Assessment of Red Sea temperatures in CMIP5 models for present and future climate

The increase of the temperature in the Red Sea basin due to global warming could have a large negative effect on its marine ecosystem. Consequently, there is a growing interest, from the scientific community and public organizations, in obtaining reliable projections of the Red Sea temperatures throughout the 21st century. However, the main tool used to do climate projections, the global climate models (GCM), may not be well suited for that relatively small region. In this work we assess the skills of the CMIP5 ensemble of GCMs in reproducing different aspects of the Red Sea 3D temperature variability. The results suggest that some of the GCMs are able to reproduce the present variability at large spatial scales with accuracy comparable to medium and high-resolution hindcasts. In general, the skills of the GCMs are better inside the Red Sea than outside, in the Gulf of Aden. Based on their performance, 8 of the original ensemble of 43 GCMs have been selected to project the temperature evolution of the basin. Bearing in mind the GCM limitations, this can be an useful benchmark once the high resolution projections are available. Those models project an averaged warming at the end of the century (2080–2100) of 3.3 ±> 0.6°C and 1.6 ±> 0.4°C at the surface under the scenarios RCP8.5 and RCP4.5, respectively. In the deeper layers the warming is projected to be smaller, reaching 2.2 ±> 0.5°C and 1.5 ±> 0.3°C at 300 m. The projected warming will largely overcome the natural multidecadal variability, which could induce temporary and moderate decrease of the temperatures but not enough to fully counteract it. We have also estimated how the rise of the mean temperature could modify the characteristics of the marine heatwaves in the region. The results show that the average length of the heatwaves would increase ~15 times and the intensity of the heatwaves ~4 times with respect to the present conditions under the scenario RCP8.5 (10 time and 3.6 times, respectively, under scenario RCP4.5).En prensa4,41

Global diversity and biogeography of deep-sea pelagic prokaryotes

En prensa8,951

Climate-driven impacts of exotic species on marine ecosystems

Aim Temperature is fundamental to the physiological and ecological performance of marine organisms, but its role in modulating the magnitude of ecological impacts by exotic species remains unresolved. Here, we examine the relationship between thermal regimes in the range of origin of marine exotic species and sites of measured impact, after human-induced introduction. We compare this relationship with the magnitude of impact exerted by exotic species on native ecosystems. Location Global. Time period 1977–2017 (meta-analysis). Major taxa studied Marine exotic species. Methods Quantitative impacts of exotic species in marine ecosystems were obtained from a global database. The native range of origin of exotic species was used to estimate the realized thermal niche for each species and compared with the latitude and climatic conditions in recipient sites of recorded impact of exotic species. The difference in median temperatures between recipient sites and the thermal range of origin (i.e., thermal midpoint anomaly) was compared with the magnitude of effect sizes by exotic species on native species, communities and ecosystems. Results Recorded impacts occurred predominantly within the thermal niche of origin of exotic species, albeit with a tendency toward higher latitudes and slightly cooler conditions. The severity of impacts by exotic species on abundance of native taxa displayed a hump-shaped relationship with temperature. Peak impacts were recorded in recipient sites that were 2.2°C cooler than the thermal midpoint of the range of origin of exotic species, and impacts decreased in magnitude toward higher and lower thermal anomalies. Main conclusions Our findings highlight how temperature and climatic context influence ecological impacts by exotic species in marine ecosystems and the implications for existing and novel species interactions under climate change.En prensa5,14

Balanço do nitrogênio e fósforo em solo com cultivo orgânico de hortaliças após a incorporação de biomassa de guandu.

Os objetivos deste trabalho foram avaliar os efeitos de faixas de guandu (Cajanus cajan) e da incorporação da biomassa proveniente de sua poda na fertilidade do solo e na produtividade de três hortaliças sob cultivo orgânico. O delineamento usado foi de blocos casualizados completos em esquema de parcelas subsubdivididas com três repetições. As produtividades de beterraba, cenoura e feijão-de-vagem não foram afetadas pelos tratamentos. Nas parcelas onde não houve incorporação da biomassa de guandu, o balanço de nitrogênio no sistema foi negativo, ao passo que com a incorporação, esse balanço foi positivo. Embora tenha ocorrido balanço positivo para o fósforo nas parcelas sem a incorporação de biomassa de guandu, houve um aumento significativo na absorção desse elemento pelas hortaliças quando o material foi incorporado. O sistema de cultivo em aléias de guandu pode representar uma prática vantajosa para os produtores orgânicos, por contribuir na manutenção da fertilidade do solo

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

Trace metals in deep ocean waters: A review

Publicado32,655