Optimal nitrogen application rates for three intensively-managed hardwood tree species in the southeastern USA.

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Forest production can be limited by nutrient and water availability, and tree species are expected to respond differently to fertilization and irrigation. Despite these common expectations, multi-species comparisons are rare, especially ones implementing a range of fertilization rates crossed with irrigation. This study compares the response of three forest hardwood species to numerous nitrogen (N) fertilization levels and water availability using a novel non-replicated technique. A range of N levels was included to determine how N affected the growth response curve, and statistical procedures for comparing these non-linear response functions are presented. We used growth and yield data to calculate ... continued below

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131-142

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Coyle, David; Aubrey, Doug P.; Siry, Jacek P.; Volfovicz-Leon, Roberto R. & Coleman, Mark D. April 15, 2013.

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  • Savannah River Forest Station
    Publisher Info: USDA Forest Service, Savannah River, New Ellenton, SC
    Place of Publication: New Ellenton, South Carolina

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Forest production can be limited by nutrient and water availability, and tree species are expected to respond differently to fertilization and irrigation. Despite these common expectations, multi-species comparisons are rare, especially ones implementing a range of fertilization rates crossed with irrigation. This study compares the response of three forest hardwood species to numerous nitrogen (N) fertilization levels and water availability using a novel non-replicated technique. A range of N levels was included to determine how N affected the growth response curve, and statistical procedures for comparing these non-linear response functions are presented. We used growth and yield data to calculate the Land Expectation Value (LEV) for these intensive management treatments, and to determine the optimal growing conditions (accounting for tree productivity and grower expenses). To accomplish these objectives, we used a series of cottonwood, sycamore, and sweetgum plots that received a range of N fertilization with or without irrigation. Regression is an economical approach to define treatment responses in large-scale experiments, and we recommend >3 treatment levels so the response of any single plot does not disproportionally influence the line. The non-replicated plots showed a strong positive N response below 150 kg N ha -1 yr -1, beyond which little response was observed. However, different amounts of fertilization were required for the greatest biomass accumulation rate in each tree species. Cottonwood and sycamore growth was optimized with less than 150 kg N ha -1 yr -1 while sweetgum growth was optimized with less than 100 kg N ha -1 yr -1. Results from this experiment should be representative of many of the nutrient-poor soils in the Coastal Plain in the southeastern USA. The LEVs were not positive for any treatment x genotype combination tested when using irrigation or liquid fertilizer, but our analysis showed that several non-irrigated treatments in sycamore and sweetgum did result in positive LEVs when fertilized with granular urea.

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131-142

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  • Journal Name: Forest Ecology and Management; Journal Volume: 303; Journal Issue: 1

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  • Report No.: 13-03-P
  • Grant Number: AI09-00SR22188
  • DOI: 10.1016/j.foreco.2013.04.016 | External Link
  • Office of Scientific & Technical Information Report Number: 1080046
  • Archival Resource Key: ark:/67531/metadc842787

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Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • April 15, 2013

Added to The UNT Digital Library

  • May 19, 2016, 9:45 a.m.

Description Last Updated

  • Dec. 9, 2016, 9:35 p.m.

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Coyle, David; Aubrey, Doug P.; Siry, Jacek P.; Volfovicz-Leon, Roberto R. & Coleman, Mark D. Optimal nitrogen application rates for three intensively-managed hardwood tree species in the southeastern USA., article, April 15, 2013; New Ellenton, South Carolina. (digital.library.unt.edu/ark:/67531/metadc842787/: accessed April 22, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.