Search

Fake controversies have influenced policy making on health and environmental issues for decades, resulting in major implementation setbacks worldwide. As a case study, in this paper we examine fake controversies produced by a small group of active Brazilian researchers that have seriously impacted environmental conservation, particularly in issues related to deforestation and climate change. Based on the literature, we develop a typology of strategies deployed in fake controversies, which include manufacturing uncertainty, misusing scientific credentials, and disregarding scientific literature. Afterwards, we examine the influence of this group of contrarians at the National Congress. We then analyze the fake controversies promoted by these contrarians and argue that, to properly understand them, we need to consider a strategy so far overlooked in the literature: the manufacture of "pseudo-facts", namely, affirmations at odds with the established literature but that strives to appear as scientific facts. Unlike other contexts, in which contrarians have mainly sought to cast doubt on consensual issues by arguing that there are still considerable uncertainties surrounding them, in Brazil pseudo-facts on deforestation have been produced and published outside the peer-reviewed literature. We conclude the study with recommendations on how to oppose fake scientific controversies that threaten environmental conservation in general. [ABSTRACT FROM AUTHOR]

Abstract: Optical imagery can reveal spectral properties of forest canopy, which rarely allows for finding accurate correspondence of canopy features with soils and hydrology. In Amazonia non-floodable swampy forests can not be easily distinguished from non-floodable terra-firme forests using just bidimensional spectral data. Accurate topographic data are required for the understanding of land surface processes at finer scales. Topographic detail has now become available with the Shuttle Radar Topographic Mission (SRTM) data. This new digital elevation model (DEM) shows the feature-rich relief of lowland rain forests, adding to the ability to map rain forest environments through many quantitative terrain descriptors. In this paper we report on the development of a new quantitative topographic algorithm, called HAND (Height Above the Nearest Drainage), based on SRTM-DEM data. We tested the HAND descriptor for a groundwater, topographic and vegetation dataset from central Amazonia. The application of the HAND descriptor in terrain classification revealed strong correlation between soil water conditions, like classes of water table depth, and topography. This correlation obeys the physical principle of soil draining potential, or relative vertical distance to drainage, which can be detected remotely through the topography of the vegetation canopy found in the SRTM-DEM data. [Copyright &y& Elsevier]

Height Above the Nearest Drainage (HAND), a state-of-the-art topo-hydrological index, has been increasingly used in geo-environmental studies. It describes the local normalized drainage potential of a large region. To date, a trial and error and cumbersome multistep process has been used to obtain the HAND index which does not result in an optimal threshold for contributing area. This study aims at developing a user-friendly geographic information system (GIS) tool, HANDTool, using the Python programming language. We successfully applied the tool for the Chehel-Chai watershed, Iran and the random forest algorithm was used to model groundwater potential. Results revealed that the HAND index made a great contribution to groundwater potential modeling among the other conditioning factors. This tool gives valuable insights on the soil-topography-moisture shared interactions and vegetation condition, especially in ungauged watersheds. [ABSTRACT FROM AUTHOR]