Soil Nitrogen Storage, Distribution, and Associated Controlling Factors in the Northeast Tibetan Plateau Shrublands

Distribution Characteristics and Controlling Factors of Soil Total Nitrogen: Phosphorus Ratio Across the Northeast Tibetan Plateau Shrublands

Nitrogen (N) and phosphorus (P) stoichiometry have significant effects on nutrient cycles in terrestrial ecosystems. However, our understanding of the patterns and the driving factors of soil N:P ratios in the Tibetan Plateau shrublands remains limited. Our study aimed to quantify the distribution of soil N:P ratio and its controlling factors based on soil, plant, and climate factors from 59 sites in shrublands across the northeast Tibetan Plateau. The kriging interpolation method was used to quantify the soil N:P distribution. Spatially, the soil N:P ratio was higher in the south than in the north and lower in the west than in the east. The soil N:P ratio in the northeast Tibetan Plateau shrublands was mainly explained by edaphic factors, which also played an important role in regulating the effects of plant and climate factors on soil N:P ratios. Mean annual precipitation, instead of mean annual temperature, significantly controlled the soil N:P ratios, and its effect on the pattern of soil N:P ratios differed between alpine shrublands and desert shrublands. The N:P ratios of different organs in shrublands also played different roles in shaping the soil N:P ratios in alpine and desert shrublands. These results provide support for the hypothesis that edaphic factors were the dominant drivers of spatial variation in soil N:P ratios across the northeast Tibetan Plateau shrublands, and our study contributes to a deeper understanding of biogeochemical cycling at high altitudes.

Environmentally stable common bean genotypes for production in different agro-ecological zones of Tanzania

Genotype by environment interaction (GxE) complicates the process of selecting genotypes suitable for quantitative traits like seed yield in beans, hence slows down the development and release of varieties by breeding programs. GxE study on seed yield in beans enables identification of stable genotypes across sites and best site(s) for discriminating the tested genotypes in terms of seed yield. The purpose of this study was to evaluate the influence of the environment, genotype, and genotype by environment interaction on seed yield stability and adaptability of common bean landraces, lines, and improved varieties across three different agro-ecologies in Tanzania. The 99 common bean genotypes (Landraces, lines, and improved varieties) were planted following alpha lattice design in three replications each contained five blocks with 20 plots. Soil properties from the experimental sites, days to 75% flowering, Seed yield, 100 seed weight, number of seeds/pod, and number of pods/plant were recorded. Data on seed yield and its components were analyzed using Additive main effect and multiplicative interaction (AMMI), genotype main effects plus genotype × environment interaction (GGE), and yield stability index (YSI). The AMMI revealed very highly significant (P ≤ 0.001) effects of genotypes, environmental, and genotype × environment interaction on all the traits. AMMI analysis revealed that genotype main effects accounted for 39.3% of the total sum square of seed yield, whereas the environment and genotype × environmental interaction accounted for 31.4% and 26.8 % respectively. Genotype main effects largely influenced the variation in days to 75% flowering (55.5%), number of pods/plant (49.2%), number of seeds/pod (73.3%), and 100 seed weight (71.2%). Among soil properties recorded, available soil phosphorus, soil pH, soil exchangeable K, Ca, and Na had a strong positive association with common bean seed yield, while soil organic carbon and total nitrogen exhibited a strong negative association with seed yield. GGE revealed that E1 (TARI-Selian) was the most discriminative and representative site for common bean genotypes seed yield. Based on the yield stability index, the most stable and high seed yielding genotypes were ACC 714, Selian 14, Selian 9, Katuku, and Msolini. The identified high seed yielding and stable genotypes can be further tested in participatory variety selection involving farmers and later on released as varieties and can also be used for different breeding purposes in different agro-ecologies of Tanzania.

Examining differences in phylogenetic composition enhances understanding of the phylogenetic structure of the shrub community in the northeastern Qinghai-Tibetan Plateau

Periodic climatic oscillations and species dispersal during the postglacial period are two important causes of plant assemblage and distribution on the Qinghai-Tibet Plateau (QTP). To improve our understanding of the bio-geological histories of shrub communities on the QTP, we tested two hypotheses. First, the intensity of climatic oscillations played a filtering role during community structuring. Second, species dispersal during the postglacial period contributed to the recovery of species and phylogenetic diversity and the emergence of phylogenetic overdispersion. To test these hypotheses, we investigated and compared the shrub communities in the alpine and desert habitats of the northeastern QTP. Notably, we observed higher levels of species and phylogenetic diversity in the alpine habitat than in the desert habitat, leading to phylogenetic overdispersion in the alpine shrub communities versus phylogenetic clustering in the desert shrub communities. This phylogenetic overdispersion increased with greater climate anomalies. These results suggest that (a) although climate anomalies strongly affect shrub communities, these phenomena do not act as a filter for shrub community structuring, and (b) species dispersal increases phylogenetic diversity and overdispersion in a community. Moreover, our investigation of the phylogenetic community composition revealed a larger number of plant clades in the alpine shrub communities than in the desert shrub communities, which provided insights into plant clade-level differences in the phylogenetic structures of alpine and desert shrub communities in the northeastern QTP.

Belowground biomass of alpine shrublands across the northeast Tibetan Plateau

Although belowground biomass (BGB) plays an important role in global cycling, the storage of BGB and climatic effects on it are remaining unclear. With data from 49 sites, we aimed to investigate BGB and its climatic controls in alpine shrublands in the Tibetan Plateau. Our study showed that the BGB (both grass-layer and shrub-layer biomass) storage in the alpine shrublands was 67.24 Tg, and the mean BGB density and shrublands area were 1,567.38 g/m2 and 4.29 × 104 km2, respectively. Shrub layer had a larger BGB stock and accounted for 66% of total BGB this area, while only 34% was accumulated in the grass layer. BGB of the grass layer in the Tibetan Plateau shrublands was larger than that of Tibetan alpine grasslands, indicating that shrubland ecosystem played a critical importance role in carbon cycle on the Tibetan Plateau. The BGB in the grass layer and shrub layer demonstrated different correlations with climatic factors. Specifically, the effects from mean annual temperature on shrub-layer BGB were not significant, similarly to the relationship between mean annual precipitation and grass-layer BGB. But shrub-layer BGB had a significantly positive relationship with mean annual precipitation (p < .05), while grass-layer BGB showed a trend of decrease with increasing mean annual temperature (p < .05). Consequently, the actual and potential increases of BGB varied due to different increases of mean annual precipitation and temperature among different areas of the Tibetan Plateau. Therefore, in the warmer and wetter scenario, due to contrary relationships from mean annual precipitation and temperature on shrub-layer BGB and grass-layer BGB, it is necessary to conduct a long-term monitoring about dynamic changes to increase the precision of assessment of BGB carbon sequestration in the Tibetan Plateau alpine shrublands.

Mapping of Soil Total Nitrogen Content in the Middle Reaches of the Heihe River Basin in China Using Multi-Source Remote Sensing-Derived Variables

Soil total nitrogen (STN) is an important indicator of soil quality and plays a key role in global nitrogen cycling. Accurate prediction of STN content is essential for the sustainable use of soil resources. Synthetic aperture radar (SAR) provides a promising source of data for soil monitoring because of its all-weather, all-day monitoring, but it has rarely been used for STN mapping. In this study, we explored the potential of multi-temporal Sentinel-1 data to predict STN by evaluating and comparing the performance of boosted regression trees (BRTs), random forest (RF), and support vector machine (SVM) models in STN mapping in the middle reaches of the Heihe River Basin in northwestern China. Fifteen predictor variables were used to construct models, including land use/land cover, multi-source remote sensing-derived variables, and topographic and climatic variables. We evaluated the prediction accuracy of the models based on a cross-validation procedure. Results showed that tree-based models (RF and BRT) outperformed SVM. Compared to the model that only used optical data, the addition of multi-temporal Sentinel-1A data using the BRT method improved the root mean square error (RMSE) and the mean absolute error (MAE) by 17.2% and 17.4%, respectively. Furthermore, the combination of all predictor variables using the BRT model had the best predictive performance, explaining 57% of the variation in STN, with the highest R2 (0.57) value and the lowest RMSE (0.24) and MAE (0.18) values. Remote sensing variables were the most important environmental variables for STN mapping, with 59% and 50% relative importance in the RF and BRT models, respectively. Our results show the potential of using multi-temporal Sentinel-1 data to predict STN, broadening the data source for future digital soil mapping. In addition, we propose that the SVM, RF, and BRT models should be calibrated and evaluated to obtain the best results for STN content mapping in similar landscapes.

Responses of biomass allocation across two vegetation types to climate fluctuations in the northern Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) is particularly sensitive to global climate change, especially to elevated temperatures, when compared with other ecosystems. However, few studies use long-term field measurements to explore the interannual variations in plant biomass under climate fluctuations. Here, we examine the interannual variations of plant biomass within two vegetation types (alpine meadow and alpine shrub) during 2008-2017 and their relationships with climate variables. The following results were obtained. The aboveground biomass (AGB) and belowground biomass (BGB) response differently to climate fluctuations, the AGB in KPM was dominated by mean annual precipitation (MAP), whereas the AGB in PFS was controlled by mean annual air temperature (MAT). However, the BGB of both KPM and PFS was only weakly affected by climate variables, suggesting that the BGB in alpine ecosystems may remain as a stable carbon stock even under future global climate change. Furthermore, the AGB in PFS was significantly higher than KPM, while the BGB and R/S in KPM were significantly higher than PFS, reflecting the KPM be more likely to allocate more photosynthates to roots. Interestingly, the proportion of 0-10 cm root biomass increased in KPM and PFS, whereas the other proportions both decreased, reflecting a shift in biomass toward the surface layer. Our results could provide a new sight for the prediction how alpine ecosystem response to future climate change.