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Intro for asm workshop see

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Intro for asm workshop see

  1. 1. Visit our website: www.quantifyinguncertainty.org Download papers and presentations Share sample code Stay updated with QUEST News Join our mailing list (quantifyinguncertainty@gmail.com) Send papers for bibliographies, write papers for our Special Feature in Ecosphere Follow us on Twitter @QUEST_RCN Join QUEST!
  2. 2. We don’t want to sample too little and not detect an important effect. But collecting and analyzing samples is expensive, so we don’t want to sample more intensively than necessary. Quantifying the relationship between sampling intensity and minimum detectable differences can help Better Monitoring through Uncertainty Analysis: Optimize allocation of effort, save time and money
  3. 3. Plan for the Workshop Introductions: name, where you are from, what you monitor, what are your concerns (too much, too little, how can we help you today) Presentations (5 minutes each, followed by discussion, no more than 10 minutes total for each) • Craig See: Taxonomy of Uncertainty, Results of the QUEST Survey (we may not know what uncertainties are important) • Christine Laney: NEON examples • Mark Green: rain gauge reduction example (HBR) • Yang Yang: Hg monitoring, loons and fish (detectable difference or rate of change) • Ruth Yanai: NH roots, Calhoun soils (detectable difference or rate of change) • Alex Young: monitoring measurement uncertainty in the FIA (confidence in inputs, waiting on sensitivity) General Discussion: Did this help you? What do you still need, and how can we help with that?
  4. 4. Current Practices in Reporting Uncertainty in Ecosystem Ecology Ruth Yanai, State University of New York Craig See, University of Minnesota John Campbell, United States Forest Service
  5. 5. Taxonomy of Uncertainty
  6. 6. Survey Distribution Listserves: Additional Distribution:
  7. 7. Survey Demographics 135 respondents 90 sites >13 Countries, 6 Continents All Current LTER sites
  8. 8. Survey Methods Respondents were asked: • How they identify unusable values • How they handle missing/unusable values • How they deal with values below detection • Whether these methods are standardized at their site
  9. 9. Survey Methods Identified major sources of uncertainty in: For each source respondents were asked: • If they report the source • If they know how to report the source • If they feel the source is important Streams Precipitatio n Soils Biomass
  10. 10. (Campbell et al. 2016)
  11. 11. (Campbell et al. 2016) Higher confidence in Ca losses (streams) than inputs (rainfall) at Hubbard Brook
  12. 12. Importance to net Ca flux at Hubbard Brook Precip. chem. gaps Precip. chem. analysis Streamflow gaps Stream chem. analysis Watershed area Stream flux calculation Precip. catch Precip interpolation model Precip volume gaps Gage/discharge model Stream flux calculation Gage/discharge model Stream chem. analysis Streamflow gaps Precip. catch Watershed area Precip chem. analysis Precip volume gaps Precip interpolation model Precip. chem. gaps Survey importance ranking
  13. 13. Summary We did a survey It can be hard to tell which sources of uncertainty matter, so it’s important to formally check This can save you time and money! You can do more with less!
  14. 14. Thank You

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