A survey of the eutrophication state of an urbanized tropical estuary, the case of the Great Vitória Estuarine System, Brazil.

Although, estuarine ecosystems have an ecological and economical importance as they have a high  biological productivity and occur within a unique and dynamic environment, they have been subjected to anthropogenic alterations. The Great Vitória Estuarine System (GVES), Espírito Santo State, Brazil, is not an exception, as urbanization is growing around it with a high quantity of sewage been added to the system. In order to evaluate the eutrophication state as well as the meiofauna response to it, several parameters in both sediments and in the water column were assessed. Orthophosphate, nitrite, nitrate, ammonia, chla and Fecal Coliform counts (FC) ranged from 0.2 to 3.2 μM, 0.25 to 1.14 μM, 1.83 to 0.19μM, 4.19 to 49.23 μM, 0.61 to 6.72 μg/L and 14 to 5.0x104 MPN/100 mL of water, respectively. These results showed that the GVES is under an eutrophication process and that the Passagem Channel experienced the largest impacts. Sewage plays an important role in this eutrophication process as indicated by PCA and correlations tests. The density of meiofauna showed similar values to those found in environments with similar levels of anthropogenic stress. This multi-approach evaluation revealed several aspects of the impacted estuary and could be used as an important tool to manage better the estuary.Although, estuarine ecosystems have an ecological and economical importance as they have a high  biological productivity and occur within a unique and dynamic environment, they have been subjected to anthropogenic alterations. The Great Vitória Estuarine System (GVES), Espírito Santo State, Brazil, is not an exception, as urbanization is growing around it with a high quantity of sewage been added to the system. In order to evaluate the eutrophication state as well as the meiofauna response to it, several parameters in both sediments and in the water column were assessed. Orthophosphate, nitrite, nitrate, ammonia, chla and Fecal Coliform counts (FC) ranged from 0.2 to 3.2 μM, 0.25 to 1.14 μM, 1.83 to 0.19μM, 4.19 to 49.23 μM, 0.61 to 6.72 μg/L and 14 to 5.0x104 MPN/100 mL of water, respectively. These results showed that the GVES is under an eutrophication process and that the Passagem Channel experienced the largest impacts. Sewage plays an important role in this eutrophication process as indicated by PCA and correlations tests. The density of meiofauna showed similar values to those found in environments with similar levels of anthropogenic stress. This multi-approach evaluation revealed several aspects of the impacted estuary and could be used as an important tool to manage better the estuary

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

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

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

The Morphometry of Lake Palmas, a Deep Natural Lake in Brazil

<div><p>Lake Palmas (A = 10.3<b> </b>km²) is located in the Lower Doce River Valley (LDRV), on the southeastern coast of Brazil. The Lake District of the LDRV includes 90 lakes, whose basic geomorphology is associated with the alluvial valleys of the Barreiras Formation (Cenozoic, Neogene) and with the Holocene coastal plain. This study aimed to investigate the relationship of morphometry and thermal pattern of a LDRV deep lake, Lake Palmas. A bathymetric survey carried out in 2011 and the analysis of hydrographic and wind data with a geographic information system allowed the calculation of several metrics of lake morphometry. The vertical profiling of physical and chemical variables in the water column during the wet/warm and dry/mild cold seasons of 2011 to 2013 has furnished a better understanding of the influence of the lake morphometry on its structure and function. The overdeepened basin has a subrectangular elongated shape and is aligned in a NW-SE direction in an alluvial valley with a maximum depth (Z_max) of 50.7<b> </b>m, a volume of 2.2×10⁸ m³ (0.22<b> </b>km³) and a mean depth (Z_mv) of 21.4<b> </b>m. These metrics suggest Lake Palmas as the deepest natural lake in Brazil. Water column profiling has indicated strong physical and chemical stratification during the wet/warm season, with a hypoxic/anoxic layer occupying one-half of the lake volume. The warm monomictic pattern of Lake Palmas, which is in an accordance to deep tropical lakes, is determined by water column mixing during the dry and mild cold season, especially under the influence of a high effective fetch associated with the incidence of cold fronts. Lake Palmas has a very long theoretical retention time, with a mean of 19.4 years. The changes observed in the hydrological flows of the tributary rivers may disturb the ecological resilience of Lake Palmas.</p></div

Wind direction frequency (%) and intensity (m.s⁻¹) from Linhares meteorological station from 2007 to 2009: a) warm and wet months; b) dry/mild cold months.

<p>Wind direction frequency (%) and intensity (m.s⁻¹) from Linhares meteorological station from 2007 to 2009: a) warm and wet months; b) dry/mild cold months.</p