Will The TMDL Result in Increased Benefits from Recreational Fishing?

Doug LiptonDepartment of Agricultural & Resource Economics

University of Maryland College ParkEPA Workshop

October 31, 2011

Motivation

• Recreational demand modeling was sophisticated in developing values for quality (i.e., catch rate) changes, but naïve in linking these changes to environmental factors (e.g., including nitrogen directly)

• Spatial ecological modeling, particularly the work of Brandt et al. utilizing bioenergetic approaches for striped bass– Spatial temperature-oxygen squeeze in Bay– Differential impacts of temp/oxygen on predator and prey locations

• One could take the Chesapeake Bay model run outputs and assign a probability of catching striped bass based on the predicted DO, temperature, and location of prey species to every output cell

Ecosystem States & Recreational Fishing

Expected Catch Rate Change

Random Utility Model

Water Quality Change

Benefit Change

Basic Premise

• Fishermen (correcting for skill – avidity, age, etc.) would expect (historical catch rate) to catch striped bass at a certain location during a certain period.

• Through communication among recreational fishermen (fishing reports, radio communication, tackle shops, online forums, etc.) they modify those expectations and travel to different sites. Those modifications to historical expectations are underlain by unobserved water quality that change observed catch rates

• Thus fishermen choose to travel to alternative sites where catch rate expectations are higher (better water quality)

Expected Catch Rate is a Function of Ecosystem State

Variable Coefficient t-test Constant -5.897 -6.592* Historic catch rate 0.631 11.396* LN(Hours) 0.344 3.337* Years Fished 0.019 6.073* Days Fished (12) 0.001 1.474 Surface Temp -0.255 -2.596* Bottom Temp 0.323 2.838* Surface Oxygen 0.259 4.414* Bottom Oxygen 0.225 1.953* Oxygen2 -0.017 -2.023*

Asset Values From Striped Bass RUM – 5% Discount Rate

• Total (Access Value) Current $1.071 Billion

• Increased Catch Rate $81.4 Million• Lower Water Quality (DO)– <= 5 mg/l -$ 98.5 Million– <= 4 mg/l -$122.9 Million– <= 3 mg/l -$145.3 Million

Other Issues

• No a priori expectations that water quality would result in decreased welfare. Could have concentrated fish in areas closer to where fishermen were located

• For a given population of fish, so didn’t capture stock dynamics as dealt with in Massey and Newbold for flounder.

• Focused on striped bass based on Breitburg trawl survey data linked to oxygen – other species not as sensitive

• What about Breitburg work suggesting decreasing fisheries productivity with reduced nutrient loads?

Data Issues

• Assigning anglers from intercept sites to fishing location

• Using water quality station data or interpolated data (see Mason M.S. thesis 2008)

Challenges

• Still don’t know where people actually fish adds error

• DO and temperature move fish around directly and indirectly – i.e., availability of prey. Wanted to capture, but lacked spatial distribution of prey species. Tried using Chlorophyll a as indicator of abundance of prey species (e.g., menhaden, bay anchovy, etc.)

Additional Work with Bricker (NOAA) on Human Use Indicators of Eutrophication

• Gulf of Maine– Exploration of approach to different species,

estuaries• Barnegat Bay– Summer flounder

• Mason Thesis– Interpolated versus point data for water quality– No difference

Statistical Results of Developing Eutrophication Indicators (Bricker et al.)