scholarly journals Spatio-temporal distribution pattern of potential natural vegetation and its response to climate change from Last Interglacial to future 2070s in China

2020 ◽  
Vol 35 (6) ◽  
pp. 1484
Author(s):  
REN Zheng-chao ◽  
ZHU Hua-zhong ◽  
SHI Hua ◽  
LIU Xiao-ni
Keyword(s):  
Climate Change ◽  
Distribution Pattern ◽  
Temporal Distribution ◽  
Natural Vegetation ◽  
Potential Natural Vegetation ◽  
Last Interglacial ◽  
Spatio Temporal

Potential natural vegetation dynamics driven by future long-term climate change and its hydrological impacts in the Hanjiang River basin, China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 73-90 ◽  
Author(s):  
Fei Yuan ◽  
Liliang Ren ◽  
Zhongbo Yu ◽  
Yonghua Zhu ◽  
Jing Xu ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
21St Century ◽  
Land Surface ◽  
Natural Vegetation ◽  
Potential Natural Vegetation ◽  
Area Index ◽  
Hanjiang River ◽  
Ipcc Sres

Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via the Lund-Potsdam-Jena dynamic global vegetation model. Subsequently, predicted PFTs and LAIs were employed in the Xinanjiang vegetation-hydrology model for rainfall–runoff simulations. Results reveal that future long-term changes in precipitation, air temperature and atmospheric CO2 concentration would remarkably affect the spatiotemporal distribution of PFTs and LAIs. These climate-driven vegetation changes would further influence regional water balance. With the decrease in forest cover in the 21st century, plant transpiration and evaporative loss of intercepted canopy water will tend to fall while soil evaporation may rise considerably. As a result, total evapotranspiration may increase moderately with a slight increase in annual runoff depth. This indicates that, for long-term hydrological prediction, climate-induced changes in terrestrial vegetation cannot be neglected as the terrestrial biosphere plays an important role in land-surface hydrological responses.

Spatio-temporal distribution pattern of the picocyanobacterium Synechococcus in lakes of different trophic states: a comparison of flow cytometry and sequencing approaches

Hydrobiologia ◽  
2017 ◽  
Vol 811 (1) ◽  
pp. 77-92 ◽  
Author(s):  
Joachim Ruber ◽  
Juergen Geist ◽  
Manuela Hartmann ◽  
Andrew Millard ◽  
Uta Raeder ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Distribution Pattern ◽  
Temporal Distribution ◽  
Spatio Temporal

Spatio-temporal distribution pattern of Calanus sinicus and its relationship with climate variability in the northern Yellow Sea

2017 ◽  
Vol 75 (2) ◽  
pp. 764-772
Author(s):  
Qing Yang ◽  
Hui Liu ◽  
Guize Liu ◽  
Yanbin Gu
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Yellow Sea ◽  
Cold Water ◽  
Temporal Distribution ◽  
Zooplankton Community ◽  
Central Portion ◽  
Calanus Sinicus ◽  
Northern Yellow Sea ◽  
Spatio Temporal

Abstract The spatio-temporal distribution pattern of Calanus sinicus, a key copepod species, was examined in the northern Yellow Sea (YS). Compared with 1959 and 1982, there was a significant increase in the abundance of C. sinicus in the spring, summer, and autumn of 2011 and winter of 2014. The percentage of C. sinicus in the zooplankton assemblages ranging from 45.6 to 75.8% in different seasons of 2011-2014 was significantly higher than that in 1982. Two different spatial distribution patterns of C. sinicus were observed, with higher abundance occurring nearshore during the cold season (e.g. January) and offshore in the central portion of the northern YS in the warm season (e.g. May, July, and October). The YS Cold Water Mass in the central portion of the northern YS likely provides an important over-summering site for the species. Additionally, a greater increase of the abundance of C. sinicus was found in the northern portion (the northern YS) of its spatial distribution during the past half century. This study has an implication on the climate-driven shifts in zooplankton community in the northern YS, highlighting the importance of C. sinicus in the warm-temperate ecosystem of Chinese coastal seas.

scholarly journals Spatio-temporal Distribution Pattern of Oyster Larvae in Guaratuba Bay, Paraná State - Brazil

2021 ◽  
Vol 64 ◽  
Author(s):  
Susete Wambier Christo ◽  
Augusto Luiz Ferreira Júnior ◽  
Theresinha Monteiro Absher ◽  
Andrea Cancela da Cruz Kaled
Keyword(s):  
Distribution Pattern ◽  
Temporal Distribution ◽  
Spatio Temporal

Snow Cover Dynamics and its Spatio-Temporal Distribution in the Central Higher Himalaya of India

2021 ◽  
Vol 14 (9) ◽  
pp. 15-22
Author(s):  
Masoom Reza ◽  
Ramesh Chandra Joshi
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Geographical Area ◽  
Temporal Distribution ◽  
Melting Rate ◽  
Optical Data ◽  
Snow Cover Area ◽  
Central Himalayas ◽  
Spatio Temporal ◽  
The Impact

Retreating glaciers, changing timber line and decreasing accumulation of snow in the Himalaya are considered the indicators of climate change. In this study, an attempt is made to observe the snow cover change in the higher reaches of the Central Himalayas. Investigation of climate change through snow cover is very important to understand the impact and adaptation in an area. Landsat thematic and multi spectral optical data with a spatial resolution of 60m and 30m are considered for the estimation and extraction of snow cover. Total 3,369 Km2 snow cover area is lost since 1972 out of total geographical area i.e. 17,227 Km2. The accumulation of snow during winter is lower than the melting rate during summer. The current study identified the decrease of 19.6 % snow cover in 47 years since 1972 to 2019. Composite satellite imageries of September to December show that the major part of the study area covered with snow lies above 3600m. Overall observation indicates that in 47 years, permanent snow cover is decreasing in Central Himalayas.

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