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5/21/2018  |   2:15 PM - 2:30 PM   |  CONNECTING LONG-TERM DATA WITH FINE-SCALE VARIATION: USING REMOTE SENSING TO EVALUATE SPATIOTEMPORAL DYNAMICS OF DRYLAND PONDS   |  310 B

CONNECTING LONG-TERM DATA WITH FINE-SCALE VARIATION: USING REMOTE SENSING TO EVALUATE SPATIOTEMPORAL DYNAMICS OF DRYLAND PONDS

In the American Southwest, lentic habitats are threatened by unsustainable water use and projections of more frequent, extreme drought. Small, manmade lentic habitats such as cattle ponds may provide critical habitat for aquatic organisms when natural habitats are lost. However, spatiotemporal dynamics of lentic habitat availability in this region are poorly understood, including spatial distribution and hydroperiod dynamics of manmade ponds. To address this knowledge gap, we asked: (1) How are manmade ponds spatially distributed in this region? (2) Which ponds are permanent, and which are intermittent? (3) What are the hydroperiod dynamics of these ponds, and do they change over time? To answer these questions, we used graph theory and spectral mixture analysis to analyze 33 consecutive years (1984-2017) of satellite imagery in Coronado National Forest, Arizona. Understanding and quantifying the spatiotemporal dynamics of these ponds can help link fine-scale environmental variability to aquatic community dynamics – an important step in managing aquatic habitats, biotic communities, and water demands in an area with increasing water demands and decreasing water supply.

  • Remote Sensing
  • Connectivity
  • Biodiversity

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Presenters/Authors

Mary Farruggia (), Virginia Tech, mfarrugg@vt.edu;


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Meghan Halabisky (), University of Washington, halabisk@u.washington.edu;


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Meryl C. Mims (), Virginia Tech, mims@vt.edu;


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