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1 ISSN X WORKING PAPER SERIES No. 3/2004 WILDLIFE CONSERVATION POLICIES AND INCENTIVES TO HUNT: AN EMPIRICAL ANALYSIS OF ILLEGAL HUNTING IN WESTERN SERENGETI, TANZANIA Anne Borge Johannesen Department of Economcs N-7491 Trondhem, Norway

2 1 Wldlfe conservaton polces and ncentves to hunt: An emprcal analyss of llegal huntng n western Serenget, Tanzana Anne Borge Johannesen Department of Economcs Norwegan Unversty of Scence and Technology, NTNU NO-7491 Trondhem (E-mal: anne.borge@svt.ntnu.no) Abstract: Ths paper nvestgates factors determnng partcpaton and effort n llegal huntng, usng cross-secton survey data from households n western Serenget, Tanzana. One purpose of the analyss s to study the mpact on llegal huntng of the ntegrated conservaton and development project establshed n ths area, namely the Serenget Regonal Conservaton Project (SRCP). The paper also nvestgates how the pattern of crop producton n agrculture, market accessblty and wldlfe-nduced damage to crops and domestc anmals affect llegal huntng. The emprcal results suggest that effort n llegal huntng s nversely related to partcpaton n SRCP. The results also show that the lkelhood of llegal huntng s a decreasng functon of the amount of agrcultural land cultvated for maze producton. Further, the huntng effort s negatvely related to the sze of cotton- and maze land, as well as wldlfe-nduced damage to crops and domestc anmals. I would lke to thank the Norwegan Research Foundaton through the NINA/NTNU/TAWIRI project Bodversty and the human-wldlfe nterface n the Serenget, Tanzana and The European Commsson s BIOECON programme for fundng for ths paper, as well as three anonymous revewers for valuable comments.

3 2 1. Introducton Protected areas such as natonal parks and game reserves have long been regarded as crucal n wldlfe conservaton. However, the establshment of protected areas has often excluded local people from the use of these areas and, durng the past decades, ths knd of exclusonary protected area management has been vewed as havng faled to preserve wldlfe n developng countres (Kss 1990, Barrett and Arcese 1995, Gbson and Marks 1995). Today there s a growng recognton that the successful management of protected areas depends on the co-operaton and support of the local people lvng wth wldlfe. In response to ths, Integrated Conservaton and Development Projects (ICDPs), amng at changng rural nhabtants ncentves to explot the resources of protected areas through beneft-sharng schemes and awareness buldng, are frequently adopted. The beneft-sharng component mght nclude drect utlzaton of wldlfe and ncome transfers from the toursm sector, as ways of compensatng the local people for restrcted access to the protected area. If substtutes are not avalable or nconsstent wth the conservaton objectve, ICDPs could provde alternatves that attempt to, for example, mprove access to agrcultural markets and ncrease agrcultural ncomes (Wells and Brandon 1992). The percepton n most projects s that the local people wll swtch from llegal huntng to legal (agrcultural) actvtes f the latter generate greater revenue. The man purpose of ths paper s to nvestgate the mpact on llegal huntng of an ICDP based on drect utlzaton of wldlfe. In addton, the analyss focuses on the relatonshp between llegal huntng and agrcultural condtons such as land use, types of crops, market accessblty and wldlfe-nduced damage to agrcultural output. In order to do ths, the paper uses cross-sectonal survey data from households n western Serenget, Tanzana. The survey was conducted n the perod June to August 2001 among local communtes along the western border of the Serenget Natonal Park. Ths area has experenced a rapd growth n human settlement (Campbell and Hofer 1995, Barrett and Arcese 1998) that concdes wth a marked ncrease n the number of poachers arrested n the park (Arcese et al. 1995). Today Serenget Natonal Park and ts surroundng game reserves contan the world s largest ungulate herds (Snclar and Arcese 1995, Barrett and Arcese 1998), but Snclar (1995, page 24) states the llegal kllng of the mgrant ungulates by poachers s potentally the most serous threat to the Serenget ecosystem.

4 3 The rest of the paper s organzed as follows. Secton 2 presents the theoretcal reasonng for the hypotheses on llegal huntng. The data set s presented n Secton 3, whle the emprcal specfcaton and the estmaton results are presented n Secton 4. Fnally, Secton 5 contans a summary and dscusson of the man fndngs n the paper. 2. Hypotheses ICDPs have recently been the focus of attenton because of the untested assumptons behnd ther strateges. In the theoretcal bo-economc lterature, Barrett and Arcese (1998) reveal possble undesrable effects of free dstrbuton of game meat to the local people usng wldebeest explotaton n the western Serenget as an example. They nvestgate the mpact of ths strategy on llegal huntng n a household model wth no market for game meat, and where the household derves utlty from consumpton of game meat, agrcultural output and lesure. They show that the household wll respond to dstrbuton of game meat by substtutng legal meat for llegal meat. Consequently, ths strategy reduces llegal huntng 1. See also Johannesen (2004). The exstng ICDP n Serenget the Serenget Regonal Conservaton Project (SRCP) s based on game meat dstrbuton to the local people (SRCS 1993, SRCS 1995, Rugumayo 1999). The man purpose of the present analyss s to nvestgate any dfferences n llegal huntng between households who partcpate n SRCP and households outsde of the project. Based on Barrett and Arcese (1998) t s expected that llegal huntng falls wth the amount of meat from SRCP. In addton, n order to capture other strateges of SRCP, such as awareness buldng and educaton of game scouts, the analyss nvestgates whether partcpaton n the project n general has a negatve mpact on llegal huntng. In order to promote wldlfe conservaton there have been repeated proposals to mplement polces that mprove economc condtons n the agrcultural sector. For nstance, Brown et al. (1993) suggest that mproved labour productvty n agrculture wll dvert labour away from huntng and, thereby, reduce the pressure on wldlfe. Ths relatonshp s also derved from e.g. Smth (1975) and Skonhoft and Solstad (1998) n standard hunter-agraran 1 However, because game meat s consdered a normal good, free dstrbuton enhances the total demand for meat. Hence, the model mples that game meat dstrbuton ncreases the aggregate offtake and, consequently, reduces the degree of wldlfe conservaton.

5 4 household models where the household dverts labour between wldlfe harvestng and agrcultural crop producton. In these models, an exogenous ncrease n cultvated land mght ncrease the productvty of labour n agrculture and, consequently, shft the allocaton of labour towards agrcultural producton. Based on these results t s expected that an ncrease n cultvated land wll reduce llegal huntng. In the same way, n the case of domestc anmal keepng, a larger herd s also expected to reduce llegal huntng. Another mportant feature that may affect llegal huntng s that wldlfe roamng outsde protected areas damages agrcultural output. Skonhoft and Solstad (1998) demonstrate that ncreased damage reduces the margnal beneft of labour n agrculture and, thus, more effort wll be allocated to huntng. Another am of the present analyss s therefore to nvestgate whether more extensve damage to crops and domestc anmals ncreases llegal huntng. For other references on wldlfe-nduced damage, see e.g. Huffaker et al. (1992), Carlson and Wetzsten (1993), Bulte and van Kooten (1996), Schulz and Skonhoft (1996), Skonhoft (1999), and Zvn et al. (2000). Marketng opportuntes tend to be lmted n regons surroundng protected areas due to remote locaton and lack of good roads and nfrastructure. Agrcultural output s therefore more lkely to be selected for subsstence use rather than for sale n small towns or other regonal markets. In order to ncrease local ncomes, several exstng ICDPs attempt to mprove market accessblty through, e.g., road constructon and the promoton of marketng assocatons (Brandon and Wells 1992). However, Brandon and Wells (1992) queston the underlyng assumpton that ncreased ncome reduces llegal huntng. They clam that ths understandng s based on an mplct assumpton of a fxed ncome need and that llegal huntng stops once ths need s covered. Instead, they assert that local people are unlkely to swtch from llegal huntng to legal actvtes unless the latter generate more ncome and ft nto an overall strategy of utlty maxmzaton. The present analyss attempts to nvestgate whether there s less llegal huntng among households who partcpate n, or have greater access to, agrcultural markets, than households who do not. Fnally, and n lne wth the standard result of hunter-agraran models, the analyss nvestgates whether an ncrease n the sze of a household ncreases llegal huntng. 3. Data collecton and descrptve analyss

6 Data collecton The emprcal analyss of llegal huntng s based on survey data from the Serenget and Bunda Dstrcts along the western border of the Serenget Natonal Park. The survey was conducted n sx vllages, equally dvded between the dstrcts, and counts 297 households. 166 and 131 households are from Bunda and Serenget, respectvely. Four of the vllages, or 148 households, partcpate n the SRCP whle, as confrmed by the vllage executve secretares, no vllage project exsts for the remanng two vllages, or 149 households. For a further descrpton of the survey, see Appendx 2. All huntng reported n the survey s llegal and one man purpose of the emprcal analyss s to nvestgate the mpact of the SRCP on ths actvty. The project was mplemented n 1993/94 and ncludes fourteen vllages spread evenly between Serenget and Bunda Dstrcts. The SRCP s strategy to select project vllages has not been based on thorough studes of llegal actvtes, but rather on ther locaton n relaton to the western border of Serenget Natonal Park. All of the project vllages are located along ths border, but at some dstance from the border 2. The SRCP dstrbutes game meat to the project vllages from a harvestng quota set equal to each vllage by the government,.e. the Mnstry of Natural Resources and Toursm. The responsblty of the SRCP s to organze huntng and brng the meat to the respectve vllages. The vllagers buy the meat at a prce set by agreement between the SRCP and the vllage authortes and below the prce of llegal meat. In addton to game meat dstrbuton, the SRCP has asssted the establshment of vllage-level nsttutons responsble for managng the fund from the huntng quota revenues. These funds fnance vllage projects such as schools and dspensares. The SRCP s also responsble for the set-up and tranng of game scouts n the project vllages. Fnally, the SRCP works wth awareness-buldng n order to mprove the relatonshp between the local people and the park. Ths ncludes publc meetngs at vllage level, semnars and tranng courses on wldlfe utlzaton and management, and other wldlfe tasks. For a broader overvew of the actvtes of the SRCP, see Rugumayo (1999) Descrptve analyss and the sample 2 The SRCP ntends to nvolve the project vllages n the future management of the outer areas located between the vllages and the park border.

7 6 The households were asked about ther partcpaton n llegal huntng, huntng trps, and targeted speces. The reported speces are wldebeest, zebra, gazelle, top, and mpala. In Table 1, 80 households, or 27 per cent of the sample, report that some household members are nvolved n llegal huntng. The partcpaton rate dffers between sub-groups of the sample. For nstance, 32 per cent of the SRCP households partcpate n llegal huntng, whle ths s the case for only 22 per cent of households outsde the SRCP. Hence, despte the advantages of lvng n a project vllage, partcpaton n llegal huntng s more wdespread n the SRCP vllages. Ths demonstrates the need for further nvestgaton of the relatonshp between llegal huntng and partcpaton n the SRCP. The partcpaton rate also vares between dstrcts, 22 per cent n Bunda Dstrct and 34 per cent n Serenget Dstrct. Table 1 about here As demonstrated n Table 2, the hunters can be dvded nto two groups. Ths dvson s also mportant for the emprcal specfcaton of the model n Secton 4. The frst group of hunters (55 per cent of the hunters) report that they go on huntng trps, whle the second group (45 per cent) does not go on huntng trps. Here, huntng trps are defned as trps that last for several days and where the hunters usually hunt wthn the protected area. The hunters who do not go on huntng trps hunt closer to ther homes and wthn the vllage area. They hunt durng the annual wldebeest mgraton when wldebeest enter vllage land durng the dry season. See Snclar and Arcese (1995) for a descrpton of the wldebeest mgraton. Several of these households report that they kll wldebeest when they concdentally enter ther agrcultural feld or yard. Ths ndcates that huntng n the home area s less tme consumng than gong on huntng trps. Whle the huntng grounds dffer between these groups, the targeted speces are the same; wldebeest s the major speces, followed by gazelle, zebra and top. In addton, both groups report that they hunt both as a source of ncome and for domestc consumpton. However, the groups dffer when t comes to the reported ncome from llegal huntng. Nnety sx per cent of households who go on huntng trps earn ncome from ths actvty, whle ths only apples to 33 per cent of those who hunt n ther home area (not shown n a table) 3. One plausble 3 The two groups of hunters dentfed n ths survey must not be confused wth the subsstence poachers from the local communty and organzed and professonal poachers from outsde as defned by Leader-Wllams and Mlner- Gulland (1993). In ths survey, all hunters come from the local communty, they all use tradtonal huntng methods

8 7 explanaton of the observed dfferences n ncome s that the average offtake s consderably hgher among households who go on huntng trps (13.86 ± anmals), compared to huntng n the home area (2.25 ± 1.99 anmals). The fracton of hunters reportng a postve number of huntng trps dffers between subgroups of the sample. For nstance, 43 per cent of the hunters n the SRCP vllages go on huntng trps, whle the same rate for hunters outsde the SRCP s 73 per cent. The partcpaton rates dffer even more between the dstrcts: 86 per cent of the hunters n Bunda go on huntng trps, whle only 30 per cent of the hunters n Serenget report the same. Table 2 about here In agrcultural producton, these households produce seven man crops: cotton, maze, mllet, sorghum, cassava, potatoes and beans. Cotton s the only cash crop and s only produced for sale. The food crops are, on the other hand, manly produced for household consumpton, or for both consumpton and sale. As seen n Table 3, crop producton s the major ncomegeneratng actvty. However, the proporton of households earnng ncome from the respectve actvtes dffers between the dstrcts. More households earn ncome from crop producton n Bunda (86 per cent) than n Serenget Dstrct (60 per cent), whch may be explaned by varaton n the crop composton between dstrcts. Seventy three per cent of the Bunda farmers grow cotton, whle the same number n Serenget s 6 per cent. Eghty sx per cent of the farmers n Serenget grow maze, compared to 54 per cent n Bunda. Further, a sgnfcantly hgher proporton of Serenget farmers produce maze for sale compared to Bunda farmers 4. However, ths s not enough to offset the ncome advantage of cotton producton n Bunda. The remanng crops n the study area are manly grown for own-household consumpton. Mllet s the major crop n ths group, and s produced by 63 per cent of households. In (.e. wre snares, ptfalls, traps, knves, machetes etc. (see Arcese et al. 1995) and they all hunt for meat (for domestc consumpton or for sale). In lne wth the termnology used by Leader-Wllams and Mlner-Gulland, both groups are therefore subsstence hunters. 4 The Kruskal-Walls test rejects the null hypothess of equal means between the dstrcts. Interested readers may contact the author for ths result and Kruskal-Walls tests on dfferences n mean ncome below.

9 8 contrast to the cotton and maze producers, the mllet producers are evenly dstrbuted between dstrcts. Domestc anmal keepng, the second major ncome-generatng actvty, covers cattle, goats, sheep and poultry. Table 3 shows that the rate of households wth postve ncome from ths actvty s hgher n Serenget than n Bunda. Fnally, 110 households earn ncome from nonagrcultural actvtes. These nclude sellng fsh, charcoal, local brew, runnng small shops etc 5. Agan, the rate of partcpaton dffers between the dstrcts, 40 per cent n Bunda and 33 per cent n Serenget. However, testng for dfferences n mean ncome from non-agrcultural actvtes shows t s sgnfcantly hgher n Serenget. When t comes to reported ncome from crop producton and anmal keepng, the data set reveals statstcally sgnfcant dfferences n mean ncome n favour of the dstrct wth the hghest partcpaton rate. However, there s no sgnfcant dfference n the mean total ncome between the dstrcts. Hence, whle the dstrcts dffer n type of ncome generatng actvtes, there s no sgnfcant dfference n mean ncome. Table 3 about here The proporton of households earnng ncome from crops and/or domestc anmals s lower n SRCP vllages than n non-srcp vllages, whle the proporton of households earnng ncome from non-agrcultural actvtes s hgher n SRCP vllages. Mean total ncome s sgnfcantly hgher outsde SRCP vllages. Wldlfe-nduced damage to crops and domestc anmals s reported by households to be caused by elephant, baboon and bushpg, whle damage to domestc anmals s caused by hyenas (lvestock), eagles (poultry) and mongooses (poultry). Households were also asked to ndcate the damage level as no damage, very lttle, much or very much. The second row n Table 4 shows that some 86 per cent of respondents complaned that wldlfe causes much or very much damage to crops. Ths number seems hgh, and a further nvestgaton of the reported damage percentage shows a consderable varaton wthn each response category. However, the survey reveals that the mean damage percentage ncreases between 5 The complete lst of other actvtes also ncludes sellng water, honey, and frut, house rent, carpentry, makng spears, and employment (teachng or other work at school, wldlfe management, vllage secretary, other employment). Only 8 respondents n the sample households (less than 3 per cent) report that they have formal employment.

10 9 the categores and the means dffer sgnfcantly. Stll, there are some serous measurement problems regardng reported measures of crop damage. One problem s that respondents may overestmate both damage mpresson and percentage n the hope for future compensaton. A second and equally mportant problem s that the respondents found t dffcult to estmate the percentage crop damage. Instead, they reported the approxmate number of acres damaged as a percentage of the number of acres cultvated. It s therefore mportant to note that ths measure reflects nether the exact share of output damaged, nor the value of the loss. Table 4 about here As seen n the ffth row of Table 4, far more households report that they experence no damage to domestc anmals compared to reported crop damage. Stll, some 60 per cent complan that wldlfe causes much or very much damage to domestc anmals. When t comes to the number of anmals klled or njured, the reported numbers vary consderably wthn each response category. Some nconsstency may be present, but the varaton may also reflect varyng dependence on domestc anmal keepng among households. 4. Emprcal specfcaton and estmaton results As already seen, three dfferent types of households were observed n ths survey. The frst type were all households who do not partcpate n llegal huntng. The second and thrd types contan all households who partcpate n llegal huntng, the second group beng all who hunt wthn the vllage area, whle the thrd group all who go on huntng trps. The startng pont of the emprcal analyss s to analyse the household s decson to partcpate, or not, n llegal huntng. Secton 4.1 presents the emprcal specfcaton and estmaton results of ths decson problem usng a Probt model. However, because some hunters go on huntng trps, whle others hunt wthn the vllage area only, t s adequate to consder the households decson problem as one where they choose whether ) to not partcpate n huntng, to partcpate n huntng but ) no huntng trps, or ) to go on huntng trps. The Probt framework s therefore extended by presentng an ordered probt model, where the ndvdual households are classfed nto three categores )-). Fnally, Secton 4.2 presents a model of the number of huntng trps,.e. huntng ntensty. 4.1 Partcpaton n llegal huntng and ordered groups

11 Emprcal specfcaton and varable defntons The probt specfcaton of the emprcal model s gven n equaton (1) 6. (1) E h 1 = 0 * h f E > 0 0 otherwse, where E = β + β SRCP + β DISTRICT + β L + β D _1 + β D _2 * h CROP 5 CROP + β M + β DISTANCE + u 6 6 h Here, E = 1 f household partcpates n llegal huntng, whle E = 0 otherwse. The explanatory varables n equaton (1) represent the startng pont for all three emprcal models n Secton 4, but other specfcatons wll also be presented. SRCP s a dummy for partcpaton n the SRCP and takes on the value one for SRCP households and zero otherwse. The dummy DISTRICT s ncluded to capture dstrct-specfc characterstcs of the data set and equals one for Bunda households and zero for households n Serenget. h L s the number of acres cultvated for crop producton by household. D CROP _ 1 and D CROP _ 2 are dummy varables for much and very much crop damage, respectvely. D 1 CROP _ ( D CROP _ 2 ) takes the value one f the household reports much damage ( very much damage) and zero otherwse. Both categores much and very much are expected to ncrease the probablty of huntng over the no or lttle damage level. M s the number of household members. DISTANCE s the dstance from the household s vllage to the natonal park. Fnally, u s the error term. Other specfcatons of the model wll also be ncluded. Frst, n order to capture the mpact of dfferent types of crops on the probablty of partcpaton n llegal huntng, the explanatory varable L wll be replaced by the number of acres devoted to cotton L_COT, maze L_MAI, and mllet L_MIL n the respectve households. These crops cover some 66 per cent of the total amount of cultvated land n the study area. Second, two dummes are ncluded to reflect 6 See Johnston and Dnardo (1997) chapter 13.

12 11 market avalablty. COT s a dummy that equals one for cotton producers and zero otherwse. MOT_MAI s a dummy reflectng whether some maze s produced for the market or not. It equals one for producers reportng that some maze s produced for sale and zero f maze s produced for own consumpton only. Because market accessblty s expected to ncrease agrcultural ncomes, we tested whether the coeffcents of COT and MOT_MAI are postve. Further, an nteracton varable L_MAI*MOT_MAI s ncluded n order to nvestgate whether the relatonshp between llegal huntng and maze producton dffers between households who sell maze on the market and those who do not. Mllet s produced for own consumpton only but not all ts producers face a mssng output market. Therefore, we nteracted L_MIL wth COT and MOT_MAI, and tested whether the relatonshp between llegal huntng and mllet producton dffers between households who have access to the relevant markets and those who do not. Thrd, the base model excludes anmal assets and damage to domestc anmals n order to avod a consderable reducton n the number of observatons (see below). Stll, because domestc anmal keepng s wdespread t s of nterest to nvestgate the mpact of ths actvty as well. The explanatory varable household, whle D ANIMAL _ 1 and D ANIMAL _ Y measures the number of domestc anmals n 2 are dummes for wldlfe-nduced damage to domestc stock. The latter are defned n the same way as the dummes for crop damage. Fnally, nstead of focusng solely on partcpaton n the SRCP, the varables MEAT_1 and MEAT_2 are dummes for the amount of meat bought from the SRCP. MEAT_1 (MEAT_2) takes the value one f the household report 5 to 10 klo ( more than 10 klo) and zero otherwse. Both categores are expected to have a non-postve effect on the number of huntng trps over the 0 to 5 klo category. Summary statstcs of the varables are reported n Table A3.1 n Appendx 3. The Ordered Probt model can be used to model a dscrete dependent varable that takes on ordered mult-nomnal outcomes for each ndvdual household. Ths apples for the three groups ) non-hunters, ) hunters, but no huntng trps, and ) hunters who go on huntng trps. As argued earler, huntng n the vllage area seems to be less tme consumng than to go on huntng trps n the protected area. The model s therefore expressed as 7 7 However, f we assume that huntng n the vllage area and huntng n the protected area are equally tme consumng, there s no orderng of the dependent varable. In ths case, a multnomnal logstc regresson s used

13 12 (2) E h 1 = 2 3 E * f h c1 f c 1 < E h * c 2 * f c2 < Eh c3 where the latent varable * h E s defned as n equaton (1) for the base model. c z represents the cut-off ponts between successve alternatves z = 1, 2, 3. Here, the ordered probt natural h h orderng yelds E = 1 for group ), E = 2 for group ), and E = 3 for group ). h Estmaton results Table 5 reports the Probt and Ordered Probt estmates for the base model as well as the alternatve specfcatons. Frst, the coeffcent of the poltcal varable SRCP n Probt regresson (a) s postve and sgnfcantly dfferent from zero. Ths suggests that the probablty of partcpaton n llegal huntng s hgher for SRCP households compared to households outsde SRCP. However, ths result s not stable across the dfferent model specfcatons. On the other hand, the frst three columns show that partcpaton n huntng gves a sgnfcantly negatve coeffcent wth respect to the dstrct. That s, the probablty of llegal huntng s hgher for Serenget households. The Probt model (a) suggests that the amount of cultvated land has no mpact on the decson to partcpate n llegal huntng. When controllng for domestc anmal keepng and the correspondng damage n model (b), the coeffcent of L s negatve but only sgnfcant at the ten per cent level of sgnfcance 8. However, when dstngushng between the amounts of land devoted to cotton, maze and mllet n model (c), the coeffcent of maze s negatve and sgnfcantly dfferent from zero at the 1 per cent level of sgnfcance 9. Hence, the type of crop grown seems to affect the probablty of llegal huntng. However, partcpaton n, or to analyse the probablty of huntng n the vllage and probablty of huntng n the protected area. The results are reported n Table A1.1, Appendx 1, where no huntng s the comparson group. 8 In model (b) the sample s reduced due to mssng observatons on damage to domestc anmals. 9 The coeffcents of L_COT (L_MIL) are also nsgnfcant when omttng the varables L_MIL (L_COT) and L_MAI.

14 13 access to, markets seems to have no mpact on the decson to hunt 10. No other varables are sgnfcant n the Probt models 11. Table 5 about here The next step s to look at the ordered probt analyses of the probabltes of refranng from llegal huntng, to hunt llegally n the vllage area, or to go on huntng trps. Whle the dstrct seems to affect the decson to partcpate n llegal huntng, the Ordered Probt estmaton results n Table 5 demonstrate that ths varable s less sgnfcant when we dstngush between the dfferent types of hunters. For ordered Probt model (c), the probablty of huntng n both the vllage area and the protected area are decreasng functons of maze producton. However, and consstent wth the Probt analyss, these probabltes seem to be ndependent of market accessblty. In contrast to the Probt analyss, very much damage to crops ncreases both the probablty of huntng n the vllage area and the probablty of gong on huntng trps over no or very lttle damage 12. See model (c) Tables 5 and 6. Recall from Secton 3 that the major speces causng crop damage do not represent the targeted speces for huntng. Hence, llegal huntng n the vllage area does not seem to be a way of gettng rd of problem anmals, but rather a way for the households to compensate themselves for the loss of agrcultural producton. 10 In model (d) the sample s reduced due to mssng observatons on motvaton for maze producton. 11 The coeffcent of DISTANCE s also nsgnfcant when DISTRICT s omtted from the model. In addton, the coeffcents of Y, D ANIMAL _1 and D ANIMAL _2 are nsgnfcant f ncluded n models (c)-(d). The same apples to the ordered probt model. 12 As mentoned n Secton 3, the survey gves nformaton on the number of acres damaged as a percentage of the number of cultvated acres as well. When usng an estmate of the number of acres damaged nstead of damage mpresson, the coeffcent s not sgnfcantly dfferent from zero. Ths result corresponds well wth the nsgnfcant coeffcent of the amount of cultvated land L. As already seen, however, the types of crop produced seem to affect the group probabltes. Therefore, one may also expect the amount of damage to the respectve crop to affect the group probabltes. Unfortunately, however, there s no data on damage to types of crops. Instead, the emprcal models control for damage mpressons, varables of whch are subjectve measures of the dmenson of wldlfe-nduced damage.

15 14 Fnally, model (c) shows that the coeffcent of the number of household members s negatve and sgnfcantly dfferent from zero at the fve per cent level of sgnfcance. Ths s n contrast wth the theoretcal predcton. However, ths result should be nterpreted wth care as the data set contans nformaton about the number of members n each household but, unfortunately, lacks nformaton about age composton, chldren s school attendance, etc. That s, the data set contans no accurate measure of the number of household members capable of workng. M counts all members of the household, frequently rangng from small chldren to elders, but not the number capable of workng. Table 6 about here 4.2 Huntng trps Emprcal specfcaton In the followng, a Tobt model s used to analyse huntng ntensty. For those who go on huntng trps, data on the number of trps and average number of days per trp was captured, whereas we captured no effort data for those who hunt n the vllage area. Instead, the emprcal analyss of huntng ntensty s related to the number of huntng trps, where ths number equals zero for those who hunt only wthn the vllage area. Due to our nablty to compare huntng effort of households huntng n the vllage area (.e. zero trps) and nonhunters (.e. zero huntng effort), however, t seems dffcult to apply the Tobt model to the whole sample. The analyss s therefore lmted to the sub-sample contanng only hunters. That s, t nvestgates factors determnng the huntng ntensty condtoned on partcpaton n llegal huntng 13. The Tobt model s gven n (3) 14 (3) E h E h = 0 * f E > 0 h otherwse where the latent varable E * h s defned as n (1) for the base model. 13 A Heckman two-step model of the decson to hunt has been consdered. However, all parameters were nsgnfcant, whch ndcates that the varables cannot smultaneously determne the decson to hunt and huntng ntensty. 14 See Johnston and Dnardo (1997) chapter 13.

16 Estmaton results Table 7 reports the Tobt estmates. The coeffcent of SRCP has a sgnfcant negatve sgn n models (a)-(d), whch ndcates a lower huntng ntensty among hunters from SRCP vllages compared to hunters from vllages outsde SRCP. Model (e) demonstrates, however, that the amount of meat bought from the SRCP has no mpact on huntng ntensty 15. Instead, the sgnfcant negatve sgn of SRCP n (a)-(d) may reflect the presence of vllage game scouts, awareness buldng, or the establshment of vllage wldlfe funds n the SRCP vllages. The latter has fnanced nvestments n school and dspensary facltes and reduced the tax burden for the ndvdual household. These factors may have reduced the antagonsm towards wldlfe among hunters n the SRCP vllages and may therefore explan the sgnfcant negatve sgn of SRCP. The Probt analyss demonstrated that households from Serenget are more lkely to partcpate n llegal huntng than households from Bunda. The Tobt estmaton results show, however, that the number of huntng trps s lower for hunters from Serenget. Hence, whle the Serenget households are more lkely to partcpate n huntng, huntng ntensty seems to be hgher among the Bunda hunters. Model (a) and (b) show that the amount of land cultvated for crops has no mpact on the number of huntng trps. When dstngushng between land devoted to cotton, maze and mllet n model (c), the coeffcents of L_COT and L_MAI are negatve, and sgnfcant at the one per cent level. In contrast, huntng ntensty s an ncreasng functon of the amount of land devoted to mllet. Ths result s surprsng but may be due to mllet, as apposed to cotton and maze, beng produced only for own consumpton. Ths may ndcate that ncreased producton for the purpose of consumpton ncreases huntng ntensty. However, there s no evdence that market accessblty affects the relatonshp between huntng ntensty, and mllet and maze producton respectvely. See model (d). The theory predcts a postve mpact of wldlfe-nduced damage on huntng ntensty. The estmated coeffcents suggest that the number of trps s sgnfcantly hgher for households experencng very much damage to crops over the no or lttle damage level. In addton, 15 Ths s also the case when ncludng MEAT_1 and MEAT_2 n models (b)-(d).

17 16 model (b) shows that more extensve damage to domestc anmals, as well as reduced anmal stock, ncreases the number of huntng trps 16, 17. Table 7 about here 5. Dscusson and concludng remarks Incentves to hunt llegally are detrmental to wldlfe conservaton n protected areas n developng countres. Understandng the underlyng motvaton for llegal huntng s crucal f sound advce s to be provded to polcymakers who are attemptng to both conserve wldlfe and promote economc development. Despte ths, lttle emprcal attenton has been pad to the ssue. Ths paper estmates models of the probablty of huntng llegally n general, the probablty of huntng n the vllage area and n the protected area respectvely, and huntng ntensty wthn the group of hunters. Cross-sectonal data from a household survey n western Serenget, Tanzana, s used to dentfy factors determnng the patterns of llegal huntng n ths area. The emprcal results suggest that the probablty of both llegal huntng n the vllage area and n the protected area are ndependent of partcpaton n the ntegrated conservaton and development project n western Serenget, namely the Serenget Regonal Conservaton Project (SRCP). In contrast, huntng ntensty s lower for hunters from SRCP vllages. However, t s mportant to note that a concluson on the mpact of the establshment of the SRCP cannot be based on ths result only, as the data set analysed here contans no tme seres. Further, even for a fxed ntensty of llegal huntng, the huntng actvty of the SRCP may have an unntended mpact on wldlfe conservaton (see Barrett and Arcese (1998) for a theoretcal and numercal analyss). Further nvestgatons of the mpact of the SRCP on llegal huntng and wldlfe conservaton s therefore of major mportance. The analyss reveals another mportant relatonshp, namely that huntng n western Serenget seems to be related to land use n agrculture. Whle the total amount of land has no mpact on the probablty of huntng and the number of huntng trps, some types of crops are detrmental to the huntng actvty. Households who use a relatvely large acreage for maze 16 The same apples f Y and D ANIMAL _1 and D ANIMAL _2 are ncluded n models (c)-(e). 17 Note, however, that a problem of causalty may be present here, as households wth fewer trps are able to spend more tme protectng ther land and anmal assets.

18 17 producton are less lkely to hunt, both n the vllage area and n the protected area. Further, the ntensty of huntng s negatvely related to the amount of land cultvated for maze, as well as cotton. However, there s no support n ths analyss for the vew that the ablty to sell food crops wll reduce llegal huntng. Nonetheless, polces that stmulate ncreased maze and cotton producton and reduced mllet producton have the potental to reduce huntng pressure. However, t s mportant to note that any agrcultural expanson nvolvng land clearng may have a negatve mpact on wldlfe conservaton due to reduced wldlfe habtat. Wldlfe mposes damage on agrcultural crops, and the emprcal results ndcate that the mpresson of very much damage to crops, as well as much or very much damage to domestc anmals, ncreases huntng ntensty among the hunters. These results should encourage polcymakers to take ntatves to reduce and prevent wldlfe-nduced damage, such as encouragng fencng, chasng problem anmals out of vllages, and so forth. Another opton s to compensate the local peasants for the costs of lvng wth wldlfe. There are, however, some obvous ptfalls to ths strategy; people may overestmate the damage and a compensaton scheme may attract people from other areas and thereby ncrease human pressure on the park borders. In summary, our emprcal results show that huntng ntensty s lower for hunters from SRCP vllages. Other ntatves that may reduce llegal huntng nclude encouragng ncreased cotton and maze producton and more extensve use of damage control. Further, such attempts may add more to local ncome than can be expected from SRCP as t works today (see also Barrett and Arcese (1998)). The data set shows that the average ncome from agrculture among cotton producers s some tzh, whch s more than twce that of noncotton producers. By comparson, records from the SRCP show that expected revenue from the meat-dstrbuton program s some tzh per household. These fgures mply that the potental gan from the SRCP for the ndvdual household s very lmted. In order to fulfl the jont objectve of wldlfe conservaton and mproved welfare wthn local communtes, focus should also be on agrcultural polces.

19 18 References Arcese, P. et al. (1995): ''Hstorcal and present-day antpoachng n Serenget'', n Snclar, A.R.E. and P. Arcese, eds., Serenget II, Chcago: Unversty of Chcago Press, Barrett, C.B. and Arcese, P. (1995): ''Are ntegrated conservaton-development projects (ICDPs) sustanable? On the conservaton of large mammals n Sub-Saharan Afrca'', World Development, 23: Barrett, C.B. and P. Arcese (1998): ''Wldlfe harvest n ntegrated conservaton and development projects: lnkng harvest to household demand, agrcultural producton, and envronmental shocks n the Serenget'', Land Economcs, 74: Brandon, K.E. and M. Wells (1992): ''Plannng for people and parks: desgn dlemmas'', World Development, 20: Brown, K. et al. (1993): ''Economcs and the conservaton of global bologcal dversty'', Global Envronmental Faclty, Workng Paper No. 2, The World Bank, New York. Bulte, E.H. and G.C. van Kooten (1999): ''Economcs of antpoachng enforcement and the vory trade ban'', Amercan Journal of Agrcultural Economcs, 81: Campbell, K. and H. Hofer (1995): ''People and wldlfe: Spatal dynamcs and zones of nteracton'', n Snclar, A.R.E. and P. Arcese, eds., Serenget II, Chcago: Unversty of Chcago Press, Carlson, G.A. and M.E. Wetzsten (1994): ''Pestcdes and pest management'', n Carlson, G.A., D. Zlberman, and J.A. Mranowsk, eds., Agrcultural and Envronmental Resource Economcs, Oxford: Oxford Unversty Press, Gbson, C.C. and S.A. Marks (1995): ''Transformng rural hunters nto conservatonsts: An assessment of communty-based wldlfe management programs n Afrca'', World Development, 23:

20 19 Huffaker, R.G., M.G. Bhat, and S.M. Lenhart (1992): ''Optmal trappng strateges for dffusng nusance-beaver populatons'', Natural Resource Modelng, 6: Johannesen, A.B. (2004): ''Desgnng Integrated Conservaton and Development Projects (ICDP): Illegal huntng, wldlfe conservaton and the welfare of the local people'', Workng Paper Seres, 2, Department of Economcs, NTNU, Norway. Johnston, J. and J. Dnardo (1997): Econometrc Methods, Sngapore McGraw Hll. Kss, A. (1990): ''Lvng wth wldlfe: Wldlfe resources management wth local partcpaton n Afrca.'' Techncal Paper No. 130, World Bank, Washngton D.C. Leader-Wllams, N. and E.J. Mlner-Gulland (1993): ''Polces for the enforcement of wldlfe laws: The balance between detecton and penaltes n Luangwa valley, Zamba'', Conservaton Bology, 7: Rugumayo, C.R. (1999): ''The partcpaton n sustanable resource management. The case of Serenget Regonal Conservaton Strategy, Tanzana'', Workng Paper No 112, Norwegan Insttute for Urban and Regonal Research, Oslo. Schulz, C.E. and A. Skonhoft (1996): ''Wldlfe management, land-use and conflcts'', Envronment and Development Economcs, 1: Snclar, A.R.E. (1995): ''Serenget past and present'', n Snclar, A.R.E. and P. Arcese, eds., Serenget II, Chcago: Unversty of Chcago Press, Snclar, A.R.E. and P. Arcese (1995): Serenget II, Chcago: Unversty of Chcago Press. Skonhoft, A. (1999): ''On the optmal explotaton of terrestral anmal speces'', Envronmental and Resource Economcs, 13:

21 20 Skonhoft, A. and J.T. Solstad (1998): ''The poltcal economy of wldlfe explotaton'', Land Economcs, 74: Smth, V.L. (1975): ''The prmtve hunter culture, plestocene extncton, and the rse of agrculture'', Journal of Poltcal Economy, 83: SRCS (1993): ''Implementaton report of the development actvtes for the year 1993''. Prepared for the Mnstry of Natural Resources and Toursm, Wldlfe Dvson, Dar es Salaam, Tanzana. SRCS (1995): ''Implementaton report of the development actvtes for the fnancal year 1994/95''. Prepared for the Mnstry of Natural Resources and Toursm, Wldlfe Dvson, Dar es Salaam, Tanzana. Zvn, J., B.M. Hueth, and D. Zlberman (2000): ''Managng a multple-use resource: The case of feral pg management n Calforna rangeland'', Journal of Envronmental Economcs and Management, 39: Wells, M. and K. Brandon (1992): ''People and Parks: Lnkng Protected Area Management wth Local Communtes'', World Bank, World Wldlfe Fund and U.S. Agency for Internatonal Development, Washngton DC.

22 21 Tables Table 1: Dstrbuton of reported partcpaton n huntng. Number Partcpaton No partcpaton Total sample (27%) 217 (73%) SRCP (32%) 101 (68%) Not SRCP (22%) 116 (78%) Bunda Dstrct (22%) 130 (78%) Serenget Dstrct (34%) 87 (66%)

23 22 Table 2: Dstrbuton of households nvolved n huntng. Number Huntng n vllage area Huntng trps Number (45%) 44 (55%) SRCP (57%) 20 (43%) Not SRCP 33 9 (27%) 24 (73%) Bunda Dstrct 36 5 (14%) 31 (86%) Serenget Dstrct (70%) 13 (30%)

24 23 Table 3: Number of households earnng ncome from varous actvtes. Crops Domestc anmals Non-agrculture* Total sample SRCP 100 (68%) 58 (39%) 66 (45%) Not SRCP 120 (81%) 95 (64%) 44 (30%) Bunda Dstrct** 142 (86%) 74 (45%) 67 (40%) Serenget Dstrct** 78 (60%) 79 (60%) 43 (33%) *Non-agrcultural actvtes do not nclude huntng. **Per cent of the number of sample households n the respectve sub-group.

25 24 Table 4: Dstrbuton of reported wldlfe-nduced damage to crops and domestc anmals. Response categores: No Very lttle Much Very much Total P* damage Number of respondents Crop % of respondents damage Mean % damage Number of respondents Damage % of respondents domestc Mean pultry lost/njured anmals Mean lvestoc lost/njured** *P s the observed sgnfcance level. The null hypothess of equal means s rejected for P **Here lvestock ncludes cattle, goats, and sheep.

26 25 Table 5: Probt and Ordered Probt estmaton results. t-values n parentheses Probt (a) (b) (c) (d) Ordered probt (a) (b) (c) (d) CONS (-0.80) (0.61) (0.34) (-0.76) SRCP 0.388** (1.98) (1.56) (-0.23) (0.12) (1.06) (0.76) (-1.11) (-0.34) DISTRICT *** (-2.80) *** (-3.05) *** (-2.69) (-0.37) (-1.25) * (-1.85) (-1.00) (0.70) L (-0.85) * (-1.91) (-0.69) * (-1.81) L_COT (-1.16) (-1.49) L_MAI *** (-3.63) (-1.20) *** (-3.61) (-1.50) L_MIL (0.03) (0.56) (0.40) (0.96) COT (-0.16) (-0.42) MOT_MAI (1.10) (1.10) L_MAI*MOT_ MAI (-1.45) (-1.17) L_MIL*COT (-0.80) (-1.00) L_MIL* MOT_MAI (0.32) (0.15) Y (-0.95) (-1.26) D CROP _ * (1.72) (0.69) (1.20) (0.98) 0.456* (1.66) (0.73) (1.11) (0.90) D CROP _ (1.23) (0.03) (1.56) (1.06) 0.400* (1.64) (0.34) 0.514** (2.00) (1.32) D ANIMAL _ (1.29) 0.430* (1.86) D ANIMAL _ (-0.37) (0.16) M (-1.40) DISTANCE (-1.29) Log-lkelhood # obs. 293 R 2 adj (-0.46) (-0.97) (-1.57) (0.35) (-1.51) (0.32) * (-1.76) (-1.04) (-0.83) (-0.79) ** (-2.02) (0.59) * (-1.74) (0.41) ***, ** and * sgnfcant at 1, 5 and 10% respectvely. Table A3.1, Appendx 3, reports the varable defntons.

27 Table 6: Margnal effects Ordered Probt model. t-values n parentheses Pr( Eh = 1 ) / x Pr( Eh = 2 ) / x Pr( Eh = 3 ) / x (a) (b) (c) (d) (a) (b) (c) (d) (a) (b) (c) (d) SRCP (-1.07) (-0.76) (1.13) (0.35) (1.05) (0.76) (-1.11) (-0.34) (1.06) (0.76) (-1.13) (-0.35) DISTRICT (1.25) 0.127* (1.86) (1.00) (-0.69) (-1.24) * (-1.77) (-1.00) (0.70) (-1.24) * (-1.81) (-0.99) (0.68) L (0.69) 0.017* (1.86) (-0.69) * (-1.68) (-0.69) * (-1.86) L_COT (1.51) (-1.45) (-1.51) L_MAI 0.059*** (3.94) (1.55) *** (-3.10) (-1.43) *** (-3.96) (-1.55) L_MIL (-0.40) (-0.96) (0.40) (0.94) (0.40) (0.96) COT (0.42) (-0.42) (-0.42) MOT_MAI (-1.05) (1.11) (1.00) L_MAI*MOT_ MAI (1.19) (-1.14) (-1.19) L_MIL*COT (1.01) (-0.98) (-1.01) L_MIL*MOT_ MAI (-0.15) (0.15) (0.15) Y (1.28) (-1.21) (-1.28) D CROP _ (-1.59) (-0.70) (-1.06) (-0.84) 0.044* (1.77) (0.74) (1.12) (0.90) (1.50) (0.68) (1.01) (0.80) D CROP _ * (-1.70) (-0.34) ** (-2.12) (-1.42) (1.60) (0.34) 0.060** (1.98) (1.33) 0.084* (1.71) (0.34) 0.087** (2.10) (1.43) D ANIMAL _ * (-1.79) 0.040* (1.79) 0.095* (1.72) D ANIMAL _ (-0.16) (0.16) (0.16) M 0.014* (1.77) (0.83) 0.015** (2.04) 0.015* (1.77) * (-1.68) (-0.81) * (-1.91) * (-1.64) * (-1.77) (-0.83) ** (-2.02) * (-1.75) DISTANCE (1.04) (0.79) (-0.60) (-0.41) (-1.03) (-0.78) (0.59) (0.41) (-1.04) (-0.79) 0.002** (0.60) (0.41) ***, ** and * sgnfcant at 1, 5 and 10% respectvely. Varable defntons are reported n Table A3.1 n Appendx 3.

28 1 Table 7: Tobt estmaton results. Dependent varable s number of huntng trps; t-values n parentheses (a) (b) (c) (d) (e) CONS (-0.81) SRCP ** (-2.40) 3.503* (1.69) *** (-2.92) (-0.41) *** (-4.23) (1.03) *** (-2.75) (-0.75) * (-1.94) MEAT_ (1.20) MEAT_ (0.46) DISTRICT 5.632*** (4.32) L (0.17) 3.365*** (3.61) (-0.58) 6.038*** (5.20) L_COT ** (-2.30) L_MAI *** (-2.76) L_MIL 0.558** (2.02) 7.054*** (5.31) *** (-2.76) (1.34) COT *** (-2.96) MOT_MAI (-0.10) L_MAI*MOT_MAI (1.15) L_MIL*COT (1.09) L_MIL*MOT_MAI (0.04) Y *** (-2.80) D CROP _ (1.26) D CROP _ ** (2.11) (0.99) 3.902** (2.37) (1.53) 4.875*** (2.78) (0.88) 3.678* (1.94) 5.634*** (4.31) (0.29) (1.18) 4.811** (2.11) D ANIMAL _ *** (4.33) D ANIMAL _ *** (3.76) M (-0.43) (-2.07) (-0.71) (-1.05) (0.47) DISTANCE (-0.97) ** (-2.20) (0.92) (0.55) (-1.17) Log-lkelhood # obs. R 2 adj ***, ** and * sgnfcant at 1, 5 and 10% respectvely. Table A3.1, Appendx 3, reports the varable defntons.

29 2 Appendx 1 Table A1.1: Multnomnal Logt estmaton results. t-values n parentheses. Vllage area (a) (b) (c) (d) Protected area (a) (b) (c) (d) CONS ** (-1.94) (-1.03) (-1.10) * (-1.64) ** (-2.12) (-0.68) (-1.37) ( SRCP 1.727*** (3.59) 2.370*** (3.29) 1.328** (1.95) (1.39) (-0.29) (-0.56) * (-1.65) (-0.88) DISTRICT *** (-5.19) *** (-4.20) *** (-4.80) *** (-2.68) (1.14) (0.53) (1.04) 1.808** (2.06) L (-0.94) * (-1.22) (-0.41) * (-1.77) L_COT (-0.17) (-1.45) L_MAI * (-1.63) (-0.03) *** (-2.64) * (-1.92) L_MIL (-0.61) (-0.03) (0.73) (1.49) COT (0.29) MOT_MAI (0.62) (-0.55) (0.63) L_MAI*MOT_ MAI (-1.08) (0.45) L_MIL*COT (-0.04) (-1.13) L_MIL* MOT_MAI (0.21) (-0.47) Y (0.17) * (-1.81) D CROP _ (1.60) (1.29) (1.44) (1.32) (1.31) (0.84) (0.85) (0.90) D CROP _ (-0.38) (-0.78) (-0.11) (0.17) 1.208* (1.86) (1.12) 1.460** (2.17) (1.48) D ANIMAL _ (-0.90) D ANIMAL _ ** (-2.01) 1.197** (2.26) (1.08) M (0.02) (0.66) (-0.20) (-0.93) ** (-1.94) (-1.17) ** (-1.97) * (-1.43) DISTANCE (-0.04) (-0.11) (0.24) (0.59) (-0.67) (-0.49) (0.56) (0.57) Log-lkelhood # obs. R 2 adj ***, ** and * sgnfcant at 1, 5 and 10% respectvely. Table A3.1, Appendx 3, reports the varable defntons.