Factors Contributing to Efficient Forest Production in the Region of the Three-North Shelter Forest Program, China

Abstract

Forests are the most important renewable resources and provide critical ecosystem services worldwide, especially the provisioning service, making a great contribution to human well-being. The Three-North Shelter Forest Program (TNSFP) is a large-scale ecological project aimed at improving ecological environments and consolidating economic construction in China through the development of artificial forests. In our study, stochastic frontier analysis was adopted to estimate forest production efficiency (FPE) by using dynamic panel data. Based on the FPE of 13 provinces located within the TNSFP region during the period 2000–2016, the effects of the natural and socioeconomic influencing factors on FPE were further explored by using the Tobit regression model. The estimated results confirmed the validity of the constructed model and revealed an increasing trend of the mean annual FPE value, which ranged from 0.3147 in 2000 to 0.5681 in 2016. The FPE was declining from the eastern region to the western region in 2000. However, this spatial distribution characteristic changed enormously in 2016; regions with low FPE were in the center of the TNSFP region, surrounded by the regions with high FPE. Moreover, the following factors positively influenced FPE: average temperature (1.4476), total annual rainfall (0.0800), per capita GDP (0.0882), the education levels of forestry employees (0.2120), the number of forest technology stations in townships (0.0149), and disease and pest control areas (0.0190). However, the impacts of the policy relating to the Natural Forest Protection Program on FPE were insignificant. These influencing factors had differential effects on FPE within the TNSFP’s three sub-regions during the period 2000–2016. These findings can contribute to more efficient forest management and strengthen resource and environment management.

Applications of DEA and SFA in benchmarking studies in forestry: state-of-the-art and future directions

“…We found it is rather common to apply panel data to study productivity change over time. More than 16 studies estimate and compare the efficiency scores of several years or periods (Nyrud and Bergseng 2002;Bogetoft et al 2003;Nyrud and Baardsen 2003;Vahid and Sowlati 2007;Adams 2008, 2009;Kao 2013;Zadmirzaei et al 2015;Obi and Visser 2017a;Xiong et al 2018;Zhang et al 2018;Shahi and Dia 2019;Wang et al 2019;Chen et al 2020;Toma et al 2020). Six studies applied Malmquist indices to evaluate the changes in productivity over time (Kao 2000;Sowlati and Vahid 2006;Salehirad and Sowlati 2007;Lin and Ge 2019;Obi and Visser 2020).…”

“…SFA usually requires a parametric functional form specification and distributional assumptions on the noise and inefficiency term, but has the advantage that it naturally handles noise in the data (Kumbhakar and Lovell 2003;Bogetoft and Otto 2011). The potential of such applications of benchmarking has so far merely been discussed in the research community (Aalmo and Baardsen 2015;Wang et al 2019;Obi and Visser 2020;Aalmo et al 2020).…”

A Degeneration Gradient of Poplar Trees Contributes to the Taxonomic, Functional, and Resistome Diversity of Bacterial Communities in Rhizosphere Soils

“…Many countries and regions have carried out natural forest protection and artificial forest cultivation programs [ 19 ], among which the Three North Shelterbelt known as “Green Wall of China” as one of the typical examples. During the decades of the construction of the Three-North Shelterbelt, many studies have made evaluations based on its achievements, and the extensive ecological benefits obtained are beyond doubt [ 20 , 21 , 22 ]. However, in recent years, with the impact of climate change and human activities, large scale Populus trees degeneration with dieback symptom and partial aggravating trend have been observed in some areas of the artificial forest [ 23 ].…”