<i>Are Brazil deforesters avoiding detection?</i> Reply to Richards <i>et al</i>. 2016

Bustamante, Mercedes M. C.; Valeriano, D. M.; Almeida, Cláudio; Cantinho, Roberta Zecchini; Maurano, L. E. P.; Nobre, Carlos A.; Oliveira, Pedro V. C.; Ometto, Jean Pierre; Roitman, Isaac; Rojas, Márcio; Santos, Mauro Meirelles De Oliveira; Shimbo, Julia

doi:10.1111/conl.12357

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…Three publications reported the underestimation of forest area loss in the PRODES data and likely casual factors 15,17,36 . The larger estimate of evergreen forest loss from the MOD100 dataset accentuates the likelihood of underestimates in other existing data products, specifically PRODES.…”

Section: Discussionmentioning

confidence: 99%

“…The PRODES forest product had high omission errors of about 40% and 28% in 2000 and 2010, respectively ( Supplementary Table 3), which can be attributed, to a large degree, to the spatial extent of satellite images to identify forest and the fact that Landsat images have a number of pixels with no good-quality observations in 1 year ( Supplementary Fig 11). PRODES forest data has a minimum mapping unit of 6.25 ha, thus it would not account for forest loss in small patches 15,36 . Compared with GFW and MOD100, PRODES underestimated forest-loss area by 67-127%.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2019

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

et al. 2019

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“…PRODES monitoring is since 2008 used to enforce the Plan for Preventing and Controlling Deforestation in the Amazon, and a notable difference between PRODES and GFC is that PRODES exclusively considers loss of primary forest. Unlike GFC, PRODES also uses a minimum mapping unit of 6.25 ha (although patches of >1 ha are later included if they subsequently combine to exceed 6.25 ha) [ 47 – 50 ]. Unpublished accuracy assessments of PRODES (based on reference data from a few scenes of higher resolution RapidEye and SPOT data) indicate an overall accuracy exceeding 90% [ 51 , 52 ].…”

Section: Methods and Datamentioning

confidence: 99%

Combining global land cover datasets to quantify agricultural expansion into forests in Latin America: Limitations and challenges

Pendrill

Persson

2017

PLoS ONE

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While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001–2011, by combining two “state-of-the-art” global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010’s Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010’s Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for deriving accurate quantifications of land cover following forest loss.

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“…Recent commentaries (M. M. C. Bustamante et al, 2017;Rajão, Moutinho, & Soares, 2017) found our methods "useful," but questioned our focus on PRODES and not Brazil's other government satellite forest monitoring systems. We focused on PRODES because of its unrivaled, but unwarranted salience.…”

Section: Introductionmentioning

confidence: 96%

“…With one exception 1 , those products which are used for enforcement monitor no greater a subset of Amazon forest than PRODES. This exception was not publicly known before Bustamante et al (2017) and thus might not have triggered (much) evasion. finer resolution monitoring has existed since 2005, but it was ambiguous in their comment when this information began being supplied to enforcement officials.…”

Section: Introductionmentioning

confidence: 99%

Enforcement Evasion Highlights Need for Better Satellite‐Based Forest Governance

Richards

Cohn

Arima

et al. 2017

CONSERVATION LETTERS

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Our recent article, "Are Brazil's Deforesters Avoiding Detection?" demonstrated that focusing illegal deforestation enforcement on the subset of forest monitored by the flagship PRODES system has caused PRODES to capture a declining share of deforestation in the Brazilian Amazon. Deforesters may be purposively seeking out forests not monitored for enforcement. Addressing the problem would help Brazil maintain a cutting-edge forest governance model worthy of transfer to other nations. Two commentaries questioned our decision to investigate solely PRODES and not additional government monitoring systems. We focused on PRODES because it is the most salient deforestation monitoring system. Other key deforestation monitoring systems are all either limited to the same monitoring footprint as PRODES, not used for enforcement, or are rarely used for measuring forest loss in the Brazilian Amazon. We do agree with the commentaries that Brazil's new satellite monitoring protocol for greenhouse gas emissions estimation is critical progress of the type we were advocating in our original article.

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Are Brazil deforesters avoiding detection? Reply to Richards et al. 2016

Cited by 5 publications

References 4 publications

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

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

Combining global land cover datasets to quantify agricultural expansion into forests in Latin America: Limitations and challenges

Enforcement Evasion Highlights Need for Better Satellite‐Based Forest Governance

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