Open metas is a reproducible tool for restoration ecology

Cdb758075f7b54ea4ef646898497ecf3?s=47 cjlortie
April 11, 2019

Open metas is a reproducible tool for restoration ecology

A set of ideas for the Society for Ecological Restoration 2019 annual meeting.



April 11, 2019


  1. @cjlortie open meta-analysis is a reproducible environmental solution

  2. None
  3. challenge couple popular ideas & assumptions with evidence

  4. big picture

  5. science will not advance by mere accumulation of data

  6. implicit biases and compelling case studies can mislead

  7. guarantee surprises syntheses

  8. we assumed fisheries can rebound

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  10. 700 spawner–recruit relationships illustrated that most commercial marine fishes produce

    less than 5 viable young a year at low population sizes
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  13. too little, too late but we had the data

  14. wind turbines kill birds (and bats)

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  16. 124 articles, 15 met criteria, 19 datasets

  17. short term bird abundance studies do not provide robust indicators

    of the potentially deleterious impacts of windfarms on bird abundance small sample sizes are a critical issue
  18. identified acceptable risks and windfarms moved forward in the UK

  19. updated meta in 2017 confirmed we made the right call

  20. need to resolve scales & heterogeneity

  21. novelty of open metas for environmental issues needs-driven critical evidence

    of what we know and what we do not paradigm change
  22. challenge to do syntheses well

  23. never vote count

  24. methods 1. Search 2. Sort 3. Synthesize 4. Summarize

    5. Statistics
  25. effect sizes are the key

  26. weighted measure of difference

  27. means variance sample sizes

  28. search sort

  29. synthesize summarize

  30. statistics

  31. meta-analysis in titles of environmental science & studies publications

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  36. all meta-challenges can now be overcome bias heterogenic data context

    scale poor quality studies
  37. biology for environmental management studies > combine > directly examine

    local versus regional solutions
  38. tools bibliometrics transparency team science rstats common sense

  39. implications: connect studies many issues have a long story arc

    in science so must be reproducible
  40. defence against the dark arts

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  45. evidence-based decision making

  46. the future open data effect sizes in primary research evidence

    thresholds reuse less Ps, more Qs