Effects of settlement designs on deforestation and fragmentation in the Brazilian Amazon

Alves, Maria Tereza Ribeiro; Piontekowski, Valderli Jorge; Buscardo, Erika; Pedlowski, Marcos Antônio; Sano, Edson Eyji; Matricardi, Eraldo Aparecido Trondoli

doi:10.1016/j.landusepol.2021.105710

Cited by 14 publications

(5 citation statements)

References 24 publications

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“…The potentially illegal deforestation was likely motivated by the expansion of extensive pasture areas and planted forests, especially of eucalyptus that is a fast growing and yielding species (Rezende et al, 2013). Deforestation triggered by pasture expansion has been demonstrated in various studies in Brazil (Alves et al, 2021; Barbosa, Duarte, et al, 2023; Barbosa, Nabout, & da, 2023; Levy et al, 2023). The private rural properties with the highest deforestation rates were in the Lower and Mid‐Lower regions and occurred in areas with physiographical conditions favorable to the expansion of single crop systems and commercial forests.…”

Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

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Trends of potentially illegal deforestation over protected areas of Rio das Velhas basin, Brazil

et al. 2023

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Despite the promise to increase control and fight against deforestation, the new Brazilian Forest Code (BFC) allowed more flexible dimensioning and land use rules in areas of private rural properties intended for native vegetation protection, namely the Legal Reserve (LR) and Areas of Permanent Preservation (APP). Following a decade of BFC implementation, the promise was somewhat flawed, while oversight and monitoring of private rural properties were not as expected. Considering this worrying scenario, the objective of this study was to quantify and map the forest balance of private rural properties listed in the Environmental Rural Registry of Rio das Velhas hydrographic basin (Minas Gerais, 2002), to assess compliance with the BCF and detect potentially illegal deforestation. The total deforested area in 6216 (28.7%) registered private rural properties reached approximately 119,800 ha after 2008, 61,500 ha of which were suppressed without surplus forest of LR. Besides, nearly half of the private rural properties presented forest deficits in the APPs. In a vast majority of cases, the deforestation was potentially illegal, but only a small number of private rural property owners was made responsible for that. The deforested areas were concentrated in small sectors within the rural properties, which would facilitate the control of illegal native vegetation suppression if oversight and law enforcement had been effective. Our results are an alert and a subside to public institutions and rural property owners while developing and executing plans, programs, and projects focused on environmental regularization of rural properties, with the ultimate goal of preventing further land degradation in the basin.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Trends of potentially illegal deforestation over protected areas of Rio das Velhas basin, Brazil

et al. 2023

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“…It is an area of around 89,900 km² (Figure 1) that covers 14 municipalities and has a population density of 8.0 inhabitants/km². This region is mostly occupied by agricultural and cattle-ranching lands due to administrative and financial support from governmental colonization programs in the Brazilian Amazon that have taken place from the 1970s onwards (Alves et al 2021). These programs are characterized by the implementation of colonization settlements, which are preceded by high deforestation rates due to the expansion of agricultural lands and cattleranching (Alves et al 2021;Duarte et al 2021), thus making the region a part of the "Arc of Deforestation" in the Brazilian Amazon.…”

Section: Study Areamentioning

confidence: 99%

Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

Duarte,

Acácio da Silva,

Paixão de Sousa

et al. 2024

GES

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Forest fires are global phenomena that pose an accelerating threat to ecosystems, affect the population life quality and contribute to climate change. The mapping of fire susceptibility provides proper direction for mitigating measures for these events. However, predicting their occurrence and scope is complicated since many of their causes are related to human practices and climatological variations. To predict fire occurrences, this study applies a fuzzy inference system methodology implemented in R software and using triangular and trapezoidal functions that comprise four input parameters (temperature, rainfall, distance from highways, and land use and occupation) obtained from remote sensing data and processed through GIS environment. The fuzzy system classified 63.27% of the study area as having high and very high fire susceptibility. The high density of fire occurrences in these classes shows the high precision of the proposed model, which was confirmed by the area under the curve (AUC) value of 0.879. The application of the fuzzy system using two extreme climate events (rainy summer and dry summer) showed that the model is highly responsive to temperature and rainfall variations, which was verified by the sensitivity analysis. The results obtained with the system can assist in decision-making for appropriate firefighting actions in the region.

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“…The occupation process of the Amazon was heterogeneous and carried by different actors supported by distinct public policies at different time frames, generating a variety of deforestation patterns (Silva et al, 2008;Alves et al, 2021). Each leaves a specific footprint of deforestation, generating a variety of landscape configurations (i.e., different forest patch sizes, numbers, shapes, and locations) (Mertens and Lambin 1997;Saito et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Forest regeneration pathways in contrasting deforestation patterns of Amazonia

Alencar

Escada

Camargo

2023

Front. Environ. Sci.

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Secondary vegetation is increasingly recognized as a key element for biodiversity conservation and carbon stocks in human-modified landscapes. Contrasting deforestation patterns should lead to distinct patterns of forest regeneration, but this relationship is yet to be unveiled for long-term studies. Using Landsat data from 1985–2015, we analyzed the surface area, spatial distribution, and age of secondary vegetation in Fishbone and Geometric patterns of deforestation. Additionally, we investigated to which extent secondary vegetation reduces forest patch isolation at the landscape level across time. We found the Fishbone pattern to consistently have more secondary vegetation over time than the Geometric pattern, despite having the same size of the deforested area. However, the Fishbone pattern showed more secondary vegetation area with less than 5 years old, while the Geometric pattern showed more area with secondary vegetation with more than 30 years old. Regarding spatial distribution, we found secondary vegetation to be more spread across the entire landscape at the Fishbone pattern and to consistently reduce forest patch isolation across time. This is congruent with the land use typically found in Geometric (industrial cropping and ranching) and Fishbone (fallow agriculture with small-scale ranching) patterns. These findings indicate that the Fishbone pattern of deforestation produces a more biodiversity-friendly landscape structure than the Geometric pattern. On the other hand, older secondary vegetation found in the Geometric deforestation pattern could indicate more carbon stocked in those landscapes. Future public policies of land use and occupation should consider better landscape planning and management to overcome this duality and create synergies between biodiversity conservation and secondary vegetation carbon stock.

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Effects of settlement designs on deforestation and fragmentation in the Brazilian Amazon

Cited by 14 publications

References 24 publications

Trends of potentially illegal deforestation over protected areas of Rio das Velhas basin, Brazil

Trends of potentially illegal deforestation over protected areas of Rio das Velhas basin, Brazil

Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

Forest regeneration pathways in contrasting deforestation patterns of Amazonia

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