Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42\ub74% vs 44\ub72%; absolute difference \u20131\ub769 [\u20139\ub758 to 6\ub711] p=0\ub767; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5\u20138] vs 6 [5\u20138] cm H2O; p=0\ub70011). ICU mortality was higher in MICs than in HICs (30\ub75% vs 19\ub79%; p=0\ub70004; adjusted effect 16\ub741% [95% CI 9\ub752\u201323\ub752]; p<0\ub70001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0\ub780 [95% CI 0\ub775\u20130\ub786]; p<0\ub70001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status. Funding: No funding

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Investigation of Hydrologically Mediated Interactions at the Critical Zone through Controlled Experimentation

The critical zone (CZ) extends from the bottom of the weathered bedrock to the top of the tree canopies. CZ processes and fluxes, such as weathering, nutrient and carbon cycling are critical for the provision of critical ecosystem services that support life on the planet. CZ function is regulated by its internal structure, as inferred for example from concentration-discharge (C-Q) relationships. On the other hand, CZ fluxes are slowly and constantly shaping its features, as seen for example in rates of mineral weathering across climatic gradients or the coevolution of soils, vegetation and topography across an elevation gradient. Understanding the relationships between CZ function and structure becomes fundamental for enhancing our capacity to predict and mitigate impacts from short term environmental disturbances to medium and long-term alterations imposed by climate change. This PhD dissertation explores the interplay between structural development and hydrologic behavior and response of the CZ. My objective was to provide empirical understanding of the following question: How water fluxes and states modulate and are subject to changes in CZ structure. In order to pursue this goal, I’ve taken advantage of the experimental set-up hosted at Landscape Evolution Observatory (LEO) - Biosphere 2, which allows for a high degree of observability and control. The system under study consists of a 1 m3 sloping lysimeter filled with fresh un-weathered crushed basalt. Due to its slope, the lysimeter can be taken as a model of a hillslope, a landscape unit in which most biogeochemical interactions occur. In the first chapter of this dissertation, I address the role of hydrology in shaping the incipient heterogeneity. Throughout 2 years, the lysimeter experienced sequences of hydrologic inputs (irrigation) and drying periods under bare soil conditions, leading to detectable biogeochemical patterns. Here, my main question was how observed geochemical weathering states and microbial diversity and abundance are influenced by hydrologic behavior within two years of imposed wet-dry cycles. For this purpose, an intensive sampling procedure was undertaken for the assessment of the incipient heterogeneity within the system, followed by modelling of the hydrologic history summarized in terms of moisture states, cumulative fluxes and average residence times of water. I’ve found significant imprints of hydrologic behavior on both biological and geochemical patterns of heterogeneity, which suggests a common framework to assess how heterogeneity develops in incipient systems. More specifically, the amount of time spent by water within the subsurface appeared, or the residence time (RT) appeared to be the main control on observed geochemical states and spatial distribution of different fila of microorganisms. The second and third chapter combined represent an effort to experimentally observe residence times of water within the subsurface. Chapter two presents a method to directly observe the transport of solute within the model system using Electrical Resistivity Tomography (ERT). For that, I have equipped the lysimeter with electrodes to be used with an ERT acquisition system, allowing me to obtain high frequency temporal images of soil resistivity along 5 cross-sections of the lysimeter. The tracking of solute movement through ERT was based on the estimation of the spatial distribution of fluid electrical conductivity (EC) within the lysimeter. It is important to note that the estimation of the spatial distribution of EC has traditionally been a challenge in ERT studies at field and laboratory scale, especially under transient conditions. The presented method has therefore the potential to be applied at different settings and find uses beyond the scope of the estimation of RT. The third chapter of this dissertation deals with the extension of an existing theory on the estimation of transit time distributions (TTD) within the context of controlled experimentation. Transit times of water (TT) are of great importance in hydrologic sciences, since they are related to the very basic question of the fate of water once it reaches the landscape. The theory of TTD represents a lumped-systems approach towards the understanding of TT at natural landscapes and has a long history of application in both natural as well as artificial systems. However, due to its lumped nature of system representation, TTD theory does not explicitly address the internal variability of flow pathways within the subsurface and therefore benefit from understanding of the mechanistic basis that they represent. The study presented in chapter 3 introduces a method for the estimation of the varying ages of water within the lysimeter under a prescribed hydrologic forcing allowing for an approach towards the time-variability of TT

An Aridity Index‐Based Formulation of Streamflow Components

Direct runoff and baseflow are the two primary components of total streamflow, and their accurate estimation is indispensable for a variety of hydrologic applications. While direct runoff is the quick response stemming from surface and shallow subsurface flow paths and is often associated with floods, baseflow represents the groundwater contribution from stored sources (e.g., groundwater) to streams and is crucial for environmental flow regulations, and water supply, among others. L'vovich (1979, ) proposed a two-step water balance partitioning, where precipitation is divided into direct runoff and catchment wetting, followed by the disaggregation of the latter into baseflow and evapotranspiration. Here, we investigate the role of the aridity index (ratio between mean-annual potential evapotranspiration and precipitation) in controlling the long-term (mean-annual) fluxes of direct runoff and baseflow. We present an analytical solution beginning with similar assumptions as proposed by Budyko (1974, ), leading to two complementary expressions for the two fluxes. The aridity index explained 77% and 89% of variability in direct runoff and baseflow from 378 catchments within the continental United States, while our formulations were able to reproduce the patterns of water balance partitioning proposed by L'vovich (1979, ) at the mean-annual timescale. Our approach can be used to further understand how climate and landscape controls the terrestrial water balance at mean-annual timescales, while also representing a step toward the prediction of baseflow and direct runoff at ungauged basins.6 month embargo; first published online 4 September 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Composição do banco de sementes de uma floresta semidecidual secundária considerando o seu potencial de uso para recuperação ambiental

Este estudo teve como objetivo caracterizar o banco de sementes de um fragmento florestal na região de Viçosa, MG, bem como inferir se esse indicador pode garantir a sustentabilidade caso seja utilizado para recuperação de áreas degradadas e, ainda, comparar sua composição florística com aquelas descritas em outros estudos com bancos de sementes. Para isso, foram coletadas 20 amostras do banco de sementes em pontos escolhidos ao acaso, sendo cada amostra composta de quatro subamostras. Para a instalação do experimento no viveiro, foram utilizadas 20 caixas de madeira no formato de 50 x 50 x 15 cm. Após 90 dias, encontraram-se 508 indivíduos, dos quais foram identificadas 38 espécies, pertencentes a 34 gêneros e distribuídas em 22 famílias. O índice de diversidade (H') foi de 2,11; já a eqüabilidade (J) de 0,67 foi considerada alta quando comparada com as de outros bancos de sementes. Cecropia hololeuca (28,91%) e Solanum erianthum (18,67%) foram as espécies mais importantes e que podem atuar diretamente na dinâmica do processo de regeneração da mata. Verificou-se, portanto, que o banco de sementes estudado pode atuar na recomposição da vegetação de uma área degradada em condições semelhantes ao fragmento estudado, agilizando e garantindo a dinâmica do processo sucessional