Brazilian Savanna Research Articles

Optimized Ultrasound-Assisted Extraction of Psidium laruotteanum Roots: A Concentrated Source of Piceid from the Brazilian Savanna

Psidium laruotteanum is a subshrub Myrtaceae, native to the Brazilian savanna, and distributed in Central and South America. Here, the health beneficial compound piceid (reservatrol-3-β-mono-d-glucoside) is described for the first time in the genus Psidium. The ultrasound-assisted extraction from P. laruotteanum roots was optimized by a response surface methodology. A central composite design was used to assess six extraction variables. Optimal extractions were obtained with 62.5% MeOH in water at 69.1 °C, amplitude of 70%, cycle of 0.5 s−1, pH 5.7 and solvent–solid ratio of 40:1, for 10 min. The method showed excellent recovery (90%–95%) and precision (CV: 0.69% for repeatability and 0.43% for intermediate precision). This species appears as the most concentrated plant source of piceid reported to date (29.15 mg·g−1 in dry roots). Additionally, a very fast extraction (5 min) can afford 96% recovery of piceid from Psidium laruotteanum roots. It could be used as a natural and cheap source of piceid for several applications.

Evaluation and Modelling of Reference Evapotranspiration Using Different Machine Learning Techniques for a Brazilian Tropical Savanna

Meteorological elements can affect the environment and cultures differently and may alter the natural development process contributing significantly to climate change. Meteorological variables of the Brazilian Pantanal were studied and used to determine evapotranspiration with fewer variables. It was found that artificial intelligence can substantially improve environmental modeling when alternative prediction techniques are used, resulting in lower project costs and more reliable results. This work tried to find the best combination by comparing machine learning techniques such as artificial neural networks, random forests, and support vector machines. A new model was created that depends on fewer climatic variables compared to the Penman–Monteith method (the standard method for estimating reference evapotranspiration) and can efficiently describe the reference evapotranspiration. Machine learning techniques are highly efficient for modeling environmental systems since they can process large amounts of data and find the best interactions between the parameters involved. In addition, more than 98% accuracy was obtained using fewer variables compared to the standard method when artificial neural networks are utilized.

Bundled contracts and technological diffusion: Evidence from the Brazilian soybean boom

Technological change in the 1970s and 1980s made it possible to grow soybeans in the remote Brazilian Savanna. However, multiple constraints typical of a developing region prevented many ranchers from adopting soybeans. Following the macroeconomic reforms that opened up the market in Brazil, international traders introduced a new farmer–trader contract that bundled technology, finance, inputs, and market access. The analysis of a novel panel dataset with farm-level census data reveals that this bundled contract led to rapid technological diffusion, agricultural expansion, and a 10-fold increase in agricultural productivity by enabling the conversion of marginal land into commercial soybean plantations.

How substrate type and elevation drive woody communities and influence species ecological strategies in the Brazilian savanna at local scale

AbstractEnvironmental heterogeneity can influence the formation of different vegetation types, even at small spatial scales. However, little is known about the factors that drive communities at local scales and species' mechanisms to adapt to different environments. Here, we investigated the influence of local environmental conditions and spatiality on the floristic variation of woody vegetation and ecological strategies of shrub‐tree species in the Brazilian savanna. We sampled adjacent sites in three substrate types—deep soil at high altitude (in Red Oxisol, with vegetation locally called Typical Cerrado—TCRO), deep soil, sandy and at low elevation (Typical Cerrado in Entisol Quartzipsamment—TCEQ), and shallow soil with rocky outcrops at high elevation (in Entisol Lithic, with vegetation known locally as Rupestrian Cerrado—RCEL). At each environment, we inventoried the vegetation, analyzed the physical–chemical soil properties, and recorded the elevation and geographic coordinates. For the most representative species of each site and the most common one among the environments, we evaluated the functional attributes (leaf nutrient concentration, specific leaf area, and maximum population heights). We showed that substrate type and elevation explain most of the floristic variation at the local scale and that the low nutritional demand constitutes the main strategy used by the species in RCEL, while in TCEQ and TCRO, species are more efficient in resource acquisition. Our results revealed that local ecological factors and processes drive species distribution. Therefore, variations in vegetation, even at the local scale must be considered to conserve biodiversity effectively.

Streamflow prediction based on machine learning models and rainfall estimated by remote sensing in the Brazilian Savanna and Amazon biomes transition

Streamflow prediction based on machine learning models and rainfall estimated by remote sensing in the Brazilian Savanna and Amazon biomes transition

Mapping Agricultural Intensification in the Brazilian Savanna: A Machine Learning Approach Using Harmonized Data from Landsat Sentinel-2

Agricultural intensification practices have been adopted in the Brazilian savanna (Cerrado), mainly in the transition between Cerrado and the Amazon Forest, to increase productivity while reducing pressure for new land clearing. Due to the growing demand for more sustainable practices, more accurate information on geospatial monitoring is required. Remote sensing products and artificial intelligence models for pixel-by-pixel classification have great potential. Therefore, we developed a methodological framework with spectral indices (Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Soil-Adjusted Vegetation Index (SAVI)) derived from the Harmonized Landsat Sentinel-2 (HLS) and machine learning algorithms (Random Forest (RF), Artificial Neural Networks (ANNs), and Extreme Gradient Boosting (XGBoost)) to map agricultural intensification considering three hierarchical levels, i.e., temporary crops (level 1), the number of crop cycles (level 2), and the crop types from the second season in double-crop systems (level 3) in the 2021–2022 crop growing season in the municipality of Sorriso, Mato Grosso State, Brazil. All models were statistically similar, with an overall accuracy between 85 and 99%. The NDVI was the most suitable index for discriminating cultures at all hierarchical levels. The RF-NDVI combination mapped best at level 1, while at levels 2 and 3, the best model was XGBoost-NDVI. Our results indicate the great potential of combining HLS data and machine learning to provide accurate geospatial information for decision-makers in monitoring agricultural intensification, with an aim toward the sustainable development of agriculture.

Anemochorous and zoochorous seeds of trees from the Brazilian savannas differ in fatty acid content and composition.

Fatty acids (FAs) stored as triacylglycerols (TAGs) are an important source of carbon and energy for germination and seedling development, particularly for plants with small wind-dispersed seeds, allowing greater efficiency in storing both energy and carbon. These plants should be under strong selection to produce seeds rich in FAs and with large amounts of saturated FAs. Their closely packed single-chain configuration allows greater packing, more carbon and energy per unit mass, and are less costly to produce. Efficient carbon storage would be less crucial for zoochorous species, which can reach much larger seed sizes (mass). We analysed the transesterified FA profile from seeds of 22 anemochorous and zoochorous tree species from the Cerrado savannas of Central Brazil. We tested if seed FA content covaried with seed mass and if anemochorous and zoochorous seeds differed in FA contents and distribution. Fatty acids were an important seed source of carbon and energy for most species. Fifteen different FAs were identified. Oleic, linoleic and linolenic tended to be the predominant unsaturated FAs. Oleic acid corresponded to more than 60 % of the total transesterified FAs in seeds of Kielmeyera coriacea, Qualea dichotoma and Triplaris americana. Linoleic acid corresponded to more than 50 % of total FA in Dalbergia miscolobium, Parkia platycephala and Ferdinandusa elliptica while linolenic acid was the dominant component in Inga cylindrica. Across species, palmitic and stearic were the dominant saturated FAs. The only exception was lauric acid (68 % of total FA) in seeds of Qualea grandiflora. On a log10 scale, as the seed increased in mass, accumulation of FAs tends to proceed at a faster rate in anemochorous species than in zoochorous species. They also became increasingly richer in saturated FAs. Zoochorous species had seed TAGs with higher proportion of polyunsaturated FAs.

Morphological traits explain the individual position within resource-consumer networks of a Neotropical marsupial.

Knowledge regarding the influence of individual traits on interaction patterns in nature can help understand the topological role of individuals within a network of intrapopulation interactions. We tested hypotheses on the relationships between individuals' positions within networks (specialization and centrality) of 4 populations of the mouse opossum Gracilinanus agilis and their traits (i.e., body length, body condition, tail length relative to body length, sex, reproductive condition, and botfly parasitism) and also seasonal effects in the Brazilian savanna. Individuals with lower body length, better body condition, and relatively shorter tail were more specialized (i.e., less connected within the network). Individuals were also more specialized and less connected during the warm-wet season. The relationship between individuals' position in the network and body traits, however, was independent of season. We propose that specialization may arise not only as a result of preferred feeding strategies by more capable individuals (i.e., those with better body condition and potentially prone to defend and access high-quality food resources) but also because of morphological constraints. Smaller/younger individuals (consequently with less experience in foraging) and short-tailed individuals (less skilled to explore the vertical strata of the vegetation) would feed only on a subset of the available food resources and consequently become more specialized. Moreover, individuals are more specialized during the warm-wet season because of high competition (population-dense period) and higher ecological opportunities (resource-rich period). Therefore, our study reveals the relevance of individual traits in shaping interaction patterns and specialization in populations.

In Case of Fire, Escape or Die: A Trait-Based Approach for Identifying Animal Species Threatened by Fire

Recent studies have argued that changes in fire regimes in the 21st century are posing a major threat to global biodiversity. In this scenario, incorporating species’ physiological, ecological, and evolutionary traits with their local fire exposure might facilitate accurate identification of species most at risk from fire. Here, we developed a framework for identifying the animal species most vulnerable to extinction from fire-induced stress in the Brazilian savanna. The proposed framework addresses vulnerability from two components: (1) exposure, which refers to the frequency, extent, and magnitude to which a system or species experiences fire, and (2) sensitivity, which reflects how much species are affected by fire. Sensitivity is based on biological, physiological, and behavioral traits that can influence animals’ mortality “during” and “after” fire. We generated a Fire Vulnerability Index (FVI) that can be used to group species into four categories, ranging from extremely vulnerable (highly sensible species in highly exposed areas), to least vulnerable (low-sensitivity species in less exposed areas). We highlight the urgent need to broaden fire vulnerability assessment methods and introduce a new approach considering biological traits that contribute significantly to a species’ sensitivity alongside regional/local fire exposure.

SOIL EROSION AND ROUTES OF USE AND PRODUCTION IN THE MATOPIBA REGION, BRAZIL

The goal was to monitor the production and soil erosion in the “MATOPIBA” region in the last 20 years. The study monitored agricultural production in the Brazilian Savanna, situated in the States of Tocantins (TO), Maranhão (MA), Bahia (BA), and Piauí (PI). The results showed that soybean occupies the largest area, corn and cotton show oscillations and coffee and sugar cane remain with values without major changes. In the production routes, the production areas present a positive correlation with k-apexes higher than 0.60 (p<0.05), indicating there is an increase in areas and no negative influence between the crops. The highest average erosivity rates were found respectively in the states of Tocantins and Maranhão. Conclude that the region MATOPIBA presents great potential for Brazilian agriculture requiring private and public actions to make sustainable use of the region through advanced technologies with conservation systems to avoid soil and water losses.

Species limits and diversification of the Dendropsophus rubicundulus subgroup (Anura, Hylidae) in Neotropical savannas

Understanding the processes that generate and maintain biodiversity at and below the species level is a central goal of evolutionary biology. Here we explore the spatial and temporal drivers of diversification of the treefrog subgroup Dendropsophus rubicundulus, a subgroup of the D. microcephalus species group, over periods of pronounced geological and climatic changes in the Neotropical savannas that they inhabit. This subgroup currently comprises 11 recognized species distributed across the Brazilian and Bolivian savannas, but the taxonomy has been in a state of flux, necessitating reexamination. Using newly generated single nucleotide polymorphism (SNP) data from restriction-site associated DNA sequencing (RADseq) and mitochondrial 16S sequence data for ∼150 specimens, we inferred phylogenetic relationships, tested species limits using a model-based approach, and estimated divergence times to gain insights into the geographic and climatic events that affected the diversification of this subgroup. Our results recognized at least nine species: D. anataliasiasi, D. araguaya, D. cerradensis, D. elianeae, D. jimi, D. rubicundulus, D. tritaeniatus, D. rozenmani, and D. sanborni. Although we did not collect SNP data for the latter two species, they are likely distinct based on mitochondrial data. In addition, we found genetic structure within the widespread species D. rubicundulus, which comprises three allopatric lineages connected by gene flow upon secondary contact. We also found evidence of population structure and perhaps undescribed diversity in D. elianeae, which warrants further study. The D. rubicundulus subgroup is estimated to have originated in the Late Miocene (∼5.45 million years ago), with diversification continuing through the Pliocene and Early Pleistocene, followed by the most recent divergence of D. rubicundulus lineages in the Middle Pleistocene. The epeirogenic uplift followed by erosion and denudation of the central Brazilian plateau throughout the Pliocene and Pleistocene, in combination with the increasing frequency and amplitude of climatic fluctuations during the Pleistocene, was important for generating and structuring diversity at or below the species level in the D. rubicundulus subgroup.

A framework to apply trait‐based ecological restoration at large scales

Abstract Upscaling trait‐based restoration to regional levels is necessary as we enter the UN Decade on Ecosystem Restoration. For this, we need to select species that achieve functional targets considering the regional species pool. Here, we present a framework to achieve multiple restoration targets using a regional species pool containing the species available on the market, species unavailable, and species that occur in reference ecosystems. The framework enables optimising functional diversity (FD), recovering FD and composition using reference ecosystems, reducing cost and increasing species diversity in restoration. Additionally, our framework allows the detection of functionally relevant species in the regional pool that are unavailable for restoration on the market. We illustrate our framework with a data set of Brazilian savanna tree communities. It was not possible to optimise FD with the species available on the market. To achieve this target, it would be necessary to use unavailable species from the regional pool. However, with the species available on the market it was possible to obtain communities resistant to fire and to restore functional composition and diversity to levels similar to or greater than those observed in reference ecosystems. Synthesis and applications. Our framework selects species to achieve multiple targets in large‐scale trait‐based restoration initiatives. The framework shows a range of solutions that can be achieved with the regional species pool. That allows the restoration practitioner to verify if functional parameters are truly optimised and which species should be added to the market or collected from the wild to achieve restoration targets. It also shows how different selected communities are from reference ecosystems, avoiding the unintentional creation of novel ecosystems.

Spatial scale affects the importance of deterministic and stochastic factors in the structuring of tadpole assemblages in Brazilian Cerrado

Many factors influence the structure of natural assemblages. Species interaction and environmental factors may generate deterministic patterns, whereas dispersal and ecological drift may generate stochastic patterns. We used pond systems to understand how deterministic and stochastic factors interact and influence tadpole assemblages at different spatial scales. We used variation partitioning and a co-occurrence analysis to evaluate how local environment heterogeneity, species interaction, and spatial variables affected species composition at local and regional scales in Brazilian savanna. Both deterministic and stochastic processes were important to explain tadpole distribution at regional scale, but with a greater contribution of stochastic factors. At local scales, environmental and niche traits were more important to explain tadpole distribution into the habitats. We demonstrate that in Brazilian Cerrado, species composition can be explained by the "MacArthur paradox", in which niche processes are important at local scales, whereas dispersal constraints and population processes lead to stochastic patterns in species distribution at large spatial scales.

Spatial and temporal deforestation in the Brazilian Savanna: The discrepancy between observed and licensed deforestation in the state of Goiás

Approximately 47% of the Brazilian savanna (Cerrado) has already been converted, mainly for agriculture and livestock activities. With low legal protection and few legally protected areas as Conservation Units, it is necessary to understand the dynamics of land use conversion and the existing legal instruments for Cerrado conservation. The state of Goiás had the second largest loss of accumulated area of native vegetation in all of the Cerrado. We evaluated the temporal and spatial trends of deforestation in Goiás between 2011 and 2021 using environmental licensing data (i.e., licensed deforestation) and land use conversion detected by remote sensing (i.e., observed deforestation). We found that observed deforestation was higher than licensed deforestation during these years, and only 13.33% of the entire deforested area in the state of Goiás obtained authorized environmental licenses. The temporal trends of deforestation indicated a reduction in deforestation from 2014 to 2019; however, in most recent years, observed deforestation increase at a higher rate than licensed deforestation. In a spatial context, the municipalities with the highest discrepancies among observed and licensed deforestation are situated in the north, northeast, and east of Goiás State. These areas are new frontiers for unlicensed deforestation, and they also presented most remaining native vegetation in Goiás. Therefore, the findings of this research may contribute to an improvement in environmental governance in Cerrado regions, thereby strengthening the Cerrado's protection.

Vertical stratification of ant assemblages varies along a latitudinal gradient in Brazilian savanna

AbstractAimArboreal and ground‐dwelling species experience distinct microclimates, have contrasting thermal tolerances and thus may be expected to respond differentially to geographic climatic gradients. We tested this idea by evaluating if the degree of vertical stratification of savanna ant assemblages varies along a latitudinal climatic gradient, and by determining how compositional dissimilarities within each stratum varies across increased geographical and climatic distances.LocationBrazil.TaxonAnts.MethodsWe sampled ants foraging on the ground or in trees at 32 sites. Species were classified according to their main foraging stratum, as arboreal, ground‐dweller or strata generalist. We used linear models to evaluate the effects of latitude and sampling stratum on species richness, and the effect of latitude on the proportion of species typical from trees or from the ground in different sampling strata. The influence of geographic and climatic distances on the compositional differences between assemblages from the same stratum was assessed using regression on distance matrices.ResultsSpecies richness on the ground increased with latitude significantly faster than in trees. The turnover of species between strata was lower at lower latitudes, where there were proportionally more strata generalists and species typical from the ground stratum foraging in trees. Consequently, the compositional dissimilarity between vertical strata decreased with decreasing latitude. Despite that, the dissimilarities between vertical strata were, on average, as great or even greater than the dissimilarities between assemblages from the same stratum across the horizontal space.Main ConclusionsWe found support for the idea that climatic variation across latitude had different effects on arboreal compared with ground‐foraging assemblages. Overall, our results suggest that as Brazilian savanna becomes hotter and drier as forecast under climate change, ant assemblages may become not only less diverse, notably on the ground, but also more homogeneous vertically.

The influence of proximity with riparian forests and the distance from urban areas on roadkills of vertebrates in a fragmented Brazilian savanna area

AbstractThe increasing development of highways severely threatens several vertebrates due to habitat fragmentation, edge effects and roadkills. Understanding how the landscape influences the occurrence of roadkills on highways can provide insights into the preferred routes of fauna dispersion and define the priority stretches to implement mitigation actions. This study evaluated the association between landscape characteristics and fauna roadkills on the BR‐158 highway (State of Mato Grosso do Sul, Brazil), where the adjacent vegetation encompasses phytophysiognomies of the Cerrado, a severely threatened biome. The spatial distribution of recorded road‐killed vertebrates (secondary data) was analysed using the statistical tool 2D Hotspot Identification, which defined the stretches with the highest mortality (hotspots). The surrounding landscape within a 1 km buffer zone around the highway was characterized based on area and distance information considering the land use and cover. Generalized linear models were applied to test the influence of locations on roadkill, considering the landscape characteristics as independent variables and the presence/absence of roadkill as the dependent variable. Our results indicated two hotspot stretches along the BR‐158 highway and a higher probability of roadkill in stretches associated with riparian forests and more distant from urban areas. The identification of landscape characteristics associated with the occurrence of vertebrate roadkills can help guide the planning and monitoring of highways. Furthermore, in dry ecosystems such as the Cerrado, we must provide information to implement priority actions in stretches of riparian forest, aiming to mitigate the adverse effects of highways on local biodiversity conservation.

Establishment and Expansion Scenario of Drosophila suzukii (Diptera: Drosophilidae) in Central Brazil.

Drosophila suzukii Matsumura (Diptera: Drosophilidae), also known as spotted wing drosophila (SWD), is an important pest that damages various wild and cultivated soft fruits worldwide, especially in the Northern Hemisphere. In Brazil, it occurs mainly in the subtropical climates of the southern and southeastern regions. However, SWD has also been sporadically found in the central region of the country in the natural vegetation of the tropical Brazilian Savanna. In this study, we investigated the occurrence of SWD at the northern limit of its range in South America - the central region of Brazil - by monitoring an established drosophilid community in an orchard located in the Brazilian Federal District. We also investigated the current geographical distribution of this pest in Brazil and its potential geographical distribution using species distribution models under two different future shared socioeconomic pathways scenarios (2040 and 2060, optimist and pessimist). Twenty drosophilid species were detected among the 6,396 captured specimens, most of which are exotic in the Neotropical region. The fly community greatly fluctuated throughout the year, and the highest abundance of SWD (3.5% relative abundance and 1.38 flies/trap/day) was recorded in April during the rainy season. Potential distribution models indicate that suitable areas for SWD spread will decrease in the south and southeast but increase in the central region of Brazil. We recommend continuous SWD monitoring and improving bioclimatic forecast models for mitigating damage to local fruit production.

Bamboo species, size, and soil water define the dynamics of available photosynthetic active solar radiation for intercrops in the Brazilian savanna biome

Bamboo has many potential applications in agroforestry systems. This study evaluated the photosynthetic active solar radiation available (PAR) to intercrops in three bamboo species as a function of estimated soil water content in the Brazilian savanna biome (tropical savanna climate with dry winters and rainy summers). The study was conducted from 2019 to 2021 (three to five years after planting), with clumps spaced at 8 × 5 m. PAR was measured below the bamboo at 0900, 1200, and 1500 h in the central, in-row, and inter-row positions. The estimated soil water balance was used to define the water available in the soil, which was correlated with the fraction of available PAR. The lowest value for the available PAR fraction occurred at the end of the maximum soil water content, being lower than 0.20 for Dendrocalamus asper and Dendrocalamus strictus and 0.80 for Guadua angustifolia. D. asper and D. strictus showed an inverse response rate of 0.50% and 0.75%, respectively, in the change in the available PAR fraction for each percentage change in the estimated mean soil water content 60 days prior to the PAR measurement date. G. angustifolia did not show any significant effect because of the smaller size of the culms and clump. The available PAR was correlated with estimated soil water content and species rate response. This information can be used to plan the cutting of bamboo culms to maximize the amount of PAR based on intercrop demand.

Sustainability Consequences of Making Land Change Decisions Based on Current Climatology in the Brazilian Cerrados

Brazil is one of the largest suppliers of commodities in the world, partly due to the agricultural expansion in the Brazilian savannas (also known as Cerrado) that began in the 1970s. However, as areas with better soil and climate for agriculture become scarce, farmers have been advancing to the ecotone between the savanna and xeric shrubland, where precipitation is less reliable for rainfed agriculture. The expected increase in temperature will lead to extended drought periods, with negative consequences for surface and groundwater resources. This study explores the hazards associated with making land-use decisions based on current climatology in regions where projected increases in temperature and reductions in water availability are anticipated to pose significant challenges to rainfed agriculture in the Brazilian Cerrado biome. We modeled future farmland expansion and how that matches with future climate change predictions (2016–2046). According to our estimates, at least 129 thousand km2 of cropland and 418 thousand km2 of pastures will be added in places with projected higher annual temperatures ranging from 26–30 °C. This is equivalent to ~60% of the current agricultural areas, and a novel agro-climatology will emerge for the Cerrado biome. Therefore, we discuss the agro-environmental policies that are pushing and pulling farmland expansion in the Cerrado. For instance, payments for environmental services could support the conservation of native vegetation on private land in regions with the highest temperature increases and deforestation risks. Moreover, in areas with expected reduced water yields, such as in the western Cerrado, the protection of riparian vegetation and strict regulation of water use could mitigate future risks to agriculture.

Do limits exist on potential woody cover of Brazilian savanna?

With the increasing concern of woody plant encroachment worldwide in savanna ecosystems, many studies endeavor to examine the upper bound of woody plant cover, which is referred to as potential woody cover. Potential woody cover defines the maximum possible woody plant encroachment and bears strong implications on savanna dynamics. Both African and North American savannas have been reported to exhibit limits on potential woody cover below 650 and 660 mm of mean annual precipitation (MAP), respectively. At present it is less clear whether that limit exists and at what level in the Brazilian savanna (the Cerrado) of South America, throughout which MAP is above 790 mm. This study models the potential woody cover pattern of Brazilian savanna over the present precipitation gradient and in relation to surface and subsurface soil moisture (SM) separately. Remotely sensed products were processed in Google Earth Engine (GEE), and included MODIS tree cover (MOD44B), TRMM monthly precipitation (3B43), and NASA-USDA Enhanced SMAP Global soil moisture. Quantile regression results suggest that below respective thresholds of MAP, surface SM, and subsurface SM, potential woody cover in Brazilian savanna is constrained. Comparison to the savanna in central Texas of the United States reveals that water availability is not the only determinant of potential woody cover. Regional context such as precipitation seasonality and woody plant species are important factors. This study also underscores the discrepancy between potential woody cover modelled based on MAP and that based on soil moisture (surface and subsurface).