Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Peng Xue,Haibo Gong,Huiyu Liu,Li Cao,Mingyang Zhang

doi:10.3390/rs14010015

Abstract

Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.

Highlights

The net primary productivity (NPP) of vegetation, the amount of organic matter accumulated by green plants in unit time and unit area, directly reflects the productivity of a plant community
We focused on the nonlinear characteristic of vegetation NPP when considering vegetation type dynamics, and only considered the effects of dynamics of vegetation types caused by human activities on the trends of vegetation NPP, ignoring the influence of climate change
Vegetation NPP was dominated by interannual variations on 3-year and 6-year time scales, and were likely to be sensitive to external disturbances

Summary

Introduction

The net primary productivity (NPP) of vegetation, the amount of organic matter accumulated by green plants in unit time and unit area, directly reflects the productivity of a plant community. The NPP can determine the carbon sources and sinks in an ecosystem; Remote Sens. 2022, 14, 15 it plays a very important role in the global change and carbon balances [1,2,3,4,5,6]. Evaluating the change in the vegetation, NPP cannot only help us understand the changes in vegetation NPP, and further evaluate the ecosystem health [7]. With the development of remote sensing technology, parameter models for estimating. NPP with remote sensing have become more and more widely used due to their easy and simple operation.

Methods

Results

Discussion

Conclusion