The Economic Value of Water and Ecosystem Preservation

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4.4.2. Production Function Approach - Data Data was also gathered from the USGS for inflows at Tivoli on the Guadalupe River which is below the confluence of the San Antonio and Guadalupe River, for the year 2000 - 2006. Rainfall data was also gathered as days of precipitation per month for the Aransas Wildlife Refuge. Finally, the main winter tourist season is from around December through February, while the greatest number of tourists is during the summer months (Morehead, Beyer et al., 2007). Tourist inflows are also influenced by bird migrations, in particular, the winter nesting of the whooping cranes which occurs from October to April. Dummy variables were constructed to account for tourist seasons and the Whooping Crane nesting period. 4.4.3. Production Function Approach – Analysis and Results The production function model was constructed based on various factors discussed previously. The output was designated as the monthly number of visitors to the Aransas Wildlife Refuge. The main input was average monthly inflows to San Antonio Bay as measured the Tivoli Station on the Guadalupe River. Other included factors attempted to account for correlation including nesting times for the whooping crane, rainfall, peak period for winter Texans, and summer holidays. As discussed earlier, an analysis was conducted to look at correlation between inflow data and visitor numbers. The strongest correlations were found for same month inflows (positive), flows lagged by 6 months (negative) and flows lagged 18 months (negative). Figure 4-4 below illustrates the monthly average flows (2000-2006) as reported at the Tivoli gauging station compared to the average number of visitors to the AWR (2001-2007). The low flow period matches with the lower visitor numbers, which may be simply be a coincidence in the data caused by the 6 month intervals between low and high flows. There are spikes in the visitor data for March from an up-tick in boat tours and also in October from bow hunters. An eco-tourism production function was specified as the monthly number of visitors to the Aransas National Wildlife Refuge as a function of several variables. The independent variables included: • “Flow_Tiv” - The monthly average flow as measured at the Tivoli gauging station; • “AWR_Precip - The total monthly precipitation at the Aransas National Wildlife Refuge; • “Holiday”- Dummy variable for summer holiday period (June-August); • “Nesting” - Dummy variable for whooping Crane winter nesting (October-April); and, • “ Winter_TX” - Dummy variable for peak Winter Texans (December- February) 40
The results of the regression yield an adjusted r-squared value of 0.62. The dummy variable for whooping crane nesting season was the only significant variable. Water inflows were positive in sign with a t-stat of 1.05. Results of the regression are presented in Table 4-3. Figure 4-4. Average number of visitors to AWR and average flow from the Tivoli gauging station on the Guadalupe River Flow (cfs) / Visitors (ppl) 10,000 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Table 4-3. Result of regression of impact of freshwater inflows on visitor numbers Standard Coefficients Error t Stat Intercept 556.31 1904.49 0.29 Flow_Tiv 2.16 2.06 1.05 Flow_Tiv_Squared -0.00047 0.00 -0.89 AWR_Precip -0.66 0.65 -1.01 Holiday -356.91 611.59 -0.58 Nesting 3615.56 579.37 6.24 Winter_TX -280.98 547.63 -0.51 41 Avg Flow Avg Visitor
Page 1 and 2: Final Report to the Texas Coastal M
Page 3 and 4: 5.2.2. Sources / Data .............
Page 5 and 6: Executive Summary The San Antonio B
Page 7 and 8: ecotourism included in the model. T
Page 9 and 10: 1. Overview of San Antonio Bay Regi
Page 11 and 12: and shellfish species and estuarine
Page 13 and 14: According to the Rockport-Fulton Ch
Page 15 and 16: effect is limited by assimilative c
Page 17 and 18: freshwater inflow acts as a mechani
Page 19 and 20: sulfide. Heavy metals bounds to sed
Page 21 and 22: inflow levels and populations of se
Page 23 and 24: and could potentially make the cran
Page 25 and 26: 3. Characterization of Ecotourism i
Page 27 and 28: Contributes actively to the conserv
Page 29 and 30: Figure 3-1. Public Protected Areas
Page 31 and 32: 1987 and then purchased in 1991. Pr
Page 33 and 34: 3.3.2. The Economics of Multiple Na
Page 35 and 36: Table 3-2. Average Willingness to P
Page 37 and 38: Table 3-3. Personal Income and Prod
Page 39 and 40: impact. It is necessary to conduct
Page 41 and 42: 4.2. Key Site Details for the Analy
Page 43 and 44: approach allows examination of ques
Page 45 and 46: This average number of trips from t
Page 47: occasional flood and drought events
Page 51 and 52: gallons, which results in a value o
Page 53 and 54: Aransas distinguishes itself from C
Page 55 and 56: thresholds vary according the size
Page 57 and 58: The total number of full-time and p
Page 59 and 60: The County also shows a lower educa
Page 61 and 62: Refugio shows a rapid decrease in t
Page 63 and 64: IM t+ n ic = E t ic ⎡⎛ E × ⎢
Page 65 and 66: included an economic analysis of th
Page 67 and 68: Table 5-5. Employment Shift-Share A
Page 69 and 70: Fishing and related activities. The
Page 71 and 72: Figure 5-15. Employment change by s
Page 73 and 74: 5.3.2. Input-Output Analysis The in
Page 75 and 76: Calhoun Calhoun County’s experien
Page 77 and 78: an advantage, particularly in oyste
Page 79 and 80: Impacts on the Freshwater Inflows t
Page 81 and 82: However, due to the lack of consist
Page 83 and 84: This implicitly assumes that flows
Page 85 and 86: for fresh product. This fishery wil
Page 87 and 88: Elliot, D. (2007). Competitive Adva
Page 89 and 90: Pearce, D. W. (1994). The MIT Dicti
Page 91 and 92: The Nature Conservancy. (2002). "Na

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