Conservation efforts are under constant threat of failure due to poaching. Efforts to combat poaching may take a number of forms, but access to each form depends on resources, and access to these resources may depend on the success of previous efforts (e.g., monetary donations from supporters could directly combat poaching, but may be more effective if partially spent on recruiting additional supporters who then also donate). We adopted a mathematical framework with inspiration from the famous colonel blotto game to model the ongoing battle between conservationists and poachers. Focusing on a marine setting as a case study, players have budgets consisting of three types of resources: monetary, non-monetary, and supporters. The heterogeneous battlefields (laws, marine reserves, and community) reflect commonly employed conservation tactics meant to limit poaching. conservationists allocate resources to limit the success of poachers, while poachers allocate resources to overcome barriers implemented by conservationists. We assumed that no action can succeed without supporters, and thus whichever player wins over all the supporters in the community (i.e., the community battlefield), wins the game. We analyzed battlefield payoffs and player budget distributions to determine overall player success. We demonstrated how initially disadvantaged players may have an opportunity to win the game, although, we found that success in the first round can be most critical under certain scenarios. By framing the question in this way, we hope to provide additional tools for decision support to guide resource allocation, improving the efficacy of conservation efforts.
Citation: Maggie R. Sullens, Nina H. Fefferman. Budget allocation and illegal fishing: a game theoretic approach[J]. Mathematical Biosciences and Engineering, 2025, 22(6): 1307-1341. doi: 10.3934/mbe.2025049
Conservation efforts are under constant threat of failure due to poaching. Efforts to combat poaching may take a number of forms, but access to each form depends on resources, and access to these resources may depend on the success of previous efforts (e.g., monetary donations from supporters could directly combat poaching, but may be more effective if partially spent on recruiting additional supporters who then also donate). We adopted a mathematical framework with inspiration from the famous colonel blotto game to model the ongoing battle between conservationists and poachers. Focusing on a marine setting as a case study, players have budgets consisting of three types of resources: monetary, non-monetary, and supporters. The heterogeneous battlefields (laws, marine reserves, and community) reflect commonly employed conservation tactics meant to limit poaching. conservationists allocate resources to limit the success of poachers, while poachers allocate resources to overcome barriers implemented by conservationists. We assumed that no action can succeed without supporters, and thus whichever player wins over all the supporters in the community (i.e., the community battlefield), wins the game. We analyzed battlefield payoffs and player budget distributions to determine overall player success. We demonstrated how initially disadvantaged players may have an opportunity to win the game, although, we found that success in the first round can be most critical under certain scenarios. By framing the question in this way, we hope to provide additional tools for decision support to guide resource allocation, improving the efficacy of conservation efforts.
| [1] |
K. T. Everatt, R. Kokes, C. Lopez Pereira, Evidence of a further emerging threat to lion conservation; targeted poaching for body parts, Biodiversity Conserv., 28 (2019), 4099–4114. https://doi.org/10.1007/s10531-019-01866-w doi: 10.1007/s10531-019-01866-w
|
| [2] |
M. Linkie, D. J. Martyr, J. Holden, A. Yanuar, A. T. Hartana, J. Sugardjito, et al., Habitat destruction and poaching threaten the Sumatran tiger in Kerinci Seblat National Park, Sumatra, Oryx, 37 (2003), 41–48. 10.1017/S0030605303000103 doi: 10.1017/S0030605303000103
|
| [3] |
F. M. Guebert, M. Barletta, M. F. da Costa, Threats to sea turtle populations in the Western Atlantic: Poaching and mortality in small-scale fishery gears, J. Coastal Res., 65 (2013), 42–47. https://doi.org/10.2112/SI65-008.1 doi: 10.2112/SI65-008.1
|
| [4] |
T. Ramesh, R. Kalle, H. Rosenlund, C. T. Downs, Low leopard populations in protected areas of Maputaland: A consequence of poaching, habitat condition, abundance of prey, and a top predator, Ecol. Evol., 7 (2017), 1964–1973. https://doi.org/10.1002/ece3.2771 doi: 10.1002/ece3.2771
|
| [5] |
F. He, C. Zarfl, V. Bremerich, A. Henshaw, W. Darwall, K. Tockner, et al., Disappearing giants: A review of threats to freshwater megafauna, WIREs Water, 4 (2017), e1208. https://doi.org/10.1002/wat2.1208 doi: 10.1002/wat2.1208
|
| [6] |
T. Kuiper, B. Kavhu, N. A. Ngwenya, R. Mandisodza-Chikerema, E. J. Milner-Gulland, Rangers and modellers collaborate to build and evaluate spatial models of African elephant poaching, Biol. Conserv., 243 (2020), 108486. https://doi.org/10.1016/j.biocon.2020.108486 doi: 10.1016/j.biocon.2020.108486
|
| [7] |
R. Sukumar, U. Ramakrishnan, J. A. Santosh, Impact of poaching on an Asian elephant population in Periyar, southern India: A model of demography and tusk harvest, Animal Conserv., 1 (1998), 281–291. https://doi.org/10.1111/j.1469-1795.1998.tb00039.x doi: 10.1111/j.1469-1795.1998.tb00039.x
|
| [8] |
D. M. P. Jacoby, F. Ferretti, R. Freeman, A. B. Carlisle, T. K. Chapple, D. J. Curnick, et al., Shark movement strategies influence poaching risk and can guide enforcement decisions in a large, remote marine protected area, J. Appl. Ecol., 57 (2020), 1782–1792. https://doi.org/10.1111/1365-2664.13654 doi: 10.1111/1365-2664.13654
|
| [9] |
K. Norris, Managing threatened species: The ecological toolbox, evolutionary theory and declining-population paradigm, J. Appl. Ecol., 41 (2004), 413–426. https://doi.org/10.1111/j.0021-8901.2004.00910.x doi: 10.1111/j.0021-8901.2004.00910.x
|
| [10] |
E. Cortés, Incorporating uncertainty into demographic modeling: Application to shark populations and their conservation, Conserv. Biol., 16 (2002), 1048–1062. https://doi.org/10.1046/j.1523-1739.2002.00423.x doi: 10.1046/j.1523-1739.2002.00423.x
|
| [11] |
L. Hannah, G. F. Midgley, D. Millar, Climate change-integrated conservation strategies, Global Ecol. Biogeogr., 11 (2002), 485–495. https://doi.org/10.1046/j.1466-822X.2002.00306.x doi: 10.1046/j.1466-822X.2002.00306.x
|
| [12] |
M. Drechsler, F. Wätzold, K. Johst, H. Bergmann, J. Settele, A model-based approach for designing cost-effective compensation payments for conservation of endangered species in real landscapes, Biol. Conserv., 140 (2007), 174–186. https://doi.org/10.1016/j.biocon.2007.08.013 doi: 10.1016/j.biocon.2007.08.013
|
| [13] |
M. L. Baskett, R. M. Nisbet, C. V. Kappel, P. J. Mumby, S. D. Gaines, Conservation management approaches to protecting the capacity for corals to respond to climate change: A theoretical comparison, Global Change Biol., 16 (2010), 1229–1246. https://doi.org/10.1111/j.1365-2486.2009.02062.x doi: 10.1111/j.1365-2486.2009.02062.x
|
| [14] |
A. Dell'Apa, M. C. Smith, M. Y. Kaneshiro-Pineiro, The influence of culture on the international management of shark finning, Environ. Manage., 54 (2014), 151–161. https://doi.org/10.1007/s00267-014-0291-1 doi: 10.1007/s00267-014-0291-1
|
| [15] |
S. Clarke, E. J. Milner-Gulland, T. Bjørndal, Social, economic, and regulatory drivers of the shark fin trade, Marine Resour. Econ., 22 (2007), 305–327. https://doi.org/10.1086/mre.22.3.42629561 doi: 10.1086/mre.22.3.42629561
|
| [16] |
V. D. Truong, N. V. H. Dang, C. M. Hall, The marketplace management of illegal elixirs: Illicit consumption of rhino horn, Consumption Mark. Culture, 19 (2016), 353–369. https://doi.org/10.1080/10253866.2015.1108915 doi: 10.1080/10253866.2015.1108915
|
| [17] |
F. Ferretti, D. M. P. Jacoby, M. O. Pfleger, T. D. White, F. Dent, F. Micheli, et al., Shark fin trade bans and sustainable shark fisheries, Conserv. Lett., 13 (2020), e12708. https://doi.org/10.1111/conl.12708 doi: 10.1111/conl.12708
|
| [18] |
D. S. Shiffman, R. E. Hueter, A United States shark fin ban would undermine sustainable shark fisheries, Marine Policy, 85 (2017), 138–140. https://doi.org/10.1016/j.marpol.2017.08.026 doi: 10.1016/j.marpol.2017.08.026
|
| [19] |
C. Brewer, Outreach and partnership programs for conservation education where endangered species conservation and research occur, Conserv. Biol., 16 (2002), 4–6. https://doi.org/10.1046/j.1523-1739.2002.01613.x doi: 10.1046/j.1523-1739.2002.01613.x
|
| [20] | J. Maschinski, S. J. Wright, C. Lewis, The critical role of the public: Plant conservation through volunteer and community outreach projects, in Plant Reintroduction in A Changing Climate: Promises and Perils, Springer Nature, (2012), 53–69. https://doi.org/10.5822/978-1-61091-183-2_4 |
| [21] |
M. Fabinyi, Historical, cultural and social perspectives on luxury seafood consumption in China, Environ. Conserv., 39 (2012), 83–92. 10.1017/S0376892911000609 doi: 10.1017/S0376892911000609
|
| [22] |
J. M. Macharia, T. Thenya, G. G. Ndiritu, Management of highland wetlands in central Kenya: The importance of community education, awareness and eco-tourism in biodiversity conservation, Biodiversity, 11 (2010), 85–90. https://doi.org/10.1080/14888386.2010.9712652 doi: 10.1080/14888386.2010.9712652
|
| [23] |
C. F. Camerer, Progress in behavioral game theory, J. Econ. Perspect., 11 (1997), 167–188. https://doi.org/10.1257/jep.11.4.167 doi: 10.1257/jep.11.4.167
|
| [24] | P. Kohli, M. Kearns, Y. Bachrach, R. Herbrich, D. Stillwell, T. Graepel, Colonel Blotto on Facebook: The effect of social relations on strategic interaction, in Proceedings of the 4th Annual ACM Web Science Conference, (2012), 141–150. https://doi.org/10.1145/2380718.2380738 |
| [25] |
S. Guan, J. Wang, H. Yao, C. Jiang, Z. Han, Y. Ren, Colonel blotto games in network systems: Models, strategies, and applications, IEEE Trans. Network Sci. Eng., 7 (2019), 637–649. https://doi.org/10.1109/TNSE.2019.2904530 doi: 10.1109/TNSE.2019.2904530
|
| [26] | A. Collins, P. T. Hester, Colonel Blotto games and Lancaster's equations: A novel military modeling combination, in Selected Papers Presented at MODSIM World 2011 Conference and Expo, (2012), 93–99. |
| [27] | Y. Wu, B. Wang, K. J. R. Liu, Optimal power allocation strategy against jamming attacks using the Colonel Blotto game, in GLOBECOM 2009–2009 IEEE Global Telecommunications Conference, (2009), 1–5. https://doi.org/10.1109/GLOCOM.2009.5425760 |
| [28] |
E. Boix-Adserà, B. L. Edelman, S. Jayanti, The multiplayer colonel blotto game, Games Econ. Behav., 129 (2021), 15–31. https://doi.org/10.1016/j.geb.2021.05.002 doi: 10.1016/j.geb.2021.05.002
|
| [29] |
X. Li, J. Zheng, Pure strategy Nash Equilibrium in 2-contestant generalized lottery colonel blotto games, J. Math. Econ., 103 (2022), 102771. https://doi.org/10.1016/j.jmateco.2022.102771 doi: 10.1016/j.jmateco.2022.102771
|
| [30] | D. Kovenock, B. Roberson, Generalizations of the general lotto and colonel blotto games, Econ. Theory, 71 (2021), 997–1032. |
| [31] | I. M. Sonin, Blotto game with testing (the locks, bombs and testing model), Stochastics, 96 (2024), 2009–2036. |
| [32] | S. Behnezhad, S. Dehghani, M. Derakhshan, M. Hajiaghayi, S. Seddighin, Fast and simple solutions of Blotto games, Oper. Res., 71 (2023), 506–516. |
| [33] |
D. G. Hernández, D. H. Zanette, Evolutionary dynamics of resource allocation in the Colonel Blotto game, J. Stat. Phys., 151 (2013), 623–636. https://doi.org/10.1007/s10955-012-0659-7 doi: 10.1007/s10955-012-0659-7
|
| [34] | G. Schwartz, P. Loiseau, S. S. Sastry, The heterogeneous colonel blotto game, in 2014 7th International Conference on NETwork Games, COntrol and OPtimization (NetGCoop), (2014), 232–238. |
| [35] | A. Mahajan, D. Teneketzis, Multi-armed bandit problems, in Foundations and Applications of Sensor Management, Springer, (2008), 121–151. |
| [36] | B. Roberson, The colonel blotto game, Econ. Theory, 29 (2006), 1–24. https://doi.org/10.1007/s00199-005-0071-5 |
| [37] |
E. Borel, The theory of play and integral equations with skew symmetric kernels, Econometrica, 21 (1953), 97–100. https://doi.org/10.2307/1906946 doi: 10.2307/1906946
|
| [38] | K. Sigmund, Introduction to evolutionary game theory, Proceed. Symp. Appl. Math., 69 (2011), 1–26. |
| [39] | K. Sigmund, M. A. Nowak, Evolutionary game theory, Curr. Biol., 9 (1999), R503–R505. https://doi.org/10.1016/S0960-9822(99)80321-2 |
| [40] | G. Oviedo, Community conserved areas in South America, Parks, 16 (2006), 49–55. |
| [41] |
V. Nijman, Illegal trade in protected sharks: The case of artisanal whale shark meat fisheries in Java, Indonesia, Animals, 13 (2023), 2656. https://doi.org/10.3390/ani13162656 doi: 10.3390/ani13162656
|
| [42] |
C. Leisher, S. Mangubhai, S. Hess, H. Widodo, T. Soekirman, S. Tjoe, et al., Measuring the benefits and costs of community education and outreach in marine protected areas, Mar. Policy, 36 (2012), 1005–1011. https://doi.org/10.1016/j.marpol.2012.02.022 doi: 10.1016/j.marpol.2012.02.022
|
| [43] |
A. García, G. Ceballos, R. Adaya, Intensive beach management as an improved sea turtle conservation strategy in Mexico, Biol. Conserv., 111 (2003), 253–261. https://doi.org/10.1016/S0006-3207(02)00300-2 doi: 10.1016/S0006-3207(02)00300-2
|
| [44] | G. D. Aguilar, Philippine fishing boats, in Turbulent Seas: The Status of Philippine Marine Fisheries, Coastal Resource Management Project, (2004), 118–121. |
| [45] |
V. M. Marsh, W. Mutemi, E. S. Some, A. Haaland, R. W. Snow, Evaluating the community education programme of an insecticide-treated bed net trial on the Kenyan coast, Health Policy Plann., 11 (1996), 280–291. https://doi.org/10.1093/heapol/11.3.280 doi: 10.1093/heapol/11.3.280
|
| [46] |
F. Herbig, A. Minnaar, Pachyderm poaching in Africa: Interpreting emerging trends and transitions, Crime Law Soc. Change, 71 (2019), 67–82. https://doi.org/10.1007/s10611-018-9789-4 doi: 10.1007/s10611-018-9789-4
|
| [47] |
A. Chanyandura, V. K. Muposhi, E. Gandiwa, N. Muboko, An analysis of threats, strategies, and opportunities for African rhinoceros conservation, Ecol. Evol., 11 (2021), 5892–5910. https://doi.org/10.1002/ece3.7536 doi: 10.1002/ece3.7536
|