Mangrove changes over the past decade in South and Southeast Brazil using spaceborne optical and SAR imagery.

Mangroves occur in the tropics and subtropics. This region is constantly covered by clouds and therefore highly challenging to map and monitor. Technological advances in remote sensing have increased the flexibility of performing such analyses. In this study, mapping and change detection were carried out for mangrove areas of the South and Southeast regions of Brazil between 2008 and 2016 using multisensor data and geographical object-based image analysis (GEOBIA). The 823.03 km² mangrove areas in study site in 2008 were reduced to 789.00 km² in 2016, representing a net loss of ~34 km². A change detection analysis of the mangrove areas showed a total gain of 138.21 km², a total loss of 172.24 km² and no change for 650.79 km². The GEOBIA classification accuracy was assessed by performing a statistical analysis of confusion matrix: (2008): global accuracy = 0.92, Kappa index = 0.84 and Tau index = 0.84; and (2016): global accuracy = 0.93, Kappa index = 0.86 and Tau index = 0.86. These results demonstrate the effectiveness of the GEOBIA to map and analyze mangrove dynamics. The results exhibit an excellent accuracy. Furthermore, mangrove areas in the south and southeast Brazil were mapped from the same methodological approach.

Status of mangroves land use on the Brazilian Amazon coast from RapidEye imagery and GEOBIA approach.

Given the ecological and socioeconomic importance of the mangroves of the Brazilian Amazon coast, RapidEye satellite images were analyzed to recognize mangrove forest and salt flat changes to different land use through human activities. Results show that mangroves are still very well preserved, with less than 1% of the total converted to other uses, primarily urban areas and roads. These human activities have been the principal causes of use in the mangrove forest, driven by local anthropogenic pressures resulting from human settlements in the transition zone between the mainland and tidal flats. In contrast, aquaculture, the principal driver of the loss of mangroves in other regions of South America and in Asian countries, plays only a secondary role in habitat conversion on the Amazon coast. However, these human activities demand more attention and policies need to be supported by Brazilian legislation.

Investigating Changes Driving Cumulative Impacts on Native Vegetation in Mining Regions in the Northeastern Brazilian Amazon.

Developing conservation strategies to mitigate cumulative impacts requires the understanding of historic land use and land cover changes at the regional scale. By using a multisensory and multitemporal approach, we identified the major changes driving cumulative impacts on native vegetation in northeastern Amazon. Comparing two regions, one with mining as the key driver and another where mining is associated with other industrial activities (cellulose), we explore the land use and land cover historic dynamics and derive implications for the assessment of cumulative impacts. Transitions of forest cover to pastureland, silviculture, and urban expansion were mapped in detail over a 20-year period, revealing that silviculture growth cleared more forests than pastureland expansion when associated with pulp mill activities and kaolin mining. In contrast, in a region with gold and iron mining, pastureland expansion was more relevant, clearing mainly areas surrounding new roads. This research shows that the interplay of major mining and industrial investments can produce cumulative losses of native vegetation, depending on the associated industries and infrastructure required for the project development. Our findings emphasize that the definition of spatial and temporal boundaries for the assessment of cumulative impacts must consider different trends in impact accumulation and changes in their spatial distribution over time.

Integrating environmental variables by multivariate ordination enables the reliable estimation of mineland rehabilitation status.

Despite the wide variety of variables commonly employed to measure the success of rehabilitation, the assessment and subsequent definition of indicators of environmental rehabilitation status are not simple tasks. The main challenges are comparing rehabilitated sites with target ecosystems as well as integrating individual environmental and eventually collinear variables into a single tractable measure for the state of a system before effective indicators that track rehabilitation may be modeled. Furthermore, a consensus is lacking regarding which and how many variables need to be surveyed for a reliable estimation of rehabilitation status. Here, we propose a multivariate ordination to integrate variables related to ecological processes, vegetation structure, and community diversity into a single estimation of rehabilitation status. As a case, we employed a curated set of 32 environmental variables retrieved from nonrevegetated, rehabilitating and reference sites associated with iron ore mines from the Urucum Massif, Mato Grosso do Sul, Brazil. By integrating this set of environmental variables into a single estimation of rehabilitation status, the proposed multivariate approach is straightforward and able to adequately address collinearity among variables. The proposed methodology allows for the identification of biases towards single variables, surveys or analyses, which is necessary to rank environmental variables regarding their importance to the assessment. Furthermore, we show that bootstrapping permitted the detection of the minimum number of environmental variables necessary to achieve reliable estimations of the rehabilitation status. Finally, we show that the proposed variable integration enables the definition of case-specific environmental indicators for more rapid assessments of mineland rehabilitation. Thus, the proposed multivariate ordination represents a powerful tool to facilitate the diagnosis of rehabilitating sites worldwide provided that sufficient environmental variables related to ecological processes, diversity and vegetation structure are gathered from nonrehabilitated, rehabilitating and reference study sites. By identifying deviations from predicted rehabilitation trajectories and providing assessments for environmental agencies, this proposed multivariate ordination increases the effectiveness of (mineland) rehabilitation.

The effect of anthropogenic drivers on spatial patterns of mangrove land use on the Amazon coast.

Mangroves play an essential ecological role in the maintenance of the coastal zone and are extremely important for the socioeconomics of coastal communities. However, mangrove ecosystems are impacted by a range of anthropogenic pressures, and the loss of this habitat can be attributed primarily to the human occupation of the coastal zone. In the present study, we analyzed the spatial patterns of land use in the mangrove of the Brazilian Amazon coast, and evaluated the anthropogenic drivers of this impact, using a remote sensing approach. We mapped the road network using RapidEye images, and human settlements using global data. The results of these analyses indicate that the Brazilian Amazon coast has a low population density and low rates of anthropogenic impact in most of the coastal microregions investigated, factors that contribute to the maintenance and conservation of the region's mangrove. The study also revealed that the paved road network is one of the principal drivers of land use in the mangrove, whereas other factors, such as population density, urban centers, and the number of settlements are much less important. While the region has 2024 km of paved highways, unpaved roads (17,496 km) facilitate access to the mangrove, with approximately 90% of anthropogenic impact being recorded within a 3 km radius of these roads. While the network of paved highways is relatively reduced in extension, preventive measures are urgently required to impede any major shift in the current scenario, caused by the expansion of major development programs. The results of the study indicate that biophysical, economic, and political factors may also contribute to the reduction, stability, and development of one of the world's largest areas of mangrove forest.

Mapping and quantification of ferruginous outcrop savannas in the Brazilian Amazon: A challenge for biodiversity conservation.

The eastern Brazilian Amazon contains many isolated ferruginous savanna ecosystem patches (locally known as 'canga vegetation') located on ironstone rocky outcrops on the top of plateaus and ridges, surrounded by tropical rainforests. In the Carajás Mineral Province (CMP), these outcrops contain large iron ore reserves that have been exploited by opencast mining since the 1980s. The canga vegetation is particularly impacted by mining, since the iron ores that occur are associated with this type of vegetation and currently, little is known regarding the extent of canga vegetation patches before mining activities began. This information is important for quantifying the impact of mining, in addition to helping plan conservation programmes. Here, land cover changes of the Canga area in the CMP are evaluated by estimating the pre-mining area of canga patches and comparing it to the actual extent of canga patches. We mapped canga vegetation using geographic object-based image analysis (GEOBIA) from 1973 Landsat-1 MSS, 1984 and 2001 Landsat-5 TM, and 2016 Landsat-8 OLI images, and found that canga vegetation originally occupied an area of 144.2 km2 before mining exploitation. By 2016, 19.6% of the canga area was lost in the CMP due to conversion to other land-use types (mining areas, pasturelands). In the Carajás National Forest (CNF), located within the CMP, the original canga vegetation covered 105.2 km2 (2.55% of the CNF total area), and in 2016, canga vegetation occupied an area of 77.2 km2 (1.87%). Therefore, after more than three decades of mineral exploitation, less than 20% of the total canga area was lost. Currently, 21% of the canga area in the CMP is protected by the Campos Ferruginosos National Park. By documenting the initial extent of canga vegetation in the eastern Amazon and the extent to which it has been lost due to mining operations, the results of this work are the first step towards conserving this ecosystem.

Quillworts from the Amazon: A multidisciplinary populational study on Isoetes serracarajensis and Isoetes cangae.

Isoetes are ancient quillworts members of the only genus of the order Isoetales. The genus is slow evolving but is resilient, and widespread worldwide. Two recently described species occur in the Eastern Brazilian Amazon, Isoetes serracarajensis and Isoetes cangae. They are found in the ironstone grasslands known as Canga. While I. serracarajensis is present mostly in seasonal water bodies, I. cangae is known to occur in a single permanent lake at the South mountain range. In this work, we undertake an extensive morphological, physiological and genetic characterization of both species to establish species boundaries and better understand the morphological and genetic features of these two species. Our results indicate that the morphological differentiation of the species is subtle and requires a quantitative assessment of morphological elements of the megaspore for diagnosis. We did not detect differences in microspore output, but morphological peculiarities may establish a reproductive barrier. Additionally, genetic analysis using DNA barcodes and whole chloroplast genomes indicate that although the plants are genetically very similar both approaches provide diagnostic characters. There was no indication of population structuring I. serracarajensis. These results set the basis for a deeper understanding of the evolution of the Isoetes genus.

Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon.

Long-term human-induced impacts have significantly changed the Amazonian landscape. The most dramatic land cover and land use (LCLU) changes began in the early 1970s with the establishment of the Trans-Amazon Highway and large government projects associated with the expansion of agricultural settlement and cattle ranching, which cleared significant tropical forest cover in the areas of new and accelerated human development. Taking the changes in the LCLU over the past four decades as a basis, this study aims to determine the consequences of land cover (forest and savanna) and land use (pasturelands, mining and urban) changes on the hydroclimatology of the Itacaiúnas River watershed area of the located in the southeastern Amazon region. We analyzed a multi-decadal Landsat dataset from 1973, 1984, 1994, 2004 and 2013 and a 40-yr time series of water discharge from the Itacaiúnas River, as well as air temperature and relative humidity data over this drainage area for the same period. We employed standard Landsat image processing techniques in conjunction with a geographic object-based image analysis and multi-resolution classification approach. With the goal of detecting possible long-term trends, non-parametric Mann-Kendall test was applied, based on a Sen slope estimator on a 40-yr annual PREC, TMED and RH time series, considering the spatial average of the entire watershed. In the 1970s, the region was entirely covered by forest (99%) and savanna (∼0.3%). Four decades later, only ∼48% of the tropical forest remains, while pasturelands occupy approximately 50% of the watershed area. Moreover, in protected areas, nearly 97% of the tropical forest remains conserved, while the forest cover of non-protected areas is quite fragmented and, consequently, unevenly distributed, covering an area of only 30%. Based on observational data analysis, there is evidence that the conversion of forest cover to extensive and homogeneous pasturelands was accompanied by systematic modifications to the hydroclimatology cycle of the Itacaiúnas watershed, thus highlighting drier environmental conditions due to a rise in the region's air temperature, a decrease in the relative humidity, and an increase in river discharge.

A socioeconomic and natural vulnerability index for oil spills in an Amazonian harbor: a case study using GIS and remote sensing.

The coastal zone of the Brazilian state of Maranhão is an area characterized by a large variety of human activities and services, in particular in the Itaqui-Bacanga port complex (IBC). The IBC is an area prone to oil spills resulting from the processes of transportation, storage, and tank cleaning. The present study aimed to map the different physical environments adjacent to this complex and the socioeconomic profile of the local population that would be most vulnerable to this type of disaster. Vulnerability studies are essential as one of the first step in the development of an integrated coastal zone management. The variables analyzed in this study included geomorphological units, and the income, education, and dependence on fishing of the local population. The estimate of the vulnerability index was based on the relationships between these variables, which were used to generate a vulnerability map using GIS and the interpretation of high-resolution remote sensing, showing the areas of highest priority for intervention in the case of oil spills. The analysis of the natural and socioeconomic environments indicated that the areas of highest vulnerability correspond to the mangroves and the Vila Nova and Alto da Esperança neighborhoods, respectively. These neighborhoods have a direct relationship with fishing, and low levels of both income and education. By contrast, the lowest vulnerability was attributed to the coastal plateau and the central Anjo da Guarda neighborhood, which is occupied by residents with relatively high income and education, who do not depend on fishing.