Additional file 1: of Mistaken perception of lipid intake and its effects: a randomized trial

Provides the results of the additional descriptive and exploratory analysis of the pre- and post-intervention measurements according to the PM classification, between the pre-action and action groups. (DOC 39 kb

Effects of increasing temperature and, CO₂ on quality of litter, shredders, and microorganisms in Amazonian aquatic systems

<div><p>Climate change may affect the chemical composition of riparian leaf litter and, aquatic organisms and, consequently, leaf breakdown. We evaluated the effects of different scenarios combining increased temperature and carbon dioxide (CO₂) on leaf detritus of <i>Hevea spruceana</i> (Benth) Müll. and decomposers (insect shredders and microorganisms). We hypothesized that simulated climate change (warming and elevated CO₂) would: i) decrease leaf-litter quality, ii) decrease survival and leaf breakdown by shredders, and iii) increase microbial leaf breakdown and fungal biomass. We performed the experiment in four microcosm chambers that simulated air temperature and CO₂ changes in relation to a real-time control tracking current conditions in Manaus, Amazonas, Brazil. The experiment lasted seven days. During the experiment mean air temperature and CO₂ concentration ranged from 26.96 ± 0.98ºC and 537.86 ± 18.36 ppmv in the control to 31.75 ± 0.50ºC and 1636.96 ± 17.99 ppmv in the extreme chamber, respectively. However, phosphorus concentration in the leaf litter decreased with warming and elevated CO₂. Leaf quality (percentage of carbon, nitrogen, phosphorus, cellulose and lignin) was not influenced by soil flooding. Fungal biomass and microbial leaf breakdown were positively influenced by temperature and CO₂ increase and reached their highest values in the intermediate condition. Both total and shredder leaf breakdown, and shredder survival rate were similar among all climatic conditions. Thus, low leaf-litter quality due to climate change and higher leaf breakdown under intermediate conditions may indicate an increase of riparian metabolism due to temperature and CO₂ increase, highlighting the risk (e.g., decreased productivity) of global warming for tropical streams.</p></div

Effects of increasing temperature and, CO₂ on quality of litter, shredders, and microorganisms in Amazonian aquatic systems - Fig 2

<p><b>Survival (%; A) and pupae (%; B) of <i>Phylloicus elektoros</i> (Trichoptera: Calamoceratidae) in treatments with leaf disks of <i>Hevea spruceana</i> under four climate conditions during the experiment in Control, Light, Intermediate and Extreme treatments</b>.</p

Mean values (standard error) and results of abiotic variables under simulated climate conditions during seven days of the experiment.

<p>Mean values (standard error) and results of abiotic variables under simulated climate conditions during seven days of the experiment.</p

Fungal biomass in treatments with leaf disks of <i>Hevea spruceana</i> under four climate conditions during the experiment in Control, Light, Intermediate and Extreme treatments.

<p>First (lower line) and third (higher line) quartile, the median (bold line), upper and lower limits (dashed line) and outliers (circles). Highest values = a; lowest values = b (p < 0.05).</p

Chemical characteristics of <i>Hevea spruceana</i> leaves growing under different conditions of temperature, CO₂ (Carbon dioxide) and humidity availability.

<p>We included paired t-tests for leaf characteristics of plants grown on flooded and non-flooded soils.</p

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.</p