16 How parameterization improves Light-use efficiency (LUE) models by taking into account the seasonal 17 variations of the maximum LUE ( max  ) has been rarely investigated. The LUE models include two 18 categories which are the one-leaf LUE model (SL-LUE) and the two-leaf LUE model (TL-LUE) with 19 separation of sunlit and shaded leaves ( msu  and msh  ). In this study, the SL-LUE and TL-LUE models 20 were parameterized for 46 towers (176 site-years data) representing eighteen typical plant functional 21 types (PFTs) by using the Metropolis-Hasting algorithm at monthly time scales. The results indicate 22 that the maximum LUE parameters varied seasonally for most PFTs having a significant positive linear 23 correlation with leaf area index (LAI) and ambient temperature changes. The relationships of msu  and 24 msh  with max  can be well described by linear equations, indicating the existence of general patterns 25 across biomes. And as expected, The LUE models with the seasonal fluctuations of max  , msu  and 26 msh  significantly improved GPP estimation except for needleleaf evergreen forests in mid-and low-27 latitude regions. The improvements of both the SL-LUE and TL-LUE models were most significant in 28 summer for tropical and Mediterranean climate regions, while most evident in spring and winter for 29 temperate and boreal climate regions. Even with seasonal parameters, both the LUE models still cannot 30 well capture GPP dynamics in cold season for some PFTs in Mediterranean and tropical regions (e.g., 31Tropical-BEF, C3-C4 grass). This study suggests that further improvement of modelling GPP requires 32 taking into account seasonal variations of the key parameters. 33

Soil organic carbon (SOC) plays an essential role in the early stages of pedogenisis and ecological restoration in reclaimed mine soils. Dynamic changes in the SOC content are essential for assessing the quality of reclaimed mine soils and the effect of ecological restoration. To objectively assess the carbon dynamics of reclaimed soils, we selected the surface (0-20 cm) soil of farmland under agricultural use (soybean-wheat rotation) from a reclamation chronosequence (R4: 4 years of reclamation, R7: 7 years of reclamation, R10: 10 years of reclamation and R13: 13 years of reclamation) in the Dongtan Mining Area, Shandong Province, China. The adjacent normal, unaffected farmland was used as a control (CK). The results showed that the SOC content gradually increased with the reclamation age until it reached 7.98 g·kg −1 for R13, which accounted for 76% of that of the CK. However, the total carbon contents of the reclaimed soils did not significantly differ from and even appeared higher than that of the CK. This is mainly because the inorganic carbon contents of the reclaimed soils ranged from 2.98 to 12.61 g·kg −1 , all of which were significantly higher than the 0.87 g·kg −1 obtained for the CK. The microbial biomass carbon (MBC) content and the microbial quotient significantly increased with the reclamation age of the soil, and both parameters were markedly higher for R13 than for the CK. The dissolved organic carbon (DOC) content and its ratio to the SOC were significantly higher for R4-R13 than for the CK and DOC/SOC gradually decreased with the reclamation age. Both the reclamation age and the temperature had positive effects on the soil basal respiration (SBR). The SBR rate constantly increased with the reclamation age and was markedly higher at 25 • C than at 15 • C. The temperature sensitivity (Q 10 ) of the SBR showed a clearly decreasing trend for the reclamation chronosequence, but its value remained higher for R13 than for the CK (2.37). The metabolic quotient constantly decreased with the reclamation age, which suggests that the survival pressure imposed on soil microbes by the soil environment gradually decreased. These results indicate that it takes a long time for organic carbon to accumulate in reclaimed mine soil and that rational agricultural use contributes to sustained improvement of the quality of reclaimed soil.

Understanding the response of vegetation and ecosystem resilience to climate variability and drought conditions is essential for ecosystem planning and management. In this study, we assessed the vegetation changes and ecosystem resilience in the Horn of Africa (HOA) since 2000 and detected their drivers based mainly on analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS) products. We found that the annual and seasonal trends of NDVI (Normalized Difference Vegetation Index) generally increased during the last two decades over the Horn of Africa particularly in western parts of Ethiopia and Kenya. The weakest annual and seasonal NDVI trends were observed over the grassland cover and tropical arid agroecological zones. The NDVI variation negatively correlated with Land Surface Temperature (LST) and positively correlated with precipitation at a significant level (p < 0.05) account for 683,197 km2 and 533,385 km2 area, respectively. The ecosystem Water Use Efficiency (eWUE) showed overall increasing trends with larger values for the grassland biome. The precipitation had the most significant effect on eWUE variation compared to LST and annual SPEI (Standardized Evapotranspiration Index). There were about 54.9% of HOA resilient to drought disturbance, whereas 32.6% was completely not-resilient. The ecosystems in the humid agroecological zones, the cropland, and wetland were slightly not-resilient to severe drought conditions in the region. This study provides useful information for policy makers regarding ecosystem and dryland management in the context of climate change at both national and regional levels.

a b s t r a c tMost current land surface models (LSMs) show poor performance in soil water and temperature simulations for cold regions because of the inappropriate model structures and ill-parameterizations. This study aims to explore how to parameterize soil organic carbon (SOC) in term of soil moisture simulations using the Community Land Model version 4.0 (CLM4.0) model and the Dynamic Land Model version 1.0 (DLM1.0) model. Firstly, we discuss the sensitivities of modeled soil moisture to SOC based on observations. The SOC parameterizations in both CLM4.0 and DLM1.0 were proved poor against the measured SOC through sensitivity analysis for the Heihe River watershed area (cold but with high SOC). A SOC parameterization was developed and tested based on multiple year observations. Our findings are twofold: (i) the soil organic parameterizations in CLM4.0 and DLM1.0 are inappropriate for simulating soil moisture in cold regions with high SOC, and the modified SOC parameterization significantly improves the soil moisture simulations; (ii) the impacts of SOC on soil moisture vary significantly with seasons, which is largest for JJA (June, July and August) followed by SON (September, October and November), MAM (March, April and May) and DJF (December, January and February). This study highlights that the impacts of SOC should be fully considered for LSMs soil moisture simulations, especially for cold areas with high SOC.

Here, we provided a comprehensive analysis of long-term drought and climate extreme patterns in the agro ecological zones (AEZs) of Pakistan during 1980–2019. Drought trends were investigated using the standardized precipitation evapotranspiration index (SPEI) at various timescales (SPEI-1, SPEI-3, SPEI-6, and SPEI-12). The results showed that droughts (seasonal and annual) were more persistent and severe in the southern, southwestern, southeastern, and central parts of the region. Drought exacerbated with slopes of −0.02, −0.07, −0.08, −0.01, and −0.02 per year. Drought prevailed in all AEZs in the spring season. The majority of AEZs in Pakistan’s southern, middle, and southwestern regions had experienced substantial warming. The mean annual temperature minimum (Tmin) increased faster than the mean annual temperature maximum (Tmax) in all zones. Precipitation decreased in the southern, northern, central, and southwestern parts of the region. Principal component analysis (PCA) revealed a robust increase in temperature extremes with a variance of 76% and a decrease in precipitation extremes with a variance of 91% in the region. Temperature and precipitation extremes indices had a strong Pearson correlation with drought events. Higher temperatures resulted in extreme drought (dry conditions), while higher precipitation levels resulted in wetting conditions (no drought) in different AEZs. In most AEZs, drought occurrences were more responsive to precipitation. The current findings are helpful for climate mitigation strategies and specific zonal efforts are needed to alleviate the environmental and societal impacts of drought.