Mato Grosso State University

Objective: To analyze the reframing of the concept of Health Promotion by nursing professors. Method: Action research, combined with Lev Vygotsky’s historical-cultural approach, developed with professors from the undergraduate Nursing course at a state university, in 2023. Data was produced during an extension course, recording and transcribing the discussions that took place in five meetings on the topic. Thematic analysis led to four themes: The concept of Health Promotion: reframing meanings; Contradictions between HP teaching and nursing practices in the service; Teaching Health Promotion in graduation; Perception of participants regarding their own transformation. Results: At first, health promotion was understood as synonymous with prevention and specific health actions. During discussions, the redefinition of the concept of health promotion was demonstrated by presenting elements of the concept, such as principles and guidelines, as well as discussions about the presence of behavioral and critical pedagogy models in health promotion. Conclusion: Reframing implies the need for reviewing, reorganizing, and transforming of teaching based on the appropriation of the concept of health promotion, with the use of innovative teaching methodologies and strategies, allowing progress in the undergraduate Nursing course. Descriptors: Health promotion; Health education; Redefinition; Nursing education; Nursing faculty

Objective: To analyze the reframing of the concept of Health Promotion by nursing professors. Method: Action research, combined with Lev Vygotsky’s historical-cultural approach, developed with professors from the undergraduate Nursing course at a state university, in 2023. Data was produced during an extension course, recording and transcribing the discussions that took place in five meetings on the topic. Thematic analysis led to four themes: The concept of Health Promotion: reframing meanings; Contradictions between HP teaching and nursing practices in the service; Teaching Health Promotion in graduation; Perception of participants regarding their own transformation. Results: At first, health promotion was understood as synonymous with prevention and specific health actions. During discussions, the redefinition of the concept of health promotion was demonstrated by presenting elements of the concept, such as principles and guidelines, as well as discussions about the presence of behavioral and critical pedagogy models in health promotion. Conclusion: Reframing implies the need for reviewing, reorganizing, and transforming of teaching based on the appropriation of the concept of health promotion, with the use of innovative teaching methodologies and strategies, allowing progress in the undergraduate Nursing course. Descriptors: Health promotion; Health education; Redefinition; Nursing education; Nursing faculty

Background Camera trapping associated with capture–recapture models is commonly used to estimate wild felid population density, relying on three main frameworks: spatially explicit capture–recapture (SECR) and two non‐spatial approaches (CR‐MMDM and CR‐hMMDM). Methodological differences, inappropriate sampling designs, and/or insufficient data explain some estimate variability, but the biological factors underpinning this remain undetermined. Prey availability, habitat suitability, and body size may all interact and influence carnivoran population size and density. Aims We aimed to (1) survey ocelot population density data and summarise information on study designs, methodological approaches, and results, (2) evaluate the relationships between them, (3) disentangle methodological and ecological effects on population density estimates, and (4) provide guidance to improve study design and reporting. Materials & Methods Our systematic review discovered 51 studies reporting 228 ocelot population density estimates from 65 sites across 13 countries. We collated ocelot body mass data (BM) and used forest canopy height (GFCH) as a surrogate for habitat suitability, as well as gross primary productivity seasonality (GPP variation) as a proxy for prey availability. Using a meta‐analytical framework, we created models to (1) determine mean ocelot population density in the Neotropics and to assess the effects of (2) methodological and (3) ecological variables on population density estimates. Results Mean population density was 20.3/100 km ² , with significant differences among methods. SECR and CR‐MMDM yielded comparable estimates (16.6/100 km ² and 18.9/100 km ² , respectively), while CR‐hMMDM produced higher estimates (27.3/100 km ² ). We found significant positive and negative effects of GFCH and BM, respectively, and a marginally significant negative effect of GPP variation on estimates. Discussion Ocelots thrive in forests with higher canopies, but their population density is limited by local habitat seasonality. Morphological differences further influence variation, with small‐bodied populations attaining higher population densities under similar ecological conditions. Conclusion Based on our findings, we provide guidelines to enhance the accuracy and standardization of study designs, methodological approaches, and general reporting. Improving these aspects will strengthen the comparability and reliability of ocelot population density estimates.

Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.

Understanding the capacity of forests to adapt to climate change is of pivotal importance for conservation science, yet this is still widely unknown. This knowledge gap is particularly acute in high-biodiversity tropical forests. Here, we examined how tropical forests of the Americas have shifted community trait composition in recent decades as a response to changes in climate. Based on historical trait-climate relationships, we found that, overall, the studied functional traits show shifts of less than 8% of what would be expected given the observed changes in climate. However, the recruit assemblage shows shifts of 21% relative to climate change expectation. The most diverse forests on Earth are changing in functional trait composition but at a rate that is fundamentally insufficient to track climate change.

We conducted a systematic review to investigate the relationship between aquatic insects and climatic seasonality in the Cerrado biome in Brazil. The review encompassed the number of studies, the spatial distribution of studies across microbasins, the duration of the studies, collection methods, taxonomic resolutions, the most significant environmental predictors for the communities, and the impact of land-use changes on the seasonal variation of aquatic insect communities. We also tested the relationship between climatic seasonality and aquatic insect diversity using a meta-analysis and discussed the potential effects of climate change on these communities. To achieve this, we used a set of keywords related to aquatic insects and climatic seasonality in the Cerrado biome to search Scopus and Web of Science databases. Our main findings indicate that the collection methods are robust and well-established, and taxonomic resolutions are generally good. However, the number of streams and the duration of sampling are often inadequate for addressing ecological questions in most studies. Additionally, the spatial distribution of studies is concentrated around areas close to universities. Finally, it was evident that the richness and abundance of aquatic insects are higher during the dry season. These results indicate ways to improve studies with temporal questions using aquatic insect communities in the Cerrado and raise awareness about the potential issues caused by climate change. Changes in precipitation patterns and temperature are expected to transform some of the currently perennial streams into intermittent ones, thereby homogenizing aquatic insect communities and negatively impacting their potential to provide ecosystem services.

Tropical forest canopies are the biosphere’s most concentrated atmospheric interface for carbon, water and energy1,2. However, in most Earth System Models, the diverse and heterogeneous tropical forest biome is represented as a largely uniform ecosystem with either a singular or a small number of fixed canopy ecophysiological properties³. This situation arises, in part, from a lack of understanding about how and why the functional properties of tropical forest canopies vary geographically⁴. Here, by combining field-collected data from more than 1,800 vegetation plots and tree traits with satellite remote-sensing, terrain, climate and soil data, we predict variation across 13 morphological, structural and chemical functional traits of trees, and use this to compute and map the functional diversity of tropical forests. Our findings reveal that the tropical Americas, Africa and Asia tend to occupy different portions of the total functional trait space available across tropical forests. Tropical American forests are predicted to have 40% greater functional richness than tropical African and Asian forests. Meanwhile, African forests have the highest functional divergence—32% and 7% higher than that of tropical American and Asian forests, respectively. An uncertainty analysis highlights priority regions for further data collection, which would refine and improve these maps. Our predictions represent a ground-based and remotely enabled global analysis of how and why the functional traits of tropical forest canopies vary across space.

Plants cope with the environment by displaying large phenotypic variation. Two spectra of global plant form and function have been identified: a size spectrum from small to tall species with increasing stem tissue density, leaf size, and seed mass; a leaf economics spectrum reflecting slow to fast returns on investments in leaf nutrients and carbon. When species assemble to communities it is assumed that these spectra are filtered by the environment to produce community level functional composition. It is unknown what are the main drivers for community functional composition in a large area such as Amazonia. We use 13 functional traits, including wood density, seed mass, leaf characteristics, breeding system, nectar production, fruit type, and root characteristics of 812 tree genera (5211 species), and find that they describe two main axes found at the global scale. At community level, the first axis captures not only the ‘fast-slow spectrum’, but also most size-related traits. Climate and disturbance explain a minor part of this variance compared to soil fertility. Forests on poor soils differ largely in terms of trait values from those on rich soils. Trait composition and soil fertility exert a strong influence on forest functioning: biomass and relative biomass production.

Identifying suitable habitats for riparian tree colonization is important for optimizing natural resource management programmes around reservoirs. We investigated the floristic relationships among riparian ecosystems associated with hydroelectric dams constructed in the Brazilian Amazon and selected predictors of biodiversity variation in these ecosystems. We addressed the following questions: (1) How are ecosystems in the Brazilian Amazon affected by hydroelectric dams related floristically? and (2) How do large- and small-scale environmental variations affect tree composition and richness? We accessed floristic data from 62 sites in areas influenced by hydroelectric dams, collected after the start of their operation, for which we obtained data on climatic, topographic and edaphic variables, and distance from the nearest water course. We found that the floristic variation among different ecosystems in the Amazon basin affected by hydroelectric dams is conditioned by the synergistic action of environmental predictors and spatial filters. The composition and richness of tree species are strongly predicted by edaphic and topographic gradients, especially by elevation and slope of the terrain, in addition to intrinsic hydrological characteristics of dams. Although they are crucial for survival and serve as reservoirs of species that must be preserved along rivers, hills and slopes are exposed to deforestation, geological instability and soil erosion, making it necessary to carry out complementary studies that will help predict the potential risk of species loss in these environments.

Motivation The accelerated and widespread conversion of once continuous ecosystems into fragmented landscapes has driven ecological research to understand the response of biodiversity to local (fragment size) and landscape (forest cover and fragmentation) changes. This information has important theoretical and applied implications, but is still far from complete. We compiled the most comprehensive and updated database to investigate how these local and landscape changes determine species composition, abundance and trait diversity of multiple taxonomic groups in forest fragments across the globe. Main Types of Variables Contained We gathered data for 1472 forest fragments, providing information on the abundance and composition of 9154 species belonging to vertebrates, invertebrates, and plants. For 2703 of these species, we obtained more than 20 functional traits. We provided the spatial location and size of each fragment and metrics of landscape composition and configuration. Spatial Location and Grain The dataset includes 1472 forest fragments sampled in 121 studies from all continents except Antarctica. Most datasets (77%) are from tropical regions, 17% are from temperate regions, and 6% are from subtropical regions. Species abundance and composition were collected at the plot or fragment scale, whereas the landscape metrics were extracted with buffer size ranging from a radius of 200–2000 m. Time Period and Grain Data on the abundance of species and community composition were collected between 1994 and 2022, and the landscape metrics were extracted from the same year that a given study collected the abundance and composition data. Major Taxa and Level of Measurement The studied organisms included invertebrates (Arachnida, Insecta and Gastropoda; 41% of the datasets), vertebrates (Amphibia, Squamata, Aves and Mammalia; 44%), and vascular plants (19%), and the lowest level of identification was species or morphospecies. Software Format The dataset and code can be downloaded on Zenodo or GitHub.

Soybean stands out for being the most economically important oilseed in the world. Remote sensing techniques and precision agriculture are being analyzed through research in different agricultural regions as a technological system aiming at productivity and possible low-cost reduction. Machine learning (ML) methods, together with the advent of demand for remotely piloted aircraft available on the market in the recent decade, have been conducive to remote sensing data processes. The objective of this work was to evaluate the best ML and input configurations in the classification of agronomic variables in different phenological stages. The spectral variables were obtained in three phenological stages of soybean genotypes: V8 (at 45 days after emergence—DAE), R1 (60 DAE), and R5 (80 DAE). A Sensefly eBee fixed-wing RPA equipped with the Parrot Sequoia multispectral sensor coupled to the RGB sensor was used. The Sequoia multispectral sensor with an RGB sensor acquired reflectance at wavelengths of blue (450 nm), green (550 nm), red (660 nm), near-infrared (735 nm), and infrared (790 nm). The following were used to evaluate the agronomic traits: days to maturity, number of branches, productivity, plant height, height of the first pod insertion and diameter of the main stem. The random forest (RF) model showed greater accuracy with data collected in the R5 stage, whose accuracies were close to 56 for the percentage of correct classifications (CC), close to 0.2 for Kappa, and above 0.55 for the F-score. Logistic regression (RL) and support vector machine (SVM) models showed better performance in the early reproductive stage R1, with accuracies above 55 for CC, close to 0.1 for Kappa, and close to 0.4 for the F-score. J48 performed better with data from the V8 stage, with accuracies above 50 for CC and close to 0.4 for the F-score. This reinforces that the use of different specific spectra for each model can enhance accuracy, optimizing the choice of model according to the phenological stage of the plants.

Global climate change is closely tied to CO2 emissions, and implementing conservation-agricultural systems can help mitigate emissions in the Amazon. By maintaining forest cover and integrating sustainable agricultural practices in pasture, these systems help mitigate climate change and preserve the carbon stocks in Amazon forest soils. In addition, these systems improve soil health, microclimate regulation, and promote sustainable agricultural practices in the Amazon region. This study aimed to evaluate the CO2 emission dynamics and its relationship with soil attributes under different uses in the Amazon. The experiment consisted of four treatments (Degraded Pasture—DP; Managed Pasture—MP; Native Forest—NF; and Livestock Forest Integration—LF), with 25 replications. Soil CO2 emission (FCO2), soil temperature, and soil moisture were evaluated over a period of 114 days, and the chemical, physical, and biological attributes of the soil were measured at the end of this period. The mean FCO2 reached values of 4.44, 3.88, 3.80, and 3.14 µmol m⁻² s⁻¹ in DP, MP, NF, and LF, respectively. In addition to the direct relationship between soil CO2 emissions and soil temperature for all land uses, soil bulk density indirectly influenced emissions in NF. The amount of humic acid induced the highest emission in DP. Soil organic carbon and carbon stock were higher in MP and LF. These values demonstrate that FCO2 was influenced by the Amazon land uses and highlight LF as a low CO2 emission system with a higher potential for carbon stock in the soil.

Objectiveto develop a socioemotional competency matrix proposal for undergraduate nursing students. Methodthis exploratory, descriptive study used a qualitative approach. Fifty-seven nursing students from a public higher education institution participated. Data were collected through focus groups and analyzed using inductive thematic analysis. Resultssix socioemotional competencies were identified: Assertive Communication, Receptivity, Adaptability, Teamwork, Emotional Intelligence, and Shared Leadership. Additionally, recognizing associated behaviors/attitudes enabled the construction of the matrix. Strategies for competency development were mentioned, such as teacher support, participation in academic leagues, research projects, and workshops as initiatives from graduate programs. Conclusionthe socio-emotional competency matrix for nursing students should assist health care managers and training centers in designing competency-based educational projects.

Objetivo crear una propuesta de matriz de competencias socioemocionales para estudiantes de grado en enfermería. Método estudio exploratorio, descriptivo con enfoque cualitativo. Participaron 57 estudiantes de enfermería de una Institución de Educación Superior pública. Se utilizó la técnica de grupo focal y para la interpretación de los datos se utilizó el análisis temático inductivo. Resultados se identificaron seis competencias socioemocionales: Comunicación Asertiva; Receptividad; Adaptabilidad; Trabajo en equipo; Inteligencia Emocional y Liderazgo Compartido. Además, el reconocimiento de comportamientos/actitudes asociados permitió crear una matriz. Se mencionaron estrategias para desarrollar las competencias, tales como: recepción de los docentes, participar en ligas académicas, proyectos de investigación y talleres como iniciativas de posgrado. Conclusión la matriz de competencias socioemocionales para estudiantes de enfermería debe ayudar a los gestores de salud y a las instituciones de formación a desarrollar proyectos pedagógicos orientados a la formación basada en competencias.

Objetivo construir uma proposta de matriz de competências socioemocionais para discentes de graduação em enfermagem. Método estudo exploratório, descritivo com abordagem qualitativa. Participaram 57 discentes de enfermagem de uma Instituição de Ensino Superior pública. Utilizou-se a técnica de grupo focal e para interpretação dos dados, a análise temática indutiva. Resultados seis competências socioemocionais foram identificadas: Comunicação Assertiva; Receptividade; Adaptabilidade; Trabalho em Equipe; Inteligência Emocional e Liderança Compartilhada. Além disso, o reconhecimento de comportamentos/atitudes associados tornou possível construir uma matriz. Estratégias para o desenvolvimento das competências foram citadas, como: acolhimento dos docentes, participação em ligas acadêmicas, projetos de pesquisa e oficinas como iniciativas da pós-graduação. Conclusão a matriz de competências socioemocionais para discentes de enfermagem deve auxiliar gestores de saúde e centros formadores na elaboração de projetos pedagógicos orientados para formação baseada em competências.

Understanding how the traits of lineages are related to diversification is key for elucidating the origin of variation in species richness. Here, we test whether traits are related to species richness among lineages of trees from all major biogeographical settings of the lowland wet tropics. We explore whether variation in mortality rate, breeding system and maximum diameter are related to species richness, either directly or via associations with range size, among 463 genera that contain wet tropical forest trees. For Amazonian genera, we also explore whether traits are related to species richness via variation among genera in mean species-level range size. Lineages with higher mortality rates—faster life-history strategies—have larger ranges in all biogeographic settings and have higher mean species-level range sizes in Amazonia. These lineages also have smaller maximum diameters and, in the Americas, contain dioecious species. In turn, lineages with greater overall range size have higher species richness. Our results show that fast life-history strategies influence species richness in all biogeographic settings because lineages with these ecological strategies have greater range sizes. These links suggest that dispersal has been a key process in the evolution of the tropical forest flora.

Foliar application of potassium silicate (K2SiO3) has been demonstrated to be a promising alternative for induced tolerance. We aimed to evaluate the effect of applying K2SiO3 on the nutrition and growth of Genipa americana L. seedlings under two luminous ambiences. Four doses of K2SiO3 via foliar spray were tested: 0.0, 2.5, 5.0, and 10.0 mL L–1, and cultivation under full sun or shade. We observed higher N content in seedlings under the full sun at 45 days and decreased with increased K2SiO3 doses in the same ambience at 90 days, while P, K, Ca, and Mg were higher in shaded seedlings and with 10.0 mL L–1 K2SiO3 at 45 and 90 days. The order of nutritional requirements for most seedlings, regardless of cultivation conditions, was K > N > Ca, with an inversion of Mg to P requirement with 10.0 mL L–1 K2SiO3. Shaded seedlings showed better growth at 45 and 90 days, but K2SiO3 contributed to photoassimilate accumulation under full sun. Foliar application of 5.0 mL L–1 K2SiO3 contributed to greater stem diameter, leaf area, and Dickson quality index. Foliar application of K2SiO3 alleviated the stressful effects of full sun and favored the nutrition and quality of G. americana seedlings.

The objective of this study was to evaluate the effect of a phytogenic additive on nutrient intake, diet digestibility, nitrogen balance, and ruminal parameters of lambs. Four lambs with an average body weight of 27.6 ± 2.9 kg were distributed in a 4 × 4 Latin square design and fed a basal diet composed of 600 g DM/day of corn silage and 400 g DM/day of concentrate. The basal diet was supplemented with no additive 0.0, 2.0, 4.0, and 6.0 g/kg DM of pepper. The intake of DM, crude protein (CP), organic matter (OM), and neutral detergent fiber (NDF) in g/day decreased linearly (P < 0.05). No effects (P > 0.05) were observed for the apparent digestibility of DM, OM, NDF, and ether extract. There was a quadratic effect (P < 0.05) on the digestibility of CP and non-fibrous carbohydrate, with maximum digestibility estimated at 707.7 and 924.8 (g/kg DM) at levels of 2.55 and 0.27 g/kg DM of pepper, respectively. There was no effect (P > 0.05) on urinary nitrogen and retention nitrogen. Increasing levels of pepper did not alter (P > 0.05) the pH value and N-NH3 concentration of the ruminal fluid. However, there was an effect (P < 0.05) of time on the pH and N-NH3 value of the rumen. The inclusion of pepper in the diet of confined lambs negatively alters dry matter and NDF intake without impairing nutrient digestibility, nitrogen utilization, and other ruminal parameters. Keywords capsaicin; digestibility; intake; nitrogen balance; ruminal parameters

Despite the progress in the measurement and accessibility of plant trait information, acquiring sufficiently complete data from enough species to answer broad‐scale questions in plant functional ecology and biogeography remains challenging. A common way to overcome this challenge is by imputation, or ‘gap‐filling' of trait values. This has proven appropriate when focusing on the overall patterns emerging from the database being imputed. However, some applications force the imputation procedure out of its original scope, using imputed values independently from the imputation context, and specific trait values for a given species are used as input for computing new variables. We tested the performance of three widely used imputation methods (Bayesian hierarchical probabilistic matrix factorization, multiple imputation by chained equations with predictive mean matching, and Rphylopars) on a database of tropical tree and shrub traits. By applying a leave‐one‐out procedure, we assessed the accuracy and precision of the imputed values and found that out‐of‐context use of imputed values may bias the estimation of different variables. We also found that low redundancy (i.e. low predictability of a new value on the basis of existing values) in the dataset, not uncommon for empirical datasets, is likely the main cause of low accuracy and precision in the imputed values. We therefore suggest the use of a leave‐one‐out procedure to test the quality of the imputed values before any out‐of‐context application of the imputed values, and make practical recommendations to avoid the misuse of imputation procedures. Furthermore, we recommend not publishing gap‐filled datasets, publishing instead only the empirical data, together with the imputation method applied and the corresponding script to reproduce the imputation. This will help avoid the spread of imputed data, whose accuracy, precision, and source are difficult to assess and track, into the public domain.