Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Microwave-activated carbons from tucumã (<i>Astrocaryum aculeatum</i>) seed for efficient removal of 2-nitrophenol from aqueous solutions

<p>Activated carbons (ACs) prepared from tucumã seed (<i>Astrocaryum aculeatum</i>) were used for 2-nitrophenol removal from aqueous solutions. The ACs were characterized by elemental analysis, FTIR, <i>N</i>₂ adsorption/desorption isotherms, TGA, hydrophobicity/hydrophilicity balance, and total of acidic and basic groups. The ACs showed to have hydrophilic surfaces and they presented high specific surface areas (up to 1318 m² g⁻¹). In batch optimization studies, maximum removal was obtained at pH 7, contact time of 30 min, adsorbent dosage 1.5 gL⁻¹ and temperature of 50°C. The general-order kinetic model and Liu isotherm model best fit the kinetic and equilibrium adsorption data with a maximum adsorption capacity of 1382 mg g⁻¹ at 50°C. Effect of temperature and thermodynamic studies revealed that the adsorption processes of 2-nitrophenol onto ACs are dependent on temperature and are exothermic and spontaneous, respectively. About the applicability of the ACs for treating simulated effluents, the tucumã seed-activated carbon showed an excellent outcome in the treatment of simulated effluents, evidencing its high efficiency for phenolic compound adsorption. Tucumã seed-ACs showed to be cost effective and highly efficient adsorbents for efficient removal of 2-nitrophenol from aqueous solutions.</p