Interactive Dynamics of Wildlife Populations, Human Health and Household Wealth Matthew D. Potts mdpotts@berkeley.edu www.pottsgroup.org 1
Objectives • Illustrate that the inclusion of human health in simple bioeconomic models of wildlife harvesting can significantly alter model behavior. • Demonstrate the functional form of feedbacks matter in models of coupled natural human systems.
Acknowledgments • Collaborators: Elaina Marshalek, Ryan Marsh, Samuel Evans, Lauren Withey • Biodiversity, Health and Livelihoods Team: Berkeley, Tanzania, Madgascar & Ghana • NSF Funding: GEO-115057, CNH: Interactive Dynamics of Wildlife Populations, Human Health and Household Wealth in Rural Africa. 3
Biodiversity & Livelihoods Wildlife is the primary source of animal protein and income for more than 1 billion people (Milner-Guilland et. al. 2003). J. Brashares How do we identify feasible strategies to improve peoples livelihoods and conserve biodiversity? J. Brashares 4
Biodiversity & Livelihoods Research has clearly demonstrated linkages between wealth, income and wildlife consumption. Wildlife Consumption & Wealth Distance to Wildlife Effects 5
Biodiversity & Health Global Anemia Prevalence 6
Biodiversity & Health Impact of Bushmeat on Hemoglobin Bushmeat could contribute app. If access to bushmeat is lost, 60-80% of what iron supplements there will be a 30% increase in accomplish the incidence of anemia C. Golden - Madagascar 7
Biodiversity, Health & Livelihoods Guiding Questions • How does the inclusion of health in bioeconomic models of wildlife harvesting effect wildlife population dynamics and overall household well-being? • What impact does the inclusion of health effects have on management strategies aimed at either conserving wildlife or improving overall household well-being? 8
Modeling Approach • Track utility and nutritional status of a “representative” subsistence household in a developing country. • In each time period, households allocates labor to hunting and agriculture so as to maximize utility in that period (not forward looking). • Nutritional status determines total amount of labor available and is updated period to period. • Wildlife population follows logistic growth with off take determined by hunting activity. • Human population growing through time. • Wildlife population goes extinct when population falls below 20% of carrying capacity. 9
Twelve Model Variations Management Interventions Labor dependence on nutritional status I. None (NM) I. No impact II. Improve agricultural yields (Ag) X II. Impacts total labor III. Conserve game (G) III. Impacts total labor & farm IV. Restrict access to game & improve labor agricultural yields (Ag & G) 10
Nitty Gritty Model Details Utility Function Key Variables Constraints Labor State Equations State Equations 11
Results (Implemented & Solved in GAMS) 12
Labor Allocation Management Intervention None Ag & Conservation Conserve Game Increase Ag 1.0 1.0 1.0 1.0 No Impact 0.8 0.8 0.8 0.8 Labor dependence on nutritional status 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 0.2 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 1.0 1.0 1.0 1.0 Total Labor 0.8 0.8 0.8 0.8 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 0.2 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 Total & Farm Labor 1.0 1.0 1.0 1.0 Farm labor 0.8 0.8 0.8 0.8 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 Hunting 0.2 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 Time Both health effects & management interventions alter patterns of labor allocation. 13 Time
Labor dependence on nutritional status Total & Farm Labor Total Labor No Impact 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 Management intervention do improve health in short run. 0 0 0 100 100 100 None 200 200 200 Time 300 300 300 400 400 400 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0 0 0 100 100 100 Nutrition Increase Ag Management Intervention 200 200 200 300 300 300 14 400 400 400 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0 0 0 Value Conserve Game 100 100 100 200 200 200 300 300 300 400 400 400 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0 0 0 Ag & Conservation 100 100 100 200 200 200 Time 300 300 300 400 400 400
Time to Collapse of Game Population Management Intervention None Increase Ag Conserve Game Ag & Conservation 500 500 500 500 400 400 400 400 No Impact Labor dependence on nutritional status 300 300 300 300 200 200 200 200 100 100 100 100 0 0 0 0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 500 500 500 500 Total Labor 400 400 400 400 300 300 300 300 200 200 200 200 100 100 100 100 0 0 0 0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 500 500 500 500 Total & Farm Labor 400 400 400 400 300 300 300 300 200 200 200 200 100 100 100 100 0 0 0 0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 Time Conserving game with health effects does not prevent game collapse. 15 Time
Conclusions • Incorporation of nutritional status and linking it to labor availability and allocation can dramatically change the time to extinction of wild game species. • Efficacy of management interventions depends on assumptions about household health and labor allocation. 16
General thoughts on modeling coupled natural-human systems Two Key Issues • Feedbacks • Mean vs. Variance
Thank You! Questions? 18
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