Scientia Agricultura Sinica ›› 2026, Vol. 59 ›› Issue (19): 4323-4334.doi: 10.3864/j.issn.0578-1752.2026.19.011

• SPECIAL FOCUS: NATURE-BASED SOLUTIONS: RESEARCH PARADIGMS AND CHINESE PRACTICES FOR GREEN AGRICULTURAL TRANSITION • Previous Articles     Next Articles

Evolutionary Trajectory, Driving Mechanisms, and China’s Pathway in Global Nature-Based Solutions for Agricultural Research

LIANG XiaoHe1(), WANG Qi1, LEI Jie1, ZHOU JiaJia2, WU Yu1(), ZHOU AiLian1()   

  1. 1 Agricultural Information Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs, Beijing 100081
    2 Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081
  • Received:2026-04-09 Accepted:2026-06-23 Online:2026-10-01 Published:2026-10-10
  • Contact: WU Yu, ZHOU AiLian

Abstract:

Against the backdrop of intensifying global climate changes and multi-faceted challenges to food security, nature-based solutions (NbS) are emerging as a key paradigm driving the green transformation of agriculture. This paper systematically traced the evolutionary logic of international and domestic research on agricultural NbS, identified the driving factors of high-impact outputs, and analyzed the localization dilemmas and institutional bottlenecks faced by China. It aimed to provide a decision-making basis for constructing an agricultural NbS theoretical system with Chinese characteristics and exploring global collaborative pathways. Based on data from the Web of Science and CNKI databases, this study adopted a quantitative analytical framework combining bibliometrics and multiple regression analysis. Scientific knowledge mapping was utilized to extract the core topics and evolutionary patterns of domestic and international research. Meanwhile, a multiple regression model was constructed to quantitatively measure the key mechanisms influencing the academic impact of global agricultural NbS research from four dimensions: collaboration networks, regional geopolitics, resource allocation, and interdisciplinary integration. The findings indicated that international research on agricultural NbS has progressed through three successive stages: Theoretical foundation, application and expansion, and mechanism deepening and model-driven. These stages have coalesced into four core research clusters: synergistic enhancement mechanism of agro-ecosystems, pathways for the ecological transformation of urban agriculture, R&D of intelligent and eco-agricultural facilities, and assessment of benefits in agricultural NbS applications, exhibiting highly empirical and granular characteristics. Regression analysis revealed that funding inputs, transnational collaboration, and interdisciplinary integration significantly elevated academic impact. Europe dominated global rule-making by virtue of its institutional advantages, and the academic spillover effect of Sino-European collaboration was significant, establishing China as a critical hub connecting Western theories with large-scale practical verification. Core funding agencies in the US and Europe effectively translated resources into academic discourse power, whereas the driving effect of China's national-level funding on frontier basic theoretical innovation remains to be strengthened. Furthermore, research within the Chinese context presented a dual-driven feature of macro-level coordination and local-level collaboration, with the research focus gradually shifting from macro-concept discussions to micro-engineering practices. However, the overall research network exhibited fragmentation, and the disciplinary distribution was highly concentrated in environmental science and traditional agricultural and forestry disciplines, lacking a comprehensive modeling paradigm for cross-system coupling. Although China currently ranks among the global leaders in terms of publication volume in agricultural NbS, it still faces challenges, such as a mismatch between publication scale and international impact, an overemphasis on localized technical validation at the expense of systematic integration, a relatively marginalized strategic status of agriculture within the broader NbS agenda, and an incomplete autonomous theoretical system. Moving forward, future research should deepen international cooperation to co-build standardized evaluation metrics, introduce social-ecological-technical system (SETS) analytical frameworks to dissolve disciplinary barriers, and strengthen top-down design to elevate the strategic weight of agricultural NbS. Furthermore, efforts should be dedicated to promoting the deep integration of the international NbS framework with China’s philosophy of a “community of life for mountains, rivers, forests, farmlands, lakes, grasslands, and deserts” thereby constructing an autonomous knowledge system for agricultural NbS that encompasses both Chinese characteristics and a global vision.

Key words: nature-based solutions, agro-ecological transition, multiple regression analysis, ecological civilization, scientific knowledge mapping, agricultural green transformation

Fig. 1

Timeline of keywords in English-language agricultural NbS research"

Fig. 2

Keyword clustering in English-language agricultural NbS research"

Table 1

Regression analysis results of the impact of collaboration, funding, and regional characteristics on the influence of agricultural NbS research"

维度Dimension 变量Variable 回归系数Coefficient 标准误Standard error P值P value
合作特征
Collaborative features
开展国际合作Engage in International Collaboration 0.3697 0.0523 <0.001***
合作国家数量Count of Collaborating Nations 0.1498 0.0138 <0.001***
中欧合作China-Europe Cooperation 0.6138 0.1329 <0.001***
中美合作China-US Cooperation 0.3571 0.1699 0.0356*
区域特征
Regional
feature
亚洲Asia 0.1666 0.0992 0.0931
非洲Africa -0.1478 0.1374 0.2820
美洲Americas -0.0527 0.0688 0.4438
欧洲Europe 0.7281 0.2970 0.0142*
大洋洲Oceania 0.1004 0.1407 0.4757
基金资助特征
(全球TOP10资助机构)
Funding Feature
(Global TOP10 Funding
Organizations)
获得基金资助Grant Funding 0.3022 0.0662 <0.001***
资助机构数量Count of Funding Organizations 0.0673 0.0122 <0.001***
巴西国家科学与技术发展委员会(CNPQ) 0.1602 0.1639 0.3284
欧盟(EU) 0.3033 0.0967 0.0017**
葡萄牙科学技术基金会(FCT) 0.1747 0.1442 0.2257
地平线2020计划(Horizon 2020) 0.2824 0.1379 0.0406*
中国国家重点研发计划(NKRDPC) 0.1759 0.2331 0.4505
中国国家自然科学基金委员会(NSFC) 0.1129 0.0985 0.2517
美国国家科学基金会(NSF) 0.4421 0.1693 0.009**
英国自然环境研究理事会(NERC) 0.2466 0.1806 0.1722
瑞典研究委员会(SRCF) 0.2399 0.1544 0.1203
英国研究与创新署(UKRI) 0.2532 0.1548 0.1019

Table 2

Regression analysis results of the impact of research field on the influence of agricultural NbS research"

序号
Serial Number
变量
Variable
回归系数
Coefficient
标准误
Standard error
P值
P value
1 建筑工程技术Construction & building technology 0.3960 0.2510 0.1146
2 区域与城市规划Regional & urban planning 0.3300 0.1687 0.0505
3 生物保护 Biodiversity conservation 0.3252 0.1316 0.0135*
4 地球科学-跨学科 Geosciences-multidisciplinary 0.2844 0.1477 0.0541
5 气象学与大气科学Meteorology & atmospheric sciences 0.2699 0.1354 0.0462*
6 海洋与淡水生物学 Marine & freshwater biology 0.2605 0.2119 0.219
7 城市研究 Urban studies 0.2509 0.0653 0.0001***
8 环境工程 Engineering environmental 0.2137 0.1000 0.0326*
9 植物科学 Plant sciences 0.2020 0.0615 0.001**
10 地理学 Geography 0.1730 0.1877 0.3566
11 跨学科 Multidisciplinary 0.1589 0.0551 0.0039**
12 环境科学 Environmental sciences 0.1279 0.0523 0.0144*
13 生态学 Ecology 0.1260 0.0718 0.0793
14 渔业 Fisheries 0.1148 0.2470 0.6419
15 能源与燃料 Energy fuels 0.0959 0.3114 0.7581
16 土木工程 Engineering civil 0.0722 0.2027 0.7218
17 环境研究 Environmental studies 0.0679 0.0561 0.2256
18 公共、环境与职业健康Public, environmental & occupational health 0.0662 0.1917 0.7299
19 跨学科科学 Multidisciplinary sciences -0.0015 0.2244 0.9946
20 自然地理学 Geography physical -0.0097 0.2695 0.9714
21 林学 Forestry -0.0285 0.0579 0.622
22 农业工程学 Agricultural engineering -0.0909 0.2547 0.7211
23 水资源 Water resources -0.0965 0.0799 0.2269
24 绿色可持续科学与技术 Green & sustainable science & technology -0.1063 0.0846 0.2092
25 土壤科学 Soil science -0.1189 0.1334 0.3729
26 遥感 Remote sensing -0.1279 0.1673 0.4445
27 农学 Agronomy -0.1630 0.1252 0.1929
28 生物技术与应用微生物学Biotechnology & applied microbiology -0.1803 0.2440 0.46
29 经济学 Economics -0.2363 0.2177 0.2777
30 农业-跨学科 Agriculture, multidisciplinary -0.2430 0.1360 0.0740
31 海洋学 Oceanography -0.4563 0.2215 0.0394*

Fig. 3

Timeline of keywords in Chinese-language agricultural NbS research"

Fig. 4

Keyword clustering in Chinese-language agricultural NbS research"

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