Degradation of net primary production in a semiarid rangeland

Abstract

Abstract. Anthropogenic land degradation affects many biogeophysical processes, including reductions of net primary production (NPP). Degradation occurs at scales from small fields to continental and global. While measurement and monitoring of NPP in small areas is routine in some studies, for scales larger than 1 km 2 , and certainly global, there is no regular monitoring and certainly no attempt to measure degradation. Quantitative and repeatable techniques to assess the extent of deleterious effects and monitor changes are needed to evaluate its effects on, for example, economic yields of primary products such as crops, lumber, and forage, and as a measure of land surface properties which are currently missing from dynamic global vegetation models, assessments of carbon sequestration, and land surface models of heat, water, and carbon exchanges. This study employed the local NPP scaling (LNS) approach to identify patterns of anthropogenic degradation of NPP in the Burdekin Dry Tropics (BDT) region of Queensland, Australia, from 2000 to 2013. The method starts with land classification based on the environmental factors presumed to control (NPP) to group pixels having similar potential NPP. Then, satellite remotely sensing data were used to compare actual NPP with its potential. The difference in units of mass of carbon and percentage loss were the measure of degradation. The entire BDT (7.45 × 10 6 km 2 ) was investigated at a spatial resolution of 250 × 250 m. The average annual reduction in NPP due to anthropogenic land degradation in the entire BDT was −2.14 MgC m −2 yr −1 , or 17 % of the non-degraded potential, and the total reduction was −214 MgC yr −1 . Extreme average annual losses of 524.8 gC m −2 yr −1 were detected. Approximately 20 % of the BDT was classified as "degraded". Varying severities and rates of degradation were found among the river basins, of which the Belyando and Suttor were highest. Interannual, negative trends in reductions of NPP occurred in 7 % of the entire region, indicating ongoing degradation. There was evidence of areas that were in a permanently degraded condition. The findings provide strong evidence and quantitative data for reductions in NPP related to anthropogenic land degradation in the BDT.

Comprehensive Research on Remote Sensing Monitoring of Grassland Degradation: A Case Study in the Three-River Source Region, China

“…Many previous studies have calculated vegetation related index and analyzed spatial-temporal dynamics successfully over the given observation period [5,8]. Some studies have attempted to monitor grassland degradation through NPP, normalized index (NDVI), enhanced vegetation index (EVI), vegetation coverage, surface temperature, land-cover dynamic, and other indicators [6,[9][10][11][12][13].…”

Impacts of land conversion and management measures on net primary productivity in semi-arid grassland

“…Net primary productivity (NPP) is the net solar energy accumulated by vegetation per unit area and unit time. It is an important proxy of ecosystem function and carbon sequestration capacity (Jackson and Prince 2016). Actual NPP is the net solar energy accumulated by vegetation under the double influences of climatic conditions and anthropogenic activities, while potential NPP is the net energy fixed by vegetation, which is solely driven by climatic factors (Haberl et al 2007).…”

Spatial pattern and temporal trend of land degradation in the Heihe River Basin of China using local net primary production scaling

“…Previous studies assessed land degradation by building a comprehensive index system or through change detection analysis of long‐term remote sensing data (Jackson & Prince, ; Nachtergaele et al, ; Noojipady, Prince, & Rishmawi, ; Qi & Luo, ). The former approach can identify the dominant factor(s) resulting in land degradation, such as water erosion, desertification, drought, salinization and so forth.…”

“…However, a pixel with low vegetation NPP does not mean it undergoes land degradation if there is no criterion of land productivity for comparison. The local NPP scaling (LNS) method (Jackson & Prince, ; Prince, ; Prince et al, ; Wessels, Prince, & Becker‐Reshef, ) can find and use reference NPP as the standard productivity with no degradation. Within the pixels sharing the same environmental conditions, the difference between present NPP and reference NPP can be regarded as a sign of a degradative process (Prince, ).…”

“…Reference NPP is difficult to determine (An et al, ) because it is challenging to accurately divide the spatial units sharing similar environmental conditions. Classifying a group of environmental variables is an effective way to derive the spatially homogeneous units (Jackson & Prince, ; Noojipady et al, ). However, the selection of environmental variables is still somewhat subjective, and the data for some key variables are not always available.…”