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Autor(en) / Beteiligte
Titel
Biomass partitioning in grassland plants along independent gradients in temperature and precipitation
Ist Teil von
  • Perspectives in plant ecology, evolution and systematics, 2016-04, Vol.19, p.1-11
Ort / Verlag
Elsevier GmbH
Erscheinungsjahr
2016
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • •Allometric scaling of roots, stems, leaves and flowers is stable across climate gradients.•Allocation to plant parts varies with climate as predicted by optimal allocation theory.•Allocation is clearly related to habitat affinity and reproductive state. How plants allocate biomass to different parts strongly affects vegetation dynamics and ecosystem processes and services such as productivity and carbon storage. We tested the hypothesis that plant size explains the majority of variation in the size of plant parts (as predicted by allometric partitioning theory, APT) and that additional variation is explained by optimal responses for a given individual reproductive state and environment (as predicted by optimal partitioning theory, OPT) for alpine-lowland species pairs from three genera of grassland plants (Veronica, Viola and Carex) sampled along orthogonal gradients in temperature and precipitation. We found general patterns of allometric scaling (allometric exponents) of roots, stems, leaves and flowers, more or less as predicted by APT, and these patterns remained fairly constant across temperature and precipitation gradients. In contrast, basic allocation (allometric coefficients) was clearly related to climate, such as less allocation to leaves but more to roots, stems and flowers with increasing temperatures, in accordance with OPT. Furthermore, our results show that basic allocation is related to habitat affinity (alpine, lowland) and individual life-history states (reproductive or not) and that there is greater variability in small plants, which suggests that biomass partitioning theory should consider both the life-history and ecology of small plants to accurately predict climate-related grassland plant allocation and its implications.
Sprache
Englisch
Identifikatoren
ISSN: 1433-8319, 1618-0437
eISSN: 1618-0437
DOI: 10.1016/j.ppees.2016.01.006
Titel-ID: cdi_swepub_primary_oai_DiVA_org_su_135075

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