南京林业大学学报(自然科学版) ›› 2024, Vol. 48 ›› Issue (1): 227-236.doi: 10.12302/j.issn.1000-2006.202204051
收稿日期:
2022-04-21
修回日期:
2022-06-28
出版日期:
2024-01-30
发布日期:
2024-01-24
通讯作者:
程宝栋
基金资助:
LUO Yiyi(), LI Lingchao, CHENG Baodong()
Received:
2022-04-21
Revised:
2022-06-28
Online:
2024-01-30
Published:
2024-01-24
Contact:
CHENG Baodong
摘要:
【目的】研究京津冀地区经济增长对森林资源造成的影响及其内在影响机制,为该地区进一步实现经济与生态的协调可持续发展提供参考。【方法】以京津冀地区为例,通过2000—2018年卫星遥感影像数据测度京津冀地区38个样本县的森林破碎化程度,采用森林转型理论、土地利用变化理论以及生长轴理论等构建经济增长、交通基础设施建设以及森林破碎化三者间的中介效应模型,并进行实证检验。【结果】经济增长水平与京津冀地区森林破碎化程度关系,同一时期内,经济增长水平每提高1%,森林破碎化程度的加深超过3%;经济增长水平与京津冀地区的交通基础设施建设关系表明,经济增长水平每提高1%,京津冀地区的公路密度的增长量超过0.1%;交通基础设施建设与京津冀地区的森林破碎化关系表明,每提高1个单位的公路密度将使得该地区增加超过4个森林斑块。作用机制检验表明,在经济增长对森林破碎化产生影响的路径中,交通基础设施建设存在显著的中介作用,其中介程度为23.255%。【结论】经济增长水平的提高对京津冀地区森林破碎化程度的提高具有显著的正向影响。经济增长水平的提高能够有效地促进交通基础设施建设,提高道路的分布密度。交通基础设施的建设对地区森林破碎化程度的加深具有显著的正向影响。在经济增长的过程中将通过交通基础设施建设这一中介要素对森林破碎化产生影响。
中图分类号:
罗奕奕,李凌超,程宝栋. 经济增长对森林破碎化的影响——以中国京津冀地区为例[J]. 南京林业大学学报(自然科学版), 2024, 48(1): 227-236.
LUO Yiyi, LI Lingchao, CHENG Baodong. The impact of economic growth on forest fragmentation: a case study of Beijing-Tianjin-Hebei Region in China[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(1): 227-236.DOI: 10.12302/j.issn.1000-2006.202204051.
表1
主要变量的描述性统计"
年份 year | PAM | G | W/ (km·km-2) | S/% | D | K | O/ (万人·km-2) | N/ (kW·人-1) |
---|---|---|---|---|---|---|---|---|
总体total | 5.604±5.376 | 9.573±0.888 | 0.666±0.381 | 80.0±40.1 | 5.624±0.970 | 9.259±1.112 | 0.197±0.014 | 2.922±3.991 |
2000 | 3.434±2.559 | 8.386±0.364 | 0.329±0.190 | 0 | 4.782±0.687 | 8.098±0.371 | 0.019±0.013 | 3.656±6.445 |
2005 | 3.186±2.369 | 9.073±0.563 | 0.620±0.339 | 100 | 5.374±0.910 | 8.690±0.426 | 0.019±0.014 | 2.879±3.467 |
2010 | 3.450±2.613 | 9.875±0.553 | 0.709±0.343 | 100 | 5.838±0.945 | 9.477±0.412 | 0.020±0.014 | 2.782±3.301 |
2015 | 7.708±6.291 | 10.236±0.491 | 0.834±0.392 | 100 | 6.049±0.907 | 9.572±1.505 | 0.021±0.015 | 2.593±2.890 |
2018 | 10.240±6.843 | 10.334±0.432 | 0.847±0.372 | 100 | 6.101±0.724 | 10.525±0.276 | 0.020±0.014 | 2.703±2.809 |
表2
中介效应实证结果"
验证方法 verification method | W | G | S | D | O | N | 系数 coefficient | 观测值 observations | R2 | |
---|---|---|---|---|---|---|---|---|---|---|
基准回归 benchmark regression | PAM(1) | — | 3.496*** | -2.828*** | 0.341 | -100.862*** | -0.059 | -25.373*** | 186 | 0.267 |
(0.621) | (0.688) | (0.385) | (20.577) | (0.093) | (4.365) | |||||
W(2) | — | 0.179*** | 0.172*** | -0.013 | 15.472*** | 0.009 | -1.444*** | 186 | 0.668 | |
(0.033) | (0.055) | (0.025) | (1.717) | (0.006) | (0.236) | |||||
PAM(3) | 4.536** | 2.683*** | -3.608*** | 0.402 | -171.043*** | -0.097 | -18.825*** | 186 | 0.301 | |
(1.813) | (0.611) | (0.795) | (0.393) | (36.921) | (0.078) | (4.15) | ||||
双向固定效应 fixed-effect regression | PAM(1) | — | 4.024*** | -3.687*** | -0.048 | 221.283 | 0.072 | -34.316*** | 186 | 0.356 |
(0.663) | (0.62) | (-0.443) | (232.204) | (0.09) | (5.858) | |||||
W(2) | — | 0.125*** | 0.176*** | 0.013 | 45.832*** | 0.013 | -1.698*** | 186 | 0.623 | |
(0.034) | (0.056) | (0.035) | (14.893) | (0.009) | (0.333) | |||||
PAM(3) | 4.120** | 3.507*** | -4.412*** | -0.104 | 32.451 | 0.017 | -27.319*** | 186 | 0.385 | |
(1.593) | (0.722) | (1.05) | (0.708) | (228.758) | (0.085) | (5.745) |
表3
Sobel检验和Bootstrap检验结果"
统计量 statistic | Sobel检验Sobel test | Bootstrap检验Bootstrap test | |||||
---|---|---|---|---|---|---|---|
系数a coef a | 系数b coef b | 中介效应 mediation effect | 直接效应 direct effect | 总效应 total effect | 间接效应 indirect effect | 直接效应 direct effect | |
统计值statistic value | 0.179 | 4.536 | 0.813 | 2.683 | 3.496 | 0.813 | 2.683 |
标准差SD | 0.032 | 1.525 | 0.310 | 0.710 | 0.669 | 0.393 | 0.633 |
Z统计量Z statistic | 4.268 | 2.813 | 2.627 | 2.430 | 3.384 | 2.070 | 4.240 |
P | <0.001 | 0.003 | 0.009 | <0.001 | <0.001 | 0.039 | <0.001 |
表4
替换关键变量逐步回归检验结果"
变量 variable | W | K | 控制变量 control variable | 时间效应 time effect | 个体效应 individual effect | 系数 coefficient | 观测值 observations | R2 | 样本量 sample |
---|---|---|---|---|---|---|---|---|---|
PAM(1) | — | 1.534 8±0.254 3*** | 控制 | 固定 | 固定 | -22.966 0±4.650 8*** | 186 | 0.302 0 | 38 |
W(2) | — | 0.039 2±0.017 9** | 控制 | 固定 | 固定 | -1.319 1±0.235 5*** | 186 | 0.604 8 | 38 |
PAM(3) | 5.162 5±1.600 0*** | 1.332 4±0.348 8*** | 控制 | 固定 | 固定 | -16.156 0±4.974 8*** | 186 | 0.349 7 | 38 |
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