Ce diaporama a bien été signalé.
Le téléchargement de votre SlideShare est en cours. ×

Belowground c allocation estimated as soil respiration minus aboveground litter inputs sarah abbott

Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Prochain SlideShare
Rotation and Time ditto
Rotation and Time ditto
Chargement dans…3
×

Consultez-les par la suite

1 sur 6 Publicité

Plus De Contenu Connexe

Plus par melnhe (20)

Plus récents (20)

Publicité

Belowground c allocation estimated as soil respiration minus aboveground litter inputs sarah abbott

  1. 1. Belowground C Allocation Estimated as Soil Respiration Minus Aboveground Litter Inputs Sarah Abbott with Tim Fahey, Ruth Yanai, Alex Young, and Shiyi Li
  2. 2. (Raich & Nadelhoffer, 1989) Introduction: Belowground Carbon Allocation Litter Respiration Belowground Carbon Allocation Belowground Carbon Allocation Respiration - Litterfall = Assumption: Steady State
  3. 3. Methods Li-Cor: Measures Soil Flux Litter Baskets 7 respiration collars per plot 13 stands 5 litter baskets per plot 13 stands
  4. 4. Nitrogen Depresses Soil Respiration Average Soil Respiration (‘15, ’16, ‘17, ‘18) .
  5. 5. Average Litterfall (‘15, ’16, ‘17). Phosphorus Depresses Leaf Litter Production
  6. 6. Calculating belowground C allocation requires putting both of these in the same units and estimating year-round soil respiration--stay tuned! RESULTS N decreases soil respiration (and likely belowground C allocation) P decreases leaf production (does this relate to greater diameter growth?) Can we conclude that P matters more aboveground and N matters more belowground?

Notes de l'éditeur

  • What goes down must come up. Litterfall must get respired, in the long run,

  • ** No Detectable Difference

    Hypothesis:

    H0: μC = μN = μNP =μP

    H1: at least one of means is different

    F: 1.73
    Fcrit: 2.81

    Reject hypothesis

    P value: 0.17
  • ** No Detectable Difference

    Hypothesis:

    H0: μC = μN = μNP =μP

    H1: at least one of means is different

    F: 1.96
    Fcrit: 2.81

    Reject hypothesis

    P value: 0.13


    Here we perform Analysis of Variance (ANOVA) to test whether the means of the treatment types are equal. The one-way analysis of variance is used to determine whether there are any statistically significant differences between the means of three or more independent groups. It’s odd that the technique is called "Analysis of Variance" rather than "Analysis of Means." but appropriate because inferences about means are made by analyzing variance.

    The X is the mean
    Bar is median
    Box is interquartile range (middle 50%)
    Whiskers are extrema

    ANOVA and Box whisker plots suggest that N and N+P may

×