Documentary Evidence of 17th Century Landcover and Climate Change in Northern China and Mongolia Compared to Modern Spectral Greening Trends

Fighting land degradation of semi-arid and climate-sensitive grasslands are among the most urgent tasks of current eco-political agenda. Particularly, northern China and Mongolia are prone to climate-induced surface transformations, which were reinforced by the heavily increased numbers of livestock during the 20th century. Extensive overgrazing and resource exploitation amplified regional climate change effects and triggered intensified land degradation that forced policy-driven interventions to prevent desertification. In the past, however, the regions have been subject to continuous shifts in environmental and socio-cultural and political conditions, which makes it particularly difficult to distinguish into regional anthropogenic impact and global climate change effects. This article presents analyses of historical written sources, palaeoenvironmental data, and Normalized Difference Vegetation Index (NDVI) temporal series from the Moderate Resolution Imaging Spectroradiometer (MODIS) to compare landcover change during the Little Ice Age (LIA) and current spectral greening trends over the period 2001–2020. Results show that decreasing precipitation and temperature records triggered increased land degradation during the late 17th century in the transition zone from northern China and Inner Mongolia Autonomous Region to Mongolia. From current climate change perspectives, modern vegetation shows enhanced physical vegetation response related to an increase in precipitation (Ptotal) and temperature (T). Vegetation response is strongly related to Ptotal and T and an increase in physical plant condition indicates local to regional grassland recovery compared to the past 20-year average.

Seasonal Vegetation Response to Climate Variability on Land use Land Cover Changes using In-Situ and Satellite Imagery Observation Data for Semi-Arid Maasai Mara National Reserve Rangeland Ecosystem, Kenya

Monitoring vegetation response through enhanced change detection by remote sensing and geographical information systems has tremendously improved real time information on surface features. Over the last few decades biomass monitoring at large scale has been made possible from information and metrics derived from satellite sensors. Maasai Mara National Reserve has been utilized in many decades as Kenyan natural grassland for wildlife grazing without periodic assessment of biomass production as affected by impact of climate variability yet it’s a tourism hub and one Kenyan economic contributor. This research evaluates the use of high spatial resolution satellite imagery such as the Moderate Resolution Imaging Spectro-radiometer or the Project for On-Board Autonomy–Vegetation and latest SENTINEL-2 for deriving the Normalized Difference Vegetation Index values in relations to in-situ measurements of biomass production between 2009 and 2019 in Mara, Kenya. Area frame sampling of biomass per unit area in Kgha-1clipped from 50cm by 50cm quadrats were used in destructive sampling. The reserve grassland area coverage was estimated to be 717.203km2 (46.75%) where the in-situ total above ground grass biomass projected in dry season was 35.094 tonha-1. This was approximated as 2,516,952.208 tonnes per the season reserve cover while in wet season, 42.123 tonha-1 was approximated as 3,021,074.197 tonnes. The error matrices developed to assess the accuracies of the ecosystem classification indicated values that ranged between 80-100% and 87.5-100% for producer’s and user’s accuracy respectively. 3 out of 7 satellite imagery maps (2017, 2018, and 2019) were assessed for accuracy using reference data collected during fieldwork in 2018 and 2019 in ecosystem. The overall accuracy was 95.22% with Kappa index of 0.94 for 14 land cover classes shown in table 7. From the findings, potential factors influencing vegetation growth in different climatic regions are varied and complex. It can be noted that climate variability influence vegetation response in spatial scale to supply sustainable quality vegetation/pasture for wildlife feeds and ecosystem development. Vegetation mapping and monitoring of ecosystem behavior help stakeholders with information of vegetation characteristics Decision policy formulation and wildlife planning.

Vegetation Response to Holocene Climate Change in the Qinling Mountains in the Temperate–Subtropical Transition Zone of Central–East China

Global warming is having a profound influence on vegetation and biodiversity patterns, especially in alpine areas and high latitudes. The Qinling Mountain range is located in the transition zone between the temperate and subtropical ecosystems of central–east China and thus the vegetation of the area is diverse. Understanding the long-term interactions between plant diversity and climate change can potentially provide a reference for future landscape management and biodiversity conservation strategies in the Qinling Mountains region. Here, we use a pollen record from the Holocene sediments of Daye Lake, on Mount Taibai in the Qingling Mountains, to study regional vegetation changes based on biomes reconstruction and diversity analysis. Temperature and precipitation records from sites close to Daye Lake are used to provide environmental background to help determine the vegetation response to climate change. The results indicate that climate change was the main factor influencing vegetation and palynological diversity in the Qinling Mountains during the Holocene. The cold and dry climate at the beginning of the early Holocene (11,700–10,700 cal yr BP) resulted in a low abundance and uneven distribution of regional vegetation types, with the dominance of coniferous forest. During the early Holocene (10,700–7,000 cal yr BP), temperate deciduous broadleaf forest expanded, palynological diversity and evenness increased, indicating that the warm and humid climate promoted vegetation growth. In the middle Holocene (7,000–3,000 cal yr BP), the climate became slightly drier but a relatively warm environment supported the continued increase in palynological diversity. After ∼3,000 cal yr BP, palynological diversity and the evenness index commenced a decreasing trend, in agreement with the decreased temperature and precipitation in the Qinling Mountains. It’s noteworthy that human activity at this time had a potential influence on the vegetation. During the past few centuries, however, palynological diversity has increased along with the global temperature, and therefore it is possible that in the short-term ongoing climatic warming will promote vegetation development and palynological diversity in the area without human interference.