Quantitative Effects of Climate Change on Vegetation Dynamics in Alpine Grassland of Qinghai-Tibet Plateau in a County

Out of the Qinghai-Tibetan plateau: Origin, evolution and historical biogeography of Morchella (both Elata and Esculenta clades)

Introduction

Morchella has become a research hotspot because of its wide distribution, delicious taste, and phenotypic plasticity. The Qinghai-Tibet Plateau subkingdoms (QTPs) are known as the cradle of Ice age biodiversity. However, the diversity of Morchella in the QTPs has been poorly investigated, especially in phylogenetic diversity, origin, and biogeography.

Methods

The genealogical concordance phylogenetic species recognition (GCPSR, based on Bayesian evolutionary analysis using sequences from the internal transcribed spacer (ITS), nuclear large subunit rDNA (nrLSU), translation elongation factor 1-α (EF1-α), and the largest and second largest subunits of RNA polymerase II (RPB1 and RPB2)), differentiation time estimation, and ancestral region reconstruction were used to infer Morchella's phylogenetic relationships and historical biogeography in the QTPs.

Results

Firstly, a total of 18 Morchella phylogenetic species are recognized in the QTPs, including 10 Elata clades and 8 Esculenta clades of 216 individuals Secondly, the divergences of the 18 phylogenetic species were 50.24-4.20 Mya (Eocene-Pliocene), which was closely related to the geological activities in the QTPs. Furthermore, the ancestor of Morchella probably originated in the Northern regions (Qilian Shan, Elata cade) and southwestern regions (Shangri-La, Esculenta clade) of QTPs and might have migrated from North America (Rufobrunnea clade) via Beringian Land Bridge (BLB) and Long-Distance Dispersal (LDD) expansions during the Late Cretaceous. Moreover, as the cradle of species origin and diversity, the fungi species in the QTPs have spread out and diffused to Eurasia and South Africa starting in the Paleogene Period.

Conclusion

This is the first report that Esculenta and Elata clade of Morchella originated from the QTPs because of orogenic, and rapid differentiation of fungi is strongly linked to geological uplift movement and refuge in marginal areas of the QTPs. Our findings contribute to increasing the diversity of Morchella and offer more evidence for the origin theory of the QTPs.

Vegetation Dynamics and Their Influencing Factors in China from 1998 to 2019

Vegetation is a critical component of ecosystems that is influenced by climate change and human activities. It is therefore of great importance to investigate trends in vegetation dynamics and explore how these are influenced by climate and human activities. This will help formulate effective ecological restoration policies and ensure sustainable development. As the Normalized Difference Vegetation Index (NDVI) is strongly correlated with vegetation dynamics and may be used as a proxy measure for vegetation condition, the spatiotemporal characteristics of NDVI derived from SPOT/VEGETATION NDVI data in China over the 1998–2019 period were assessed using the Mann–Kendall test and the Hurst exponent. The Pearson correlation analysis and residual analysis methods were employed to analyze the influencing factors of NDVI dynamics. Integrating the results of the Hurst exponent and the NDVI trend analysis, it was found that the majority area of China is presenting an increasing NDVI trend at present but is likely to reverse in the future. A significant positive correlation between the NDVI and temperature was observed on the southeast coast of China and the north Qinghai–Tibet Plateau. Precipitation was the dominant factor affecting vegetation dynamics as indicated by a positive correlation with the NDVI for most parts of China except for the inland area in the Northwest and the Hengduan Mountains in Southwest China. Extreme temperature and extreme precipitation have also shown varying degrees of influence on vegetation dynamics at various locations. In addition, this study revealed trends of increasing NDVI, suggesting improved vegetation condition attributable to the implementation of ecological engineering projects. This study is helpful for studying the interaction mechanisms between terrestrial ecosystems and climate and for sustaining the ecological environment.

Long-Term Dynamics and Response to Climate Change of Different Vegetation Types Using GIMMS NDVI3g Data over Amathole District in South Africa

Monitoring vegetation dynamics is essential for improving our understanding of how natural and managed agricultural landscapes respond to climate variability and change in the long term. Amathole District Municipality (ADM) in Eastern Cape Province of South Africa has been majorly threatened by climate variability and change during the last decades. This study explored long-term dynamics of vegetation and its response to climate variations using the satellite-derived normalized difference vegetation index from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS NDVI3g) and the ERA5-Land global reanalysis product. A non-parametric trend and partial correlation analyses were used to evaluate the long-term vegetation changes and the role of climatic variables (temperature, precipitation, solar radiation and wind speed) during the period 1981–2015. The results of the ADM’s seasonal NDVI3g characteristics suggested that negative vegetation changes (browning trends) dominated most of the landscape from winter to summer while positive (greening) trends dominated in autumn during the study period. Much of these changes were reflected in forest landscapes with a higher coefficient of variation (CV ≈ 15) than other vegetation types (CV ≈ 10). In addition, the pixel-wise correlation analyses indicated a positive (negative) relationship between the NDVI3g and the ERA5-Land precipitation in spring–autumn (winter) seasons, while the reverse was the case with other climatic variables across vegetation types. However, the relationships between the NDVI3g and the climatic variables were relatively low (R < 0.5) across vegetation types and seasons, the results somewhat suggest the potential role of atmospheric variations in vegetation changes in ADM. The findings of this study provide invaluable insights into potential consequences of climate change and the need for well-informed decisions that underpin the evaluation and management of regional vegetation and forest resources.