spatial variability in soil community composition
has been simultaneously analysed.
The composition of the soil community varies
more over time in the litter horizon (L) than in the
underlying fragmented litter (F) and humus hori-
zons (H) (BCL¼0.560.057, BCF¼0.670.030,
BCH¼0.680.032). The observed higher average
variability in litter is caused by a significant de-
crease in similarity between samples when the
time interval between sampling increases (decrease
in BCLfrom 0.73 to 0.39 over 2.5 years). Only the
litter horizon shows a significant increase in varia-
bility over time. This difference in compositional
variability between horizons corresponds with the
mass loss of organic matter after 2.5 years, which is
significantly higher in litter (mass loss L¼44.2% of
initial mass, versus 4.2% and 2.8% for F and H,
respectively). Moreover, mass loss in litter is corre-
lated with change in chemical properties of litter,
especially C:N ratios (Berget al. 1998b). This strong-
ly suggests that increase in compositional variabil-
ity in litter over time is linked to changes in the
quantity and/or quality of organic matter. Organic
matter turnover is mentioned as one of the most
important parts of environmental variability in for-
ests (Bengtsson 1994).
Within-year variability in community composi-
tion is larger than between-year variability in com-
munity composition, but only in litter. Samples
taken a year apart have significant lower commu-
nity variability than samples obtained with half-
year intervals. This confirms the findings of Bengts-
son and Berg (2005), who showed for a managed
pine forest and a virgin spruce forest that within-
year variability in the composition of animal
functional groups can be as large as between-year
variability. The seasonal periodic oscillation in
community variability coincides with a similar
seasonal pattern in soil temperature and moisture
values (Berg and Verhoef 1998). The annual ampli-
tudes of soil temperature and water content are
greater in litter than in underlying horizons.
Owing to their short generation times many soil
organisms can react relatively fast to short-term
changes in the environment. This can be of the
order of some days for organisms at the base of
the food web to several months for animals at the
top of the food web (Huntet al. 1987). The high
within-year variability in the litter community com-
pared with deeper horizons can be explained by its
higher resource quality. However, within-year
variability in community composition is not easily
explained by changes in organic matter quality,
although input of detritus onto soil shows a season-
al pattern too. In an additional set of litterbags,
filled with freshly fallen litter and replaced in the
field every 8 weeks to obtain a constant litter quality
over time, similar temporal trends in community1.6–3.8 cm8 weeksT = 1T = 2T = 3N = 6T = 151.5–45 m
L
F
HFigure 6.2Stratified litterbag sets to measure organic
matter and functional group dynamics over time and
across space. The litterbags in a set, sized 1010 cm
each, were filled with homogenized pine litter (L; mesh
size 3 mm), fragmented pine litter (F; mesh size 1.3 mm)
or pine humus (H; mesh size 1 mm on top, 0.2 mm at
bottom) and were 1.0 cm, 2.2 cm and 2.2 cm thick,
respectively. Each litterbag set was 5.4 cm thick and
reflected the thickness and detrital composition of the
local organic soil horizon in which the sets were
introduced. The 180 litterbag sets (12 sets, 15 samplings),
each consisting of three litterbags filled with the three
successive horizons, were placed randomly within a (40
50 m) area, and sampled at 8 week intervals over a period
of 2.5 years. The distance between litterbag sets ranged
between 1.5 m and 45 m. On each sampling occasion six
litterbag sets were used to extract soil meso- and
macrofauna and to analyse mass loss and chemical
composition of organic matter. The remaining six sets
were used to extract the microflora and microfauna. See
Berg and Bengtsson (2007) for details about extraction
methods of soil organism and biomass calculation
procedures.
SPATIO-TEMPORAL STRUCTURE 73