Final Report - Asian Development Bank

48
TA 4721-PRC: Preparing the Shaanxi-Qinling Mountains Integrated Ecosystem Management Project
Final Report Appendix 5
outcome of NFPP of SLCP in the Qinling. Use of remote sensing in combination with ground-truthing
and sampling of revegetated plots would enable assessment of the effectiveness of these two
projects, and could lead to modifications that would be beneficial for conservation and for the
participating farmers.
c. Humans and the Protected Area System
190. Research on human interactions with panda habitats has been carried out since 2000 with
leadership by Michigan State University in USA. Research focused on demography and socioeconomics
of villages (4,320 people in 942 households in 1998) in and near Wolong National Nature
Reserve, the largest panda reserve in China (2,000 km 2 ). A model for simulating impacts of
demographic and socio-economic parameters on panda habitats was tested in 2000 59 . Use of the
model in the field could help reserve managers to “understand the relationships among local economy,
local cultural traditions, and habitat degradation”. This knowledge should lead to more scientific and
efficient management of people in and near reserves.
191. The above work was extended in 2003 to “detect…patterns of change in land cover and
panda habitat, to understand the mechanisms behind these patterns, and to develop new policy
scenarios and evaluate short- and long-term consequences of different scenarios” 60 . Several
important conclusions were drawn from the combination of field interviews, remote sensing, and
computer modeling. Field work showed that 22 new households were added to the reserve annually
from 1975-98.
192. Modeling predicted that if 22% of 17-25 year old villagers relocated outside the reserve (e.g.
for study, work, marriage), the human population of the reserve would fall from 4,300 in 1997 to 700 in
2047, and panda habitats would then increase by 7%. In contrast, if nothing changes, the human
population would increase to 6,000 (40%) and about 40% of panda habitats would be reduced by
2047. Most importantly, relocation of young people was found to be “socially acceptable,
economically efficient, and ecologically sound”: By providing access to opportunities outside the
nature reserve this type of voluntary relocation rapidly reduces the adult child-bearing population of
the future. It is this segment of the population that has the most severe adverse impact on panda
habitat.
193. A final and surprising conclusion was a reiteration of a finding from the 2001 report
discussed above: “high-quality panda habitat in the reserve had been lost and had become
fragmented more rapidly after the reserve was established”.
194. Under leadership of the same researchers as above, multi-disciplinary research continued at
Wolong in 2002-3 61 . Human impacts were predicted to result in loss of up to 16% of remaining panda
habitat in Wolong Nature Reserve by 2034. Not surprisingly, in the rugged terrain of Wolong,
accessibility largely controlled the spatial distribution of village houses. This supports the contention
that roads accelerate and intensify human impacts on landscapes. Firewood collection was the
primary agent of forest degradation: the average household used 15 m 3 of firewood per year.
Firewood collection was predicted to further reduce forest cover unless efforts are made to reduce
firewood collection, provide alternative energy sources for existing households, and provide “viable
means and incentives to encourage emigration” as reported in 1999 62 .
59 An L., Liu J., Z. Ouyang, M. Linderman, S. Zhou and H. Zhang. 2001. Simulating demographic and socioeconomic
processes on household level and implications for giant panda. Ecologcial Modeling 140:31-49.
60 Liu J., L. An, S. S. Batie, R. E. Groop, Z. Liang, M. A. Linderman, A. G. Mertig, Z. Ouyang and J. Qi. 2003.
Human impats on land cover and panda habitat in Wolong Nature Reserve: Liinking ecological,
socioeconomic, demographic and behavioral data. Chapter 9 in People and the Enviornment: Approaches for
linking household & community surveys to remote sensing & GIS (J. Fox, V. Mishra, R. Rindfoss and S.
Walsh, eds.) Kluwer Acad. Pub. Boston, p 241-263.
61 Linderman, M. A., A. Li, S. Bearer, G. He, Z. Ouyang and J. Liu. 2004. Modeling the spatio-temporal dynamics
and interactions of households, landscapes and giant panda habitat. Ecologial Modelling (detail not available).
62 Liu, J., Z. Ouyang, Z. Yang, W. Taylor, R. Groop, Y. Tan and H. Zhang. 1999. A framework for evaluating the
effects of human factors on wildlife habitat: The case of giant pandas. Conservation Biol. 13(6):1360-1370.