Quantifying landscape fragmentation and forest carbon dynamics over 35 years in the Brazilian Atlantic Forest
Environmental Research Letters, ISSN: 1748-9326, Vol: 19, Issue: 3
2024
- 5Citations
- 46Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The Brazilian Atlantic Forest (AF) covers 13% of Brazil but retains only 26% of its original forest area. Utilizing a Morphological Spatial Pattern Analysis (MSPA), we generated 30 m spatial resolution fragmentation maps for old-growth and secondary forests across the AF. We quantified landscape fragmentation patterns and carbon (C) dynamics over 35 years using MapBiomas data between the years 1985 and 2020. We found that from 1985 to 2020 the forest suffered continuous fragmentation, losing core (nuclei forest fragments) and bridge (areas that connect different core areas) components of the landscape. About 87.5% (290 468.4 km) of the remaining forest lacked core areas, with bridges (38.0%) and islets (small, isolated fragments) (35.4%) being predominant. Secondary forests (1986-2020) accounted for 99 450.5 km and played a significant role in fragmentation pattern, constituting 44.9% of the areas affected by edge effects (perforation, edge, bridge, and loop), 53.7% of islets, and comprising only 1.4% of core forest. Additionally, regeneration by secondary forests contributed to all fragmentation classes in 2020. Even with the regrowth of forests, the total forested area in the biome did not increase between 1985 and 2020. Deforestation emissions reached 818 Tg CO, closely paralleled by edge effects emissions at 810 Tg CO, highlighting a remarkable parity in C emissions between the two processes. Despite slow changes, AF biome continues to lose its C stocks. We estimated that around 1.96 million hectares (19 600 km) of regenerated forest would be required to offset the historical C emissions over the analysed period. Hence, MSPA can support landscape monitoring, optimizing natural or active forest regeneration to reduce fragmentation and enhance C stocks. Our study’s findings are critical for guiding land-use policies focusing on minimizing emissions, promoting forest regrowth, and monitoring its permanence. This study offers biome scale, spatially explicit information, critical for AF conservation and management.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85187550828&origin=inward; http://dx.doi.org/10.1088/1748-9326/ad281c; https://iopscience.iop.org/article/10.1088/1748-9326/ad281c; https://dx.doi.org/10.1088/1748-9326/ad281c; https://validate.perfdrive.com/9730847aceed30627ebd520e46ee70b2/?ssa=9da1aceb-a720-4e73-8e33-d620637c1e80&ssb=71912291072&ssc=https%3A%2F%2Fiopscience.iop.org%2Farticle%2F10.1088%2F1748-9326%2Fad281c&ssi=8965c03a-cnvj-4fbd-92c3-bd5ba81f476f&ssk=botmanager_support@radware.com&ssm=62195268643226505239290712647251885&ssn=5ca1dcc6111b5c6c95dea3649aeade24f7b06ca9cb41-f3d7-4e1b-9d18c5&sso=c5d20715-ffdfc99f494fefd25dbabdd52afdedb24ce46ef9823acfb5&ssp=43295180661735165453173520624471766&ssq=57345287844642936732007047776377148485621&ssr=NTIuMy4yMTcuMjU0&sst=com.plumanalytics&ssu=&ssv=&ssw=&ssx=eyJyZCI6ImlvcC5vcmciLCJfX3V6bWYiOiI3ZjYwMDA3MTE4OTkzYS0wYzlhLTRlYmYtYTIxZS1lMGE3MGYxZTJkNGMxNzM1MTA3MDQ3ODQ1MTcxMzk5MDk3LWExNmQzZjNmZTQwOGYyNDIyMzkyNiIsInV6bXgiOiI3ZjkwMDA3Mjg5N2Y1OC05ODg2LTQyOGEtOWNjNy1mYjBlMTdlNjk2MGIzLTE3MzUxMDcwNDc4NDUxNzEzOTkwOTctY2Y3M2QzNmZjY2I3MWQxOTIzOTI2In0=
IOP Publishing
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know