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A spatially explicit tree search application for agroforestry in the United States

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Abstract

A spatially explicit application has been developed for the conterminous United States to assist farmers and extension agents with selecting appropriate tree species for agroforestry applications. The application combines several spatially explicit databases of tree species, high-resolution soil data, and climate. On the front-end of the application, a simple graphical user interface (GUI) allows the user to indicate their location, the size of the area to be searched, and the functional use category for the trees. These parameters are used to query a PostGRESQL relational database management system on the back-end via a Python script. All tree species within the user-specified area and matching the user-specified objectives, are returned to the web page along with tree characteristics, and soil and climate data for the specified location. Expert feedback on the application was solicited and used to make improvements to the service. The accuracy of the application was tested at several locations in Missouri, USA, and found satisfactory.

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References

  • Butler PR, Iverson L, Thompson FR, Brandt L, Handler S, Janowiak M et al (2015) Central Appalachians forest ecosystem vulnerability assessment and synthesis: a report from the Central Appalachians Climate Change Response Framework project. General Technical Report, NRS-146. US Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, vol 146, pp 1–310

  • Daly C, Widrlechner MP, Halbleib MD, Smith JI, Gibson WP (2012) Development of a new USDA plant hardiness zone map for the United States. J Appl Meteorol Climatol 51(2):242–264

    Article  Google Scholar 

  • Digitized Plant Hardiness Zone Map (2015) Open Plant Hardiness Zone. https://github.com/wboykinm/ophz/tree/master. Accessed 2 Feb 2016

  • Ellis EA, Nair PKR, Linehan PE, Beck HW, Blanche CA (2000) A GIS-based database management application for agroforestry planning and tree selection. Comput Electron Agric 27(1):41–55

    Article  Google Scholar 

  • Ellis EA, Bentrup G, Schoeneberger MM (2004) Computer-based tools for decision support in agroforestry: current state and future needs. Agroforestry Systems 61:401–421

  • Ellis EA, Nair PKR, Jeswani SD (2005) Development of a web-based application for agroforestry planning and tree selection. Comput Electron Agric 49(1):129–141

    Article  Google Scholar 

  • GBIF.org (4th April 2016) GBIF Occurrence Download. http://doi.org/10.15468/dl.y1uhtm

  • U.S. Geological Survey (1999) Digital representation of “Atlas of United States Trees” by Elbert L. Little, Jr.

  • Graymore ML, Wallis AM, Richards AJ (2009) An Index of regional sustainability: a GIS-based multiple criteria analysis decision support system for progressing sustainability. Ecol Complex 6(4):453–462

    Article  Google Scholar 

  • Gunderson CA, Edwards NT, Walker AV, O’Hara KH, Campion CM, Hanson PJ (2012) Forest phenology and a warmer climate–growing season extension in relation to climatic provenance. Glob Change Biol 18(6):2008–2025

    Article  Google Scholar 

  • Jacke D, Toensmeier E (2005) Edible forest gardens, volume II: ecological design and practice for temperate-climate permaculture. Chelsea Green Publishing, White River Junction, Vermont

    Google Scholar 

  • Jones KS, Costello LR (2007) Selecting fruit, nut, and berry crops for home gardens in San Mateo and San Francisco Counties Publication 8261 (2007)

  • Jose S (2011) Managing native and non-native plants in agroforestry systems. Agrofor Syst 83(2):101

    Article  Google Scholar 

  • Luedeling E, Zhang M, Girvetz EH (2009) Climatic changes lead to declining winter chill for fruit and nut trees in California during 1950––2099. PLoS ONE 4(7):e6166. https://doi.org/10.1371/journal.pone.0006166

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • McKENNEY DW, Pedlar JH, Lawrence K, Campbell K, Hutchinson MF (2007) Beyond traditional hardiness zones: using climate envelopes to map plant range limits. Bioscience 57(11):929–937

    Article  Google Scholar 

  • Orwa C (2010) Agroforestree Database 4.0: a tree reference and selection guide. World Agroforestry Centre

  • Park IW, Schwartz MD (2015) Long-term herbarium records reveal temperature-dependent changes in flowering phenology in the southeastern USA. Int J Biometeorol 59(3):347–355

    Article  PubMed  Google Scholar 

  • Plants for a Future (PFAF) (2011), Plant Database Search. (n.d.). http://www.pfaf.org/user/plantsearch.aspx. Retrieved 11 June 2011

  • Soil Survey Staff (2014). Gridded Soil Survey Geographic (gSSURGO) Database for the United States of America and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS. United States Department of Agriculture, Natural Resources Conservation Service. http://datagateway.nrcs.usda.gov/. 20 Feb 2016 (FY2014 official release)

  • University of Missouri-Columbia. Center for Agroforestry (2015) Training manual for applied agroforestry practices. University of Missouri Center for Agroforestry

  • Vegetation Impact Program (VIP), Midwestern Regional Climate Center (2016) Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign. Mrcc.isws.illinois.edu/VIP/page_name.html. Accessed 25 Apr 2016

  • Vogel KP, Schmer MR, Mitchell RB (2005) Plant adaptation regions: ecological and climatic classification of plant materials. Rangel Ecol Manag 58(3):315–319

    Article  Google Scholar 

  • Wallace DC, Young FJ (2008). Black walnut suitability index: a natural resources conservation service national soil information system based interpretive model. In: Proceedings, 16th Central Hardwood forest conference, West Lafayette, IN, pp 589–595

  • Widrlechner MP, Daly C, Keller M, Kaplan K (2012) Horticultural applications of a newly revised USDA plant hardiness zone map. HortTechnology 22(1):6–19

    Article  Google Scholar 

  • Wilson BT, Lister AJ, Riemann RI (2012) A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data. For Ecol Manag 271:182–198

    Article  Google Scholar 

  • Wilson BT, Lister AJ, Riemann RI, Griffith DM (2013) Live tree species basal area of the contiguous United States (2000–2009). USDA Forest Service, Rocky Mountain Research Station, Newtown Square. https://doi.org/10.2737/RDS-2013-0013

    Book  Google Scholar 

  • Woodall CW, Oswalt CM, Westfall JA, Perry CH, Nelson MD, Finley AO (2009) An indicator of tree migration in forests of the eastern United States. For Ecol Manag 257(5):1434–1444

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank all the agroforestry professionals and land managers who gave feedback on the application.

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Correspondence to Michael Borucke.

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Borucke, M., Howard, D. & Jose, S. A spatially explicit tree search application for agroforestry in the United States. Agroforest Syst 94, 831–842 (2020). https://doi.org/10.1007/s10457-019-00462-9

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