Search Results (142)

The Peruvian Amazon faces an increasing threat of soil erosion, driven by unsustainable agricultural practices and accelerated deforestation. In Neshuya (Ucayali region), agricultural activity has intensified since 2014, but the effect on soil erosion is unknown. The present study aimed to evaluate the increase in erosion levels, at a sub-basin of the central–eastern Amazon of Peru, in a Geographic Information System (GIS) environment. The revised universal soil loss equation (RUSLE) model was used for assessing the effect of vegetation cover change from 2016 to 2022. In the Neshuya sub-basin (973.4 km²), the average erosion increased from 3.87 to 4.55 t ha⁻¹ year⁻¹, on average. In addition, there is great spatial variability in the values. In addition, 7.65% of the study area (74.52 km²) exceeds the soil loss tolerance limit (15 t ha⁻¹ year⁻¹). The deforestation rate was 17.99 km² year⁻¹ and by 2022 the forested area reached 237.65 km². In conclusion, the transition from forest to farmland was related to the most critical erosion values. Unsustainable soil management practices can be the underlying explanation of changes in soil chemical and physical properties. Also, social dynamic changes and differences in landscape patterns play a role. Full article

Pollen rain studies are rare in arid and semi-arid regions worldwide. Interpretations related to the dynamics of plant communities and possible paleoclimatic changes in these areas face significant limitations due to this lack of data. The global biome of Seasonally Dry Tropical Forests and Shrublands (SDTFS) is represented in Northeast Brazil by the caatinga, which is composed of xerophytic vegetation. This study aimed to generate information about the pollen rain in this area and to understand its relationship with species flowering, pollination syndromes, life forms, and climatic aspects. A caatinga area in Canudos, Bahia, Brazil (09°54′ S 39°07′ W), was selected for this purpose. Artificial pollen collectors were installed and exchanged monthly over two years for palynological analyses of the collected material, using standard palynological techniques. A total of 124 pollen types were identified, with approximately 8823 pollen grains deposited per cm² over the two years. Several vegetation components were represented in the pollen rain, reflecting local plant diversity, life forms, and physiognomies. A positive relationship was observed between increased temperature and pollen production from trees and shrubs, and new pollen types were associated with indicator species of caatinga vegetation. Full article

Urban settlements can support significant biodiversity and provide a wide range of ecosystem services. Remote sensing (RS) offers valuable tools for monitoring and conserving urban biodiversity. Our research, funded by the Italian Recovery and Resilience Plan (National Biodiversity Future Centre—Urban Biodiversity), undertakes a systematic scientific review to assess the current status and future prospects of urban biodiversity evaluation using RS. An extensive literature search of indexed peer-reviewed papers published between 2008 and 2023 was conducted on the Scopus database, using a selective choice of keywords. After screening the titles, abstracts, and keywords of 500 articles, 117 relevant papers were retained for meta-data analysis. Our analysis incorporated technical (e.g., sensor, platform, algorithm), geographic (e.g., country, city extent, population) and ecological (biodiversity target, organization level, biome) meta-data, examining their frequencies, temporal trends (Generalized Linear Model—GLM), and covariations (Cramer’s V). The rise in publications over time is linked to the increased availability of imagery, enhanced computing power, and growing awareness of the importance of urban biodiversity. Most research focused on the Northern Hemisphere and large metropolitan areas, with smaller cities often overlooked. Consequently, data coverage is predominantly concentrated on Mediterranean and temperate habitats, with limited attention given to boreal, desert, and tropical biomes. A strong association was observed between the source of RS data (e.g., satellite missions), pixel size, and the purpose of its use (e.g., modeling, detection). This research provides a comprehensive summary of RS applications for evaluating urban biodiversity with a focus on the biomes studied, biodiversity targets, and ecological organization levels. This work can provide information on where future studies should focus their efforts on the study of urban biodiversity using remote sensing instruments in the coming years. Full article

Tropical forests have high species richness, being considered the most diverse and complex ecosystems in the world. Research on the variation and maintenance of biodiversity in these ecosystems is important for establishing conservation strategies. The main objective of this study was to test the Spectral Variation Hypothesis through associations between species diversity and richness measured in the field and hyperspectral data collected by a Remotely Piloted Aircraft (RPA) in areas with secondary tropical forest in the Brazilian Atlantic Forest biome. Specific objectives were to determine which dispersion measurements, standard deviation (SD) or coefficient of variation (CV), estimated for the n pixels occurring within each sampling unit, better explains species diversity; the effects of pixel size on the direction and intensity of this relationship; and the effects of shaded pixels within each sampling unit. The spectral variability hypothesis was confirmed for the Atlantic Forest biome, with R² of 0.83 for species richness and 0.76 and 0.69 for the Shannon and Simpson diversity indices, respectively, using 1.0 m illuminated pixels. The dispersion (CV and SD) of hyperspectral bands were most strongly correlated with taxonomic diversity and richness in the red-edge and near-infrared (NIR) regions of the electromagnetic spectrum. Pixel size affected R² values, which were higher for 1.0 m pixels (0.83) and lower for 10.0 m pixels (0.71). Additionally, illuminated pixels had higher R² values than those under shadow effects. The main dispersion variables selected as metrics for regression models were mean CV, CV for the 726.7 nm band, and SD for the 742.3 and 933.4 nm bands. Our results suggest that spectral diversity can serve as a proxy for species diversity in the Atlantic Forest. However, factors that can affect this relationship, such as taxonomic and spectral diversity metrics used, pixel size, and shadow effects in images, should be considered. Full article

The mangrove biome is a highly productive system globally, with flora and fauna adapted to significant saline influence, where salt flats coexist alongside these systems, emerging over sands and muds with high salinity and sparse vegetation. The objective of this research is to describe, for the first time in Ecuador, the diversity of epiphytic lichens in salt flats in the southern region of Ecuador. Two salt flats were selected where Avicennia germinans and Laguncularia racemosa were the dominant trees with the shrub Batis maritima. A total of 30 species of epiphytic lichens were recorded, with the families Arthoniaceae, Graphidaceae, and Ramalinaceae having the highest number of species, and crustose lichens with photobiont type Trentepohlia showed high richness. The salt flats in the southern region of Ecuador have a high richness of epiphytic lichen species, and the species composition is similar to mangroves, highlighting the importance of their conservation as biodiversity refuges for lichens and consequently other flora and fauna groups. Therefore, epiphytic lichens in salt flats can be used as model organisms to assess their conservation in tropical areas. Full article

This study provides a comprehensive overview of Phase I of the deforestation dryland alert system. It focuses on its operation and outcomes from 2020 to 2022 in the Caatinga biome, a unique Brazilian dryland ecosystem. The primary objectives were to analyze deforestation dynamics, identify areas with highest deforestation rates, and determine regions that require prioritization for anti-deforestation efforts and conservation actions. The research methodology involved utilizing remote sensing data, including Landsat imagery, processed through the Google Earth Engine platform. The data were analyzed using spectral unmixing, adjusted Normalized Difference Fraction Index, and harmonic time series models to generate monthly deforestation alerts. The findings reveal a significant increase in deforestation alerts and deforested areas over the study period, with a 148% rise in alerts from 2020 to 2022. The Caatinga biome was identified as the second highest in detected deforestation alerts in Brazil in 2022, accounting for 18.4% of total alerts. Hexagonal assessments illustrate diverse vegetation cover and alert distribution, enabling targeted conservation efforts. The Bivariate Choropleth Map demonstrates the nuanced relationship between alert and vegetation cover, guiding prioritization for deforestation control and native vegetation restoration. The analysis also highlighted the spatial heterogeneity of deforestation, with most deforestation events occurring in small patches, averaging 10.9 ha. The study concludes that while the dryland alert system (SAD-Caatinga—Phase I) has effectively detected deforestation, ongoing challenges such as cloud cover, seasonality, and more frequent and precise monitoring persist. The implementation of DDAS plays a critical role in sustainable forestry by enabling the prompt detection of deforestation, which supports targeted interventions, helps contain the process, and provides decision makers with early insights to distinguish between legal and illegal practices. These capabilities inform decision-making processes and promote sustainable forest management in dryland ecosystems. Future improvements, including using higher-resolution imagery and artificial intelligence for validation, are essential to detect smaller deforestation alerts, reduce manual efforts, and support sustainable dryland management in the Caatinga biome. Full article

We present a molecular phylogeny for the subtribe Ecliptinae (Asteraceae, Heliantheae) based on three plastid (matK, psbA-trnH, and trnQ-rps16) and two nuclear (nrITS and nrETS) markers. The results of the phylogenetic reconstruction were utilised as a topological constraint for a subsequent divergence dating analysis and ancestral range reconstructions. We sampled 41 species and 40 genera (72%) of Ecliptinae and two species of Montanoa (as outgroups) to elucidate the generic relationships between the genera of this subtribe. The Bayesian inference (BI) and Maximum Likelihood (ML) analyses were performed for the combined molecular dataset. The divergence dating analysis was performed using a relaxed, uncorrelated molecular clock with BEAST v1.8.4 and calibrated using a single secondary calibration point from a recently published chronogram for the family. The ancestral range reconstructions focusing on continents (i.e., South America, North America, Africa, Asia, and Oceania) and biomes (Dry forests, Altitudinal grasslands, Savannas, and Rainforests) were performed on BioGeoBEARS. Our phylogenetic results indicate that the genera of Ecliptinae are grouped into five clades, informally named the Monactis, Oblivia, Blainvillea, Wedelia, and Melanthera clades. The most recent, common ancestor of Ecliptinae was widespread in the North and South American dry forests at 8.16 Ma and mainly radiated in these regions up to the Pleistocene. At least eight dispersal events to South America and four dispersal events from North America to Africa, Asia, and Oceania took place during this period in all five informal clades of Ecliptinae. At least 13 biome shifts from dry forests to rainforests were evidenced, in addition to ten biome shifts from dry forests to altitudinal grasslands and savannas. These results corroborate the mid-late Miocene to early Pleistocene radiation of Ecliptinae in tropical dry forests. Future studies should aim to sample the remaining 14 unsampled genera of Ecliptinae to position them in one of the five informal clades proposed in this study. Full article

The ecotone zone, located between the Cerrado and Amazon biomes, has been under intensive anthropogenic pressures due to the expansion of commodity agriculture and extensive cattle ranching. This has led to habitat loss, reducing biodiversity, depleting biomass, and increasing CO₂ emissions. In this study, we employed an artificial neural network, field data, and remote sensing techniques to develop a model for estimating biomass in the remaining native vegetation within an 18,864 km² ecotone region between the Amazon and Cerrado biomes in the state of Mato Grosso, Brazil. We utilized field data from a plant ecology laboratory and vegetation indices from Sentinel-2 satellite imagery and trained artificial neural networks to estimate aboveground biomass (AGB) in the study area. The optimal network was chosen based on graphical analysis, mean estimation errors, and correlation coefficients. We validated our chosen network using both a Student’s t-test and the aggregated difference. Our results using an artificial neural network, in combination with vegetation indices such as AFRI (Aerosol Free Vegetation Index), EVI (Enhanced Vegetation Index), and GNDVI (Green Normalized Difference Vegetation Index), which show an accurate estimation of aboveground forest biomass (Root Mean Square Error (RMSE) of 15.92%), can bolster efforts to assess biomass and carbon stocks. Our study results can support the definition of environmental conservation priorities and help set parameters for payment for ecosystem services in environmentally sensitive tropical regions. Full article

Tropical forests are incredibly diverse in structure and function. Despite, or perhaps because of, this diversity, tropical biologists often conduct research exclusively in one or perhaps a few forest types. Rarely do we study the ecotone—the interstitial region between forest types. Ecotones are hyper-diverse, dynamic systems that control the flow of energy and organisms between adjacent ecosystems, with their locations determined by species’ physiological limits. In this review, we describe how studying ecotones can provide key indicators for monitoring the state of Neotropical forests from organisms to ecosystems. We first describe how ecotones have been studied in the past and summarize our current understanding of tropical ecotones. Next, we provide three example lines of research focusing on the ecological and evolutionary dynamics of the ecotone between tropical dry forests and desert; between tropical dry and rainforests; and between Cerrado and Atlantic rainforests, with the latter being a particularly well-studied ecotone. Lastly, we outline methods and tools for studying ecotones that combine remote sensing, new statistical techniques, and field-based forest dynamics plot data, among others, for understanding these important systems. Full article

The climate and soil properties are major determinants of plant growth and forest community assembly across diverse biomes. However, the contribution of climate and soil on species diversity in tropical and subtropical forests remains controversial. Therefore, this study aims to evaluate the effects of soil and climate on tree species richness using survey data across 495 tropical and subtropical forest plots in Southern China. The selected predictors were categorized as local plot characteristics, climate, and soil factors, and their relationship with tree species richness was modeled using negative binomial generalized linear models. The results revealed that the considering of the interaction between climate and soil properties considerably improved the goodness−of−fit of these models. The individual effects of climate and soil factors had weak relationships with species richness, accounting for 3.61% and 5.77% of the overall 58.9% explained variance in species richness, respectively. Instead, the interaction between climate and soil properties explained most of the statistical variation in tree species richness (84.34% of the overall 58.9% explained variance). The results highlight the importance of soil and climate interactions on tree diversity in tropical and subtropical mature natural forests and their incorporation into biodiversity assessment models to enhance the prediction of community change and responses to climate change. Full article

This study develops a structure for mapping native vegetation in a transition area between the Brazilian Cerrado and the Atlantic Forest from integrated spatial information of Sentinel-1 and Sentinel-2 satellites. Most studies use integrated data to improve classification accuracy in adverse atmospheric conditions, in which optical data have many errors. However, this method can also improve classifications carried out in landscapes with favorable atmospheric conditions. The use of Sentinel-1 and Sentinel-2 data can increase the accuracy of mapping algorithms and facilitate visual interpretation during sampling by providing more parameters that can be explored to differentiate land use classes with complementary information, such as spectral, backscattering, polarimetry, and interferometry. The study area comprises the Lobo Reservoir Hydrographic Basin, which is part of an environmental conservation unit protected by Brazilian law and with significant human development. LULC were classified using the random forest deep learning algorithm. The classifying attributes were backscatter coefficients, polarimetric decomposition, and interferometric coherence for radar data (Sentinel-1), and optical spectral data, comprising bands in the red edge, near-infrared, and shortwave infrared (Sentinel-2). The attributes were evaluated in three settings: SAR and optical data in separately settings (C1 and C2, respectively) and in an integrated setting (C3). The study found greater accuracy for C3 (96.54%), an improvement of nearly 2% compared to C2 (94.78%) and more than 40% in relation to C1 (55.73%). The classification algorithm encountered significant challenges in identifying wetlands in C1, but performance improved in C3, enhancing differentiation by stratifying a greater number of classes during training and facilitating visual interpretation during sampling. Accordingly, the integrated use of SAR and optical data can improve LULC mapping in tropical regions where occurs biomes interface, as in the transitional Brazilian Cerrado and Atlantic Forest. Full article

The 204-million-hectare Brazilian tropical savanna (Cerrado biome), located in the central part of Brazil, constitutes the main region of food and natural fiber production in the country. An important part of this production is based on center pivot irrigation. Existing studies evaluating the spatio-temporal dynamics of center pivots in Brazil do not consider their retraction. This study aimed to evaluate the expansion and retraction of center pivots in the Cerrado biome in the period 1985–2020. We relied on the data produced by the MapBiomas Irriga project. In this period, the area occupied by center pivots increased from 47 thousand hectares in 1985 to 1.2 million hectares in 2020, mostly concentrated in the states of Minas Gerais, Goiás, São Paulo, and Bahia, confirming previous reports available in the literature. Among the 13 irrigation poles recognized by the National Water Agency (ANA), the Oeste Baiano (Bahia State) and the São Marcos (Goiás State) presented the largest areas of center pivots (173,048 ha and 101,725 ha, respectively). We also found that 76% of the center pivots are concentrated in the regions with low water availability (0.01–0.45 mm day⁻¹). Within this 16-year period (2005–2020), more than 10% of center pivots found in 2005 were either abandoned or converted into rain-fed crop production. The results of this study can provide an important foundation for public policies directed toward the sustainable use of water resources by different consumers. Full article

This study examines the importance of cupuassu, a tropical fruit native to the Amazon, to Brazil’s biodiversity, the Amazon biome, and its potential for economic development. Cupuassu is a Non-Timber Forest Product and a fruit of the Theobroma genus, which also includes cocoa. Just in the state of Pará alone, cupuassu production in 2019 was over 4100 t with a gross value of 2.6 million USD produced. However, cupuassu cultivation still needs investment through technological advances to overcome threats such as witches’ broom disease and mycotoxin contamination. Cupuassu fruit is composed of pulp, seeds, and a shell; all these parts have a chemical composition with numerous bioactive compounds, especially the seeds, which also contain stimulant compounds, besides lipids and proteins. The processing of the whole cupuassu fruit has its economic value in the commercialization of the pulp, the extraction of cupuassu butter, and a product called Cupulate^®. However, in this process, the cake resulting from the oil pressing, often considered a waste product, has potential as a source of proteins, peptides, lipids, and bioactive molecules with functional and nutritional properties. Recycling this fruit processing waste can create high-value-added products for various industries and promote a circular economy. Full article

The degree to which Grinnellian and Eltonian niche characteristics influence species distribution may depend on latitude. Tropical regions are environmentally stable and resource-rich, whereas temperate regions are comparatively less environmentally stable (e.g., environmental filtering). Moreover, phylogenetic niche conservatism could influence distributions by inhibiting the ability for species to colonize environmentally different locations. Herein, we examine relationships between niche characteristics, passerine distributions, and phylogenetic niche conservatism across the latitudinal gradient. We used environmental and climatic variables to characterize Grinnellian niches and diets to characterize Eltonian niches. We conducted variation partitioning with retained components from ordination methods to evaluate the degree of association of Grinnellian and Eltonian niche characteristics with passerine distribution across latitudes. We examined the relationship between phylogenetic signal and niche characteristics with a phylogenetic regression. Passerine distributions were more related to environmental gradients than resources across latitudes. While niche conservatism was prevalent in Eltonian niche characteristics, phylogeny was related to Grinnellian niche characteristics in only 46% of biomes. There was no latitudinal gradient in phylogenetic niche conservatism or the degree to which Eltonian and Grinnellian niche characteristics relate to passerine distribution. Niche conservatism, albeit weak, was present for Grinnellian niche characteristics, thus potentially influencing the expansion of passerine distributions into the northern hemisphere. Full article

Phellinotus (Polyporales) is a common genus of wood-decay fungi in tropical and subtropical areas, endemic to the Seasonally Dry Tropical Forest (SDTF) biome. However, Phellinotus diversity remains unexplored, despite being a major threat to living trees. Therefore, this study is aimed at confirming and characterizing through morphological and molecular data the first isolates of Phellinotus teixeirae in Pithecellobium dulce (Fabaceae) trees (locally referred to as ‘Chiminango’) from the endangered Colombian SDTF biome. Fifteen fungal specimens were recovered from living P. dulce trees, in the urban area and at the Universidad del Valle campus, and classified as P. teixeirae based on taxonomical descriptors. Phylogenetic relationships were inferred from a four-loci dataset (ribosomal and gene-coding regions), including 82 taxa covering 3991 nucleotide positions. The analysis recovered seven highly supported (>90% bootstrapping) monophyletic taxa of the ‘Phellinotus Clade’, and confirmed the new distribution range of P. teixeirae (100% bootstrap support), which extends approx. 1000 km north in the Neotropics. Hierarchical stratified Analysis of MOlecular VAriance (AMOVA) provided a clear genetic distinction between species (70% of variation, p-value = 0.001) and low differentiation among country of origin within species (11%, p-value = 0.044). Discriminant Analysis for Principal Components (DAPC) indicated complex clustering including closely related species, probably a signal of recent radiation and weak species boundaries. Median-joining haplotype network analysis identified unique haplotypes, which may correlate with new host colonization and population expansion (Tajima’s D ≤ −0.5). In conclusion, this study provides the first assessment of the genetic diversity of P. teixeirae in a novel geography (SDTP) and host tree (P. dulce). However, increasing the number of isolates remains critical to understand further the genus’ distribution patterns and drivers of genetic diversity. Full article