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Search: WFRF:(Barbosa Fernando) > (2020-2024)

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1.
  • Householder, John Ethan, et al. (author)
  • One sixth of Amazonian tree diversity is dependent on river floodplains
  • 2024
  • In: NATURE ECOLOGY & EVOLUTION. - 2397-334X.
  • Journal article (peer-reviewed)abstract
    • Amazonia's floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region's floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon's tree diversity and its function.
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2.
  • ter Steege, Hans, et al. (author)
  • Mapping density, diversity and species-richness of the Amazon tree flora
  • 2023
  • In: COMMUNICATIONS BIOLOGY. - 2399-3642. ; 6:1
  • Journal article (peer-reviewed)abstract
    • Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution. A study mapping the tree species richness in Amazonian forests shows that soil type exerts a strong effect on species richness, probably caused by the areas of these forest types. Cumulative water deficit, tree density and temperature seasonality affect species richness at a regional scale.
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3.
  • Luize, Bruno Garcia, et al. (author)
  • Geography and ecology shape the phylogenetic composition of Amazonian tree communities
  • 2024
  • In: JOURNAL OF BIOGEOGRAPHY. - 0305-0270 .- 1365-2699.
  • Journal article (peer-reviewed)abstract
    • Aim: Amazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types. Location: Amazonia. Taxon: Angiosperms (Magnoliids; Monocots; Eudicots). Methods: Data for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny. Results: In the terra firme and v & aacute;rzea forest types, the phylogenetic composition varies by geographic region, but the igap & oacute; and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R-2 = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R-2 = 28%). A greater number of lineages were significant indicators of geographic regions than forest types. Main Conclusion: Numerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions.
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4.
  • Cooper, Declan L.M., et al. (author)
  • Consistent patterns of common species across tropical tree communities
  • 2024
  • In: Nature. - 0028-0836 .- 1476-4687. ; 625:7996, s. 728-734
  • Journal article (peer-reviewed)abstract
    • Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations 1–6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories 7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.
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5.
  • Daelman, Bo, et al. (author)
  • Frailty and cognitive function in middle-aged and older adults with congenital heart disease
  • 2024
  • In: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 83:12, s. 1149-1159
  • Journal article (peer-reviewed)abstract
    • Background: Life expectancy of patients with congenital heart disease (CHD) has increased rapidly, resulting in a growing and aging population. Recent studies have shown that older people with CHD have higher morbidity, health care use, and mortality. To maintain longevity and quality of life, understanding their evolving medical and psychosocial challenges is essential.Objectives: The authors describe the frailty and cognitive profile of middle-aged and older adults with CHD to identify predictor variables and to explore the relationship with hospital admissions and outpatient visits.Methods: Using a cross-sectional, multicentric design, we included 814 patients aged ≥40 years from 11 countries. Frailty phenotype was determined using the Fried method. Cognitive function was assessed by the Montreal Cognitive Assessment.Results: In this sample, 52.3% of patients were assessed as robust, 41.9% as prefrail, and 5.8% as frail; 38.8% had cognitive dysfunction. Multinomial regression showed that frailty was associated with older age, female sex, higher physiologic class, and comorbidities. Counterintuitively, patients with mild heart defects were more likely than those with complex lesions to be prefrail. Patients from middle-income countries displayed more prefrailty than those from higher-income countries. Logistic regression demonstrated that cognitive dysfunction was related to older age, comorbidities, and lower country-level income.Conclusions: Approximately one-half of included patients were (pre-)frail, and more than one-third experienced cognitive impairment. Frailty and cognitive dysfunction were identified in patients with mild CHD, indicating that these concerns extend beyond severe CHD. Assessing frailty and cognition routinely could offer valuable insights into this aging population.
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6.
  • Artaxo, Paulo, et al. (author)
  • Tropical and Boreal Forest – Atmosphere Interactions : A Review
  • 2022
  • In: Tellus. Series B, Chemical and physical meteorology. - : Stockholm University Press. - 0280-6509 .- 1600-0889. ; 74:1, s. 24-163
  • Research review (peer-reviewed)abstract
    • This review presents how the boreal and the tropical forests affect the atmosphere, its chemical composition, its function, and further how that affects the climate and, in return, the ecosystems through feedback processes. Observations from key tower sites standing out due to their long-term comprehensive observations: The Amazon Tall Tower Observatory in Central Amazonia, the Zotino Tall Tower Observatory in Siberia, and the Station to Measure Ecosystem-Atmosphere Relations at Hyytiäla in Finland. The review is complemented by short-term observations from networks and large experiments.The review discusses atmospheric chemistry observations, aerosol formation and processing, physiochemical aerosol, and cloud condensation nuclei properties and finds surprising similarities and important differences in the two ecosystems. The aerosol concentrations and chemistry are similar, particularly concerning the main chemical components, both dominated by an organic fraction, while the boreal ecosystem has generally higher concentrations of inorganics, due to higher influence of long-range transported air pollution. The emissions of biogenic volatile organic compounds are dominated by isoprene and monoterpene in the tropical and boreal regions, respectively, being the main precursors of the organic aerosol fraction.Observations and modeling studies show that climate change and deforestation affect the ecosystems such that the carbon and hydrological cycles in Amazonia are changing to carbon neutrality and affect precipitation downwind. In Africa, the tropical forests are so far maintaining their carbon sink.It is urgent to better understand the interaction between these major ecosystems, the atmosphere, and climate, which calls for more observation sites, providing long-term data on water, carbon, and other biogeochemical cycles. This is essential in finding a sustainable balance between forest preservation and reforestation versus a potential increase in food production and biofuels, which are critical in maintaining ecosystem services and global climate stability. Reducing global warming and deforestation is vital for tropical forests.
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7.
  • Barbosa, Fernando S., 1992-, et al. (author)
  • Formal Methods for Robot Motion Planning with Time and Space Constraints (Extended Abstract)
  • 2021
  • In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer Nature. ; , s. 1-14
  • Conference paper (peer-reviewed)abstract
    • Motion planning is one of the core problems in a wide range of robotic applications. We discuss the use of temporal logics to include complex objectives, constraints, and preferences in motion planning algorithms and focus on three topics: the first one addresses computational tractability of Linear Temporal Logic (LTL) motion planning in systems with uncertain non-holonomic dynamics, i.e. systems whose ability to move in space is constrained. We introduce feedback motion primitives and heuristics to guide motion planning and demonstrate its use on a rover in 2D and a fixed-wing drone in 3D. Second, we introduce combined motion planning and hybrid feedback control design in order to find and follow trajectories under Metric Interval Temporal Logic (MITL) specifications. Our solution creates a path to be tracked, a sequence of obstacle-free polytopes and time stamps, and a controller that tracks the path while staying in the polytopes. Third, we focus on motion planning with spatio-temporal preferences expressed in a fragment of Signal Temporal Logic (STL). We introduce a cost function for a of a path reflecting the satisfaction/violation of the preferences based on the notion of STL spatial and temporal robustness. We integrate the cost into anytime asymptotically optimal motion planning algorithm RRT ⋆ and we show the use of the algorithm in integration with an autonomous exploration planner on a UAV.
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8.
  • Barbosa, Fernando S., 1992-, et al. (author)
  • Provably safe control of Lagrangian systems in obstacle-scattered environments
  • 2020
  • In: 2020 59th IEEE Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE).
  • Conference paper (peer-reviewed)abstract
    • We propose a hybrid feedback control law that guarantees both safety and asymptotic stability for a class of Lagrangian systems in environments with obstacles. Rather than performing trajectory planning and implementing a trajectory-tracking feedback control law, our approach requires a sequence of locations in the environment (a path plan) and an abstraction of the obstacle-free space. The problem of following a path plan is then interpreted as a sequence of reach-avoid problems: the system is required to consecutively reach each location of the path plan while staying within safe regions. Obstacle-free ellipsoids are used as a way of defining such safe regions, each of which encloses two consecutive locations. Feasible Control Barrier Functions (CBFs) are created directly from geometric constraints, the ellipsoids, ensuring forward-invariance, and therefore safety. Reachability to each location is guaranteed by asymptotically stabilizing Control Lyapunov Functions (CLFs). Both CBFs and CLFs are then encoded into quadratic programs (QPs) without the need of relaxation variables. Furthermore, we also propose a switching mechanism that guarantees the control law is correct and well-defined even when transitioning between QPs. Simulations show the effectiveness of the proposed approach in two complex scenarios.
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9.
  • Barbosa, Fernando S., 1992-, et al. (author)
  • Risk-Aware Motion Planning in Partially Known Environments
  • 2021
  • In: 2021 60th IEEE  conference on decision and control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 5220-5226
  • Conference paper (peer-reviewed)abstract
    • Recent trends envisage robots being deployed inareas deemed dangerous to humans, such  as buildings with gasand radiation leaks. In such situations, the model of the underlying  hazardous process might be unknown to the agent a priori, giving rise to the problem of planning for safe behaviour inpartially known environments. We employ Gaussian Process regression to create a probabilistic model of the hazardous process from local noisy samples. The result of this regression is then used by a risk metric, such as the Conditional Value-at-Risk, to reason about the safety at a certain state. The outcome is a risk function that can  be employed in optimal motion planning problems. We demonstrate the use of the proposed function in two approaches. First is a sampling-based motion planning algorithm with an  event-based trigger for online replanning. Second is an adaptation to the  incremental Gaussian Process motion planner (iGPMP2), allowing it to quickly react and adapt to the environment. Both algorithms are evaluated in representative simulation scenarios, where they demonstrate the ability of avoiding high-risk areas.
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10.
  • Barbosa, Fernando S., 1992- (author)
  • Towards Safer and Risk-aware Motion Planning and Control for Robotic Systems
  • 2022
  • Doctoral thesis (other academic/artistic)abstract
    • Safety and risk-awareness are important properties for robotic systems, be it for protecting them from potentially dangerous internal states, or for avoiding collisions with obstacles and environmental hazards in disaster scenarios. Ensuring safety may be the role of more than one algorithmic layer in a system, each with varying assumptions and guarantees. This thesis investigates how to provide safety and risk-awareness in a robotic system by leveraging temporal logics, motion planning algorithms, and control theory.Traditional control theory approaches interpret the collision avoidance safety task as a `stay-away' task; obstacles are abstracted as collections of geometric shapes, and controllers are designed to avoid each shape individually. We propose interpreting the collision avoidance problem as a `stay-within' task: the obstacle-free space is abstracted into safe regions. We propose control laws based on Control Barrier functions that guarantee that the system remains within such safe regions throughout its mission. Our results demonstrate that our controller indirectly avoids obstacles while providing the system the freedom to move within the safe regions, without the necessity to plan and track a safe trajectory. Furthermore, by extending our idea with Metric Interval Temporal Logic, we are able to consider missions with explicit time bounds. Temporal logics are often used to define hard constraints on motion plans for robotic systems. However, some missions may require the system to violate constraints to make progress. Therefore, we propose to soften the hard constraints when necessary. Such soft constraints, here coined as spatial preferences, are used to account for relations between the system and the environment, such as distance from obstacles. The proposed minimally-violating motion planning algorithm attempts to find trajectories that satisfy the spatial preferences as much as possible, but violate them when needed. We demonstrate the use of spatial preferences on 3D exploration scenarios with Unmanned Aerial Vehicles, where we provide safer trajectories to the system while improving exploration efficiency. In the last part of the thesis, we address safety in scenarios where a precise model of the environment is not available. In such scenarios, the system is required to fulfil the mission while minimizing risk, considering the imprecise model. We leverage Gaussian Processes to build approximate models of the environment, and use their posterior distributions in a risk metric. This risk metric allows us to consider less likely but possible events along the missions. To this end, we propose an online risk-aware motion planning approach, and validate it on disaster scenarios, where exposure to the unmodeled hazards might damage the system. Moreover, we explore risk-awareness between the control and mapping layers, by considering smooth approximations of Euclidean Distance Fields.Our results indicate that our algorithms provide robotic systems with i) provably-safe controllers, ii) soft safety constraints, and iii) risk-awareness in unmodeled environments. These three properties contribute to safer and risk-aware robotic systems in the real world.
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  • Result 1-10 of 23
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