Search Results (169)

In recent decades, the Brazilian Cerrado has faced rapid land conversion, resulting in the loss of approximately half of its original vegetation cover. Most existing conservation units within the biome are increasingly threatened by the expansion of land use around their boundaries. The establishment of buffer zones with land use regulations may protect biodiversity within these protected areas. In this study, we evaluated and ranked the 10 km buffer zones of 15 national parks (NPs) located in the Cerrado biome, identifying their priority for biodiversity conservation and sustainable land use interventions. The analysis considered the following data: land use and land cover change from 2012 to 2020, extent of natural vegetation fragments, presence or absence of state and municipal conservation units within the buffer zones, and drainage density. Two multicriteria analysis methods, the analytic hierarchy process and the weighted linear combination, were applied to classify the buffer zones into five levels of threat: very high, high, moderate, low, and very low. Among the 15 buffer zones analyzed, 11 were classified as having high to very high priority for conservation actions. The buffer zones surrounding the Serra da Bodoquena, Emas, Canastra, and Brasília NPs were ranked as having very high priority. Between 2012 and 2020, the most severe reductions in ecological connectivity were observed in the buffer zones of Grande Sertão Veredas (44.5%), Nascentes do Rio Parnaíba (40.4%), and Serra das Confusões (36.7%). Given the relatively high proportion of natural vegetation in the buffer zones located in the northern Cerrado, we recommend prioritizing conservation efforts in this region. In contrast, in the southern portion of the biome, where land occupation is more intense, strategies should focus on promoting environmentally sustainable land use practices. Full article

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas. Full article

This study assessed the influence of meteorological conditions on particulate matter (PM) concentrations in Campo Grande, Brazil, from May to December 2021. Using statistical analyses, including Pearson’s correlation coefficient and multivariate regression, we analyzed secondary data on PM2.5 and PM10 concentrations and meteorological variables from the Federal University of Mato Grosso do Sul’s Physics Department. Daily PM concentrations complied with Brazil’s National Ambient Air Quality Standards (PQAr). The PM2.5/PM10 ratios averaged 0.436 (hourly) and 0.442 (daily), indicating a mix of fine and coarse particles. Significant positive correlations were found with temperature, while relative humidity showed a negative correlation, reducing PM levels through deposition. Wind speed had no significant impact. Meteorological influences suggest that air quality management should be tailored to regional conditions, particularly addressing local emission sources like vehicular traffic and biomass burning. Full article

Fire is a key ecological driver in tropical savannas, yet its effects on plant biodiversity remain understudied in Amazonian savannas. This study investigates how fire recurrence influences taxonomic and functional diversity in savanna ecosystems in northeastern Amazonia. We conducted vegetation surveys across five phytophysiognomies in Amapá State, Brazil, and compiled trait data for 226 plant species. Generalized Additive Mixed Models (GAMMs) were used to evaluate the relationships between fire frequency and diversity metrics across five landscape scales. The results showed that taxonomic diversity—particularly Shannon diversity—exhibited a unimodal response to fire recurrence, with peak diversity occurring at intermediate fire frequencies. Abundance increased with fire frequency, indicating potential dominance by fire-tolerant species. Functional diversity responded more subtly: functional richness and dispersion showed weak, non-linear associations with fire, while functional evenness remained stable. These findings suggest that recurrent fire can reduce taxonomic diversity without strongly altering functional structure, possibly due to functional redundancy among species. The use of multiscale models revealed that biodiversity–fire relationships vary with spatial context. In conclusion, this study highlights the moderate resilience of Amazonian savannas to fire recurrence and emphasizes the need to incorporate these ecosystems into fire management plans in climate change scenarios. Full article

The Brazilian savanna, South America’s second-largest biome, is vital to Brazil’s economy but has suffered from environmental degradation due to unregulated agricultural and urban expansion. This study assesses climate change in the biome from 1961 to 2021 using the Köppen climate classification, drought indices, historical trend analyses, and the climatological water balance. Fourteen municipalities across the biome were analyzed. According to the Köppen classification, most municipalities were identified as Aw (tropical with dry winters) and Am (tropical monsoon), with Dourados, MS, and Sapezal, MT, alternating between Am and Aw. The standardized precipitation index (SPI) revealed changes in rainfall distribution. The Mann–Kendall test detected rising air temperatures in 13 of the 14 municipalities, with Sen’s slope ranging from 0.0156 to 0.0605 °C per year. Rainfall decreased in seven municipalities, with decreases from −4.54 to −12.77 mm per year. The climatological water balance supported the observed decrease in precipitation. The results indicated a clear warming trend and declining rainfall in most of the Brazilian savanna, highlighting potential challenges for water availability in the face of ongoing climate change. Full article

High-albedo ground and wall materials are promoted to mitigate heat stress in tropical climates, yet conflicting evidence driven by climatic and metric variability make their impact on Outdoor Thermal Comfort (OTC) unclear. This study employed parametric simulations to assess how ground and wall albedo affect OTC, measured via the Universal Thermal Climate Index (UTCI) in typical urban canyons. Using ENVI-met, we tested ground albedo (0.2–0.8) and wall albedo (0.05–0.90) with emissivity fixed at 0.9. Findings reveal that ground albedo had a minimal impact on the UTCI (mean amplitude 0.44 °C), while wall albedo reduced the UTCI by up to 2.80 °C, prioritizing wall material selection for heat mitigation. It was also found that the increase in ground albedo offsets the cooling potential of high-albedo walls. Furthermore, differences in the impact under shaded and unshaded areas were observed. These results question assumptions of universal high-albedo benefits, recommending case-specific simulations in urban design. Full article

This study presents a global aerosol climatology derived from six years (October 2018–October 2024) of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, using a U-Net Convolutional Neural Network (CNN) machine learning algorithm for Cloud–Aerosol Discrimination (CAD). Despite ICESat-2’s design primarily as an altimetry mission with a single-wavelength, low-power, high-repetition-rate laser, ICESat-2 effectively captures global aerosol distribution patterns and can provide valuable insights to bridge the observational gap between the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) missions to support future spaceborne lidar mission design. The machine learning approach outperforms traditional thresholding methods, particularly in complex conditions of cloud embedded in aerosol, owing to a finer spatiotemporal resolution. Our results show that annually, between 60°S and 60°N, 78.4%, 17.0%, and 4.5% of aerosols are located within the 0–2 km, 2–4 km, and 4–6 km altitude ranges, respectively. Regional analyses cover the Arabian Sea (ARS), Arabian Peninsula (ARP), South Asia (SAS), East Asia (EAS), Southeast Asia (SEA), the Americas, and tropical oceans. Vertical aerosol structures reveal strong trans-Atlantic dust transport from the Sahara in summer and biomass burning smoke transport from the Savanna during dry seasons. Marine aerosol belts are most prominent in the tropics, contrasting with earlier reports of the Southern Ocean maxima. This work highlights the importance of vertical aerosol distributions needed for more accurate quantification of the aerosol–cloud interaction influence on radiative forcing for improving global climate models. Full article

The Cerrado, the world’s most diverse savanna, has several adaptations to fire. However, intense and frequent fires, especially after frosts, can severely impact this ecosystem. Despite this, few studies have evaluated the combined effects of frost followed by fire. We investigated how these disturbances affect plant traits, floral resources, floral visitor richness, and the structures of plant–pollinator interaction networks by using Byrsonima intermedia, a common Malpighiaceae shrub, as a model. We compared areas affected by frost alone and frost followed by fire and the same fire-affected area two years later. We examined pollen, oil volume, buds, and racemes and recorded floral visitors. Our main hypothesis was that fire-affected areas would exhibit higher floral visitor richness, more conspicuous plant traits, and greater fruit production than areas affected by frost only, which would show higher interaction generalization due to stronger negative impacts. The results confirmed that frost drastically reduced floral traits, visitor richness, and reproductive success. In contrast, fire facilitated faster recovery, triggering increased floral resource quantities, richer pollinator communities, more specialized interactions, and greater fruit production. Our findings highlight that fire, despite its impact, promotes faster ecosystem recovery compared to frost, reinforcing its ecological role in the Cerrado’s resilience. Full article

The Cerrado-Amazon Transition (CAT) in Brazil represents one of the most ecologically complex and dynamic tropical ecotones globally; however, it remains insufficiently characterized at high spatial resolution, primarily due to its intricate vegetation mosaics and the limited availability of reliable ground reference data. Accurate land cover maps are urgently needed to support conservation and sustainable land-use planning in this frontier region, especially for distinguishing critical vegetation types such as Amazon rainforest, Cerradão (dense woodland), and Savanna. In this study, we produce the first high-resolution land cover map of the CAT by integrating PlanetScope optical imagery, Sentinel-2 multispectral data, and Sentinel-1 SAR data within a U-net deep learning framework. This data fusion approach enables improved discrimination of ecologically similar vegetation types across heterogeneous landscapes. We systematically compare classification performance across single-sensor and fused datasets, demonstrating that multi-source fusion significantly outperforms single-source inputs. The highest overall accuracy was achieved using the fusion of PlanetScope, Sentinel-2, and Sentinel-1 (F1 = 0.85). Class-wise F1 scores for the best-performing model were 0.91 for Amazon Forest, 0.76 for Cerradão, and 0.76 for Savanna, indicating robust model performance in distinguishing ecologically important vegetation types. According to the best-performing model, 50.3% of the study area remains covered by natural vegetation. Cerradão, although ecologically important, covers only 8.4% of the landscape and appears highly fragmented, underscoring its vulnerability. These findings highlight the power of deep learning and multi-sensor integration for fine-scale land cover mapping in complex tropical ecotones and provide a critical spatial baseline for monitoring ecological changes in the CAT region. Full article

Understanding the seasonal regulation of transpiration and stomatal conductance is critical for evaluating plant water-use strategies in response to environmental variability. This study assessed these physiological traits in three dominant savanna tree species (Piliostigma thonningii (Schumach.) Milne-Redh., Combretum molle R.Br. ex G.Don, and Balanites aegyptiaca (L.) Delile) in Ruma National Park, Kenya. Measurements were taken during wet and dry seasons under varying canopy light conditions (light-exposed vs. shaded leaves) and soil moisture regimes. A randomized design with four treatments and three replicates was employed. Results showed significantly higher transpiration and stomatal conductance during wet seasons, especially in sunlit leaves (p < 0.05). P. thonningii exhibited the highest rates of transpiration (9 mmol m⁻² s⁻¹) and stomatal conductance (~2.2 mmol m⁻² s⁻¹) in light conditions, while B. aegyptiaca maintained consistently low values, reflecting a drought-tolerant strategy. C. molle demonstrated intermediate responses, suggesting a balance between water conservation and resource use. Despite seasonal trends, low R² values indicated that internal physiological regulation outweighed the influence of external climatic drivers. These findings reveal species-specific water-use strategies and highlight the ecological significance of leaf-level responses to light and moisture availability in tropical savannas. The study provides valuable insights for forest management and climate-resilient restoration planning in water-limited ecosystems. Full article

We evaluated the effects of different fire regimes on the ground-ant community from a savanna (Cerrado) reserve in southern Brazil, where a process of woody encroachment has been taking place. Ants are a dominant faunal group in tropical savannas. Over ~8 years, experimental plots were protected from fire or burned every one or two years. An additional treatment (adaptive) included annual fires and a reduction in woody biomass to increase fuel loads. Ants were collected prior to the first prescribed fire and again four times. We expected that fire would increase the diversity and overall abundance of open-savanna ant specialists, depending on the extent of changes in vegetation structure. Changes in litter depth, grass cover and bare ground in burned plots were most evident 88 months after the first fire and did not differ between fire regimes. Similarly, overall ant species richness and occurrence neither differed between fire treatments nor from the control. However, burned plots showed a significant increase in the richness and occurrence of open savanna specialists, and a decrease in species most typical of dense savanna or dry forests. As ant responses did not differ between the annual, biennial, and adaptive treatments, we suggest that a fire return interval of two years is enough for reverting the loss of open savanna ant specialists in areas that have been protected from fire for decades. Full article

Pre-rain green-up is a distinctive phenological phenomenon observed in arid and semi-arid regions, featuring the sprouting of plants before the onset of the rainy season. This phenomenon indicates the intricate controls of vegetation phenology other than precipitation, yet its global distribution patterns and underlying causes remain unclear. In this study, we used remotely sensed phenology and rainfall data to map the global distribution of pre-rain green-up vegetation for the first time in arid and semi-arid savanna areas. The results revealed that over one-third of pre-rain green-up vegetation is in mountainous regions. Furthermore, to explore the potential effect of groundwater accessibility on pre-rain green-up, we employed high-resolution imagery to quantify phenological parameters and analyzed the relationship between pre-rain green-up and elevation at the watershed scale in a typical mountainous pre-rain green-up region in Africa. We found that within the pre-rain green-up area, 60.64% of sub-watersheds show a significant negative correlation (p < 0.05) between the start of the season (SOS) and elevation, indicating that the SOS occurs earlier at higher elevations despite the complex spatial variability overall. Our study provides a global picture of the pre-rain green-up phenomenon in tropical drylands and suggests that tree internal water regulation mechanisms rather than groundwater accessibility control the pre-rain green-up. Full article

Regional mapping of Above Ground Biomass Density (AGBD) using Remote Sensing data has shown high accuracy but lacks replicability at a global scale. In contrast, global models capture AGBD variability across biomes but struggle with biome-specific accuracy. To address this gap, we develop and assess the performance of a Deep Learning model for mapping AGBD at 10-m resolution using multi-source satellite data (Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI) across four biomes: Mediterranean, taiga (boreal forests), tropical rainforests, and semi-arid savannas. The model is trained and validated separately for each biome, yielding four regional models with normalized RMSEs of 0.43–0.67 and correlation coefficients (r) of 0.61–0.77 against forest inventories. We compare predictions from these models to a benchmark dataset and to a model trained on all four biomes combined. The regional models consistently outperform both, achieving better metrics than the benchmark. Additionally, an analysis of prediction drivers reveals biome-specific differences, reinforcing the importance of per-biome mapping approaches. This study highlights the advantages and limitations of regional against global modeling, creating the basis for biome-specific, replicable, scalable and multi-temporal AGBD mapping. Full article

Apomictic populations, which produce seeds with embryos without proper sexual syngamy, often show low genetic diversity, but eventually, such diversity has been reported to be surprisingly high. We studied here the genetic diversity in agamic complexes of Eriotheca crenulata (comb. n. E. gracilipes), E. pubescens (Malvaceae-Bombacoideae), and Handroanthus ochraceus (Bignoniaceae), tropical tree species from the savannas in Central Brazil. We evaluated the genetic diversity and structure of self-fertile polyploid sporophytic apomicts versus self-sterile diploid or tetraploid sexual populations by using dominant ISSR markers. Genetic diversity was either similar or even higher in apomictic populations of E. crenulata and E. pubescens, but the opposite was observed in some populations of H. ochraceus. Only two individuals of E. pubescens showed identical ISSR profiles, so strict clonality in adult individuals was very rare among the studied trees. The genetic variability was notably higher within populations than among populations of H. ochraceus and very similar among and within populations of Eriotheca species. Ordination, clustering, and Bayesian analyses showed a clear distinction between populations of Eriotheca species with different breeding systems. But for H. ochraceus, a sexual population was actually grouped with the apomictics. As in other studies, eventual sexual and recombination events seem to increase genetic diversity in apomictic populations. This may explain the similar genetic diversity among apomictic and sexual populations in the studied agamic complexes and the virtual absence of strict clonal individuals. The results have evolutionary and ecological consequences for the threatened Neotropical savanna trees. Full article

The Urban Heat Island’s (UHI) effect intensifies thermal discomfort for urban communities, increasing energy requirements. This study assesses the incorporation of Phase Change Materials (PCMs) into building envelopes to reduce Urban Heat Island (UHI) impacts in the Trichy urban area, characterised by a dry-summer tropical savanna environment. To evaluate energy efficiency and indoor temperature regulation, simulations were conducted using Design Builder and Climate 6.0 software. The results show that overall room electricity consumption decreased from 480 kWh to 380 kWh, demonstrating the energy-saving benefits of the modifications. Overall energy consumption was reduced to 271.9 kWh/m²/year from 312.23 kWh/m²/year in the base case, a 13% decrease, equating to 40.33 kWh/m²/year in energy savings. The payback period for PCM installation was predicted to be around 30.64 years. These results show that PCM-enhanced building envelopes reduce UHI effects and improve thermal comfort and energy efficiency, making them a feasible, sustainable urban development strategy. Full article