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Filters: Tags: Data and Information Assets (X) > partyWithName: John B Bradford (X) > partyWithName: Caitlin M Andrews (X)

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Droughts are becoming more frequent and severe and this trend is expected to continue in the coming century. Drought effects on natural resources include reduced water availability for plants and humans, as well as increased insect, disease, and vegetation mortality. Land managers need more information regarding how water availability may change and how drought will affect their sites in the future. We developed an online, interactive application that allows natural resource managers to access site-specific, observed historical and predicted future water availability. Users are able to set information that affects water balance, including soil texture and vegetation composition. With these inputs, as well as site-specific...
Natural resources managers are regularly required to make decisions regarding upcoming restoration treatments, often based on little more than business as usual practices. To assist in the decision-making process, we created a tool that predicts site-specific soil moisture and climate for the upcoming year, and provides guidance on whether common restoration activities (i.e. seeding, planting) will be successful based on these conditions. This tool is hosted within the Land Treatment Exploration Tool (LTET), an application already used by land managers that delivers a report of site condition and treatment history. Incorporated within the short-term drought forecaster (STDF) is a rigorous statistical process,...
Drought is a major problem in the American Southwest that is expected to worsen under the effects of climate change. Currently, the Southwest Biological Science Center is monitoring the effects of drought with soil moisture probes in a range of ecosystems across an elevational gradient on the Colorado Plateau. These data are used in multiple studies to analyze the effects of drought on vegetation composition and demography. Accessing and analyzing that data still relies on traditional site visits, which can result in delayed recognition of erroneous data, a common pitfall in many field-science operations. We propose to improve upon this traditional data workflow by leveraging the use of Internet of Things (IoT)...