What’s your game? Heterogeneity amongst New Zealand hunters Geoff Kerr & Walt Abell Lincoln University New Zealand Agricultural & Resource Economics Society annual conference Nelson, 28-29 August2014 Game Animal Council Act 2013 • Herds of Special Interest – Ability to manage game as a resource – Environmental constraints • Issues – Proving “special interest” status – Objective setting • Research goals – Value recreational Sika deer and Himalayan tahr hunting – Identify preference diversity – Identify better hunting experiences Designer hunting! Greg Duley Sika deer Cervus nippon • Introduced 1905 • Kaimanawa & Kaweka ranges & surrounds – 6,000 km2 – Expanding range – Displacing Red deer • Indigenous forest, scrubland & tussock grasslands • Negative effects on beech forest www.poronui.com – canopy collapse possible Greg Duley Fraser et al. (2000) Himalayan tahr Jemlahicus hemitragus • Introduced 1904 • Central Southern Alps – 4,200 km2 • Scrub, tussock & mountains • Himalayan Tahr Control Plan – Max 10,000 tahr – Max densities • IUCN – 1996: Vulnerable – 2008: Near threatened Geoff Kerr Multiple uses • Commercial meat harvests • Guided trophy hunts – Tahr: AATH (helihunting) • Guided meat/management hunts • Recreational hunting – 10,000 ~ 15,000 Sika hunters – Sika hunts ~ 11% big game effort – Unknown number of tahr hunters • Diverse motivations – Trophy – Meat – Seeing animals – Social – Experiencing the outdoors Methods Greg Duley Three internet surveys 1. Hunter recruitment & demographics (2011) 2. Monthly hunter activity monitoring (2011/2012) 3. Choice experiment (2012) Convenience sample – No hunter register – Advertisements in hunting magazines & on web Latent class models – Address heterogeneity – More useful for management than RPL Geoff Kerr Choice Experiment Attributes Hunt duration: days 1,2,3,5,7 Terrain easy, moderate, difficult Hut no, yes Motorised access none, 4WD, aircraft, all (tahr only) Other hunters present no, possibly, definitely Sika/tahr density low, moderate, high Trophy potential low, moderate, high Travel distance: km Xi, Xi+150, Xi+250 • Design efficiency: 2 Waves (N = 2x150=300 sika, 309 tahr) • Avoid money attribute • Pivot off individual travel distances (Xi) • 3 hunt alternatives plus no hunt option, 8 choice sets per respondent • 128 useable sika responses (43%) 1018 choices • 149 useable tahr responses (48%) 1211 choices Sika model Rho2 = 0.200 Class 1 Class 2 Class 3 Distance -0.0017*** -0.0023*** -0.0180*** ASC Hunt 2.0484** 4.1533*** 1.6445*** 1 Day hunt -1.2319*** -1.2322*** 2 Day hunt -1.1902*** 1.6672*** 7 Day hunt -1.9864*** No other hunters 0.2575** Definitely other hunters -1.0557** -0.6355*** Low numbers of Sika -0.7789*** -0.7789*** -0.7789*** High numbers of Sika 0.5309** Low trophy potential -0.7939** -1.0499*** High trophy potential -0.7143** 0.7569*** 1.6928*** Class probability 0.21 0.67 0.13 Modal probability 0.19 0.69 0.13 * significant at 10% level, ** 5%, *** 1% Tahr model Rho2 = 0.243 Class 1 Class 2 Class 3 Distance -0.0019*** -0.0028*** -0.0011** ASC Hunt 2.5457*** 4.4715*** 0.8025*** 1 Day hunt -1.5806*** -0.9908*** 5 Day hunt 1.3850*** 7 Day hunt 1.1752*** -1.4854*** All forms of access -0.4176** Difficult terrain -0.5190*** No other hunters 0.4138*** Definitely other hunters -0.8194** -0.4251** -1.2572*** Low trophy potential -1.9185*** -0.6385*** -1.7217*** High trophy potential 1.1751*** 0.9162*** Hunter’s age-mean -0.0728*** Class probability 0.46 0.29 0.26 Modal probability 0.46 0.28 0.26 * significant at 10% level, ** 5%, *** 1% Consumers’ surplus: sika (Q4 2012 NZ$ hunt-1) $2,000 $1,500 $1,000 Class 1 Class 2 Class 3 $500 Mean consumers' surplus perhunt surplus consumers' Mean $0 1 2 3 5 7 -$500 Sika hunt duration (days) Values of attribute changes (Q4 2012 NZ$ hunt-1) SIKA Class 1 Class 2 Class 3 1 Day hunt -$598* -$435*** 2 Day hunt -$578* $76*** 7 Day hunt -$91*** No others $91** Definitely others -$513 -$224*** Low numbers of Sika -$378** -$275*** -$36*** High numbers of Sika $187*** Low trophy potential -$386 -$371*** High trophy potential -$347 $267*** $78*** Values of attribute changes (Q4 2012 NZ$ hunt-1) SIKA Class 1 Class 2 Class 3 • 13% of sample 1 Day hunt -$598* -$435*** • Locals 2 Day hunt -$578* $76*** • Frequent sika hunts 7 Day hunt -$91*** • Short hunts No others $91** • Small consumers’ surplus Definitely others -$513 -$224*** • Low helicopter use Low numbers of Sika -$378** -$275*** -$36*** • Marginal value hunters High numbers of Sika $187*** Low trophy potential -$386 -$371*** High trophy potential -$347 $267*** $78*** Values of attribute changes (Q4 2012 NZ$ hunt-1) SIKA Class 1 Class 2 Class 3 • 20% of sample 1 Day hunt -$598* -$435*** • Least avid hunters 2 Day hunt -$578* $76*** • Few sika hunts 7 Day hunt -$91*** • Best educated No others $91** • Not very sensitive to Definitely others -$513 -$224*** conditions Low numbers of Sika -$378** -$275*** -$36*** • Moderate value High numbers of Sika $187*** hunters Low trophy potential -$386 -$371*** High trophy potential -$347 $267*** $78*** Values of attribute changes (Q4 2012 NZ$ hunt-1) •SIKA68% of sample Class 1 Class 2 Class 3 1• DayMost hunt avid hunters -$598* -$435*** • Least urban 2 Day hunt -$578* $76*** • Highly sensitive to conditions 7• DayHigh hunt value hunters -$91*** No• Potentialothers to increase $91** Definitelyvalue others -$513 -$224*** Low numbers of Sika -$378** -$275*** -$36*** High numbers of Sika $187*** Low trophy potential -$386 -$371*** High trophy potential -$347 $267*** $78*** Consumers’ surplus: tahr (Q4 2012 NZ$ hunt-1) $2,500 $2,000 $1,500 Class 1 $1,000 Class 2 Class 3 $500 Mean consumers' surplus perhunt surplus consumers' Mean $0 1 2 3 5 7 -$500 Tahr hunt duration (days) Values of attribute changes (Q4 2012 NZ$ hunt-1) High CS (45%) Low CS (25%) TAHR Class 1 Class 2 Class 3 1 Day hunt -$744*** -$317*** 5 Day hunt $652*** 7 Day hunt $553*** -$475*** All access -$197* Difficult terrain -$166*** No others $195** Definitely others -$386*** -$136** -$1074** Low trophy potential -$903*** -$204** -$1471** High trophy potential $553*** $293*** Conclusions • Economic analysis has been able to show that: – Recreational hunting is a high value activity – Changing attributes significantly changes benefits – There are unique groups of hunters who seek different opportunities – There are strong prospects for management to enhance value • More research required – Costs of management – Costs of being managed [email protected] www.lincoln.ac.nz/hunt .