Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Capim-piatã adubado com fontes de fósforo de diferente solubilidade em água

The development of piatã grass fertilized with phosphorus sources with different solubilities in water was evaluated. The experiment was developed in the unit of Aquidauana of UEMS, MS, from February to August, 2012. Four treatments were evaluated: control (without phosphorus fertilization), slow solubility, fast solubility (readily available), and mixed solubility sources of phosphorus (FH Pasture(r)). It was adopted a randomized blocks design with four blocks and four replicates in a total of 16 pastures (0.5 ha each one). Measurements were performed weekly to evaluate structural characteristics and morphogenic variables of the plants. Data were submitted to a variance analysis according to the model. When necessary, the means of treatments with different phosphorus fertilizer sources were compared with the control using the Dunnett test and with other treatments by using student's t test. The significance level of 5% was adopted in all analysis. No significant effect was observed (P<0.05) in the evaluated traits in the first year of the experiment