Thresholds of species loss in Amazonian deforestation frontier landscapes

In the Brazilian Amazon, private land accounts for the majority of remaining native vegetation. Understanding how land‐use change affects the composition and distribution of biodiversity in farmlands is critical for improving conservation strategies in the face of rapid agricultural expansion. Working across an area exceeding 3 million ha in the southwestern state of Rondônia, we assessed how the extent and configuration of remnant forest in replicate 10,000‐ha landscapes has affected the occurrence of a suite of Amazonian mammals and birds. In each of 31 landscapes, we used field sampling and semistructured interviews with landowners to determine the presence of 28 large and medium sized mammals and birds, as well as a further 7 understory birds. We then combined results of field surveys and interviews with a probabilistic model of deforestation. We found strong evidence for a threshold response of sampled biodiversity to landscape level forest cover; landscapes with <30–40% forest cover hosted markedly fewer species. Results from field surveys and interviews yielded similar thresholds. These results imply that in partially deforested landscapes many species are susceptible to extirpation following relatively small additional reductions in forest area. In the model of deforestation by 2030 the number of 10,000‐ha landscapes under a conservative threshold of 43% forest cover almost doubled, such that only 22% of landscapes would likely to be able to sustain at least 75% of the 35 focal species we sampled. Brazilian law requires rural property owners in the Amazon to retain 80% forest cover, although this is rarely achieved. Prioritizing efforts to ensure that entire landscapes, rather than individual farms, retain at least 50% forest cover may help safeguard native biodiversity in private forest reserves in the Amazon. Umbrales de Pérdida de Especies en los Paisajes Fronterizos de Deforestación en el Amazonas Ochoa‐Quintero     

Healthcare waste generation in hospitals per continent: a systematic review

Environmental Science and Pollution Research - There are increasing worldwide concerns about the negative impacts of healthcare waste generated in hospitals, especially in low- and middle-income...     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.     

Ionic Dye Removal Using Solvent-Assisted Ionic Micellar Flocculation

Journal of Polymers and the Environment - The environmental impacts caused by dyes in industrial wastewater are incalculable, due to their adverse effects on the ecosystem and human life,...     

Humic substances formation during poultry litter composting and its influence on the structural characteristics of the compost

Journal of Material Cycles and Waste Management - This study aimed to elucidate the formation process of humic substances (HS) during poultry litter (PL) composting and its influence on the...     

Approaches on the Complex Crystallization in PLA/Babassu Based on Modulated Differential Scanning Calorimetry Analyses

Journal of Polymers and the Environment - Poly(lactic acid) (PLA) and PLA/5% Babassu compounds were molten mixed, afterwards aged at temperatures ranging from 50 to 90&nbsp;°C during 15 to...