In Amazonian igapó forests (seasonally flooded forests on blackwater river margins), the end of the annual flood pulse results in the formation of extensive mat-like seed patches. The seeds in these patches then germinate, forming a dense, highly heterogeneous, assemblage. Animal–plant interactions in these areas, as well as the influence that the patches have on the occurrence of herbivorous vertebrates, remain almost completely unstudied. Using camera traps in areas with and without seed/seedling patches, we tested the relationship between these seed accumulation sites and the presence of bird and mammal species. At the micro-scale (between treatments), vertebrate occurrence was not related to patch presence. At the larger scale (local), distance from adjacent upland (terra firme) forest and seed patch size were correlated with vertebrate distribution. The widespread occurrence of terrestrially active birds and mammals throughout igapó forests, not just where food resource densities were high, seems to be a compromise strategy between exploring the area to select the most favourable food items, and minimizing the risk of being predated when spending extended time foraging at the concentrated food sources represented by the seed patches. Our results underline the potential importance of igapó forests as a key habitat for a variety of terrestrial terra firme taxa, as well as emphasize the dynamic nature of this forest type, and should encourage further studies of this habitat and resource availability system.

The screening of flu-like syndrome is difficult due to nonspecific symptoms or even oligosymptomatic presentation and became even more complex during the Covid-19 pandemic. However, an efficient screening tool plays an important role in the control of highly contagious diseases, allowing more efficient medical-epidemiological approaches and rational management of global health resources. Infrared thermography is a technique sensitive to small alterations in the skin temperature which may be related to early signs of inflammation and thus being relevant in the detection of infectious diseases. Thus, the objective of this study was to evaluate the potential of facial thermal profiles as a risk evaluator of symptoms and signs of SARs diseases, using COVID-19 as background disease. A total of 136 patients were inquired about the most common symptoms of COVID-19 infection and were submitted to an infrared image scanning, where the temperatures of 10 parameters from different regions of the face were captured. We used RT-qPCR as the ground truth to compare with the thermal parameters, in order to evaluate the performance of infrared imaging in COVID-19 screening. Only 16% of infected patients had fever at the hospital admission, and most infrared thermal variables presented values of temperature significantly higher in infected patients. The maximum eye temperature (MaxE) showed the highest predictive value at a cut-off of >35.9°C (sn = 71.87%, sp = 86.11%, LR+ = 5.18, LR- = 0.33, AUC = 0.850, p < 0.001). Our predictive model reached an accuracy of 86% for disease detection, indicating that facial infrared thermal scanning, based on the combination of different facial regions and the thermal profile of the face, has potential to act as a more accurate diagnostic support method for early COVID-19 screening, when compared to classical infrared methods, based on a single spot with the maximum skin temperature of the face.

Despite the diversity and functional importance of invertebrates, predicting their response to global warming remains challenging as it requires extensive measurements of physiological performance or rarely available high-resolution distribution data. Mechanistic models can help overcome these limitations by generalizing fundamental physiological processes. However, their predictions typically omit the effects of species interactions. Movement is a key process of species interactions underpinning animal performance in the real world. Here, we developed an empirically-grounded mechanistic model that incorporates allometric and thermodynamic constraints on movement and predator-prey interactions. We illustrate how it can be used to quantify the thermal performance of invertebrates under current and future climatic conditions. This trait-based approach (1) contributes to our understanding of the mechanisms underlying thermal fitness, (2) allows generalized predictions of thermal performance across invertebrate species worldwide and (3) can be used to inform species distribution models and thereby help infer species range limits under climate change.

The Amazon forest has the highest biodiversity on earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed and grey literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive dataset of inventories of mammal, bird and reptile species ever assembled for the area. The complete dataset comprises 154,123 records of 317 species (185 birds, 119 mammals and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil,

The relationship between species body masses and densities is strongly conserved around a three-quarter power law when pooling data across communities. However, studies of local within-community relationships have revealed major deviations from this general pattern, which has profound implications for their stability and functioning. Despite multiple contributions of soil communities to people, there is limited knowledge on the drivers of body mass-abundance relationship in these communities. We compiled a dataset comprising 155 soil-animal communities across four countries (Canada, Germany, Indonesia, USA), all sampled using the same methodology. We tested if variation in local climatic and edaphic conditions drives differences in local body mass-abundance scaling relationships. We found substantial variation in the slopes of this power-law relationship across local communities. Structural equation modeling showed that soil temperature and water content have a positive and negative net effect, respectively, on soil communities. These effects are mediated by changes in local edaphic conditions (soil pH and carbon content) and the body-mass range of the communities. These results highlight ways in which alterations of soil climatic and edaphic conditions interactively impact the distribution of abundance, and thus energy, between populations of small and large animals. These quantitative mechanistic relationships facilitate our understanding of how global changes in environmental conditions, such as temperature and precipitation, will affect community-abundance distributions and thus the stability and functioning of soil-animal communities.