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Article

Effects of Payments for Ecosystem Services and Livelihoods on Non-Grain Agricultural Land Use

1
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Bei**g 100085, China
2
University of Chinese Academy of Sciences, Bei**g 100049, China
*
Authors to whom correspondence should be addressed.
Forests 2024, 15(3), 521; https://doi.org/10.3390/f15030521
Submission received: 23 January 2024 / Revised: 9 March 2024 / Accepted: 10 March 2024 / Published: 12 March 2024
(This article belongs to the Section Forest Economics, Policy, and Social Science)

Abstract

:
Non-grain agricultural land use (NGALU) could be an alternative to payments for ecosystem services (PES) to achieve ecosystem benefits, given their joint contribution to forest transition. Unraveling the correlation between PES and NGALU can enhance cost-effective decisions. While farmland abandonment and non-grain cash crops (NGCCs) plantation are two main manifestations of NGALU, previous studies have primarily assessed the effects of PES on farmland abandonment. Little is known about the effects of PES on NGCC planting. This study evaluated the effects of China’s two nationwide PES programs (i.e., the Grain to Green Program, GTGP, and the Ecological Welfare Forest Program, EWFP) on NGALU in the Black River Basin of Shaanxi province. The study found a wide adoption of NGALU, with 52% of households adopting NGALU. The total area of NGALU is more than half of the afforested area through the GTGP. A quarter of the NGALU area is abandoned farmland, while the remaining NGALU area is planted with NGCCs. The two PES programs did not have effects on NGCC planting, but reduced farmland abandonment. Engagement in labor migration and local non-farm employment increased NGALU, while livestock breeding and farmland area reduced NGALU. Furthermore, the large area and unfavorable geographical conditions of farmland parcels promoted NGALU. These results highlight the important implications of leveraging NGALU to boost ecological gains from conservation investments.

1. Introduction

The urgent needs to reverse land degradation and promote ecosystem restoration have increasingly received international attention, such as in the United Nations Sustainable Development Goal 15 (“Life on Land”) and the Post-2020 Global Biodiversity Conservation Framework [1,2], which emphasize the diverse roles of forested landscapes with multiple ecosystem services (ES) and the benefits that ecosystems provide for human society [3]. However, how to reconcile the protection and restoration of natural landscapes with the maintenance of food security remains one of the greatest challenges that both decisionmakers and academic communities encounter in the 21st century [4]. Rapid urbanization with the increasing imbalance in economic development between urban and rural areas has raised global concerns about non-grain agricultural land use (NGALU), a phenomenon where farmland used for grain production is converted into land uses with non-grain agricultural activities (e.g., cash crops and nursery plantation, farmland abandonment) [5,6], which has been addressed in China’s public policy [7]. Under the context of agricultural restructuring, NAGLU could affect food production by altering the quality of soil conditions [8] and could contribute to forest transition, which characterizes the shift of forest cover from shrinkage to expansion over time [9,10] and triggers variations in forest ES, such as freshwater provision, flood mitigation, and soil retention, which are strongly associated with ecological security and human wellbeing at the local and regional levels.
As a global phenomenon, NGALU facilitates forest transition primarily through farmland abandonment caused by labor migration from rural areas to urban areas and by extensive plantation of non-grain cash crops (NGCCs) with the increasing pursuit of economic diversification [11,12]. As the two main manifestations of NGALU, farmland abandonment followed by secondary forest succession reflects a decline in traditional agricultural management and interlinks with ecological and socioeconomic aspects of agricultural practices [8], whereas diverse plantation of NGCCs could enhance the resilience of smallholders in the face of external shocks from uncertainties caused by market price and disease infection [5]. Here, this study integrated farmland abandonment and NGCC planting into the concept of NGALU for two reasons. Firstly, both of these land use conversions represent the transition of agricultural land use from traditional grain production to non-grain production under the backdrop of socioeconomic development. Secondly, both of these land use conversions contribute to the increase in tree cover, thereby holding potential for promoting forest transition.
While the contribution of NGALU to forest transition was determined by the combination of household consumption structure and market demand, governmental financial investments in forest improvement made in response to ecological security concerns have proliferated worldwide over the past decades [13,14]. One of the most important policy responses to biodiversity loss and ecosystem degradation that has negative impacts on people is payment for ecosystem services (PES), which has been implemented with variable manifestations in many countries [13,15,16]. The implementation of these PES programs offers valuable opportunities for ecosystem structure and composition to stabilize with increasing service provision over a time horizon along which landowners could make alternative reformulations of land use plans [17]. The occurrence of NGALU with the altering agricultural structure and livelihood strategy after the initialization of PES programs reveals a time-lag effect of forest restoration and rehabilitation policies [18] which is crucial for policy evaluation and management plans designation aiming to ensure rapid and fitting ecosystem responses, especially in the face of the increasing pace of global change.
The occurrence and evolution of NGALU areas were associated with environmental factors ranging from geographical conditions [19,20] and households’ individual and family characteristics [5,21] to ecological conservation policies [22]. For example, the adoption of cash crop plantation was affected by the demographic and economic characteristics of households [5,23], while poor geographical conditions (e.g., rough topography, high elevation) that are unfavorable for plant growth and human accessibility [19,24] are conducive to low grain production or farmland abandonment. Assessments of farmland abandonment under different policy and economic environments have revealed the effects of PES on land decisions by redistributing rural economic opportunities and altering the livelihood strategy of rural households, like labor allocation and non-farm employment [22,25]. Additionally, studies evaluating rural land decisions highlighted the important role played by household capital assets (e.g., farmland area, breeding stock) in the diversification of livelihood strategies [25,26] and emphasized the effectiveness of PES programs in sha** multiple livelihood strategies from an integrated perspective [22,27]. Previous studies relating to policy evaluation mainly focused on the effects of PES on farmland abandonment. However, little is known about how PES affects NGCC planting.
To bridge this knowledge gap, we took China’s two PES programs (i.e., the Grain to Green Program, GTGP, and the Ecological Welfare Forest Program, EWFP) to illustrate how these two programs affected NGALU by taking the Black River Basin within the Shaanxi province as a case study. Since the occurrence of severe droughts and massive floods in 1998, the detrimental impacts of ecosystem degradation and accelerated ES losses have promoted the Chinese government to implement a series of PES programs for protecting forests, including GTGP and EWFP. The GTGP aims to convert farmlands on steep slopes area into forest or grassland to protect soil and water [28].The GTGP was piloted in the Sichuan, Shaanxi, and Gansu provinces in 1999 and then implemented nationwide in 2002, covering 2435 counties in 25 provinces [29]. By 2019, China had completed afforestation of 34.33 million hectares through the GTGP, with an investment of 517.4 billion RMB, benefiting an estimated 41 million households and 158 million farmers directly [29]. The EWFP, on the other hand, was initiated in 2001, and aimed to protect ecologically important or vulnerable forests by providing subsidies to households living within and around forests to enforce logging bans [30]. The successful implementation of these programs has significantly increased forest cover and brought a wide range of ecological and socioeconomic benefits to human society [13]. Understanding the correlations of PES with the process of NGALU is critical for systematically elucidating how PES contributes to sustainable development by promoting forest transition while enhancing poverty alleviation in rural areas [11]. This study hypothesizes that changes in household assets resulting from PES, such as decreases in farmland area, will increase households’ investments in remaining farmland and reduce the adoption of NGALU. Drawing on in-depth household survey data, this study aimed to gain a complicated understanding of NGALU and its driving mechanism. Specific tasks of this study included: (1) investigating the characteristics of NGALU by analyzing the heterogeneity of farmland abandonment and NGCC planting across households; (2) exploring the effects of PES programs (i.e., GTGP, EWFP) and livelihood strategies on NGALU. Given the great challenges in achieving sustainability of the ES provision both in China and worldwide, our study provided critical implications for improving PES and leveraging NGALU to boost ecological gains from conservation investments. The framework and analytical approaches can be applied to evaluate conservation investments and land use strategies in other countries around the world.

2. Methods

2.1. Study Area

The study area covering 159,900 ha includes four towns located in the southern mountainous area of ** them to better adapt to the shocks from economic fluctuations by comprehensively considering the evolution of NGALU and its response to environmental factors.
Quantitative analyses on the relationships between NAGLU and different environmental factors ranging from the biophysical attributes of land parcels to household livelihood strategies revealed varying types and strengths for the driving forces of different manifestations. Across the landscapes, NGALU occurred with different manifestations, depending on the locations and the primary factors that affect the land transfer processes at both household and parcel levels. The identification and comprehensive analyses of the NGALU manifestation and its varying responses to different environmental factors are a prerequisite for understanding and managing the occurrence and evolution of NGALU at different locations. Additionally, linking PES programs with the occurrence of NGALU as illustrated in our study could inform coordinated management plans by incorporating local-scale targets, like high-efficient returns from economic diversification, into national-scale targets which focus on ensuring the security of ecosystem and food supply [42], thus supporting the idea that rural revitalization with sustainable economic development requires a basis of ecological conservation and environmental improvement [27].
While this study provided an in-depth understanding of NGALU and its driving forces, there were several limitations. Suggestions were proposed for future studies. Firstly, we investigated the characteristics of NGALU with a combination of descriptive and quantitative analyses and focused on a single-time statistical feature based on field survey data. Spatially explicit information on the heterogeneity of NGALU and its dynamic changes over time could facilitate the improvement of management plans in terms of their accuracy and efficiency. Secondly, this study assessed the effects of PES and livelihoods on NGALU, without considering the ecological benefits of NGALU, such as changes in forest cover and forest ecosystem services. Thirdly, policy outcomes involve complex linkages and feedback among individual and household decisions and land use conversion, with potential time-lags and heterogeneity [43]. The development of comprehensive models considering these reciprocal feedback effects in the coupled human-natural systems is underway in our follow-up works. Furthermore, while the current study delineated simple linear relationships of NGALU with different driving forces, incorporating non-linear and interactive effects of different environmental factors into future models could help decisionmakers unravel the complex driving mechanism of NGALU.

5. Conclusions

This study evaluated the effects of PES (i.e., GTGP, EWFP) and livelihoods on NGALU and explored the driving forces of two NGALU manifestations by focusing on the heterogeneity of households and land parcels. Over half of the surveyed households adopted NGALU, with its total area being over half of the afforested area through the GTGP. Quantitative analyses showed that PES had no significant effects on NGCC planting but that it reduced farmland abandonment. Participation in non-farm livelihoods increased the adoption of NGALU, while livestock breeding and farmland area decreased NGALU. Additionally, the biophysical conditions of farmland parcels, such as large area, distant from households, and being adjacent to the forest edge or at a high elevation increased NGALU. This study highlights the importance of leveraging NGALU to boost ecological gains from conservation investments and provides critical implication for the extension of future PES programs with greater cost-efficiency, which can benefit the sustainable management of land resources in mountainous areas or other regions experiencing stresses for ES enhancement and human wellbeing insurance in the future.

Author Contributions

Conceptualization, X.C.; Methodology, J.N.; Formal analysis, Y.W.; Investigation, Y.W.; Writing—original draft, Y.W.; Writing—review & editing, Y.Z. and H.Y.; Supervision, X.C.; Funding acquisition, X.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (42071265; 41701549).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Figure 1. The study area.
Figure 1. The study area.
Forests 15 00521 g001
Figure 2. Farmland area with and without non-grain agricultural land use (NGALU). Farmland abandonment and NGCC planting are two types of NGALU.
Figure 2. Farmland area with and without non-grain agricultural land use (NGALU). Farmland abandonment and NGCC planting are two types of NGALU.
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Figure 3. Differences between parcel-level variables ((a), farmland area; (b), elevation; (c), slope; (d), distance to house; (e), distance to road; (f), distance to forest edge) with grain production and those with non-grain agricultural land use. FA refer to farmland abandonment. *** and ** represent significant levels of 0.001, and 0.01, respectively.
Figure 3. Differences between parcel-level variables ((a), farmland area; (b), elevation; (c), slope; (d), distance to house; (e), distance to road; (f), distance to forest edge) with grain production and those with non-grain agricultural land use. FA refer to farmland abandonment. *** and ** represent significant levels of 0.001, and 0.01, respectively.
Forests 15 00521 g003
Figure 4. Differences between household-level variables ((a), GTGP area; (b), EWFP subsidy of households; (c), proportion of households involved in tourism; (d), proportion of households involved in labor migration; (e), proportion of households involved in local non-farm; (f), proportion of households with livestock breeding; (g), farm labors; (h), farmland area; (i), proportion of households with agricultural machinery; (j), age of household head; (k), education of household head) with and without non-grain agricultural land use. FA refer to farmland abandonment. ***, **, and * represent significant levels of 0.001, 0.01, and 0.05, respectively.
Figure 4. Differences between household-level variables ((a), GTGP area; (b), EWFP subsidy of households; (c), proportion of households involved in tourism; (d), proportion of households involved in labor migration; (e), proportion of households involved in local non-farm; (f), proportion of households with livestock breeding; (g), farm labors; (h), farmland area; (i), proportion of households with agricultural machinery; (j), age of household head; (k), education of household head) with and without non-grain agricultural land use. FA refer to farmland abandonment. ***, **, and * represent significant levels of 0.001, 0.01, and 0.05, respectively.
Forests 15 00521 g004
Table 1. Adoption of different types of NGCCs.
Table 1. Adoption of different types of NGCCs.
Number of Plantation HouseholdsProportion of Plantation Households to Total Households Surveyed (%)
Cornus9634.9
Chinese medicinal herbs217.6
Nursery trees134.7
Other economic trees134.7
Table 2. Effects of household and parcel variables on NGALU.
Table 2. Effects of household and parcel variables on NGALU.
VariablesNGCC PlantingFarmland AbandonmentVIF
Odds Ratiop-Value > |z|Odds Ratiop-Value > |z|
Household level
GTGP area0.9930.1040.9260.020 **1.300
EWFP subsidy0.9970.7650.8500.020 **1.280
Livestock breeding0.5490.071 *0.2850.3081.170
Tourism business0.5430.1351.2790.8681.370
Labor migration1.8270.029 **1.7310.5921.180
Local non-farm employment1.6910.060 *8.7850.068 *1.220
Number of farm labors1.0030.9830.8680.8061.210
Farmland area0.9920.001 ***0.9750.057 *1.340
Mechanization1.0770.7843.5970.2941.240
Age of household head0.9890.2851.0360.2941.190
Education of household head0.9780.5540.9620.7911.200
Parcel level
Parcel area1.0710.000 ***1.1340.000 ***1.270
Elevation1.0100.1671.0490.058 **1.780
Slope1.0140.1121.0410.1051.180
Distance to house1.0910.020 **1.3680.007 ***1.240
Distance to road0.9920.5541.0720.1851.230
Distance to forest edge0.8010.003 **0.6250.075 *1.400
Constant0.3120.3220.0000.013-
Likelihood-ratio−324.040
Wald chi-square76.770 ***
Note: Odds ratio indicates the positive (odds ratio > 1) or negative (odds ratio < 1) effect of an environmental variable on the adoption of NGALU. VIF represents the variation inflation factor. A value of VIF < 2 suggests no collinearity for a variable with other variables. *** p < 0.01, ** p < 0.05, * p < 0.1.
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MDPI and ACS Style

Wang, Y.; Zhang, Y.; Yang, H.; Niu, J.; Chen, X. Effects of Payments for Ecosystem Services and Livelihoods on Non-Grain Agricultural Land Use. Forests 2024, 15, 521. https://doi.org/10.3390/f15030521

AMA Style

Wang Y, Zhang Y, Yang H, Niu J, Chen X. Effects of Payments for Ecosystem Services and Livelihoods on Non-Grain Agricultural Land Use. Forests. 2024; 15(3):521. https://doi.org/10.3390/f15030521

Chicago/Turabian Style

Wang, Yujun, Yan Zhang, Hongbo Yang, Jiamei Niu, and **aodong Chen. 2024. "Effects of Payments for Ecosystem Services and Livelihoods on Non-Grain Agricultural Land Use" Forests 15, no. 3: 521. https://doi.org/10.3390/f15030521

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