资源科学 ›› 2022, Vol. 44 ›› Issue (3): 494-507.doi: 10.18402/resci.2022.03.06

• 土地资源 • 上一篇    下一篇

1990年以来卢旺达森林转型路径及趋势模拟

李天润(), 陈爽()   

  1. 南京信息工程大学地理科学学院/“一带一路”城市可持续发展研究院,南京 210044
  • 收稿日期:2021-07-06 修回日期:2021-10-24 出版日期:2022-03-25 发布日期:2022-05-25
  • 通讯作者: 陈爽,女,湖南湘潭人,教授,主要研究方向为城市生态及人居环境,城市与区域可持续发展。E-mail: schens@nuist.ac.cn
    陈爽,女,湖南湘潭人,教授,主要研究方向为城市生态及人居环境,城市与区域可持续发展。E-mail: schens@nuist.ac.cn
  • 作者简介:李天润,男,河北沧州人,硕士生,研究方向为土地利用变化与资源可持续利用。E-mail: 20201210011@nuist.edu.cn
  • 基金资助:
    国家重点研发计划项目(2018YFE0105900);国家自然科学基金项目(41771140)

Forest transition paths in Rwanda since 1990 and trend prediction

LI Tianrun(), CHEN Shuang()   

  1. School of Geographical Sciences / Research Centre of Urban Sustainable Development, Nanjing University of information Science & Technology, Nanjing 210044, China
  • Received:2021-07-06 Revised:2021-10-24 Online:2022-03-25 Published:2022-05-25

摘要:

社会经济发展过程中一个国家(地区)森林面积由减少转为增加的“森林转型“内在驱动机制,是资源环境研究关注的热点。以4期卢旺达土地覆盖数据为主要信息源,分析1990—2015年该地区森林变化的趋势和时空特征。结合社会经济数据,借助森林转型的路径分析法,探究卢旺达森林面积变化的影响因素及其所遵循的转型路径。在此基础上,利用PLUS模型对卢旺达2030年的森林空间动态分布进行模拟预测,对如何继续保持良好转型态势提出相关建议。结果表明:①卢旺达森林面积在2010年开始出现净增长,由2010年的197383.2 hm2增加到2015年的213087.8 hm2,年增加率0.8%;②国家公园和保护区是森林增长主要地区,且主要来源于稀树草原和耕地,分别占森林净增加总面积的87.8%和8.8%;③转型的内在驱动机制主要是国家政策引导下发生的“国家森林政策路径”和“森林稀缺路径”,全球化路径体现在植树技术与资金支持;④对卢旺达2030年森林模拟预测显示,森林转型仍将继续,预计到2030年森林面积将净增加34065.2 hm2。为进一步提高研究区森林覆盖率,卢旺达政府部门应改善森林恢复的薄弱环节,加快农业集约化推广;通过为农村社区创造场外就业机会,引导经济和就业发生转型,从而推动基于“经济发展路径”与“农村集约化路径”的森林增加。

关键词: 森林转型, 国家政策路径, 驱动机制, PLUS模型, 卢旺达

Abstract:

In the process of socioeconomic development, the internal driving mechanism of the “forest transition” in which the forest area of a country (region) changes from decreasing to increasing is a hotspot in resources and environment research. This study used Rwanda's land cover data as the main source of information to analyze the trends and temporal and spatial characteristics of forest changes in the country from 1990 to 2015. Using socioeconomic data and the path analysis method of forest transition, this study explored the influencing factors of the change in forest area in Rwanda and the transition paths that it followed. On this basis, the patch-generating land use simulation (PLUS) model was used to simulate and predict the spatial dynamics of Rwanda's forest distribution in 2030, and relevant policy recommendations on healthy forest transition was made. The results indicate that: (1) The forest area of Rwanda began to show a net increase in 2010, from 197383.2 hm2 to 213087.8 hm2, with an annual change rate of 0.8%. (2) The National parks and protected areas were the main areas of forest growth, and the growth were mainly from savanna and cropland, accounting for 87.8% and 8.8% of the total forest net increase respectively. (3) The internal driving mechanism was mainly the “national forest policy path” and the “forest scarcity path” under the guidance of national policies. The path of globalization was reflected in tree planting technology and financial assistance. (4) The simulation result shows that forest transition will continue in Rwanda by 2030. The forest area is expected to increase by 34065.2 hm2. To increase the forest coverage rate, the state should improve the weak links of forest restoration and accelerate the promotion of agricultural intensification. By creating employment opportunities for rural communities, the government can guide the transformation of the economy and employment. The state can promote the “economic development path” and “agricultural intensification path” through the above measures.

Key words: forest transition, national policy path, driving mechanism, PLUS model, Rwanda