile provided by Adison et al (2020) are available at http://www.lepfor. ufro.cl/?page_id=530.…”