Fires Drive Long-Term Environmental Degradation in the Amazon Basin

The Amazon Basin is undergoing extensive environmental degradation as a result of deforestation and the rising occurrence of fires. The degradation caused by fires is exacerbated by the occurrence of anomalously dry periods in the Amazon Basin. The objectives of this study were: (i) to quantify the extent of areas that burned between 2001 and 2019 and relate them to extreme drought events in a 20-year time series; (ii) to identify the proportion of countries comprising the Amazon Basin in which environmental degradation was strongly observed, relating the spatial patterns of fires; and (iii) examine the Amazon Basin carbon balance following the occurrence of fires. To this end, the following variables were evaluated by remote sensing between 2001 and 2019: gross primary production, standardized precipitation index, burned areas, fire foci, and carbon emissions. During the examined period, fires affected 23.78% of the total Amazon Basin. Brazil had the largest affected area (220,087 fire foci, 773,360 km2 burned area, 54.7% of the total burned in the Amazon Basin), followed by Bolivia (102,499 fire foci, 571,250 km2 burned area, 40.4%). Overall, these fires have not only affected forests in agricultural frontier areas (76.91%), but also those in indigenous lands (17.16%) and conservation units (5.93%), which are recognized as biodiversity conservation areas. During the study period, the forest absorbed 1,092,037 Mg of C, but emitted 2908 Tg of C, which is 2.66-fold greater than the C absorbed, thereby compromising the role of the forest in acting as a C sink. Our findings show that environmental degradation caused by fires is related to the occurrence of dry periods in the Amazon Basin.

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Spatial scales influence long-term response of herbivores to prescribed burning in a savanna ecosystem

International Journal of Wildland Fire ◽

10.1071/wf16152 ◽

2017 ◽

Vol 26 (4) ◽

pp. 287 ◽

Cited By ~ 1

Author(s):

Duncan M. Kimuyu ◽

Ryan L. Sensenig ◽

Robert M. Chira ◽

John M. Githaiga ◽

Truman P. Young

Keyword(s):

Prescribed Burning ◽

Spatial Scales ◽

Fire Effects ◽

Spatial Extent ◽

Burned Area ◽

Burned Areas ◽

Spatial And Temporal Heterogeneity ◽

Intermediate Size ◽

Term Response

Both wild and prescribed fire in savanna ecosystems influence habitat use by herbivores by creating or maintaining spatial and temporal heterogeneity in forage quality and vegetation cover. Yet little is known about how spatial scales influence long-term persistence of fire effects. We examined changes over a 6-year period in herbivore preference for experimentally burned patches that varied in spatial extent and grain. Avoidance for the burns by elephants and preference for the burns by impala and Grant’s gazelle decreased significantly. For the rest of the species (zebra, eland, oryx, hartebeest, warthog and hare), there were no significant changes in preference for the burns. Changes in preference for the burned areas depended on the spatial extent and grain of the burn, with intermediate-size (9-ha) burns and large (8-ha) patchy burns being more preferred 6–7 years after fire. Grain, but not the spatial extent of the burned area, influenced changes in grass height. Fire resulted in a delayed reduced tree density irrespective of the spatial scale of the burn. Results of this study indicate that, depending on the scale of fire prescription, the impacts of fire on herbivores may last longer than previous studies suggest.

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Assessing the wildfire activity in protected areas of the Amazon basin

10.5194/egusphere-egu21-7200 ◽

2021 ◽

Author(s):

Emmanuel Da Ponte ◽

Fermin Alcasena ◽

Tejas Bhagwat ◽

Zhongyang Hu

Keyword(s):

Land Use ◽

Land Cover ◽

Protected Areas ◽

Amazon Basin ◽

Burned Area ◽

Land Use Land Cover ◽

Fire Control ◽

Burned Areas ◽

Burn Probability ◽

Fire Ignition

Despite &#160;growing concerns regarding the Amazonian wildfires, the magnitude of the problem is poorly understood. In this study, we assessed the wildfire activity in the &#160;protected natural sites (n= 428) of Bolivia, Brazil, Colombia, Ecuador, French Guyana, Guyana, Peru, Suriname, and Venezuela, encompassing an area of 1.4 million km2 of the Amazon basin. A 250 m resolution spectroradiometer sensor imaging (MODIS) was used to obtain land-use/land-cover (MODIS land use land cover product) changes and derive the wildfire activity data (ignition locations and burned areas (MODIS active fire products)) from 2001 to 2018. First, we characterized the mean fire return interval, wildfire occurrence, and empiric burn probability. Then, we implemented a transmission analysis to assess the burned area from incoming fires. We used transmission analysis to characterize the land use and anthropic activities associated to fire ignition locations across the different countries. On average, 867 km 2 of natural forests were burned in protected natural sites annually, and about 85 incoming fires per year from neighboring areas accounted for 10.5% (9,128 ha) of the burned area. The most affected countries were Brazil (53%), Bolivia (24%), and Venezuela (16%).Considerable amount of fire ignition points were detected in open savannas (29%) and grasslands (41%) , where the fire is periodically used to clear extensive grazing properties. The incoming fires from savannas were responsible for burning the largest forest areas within protected sites, affecting as much as 9,800 ha in a single fire event. In conclusion, we &#160;discuss the potential implications of the main socioeconomic factors and environmental policies that could explain increasing trends of burned areas. Wildfire risk mitigation strategies include the fire ignition prevention in developed areas, fire use regulation in rural communities, increased fuels management efforts in the buffer areas surrounding natural sites, and the early detection system that may facilitate a rapid and effective fire control response. Our analysis and quantitative outcomes describing the fire activity represent a sound science-based approach for an well defined wildfire management within the protected areas of the Amazonian basin.

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The “New Transamazonian Highway”: BR-319 and Its Current Environmental Degradation

Sustainability ◽

10.3390/su14020823 ◽

2022 ◽

Vol 14 (2) ◽

pp. 823

Author(s):

Mendelson Lima ◽

Dthenifer Cordeiro Santana ◽

Ismael Cavalcante Maciel Junior ◽

Patricia Monique Crivelari da Costa ◽

Pedro Paulo Gomes de Oliveira ◽

...

Keyword(s):

Environmental Degradation ◽

Statistical Tests ◽

Ghg Emissions ◽

Principal Component ◽

Amazon Forest ◽

Road Maintenance ◽

Conservation Units ◽

Capital Cities ◽

Burned Areas ◽

Brazilian Government

The Brazilian government intends to complete the paving of the BR-319 highway, which connects Porto Velho in the deforestation arc region with Manaus in the middle of the Amazon Forest. This paving is being planned despite environmental legislation, and there is concern that its effectiveness will cause additional deforestation, threatening large portions of forest, conservation units (CUs), and indigenous lands (ILs) in the surrounding areas. In this study, we evaluated environmental degradation along the BR-319 highway from 2008 to 2020 and verified whether highway maintenance has contributed to deforestation. For this purpose, we created a 20 km buffer adjacent to the BR-319 highway and evaluated variables extracted from remote sensing information between 2008 and 2020. Fire foci, burned areas, and rainfall data were used to calculate a drought index using statistical tests for a time series. Furthermore, these were related to data on deforestation, CUs, and ILs using principal component analysis and Pearson’s correlation. Our results showed that 743 km2 of forest was deforested during the period evaluated, most of which occurred in the last four years. A total of 16,472 fire foci were identified. Both deforestation and fire foci occurred mainly outside the CUs and ILs. The most affected areas were close to capital cities, and after resuming road maintenance in 2015, deforestation increased outside the capital cities. Current government policy for Amazon occupation promotes deforestation and will compromise Brazil’s climate goals of reducing greenhouse gas (GHG) emissions and deforestation.

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Multi-Sensor, Active Fire-Supervised, One-Class Burned Area Mapping in the Brazilian Savanna

Remote Sensing ◽

10.3390/rs13194005 ◽

2021 ◽

Vol 13 (19) ◽

pp. 4005

Author(s):

Allan A. Pereira ◽

Renata Libonati ◽

Julia A. Rodrigues ◽

Joana Nogueira ◽

Filippe L. M. Santos ◽

...

Keyword(s):

Fire Regime ◽

Training Sample ◽

Burned Area ◽

Mapping Accuracy ◽

Mapping Algorithm ◽

Burned Areas ◽

Active Fire ◽

Landsat Satellite ◽

Omission Errors

Increasing efforts are being devoted to understanding fire patterns and changes highlighting the need for a consistent database about the location and extension of burned areas (BA). Satellite-derived BA mapping accuracy in the Brazilian savannas is limited by the underestimation of burn scars from small, fragmented fires and high cloudiness. Moreover, systematic mapping of BA is challenged by the need for human intervention in training sample acquisition, which precludes the development of automatic-generated products over large areas and long periods. Here, we developed a multi-sensor, active fire-supervised, one-class BA mapping algorithm to address several of these limitations. Our main objective is to generate a long-term, detailed BA atlas suitable to improve fire regime characterization and validation of coarse resolution products. We use composite images derived from the Landsat satellite to generate end-of-season maps of fire-affected areas for the entire Cerrado. Validation exercises and intercomparison with BA maps from a semi-automatic algorithm and visual photo interpretation were conducted for the year 2015. Our results improve the BA mapping by reducing omission errors, especially where there is high cloud frequency, few active fires are detected, and burned areas are small and fragmented. Finally, our approach represents at least a 45% increase in BA mapped in the Cerrado, in comparison to the annual extent detected by the current coarse global product from MODIS satellite (MCD64), and thus, it is capable of supporting improved regional emissions estimates.

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Assessing Wildfire Regimes in Indigenous Lands of the Brazilian Savannah-Like Cerrado

Fire ◽

10.3390/fire4030034 ◽

2021 ◽

Vol 4 (3) ◽

pp. 34

Author(s):

Pedro Melo ◽

Javier Sparacino ◽

Daihana Argibay ◽

Vicente Sousa Júnior ◽

Roseli Barros ◽

...

Keyword(s):

Forest Fires ◽

Fire Regime ◽

Management Strategies ◽

Fire Regimes ◽

Google Earth ◽

Dry Season ◽

Burned Area ◽

Burned Areas ◽

Brazilian Savannah ◽

Indigenous Lands

The Brazilian savannah-like Cerrado is classified as a fire-dependent biome. Human activities have altered the fire regimes in the region, and as a result, not all fires have ecological benefits. The indigenous lands (ILs) of the Brazilian Cerrado have registered the recurrence of forest fires. Thus, the diagnosis of these events is fundamental to understanding the burning regimes and their consequences. The main objective of this paper is to evaluate the fire regimes in Cerrado’s indigenous lands from 2008 to 2017. We used the Landsat time series, at 30 m spatial resolution, available in the Google Earth Engine platform to delineate the burned areas. We used precipitation data from a meteorological station to define the rainy season (RS), early dry season (EDS), middle dry season (MDS), and late dry season (LDS) periods. During 2008–2017, our results show that the total burned area in the indigenous lands and surrounding area was 2,289,562 hectares, distributed in 14,653 scars. Most fires took place between June and November, and the annual burned area was quite different in the years studied. It was also possible to identify areas with high fire recurrence. The fire regime patterns described here are the first step towards understanding the fire regimes in the region and establishing directions to improve management strategies and guide public policies.

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DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

Proceedings of the 7th International Scientific Conference Rural Development 2015 ◽

10.15544/rd.2015.059 ◽

2015 ◽

Cited By ~ 1

Author(s):

Laima TAPARAUSKIENĖ ◽

Veronika LUKŠEVIČIŪTĖ

Keyword(s):

Meteorological Data ◽

Standardized Precipitation Index ◽

Vegetation Period ◽

Climatic Conditions ◽

Precipitation Record ◽

Calculation Step ◽

Drought Conditions ◽

The Standardized Precipitation Index ◽

June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

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Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

Remote Sensing ◽

10.3390/rs13081509 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1509

Author(s):

Xikun Hu ◽

Yifang Ban ◽

Andrea Nascetti

Keyword(s):

Deep Learning ◽

Large Scale ◽

Multiple Scales ◽

Detection Methods ◽

Burned Area ◽

Landsat 8 ◽

Multispectral Imagery ◽

Burned Areas ◽

Local Climate Zones ◽

Sentinel 2

Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems. Various burned area detection methods have been developed using satellite remote sensing measurements with wide coverage and frequent revisits. Our study aims to expound on the capability of deep learning (DL) models for automatically mapping burned areas from uni-temporal multispectral imagery. Specifically, several semantic segmentation network architectures, i.e., U-Net, HRNet, Fast-SCNN, and DeepLabv3+, and machine learning (ML) algorithms were applied to Sentinel-2 imagery and Landsat-8 imagery in three wildfire sites in two different local climate zones. The validation results show that the DL algorithms outperform the ML methods in two of the three cases with the compact burned scars, while ML methods seem to be more suitable for mapping dispersed burn in boreal forests. Using Sentinel-2 images, U-Net and HRNet exhibit comparatively identical performance with higher kappa (around 0.9) in one heterogeneous Mediterranean fire site in Greece; Fast-SCNN performs better than others with kappa over 0.79 in one compact boreal forest fire with various burn severity in Sweden. Furthermore, directly transferring the trained models to corresponding Landsat-8 data, HRNet dominates in the three test sites among DL models and can preserve the high accuracy. The results demonstrated that DL models can make full use of contextual information and capture spatial details in multiple scales from fire-sensitive spectral bands to map burned areas. Using only a post-fire image, the DL methods not only provide automatic, accurate, and bias-free large-scale mapping option with cross-sensor applicability, but also have potential to be used for onboard processing in the next Earth observation satellites.

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Using the Landsat Burned Area Products to Derive Fire History Relevant for Fire Management and Conservation in the State of Florida, Southeastern USA

Fire ◽

10.3390/fire4020026 ◽

2021 ◽

Vol 4 (2) ◽

pp. 26

Author(s):

Casey Teske ◽

Melanie K. Vanderhoof ◽

Todd J. Hawbaker ◽

Joe Noble ◽

John Kevin Hiers

Keyword(s):

Prescribed Fire ◽

Spatial Data ◽

Fire History ◽

Fire Management ◽

Fire Behavior ◽

Fire Risk ◽

Behavior Modeling ◽

Burned Area ◽

Burned Areas ◽

Burn Probability

Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.

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Leopard Density Estimation within an Enclosed Reserve, Namibia Using Spatially Explicit Capture-Recapture Models

Animals ◽

10.3390/ani9100724 ◽

2019 ◽

Vol 9 (10) ◽

pp. 724

Author(s):

Noack ◽

Heyns ◽

Rodenwoldt ◽

Edwards

Keyword(s):

Management Strategies ◽

Camera Traps ◽

Spatially Explicit ◽

Conservation Areas ◽

Term Survival ◽

New Class ◽

Capture Recapture ◽

Wildlife Populations ◽

Effective Conservation

The establishment of enclosed conservation areas are claimed to be the driving force for the long-term survival of wildlife populations. Whilst fencing provides an important tool in conservation, it simultaneously represents a controversial matter as it stops natural migration processes, which could ultimately lead to inbreeding, a decline in genetic diversity and local extinction if not managed correctly. Thus, wildlife residing in enclosed reserves requires effective conservation and management strategies, which are strongly reliant on robust population estimates. Here, we used camera traps combined with the relatively new class of spatially explicit capture-recaptured models (SECR) to produce the first reliable leopard population estimate for an enclosed reserve in Namibia. Leopard density was estimated at 14.51 leopards/100 km2, the highest recorded density in Namibia to date. A combination of high prey abundance, the absence of human persecution and a lack of top-down control are believed to be the main drivers of the recorded high leopard population. Our results add to the growing body of literature which suggests enclosed reserves have the potential to harbour high densities and highlight the importance of such reserves for the survival of threatened species in the future.

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Retrievals of Atmospheric Carbonyl Sulfide from IASI

10.5194/egusphere-egu21-10373 ◽

2021 ◽

Author(s):

Michael P. Cartwright ◽

Jeremy J. Harrison ◽

David P. Moore

Keyword(s):

Gross Primary Production ◽

Carbonyl Sulfide ◽

Optimal Estimation ◽

Stratospheric Aerosol ◽

Data Set ◽

Spatial Coverage ◽

Retrieval Scheme ◽

The University ◽

Fresh Insight

Carbonyl sulfide (OCS) is the most abundant sulfur containing gas in the atmosphere and is an important source of stratospheric aerosol. Furthermore, it has been shown that OCS can be used as a proxy for photosynthesis, which is a powerful tool in quantifying global gross primary production. While considerable improvements have been made in our understanding of the location and magnitude of OCS fluxes over the past few decades, recent studies highlight the need for a new satellite dataset to help reduce the uncertainties in current estimations. The Infrared Atmospheric Sounding Interferometer (IASI) instruments on-board the MetOp satellites offer over 14 years of nadir viewing radiance measurements with excellent spatial coverage. Given that there are currently three IASI instruments in operation, there is the potential for a significantly larger OCS dataset than is currently available elsewhere. Retrievals of OCS from these IASI radiances have been made using an adapted version of the University of Leicester IASI Retrieval Scheme (ULIRS). OCS total column amounts are calculated from profiles retrieved on a 31-layer equidistant pressure grid, using an optimal estimation approach for microwindows in the range 2000 &#8211; 2100 cm-1 wavenumbers. Sensitivity of the measurements peak in the mid-troposphere, between 5 &#8211; 10 km.The outlook of this work is to produce a long-term OCS satellite observational data set that provides fresh insight to the spatial distribution and trend of atmospheric OCS. Here, we present subsets of data in the form of case studies for different geographic regions and time periods.

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