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New Tools for Interpreting Foliar Nutrient Status

This document outlines innovative methods for evaluating foliar nutrient status which are crucial for effective fertilization strategies in forestry. It emphasizes the significance of foliar analysis as a planning tool to confirm nitrogen deficiencies, identify secondary nutrient deficiencies (like sulfur and boron), and formulate appropriate fertilizer prescriptions. The guide also details foliar sampling protocols, including optimal timing and methods for collecting foliage. Additionally, it addresses factors affecting the interpretation of nutrient data, ensuring accurate decision-making based on reliable diagnostic information.

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New Tools for Interpreting Foliar Nutrient Status

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  1. New Tools for Interpreting Foliar Nutrient Status Fertilization Working Group February 8, 2012

  2. Operational fertilization decision-making • Forest level considerations • Stand level considerations • operational factors • biological factors • species • stand structure • crown conditions • insect/disease • nutrient status

  3. Foliar analysis as a planning tool • Foliar analysis can be used to: • confirm N deficiency

  4. Foliar analysis as a planning tool • Foliar analysis can be used to: • confirm N deficiency • identify secondary nutrient deficiencies (e.g., S, B)

  5. Foliar analysis as a planning tool • Foliar analysis can be used to: • confirm N deficiency • identify secondary nutrient deficiencies (e.g., S, B) • make appropriate fertilizer prescriptions

  6. Foliar analysis as a planning tool • Foliar analysis can be used to: • confirm N deficiency • identify secondary nutrient deficiencies (e.g., S, B) • make appropriate fertilizer prescriptions • assess post-fertilization nutrient uptake and foliar nutrient balance

  7. Foliar Sampling Protocol

  8. Foliar Sampling Protocol • Sample during the dormant season

  9. Seasonal change in foliar %N in Douglas-fir foliage Moderate deficiency May Dec June July Aug Sept Oct Nov Month

  10. Seasonal change in foliar %N in Douglas-fir foliage Moderate deficiency May Dec June July Aug Sept Oct Nov Month

  11. Foliar Sampling Protocol • Sample during the dormant season • Sample current year’s foliage

  12. Foliar Sampling Protocol • Sample during the dormant season • Sample current year’s foliage • Collect foliage from between top 1/4 and bottom 1/2 of live crown

  13. Foliar Sampling Protocol • Sample during the dormant season • Sample current year’s foliage • Collect foliage from between top 1/4 and bottom 1/2 of live crown • Collect foliage from healthy, representative trees

  14. Foliar Sampling Protocol • Sample during the dormant season • Sample current year’s foliage • Collect foliage from between top 1/4 and bottom 1/2 of live crown • Collect foliage from representative trees • Collect foliage from at least 20 trees per stand or stratum

  15. Foliar sampling layout Road x x x x x x x x Line 2 x x Line 1 x x x x x x /01 x x x x /02

  16. Foliar Sampling Protocol • Sample during the dormant season • Sample current year’s foliage • Collect foliage from between top 1/4 and bottom 1/2 of live crown • Collect foliage from representative trees • Collect foliage from at least 20 trees per stand or stratum • For routine diagnoses, combine equal amounts of foliage from individual trees into one composite sample per stratum

  17. Foliar Sampling Protocol • Sample during the dormant season • Sample current year’s foliage • Collect foliage from between top 1/4 and bottom 1/2 of live crown • Collect foliage from representative trees • Collect foliage from at least 20 trees per stand or stratum • For routine diagnoses, combine equal amounts of foliage from individual trees into one composite sample per stratum • Keep samples cool until foliage is dried

  18. Factors affecting interpretation of foliar nutrient data

  19. Factors affecting interpretation of foliar nutrient data • Foliar sampling protocol

  20. Factors affecting interpretation of foliar nutrient data • Foliar sampling protocol • Site ecological characteristics

  21. from DeLong (2003)

  22. from DeLong (2003)

  23. Factors affecting interpretation of foliar nutrient data • Foliar sampling protocol • Site ecological characteristics • Laboratory analytical methodology

  24. Relationship between foliar N analytical methodologiesdry combustion vs. wet digestion

  25. Relationship between foliar S analytical methodologies dry combustion vs. wet digestion

  26. Accounting for differences in laboratory analytical methodology • Differences may be large enough to affect interpretation

  27. Accounting for differences in laboratory analytical methodology • Differences may be large enough to affect interpretation • Nutrient interpretative criteria do not account for differences in methodology

  28. Accounting for differences in laboratory analytical methodology • Differences may be large enough to affect interpretation • Nutrient interpretative criteria do not account for differences in methodology • Known differences in laboratory analytical results can be used to “normalize” foliar data prior to interpretation

  29. Accounting for differences in laboratory analytical methodology • Differences may be large enough to affect interpretation • Nutrient interpretative criteria do not account for differences in methodology • Known differences in laboratory analytical results can be used to “normalize” foliar data prior to interpretation • “Normalization” requires inter-laboratory comparisons

  30. Accounting for differences in laboratory analytical methodology • Differences may be large enough to affect interpretation • Nutrient interpretative criteria do not account for differences in methodology • Known differences in laboratory analytical results can be used to “normalize” foliar data prior to interpretation • “Normalization” requires inter-laboratory comparisons • The “normalization” process does not make inferences about the quality of foliar nutrient data

  31. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment

  32. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously collected Pl foliage samples were selected

  33. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously analyzed Pl foliage samples were used • Samples were selected to cover a broad range of foliar nutrient levels

  34. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously analyzed Pl foliage samples were used • Samples were selected to cover a broad range of foliar nutrient levels • Each sample was thoroughly mixed and split into two sub-samples

  35. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously analyzed Pl foliage samples were used • Samples were selected to cover a broad range of foliar nutrient levels • Each sample was thoroughly mixed and split into two sub-samples • One sub-sample was shipped to each lab in December 2011

  36. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously analyzed Pl foliage samples were used • Samples were selected to cover a broad range of foliar nutrient levels • Each sample was thoroughly mixed and split into two sub-samples • One sub-sample was shipped to each lab in December 2011 • For each nutrient, laboratory results were reviewed and subjected to regression analysis

  37. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously analyzed Pl foliage samples were used • Samples were selected to cover a broad range of foliar nutrient levels • Each sample was thoroughly mixed and split into two sub-samples • One sub-sample was shipped to each lab in December 2011 • For each nutrient, laboratory results were reviewed and subjected to regression analysis • Based on previous research, equations were selected to “normalize” foliar nutrient data

  38. Inter-laboratory comparisonPacific Soil Analysis vs. Ministry of Environment • 48 previously analyzed Pl foliage samples were used • Samples were selected to cover a broad range of foliar nutrient levels • Each sample was thoroughly mixed and split into two sub-samples • One sub-sample was shipped to each lab in December 2011 • For each nutrient, laboratory results were reviewed and subjected to regression analysis • Based on previous research, equations were selected to “normalize” foliar nutrient data • An Excel spreadsheet was developed to facilitate “normalization” for practitioners

  39. Laboratory foliar N comparison PSAI vs. MoE

  40. Laboratory foliar S comparison PSAI vs. MoE

  41. Laboratory foliar SO4-S comparison PSAI vs. MoE

  42. “Normalization” of laboratory foliar nutrient data

  43. “Normalization” of laboratory foliar nutrient data

  44. “Normalization” of laboratory foliar nutrient data

  45. “Normalization” of laboratory foliar nutrient data

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