植被净初级生产力(NPP)是地表碳循环的重要组成部分,准确评估NPP对正确理解生态系统能量转化,评价生态系统健康情况具有重要意义｡当前,已有研究分别从光能利用率､生态系统过程模拟､遥感数据驱动的角度对NPP评估开展了综述,但针对模型具体计算方法的研究综述仍值得进一步完善｡文章依照气候生产力模型､生理生态过程模型和光能利用模型的划分思路,系统梳理了典型的NPP评估模型;重点关注各模型的结构与驱动参数,探讨分析了各模型的特点及适用性;针对模型发展存在的关键问题作出展望,探讨了未来研究的发展趋势,即需要融合多学科视角,发挥好对新型地观测技术的优势,进一步深化尺度转换的相关研究｡

Net primary productivity ( NPP) of vegetation is an important component of the surface carbon cycle, and the accurate assessment of NPP is of great significance to the correct understanding of ecosystem energy transformation and the evaluation of ecosystem health. While existing studies have reviewed NPP assessment from perspectives such as light use efficiency, ecosystem process simulation, and remote sensing data-driven approaches, there remains a need for further refinement in reviewing specific drug molecules, and the relationship trend between different descriptors and the three performance indicators were preliminarily explored. Secondly, six machine learning models including Random Forest, Extreme Gradient Boosting ( XGB) , Gradient Boosting Decision Tree, Light Gradient Boosting Machine, Backpropagation Neural Network, and Support Vector Regression six machine learning algorithms with eight descriptors and three performance evaluation criteria ( Adsorption selectivity SS-IBU/ N2 ,Adsorption capacity NS-IBU/ N2 and Tradeoff value TSN) for big data training and mining, were used to establish quantitative relationships. The results show that the prediction accuracy of the six ML algorithms is N > TSN > S . For S , XGB showed the best prediction ( R2 = 0.83) . Subsequently, based on the XGB model, the SHaple Additive explanation ( SHAP) method was used to explain and analyze the importance of MOF descriptors to performance indicators. The total energy generated during MOF adsorption is considered to be the key influencing factor, and it shows a positive correlation trend with both TSN and NS-IBU . Finally, combined with toxicological analysis, a series of high-performance MOF materials were recommended and designed. This work, from molecular level, high-throughput computing to big data mining, systematically studied the adsorption and delivery mechanism of ibuprofen drug molecules in MOF, which provides theoretical guidance for drug delivery materials. calculation methods. In this study, typical NPP assessment models are systematically reviewed according to the classification of climate productivity model, physiological and ecological process model, and light energy use model. Focusing on the structure and driving parameters of each model, this paper discusses and analyzes the characteristics and applicability of each model, and makes an overview of the key issues of the models-development, pointing out that future research needs to integrate the perspectives of multiple disciplines, give full play to the advantages of the new earth observation technology, and further deepen the scale conversion related to NPP assessment.