Diversifying crop rotations with temporary grasslands - Université de ...

12 H. Meiss et al. / Agriculture, Ecosystems and Environment 138 (2010) 10–16
ferent weed species that are known to vary in their attractiveness
to seed predators (Alignier et al., 2008) and selective exclusion
treatments to separate seed losses caused by invertebrates and
vertebrates.
2. Material and methods
The study was located at the INRA experimental farm “Epoisses”
near Dijon in eastern France (47 ◦ 20 ′ N, 05 ◦ 02 ′ E, 230 m a.s.l.). Seed
predation trials were conducted on plots of an ongoing cropping
system experiment established in 2006. Five treatments were compared
including two perennial forage crop species: Medicago sativa
L. (alfalfa) and Dactylis glomerata L. (cocksfoot) that both received
two contrasting cuttings (forage mowing, see below), and bare soil
plots (no crop sown in 2008 but 5 cm superficial soil tillage to
remove weed plants prior to the first and third trial periods, see
Fig. 1). These five treatments were chosen (i) to create a gradient
of vegetation cover and (ii) to test the impacts of, and interactions
between, the factors crop species (legume vs. grass) and cutting (cut
vs. uncut). Each treatment was replicated four times in a randomized
complete block design. Plot size was 75 m 2 (7.5 m × 10 m) for
all perennial crops and 35 m 2 (3.5 m × 10 m) for bare soil plots. All
plots were arranged in an experimental field of about 0.75 ha which
should reduce spatial heterogeneities in soil characteristics, crop
succession histories and predator abundances, as the plot size was
smaller than the foraging range of many seed predators (Menalled
et al., 2006). Trials lasted for two weeks and were repeated three
times (trials 1–3, Fig. 1).
2.1. Vegetation cover
Vegetation cover was estimated halfway through each trial
period by measuring the photosynthetically active radiation on
sunny days twice above (PARa) and three times below the canopy
close to the soil surface (PAR b) around the locations of the seed
cards, using a Sunscan Canopy Analysis System SS1-UM-1.05
(Delta-T Devices Limited) with 64 light sensors on a 1-m stick. All
measurements taken in the same plot at one period were averaged
and a ‘light transmittance rate’ was calculated using the formula:
PAR b/PARa (Heggenstaller et al., 2006). The complement of light
transmittance to 1, ‘light interception rate’, was used as an indicator
of vegetation cover.
2.2. Weed seed predation
Weed seed predation rates were measured using “seed cards”
(Westerman et al., 2003b). Three common annual weed species,
Alopecurus myosuroides Huds., Sinapis arvensis L. and Viola arvensis
Murray were tested at each trial, giving a total of 540 seed
cards (three weed species × three exclusion treatments × five treatments
× four replicate blocks × three trials). Twenty-five seeds per
species were lightly glued to textile sandpaper cards (5 cm × 10 cm,
grain size 100) using a spray adhesive (Sader, Bostik SA, Paris,
France). This technique prevented seed losses caused by wind or
rain, while most seed predators should still be able to remove the
seeds (Westerman et al., 2003b). Nails (10 cm) were used to fix
the cards horizontally on the soil surface. After exposure periods
of 14 days, seed cards were removed and remaining seeds were
immediately counted in the field.
Two different methods were used in each treatment to estimate
the amount of accidental seed losses. (A) One third of seed cards was
put into total exclusion cages (24 cm × 12 cm × 3 cm boxes made
from metal wire gauze with 1 mm × 1 mm mesh size) which were
permeable to wind and rain but would exclude any type of seed
predator. (B) Plastic beads were presented instead of weed seeds.
Results obtained with both control methods indicated that accidental
seed losses were always marginal (A: 0–2% in 1-mm cages,
B: 0–4% for plastic beads). It was thus not necessary to correct the
measured seed predation rates for accidental losses.
To separate seed losses caused by different predator guilds,
one third of seed cards were put into vertebrate exclusion cages
(24 cm × 14 cm × 4 cm boxes made from metal fence wire with
12 mm × 12 mm mesh size), excluding all predators >12 mm, thus
(at least) all birds and mammals. The seed loss rates on open
(uncaged) seed cards were designated ‘Total seed predation’, seed
loss rates in the 12-mm cages ‘Invertebrate seed predation’; ‘Vertebrate
seed predation’ was calculated by subtracting ‘Invertebrate
seed predation’ from ‘Total seed predation’.
2.3. Statistical analysis
The response variable ‘seed predation rate’ was arcsin (squareroot(y))-transformed
to satisfy assumptions of normality and
homogeneity of error variances. The explanatory variable ‘light
transmittance’ was log 10(x + 1)-transformed, which increased the
linearity of the models. Figures show untransformed data.
2.3.1. Overall variability
A three-way ANOVA model was fitted to analyze the impacts of
‘trial period’ (three levels), ‘predator guild’ (two levels), and ‘weed
species’ (three levels).
2.3.2. Vegetation cover
The impact of vegetation cover was first analyzed by fitting
ANCOVA models for Total, Vertebrate, and Invertebrate seed predation,
containing the continuous variable ‘light interception’, and
the two factors ‘trial period’ and ‘weed species’. Owing to significant
interactions, the impact of vegetation cover was also investigated
for all weed species and trial periods separately using correlation
analysis.
2.3.3. Treatment
To analyze the impact of ‘treatment’, ANOVA models were fitted
that integrated the same variables as the ANCOVA models cited
above, except that the continuous variable ‘light interception’ was
replaced by the categorical variable ‘treatment’. Owing to significant
interactions, the impact of treatment was also analyzed for all
trial periods and weed species separately using one-way ANOVA
models.
2.3.4. Crop species vs. cutting
The relative importance of, and possible interaction between,
the factors crop species and cutting were analyzed by fitting ANOVA
models with three factors: ‘crop species’ (Medicago–Dactylis), ‘cutting’
(cut–uncut), and ‘trial period’ (May–July). The April data were
excluded due to the lack of cut plots at this period.
2.3.5. Vegetation cover as a predictor
To analyze whether the differences between the treatments
might also be explained by vegetation cover (two ‘competing’
variables), a ‘variance partitioning’ approach was used that can
integrate continuous and categorical variables. It was simply based
on several sequential ANOVA models with Type-I sums-of-squares
(Type-I SOS) to calculate both the ‘total’ and ‘exclusive’ variances
(Mac Nally, 2000) explained by each variable, using R (R
Development Core Team, 2008). The common additive variance
that may be explained both by ‘treatments’ and ‘vegetation cover’
(‘joint’ variance, Mac Nally, 2000) was obtained by subtracting
the two exclusive variances from the total variance explained by
both factors. Finally, the percentage of the variability among the
treatments that may equally be explained by vegetation cover