Livelihood Strategies in Shaxi, Southwest China: Conceptualizing Mountain–Valley Interactions as a Human–Environment System
Abstract
:1. Introduction
2. Methods
2.1. Study Area
2.2. Analytical Framework
2.3. Data Collection
2.4. Statistical Tools and Tests
3. Results
3.1. Livelihood Strategies
3.1.1. At the Village Level
Variables | Mountains | Valley | ANOVA/Kruskal–Wallis | ||
---|---|---|---|---|---|
Xishan | Huacongshan | Changle | Silian | ||
Accessibility 1 | very low | low | very high | very high | n/a |
Elevation 2 (m.a.s.l.) | 2987 ± 85 | 2908 ± 82 | 2125 ± 6 | 2124 ± 7 | n/a |
Total No. of households | 33 | 92 | 199 | 311 | n/a |
Average household size (# of people) | 3.9 ± 1.0 a | 3.7 ± 1.1 a | 5.4 ± 1.2 b | 5.5 ± 1.2 b | F = 10.293, p < 0.001 |
Landholding per capita (mu) | 2.21 ± 0.87 a | 10.35 ± 6.67 b | 1.25 ± 0.37 c | 1.32 ± 0.69 c | F = 26.963, p < 0.001 |
Education 3,4 (y) | 2.97 ± 2.98 a | 3.76 ± 3.99 a | 8.77 ± 5.00 b | 8.69 ± 3.50 b | F = 23.863, p < 0.001 |
Education men 3 (y) | 4.50 ± 2.94 a | 5.61 ± 4.34 a | 10.18 ± 3.67 b | 9.24 ± 2.73 b | F = 13.676, p < 0.001 |
Education women 3 (y) | 1.33 ± 2.06 a | 1.69 ± 2.24 a | 7.11 ± 5.86 b | 8.21 ± 4.04 b | F = 14.345, p < 0.001 |
Variables | Mountains | Valley | ANOVA/Kruskal–Wallis | ||
---|---|---|---|---|---|
Xishan | Huacongshan | Changle | Silian | ||
Subsistence income 1 per capita (CNY) | 417 ± 352 a | 1530 ± 2023 b | 805 ± 556 a,b | 854 ± 499 a,b | F = 2.588, p = 0.062 |
Total cash income per capita (CNY) | 2977 ± 1057 a | 4349 ± 2820 a | 4317 ± 3803 a | 3925 ± 1552 a | F = 0.929, p = 0.433 |
% of subsistence income in total income per capita 2 | 12.2 ± 7.6 | 23.3 ± 22.4 | 23.2 ± 21.1 | 20.2 ± 15.9 | χ2 = 1.844, df = 3, p = 0.605 |
Overall agricultural income per capita (CNY) | 1121 ± 681 a | 2332 ± 1296 a | 1462 ± 878 a | 2089 ± 1797 a | F = 2.711, p = 0.054 |
% of total cash income 3 | 38.5 ± 19.5 | 57.2 ± 15.8 | 46.1 ± 23.1 | 55.9 ± 38.0 | χ2 = 4.555, df = 3, p = 0.21 |
—Tobacco income per capita (CNY) | 0 a | 0 a | 157 ± 447 b | 911 ± 1117 c | F = 7.239, p < 0.001 |
% of total cash income | 0 | 0 | 4.7 ± 15.2 | 23.2 ± 27.9 | χ2 = 14.671, df = 3, p = 0.002 |
Overall forest resources income per capita (CNY) | 1549 ± 887 a | 1116 ± 1467 a | 165 ± 232 b | 73 ± 221 b | F = 11.272, p < 0.001 |
% of total cash income | 52.1 ± 25.1 | 23.6 ± 13.9 | 8.3 ± 15.1 | 1.4 ± 3.9 | χ2 = 37.539, df = 3, p < 0.001 |
—NTFP income per capita (CNY) | 734 ± 475 a,b | 1116 ± 1467 a | 165 ± 232 b | 73 ± 221 b | F = 6.349, p = 0.001 |
% of total cash income | 24.0 ± 14.2 | 23.6 ± 13.9 | 8.3 ± 15.1 | 1.4 ± 3.9 | χ2 = 30.971, df = 3, p < 0.001 |
—Logging income per capita (CNY) | 815 ± 500 a | 0 b | 0 b | 0 b | F = 41.120, p < 0.001 |
% of total cash income | 28.1 ± 15.5 | 0 | 0 | 0 | χ2 = 51.514, df = 3, p < 0.001 |
Overall off-farm income per capita (CNY) | 307 ± 676 a | 901 ± 1186 a,b | 2690 ± 3927 b | 1764 ± 1651 a,b | F = 2.843, p = 0.046 |
% of total cash income | 9.4 ± 23.2 | 19.2 ± 20.4 | 45.6 ± 29.8 | 42.6 ± 37.5 | χ2 = 15.061, df = 3, p = 0.002 |
—Local off-farm income per capita | 0 a | 58 ± 208 a | 1123 ± 2675 a | 343 ± 680 a | F = 1.877, p = 0.144 |
% of total cash income | 0 | 1.7 ± 6.2 | 15.1 ± 24.0 | 7.6 ± 16.3 | χ2 = 7.806, df = 3, p = 0.05 |
—Public service income per capita (CNY) | 122 ± 441 a | 282 ± 921 a | 820 ± 1710 a | 555 ± 1508 a | F = 0.830, p = 0.483 |
% of total cash income | 5.4 ± 19.5 | 7.1 ± 20.5 | 12.2 ± 23.0 | 11.1 ± 30.1 | χ2 = 3.100, df = 3, p = 0.376 |
—Migrant working income per capita (CNY) | 185 ± 666 a | 562 ± 982 a | 747 ± 1220 a | 866 ± 1090 a | F = 1.173, p = 0.328 |
% of total cash income | 4.0 ± 14.3 | 10.4 ± 13.5 | 18.3 ± 22.5 | 23.9 ± 30.8 | χ2 = 6.293, df = 3, p = 0.098 |
Gini coefficient | 0.178 | 0.303 | 0.384 | 0.218 | n/a |
Average Herfindahl diversity index | 0.42 | 0.55 | 0.52 | 0.33 | n/a |
3.1.2. At the Household Level
3.1.3. At the Individual Level
Variables | Mountains | Valley | |||||
---|---|---|---|---|---|---|---|
Low-Income Group | Medium-Income Group | High-Income Group | Low-Income Group | Medium-Income Group | High-Income Group | ANOVA/Kruskal–Wallis | |
Average household size (# people) | 3.7 ± 1.0 a | 4.0 ± 0.8 a | 3.7 ± 1.3 a | 5.6 ± 1.6 b | 5.4 ± 0.7 b | 5.0 ± 0.8 a,b | F = 6.457, p < 0.001 |
Landholding per capita (mu) | 2.8 ± 1.7 a | 5.8 ± 4.5 a,b | 10.2 ± 8.3 b | 1.2 ± 0.5 a | 1.2 ± 0.5 a | 1.6 ± 0.5 a | F = 8.869, p < 0.001 |
Average household education (y) | 2.6 ± 1.7 a | 4.6 ± 1.9 a,b | 3.0 ± 1.9 a | 7.6 ± 2.3 b,c | 8.1 ± 3.1 c | 10.1 ± 2.4 c | F = 16.856, p < 0.001 |
Highest education in household (y) | 5.2 ± 3.4 a | 6.7 ± 2.3 a | 5.6 ± 5.1 a | 10.6 ± 4.1 a,b | 10.8 ± 4.3 a,b | 13.1 ± 3.6 b | F = 6.666, p < 0.001 |
Average Herfindahl diversity index | 0.46 ± 0.15 a | 0.51 ± 0.15 a | 0.49 ± 0.21 a | 0.35 ± 0.22 a | 0.43 ± 0.17 a | 0.50 ± 0.17 a | F = 1.112, p = 0.365 |
Variables | Mountains | Valley | |||||
---|---|---|---|---|---|---|---|
Low-Income group | Medium-Income group | High-Income Group | Low-Income Group | Medium-Income Group | High-Income Group | ANOVA/Kruskal–Wallis | |
Subsistence income 1 per capita (CNY) | 331 ± 189 a | 638 ± 654 a,b | 1914 ± 2313 a,b | 972 ± 517 a,b | 796 ± 450 a,b | 719 ± 603 a,b | F = 2.584, p = 0.036 |
Total cash income per capita (CNY) | 2367 ± 633 a | 3041 ± 934 a,b | 5512 ± 2765 b,c | 1904 ± 949 a | 3734 ± 689 a,b,c | 6742 ± 3518 c | F = 9.551, p < 0.001 |
Total income2 per capita (CNY) | 2698 ± 283 a | 3679 ± 499 a | 7427 ± 3723 b | 2876 ± 743 a | 4530 ± 573 a,c | 7461 ± 3203 b,c | F = 10.909, p < 0.001 |
% of subsistence income in total income | 12.7 ± 8.2 | 18.1 ± 18.3 | 22.4 ± 22.9 | 36.0 ± 22.8 | 17.7 ± 10.6 | 11.5 ± 10.4 | χ2 = 10.136, df = 5, p = 0.071 |
Overall agricultural income per capita (CNY) | 1124 ± 441 a | 1332 ± 607 a | 2680 ± 1518 a | 1286 ± 980 a | 1614 ± 1093 a | 2396 ± 1879 a | F = 2.650, p = 0.033 |
% of total cash income | 47.4 ± 15.9 | 46.0 ± 21.6 | 50.0 ± 23.5 | 66.9 ± 29.4 | 44.6 ± 29.6 | 41.0 ± 30.6 | χ2 = 4.940, df = 5, p = 0.423 |
—Tobacco income per capita (CNY) | 0 a | 0 a | 0 a | 307 ± 728 b | 700 ± 993 b | 561 ± 1,029 b | F = 1.995, p = 0.094 |
% of total cash income3 | 0 | 0 | 0 | 10.8 ± 23.9 | 20.6 ± 29.0 | 9.7 ± 17.9 | χ2 = 9.790, df = 5, p = 0.081 |
Overall forest resources income per capita (CNY) | 1001 ± 601 a,b,c | 1263 ± 598 b,c | 1725 ± 1893 c | 101 ± 164 a | 73 ±164 a | 187 ± 323 a,b | F = 7.093, p < 0.001 |
% of total cash income | 41.5 ± 21.1 | 42.8 ± 22.9 | 29.8 ± 29.7 | 9.1 ± 17.9 | 2.6 ± 6.5 | 3.2 ± 5.8 | χ2 = 34.421, df = 5, p < 0.001 |
—NTFP income per capita (CNY) | 465 ± 302 a,b | 938 ± 349 a,b | 1373 ± 1738 b | 101 ± 164 a | 73 ±164 a | 187 ± 323 a | F = 5.119, p = 0.001 |
% of total cash income | 19.3 ± 11.1 | 31.5 ± 11.0 | 21.4 ± 16.7 | 9.1 ± 17.9 | 2.6 ± 6.5 | 3.2 ± 5.8 | χ2 = 31.707, df = 5, p < 0.001 |
—Logging income per capita (CNY) | 536 ± 430 a | 325 ± 440 a | 352 ± 729 a | 0 b | 0 b | 0 b | F = 3.957, p = 0.004 |
% of total cash income | 22.2 ± 18.6 | 11.3 ± 15.8 | 8.4 ± 18.0 | 0 | 0 | 0 | χ2 = 23.875, df = 5, p < 0.001 |
Overall off-farm income per capita (CNY) | 242 ± 522 a | 446 ± 834 a | 1107 ±1394 a | 517 ± 671 a | 2047 ± 1390 a,b | 4159 ± 4442 b | F = 5.053, p = 0.001 |
% of total cash income | 11.2 ± 23.2 | 11.2 ± 18.5 | 20.2 ± 24.7 | 24.0 ± 28.9 | 52.8 ± 32.0 | 55.8 ± 31.7 | χ2 = 18.828, df = 5, p = 0.002 |
— Local off-farm income per capita | 0 a | 0 a | 83 ± 250 a | 0 a | 538 ± 839 a | 1695 ± 3207 a | F = 2.305, p = 0.057 |
% of total cash income | 0 | 0 | 2.5 ± 7.4 | 0 | 13.8 ± 21.2 | 20.6 ± 25.9 | χ2 = 18.117, df = 5, p = 0.003 |
—Public service income per capita (CNY) | 214 ± 528 a | 0 a | 370 ± 1,111 a | 172 ± 513 a | 445 ± 1,445 a | 1457 ± 2189 a | F = 1.796, p = 0.130 |
% of total cash income | 10.0 ± 23.5 | 0 | 8.1 ± 24.2 | 7.0 ± 20.9 | 9.0 ± 28.9 | 19.1 ± 29.2 | χ2 = 4.376, df = 5, p = 0.497 |
—Migrant working income per capita (CNY) | 28 ± 83 a | 446 ± 834 a | 654 ± 1,167 a | 344 ± 548 a | 1063 ± 1084 a | 1006 ± 1533 a | F = 1.572, p = 0.184 |
% of total cash income | 1.1 ± 3.3 | 11.2 ± 18.5 | 9.6 ± 15.5 | 17.0 ± 24.8 | 30.0 ± 31.1 | 16.1 ± 23.4 | χ2 = 7.799, df = 5, p = 0.168 |
Income Source | Explanatory Variable | B (T) | Summary of Model |
---|---|---|---|
Total income 1 per capita (CNY) | Intercept | (2.392) * | R = 0.515; Adjusted R2 = 0.238 |
Total agricultural land/capita | 0.490 (3.962) *** | ||
Household mean education level | 0.388 (3.136) ** | ||
Total cash income per capita (CNY) | Intercept | (3.742) *** | R = 0.288; Adjusted R2 = 0.066 |
Household mean education level | 0.288 (2.233) * | ||
Subsistence income 2 per capita (CNY) | Intercept | (4.184) *** | R = 0.685; Adjusted R2 = 0.450 |
Total agricultural land/capita | 0.790 (6.876) *** | ||
Mountain (dummy) | −0.332 (−2.891) ** | ||
% of subsistence income in total income | No statistically significant explanatory variable | n/a | |
Overall agricultural income per capita (CNY) | Intercept | (4.996) *** | R = 0.394; Adjusted R2 = 0.126 |
Total agricultural land/capita | 0.377 (2.969) ** | ||
Silian (dummy) | 0.263 (2.071) * | ||
% of total cash income | Intercept | (9.308) *** | R = 0.430; Adjusted R2 = 0.156 |
Household maximum education level | −0.419 (−3.172) ** | ||
Xishan (dummy) | −0.380 (−2.875) ** | ||
—Tobacco income per capita (CNY) | Intercept | (0.686) | R = 0.488; Adjusted R2 = 0.224 |
Silian (dummy) | 0.488 (4.145) *** | ||
% of total cash income3 | Intercept | (0.784) | R = 0.465; Adjusted R2 = 0.202 |
Silian (dummy) | 0.465 (3.900) *** | ||
Overall forest resources income per capita (CNY) | Intercept | (2.893) ** | R = 0.660; Adjusted R2 = 0.415 |
Mountains (dummy) | 0.391 (3.085) ** | ||
Household size | −0.349 (−2.756) ** | ||
% of total cash income | Intercept | (5.116) *** | R = 0.800; Adjusted R2 = 0.620 |
Xishan (dummy) | 0.524 (5.499) *** | ||
Household size | −0.238 (−2.566) * | ||
Household mean education level | −0.237 (−2.363) * | ||
—NTFP income per capita (CNY) | Intercept | (3.967) *** | R = 0.552; Adjusted R2 = 0.279 |
Household size | −0.409 (−3.331) ** | ||
Huacongshan (dummy) | 0.247 (2.014) * | ||
% of total cash income | Intercept | (6.729) *** | R = 0.636; Adjusted R2 = 0.382 |
Household mean education level | −0.486 (−4.141) *** | ||
Household size | −0.248 (−2.111) * | ||
—Logging income per capita (CNY) | Intercept | (0.000) | R = 0.830; Adjusted R2 = 0.684 |
Xishan (dummy) | 0.830 (11.051) *** | ||
% of total cash income | Intercept | (0.000) | R = 0.856; Adjusted R2 = 0.728 |
Xishan (dummy) | 0.856 (12.282) *** | ||
Overall off-farm income per capita (CNY) | Intercept | (−1.457) | R = 0.609; Adjusted R2 = 0.348 |
Household mean education level | 0.426 (3.585) *** | ||
Old persons in household | 0.292 (2.459) * | ||
% of total cash income | Intercept | (−0.857) | R = 0.669; Adjusted R2 = 0.427 |
Household maximum education level | 0.534 (4.934) *** | ||
Old persons in household | 0.254 (2.349) * | ||
—Local off-farm income per capita | Intercept | (−1.733) | R = 0.493; Adjusted R2 = 0.215 |
Old persons in household | 0.295 (2.266) * | ||
Household mean education level | 0.290 (2.222) * | ||
% of total cash income | Intercept | (−1.307) | R = 0.423; Adjusted R2 = 0.164 |
Household mean education level | 0.423 (3.465) *** | ||
—Public service income per capita (CNY) | Intercept | (−3.791) *** | R = 0.684; Adjusted R2 = 0.438 |
Household maximum education level | 0.567 (4.486) *** | ||
Old persons in households | 0.445 (4.015) *** | ||
Dummy mountains | 0.326 (2.530) * | ||
% of total cash income | Intercept | (−3.163) ** | R = 0.613; Adjusted R2 = 0.341 |
Old persons in household | 0.412 (3.437) *** | ||
Household maximum education level | 0.515 (3.756) *** | ||
Dummy mountain | 0.357 (2.556) * | ||
—Migrant working income per capita (CNY) | No statistically significant explanatory variable | n/a | |
% of total cash income | Intercept | (−5.672) *** | R = 0.408; Adjusted R2 = 0.136 |
Dummy mountain | −0.432 (−3.187) ** | ||
Old persons in household | −0.274 (−2.022) * |
Location | Sex of Collectors | Mushrooms | Medicinal Plants | Off-Farm |
---|---|---|---|---|
Valley | Male | 45% | 50% | 89% |
Female | 55% | 50% | 11% | |
Mountains | Male | 44% | 44% | 100% |
Female | 56% | 56% | 0% |
3.2. Education
3.3. Depiction of the Main Mountain–Valley Interactions in a Simplified Model
4. Discussion
4.1. Structuring the Data with the HES Framework
4.2. Socioeconomic and Political Status of Mountain and Valley Communities
4.3. Education and Livelihood Strategies
4.4. Diversity of Livelihood Strategies in Mountain and Valley Communities
4.5. The Role of NTFP Collection in Mountain and Valley Communities
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Share and Cite
Huber, F.K.; Morlok, M.; Weckerle, C.S.; Seeland, K. Livelihood Strategies in Shaxi, Southwest China: Conceptualizing Mountain–Valley Interactions as a Human–Environment System. Sustainability 2015, 7, 3204-3229. https://doi.org/10.3390/su7033204
Huber FK, Morlok M, Weckerle CS, Seeland K. Livelihood Strategies in Shaxi, Southwest China: Conceptualizing Mountain–Valley Interactions as a Human–Environment System. Sustainability. 2015; 7(3):3204-3229. https://doi.org/10.3390/su7033204
Chicago/Turabian StyleHuber, Franz K., Michael Morlok, Caroline S. Weckerle, and Klaus Seeland. 2015. "Livelihood Strategies in Shaxi, Southwest China: Conceptualizing Mountain–Valley Interactions as a Human–Environment System" Sustainability 7, no. 3: 3204-3229. https://doi.org/10.3390/su7033204
APA StyleHuber, F. K., Morlok, M., Weckerle, C. S., & Seeland, K. (2015). Livelihood Strategies in Shaxi, Southwest China: Conceptualizing Mountain–Valley Interactions as a Human–Environment System. Sustainability, 7(3), 3204-3229. https://doi.org/10.3390/su7033204