Soil phosphorus crisis in the Tibetan alpine permafrost region

Abstract

Phosphorus (P) is an essential nutrient for living systems and is critical to the functioning of ecosystems. Permafrost areas have a huge reservoir of soil P that is currently not used very much; however, the direction and magnitude of changes in soil P stocks across the Tibetan alpine permafrost regions over recent decades remain unclear and the P budget has not been well assessed. Here we use a unique combination of a soil resampling method and a modified process-balanced model to assess the historical dynamics of soil P pools (0-30 cm depth) and the key flows of P in ecosystems across Tibetan alpine permafrost region. Compared with the 1980s, the soil P stock decreases dramatically by 36.1% in the 2020 s, decreasing from 346.5 to 221.4 Tg P (1 Tg = 10¹² g) during the last three decades. Water erosion accounts for 82.3% of the total soil P outflow. Our projections suggest that the soil P stock will only be 20.3% of the 1980s stock by the end of this century, leading to an unprecedented crisis of P limitation in permafrost regions.

Fig. 1. Schematic model of P flow in ecosystems (MPFE) in the Tibetan alpine permafrost region.

The MPFE includes historical trajectories, current assessments, and future predictions of the soil P budget. The soil resampling P data provided the dynamic background of soil nutrients used to verify and improve the accuracy of the MPFE. The proven MPFE was then used to predict the soil P budget until 2100 according to different scenarios. The MPFE consists of the main key P inflow (weathering, atmospheric deposition, fertilizer, the deposition of livestock excretions, and the return of plant litter) and outflow (plant absorption, soil erosion, and dissolved P in runoff) subsystems. The net change in the soil P is the P inflow minus the P outflow. The plant-related P flows are defined as plant–animal–human consumption systems, consisting of three subsystems: grass–animal–human consumption system, forest–human consumption system and crop–animal–human consumption system. The boundary of the Tibetan Plateau was sourced from Zhang et al..

Fig. 2. Changes in soil P density and stock from the 1980s to the 2020s based on resampling observations.

a Frequency distributions of the soil P density during the two sampling periods. The soil P density is fitted with a ln-normal distribution and the horizontal axis is displayed on a ln scale. The frequencies of samples are shown as bars, with the curves for the probability density functions shown as orange (1980s) and blue (2020s) lines. b Relationships between soil P density in the 1980s and the 2020s. The soil P density is fitted with a in-normal distribution. The dashed line indicates the ordinary least-squares fit of the linear equation for soil P density between the two sampling periods. The shading accompanying the dashed fitted line represents the 95% confidence interval. c Changes in the soil P density during the two sampling periods. The temporal changes of the soil P density were examined with linear mixed-effects models in which the fixed effect was the sampling period and the random effect was the sampling plot. Asterisks indicate that the null hypothesis could be rejected at a significance level of **0.01 and ***0.001. The standard errors are indicated in part c. The error bars represent 95% confidence intervals. d Changes in the soil P stock derived from the large-scale resampling investigations. The change in soil P stock was calculated based on the P density and the proportion of each soil type in a given ecosystem.

Fig. 3. Change in soil P density between observations and simulations from the 1980s to the 2020s.

a Sampling plots. b Counties. Changes in grassland, forest, and cropland are given, and each symbol in part (a) corresponds to one resampling plot. The sizes of the circles in part (b) represent the relative weights of the corresponding observations in each county. The effect of measurements on the soil P density was examined with linear mixed-effects models in which the fixed effect was the method and the random effect was the sampling plot and county. The effect of methods on soil P density was considered significant if P < 0.05. The dashed lines indicate the ordinary least-squares fit of the linear equation of changes in soil P density between the observations and simulations. The shading accompanying the dashed fitted line represents the 95% confidence interval.

Fig. 4. Historical trends of annual soil P inflows and outflows in the Tibetan alpine permafrost region for the period from the 1980s to the 2020s.

a Annual soil P inflows and outflows for the overall ecosystem. b Annual soil P inflows and outflows for grassland. c Annual soil P inflows and outflows for forest. d Annual soil P inflows and outflows for cropland. e Cumulative soil P inflows and outflows for the overall ecosystem. f Cumulative soil P inflows and outflows for grassland. g Cumulative soil P inflows and outflows for forest. h Cumulative soil P inflows and outflows for cropland. The soil P inflow represents the sum of the supply of P from weathering, atmospheric deposition, fertilizer, the deposition of livestock excretions, and the return of plant litter. The soil P outflow represents the sum of P losses from plant absorption, soil erosion, and dissolved P in runoff.

Fig. 5. Trends in the soil P budget for the time period 2021–2100.

a Soil P outflows. b Soil P inflows. c Erosion and plant uptake of P as a proportion of total P outflows. d Soil P net losses. The projected P dynamics were derived under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 future climate scenarios. The SSP2-4.5 and SSP5-8.5 scenarios were applied to predict future soil P flows from 27 CMIP6 global climate models, whereas the SSP1-2.6 and SSP3-7.0 scenarios were applied to predict future soil P flows from 23 CMIP6 global climate models. The shading represents the standard deviation calculated for the corresponding 23/27 CMIP6 global climate models in each scenario. The black line shows the historical soil P budget data. The soil P outflows from erosion represent the sum of P losses from water and wind erosion. The results of the Mann–Kendall and change point tests show that the change point for the soil P budget is around 2050.