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