Arboriculture & Urban Forestry 37(4): July 2011 This study asked whether attributes of state and federal U&CF programs within the 50 United States are related or explain in- creased local urban forestry activity. First, the study authors examined whether urban forestry activity within local U&CF programs had increased. Attributes of state U&CF programs were then tested with an a priori multiple regression model that included indicators of technical assistance, financial assistance, and program money sources to determine if these were related to increased local urban forestry activity. These indicators were hypothesized to have an effect based on prior studies (Baugman 1980; Still et al. 1996; Vitosh and Thompson 2000; Bird 2002). Then, sequential and stepwise multiple regression techniques were used to explore if other indicators of state U&CF programs further explained an increase in local urban forestry activity. METHODS Study Questions Data Sources Data used in this study was obtained from two sources. First, the USFS Performance Measures and Accountability System (PMAS) data for all 50 states (available by request from the USDA Forest Service, Northeastern Area State & Private Forestry, Newtown Square, PA) was used to determine local U&CF activity as the de- pendent variable (Appendix; Table 1). The study authors used the PMAS data as it was developed to measure urban forestry activity at the local level. The PMAS methods (USDA-FS 2003) guide state U&CF coordinators to group communities into either an in- active ranking (no demonstrated urban forestry activity) or one of four activity rankings (project, formative, developmental, and sustained). Community activity increases from the lowest (proj- ect) to highest (sustained). Community activity rankings were de- veloped by state U&CF program leaders using USFS guidelines for each geographical political subdivision (community) with 100 or more people within a state. Second, a self-administered questionnaire completed by state U&CF program coordinators Description Three study questions were created before data analysis: 1) Has lo- cal urban forestry activity increased nationally between 1997 and 2002, within each PMAS activity level and at the composite (sum of all four) activity levels? 2) Are U&CF program indicators and attributes of financial assistance, technical assistance, and program money sources related to effective state programs, with effective being interpreted as an increase in the composite local-level urban forestry program activity within a state? 3) Are there other attri- butes or indicators of state U&CF programs related to a change in the composite local-level urban forestry activity within a state? Statistical Procedure Descriptive statistics, t-tests, correlation, and multiple regression modeling used SPSS version 18.0. A paired t-test was used to test for differences in local urban forestry activity between 1997 and 2002. Scaling of continuous variables was done by dividing the dependent and independent variables by the number of com- munities in each state. It is possible that nonscaled results may Table 1. Model variables used in the a priori models and exploratory models. Variables Dependent Variables used in a priori, Exploratory, and Validation Models ActDiff z Dependent variable derived from the change in urban forestry activity at the local level between 1997 and 2002 as reported in PMAS. Initial a priori Independent Test Variables TechFreq An index that captured how frequent 27 technical assistance indicators ranged from never = 0, to frequent = 3, were offered FinAsstz TechAsstz FedGrant StaGrant FedMoneyz StaMoneyz Number of communities provided financial assists annually within a state Number of communities provided technical assists annually within a state Bivariate indicator of a state either providing or not providing Federal Cooperative Forestry Assistance Challenge Cost-share Grants to communities Bivariate indicator of a state either providing or not providing state grants Amount of federal money only that funds the state U&CF program Amount of state money only that funds the state U&CF program Exploratory Independent Test Variables EnabLeg Bivariate indicator of a state having or not having enabling legislation from state statute that authorizes the program FTEz Agency Indicator of level of coordination within a state with ranking from not occurring = 0, to excellent = 4 Number of urban forestry positions in full-time equivalents within the state agency housing the state U&CF program Bivariate indicator of the state agency that houses the state U&CF program providing adequate attention to the state U&CF program OtherAgn Indicator of frequency of other agencies and entities in a state providing technical assistance with ranking from never = 0, to frequently = 3 Coordin ProgYear Year the state U&CF program was initiated FundAdeq Adequacy of current funding from all sources based on identified program needs with ranking from very inadequate = 0, to very adequate = 3 Council StraPlan Perception of how well a state council functions overall in coordination of U&CF programs in a state from no effect = 0, to excellent = 4 Input into development of strategic plan with no input from outside sources = 0, to state U&CF council led development = 4 z Scaled variable by dividing by number of communities in the state from which the data were derived. 153 was used to develop the model data set of independent variables (Appendix). Portions of the 16-page questionnaire used for this study asked staffing levels, state and federal money for program operation and grants, technical assistance types and frequency, year program started, other agencies who provide state U&CF assistance, program coordination, input with developing the state U&CF strategic plan, and state council coordination. State U&CF coordinators are responsible for delivery of U&CF assis- tance to local urban forestry programs and document local-level assistance provided and outcomes. Questionnaire delivery used the Tailored Design Method and 84% of the 50 state U&CF coor- dinators responded, with all questionnaires usable except for one returned but not completed (Hauer 2005; Dillman 2007; Hauer and Johnson 2008). Non-response error or non-item response error was not detected (Hauer 2005; Hauer and Johnson 2008). ©2011 International Society of Arboriculture
July 2011
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