The Journal of Agricultural Science · 2020 · 22 citations · 69 references
Life SciencesEcologyPlant BiologyEcosystem EcologyPlant EcologyTerrestrial EcologyCarbon BalanceCarbon CycleGrassland EcologyLegume-grass InteractionsNet Ecosystem ExchangePlant Functional EcologyClimate-vegetation InteractionsGrassland Carbon ExchangePhenologyPlant Functional Type DifferencesSeasonal ScaleSubalpine ZoneVegetation Community StructureVegetation-climate Interactions
Abstract Understanding the mechanisms underlying net ecosystem CO 2 exchange (NEE) in mountain grasslands is important to quantify their relevance in the global carbon budget. However, complex interactions between environmental variables and vegetation on NEE remain unclear; and there is a lack of empirical data, especially from the high elevations and the Mediterranean region. A chamber-based survey of CO 2 exchange measurements was carried out in two climatically contrasted grasslands (montane v . subalpine) of the Pyrenees; assessing the relative contribution of phenology and environmental variables on CO 2 exchange at the seasonal scale, and the influence of plant functional type dominance (grasses, forbs and legumes) on the NEE light response. Results show that phenology plays a crucial role as a CO 2 exchange driver, suggesting a differential behaviour of the vegetation community depending on the environment. The subalpine grassland had a more delayed phenology compared to the montane, being more temperature than water constrained. However, temperature increased net CO 2 uptake at a higher rate in the subalpine than in the montane grassland. During the peak biomass, productivity (+74%) and net CO 2 uptake (NEE +48%) were higher in the subalpine grassland than in the montane grassland. The delayed phenology at the subalpine grassland reduced vegetation's sensitivity to summer dryness, and CO 2 exchange fluxes were less constrained by low soil water content. The NEE light response suggested that legume dominated plots had higher net CO 2 uptake per unit of biomass than grasses. Detailed information on phenology and vegetation composition is essential to understand elevation and climatic differences in CO 2 exchange.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
nlme : Linear and nonlinear mixed effects models
Saikat DebRoy · Medical Entomology and Zoology · 2006 · 10.2K citations
Mixed-Effects Models in S and S-PLUS
Technometrics · 2001 · 9.4K citations · Full text
EFFECTS OF BIODIVERSITY ON ECOSYSTEM FUNCTIONING: A CONSENSUS OF CURRENT KNOWLEDGE
David U. Hooper, F. Stuart Chapin, John J. Ewel et al. · Ecological Monographs · 2005 · 7.9K citations · Full text
Life Sciences, Biology, Ecology +12