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Recreational Fishing and Other Water Based Recreation

Recreational Fishing and Other Water Based Recreation. Matt Massey and Steve Newbold National Center for Environmental Economics October 2011. Linkages from Water Quality to $. (1) The change in WQ affects fish population levels. (2) Changes in fish populations affect expected catch.

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Recreational Fishing and Other Water Based Recreation

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  1. Recreational Fishing and Other Water Based Recreation Matt Massey and Steve Newbold National Center for Environmental Economics October 2011 National Center for Environmental Economics

  2. Linkages from Water Quality to $ (1) The change in WQ affects fish population levels (2) Changes in fish populations affect expected catch (3) Changes in expected catch affects (3a) utility per trip and (3b) the number of trips demanded (4) Changes in utility can then be monetized National Center for Environmental Economics Water quality improves as a result of the TMDL

  3. #1: Fish Population • The effect of changes in water quality on fish population levels will be captured in the EwE and Atlantis models discussed earlier • We will focus on the major recreational species in the bay (striped bass, bluefish, summer flounder, croaker, spot, white perch, tautog, and blue crabs) • The bay serves as a nursery for a number of species who spend significant portions of their adult lives outside of the Bay • Assume that Bay populations make up a certain percentage of total coastal populations • Assume that a certain percentage of the stock returns to the Bay each year and the rest join the coastal populations • Develop a model of coastal populations that includes Bay contributions National Center for Environmental Economics

  4. #2-4: MRFSS Issues • We will rely heavily on NOAA’s MRFSS data for the other relationship linkages • Strand et al (1991), McConnell et al (1994), Hicks et al (1999), McConnell and Strand (1999), Haab et al (2006) • There are two components to the survey: • In-person intercepts • Identifies anglers choice of fishing location and includes reported and observed catch • Telephone surveys • Used to estimate effort and participation National Center for Environmental Economics

  5. #2-4: MRFSS Issues • As pointed out by the 2006 NRC review, the intercept sampling design of the MRFSS survey produces a non-random sample • In the past, most studies have ignored the non-random sample issue which likely leads to biased estimates • NOAA has developed a weighting scheme designed to simulate a random sample. The weights should be available sometime next year. • Hindsley, Landry, and Gentner (2011) have suggested a weighting method using propensity score weights National Center for Environmental Economics

  6. #2-4: MRFSS Issues There are a lot of intercept sites in the Chesapeake Bay =~400 National Center for Environmental Economics

  7. #2-4: MRFSS Issues • For estimation aggregation of sites will be necessary • How should sites be aggregated? • Similarity of water body conditions? • Proximity? • Some combination of both? • We will conduct sensitivity and goodness of fit tests • How the aggregation is done will be important because it will effect how site specific characteristics are constructed National Center for Environmental Economics

  8. #2-4: MRFSS Issues • The survey intercepts fishermen at the dock and not where they actually fished • It is cheaper to travel on land than on water so it is standard to assume that fishermen will drive to a site near where they plan to fish • However, once a fisherman leaves the dock they could potentially travel anywhere in the bay • We plan to use questions on distance traveled to fish to define an average radius from the launch point that fishermen stay within National Center for Environmental Economics

  9. #2: Catch Rates • Use MRFSS in-person intercept survey catch data to estimate expected catch rates (2) for all species or species groups at all sites on and near the bay • There are several methods of estimating expected catch that we are considering • Calculate average reported catch at each site • Estimate expected catch as a function of fish population by combining reported catch with historic trawl data, water quality, and other predictors • McConnell et al (1995), Lipton and Hicks (2003), Massey, Newbold, and Gentner (2006). National Center for Environmental Economics

  10. #2: Catch Rates • Catch and effort restricting regulations may also effect expected catch. There are several options for incorporating regulations • Simplest option is to assume fishermen have the same value for fish they keep and fish they release • The effects of regulations would then be felt through the number of fish kept in the ecosystem models • The other option is to try to estimate the value of total expected catch and expected take-home catch separately • Regulations would then impact both trip demand and fish populations National Center for Environmental Economics

  11. #3a: Site Choice • In order to estimate the effect of catch rates on fishing site choice we will use the MRFSS intercept survey data to estimate a RUM travel cost model of recreational fishing demand • Haab and McConnell (2002), Parsons (2003), Lipton and Hicks (2003), Massey, Newbold, and Gentner (2006) • Trips = f(TC, Catch Rate, Angler Characteristics, Water Quality, Site Specific Constant) National Center for Environmental Economics

  12. #3a: Site Choice • We would like to model fishermen’s decision on each choice occasion: • Whether or not to go fishing (#3b) • Then conditional on going fishing which site they choose (#3a) • However, the on-site intercept nature of the survey means that we never observe anyone choosing not to fish • The obvious option is to estimate a model that would model fishermen’s site choices conditional on them already having decided to take a trip National Center for Environmental Economics

  13. #3b: Participation Rate • We would like to estimate (simultaneously if possible) site choices and participation decisions. A few potential options include: • Estimate the participation and site choice parameters using a combination of the intercept data and data on total trips to sites and/or total trips from specific zip codes to sites, • Using the estimated RUM coefficients and data on total number of fisherman, total trips taken, and number of choice occasions available to calibrate the values of the participation parameters needed • It may also be possible to predict changes in participation rates by estimating total trips taken as a function of annual catch rates or fish population sizes National Center for Environmental Economics

  14. #4 WTP National Center for Environmental Economics • The results of steps #1, #2, and #3 will then be combined to predict the changes in WTP across the years necessary for the TMDL to reach its final state • WQ affects fish population • Fish populations affect expected catch • Expected catch affects utility per trip and the number of trips taken • The number of trips taken affects fish populations • ….

  15. Other Water Based Recreation National Center for Environmental Economics • Fishing is clearly not the only water based recreation that takes place around the Chesapeake Bay • Boating, swimming, hiking, bird watching, hunting, … • Very little data exists on these activities however • Visitation totals to a small percentage of Bay access sites • Boat registration records • Hunting licences • NSRE fresh and salt water recreation surveys

  16. Other Water Based Recreation National Center for Environmental Economics 1122 recreational sites identified 141 sites have aggregate visitation data If enough data is available original estimation may be possible BT also an option

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