https://ri.ufs.br/jspui/handle/riufs/2415 Fri, 10 Jul 2026 21:26:06 GMT 2026-07-10T21:26:06Z http://ri.ufs.br:80/retrieve/ee94124c-6739-452b-a95c-0dd714390336/PPEC.jpg https://ri.ufs.br/jspui/handle/riufs/2415 https://ri.ufs.br/jspui/handle/riufs/25505 Título: Aspectos da ecologia básica do Guigó-da-caatinga (Callicebus Barbarabrownae Hershkovitz, 1990) em fragmentos de Caatinga, Nordeste do Brasil Autor(es): Barreto, Hamilton Ferreira Abstract: The blond titi monkey (C. barbarabrownae), classified as Critically Endangered (CR) by the International Union for Conservation of Nature (IUCN), is the only primate endemic to the Caatinga biome. Despite its high threat status and endemism, there are still significant knowledge gaps regarding the species. With this in mind, this study was developed to expand knowledge about its biology and ecology. The first chapter addresses acoustic ecology, with the main objective of describing the species’ vocalization patterns and their daily, seasonal, and annual variations, in association with resource availability. Over two years (10 days per month), we collected acoustic data using autonomous recorders in two forest fragments of different sizes. We recorded 242 independent vocalization events in 193 samples, 28 in the smaller fragment (7 ha) and 214 in the larger fragment (70 ha). Of these, 81% were recorded in the morning period, with the highest frequency at 08:00. The month with the lowest number of records was October 2021 and the highest was June 2022. Vocalization frequency showed significant differences between morning and afternoon periods, times of day, months of the year, fragments, and seasons. No significant relationship was found between vocalization frequency and the availability of ripe fruits, suggesting that ripe fruits may influence vocalization frequency. The second chapter investigates the structure and composition of trees in fragments where the species occurs, with the main objective of characterizing the habitat in five fragments and examining its relationship with species density in these locations. Data were collected at five sites in the municipalities of Euclides da Cunha, Jacobina, Jeremoabo, and Lamarão (Bahia State), and Monte Alegre de Sergipe (Sergipe State). We sampled 200 trees in five transects per fragment (point-centered quarter method), selecting individuals with diameter at breast height (DBH) > 10 cm. For each tree, we identified the species and measured DBH, tree height (TH), distance to the previous tree (DPT), and crown cover (CC). Fabaceae was the most abundant family in all areas, except in Jacobina, where Myrtaceae predominated. The areas differed in diversity (H’), ranging from 2.27 to 3.35. Significant differences among areas were also found for TH, DPT, and CC, but not for DBH. This study represents the first approach to identifying habitat factors and their relationship with ecological aspects of C. barbarabrownae, highlighting its response to fruit availability as well as its occurrence in structurally heterogeneous yet compositionally more homogeneous areas. Tue, 26 Aug 2025 00:00:00 GMT https://ri.ufs.br/jspui/handle/riufs/25505 2025-08-26T00:00:00Z https://ri.ufs.br/jspui/handle/riufs/25445 Título: A influência da hidratação descontínua de sementes e dos ciclos de rega em mudas no comportamento germinativo e no potencial alelopático de espécies exóticas invasoras da Caatinga Autor(es): Hora, Igor Silva da Abstract: Biological invasion is one of the main causes of biodiversity loss worldwide. Certain characteristics can increase invasiveness, such as the presence of hydration memory in seeds and the allelopathic potential of the plant. This is the ability to release allelochemicals that affect the development of target species in the environment and can be influenced by environmental conditions such as discontinuous seed hydration and irrigation cycles in seedlings. This thesis aims to understand the influence of these environmental conditions on the germination behavior and allelopathic potential of invasive exotic species in the Caatinga biome. In this sense, this work has three chapters, the first of which is dedicated to verifying whether the germination of seeds of the invasive species Neltuma juliflora (Sw.) Raf., Sylva Tellur. var. juliflora is favored in situations of water deficit when subjected to discontinuous hydration. Among the results, I observed that the germination behavior of the species, through the measured parameters, was altered due to the passage through hydration and dehydration (HD) cycles of the seeds. Thus, the species benefits from the hydration memory of the seeds under water deficit conditions during the invasion process, demonstrating an invasive characteristic. In the second and third chapters, I analyzed how the passage through water deficit cycles and irrigation cycles in seedlings of Leucaena leucocephala (Lam.) de Wit (Fabaceae) and N. juliflora influences allelopathy during germination and initial development of a model species (in the laboratory) and a native species (in the laboratory and in a greenhouse), respectively. In the second chapter, I observed that the allelopathy of L. leucocephala was favored by the passage through these previous cycles, while N. juliflora did not show alterations in its allelopathy. Finally, the third chapter showed that, despite the native species being tolerant to allelopathic stresses, extracts of L. leucocephala in laboratory experiments influenced the germination time of the batch, while in the greenhouse, the effects occurred in various ways, such as a decrease in seedling emergence and the length of the roots. This thesis demonstrates that the presence of hydration memory in seeds of N. juliflora and L. leucocephala, when subjected to discontinuous hydration, can be a characteristic of invasiveness. Furthermore, allelopathy is a dynamic process influenced by previous conditions, so its invasive potential can increase in environments that naturally present situations similar to discontinuous hydration and irrigation cycles. Fri, 19 Dec 2025 00:00:00 GMT https://ri.ufs.br/jspui/handle/riufs/25445 2025-12-19T00:00:00Z https://ri.ufs.br/jspui/handle/riufs/25443 Título: Dimensões ecomorfológicas, espaciais e climáticas da ictiofauna da bacia hidrográfica do rio São Francisco: diagnóstico atual e cenários de vulnerabilidade Autor(es): Luduvice, Jefferson Saulo da Vitória Wed, 25 Feb 2026 00:00:00 GMT https://ri.ufs.br/jspui/handle/riufs/25443 2026-02-25T00:00:00Z https://ri.ufs.br/jspui/handle/riufs/25415 Título: A aplicação de modelos de aprendizado de máquina na previsão de acidentes escorpiônicos na amazônia legal Autor(es): Moura, Thais de Andrade Abstract: The incidence of scorpionism emerges as a significant public health issue in tropical and subtropical regions, with the Amazon experiencing a notable increase in cases between 2000 and 2017. Holding 13% of the world's scorpion fauna, this region faces challenges due to climate change and indiscriminate soil use, exerting substantial pressure on biodiversity. This study aimed to integrate scorpion occurrence data, bioclimatic information, land use, and epidemiological data to predict scorpionism incidence in northern Brazil. We collected occurrence and bioclimatic data for four species associated with accidents in distinct endemic areas in the Legal Amazon: Tityus obscurus, T. silvestris, T. metuendus, and T. bastosi. Species distribution models (SDMs) were built using MaxEnt software, and niche overlap among species was analyzed. Scorpionism accident data were obtained from the Notifiable Diseases Information System (SINAN) for the period 2015 to 2022. Additionally, land use data from the LUH2 dataset for present and future scenarios were utilized. The predictive model incorporated SINAN incidence estimates, land use data, climatic information, and climatic suitability derived from SDMs as predictors. The model construction employed Machine Learning algorithms, such as XGBoost and Random Forest, and variable importance was assessed using the SHAP (Shapley Additive exPlanations) method. Results indicate significant challenges for scorpion species in the Amazon due to climate change, with substantial losses of climatically suitable areas for some species. While some species showed a reduction in potential distribution, others, like Tityus silvestris, exhibited an increase. The findings not only highlight the challenges faced by scorpion species in the Amazon but also underscore the potential of Machine Learning techniques in analyzing large datasets. The successful application of algorithms such as XGBoost and Random Forest not only enabled the prediction of scorpionism incidence but also emphasizes the crucial role of these methodologies in fields like ecology, epidemiology, and public health. Fri, 16 Feb 2024 00:00:00 GMT https://ri.ufs.br/jspui/handle/riufs/25415 2024-02-16T00:00:00Z