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Urban Ecosystems

, Volume 21, Issue 4, pp 657–671 | Cite as

Socioeconomic and ecological perceptions and barriers to urban tree distribution and reforestation programs

  • Leaundre C. Dawes
  • Alison E. Adams
  • Francisco J. Escobedo
  • José R. Soto
Article
  • 204 Downloads

Abstract

Tree planting and reforestation initiatives in urban and peri-urban areas often use tree distribution or “giveaway” programs as a strategy to increase tree cover and subsequent benefits. However, the effectiveness of these programs in terms of increasing overall tree cover and providing benefits to low-income and disadvantaged communities has been little studied. We assess these programs by exploring community participation in, and barriers to, an urban tree distribution program in Fort Lauderdale, United States and the role socioeconomic background and tree functional types have on participation. We use a mixed-methods approach, panel data, choice experiments, and econometrics to quantitatively analyze respondent’s ranking of program options. High income, White respondents had the highest level of awareness and participation while low income, African Americans (AA) had the lowest level. Monetary rebates were perceived as positive and significant as the compensation value increased to US$8.00 - $12.00. Fruit-bearing and native tree functional types were more preferred than flowering or shade trees. Latinos, AA, and high income respondents preferred fruit trees, while White, high income preferred native trees. Overall, low income respondents perceived the greatest barriers towards participation. 20% of Broward County residents who participated in the survey were aware of the tree giveaway programs and 13% had previously participated. Findings indicate an adaptive governance mismatch between program objectives to equitably increase city tree cover via planting shade trees versus individual’s knowledge and preference for other tree types and functions. Results can be used for developing and evaluating reforestation initiatives to equitably increase tree cover and improve the governance of urban ecosystems.

Keywords

Environmental justice Adaptive governance Urban ecosystems Best-worst-choice Urban forests Functional traits 

References

  1. Bloomington Urban Forestry Research Group (BUFRG) (2014). Interview Script for Neighborhood Leaders and Tree Planting Project Leaders, originally developed for use with the “Evaluating the Ecological and Social Outcomes of Neighborhood and Nonprofit Urban Forestry: NUCFAC Grant” project. Bloomington, IN: Bloomington Urban Forest Research Group at the Center for the Study of Institutions, Population and Environmental Change, Indiana University. 20 pp. Last updated May 22 2014. Retrieved from https://urbanforestry.indiana.edu/doc/projects/bufrg-resident-survey.pdf
  2. Chakraborty J (2006) Evaluating the environmental justice impacts of transportation improvement projects in the US. Transp Res Part D: Transp Environ 11(5):315–323CrossRefGoogle Scholar
  3. City of Orlando, Florida, (2016) One person, one tree. Retrieved from http://www.cityoforlando.net/trees/
  4. City of Portland, Oregon, (2016) It's tree planting season: Apply for a Treebate! Retrieved from https://www.portlandoregon.gov/bes/51399
  5. City Policy Associates, Washington D.C., (2008) Protecting and developing the urban tree canopy a 135-city study. U.S. Conference of MayorsGoogle Scholar
  6. Collins D (2003) Pretesting survey instruments: an overview of cognitive methods. Qual Life Res 12(3):229–238CrossRefPubMedGoogle Scholar
  7. Conway TM (2016) Tending their urban forest: Residents' motivations for tree planting and removal. Urban For Urban Green 17:23–32CrossRefGoogle Scholar
  8. Dicicco-Bloom B, Crabtree BF (2006) Making sense of qualitative research, the qualitative research interview. Med Educ 40(4):314–321CrossRefPubMedGoogle Scholar
  9. Dilley J, Wolf KL (2013) Homeowner interactions with residential trees in urban areas. Arboricult Urban For 39(6):267–277Google Scholar
  10. Dillman DA, Smyth JD, Christian LM (2014) Internet, phone, mail, and mixed-mode surveys: the tailored design method. John Wiley & Sons, HobokenGoogle Scholar
  11. Escobedo FJ, Kroeger T, Wagner JE (2011) Urban forests and pollution mitigation: analyzing ecosystem services and disservices. Environ Pollut 159(8):2078–2087CrossRefPubMedGoogle Scholar
  12. Faber D (1998) The struggle for ecological democracy: environmental justice movement in United States. Guilford, New YorkGoogle Scholar
  13. Feldman LR, (2014) Press play Fort Lauderdale: our city, our strategic plan 2018 Retrieved from http://www.fortlauderdale.gov/home/showdocument?id=4642
  14. Fischer A, Selge S, Van Der Wal R, Larson BM (2014) The public and professionals reason similarly about the management of non-native invasive species: a quantitative investigation of the relationship between beliefs and attitudes. PLoS One 9(8):e105495CrossRefPubMedPubMedCentralGoogle Scholar
  15. Flocks J, Escobedo FJ, Wade J, Varela S, Wald C (2011) Environmental justice implications of urban tree cover in Miami-Dade County, Florida. Environ Justice 4(2):125–134CrossRefGoogle Scholar
  16. Flynn TN, Louviere JJ, Peters TJ, Coast J (2007) Best–worst scaling: what it can do for health care research and how to do it. J Health Econ 26(1):171–189CrossRefPubMedGoogle Scholar
  17. Gerrish E, Watkins SL (2018) The relationship between urban forests and income: a meta-analysis. Landsc Urban Plan 170:293–308CrossRefPubMedGoogle Scholar
  18. Green OO, Garmestani AS, Albro S, Ban NC, Berland A, Burkman CE, Gardiner M, Gunderson L, Hopton ME, Schoon ML, Shuster WD (2016) Adaptive governance to promote ecosystem services in urban green spaces. Urban Ecosyst 19(1):77–93CrossRefGoogle Scholar
  19. Greene CS, Millward AA, Ceh B (2011) Who is likely to plant a tree? The use of public socio-demographic data to characterize client participants in a private urban forestation program. Urban For Urban Green 10(1):29–38CrossRefGoogle Scholar
  20. Hwang WH, Wiseman PE, Thomas VA (2017) Enhancing the energy conservation benefits of shade trees in dense residential developments using an alternative tree placement strategy. Landsc Urban Plan 158:62–74CrossRefGoogle Scholar
  21. Koeser AK, Gilman EF, Paz M, Harchick C (2014) Factors influencing urban tree planting program growth and survival in Florida, United States. Urban For Urban Green 13(4):655–661CrossRefGoogle Scholar
  22. Landry SM, Chakraborty J (2009) Street trees and equity: evaluating the spatial distribution of an urban amenity. Environ Plan 41:2651–2670CrossRefGoogle Scholar
  23. Lien PT (1994) Ethnicity and political participation: a comparison between Asian and Mexican Americans. Polit Behav 16:237–264CrossRefGoogle Scholar
  24. Lo AY, Jim CY (2015) Protest response and willingness to pay for culturally significant urban trees: implications for contingent valuation method. Ecol Econ 114:58–66CrossRefGoogle Scholar
  25. Locke DH, Grove JM (2016) Doing the hard work where it’s easiest? Examining the relationships between urban greening programs and social and ecological characteristics. Appl Spat Anal Policy 9(1):77–96CrossRefGoogle Scholar
  26. Locke DH, Roman LA, Murphy-Dunning C (2015) Why opt-in to a planting program? Long-term residents value street tree aesthetics. Arboricult Urban For 41(6)Google Scholar
  27. Locke DH, Romolini M, Galvin M, O'Neil-Dunne JP, Strauss EG (2017) Tree canopy change in coastal Los Angeles, 2009-2014. Cities Environ 10(2):3Google Scholar
  28. Loureiro ML, Arcos FD (2012) Applying best–worst scaling in a stated preference analysis of forest management programs. J For Econ 18(4):381–394Google Scholar
  29. Louviere JJ, Flynn TN (2010) Using best-worst scaling choice experiments to measure public perceptions and preferences for healthcare reform in Australia. The Patient: Patient-Centered Outcomes Research 3(4):275–283CrossRefGoogle Scholar
  30. Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and applications. Cambridge University Press, New YorkCrossRefGoogle Scholar
  31. Louviere JJ, Flynn TN, Marley AAJ (2015) Best-worst scaling: theory, methods and applications. Cambridge University Press, New YorkCrossRefGoogle Scholar
  32. Morrison M, Brown TC (2009) Testing the effectiveness of certainty scales, cheap talk, and dissonance-minimization in reducing hypothetical bias in contingent valuation studies. Environ Res Econ 44(3):307–326CrossRefGoogle Scholar
  33. Nguyen VD, Roman LA, Locke DH, Mincey SK, Sanders JR, Smith Fichman E, Duran-Mitchell M, Tobing SL (2017) Branching out to residential lands: missions and strategies of five tree distribution programs in the U.S. Urban For Urban Green 22:24–35CrossRefGoogle Scholar
  34. Pedlowski MA, Da Silva VA, Adell JC, Heynen NC (2002) Urban forest and environmental inequality in Campos dos Goytacazes, Rio de Janeiro, Brazil. Urban Ecosyst 6:9–20CrossRefGoogle Scholar
  35. Perkins HA, Heynen N, Wilson J (2004) Inequitable access to urban reforestation: the impact of urban political economy on housing tenure and urban forests. Cities 21:291–299CrossRefGoogle Scholar
  36. Pincetl S (2010) Implementing municipal tree planting: Los Angeles million-tree initiative. Environ Manag 45(2):227–238CrossRefGoogle Scholar
  37. Plant L, Rambaldi A, Sipe N (2017) Evaluating revealed preferences for street tree cover targets: a business case for collaborative investment in Leafier Streetscapes in Brisbane, Australia. Ecol Econ 134:238–249CrossRefGoogle Scholar
  38. Poe GL, Clark JE, Rondeau D, Schulze WD (2002) Provision point mechanisms and field validity tests of contingent valuation. Environ Resour Econ 23(1):105–131CrossRefGoogle Scholar
  39. Roman LA, Battles JJ, McBride JR (2014) Determinants of establishment survival for residential trees in Sacramento County, CA. Landsc Urban Plan 129:22–31CrossRefGoogle Scholar
  40. Selge S, Fischer A, Van der Wal R (2011) Public and professional views on invasive non-native species–a qualitative social scientific investigation. Biol Conserv 144(12):3089–3097CrossRefGoogle Scholar
  41. Simpson JR, McPherson EG (1998) Simulation of tree shade impacts on residential energy use for space conditioning in Sacramento. Atmos Environ 32(1):69–74CrossRefGoogle Scholar
  42. Soto JR, Adams DC, Escobedo FJ (2016) Landowner attitudes and willingness to accept compensation from forest carbon offsets: application of best–worst choice modeling in Florida USA. Forest Policy Econ 63:35–42CrossRefGoogle Scholar
  43. Soto JR, Escobedo FJ, Khachatryan H, Adams DC (2018) Consumer demand for urban forest ecosystem services and disservices: examining trade-offs using choice experiments and best-worst scaling. Ecosyst Serv 29:31–39CrossRefGoogle Scholar
  44. Summit J, McPherson EG (1998) Residential tree planting and care: a study of attitudes and behavior in Sacramento, California. J Arboric 24(2):89–97Google Scholar
  45. Szantoi Z, Escobedo F, Wagner J, Rodriguez JM, Smith S (2012) Socioeconomic factors and urban tree cover policies in a subtropical urban forest. GISci Remote Sens 49(3):428–449CrossRefGoogle Scholar
  46. U.S. Census Bureau, (2010) 2010 Census Urban and Rural Classification and Urban Area Criteria. Retrieved from https://www.census.gov/geo/reference/ua/urban-rural-2010.html
  47. U.S. Census Bureau, (2015) Community Facts for Broward County, Florida-Demographic and Housing Estimates 2011–2015 American Community Survey 5-Year Estimates. Retrieved from https://factfinder.census.gov/faces/nav/jsf/pages/community_facts.xhtml
  48. Watkins SL, Gerrish E (2018) The relationship between urban forests and race: a meta-analysis. J Environ Manag 209:152–168CrossRefGoogle Scholar
  49. Watkins SL, Mincey SK, Vogt J, Sweeney SP (2017) Is planting equitable? An examination of the spatial distribution of nonprofit urban tree-planting programs by canopy cover, income, race, and ethnicity. Environ Behav 49(4):452–482CrossRefGoogle Scholar
  50. Wyman M, Escobedo F, Varela S, Asuaje C, Mayer H, Swisher M (2011) Analyzing the natural resource extension needs of Spanish-speakers: a perspective from Florida. J Ext 49(2):n2Google Scholar
  51. Zhao M, Escobedo FJ, Staudhammer C (2010) Spatial patterns of a subtropical, coastal urban forest: implications for land tenure, hurricanes, and invasives. Urban For Urban Green 9(3):205–214CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Leaundre C. Dawes
    • 1
  • Alison E. Adams
    • 1
  • Francisco J. Escobedo
    • 2
  • José R. Soto
    • 3
  1. 1.School of Forest Resources and ConservationUniversity of FloridaGainesvilleUSA
  2. 2.Facultad de Ciencias Naturales y Matemáticas, Programa de BiologíaUniversidad del RosarioBogotá D.C.Colombia
  3. 3.School of Natural Resources and the EnvironmentThe University of ArizonaTucsonUSA

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