Bis(tetra­phenyl­phospho­nium) bis­[N-(phenyl­sulfon­yl)dithio­carbimato-κ2 S,S′]platinate(II) monohydrate

The asymmetric unit of the title compound, (C24H20P)2[Pt(C7H5NO2S3)2]·H2O, consists of two tetra­phenyl­phospho­nium cations, two half bis­[N-(phenyl­sulfon­yl)dithio­carbim­ato]platinate(II) dianions and one water mol­ecule. The anions are completed by crystallographic inversion symmetry associated with the central PtII ion. The PtII ion is doubly S,S′-chelated by two symmetry-related phenyl­sulfonyl­dithio­carbimate ligands, forming a slightly distorted square-planar configuration. Besides the electrostatic attraction between oppositely charged ions in the crystal packing, intra­molecular C—H⋯O and several inter­molecular C—H⋯O, C—H⋯N and O—H⋯O hydrogen-bonding inter­actions between the cations, anions and water mol­ecules are observed

Amazonia Camtrap: a data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest.

Abstract : The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scatteredacross the published, peer-reviewed, and gray literature and in unpublishedraw 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 Amazonregions to compile the most extensive data set of inventories of mammal,bird, and reptile species ever assembled for the area. The complete data setcomprises 154,123 records of 317 species (185 birds, 119 mammals, and13 reptiles) gathered from surveys from the Amazonian portion of eightcountries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru,Suriname, and Venezuela). The most frequently recorded species per taxawere: mammals:Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles:Tupinambis teguixin(716 records). The infor-mation detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a moreaccurate evaluation of the effects of habitat loss, fragmentation, climatechange, and other human-mediated defaunation processes in one of themost important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when usingits data in publications and we also request that researchers and educator sinform us of how they are using these data

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