Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 26 von 198

Details

Autor(en) / Beteiligte
Titel
Spatial patterns and environmental factors influencing leaf carbon content in the forests and shrublands of China
Ist Teil von
  • Journal of geographical sciences, 2018-06, Vol.28 (6), p.791-801
Ort / Verlag
Heidelberg: Science Press
Erscheinungsjahr
2018
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Leaf carbon content (LCC) is widely used as an important parameter in estimating ecosystem carbon (C) storage, as well as for investigating the adaptation strategies of vegetation to their environment at a large scale. In this study, we used a dataset collected from forests (5119 plots) and shrublands (2564 plots) in China, 2011–2015. The plots were sampled following a consistent protocol, and we used the data to explore the spatial patterns of LCC at three scales: plot scale, eco-region scale (n = 24), and eco-region scale (n = 8). The average LCC of forests and shrublands combined was 45.3%, with the LCC of forests (45.5%) being slightly higher than that of shrublands (44.9%). Forest LCC ranged from 40.2% to 51.2% throughout the 24 eco-regions, while that of shrublands ranged from 35% to 50.1%. Forest LCC decreased with increasing latitude and longitude, whereas shrubland LCC decreased with increasing latitude, but increased with increasing longitude. The LCC increased, to some extent, with increasing temperature and precipitation. These results demonstrate the spatial patterns of LCC in the forests and shrublands at different scales based on field-measured data, providing a reference (or standard) for estimating carbon storage in vegetation at a regional scale.
Sprache
Englisch
Identifikatoren
ISSN: 1009-637X
eISSN: 1861-9568
DOI: 10.1007/s11442-018-1505-x
Titel-ID: cdi_proquest_journals_2918625938

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX