Distribution, trends and drivers of precipitation use efficiency in the loess plateau

Abstract

Against the background of climate change, the global carbon and water cycle has undergone significant changes, and it is of great significance to explore the interrelationships of the carbon and water cycles in different regions to cope with future climate change. In this study, based on gross primary productivity (GPP) and precipitation (PRE) data, the precipitation use efficiency (PUE) of the Loess Plateau (LP) was calculated, and the Sen trend analysis and Mann‐Kendall test were used to analyse the temporal and spatial variation characteristics of PUE, as well as the first‐order difference method was used to derive the relative contributions to quantify the impact of vegetation growth and meteorological factors on PUE. The results show that (1) from 2001 to 2018, the spatial distribution pattern of vegetation PUE exhibited an increasing trend from northwest to southeast. On the time scale, the multi‐year average value of PUE was 1.17 gC m−2 mm−1, showing an overall upward trend. Among the different land cover types, paddy fields had the highest PUE level, and sparse grassland had the lowest; (2) LAI had the highest relative contribution to vegetation PUE, followed by temperature (Temp), net radiation of the ground surface (RN), specific humidity (Shum), and wind speed (WS). LAI contributes positively to 88.9% of the area. RN positively influences high‐altitude areas, while Shum had a larger area with a negative contribution. The contribution of Temp increases from northwest to southeast, and WS has balanced positive and negative contributions; (3) LAI is the dominant factor for the spatial and temporal variation of PUE in the LP, and the size of the areas where different meteorological factors dominate the changes of PUE are as follows: WS > Shum>RN > Temp. At high altitudes, the dominant meteorological driver is WS, while at low altitudes, the dominant climate driver is Shum. This study is of guiding significance for the ecological restoration and management of the LP, and it can also provide a scientific basis for the improvement of ecosystems and the sustainable management of water resources in the context of global climate change.

Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment

“…GPP varies dynamically across multiple scales in time, but studies tend to conduct trend analyses of annual GPP values. For example, the annual trend of GPP values has been investigated in studies where the entire Earth is considered as the study area [25,26], in studies for China [27][28][29][30], in studies for India [21,31] and in studies for Australia [32]. While this may provide acceptable results for the study at hand, the trend of monthly GPP values over time is important in natural areas, and especially in cultivated agricultural areas, for understanding trends in productivity and investigating changes in seasonal patterns that may have management implications [33].…”