Exploring the Response of Net Primary Productivity Variations to Land Use/Land Cover Change: A Case Study in Anhui, China

Abstract

Land use and land cover change (LUCC) has a significant influence on regional net primary productivity (NPP) in territorial ecosystems. Evaluating the driving factors of LUCC and the influences of LUCC on NPP is significant for understanding the driving mechanisms deeply and improve land management. NPP as estimated by the Carnegie-Ames-Stanford Approach (CASA) model was employed as an important indicator to evaluate the influences of LUCC on regional NPP and decouple interactive effects of LUCC and climate change on NPP in Anhui from 2001 to 2010. The results demonstrated that 34.25% of the whole area had occurred in LUCC. The most dominant transformation of LUCC was the conversion from grassland and crop/natural vegetation mosaic to forest and cropland. The area of cropland and forest had the most increments compared to other land use types, with an increase of 30.52% and 35.29% of that in 2001. Socioeconomic development, economic interests and government policies took an important role in driving the LUCC. The total NPP increased mainly due to the contributions of the area expansion of cropland and forest. Climate change resulted in the decreased NPP of 449.84 GgC, whereas LUCC facilitated the NPP in the increase of 1816.05 GgC. This result indicates that the increased NPP induced by LUCC could offset the NPP decrease from climate change during the study periods. This paper also demonstrated that reforestation and forest protection were indeed effective in promoting ecosystem productivity.

Characteristic Analysis of Carbon Sink Capacity Changes in Xinjiang’s Terrestrial Ecosystem Based on EEMD

“…However, existing research has predominantly focused on data analysis for the initial and final years of LUCC, overlooking the dynamic processes during this period. Additionally, there exists a restricted research corpus concerning the influence of landscape patterns on NEP [11]. Examining how alterations in landscape patterns affect NEP facilitates the development of more efficient land management tactics, fostering favorable advancements in carbon balance.…”

Estimation and Climate Impact Analysis of Terrestrial Vegetation Net Primary Productivity in China from 2001 to 2020

“…In recent years, the CASA model has been applied to the estimation of different vegetation, such as grassland [15,16], cropland [17,18], and various types of forests [4,19]. In terms of research regions, in China, for example, experiments on NPP estimation have been conducted in local research units, such as the Qinghai-Tibet plateau [20], central China [21], provincial units [22][23][24], and so on. The effectiveness of the model for the NPP estimation of different vegetation at the national scale, and the effect of NPP estimation of the same vegetation type in different regions, still need to be compared and evaluated, thus providing a reference for model selection by subsequent researchers.…”