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Long-term effects of family planning and other determinants of fertility on population and environment: agent-based modeling evidence from Wolong Nature Reserve, China

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Abstract

The practice of family planning has a long history, but its environmental implications have not often been considered. Using data from Wolong Nature Reserve for the conservation of the world-famous giant pandas in China, we employ a spatially explicit agent-based model to simulate how family-planning and other fertility-related decisions may affect human population, household number, and panda habitat over time. Simulation results indicate that (1) population size has the shortest time lag in response to changes in family-planning decisions, and panda habitat has the longest time lag; (2) the amount of panda habitat is more sensitive to factors affecting number of households than those affecting population size; (3) although not large in quantity nor changing landscape fragmentation substantially, the associated changes in habitat are in good areas for the panda. This study offers a novel approach to studying long-term demographic and environmental effects of family-planning and fertility-related decisions across space.

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Notes

  1. An agent-based model “predicts or explains emergent higher-level phenomena by tracking the actions of multiple low-level ‘agents’ that constitute, or at least impact, the system behaviors” (An et al. 2005). Agents are objects (e.g., individual people, households, animals) with some degree of self-awareness, intelligence, and knowledge of the environment and other agents. Agents can adjust their own goals or actions in response to changes in other agents or the environment.

  2. In light of frameworks for analysis, research efforts about family planning have been devoted, but not limited, to (1) the effects of family-planning programs (e.g., laws or policies, media, service quality) on contraceptive use, fertility preferences, and realized fertility (e.g., Ross and Issacs 1988); Freedman 1997; Hong et al. 2006; Hutchinson and Wheeler 2006; Demographic and Health Surveys 2009; (2) various clinic-based contraceptive services, their effectiveness on reducing pregnancies and fertility, and people’s opinions or attitudes about them (e.g., Eryilmaz 2006; Foster et al. 2006; Population Council 1998; Steiner et al. 2006); and (3) demographic and socioeconomic characteristics of family-planning participants or non-participants and the psychosocial factors associated with use of family-planning services (e.g., Clarke et al. 2006; Sable et al. 2006).

  3. Other legal activities (e.g., farming) exert much less direct impact on panda habitat. China has a land system in which land is owned by governments and people have usufruct only. Converting forested land to farmland is subject to a very strict approval process, which is even more difficult in Wolong due to its status as a nature reserve.

  4. Fuelwood collection is legal in some parts of the reserve although use of electricity is encouraged.

  5. The one-child policy is implemented in urban areas. Two children are allowed in many rural areas of China.

  6. These rates incorporate deaths caused by all possible factors, such as maternal mortality.

  7. Between the household and the forest, a buffered area is constructed along the straight line connecting them. This buffered area, controlled by a parameter for its size, would help the fuelwood collector stray as little as possible to save energy cost. The collector chooses the cell that has a lower elevation (or the cell with the smallest elevation increase) largely in the direction of the household within the buffer area. To save energy cost, we assume the collector would not turn back once he/she moves to a new cell. He/she will keep searching the cells in front until the target household cell is reached. Calculating the Euclidean distance between each pair of adjacent cells that he/she passes, the model readjusts the distance by dividing the cotangent of the slope angle between the two cells. The sum of all such adjusted distances is defined as the cost distance between the household and the forest. Using the same algorithm, the distances between the household and other potential forest cells can be calculated. The forest cell with the smallest cost distance from the household will be chosen as the fuelwood collection site.

  8. This variable has been shown to have a negative association with fertility (e.g., Jones 2007).

  9. Spacing and timing of births have also received considerable attention as they affect completed fertility (e.g., Kohler and Ortega 2002).

  10. We produce (1) a map of habitat at year 0 (1996); (2) a probability map of habitat in the baseline scenario at year 50 (2046; the same hereafter); (3) a probability map of habitat in the demographic contraction scenario at year 50; and (4) a probability map of habitat in the demographic expansion scenario at year 50. Maps 2–4 are calculated as the averages of the 30 replicates at year 50 and expressed as a probability gradient of 0 (non-habitat) to 1 (habitat).

  11. We measure number of habitat patches, patch cohesion index (a measure of habitat connectivity), mean patch area, contagion (a measure of spatial clumpedness), and Shannon evenness index (for detail see Chap. 5 in Turner et al. 2001).

  12. We calculate the amount of saved or lost habitat at the probabilities of 0.20, 0.25, …, 0.90, resulting in a near-linear relationship between amount of saved or lost habitat and threshold probabilities. So we choose 0.5 (i.e., 50%) as the threshold value: When a cell has 0.5 or higher likelihood to be habitat, it will be counted as a “habitat” cell; otherwise it will be “non-habitat”.

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Acknowledgments

We are indebted to financial support from the National Science Foundation (Dynamics of Coupled Natural and Human Systems, Partnership for International Research and Education), the National Institute of Child Health and Human Development (R01 HD39789), the National Aeronautics and Space Administration (Land Use/Land Cover Change program and Terrestrial Ecology and Biodiversity program), the Guggenheim Foundation, Michigan State University, and San Diego State University. We also thank Dean Daniels, Guangming He, Marc Linderman, Zhiyun Ouyang, Andres Vina, Hemin Zhang, and Shiqiang Zhou for their assistance in data acquisition and processing. We are grateful to Joanna Broderick, Lori Hunter, and anonymous reviewers for their constructive comments on earlier versions of this paper. The data collection and analyses (including computer experiments) conducted in this article comply with the current laws of China.

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  1. Department of Geography, San Diego State University, 5500 Campanile Dr., San Diego, CA, 92182-4493, USA

    Li An

  2. Center for Systems Integration and Sustainability, Michigan State University, 1405 S. Harrison Road, Suite 115 Manly Miles Building, East Lansing, MI, 48823-5243, USA

    Jianguo Liu

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  1. Li An
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Correspondence to Li An.

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An, L., Liu, J. Long-term effects of family planning and other determinants of fertility on population and environment: agent-based modeling evidence from Wolong Nature Reserve, China. Popul Environ 31, 427–459 (2010). https://doi.org/10.1007/s11111-010-0111-3

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