Tong Guo

Plant diversity plays an important role in shaping the carbon cycling of grassland ecosystems. However, differences in the diversity effect on aboveground and belowground carbon storage remains unclear at specific spatiotemporal scales. A transplant experiment was carried out along the gradient of altitude (4600–5200 m) in alpine grasslands of the Qinghai–Tibetan Plateau in the year 2017. Vegetation characteristics like species richness, vegetation cover and height were measured in the years 2020 and 2021. The plant diversity was described by species richness. Then, I calculated the vegetation biomass to quantify the aboveground carbon storage. The belowground carbon storage was represented by soil organic carbon. The results showed that the effect of species richness on belowground carbon storage was significantly positive (p < 0.05) at most altitudes for both years. However, the diversity effect on aboveground carbon storage was weak and inconsistent. The relationship between species richness and belowground carbon storage remained relatively stable over a period of two years. In contrast, the relationship altered greatly in terms of aboveground carbon storage in terms of inter-annual changes. Precipitation of growing seasons significantly impacted the species richness rather than aboveground carbon storage. Soil temperature was significantly associated with belowground carbon storage. These findings provide a new insight which will help us to assess the relationship between plant diversity and ecosystem functioning. They also allow us to understand how vegetation responds to climate change in high-altitudes areas.

Various disturbances like extreme climate events, fires, and insect outbreak severely impact forest ecosystems, and differences are expected between planted and natural forests. However, there is little information on the spatio-temporal dynamics of the disturbances in terms of both forest types. In this study, we used the LandTrendr algorithm to detect disturbances in planted and natural forests in a temperate region of Northern China from 1985 to 2020 using Landsat and Sentinel 2 satellite data. The planted and natural forests suffered severe disturbances in 1994 in the south (park establishment) and in 2012 in the north (severe drought). More than one third of the area of planted (37.5%) or natural (35.8%) forests was highly disturbed. The duration of forest disturbances was mostly 1 to 3 years in terms of planted or natural forests. The NDVI anomaly of the planted forests decreased from 0.24 to −0.08 after drought events, while the reduction was from 0.22 to −0.06 for natural forests. Afterwards, the NDVI anomaly of the planted forests showed a slow upward variation but not for the natural forests. This study allows us to evaluate the response of various forest types to disturbance regimes.

Changes in soil nitrogen mineralization can impact nutrient availability, and further affect plant growth. It is unclear, however, how temperature elevation in alpine grassland will affect soil net N mineralization rate (N_min) across altitudes. At six altitudes (3200 m to 4200 m with an interval of 200 m) along a slope in Lenglong mountain in the northern Qinghai-Tibetan Plateau, we performed an in-situ soil incubation experiment by using the resin-core method to assess altitudinal variations of N_min. Meanwhile, we evaluated the effects of temperature elevation on N_min and its temperature sensitivity (Q₁₀) through a soil downward transplantation experiment based on three reference baseline altitudes (3800 m, 4000 m, and 4200 m). The results showed that high altitudes generally led to low values of N_min. Structural equation modelling analysis revealed that N_min along the altitude was mainly controlled by soil temperature. Increased temperature caused by the altitude transplantation significantly elevated N_min for all of the three reference altitudes. The value of Q₁₀ was 3.4 for soil samples transplanted from the reference altitude of 4200 m, which was about twice that of the lower reference altitudes of 4000 m and 3800 m.

Characterizing extreme precipitation precisely is crucial for predicting vegetation response to drought or storms. However, current precipitation generators in vegetation models do not simulate the occurrence and amount of extreme precipitation well. This study examined the effects of extreme precipitation on the skewness, kurtosis, and skewness–kurtosis interaction of annual precipitation distribution. The examination was based on theoretical calculations and monitoring data from 78 meteorological stations on the Qinghai–Tibetan Plateau (QTP). The results showed that extreme precipitation generally increased the skewness and kurtosis of annual precipitation distribution. A higher mean annual precipitation amplified the effects of precipitation extremes on promoting skewness and kurtosis in normal distribution scenarios. In contrast, these effects tended to be saturated for scenarios of higher mean annual precipitation in probability-based distributions. A reduction of dry days in a year markedly intensified the interaction of the skewness and the kurtosis, while the skewness–kurtosis interaction weakened with decreased maximum daily precipitation in a year. Moreover, the effect of extreme precipitation on the skewness–kurtosis interaction was stronger in arid or low-altitude areas. This study illustrates the fact that considering the skewness and kurtosis of annual precipitation distributions will be very helpful for simulating extreme precipitation on the QTP in the future. This will allow us to better understand the impact of climate change on alpine plants.

Conserving aquatic ecosystems requires efficient tools to accurately assess the biodiversity of aquatic species. However, existing knowledge is insufficient in terms of the reliability and the comparability of methods measuring fish diversity. Environmental DNA (eDNA), as a promising method, was used to detect fish taxa in this study. We optimized the eDNA method in the laboratory, and applied the optimal eDNA method to survey fish diversity in a natural aquatic life reserve. We simulated necessary steps of the eDNA method in the lab to increase the confidence of the field survey. Specifically, we compared different eDNA sampling, extraction, and sequencing strategies for accurately capturing fish species of the target area. We found that 1L water samples were sufficient for sampling eDNA information of the majority taxa. The filtration was more effective than the centrifugal precipitation for the eDNA extraction. The cloning sequencing was better than the high-throughput sequencing. The field survey showed that the Shannon–Wiener diversity index of fish taxa was the highest in Huairou Reservoir. The diversity index also showed seasonal changes. The accuracy rate of detecting fish taxa was positively correlated with the eDNA concentration. This study provides a scientific reference for an application of the eDNA method in terms of surveying and estimating the biodiversity of aquatic species.

Long-term variabilities in daily precipitation and temperature are critical for assessing the impacts of climate change on ecosystems. We characterized intra- and interannual variabilities in daily precipitation and temperature obtained from 1960 to 2015 at 78 meteorological stations on the Qinghai-Tibetan Plateau. The results show that 1) The intra-annual variability of daily precipitation increases for 55 meteorological stations with a rate of 0.08 mm per decade. In contrast, the intra-annual variability markedly decreases for daily mean, daytime mean, and nighttime mean temperatures with a rate of 0.09, 0.07, and 0.12 °C per decade, respectively at 90% or more of stations. 2) Variabilities of daily precipitation and temperatures are quite sensitive to high altitudes (> 3500 m). The intra- and interannual variabilities of daily precipitation significantly decrease at 1.0 and 0.07 mm per 1000 m, respectively. However, variations of high altitudes increase the intra- and interannual variabilities of daily mean temperature at 1.0 °C and 0.2 °C per 1000 m. Moreover, the interannual variability of nighttime mean temperature varies at 0.3 °C per 1000 m, the fastest rate among three temperature indices. 3) A larger mean annual precipitation is accompanied by a higher intra- and interannual variability of daily precipitation on the Qinghai-Tibetan Plateau; however, a higher mean annual temperature leads to lower variabilities of daily temperatures. This study illustrates that long-term climatic variability is understudied in alpine ecosystems characterized by high climatic sensitivity. Precipitation and temperature variabilities should be characterized to improve predictions of vulnerable ecosystems responding to climate change. Long-term variabilities in daily precipitation and temperature are critical for assessing the impacts of climate change on ecosystems. We characterized intra- and interannual variabilities in daily precipitation and temperature obtained from 1960 to 2015 at 78 meteorological stations on the Qinghai-Tibetan Plateau. The results show that 1) The intra-annual variability of daily precipitation increases for 55 meteorological stations with a rate of 0.08 mm per decade. In contrast, the intra-annual variability markedly decreases for daily mean, daytime mean, and nighttime mean temperatures with a rate of 0.09, 0.07, and 0.12 °C per decade, respectively at 90% or more of stations. 2) Variabilities of daily precipitation and temperatures are quite sensitive to high altitudes (> 3500 m). The intra- and interannual variabilities of daily precipitation significantly decrease at 1.0 and 0.07 mm per 1000 m, respectively. However, variations of high altitudes increase the intra- and interannual variabilities of daily mean temperature at 1.0 °C and 0.2 °C per 1000 m. Moreover, the interannual variability of nighttime mean temperature varies at 0.3 °C per 1000 m, the fastest rate among three temperature indices. 3) A larger mean annual precipitation is accompanied by a higher intra- and interannual variability of daily precipitation on the Qinghai-Tibetan Plateau; however, a higher mean annual temperature leads to lower variabilities of daily temperatures. This study illustrates that long-term climatic variability is understudied in alpine ecosystems characterized by high climatic sensitivity. Precipitation and temperature variabilities should be characterized to improve predictions of vulnerable ecosystems responding to climate change.

Extreme climate events are typically defined based on the statistical distributions of climatic variables; their ecological significance is often ignored. In this study, precipitation and temperature data from 78 weather stations spanning from 1960 to 2015 on the Qinghai-Tibetan Plateau were examined. Specifically, long-term and altitudinal variability in ecologically relevant climate indices and their seasonal differences was assessed. The results show that indices of daily temperatures greater than 10 °C and 25 °C show positive annual change trends during the growing season (May to September). Indices of daily rainfall greater than 2 mm, 3 mm and 5 mm positively alternate with years both in and around the growing season (May–September, April and October). In contrast, the index of daily snowfall greater than 2 mm shows opposite annual variability. Additionally, a higher altitude significantly leads to fewer days with temperature deviations above 20 °C, except for in October. The three abovementioned rainfall indices present significantly positive variability with increasing altitude during the growing season. In contrast, the snow index shows similar altitudinal changes in the months surrounding the growing season. This study allows us to better cope with the threats of climate change to vulnerable ecosystems.

Plant communities and their environments are a vital part of synecology research. In this study, we investigated the characteristics of three typical medicinal perennial herbs, Glycyrrhiza uralensis, Rheum altaicum, and Ferula sinkiangensis, and examined their response to local soil properties in Altay Prefecture, China. A total of 29 species belonging to 15 families and 25 genera were recorded. In terms of the target medicinal plants, the importance value was low and community structures were exceedingly simple. Quantitative classification based on WARD cluster analysis suggested that each medicinal plant can be classified into one of three types: annual herbaceous, perennial herbaceous, and subshrub or shrub. Interestingly, the plants gradually transformed from exhibiting nonresistance to xerophytes or halophytes. An investigation of the soil properties beneath the medicinal plants showed that nutrients in black soil were much more abundant than those in sandy and saline soil. Except for leaching phenomenon, the nutrient contents in the soil surface layer (0–10 cm) were higher than those in deep layers (10–20 cm and 20–40 cm), and to some extent, the nutrient contents were inversely proportional to the depth of the soil. The redundancy analysis (RDA) results of the medicinal plants and their relationship with soil properties indicated that the main soil variables impacting the distribution of G. uralensis were available potassium (AK), aspect (ASP), soil moisture (SM), total nitrogen (TN), and total phosphorus (TP); SM, electric conductivity (EC), elevation (ELE), ASP, pH value (pH), available nitrogen (AN), soil organic content (SOC), and the carbon/nitrogen (C/N) ratio had positive effects on the distribution of R. altaicum. F. sinkiangensis grew better in habitats with high contents of SM, EC, TN, AN, available phosphorus (AP), total potassium (TK), and AK. This study aimed at providing effective suggestions for artificial cultivation, conservation, and resilience of Chinese medicinal plants.