Improved estimates of forest cover and loss in the Brazilian Amazon in 2000–2017

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Yao; Wu, Xiaocui; Shimabukuro, Yosio E.; Arai, Egídio; Biradar, Chandrashekhar; Wang, Jie; Liu, Fang; Shi, Zheng; Moore, Berrien

doi:10.1038/s41893-019-0336-9

Cited by 87 publications

(73 citation statements)

References 55 publications

(94 reference statements)

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“…Land Cover, Precipitation, and PAR Datasets. To determine forest and nonforest land cover, we used annual forest cover maps for 2008-2017 for the Amazon Basin with a spatial resolution of 500 m (36,37). Only TROPOMI soundings that were in land cover map pixels that were consistently forest or nonforest were used in the data analysis.…”

Section: Methodsmentioning

confidence: 99%

TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest

Doughty

Köhler

Frankenberg

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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100

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Photosynthesis of the Amazon rainforest plays an important role in the regional and global carbon cycles, but, despite considerable in situ and space-based observations, it has been intensely debated whether there is a dry-season increase in greenness and photosynthesis of the moist tropical Amazonian forests. Solar-induced chlorophyll fluorescence (SIF), which is emitted by chlorophyll, has a strong positive linear relationship with photosynthesis at the canopy scale. Recent advancements have allowed us to observe SIF globally with Earth observation satellites. Here we show that forest SIF did not decrease in the early dry season and increased substantially in the late dry season and early part of wet season, using SIF data from the Tropospheric Monitoring Instrument (TROPOMI), which has unprecedented spatial resolution and near-daily global coverage. Using in situ CO2 eddy flux data, we also show that cloud cover rarely affects photosynthesis at TROPOMI’s midday overpass, a time when the forest canopy is most often light-saturated. The observed dry-season increases of forest SIF are not strongly affected by sun-sensor geometry, which was attributed as creating a pseudo dry-season green-up in the surface reflectance data. Our results provide strong evidence that greenness, SIF, and photosynthesis of the tropical Amazonian forest increase during the dry season.

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Section: Methodsmentioning

confidence: 99%

TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest

Doughty

Köhler

Frankenberg

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

100

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“…In the Amazon, deforestation is often accompanied by fire [15,16]. Because a more intense dry season makes the Amazon forest more flammable [4,[17][18][19][20][21], it seems reasonable to hypothesize that increasing dry-season intensity facilitates clear-cut deforestation in several ways: (1) traditional slashand-burn agriculture depends on a sufficiently dry season [15,17]; (2) pastures are often repeatedly cleared of encroaching woody vegetation and weeds with the use of fire [15,22]; and (3) deforestation using mechanical methods is often followed by the combustion of the remaining vegetation, which is easier when the material is drier [15,17,23,24].…”

mentioning

confidence: 99%

Feedback between drought and deforestation in the Amazon

Staal

Flores

Aguiar

et al. 2020

Environ. Res. Lett.

138

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Deforestation and drought are among the greatest environmental pressures on the Amazon rainforest, possibly destabilizing the forest-climate system. Deforestation in the Amazon reduces rainfall regionally, while this deforestation itself has been reported to be facilitated by droughts. Here we quantify the interactions between drought and deforestation spatially across the Amazon during the early 21st century. First, we relate observed fluctuations in deforestation rates to dry-season intensity; second, we determine the effect of conversion of forest to cropland on evapotranspiration; and third, we simulate the subsequent downwind reductions in rainfall due to decreased atmospheric water input. We find large variability in the response of deforestation to dry-season intensity, with a significant but small average increase in deforestation rates with a more intense dry season: with every mm of water deficit, deforestation tends to increase by 0.13% per year. Deforestation, in turn, has caused an estimated 4% of the recent observed drying, with the south-western part of the Amazon being most strongly affected. Combining both effects, we quantify a reinforcing drought-deforestation feedback that is currently small, but becomes gradually stronger with cumulative deforestation. Our results suggest that global climate change, not deforestation, is the main driver of recent drying in the Amazon. However, a feedback between drought and deforestation implies that increases in either of them will impede efforts to curb both.

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“…Large inter-and intra-annual variability in rates of loss suggests that actors responsible for land cover change are doing so in response to external factors. Accurate dating of individual events aids in diagnosing these factors and potential future mitigation (Qin et al, 2019). For law enforcement and others involved in efforts to prevent further loss, the ability to continuously monitor ongoing change will serve as a strong deterrent, and aid in the deployment of existing resources.…”

Section: Discussionmentioning

confidence: 99%

Locating and dating land cover change events in the Renosterveld, a Critically Endangered shrubland ecosystem

Moncrieff

2020

Preprint

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Land cover change is the leading cause of global biodiversity decline. New satellite platforms allow monitoring of habitats in increasingly fine detail, but most applications have been limited to forested ecosystems. I demonstrate the potential for detailed mapping and accurate dating of land cover change events in a highly biodiverse, Critically Endangered, shrubland ecosystem - the Renosterveld of South Africa. Using supervised classification of Sentinel 2 data, and subsequent manual verification with very high resolution imagery, I locate all conversion of Renosterveld to non-natural land cover between 2016 and 2020. Land cover change events are further assigned dates using high temporal frequency data from Planet labs. 478.6 hectares of Renosterveld loss was observed over this period, accounting for 0.72 % of the remaining natural vegetation in the region. 50% of change events were dated to within two weeks of their actual occurrence, and 87% to within two months. Change often preceded the planting and harvesting seasons of rainfed annual grains. These results show the potential for new satellite platforms to accurately map land cover change in non-forest ecosystems, and detect change within days of its occurrence. There is potential to use this and similar datasets to automate the process of change detection and monitor change continuously.

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Improved estimates of forest cover and loss in the Brazilian Amazon in 2000–2017

Cited by 87 publications

References 55 publications

TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest

TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest

Feedback between drought and deforestation in the Amazon

Locating and dating land cover change events in the Renosterveld, a Critically Endangered shrubland ecosystem

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