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Impacts of willow and miscanthus bioenergy buffers on
biogeochemical N removal processes along the soil–
groundwater continuum
ANDREA FERRARINI
1
,FLAVIO FORNASIER
2
, PAOLO SERRA
1
, FEDERICO FERRARI
3
,
MARCO TREVISAN
4
and STEFANO AMADUCCI
1
1
Department of Sustainable Crop Production, Universit
a Cattolica del Sacro Cuore, via Emilia Parmense 84, Piacenza 29122,
Italy,
2
Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Via Trieste 23, 34170 Gorizia, Italy,
3
Aeiforia
srl, Via Gramsci 22, 43036 Fidenza, Italy,
4
Institute of Agricultural and Environmental Chemistry, Universit
a Cattolica del
Sacro Cuore, via Emilia Parmense 84, Piacenza, 29122, Italy
Abstract
In this article, the belowground and aboveground biomass production in bioenergy buffers and biogeochemical
N removal processes along the soil–groundwater continuum was assessed. In a sandy loam soil with shallow
groundwater, bioenergy buffers of miscanthus and willow (5 and 10 m wide) were planted along a ditch of an
agricultural field (AF) located in the Po valley (Italy). Mineral N forms and dissolved organic C (DOC) were
monitored monthly over an 18-month period in groundwater before and after the bioenergy buffers. Soil sam-
ples were measured for inorganic N, DOC, microbial biomass C (MBC) and N (MBN), and potential nitrate
reductase activity (NRA). The results indicated that bioenergy buffers are able to efficiently remove from
groundwater the incoming NO
3
-N (62% –5 m and 80% –10 m). NO
3
-N removal rate was higher when nitrate
input from AF increased due to N fertilization. Willow performed better than miscanthus in terms of biomass
production (17 Mg DM ha
1
yr
1
), fine root biomass (5.3 Mg ha
1
) and N removal via harvesting
(73 kg N ha
1
). The negative nonlinear relationship found between NO
3
-N and DOC along the soil–groundwa-
ter continuum from AF to bioenergy buffers indicates that DOC:NO
3
-N ratio is an important controlling factor
for promoting denitrification in bioenergy buffers. Bioenergy buffers promoted soil microbial functioning as they
stimulated plant–microbial linkages by increasing the easily available C sources for microorganisms (as DOC).
First, willow and miscanthus promoted high rates of biological removal of nitrate (NRA) along the soil profile.
Second, rhizosphere processes activated the soil microbial community leading to significant increases in MBC
and microbial N immobilization. Herbaceous and woody bioenergy crops have been confirmed as providing
good environmental performances when cultivated as bioenergy buffers by mitigating the disservices of agricul-
tural activities such as groundwater N pollution.
Keywords: bioenergy buffers, biomass production, dissolved organic C, ecological stoichiometry, fine root biomass, groundwa-
ter quality, miscanthus, nitrate removal, soil microbial biomass, willow
Received 15 October 2015; accepted 1 December 2015
Introduction
In the last decade, it has become increasingly important
to identify which proportion of the landscape should be
occupied by bioenergy cropping systems (Gelfand et al.,
2013; Manning et al., 2015). The key question is which
land-use strategy can be implemented to avoid land-use
conflicts while maximizing yields and ecosystem ser-
vices provision (Fritsche et al., 2010; Payne, 2010; Dale
et al., 2011; Popp et al., 2011; Anderson-Teixeira et al.,
2012). To solve the so called ‘food, energy and environ-
ment trilemma’ (Tilman et al., 2009), several scenarios in
which food and bioenergy cropping systems are spa-
tially mixed within farmlands have been recently pro-
posed (Asbjornsen et al., 2012; Gopalakrishnan et al.,
2012; Christen & Dalgaard, 2013; Manning et al., 2015).
Positive impacts on the regulation of climate, water
and biodiversity ecosystem services have been reviewed
during the transition of cropland to the production of
bioenergy feedstock with perennial herbaceous and
woody crops (Holland et al., 2015; Milner et al., 2015).
The application of spatial multicriteria analysis revealed
that a careful allocation of perennial cropping systems
into the landscape would foster multiple ecosystem
services and mitigate ecosystem disservices from
Correspondence: Andrea Ferrarini, tel. +390523 599223, fax +390523
5992222, e-mail: andrea.ferrarini@unicatt.it
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License,
which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 1
GCB Bioenergy (2016), doi: 10.1111/gcbb.12340
current annual food cropping systems (Powers et al.,
2011; Parish et al., 2012; Meehan et al., 2013). Neverthe-
less, it emerged that the links of bioenergy crops with
the provision of ecosystem services are strictly depen-
dent on the spatial allocation of the crops relative to the
adjacent land uses as revealed for pest regulation and
pollination (Meehan et al., 2012; Werling et al., 2013;
Bourke et al., 2014) and for water quality regulation
(Meehan et al., 2013).
Within this framework, an excellent case study area
in which to explore the possibility to optimize land use
for food, energy and ecosystem services is the agricul-
tural landscape of Po valley (northern Italy). In the last
decades, this area experienced an intensification of the
conventional farming systems with the result that sev-
eral areas suffer from problems of nitrate contamination
of surface and groundwater (Capri et al., 2009). At the
EU level, buffer strips have become a widely adopted
measure to mitigate such problems of nonpoint source
agricultural pollution. The efficiency in removing NO
3
-
N from groundwater is widely reported in the literature
for riparian areas (Sabater et al., 2003; Hickey & Doran,
2004; Mayer et al., 2007) and for filter strips (van Beek
et al., 2007; Zhou et al., 2010). For this reason, buffer
strips were made mandatory among member states in
order to fulfil the obligations to maintain and improve
Good Ecological Status under the EU Water Framework
Directive (EC 2000/60). In Italy, 5-m-wide buffer strips
are mandatory along watercourses where water quality
status is scarce or bad (Italian Ministerial Decree DM
27417 of 22 December 2011). Within the 2014–2020 Rural
Development Programmes (RDP) of the Emilia-
Romagna and Lombardy regions, in Italy, two volun-
tary measures that provide money to farmer to install
and maintain herbaceous buffers or woodland buffer
strips have been introduced. Nevertheless, some operat-
ing spaces are left by these RDP measures for including
bioenergy crops in buffer strips. For this reason, the
water quality issue seems to offer an opportunity to
redesign bioenergy landscapes with buffers for biomass
production.
In this manuscript, bioenergy buffers have been pro-
posed as an alternative land-use scenario for bioenergy
production within the intensively managed agricultural
landscape of the Po valley. Bioenergy buffers, in our
view, are perennial landscape elements consisting of lin-
ear narrow bands placed along watercourses and culti-
vated with perennial herbaceous or woody bioenergy
crops. Although extensive knowledge on the ecological
functioning of buffer strips with natural vegetation is
available for the case study area (Balestrini et al., 2008,
2011), several research questions on bioenergy buffers
relative to their productive performances still have to be
explored, as do their role in providing ecosystem
services and sustaining soil functioning (such as mitiga-
tion of groundwater N pollution and soil microbial C-
and N cycling). To date, the only literature available on
the effectiveness of bioenergy buffers in removing N is
modelling studies (Gopalakrishnan et al., 2012; Meehan
et al., 2013; Ssegane et al., 2015). Furthermore, there
have been no specific studies for bioenergy crops on the
role of dissolved organic C (DOC) and belowground
biomass as indicators for the activation of the soil
microbial community and its implications on N removal
processes from soil (e.g. denitrification and microbial N
immobilization). To be adopted under different climatic
and pedological conditions, there needs to more evi-
dence on the biogeochemical processes involved in N
removal in the plant–soil–groundwater system under
bioenergy buffers. Within the case study area, an experi-
mental field trial of bioenergy buffers with miscanthus
and willow was set up in a sandy loam soil with shal-
low groundwater. The main objectives of the experi-
ment were as follows: (i) to evaluate bioenergy buffers
effectiveness (BSE) in removing N from shallow
groundwater; (ii) to identify the main biogeochemical
processes and key factors governing N removal along
the soil–groundwater continuum; and (iii) to quantify
root fine biomass, biomass production and plant N
removal in bioenergy buffers.
Materials and methods
Site description and experimental design of bioenergy
buffers
The experiment was located in a typical farm in the north-west
of Italy (Fig. 1a) (45°3037.87″N, 9°47030.19″E altitude 43 m a.s.l.),
where the climate is continental with an average annual rainfall
of 980 mm and rainfall peaks in autumn and spring. The aver-
age temperatures during the experiment were 5.5, 15.5, 15,
24.4 °C, respectively, for winter, autumn, spring and summer.
The field was flat, rectangular and bordered at one side by a
ditch (Fig. 1b). It was 200 m wide with a 180 m long 2% slope
downward to a 3-m-wide ditch. The water level in the ditch
fluctuated from 0.2 to 0.9 m below soil surface (-bss). The field
was characterized by a deep sandy aquifer interrupted by a
silty clay aquitard (Fig. 1c). The local groundwater system
showed a prevalent SW-NE direction, and it was perpendicular
to the ditch. The agricultural field was cultivated following a
common crop rotation for the area: maize (2013), soybean
(2014) and tomato (2015). Maize was fertilized with KNO
3
(170 kg N ha
1
). Soybean was irrigated twice in June 2014 (to-
tal 60 mm of water) but not fertilized. In May 2015, there was a
preplanting fertilization (70, 110 and 170 kg ha
1
, respectively
for N, P and K), and after planting the tomatoes, there was a
biweekly fertirrigation from June to August (18 events; total
210 mm water and 50, 40 and 100 kg ha
1
, respectively, of N,
P and K). According to the USDA Soil Taxonomy (Soil Survey
Staff, 2014), the soil is Udifluventic Haplustept, the texture is
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
2A. FERRARINI et al.
sandy loam, and the content of soil organic C and total N is
low. The main soil physical and chemical characteristics of the
soil profile are reported in Table S1.
The bioenergy buffers were installed in April 2013, with two
buffer widths: the mandatory 5 m width (as requested by Ital-
ian Ministerial Decree DM 27417 of 22 December, 2011) and
10 m width. No pest management, irrigation and fertilization
were applied. Soil was ploughed at 30 cm depth before the
experiment started. The experiment was organized following a
randomized block design (RBD) with three replicates (Fig. 1b).
Bioenergy buffers consisted of miscanthus (Miscanthus x gigan-
teus L.) and willow (Salix matsudana Koidz (hybrid)). The plots
hosting the control treatment (hereinafter referred to as ‘spon-
taneous species’) were not planted to enable natural revegeta-
tion. The control treatment has been considered as an unsown
field margin strip (De Cauwer et al., 2005) Spontaneous species
recorded were (%) as follows: Echinochloa crus-galli (L.) Beauv.
(30%), Sorghum halepense (L.) Pers. (30%), Amaranthus retroflexus
L. (10%), Convolvulus arvensis L. (10%), Cynodon dactylon (L.)
Pers. (10%) and other species (10%). Willow bioenergy buffers
were planted by stem transplantation (up to 40 cm depth).
Plant density was 13.000 plants ha
1
(0.6 91.5 m spacing).
The failure of the transplants was nearly zero after establish-
ment. Miscanthus buffers were planted with rhizomes (0.1 m
depth) with a density of 4 rhizomes m
2
(0.36 90.7 m spacing).
Emergence rates for rhizomes in May 2013 ranged from 15 to
20% due to a severe waterlogging event. New rhizomes were
planted in June 2013 to reduce patchiness (in February 2015
patchiness reached values <5%).
Groundwater, soil, root and aboveground biomass
measurements
Before bioenergy buffer establishment, a whole soil profile was
opened to describe the soil horizons (Table S1) and a geological
survey was carried out in order to characterize the local aquifer
system. Some preliminary piezometers were installed at 2 and
5 m depth at random intervals to get information on ground-
water hydraulic head and the groundwater table dynamics.
This was carried out to spatially design the RBD experimental
design. After having fully characterized the aquifer, the experi-
mental site was equipped in May 2014 with piezometers
installed along a series of perpendicular transects from the
agricultural field to the ditch (Fig. 1b). Each of the transects
consisted of three sampling piezometers. Two piezometers
were installed within the agricultural field upgradient of each
group of experimental blocks, and one was installed immedi-
ately downgradient of each buffer plot to study the effects of
bioenergy buffers on groundwater N coming from the agricul-
tural field (AF). The PVC piezometers were installed at a depth
of 1.5–2 m. Piezometers were 2.5-m-long, 5-cm-diameter PVC
pipe and were screened at 1–2 m -bss. Piezometers were
Po river
Nitrates vulnerable zones (NVZ)
Depth [m]
0.5
1
2
3
Ditch
Sand loamy soil
Aquitard Groundwater table depth
Native species
Miscanthus
Willow
Piezometer
Groundwater direction
10 m
5 m
10 m
10 m
Ditch
Piezometer
Bioenergy buffers
Agricultural field
Growing season
Leaching season
(a)
(b)
(c)
Fig. 1 Localization of the field trial in NW Italy (a) and distribution of the nitrate-vulnerable zones (source: ISPRA –Institute for
Environmental Protection and Research), field experimental design for bioenergy buffers (b) and vertical-cross section of the field trial
representing the shallow groundwater system (c).
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
N REMOVAL BY BIOENERGY BUFFERS 3
installed by driving into the soil twice a steel corer with an
inner removable PVC pipe (5 cm diameter, 1 m long) using a
hydraulic jackhammer and extracted using a tripod ratchet.
The final piezometer was then manually inserted into the soil.
This procedure was also used to obtain soil samples.
Groundwater samples were collected from May 2014 until
August 2015 approximately with a monthly sampling
frequency during the 2014 and 2015 growing seasons.
Hereinafter, the monitoring season is divided as follows: 2014
growing season (T1: 30 May 2014, T2: 28 June 2014, T3: 1
August 2014, T4: 10 September 2014), 2014 leaching season
(T5: 18 December 2014, T6: 4 February 2015) and 2015 growing
season (T7: 24 April 2015, T8: 6 May 2015, T9: 2 June 2015,
T10: 15 July 2015 and T11: 1 August 2015). Groundwater table
depth was measured using a sounding probe during each
sampling event. Differences in groundwater table depth in
total heads along the piezometer transects were used to deter-
mine dominant flow paths of groundwater. Before sampling,
the wells were pumped empty and allowed to settle again.
Dissolved O
2
(ppm), groundwater total dissolved solids
(ppm), conductivity (lscm
1
), pH and water temperature (°C)
were measured within each piezometer by inserting a specific
multiparameter probe (HI 98196; Hanna Instruments, Padova,
Italy). Groundwater was sampled with a slow pumping tech-
nique, 0.5–1 L was collected from each piezometer, and sam-
ples were kept refrigerated during the transport to the
laboratory. Samples were then immediately filtered (0.45 lm
cellulose acetate) and kept at 4 °C until analysis. Samples
were analysed for NO
3
-N, NH
4
-N, NO
2
-N, TDN (Total Dis-
solved N), DOC (dissolved organic C), TDP (total dissolved
P), PO
4
-P and chlorides (Cl
-
). The sum of NO
3
-N, NH
4
-N and
NO
2
-N forms the dissolved inorganic N (DIN), and the differ-
ence between TDN and DIN is the dissolved organic N
(DON). NO
3
-N was analysed with dual wavelength UV spec-
troscopy (275, 220 nm) on acidified (HCL 1M) samples and
pipetted into 96-well quartz microplates. NH
4
-N, NO
2
-N and
PO
4
-P were measured through colorimetric reactions based on
a 96-well microplate format and read with a microplate reader
(Biotek Synergy 2, Winooski, VT, USA). NH
4
-N was measured
with Berthelot reaction (Rhine et al., 1998), NO
2
-N with Griess
reaction (Griess Reagent Kit G-7921; Molecular Probes Inc.,
Life Technologies, Monza, Italy) and PO
4
-P with the green
malachite method (D’Angelo et al., 2001). TDN and DOC were
measured using a TOC–TN analyser (TOC-VCSN Shimadzu).
TDP was measured by an inductively coupled plasma atomic
emission spectrometry. Chlorides were analysed by ion chro-
matography using a Dionex DX-120 equipped with an AS22A
column and Na
2
CO
3
+NaHCO
3
as eluent. Chlorides were used
as a conservative tracer in groundwater to separate between
dilution and N removal (Altman & Parizek, 1995). TDP and
PO
4
-P in most of the groundwater samples were lower than
the detection limit, and the data were therefore not included
in this manuscript. Buffer strip effectiveness (BSE) in remov-
ing N forms in shallow groundwater was calculated using the
formula:
Buffer strip effectiveness ðBSEÞi¼1Cigw;BUFFER
Cigw;avg;AF
100 ð1Þ
where iis the N
i
form for which BSE was calculated (NO
3
-N,
NH
4
-N, NO
2
-N, DIN, TDN and their respective i/Cl
-
ratios),
C
igw, BUFFER
is the concentration of the Ni form in groundwater
after buffer plots, and C
igw, avg, AGR
is the average concentration
of the Ni form in piezometers installed in the agricultural field
(AF).
Soil was sampled four times in 10-m-wide buffers with the
same procedure used for piezometer installation. There were
two soil samplings in the first growing season after buffer estab-
lishment (1 July 2013 and 10 February 2014), one at the end of
second (4 February 2015) and one in the third season (1 August
2015). At each sampling time, three soil cores were taken from
each plot to a depth of 60 cm. For miscanthus and willow four
soil, cores were taken in two different sampling positions: two
cores in the middle of the plant row and two in the inter-row
centre. Four random cores were taken from the spontaneous
species plots and from the agricultural field. Each soil core was
then divided into four sections (0–10, 10–20, 20–30 and 30–
60 cm depth). The divided soil cores from each plot were imme-
diately bulked in one composite sample in plastic bags accord-
ing to the respectively depth, stored at 18 °C and analysed
within a month. Soil samples were analysed for extractable
NO
3
-N, NO
2
-N, NH
4
-N, DOC, TDN, microbial biomass C
(MBC) and for the two microbial N removal processes in soils:
microbial N immobilization (MBN) and potential nitrate reduc-
tase activity (NAR), the latter as marker for denitrification.
Microbial biomass was determined by the fumigation–extrac-
tion technique in fresh soil (Vance et al., 1987). The unfumigated
soil extracts were used to measured DOC, TDN, extractable
NO
3
-N, NH
4
-N and NO
2
-N. As for groundwater samples, DIN
and DON were calculated. Extractable mineral N pools were
measured with the same microplate-based colorimetric methods
adopted for groundwater analysis. For the entire set of soil C
and N pools analysed, the values are reported on a stock basis
(kg ha
1
). Soil nitrate reductase activity (NRA) was measured
by soil anaerobic incubation following the modifications of the
protocol of Abdelmagid & Tabatabai (1987) introduced by
Ch
eneby et al. (2010). NRA were calculated as lgofNO
2
-N pro-
duced per g of dry soil per day (lgNO
2
-N g
soil1
day
1
). See
Supporting Information (Appendix S1) for a detailed descrip-
tion of the procedure adopted for NRA.
Soil cores for fine root biomass were collected during the
last soil sampling (1 August 2015). During this soil sampling,
three additionally soil cores were collected for fine root bio-
mass quantification. For miscanthus and willow, soil cores
were taken in three different sampling positions following the
scheme proposed by Zatta et al. (2014): one next to the plants,
one in the middle of the plant row and one in the inter-row
centre. From the spontaneous species plots, three cores were
taken randomly. All cores were divided into the same four
sections as for soil cores (0–10, 10–20, 20–30 and 30–60 cm
depth). Before root extraction, soil samples were stored at
18 °C. To extract fine roots (<2 mm), soil samples were
immersed in oxalic acid (2%) for 2 h and then washed in a
hydraulic sieving-centrifuge device (Chimento & Amaducci,
2015). Once cleaned, roots were recovered by hand picking
from the water using a 2-mm-mesh sieve, oven dried at 65 °C
for 48 h and weighed.
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
4A. FERRARINI et al.
Some samples of miscanthus included rhizomes, which were
not included in the root biomass sample. The dry root weight
was divided by the whole volume of soil samples and reported
as Mg of fine roots per hectare (Mg ha
1
). After weighing, the
three replicates were combined by depth for each plot and
ground to 1 mm. The samples were then analysed for N using
a CN analyzer (Vario Max CN Analyzer; Elementar Americas,
Inc., Hanau, Germany).
Harvestable biomass from bioenergy buffers was collected in
late winter periods every year for miscanthus (10 February
2014 and 15 February 2015) and at the end of 2nd growing sea-
son for willow (15 February 2015). Aboveground biomass sam-
ples were collected cutting each row of plants along a transect
in each plot. Each plant row was weighed in the field and a
subsample was taken for fresh weight to dry matter (DM) con-
version and CN analysis. Calculations for harvestable biomass
(Mg DM ha
1
) and N exportations by harvesting (kg N ha
1
)
were performed for each plot as a whole (by averaging the DM
values of all plant rows along the buffer transect) and on a
plant row basis (DM and kg N ha
1
plant row
1
).
Statistical analysis
All the data were analysed using the ‘nlme’ package (Pinheiro
et al., 2015) of RStudio 0.99.484. For groundwater data (concen-
tration and BSE), a mixed model of repeated-measures ANOVA
was used with crop type (CROP), buffer width (WIDTH) and
monitoring season (SEASON) as fixed effects, whereas
piezometers (PIEZ) and sampling times (TIME) were crossed
within the random effects structure of the model. Significance
of the fixed effects was assessed with Fand Pvalues. Model
residuals were checked for normality by the Kolmogorov–Smir-
nov test and for homogeneity of variances by the Levene’s test
for each of the fixed factors. The temporal autoregressive struc-
ture (based on moving average residual) was used as covari-
ance matrix within the mixed model. This structure obtained
the lowest Akaike’s information criteria (AIC) values than
those obtained for other structure tested (autoregressive tempo-
ral structure and block diagonal). Significant differences among
levels of the fixed factors were identified at the 0.05 probability
level of significance constructing specific contrast matrices
based on Tukey’s contrasts carried out using the multcomp
package of R software (Hothorn et al., 2015).
Similar mixed models of repeated ANOVA and post hoc analy-
sis were applied to soil variables. Crop type (CROP), soil
depths (DEPTH) and sampling seasons (SEASON) were used
as fixed effects, whereas experimental blocks (BLOCK) and
SEASON were defined as random effects. For belowground
measurements, only CROP and DEPTH as fixed effects were
studied, being root biomass sampled only once during the 2015
growing season. To assess differences in harvestable biomass
and N exportation, one-way ANOVA comparisons for RBD
designs were run, with CROP and BLOCK as fixed factors. For
these parameters, to assess their differences among plant rows
along buffer transect, one-way ANOVA comparisons were made
separately for miscanthus and willow buffers, with PLANT
ROW (n
rows
=13 for miscanthus, n
rows
=7 for willow) and
BLOCK as main factors. For all these one-way ANOVAs, means
were compared by the Tukey’s test (a=0.05), after confirma-
tion that data were normally distributed and variance was
homogeneous.
Additional regression analyses were then performed on soil,
root and groundwater data using nlme package of R software.
The relationship between the concentration (mg L
1
) of DOC
and NO
3
-N in groundwater samples and soil extracts was cal-
culated applying a nonlinear regression model (y=a+be
-k(x)
)
(Taylor & Townsend, 2010). The relationship between ground-
water nitrate input entering the buffers and buffer strips
effectiveness (BSE) in removing N was calculated by a power
function: y=ax
b
(Mayer et al., 2007). BSE (%) in removing
NO
3
-N was also plotted against buffer width. A nonlinear
regression model (y=ax
b
) was used here to obtain information
on the optimal buffer width necessary to obtain a given value
of BSE (50%, 75%, 90% and 100%).
Results
N concentration patterns in groundwater
The concentrations of NO
3
-N, NH
4
-N, DIN and TDN in
groundwater were significantly lower after the bioen-
ergy buffers by comparison with the concentration in
the agricultural field (AF) (Table 1). In particular,
groundwater nitrate had the highest reduction com-
pared to AF (F=77.1, P<0.0001). For TDN, the values
were F=40.1, P<0.0001. The only mineral N that
resulted slightly increased was NO
2
-N that after bioen-
ergy buffers increased up to 0.2 mg NO
2
-N L
1
.No
significant differences (F=1.9, P=0.55) were found in
Cl
-
concentration after bioenergy buffers suggesting that
no input of Cl
-
occurred in the local aquifer system and
thus no dilution effects were observed in groundwater
before and after bioenergy buffers (Table S2). Cl
-
/NO
3
-
N and Cl
-
/TDN ratios increased in groundwater after
bioenergy buffers (data not shown), indicating that for
the entire period of monitoring, all N forms were effec-
tively removed from the shallow groundwater. On aver-
age, 70% and 85% of groundwater TDN was mineral N
(DIN), respectively, in bioenergy buffer and AF. On
average, groundwater DIN in AF was formed by NO
3
-
N (60%), NH
4
-N (29%) and NO
2
-N (10%). After the
bioenergy buffers, NO
3
-N (47%) was still the main com-
ponent of groundwater DIN, but the proportion of NO
2
-
N (14%) and NH
4
-N (38%) increased significantly.
The NO
3
-N concentration in groundwater after
the bioenergy buffers ranged from 0.32 mg NO
3
-N L
1
(or 1.4 mg NO
3L
1
) to 1.27 mg NO
3
-N L
1
(5.6 mg
NO
3L
1
). TDN ranged from 1.54 to 2.77 mg L
1
. The
mean input of NO
3
-N and TDN from the AF was differ-
ent when soybean (2014) and tomato (2015) were culti-
vated. N fertilization during the fertirrigation of tomato
affected the concentration of NO
3
-N in groundwater; it
was on average 4.73 mg NO
3
-N L
1
(20.9 mg NO
3L
1
)
during the tomato growing season. The maximum NO
3
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
N REMOVAL BY BIOENERGY BUFFERS 5
level of 11.3 mg N L
1
(50 mg NO
3L
1
) indicated in
the EU nitrate directive (91/676/EEC) was not exceeded.
Buffer strip effectiveness (BSE) in removing N from
shallow groundwater
Similar Fand Pvalues for BSE in removing N forms
and their respective Cl
-
/N ratios were observed among
the ANOVA factors tested (Table 2). This similarity
indicates that Cl
-
concentration patterns in groundwater
did not affected N removal dynamics.
Figure 2 shows the temporal dynamics of the BSE in
removing NO
3
-N (Fig. 2a, b) and TDN (Fig. 2c, d). No
effect of crop types on BSE in removing any of the N
forms analysed in shallow groundwater was found
(Table 2). However, buffer width had a significant effect
on NO
3
-N and TDN removal rates. Ten-metre-wide buf-
fers (Fig. 2a, c) removed significantly more nitrate
(F=31.7, P<0.0001) and TDN (F=5.2, P=0.012) com-
pared to 5-m-wide buffers (Fig. 2b, d). The results of
nonlinear regression model (Table S3) confirmed that a
significant percentage of variance of BSE in removing
Table 1 Average concentrations of the N forms measured in shallow groundwater after bioenergy buffers (BS- crop) of two different
widths and in the agricultural field (AF-crop). Values with different letters in superscript show statistically different means among
crop types across growing seasons (Tukey’s HSD test, P < 0.05) and within N forms
CROP
NO
3
-N NO
2
-N NH
4
-N DIN DON TDN
5m 10m 5m 10m 5m 10m 5m 10m 5m 10m 5m 10m
2014
growing
season
BS
Spontaneous spp. 0.66
A
0.59
A
0.15
A
0.20
A
0.69
A
0.66
A
1.44
A
1.51
A
1.00
A
0.33
B
2.44
A
1.84
BC
Miscanthus 0.58
A
0.49
B
0.15
A
0.21
A
0.80
C
0.67
AB
1.44
A
1.47
A
0.57
B
0.38
B
2.01
B
1.85
C
Willow 0.45
A
0.56
A
0.14
A
0.20
A
0.80
C
0.74
BC
1.57
A
1.33
A
0.54
B
0.34
B
2.11
B
1.67
C
AF Soybean 1.49
C
* 0.11
B
1.37
D
3.01
B
0.99
A
4.11
D
2014
leaching
season
BS
Spontaneous spp. 0.43
B
0.42
B
0.15
A
0.20
A
0.23
E
0.23
E
0.85
C
0.84
C
1.29
C
0.80
A
2.10
B
1.65
C
Miscanthus 0.44
B
0.32
B
0.15
A
0.21
A
0.12
F
0.30
E
0.84
C
0.71
C
0.84
A
0.82
A
1.77
C
1.48
E
Willow 0.41
B
0.32
B
0.16
A
0.20
A
0.41
G
0.30
E
1.03
C
0.77
C
0.55
A
0.77
A
1.58
AC
1.54
AC
AF Bare soil 1.90
C
0.12
A
0.53
D
2.62
B
0.83
A
3.45
D
2015
growing
season
BS
Spontaneous spp. 1.27
D
1.19
d
0.15
A
0.20
A
0.54
A
0.49
AG
1.96
D
1.86
D
0.82
A
0.66
A
2.77
A
2.52
A
Miscanthus 1.14
D
0.95
E
0.15
A
0.18
A
0.57
A
0.51
A
1.86
D
1.65
AD
0.88
A
0.53
AB
2.74
A
2.18
B
Willow 1.38
D
0.90
E
0.20
A
0.13
A
0.55
A
0.54
A
2.14
B
1.58
A
0.36
B
0.50
B
2.48
AB
2.08
B
AF Tomato 4.73
F
0.14
A
0.89
C
5.84
E
0.43
B
6.27
F
All
seasons BS
Spontaneous spp. 0.87
A
†0.85
A
0.15
AB
0.19
A
0.54
A
0.50
A
1.56
A
1.55
A
0.97
A
0.56
B
2.53
A
2.11
B
Miscanthus 0.78
A
0.70
A
0.15
AB
0.20
A
0.57
A
0.53
A
1.50
A
1.44
A
0.80
A
0.50
B
2.30
AB
1.93
BC
Willow 0.91
A
0.63
B
0.16
A
0.21
A
0.62
A
0.57
A
1.73
B
1.34
A
0.46
B
0.49
B
2.18
B
1.83
C
AF Food crops 3.04
C
0.12
B
1.01
B
4.27
C
0.71
AB
4.87
D
*Average concentration of all the piezometers installed in AF along the perpendicular transects towards bioenergy buffers (see
Fig. 1c, d).
†Values with different letters in superscript show statistically different means among crop types (Tukey’s LSD test, P<0.05) within
averaged values for all seasons.
N form
Crop Width Season CxW CxS WxS CxWxS
FPF PF PFPFPF PFP
NO
3
1.8 ns 31 *** 14 *** 1.6 ns 1.4 ns 10 *** 1.2 ns
Cl/NO
3
1.5 ns 17 *** 13 *** 1.1 ns 1.4 ns 7.8 *** 1.1 ns
NO
2
0.8 ns 1.4 ns 0.2 ns 0.2 ns 0.1 ns 0.1 ns 0.1 ns
Cl/NO
2
0.2 ns 1.2 ns 0.6 ns 0.1 ns 0.1 ns 0.2 ns 0.1 ns
NH
4
0.6 ns 0.1 ns 7.4 *** 0.4 ns 1.9 * 0.6 ns 0.7 ns
Cl/NH
4
0.7 ns 0.1 ns 7.3 *** 0.5 ns 1.2 * 0.2 ns 0.8 ns
DIN 1.4 ns 1.4 ns 11 *** 0.6 ns 0.6 ns 1.7 ns 0.4 ns
Cl/DIN 1.1 ns 1.2 ns 9.8 *** 0.7 ns 0.2 ns 1.6 ns 0.2 ns
TDN 1.9 ns 5.4 * 7.0 *** 0.1 ns 0.6 ns 3.1 ** 1.8 *
Cl/TDN 1.7 ns 5.2 * 6.8 *** 0.1 ns 0.5 ns 2.4 * 1.5 *
*Denotes significance at P<0.05 ** P<0.01 *** P<0.001
Table 2 Results of the mixed model of
repeated measures ANOVA used to
investigate the effect of crop (C), buffer
width (W) and season (S) on buffer strip
effectiveness (BSE) in removing from
shallow groundwater the different N
forms. The table presents the F and
P values of the main fixed effect terms
and their interactions. All mixed models
showed values of adjusted R
2
(including
both fixed and random effects) higher
than 0.87 (expect for NH
4
and NO
2
that
were respectively 0.56 and 0.45)
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
6A. FERRARINI et al.
NO
3
-N was explained by buffer width. For the entire
period of monitoring, NO
3
-N removal rate indicates that
50, 75, 90 and 100% of BSE could potentially be reached
by creating bioenergy buffers, respectively, 3, 9, 15 and
20 m wide (R
2
=0.18, P=0.031) (Table S3). The highest
percentages of variance of BSE explained by buffer
width were found in the 2014 leaching season
(R
2
=0.83, P<0.001) and 2014 growing season
(R
2
=0.29, P=0.008).
A relevant seasonal pattern of the BSE in removing
nitrate was observed (Table 2, Table S3 and Fig. 2). Dur-
ing the 2015 growing season, nitrate removal rates of
bioenergy buffers were significantly higher than in 2014
(Table S3). A significant positive relationship between
groundwater NO
3
input (mg NO
3L
1
) and buffer strip
effectiveness in removing NO
3-
(BSE %) was found
(Fig. 3). Bioenergy buffers exponentially increase their
NO
3
removal rates when they started to receive more
NO
3
in May 2015 after the beginning of NPK fertirriga-
tion of tomato in the adjacent AF. Five-metre-wide buf-
fers (Fig. 3a) were found to be more correlated with
NO
3-
input than wider buffers that, on the other hand,
showed to have reached their maximum buffering
capacity (Fig. 3b).
As result of the influence of NO
3-
input on N removal
rate, a significant interaction between buffer width and
season was found for NO
3
-N (F=10.3, P<0.0001) and
TDN (F=3.1, P=0.023). The most significant effects of
buffer width on nitrate removal were observed during
the 2014 growing season (F=12.45, P=0.001) and in
the 2014 leaching season (F=16.2, P<0.0001). Based
on the model y=ax
b
, 50% and 75% of the BSE in
removing NO
3
were estimated to occur during the 2015
growing season in 1-m and 4-m-wide bioenergy buffers,
respectively (Table S3).
Among the other mineral N forms, NH
4
-N and NO
2
-N
removal rates were not affected as much as NO
3
-N and
TDN by buffer width, season and by their interaction.
NH
4
-N and NO
2
-N had large variances explained by the
random factor in mixed model of ANOVA (data not
0
20
40
60
80
100
BSE for NO3-N (%)
native species Miscanthus Willow
0
20
40
60
80
100
BSE for NO3-N (%)
native species Miscanthus Willow
0
20
40
60
80
100
BSE for TDN (%)
native species Miscanthus Willow
0
20
40
60
80
100
BSE for TDN (%)
native species Miscanthus Willow
2014 growing
season
2015 growing
season
leaching
season
2014 growing
season
2015 growing
season
leaching
season
(c) (d)
(a) (b)
5m width 10 m width
5 m width 10 m width
Spontaneous spp.
Spontaneous spp.
Spontaneous spp.
Spontaneous spp.
Fig. 2 Temporal dynamics of bioenergy buffers effectiveness (BSE –%) in removing NO
3
N(a–b) and TDN (c–d) for buffers 5 m
wide (a–c) and 10 m wide (b–d). Error bars show standard error of the mean (n=3).
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
N REMOVAL BY BIOENERGY BUFFERS 7
shown). On average, NH
4
-N removal rates were 44% for
bioenergy buffers. Nitrite instead showed in 92% of the
cases negative values of BSE indicating that release of
nitrite in groundwater by bioenergy buffers prevailed
over removal (Table 2). As consequence of the contrast-
ing patterns revealed by NO
2
-N (release) and NH
4
-N
(high variability among replicates), DIN resulted not
significantly affected by crop type, buffer width and
by the interactions of these factors (Table 2). DIN
removal by bioenergy buffers ranged from 56% in
2014 growing season to 69% in 2015 growing season.
Groundwater geochemistry and hydrology
Water table fluctuated along the measuring period fol-
lowing the precipitations pattern (Fig. S1). On average,
water table depth ranged between 0.95 m –bss in win-
ter and autumn and 0.62 m –bss during spring and
summer. Water table depth did not differ significantly
in AF and bioenergy buffers (F=0.626, P=0.6082). Dis-
solved oxygen in AF resulted significantly higher
(F=5.2, P=0.034) than under bioenergy buffers. Dis-
solved oxygen in AF was on average 2.74 and
2.25 mg L
1
in bioenergy buffers (Table S2). No statisti-
cal differences were found instead for dissolved O
2
among bioenergy buffers types. DOC concentration
showed an increase along the transect of piezometers
towards the ditch (Table S2). Agricultural field showed
significant lower DOC levels (on average
1.71 mg DOC L
1
) compared to groundwater after
bioenergy buffers (F=11.2, P=0.004). Willow showed
the highest groundwater DOC values (on average
7.76 mg DOC L
1
), while no significant differences
were found for the same parameter between sponta-
neous species and miscanthus. Moreover, a significant
negative nonlinear relationship was found between
groundwater DOC and NO
3
-N (P=0.025 R
2
=0.58).
Overall, groundwater after bioenergy buffers resulted
more C rich and more N depleted in NO
3
-N compared
to groundwater coming from AF (Fig. 4). A potential
decrease in elemental DOC:NO
3
-N ratio in groundwater
under bioenergy buffer was found (Table S2). Under
bioenergy buffers, starting from the 2014 leaching sea-
son until the 2015 growing season, elemental DOC:NO
3
-
N was below 3 in 95% of the cases. A significant inverse
linear relationship between BSE (%) in removing nitrate
and elemental DOC:NO
3
-N was found (Fig. 4). Elemen-
tal DOC:NO
3
-N ratio was also seen to be a significant
factor in determining BSE of 5-m-wide buffers more
0
20
40
60
80
100
0102030
BSE for NO3-N (%)
0
20
40
60
80
100
BSE for NO3-N (%)
Nitrate input (mg NO3 L–1) Nitrate input (mg NO3 L–1)
native species
miscanthus
willow
(a)
0102030
native species
miscanthus
willow
(b)
R²: 0.36 P: <0.01
R²: 0.38 P: <0.01
R²: 0.16 P: 0.04
R²: 0.21 P: 0.02
R²: 0.36 P: <0.01
Spontaneous spp.
Miscanthus
Willow
R²: 0.39 P: <0.01
Spontaneous spp.
Miscanthus
Willow
Fig. 3 Relationship between lateral NO
3
inputs and buffer strip effectiveness (BSE) in removing NO
3
for bioenergy buffers 5 m
wide (a) and 10 m wide (b). Data points represent mean values (n=3) of the eleven groundwater sampling events.
0
2
4
6
8
0481216
NO3-N (mg L–1)
DOC (mg L–1)
Buffers (groundwater)
Buffers (soil)
Agricultural field (groundwater)
Agricultural field (soil)
SOIL: y = 1.5 + 5.9 e – (0.41 x)
GROUNDWATER: y = 0.6 + 7.5 e – (0.42 x)
Fig. 4 Relationship between the concentration of DOC and
NO
3
N in groundwater (black) and soil (gray). The data are
grouped for bioenergy buffers (points) and agricultural field
(diamonds). The soil dataset (unfumigated samples of soil
microbial biomass extraction) was created using the data of the
last two sampling seasons (n=64) that represent the temporal
window where groundwater was monitored (samples of 10 m
wide buffers, n=44, where soil samples were collected). The
results of the regressions model (y =a+be
k(x)
) were signifi-
cant for both dataset: groundwater (R
2
: 0.58, P: 0.025) and soil
(R
2
: 0.74, P: 0.012).
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
8A. FERRARINI et al.
than in 10-m-wide buffers (Fig. S2a). Only during the
2015 growing season was DOC:NO
3
-N ratio signifi-
cantly correlated with BSE (Fig. S2b) because of the
increase in N input from AF.
Impacts of bioenergy buffers on soil C and N cycling
Bioenergy buffers had a significant impact on the stock
of several soil N and C pools compared to AF (Table S4
and Fig. 5a–d). Considering the dissolved mineral N
forms that were analysed, AF showed lower dissolved
inorganic N (DIN) and NH
4
-N in the soil compared to
the bioenergy buffers. No effects of crop type and sea-
son were found for TDN (Table S4). Only in the third
growing season (2015) was a significantly higher TDN
stock found in the AF (F=6.65, P<0.0001). Under the
tomato cultivation, potential leachable NO
3
-N was high-
est (F=6.05, P<0.0001) at all soil depths (Fig. 5a), and
consequently, TDN was increased along the soil profile.
Three months after willow buffer establishment, a
significant increase in potential leachable NO
3
-N along
the soil profile was found compared to the other bioen-
ergy buffer types (Fig. 5a). No other significant potential
leaching phenomena were found for willow in the fol-
lowing years compared to other bioenergy buffers.
On average, the proportion of NO
3
-N, NH
4
-N and
NO
2
-N in soil DIN of AF was 92%, 6%, 2%, respectively.
In comparison with AF, the proportions of NO
2
-N (9%)
and of NH
4
-N (14%) in soil DIN of bioenergy buffers
were significantly increased and NO
3
-N was signifi-
bab b
ccc
b
a
aa
bb
b
b
b
aa
bb
b
b
b
ab a
ac
a
b
0
20
40
60
80
100
120
NO3-N (kg ha–1)
MBN (kg ha–1)MBC (kg ha–1)
0-10 cm 10-20 cm 20-30 cm 30-60 cm
a
bab ab bab aab ab b
a
aa
baa
a
aaa
a
aa
baa
a
ab ab
b
a
aa
b
aa
a
a
a
b
0
20
40
60
80
100
120
140
a
bb
ccccbc bc bc
cb
b
aab
cbb
ba
b
b
b
b
b
bb
b
b
b
a
a
a
ab
ab ab
0
100
200
300
400
a
a
a
b
aa
bbb
a
bbb
a
bbb
a
a
a
aa
aaa
b
aaa
b
aa
a
b
a
a
a
b
aaa
b
aaa
b
aa
a
b
a
a
b
a
bbb
a
bbb
a
bb
b
a
0
100
200
300
400
DOC (kg ha–1)
a
a
a
a
a a
a
Buffer
establishment
1st growing
season
2nd growing
season
3rd growing
season
(a) (b)
(c) (d)
0-10 cm 10- 20 cm 20-30 cm 30-60 cm
0-10 cm 10- 20 cm 20-30 cm 30-60 cm
0-10 cm 10- 20 cm 20-30 cm 30-60 cm
Buffer
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_soybean
Spontaneous spp.
Miscanthus
Willow
AF_tomato
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_soybean
Spontaneous spp.
Miscanthus
Willow
AF_tomato
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_soybean
Spontaneous spp.
Miscanthus
Willow
AF_tomato
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_maize
Spontaneous spp.
Miscanthus
Willow
AF_soybean
Spontaneous spp.
Miscanthus
Willow
AF_tomato
establishment
1st growing
season
2nd growing
season
3rd growing
season
Fig. 5 Average values of potentially leachable NO
3
N (a), microbial biomass nitrogen –MBN (b), dissolved organic C –DOC (c)
and microbial biomass C –MBC (d) in bioenergy buffers and in agricultural field (AF) at different soil depths across different grow-
ing seasons. Different letters within staked columns show statistically different means among crop types (Tukey’s test, P: 0.05) within
the same soil depth. Horizontal lines above column(s) indicate that the letter is the same for all the soil depths.
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
N REMOVAL BY BIOENERGY BUFFERS 9
cantly reduced (77%). Soil TDN pool in bioenergy buf-
fers consisted of a great percentage of N in a dissolved
organic form (DON). DON was significantly higher in
bioenergy buffers that in AF in the top soil layers (0–10,
10–20 and 20–30 cm).
Three years after bioenergy buffer establishment,
DOC resulted the soil C pool mostly affected (in terms
of positive stocking) by the crop types (Fig. 5c). Signifi-
cant effects for crop type (F=7.40, P=0.006), soil
depth (F=5.40, P=0.002), growing season (F=5.97,
P=0.003) and their interactions were found for DOC
(Table S4). Bioenergy buffers soils showed a significant
increase in DOC stock compared to AF at all soil depths
and for each of the first three growing seasons (Fig. 5c).
No differences in these parameters were found among
bioenergy buffers indicating a similar trend of increase
in DOC stock along the soil profile. The most significant
increases in DOC under bioenergy buffers were
observed in the 20–30 and the 30–60 cm soil layers. Sim-
ilarly to what observed in groundwater, a significant
negative nonlinear relationship (P=0.012 R
2
=0.74)
was found in soil between the concentrations of DOC
and NO
3
-N (Fig. 4).
The increase in DOC in bioenergy buffers also con-
tributed to an increased C availability for microorgan-
isms. Figure 5d clearly shows how microbial biomass C
(MBC) significantly increased along the soil profile in
bioenergy buffers compared to AF (F=5.92, P=0.004).
After the first period of buffers establishment, signifi-
cant interactions between crop and soil depths
(F=3.91, P=0.029) and between crop and growing
seasons (F=3.38, P=0.013) were observed for MBC.
Under bioenergy buffers, the 30–60 cm soil layer
showed the greatest increase in MBC stock (P=0.013)
compared to AF. A significant increase in microbial bio-
mass N (MBN) stock was also observed in bioenergy
buffers compared to AF (F=3.99, P=0.023) (Fig. 5b).
Among bioenergy buffers, spontaneous species was
seen the treatment with the highest ability to immobi-
lize N in soil microbial biomass at different depths com-
pared to miscanthus (P=0.028) and willow (P=0.003).
Elemental C:N ratio of microbial biomass was found
significantly higher (F=2.11, P=0.047) in bioenergy
buffers (6.01) compared to the AF (4.45).
The rate of biological reduction of nitrate to nitrite
(nitrate reductase activity –NRA) was found to be
strongly affected by the crop types, soil depths and
across different growing seasons (Fig. 6 and Table S4).
Bioenergy buffers, in particular willow, supported a soil
microbial community able to remove nitrate at higher
rates compared to AF since the first periods after crop
establishment (Fig. S3). On average, NRA values along
the soil profile were 38.1 and 43.4 lgN-
a
a
a
a
ab
b
b
b
b
c
c
c
c
c
c
c
0
10
20
30
40
50
60
10 20 30 40 50
Depth (cm)
NRA (μg NO2-N gsoil–1 day–1)
Agricultural field
Miscanthus
Willow
Spontaneous spp.
Fig. 6 Soil nitrate reductase activity (NRA) in bioenergy buf-
fers and in agricultural field at different soil depths. Values are
reported as average values of the first three growing seasons.
Different letters show statistically different means (Tukey’s test,
P: 0.05) within soil depths.
R²: 0.38 P: 0.02
R²: 0.51 P: 0.01
0
10
20
30
40
50
60
0.0 0.5 1.0 1.5 2.0 2.5
NRA (μg NO2-N g–1day–1)
Fine root biomass (Mg ha–1)
Miscanthus
Willow
(c)
a
a
a
a
a
b
b
a
b
b
b
c
ab
c
b
c
0.0 0.5 1.0 1.5 2.0 2.5
Fine root biomass (Mg ha–1)
(a)
a
a
a
a
a
a
b
a
a
a
b
ab
b
b
b
0 2 4 6 8 10 12 14 16
Root N stock (kg ha–1)
Miscanthus
Willow
a
(b)
Crop (C)
Depth (D)
C x S
F
47.2
89.8
11.6
P
<0.001
<0.001
<0.001
Crop (C)
Depth (D)
C x S
F
33.0
55.1
9.3
P
<0.001
<0.001
<0.001
Spontaneous spp.
Miscanthus
Willow
Spontaneous spp.
Spontaneous spp. ns
Fig. 7 Fine root biomass (a) and root N stocks (b) in bioenergy buffers at different soil depths. Different letters show statistically dif-
ferent means (Tukey’s test, P: 0.05) among crop types within the same soil depth interval. (c) Linear relationship between fine root
biomass and soil nitrate reductase activity (NRA) in bioenergy buffers in third growing season (2015).
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
10 A. FERRARINI et al.
NO
2
g
soil1
day
1
, respectively, for miscanthus and wil-
low. These values were significantly higher (F=56.50,
P<0.0001) than those observed for the spontaneous
species (30.3 lg N-NO
2
g
soil1
day
1
) and for the AF
(21.5 lg N-NO
2
g
soil1
day
1
).
Belowground and aboveground biomass production and N
stocks
After 3 years from the establishment of bioenergy
buffers, fine root biomass (<2 mm) was significantly
affected by crop type, soil depths and by the interac-
tion of both factors (Fig. 7a). In the whole soil profile
(0–60 cm), willow showed the significantly highest
fine root biomass (5.30 Mg ha
1
) compared to mis-
canthus (3.99 Mg ha
1
), while the lowest value was
found for the spontaneous species (2.03 Mg ha
1
). On
average, 59% of fine roots in willow and miscanthus
were found in the top soil layer (0–30 cm) and 41%
in bottom soil layer (30–60 cm). In the spontaneous
species, the greatest proportion of fine root biomass
(70%) was found in the top layer. Significant linear
relationships were found between fine root biomass
and soil NRA for miscanthus and willow (Fig. 7c).
The crop ranking for fine root biomass (willow >mis-
canthus >spontaneous species) was the same for soil
NRA.
N root content (g kg
1
) did not vary significantly
among crops (F=1.67, P=0.211) and along the soil
profile (F=0.15, P=0.926). On average, at 0–10, 10–20,
20–30 cm and 30–60 cm depth root N content was,
respectively, 5.8, 6.1, 6.1 and 5.9 kg N g
root1
. N stock
in fine roots was significantly affected by crop types,
soil depths and by the interaction of both factors
(Fig. 7b). Willow showed a higher root N stock
(32.40 kg N ha
1
) along the whole soil profile (0–60 cm)
compared to miscanthus (20.79 kg N ha
1
). Sponta-
neous species instead showed the lowest root N stock
(12.67 kg N ha
1
).
Harvestable biomass in bioenergy buffers for miscant-
hus, after winter killing frost (February), was
3.2 0.6 Mg DM ha
1
in the establishment year (2013)
and 10.76 0.51 Mg DM ha
1
at the second year
(2014). Willow, after the first 2 years rotation cycle, pro-
duced significantly more than miscanthus (F=99.55,
P<0.0001) with a harvestable biomass of 34.15
1.71 Mg DM ha
1
. N exportations via harvesting were,
respectively, 5.9 kg N ha
1
in 2013 and 16.1 kg N ha
1
in 2014 for miscanthus and 73.7 kg N ha
1
for willow
in 2014. By analysing the biomass data of each single
row in each plot, it was found that there was an expo-
nential decrease in biomass yield along the buffer tran-
sect (Fig. S4). The plant rows closer to the AF showed
the highest values in harvestable biomass and N
removal in comparison with the plant rows near to the
ditch. Harvestable biomass for the 10-m-wide willow
buffers (Fig. S4a) ranged from 47.4 Mg DM ha
1
in the
plant rows adjacent to the AF to 26.6 Mg DM ha
1
in
the plant rows near to the ditch. Similarly, N removal
was highest in plant rows adjacent to the AF
(120.6 kg N ha
1
) and lowest near the ditch
(51.78 kg N ha
1
). The same effect was less evident in
miscanthus, and it was limited to the first two rows
adjacent to the AF (Fig. S4b).
Discussion
Bioenergy buffers effectiveness (BSE) in removing N and
key factors governing BSE
Our results clearly indicate bioenergy buffers effective-
ness in removing NO
3
-N and TDN from shallow
groundwater (Fig. 2 and Table S3). BSE in removing
NO
3
-N was 70% for miscanthus and 71% for willow,
respectively (Table S3). These values are in accordance
with the 60–70% range reported at landscape level by
Ssegane et al. (2015) and Gopalakrishnan et al. (2012) for
buffer strips cultivated with switchgrass, miscanthus
and willow. Similar findings were reported also in
riparian buffers of Salix spp. (Young & Briggs, 2005).
No differences between herbaceous and woody crops
and between bioenergy crops and spontaneous species
on N removal rate were observed (Table 2). This indi-
cates that vegetation types in narrow buffer strips do
not remove N from subsurface water flow with signifi-
cant differences (Sabater et al., 2003; Mayer et al., 2007).
Mayer et al. (2007) conducted a meta-analysis over 45
published studies on nitrate removal by riparian buffers
and found that the mean mass of NO
3
-N removed per
unit length was not statistically different between
forested and herbaceous buffers. Similarly, our results
confirmed that DIN was dominantly present as NO
3
and it was removed 9.38% m
1
by spontaneous species,
10.12% m
1
by miscanthus and 9.43% m
1
by willow,
respectively. These values are in accordance with the
mean values found in 14 riparian buffers across Europe
(Sabater et al., 2003)
.
Yet, it is confirmed that from the
first periods after establishment bioenergy crops can
remove N from groundwater as much as buffers strips
with spontaneous species.
Buffer width had a significant effect on NO
3
-N and
TDN removal rates from shallow groundwater, with 10-
m-wide buffers being more effective. Nonetheless,
bioenergy buffers that are as wide as national recom-
mendations (5 m) suffice to remove more than 50% of
the incoming nitrate in most cases (Table S3). The effect
of buffer width in this study was unexpected as in liter-
ature reports have shown significant differences where
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
N REMOVAL BY BIOENERGY BUFFERS 11
buffer widths differed by more than 10–20 m (Hickey &
Doran, 2004; Mayer et al., 2007; Sweeney & Newbold,
2014). In addition, nitrate removal rate was seen to be
even higher when nitrate input from AF increased
(Fig. 3). The results of nonlinear regression (Table S3)
suggested that, in linear and straightforward hydrologi-
cal conditions similar to our case study, a 3-m-wide buf-
fer, made of miscanthus or willow, can remove up to
75% of nitrate during a high N input season. This indi-
cates that no N saturation effects occurred in our
3-year-old bioenergy buffers, although clear symptoms
of N saturation have been reported in situations with
long-term N loadings (Aber, 1992; Hanson et al., 1994;
Sabater et al., 2003; Hefting et al., 2006).
Biomass production and plant N removal in bioenergy
buffers
The reasons for which no evidence of N saturation was
observed in this study can be found in the aboveground
and belowground biomass dynamics. Biomass produc-
tion and plant N uptake have been shown to be impor-
tant N removal processes in forested (Hefting et al.,
2005) and herbaceous buffers (van Beek et al., 2007;
Balestrini et al., 2011). In this study, willow buffers per-
formed very well in terms of biomass production in the
first 2-year cycle (34.2 Mg DM ha
1
). This value of bio-
mass yield is higher than the mean values reported for
Salix spp. in Canada and the United States (Amichev
et al., 2014), Europe (Zegada-Lizarazu et al., 2010) and
in northern Italy (Rosso et al., 2013). The tolerance of
willow to saturated soils and oxygen shortage at deeper
soil layers is widely reported (Krasny et al., 1988; Jack-
son & Attwood, 1996; Aronsson & Perttu, 2001). Fur-
thermore, lateral N loadings by enriched groundwater
significantly affected biomass production along the buf-
fer transect (Fig. S4a) with the first two rows (adjacent
to the AF) being the most productive (up to
48 Mg DM ha
1
plant row
1
) and the ones that con-
tributed most to N removal via uptake and harvesting
(Fig. S4).
Miscanthus biomass production in the first 2 years
was 3.2 and 10.8 Mg DM ha
1
. These values are lower
than those found in field trials with similar stand age in
temperate regions; from 15 to 20 Mg DM ha
1
(Lewan-
dowski & Heinz, 2003; Angelini et al., 2009). For mis-
canthus, the low yields might have been affected by the
presence of shallow groundwater (Lewandowski et al.,
2003) and by the high soil hydraulic conductivity and
sandy loam texture (Table S1). The latter two factors
may increase the soil moisture deficit in upper soil lay-
ers for relatively long periods during the summer sea-
son; previous studies (Heaton et al., 2004; Monti &
Zatta, 2009; Mann et al., 2012) have shown miscanthus
to be highly productive where water is not limiting, but
very sensitive to water shortage.
By comparison with spontaneous species, both willow
and miscanthus had deeper fine root systems (Fig. 7a)
and higher root N stocks (Fig. 7b). The ability of peren-
nial bioenergy crops to penetrate deep-rooting zones (to
access nutrients more efficiently) is widely recognized
(Rytter, 2001; Glover et al., 2010; Ens et al., 2013; Owens
et al., 2013; Amichev et al., 2014). The total belowground
biomass found in willow can be placed at the highest
ranking positions among the willow hybrids studied in
Stadnyk (2010) and reviewed in Amichev et al. (2014).
After 2 years from planting, miscanthus had a mean
belowground biomass of 4 Mg ha
1
between 0 and
60 cm in depth. At this depth interval, this value is in
line with those reported in previous studies carried out
on mature stands (>3–4 years) in Italy (Monti & Zatta,
2009; Chimento & Amaducci, 2015), Europe and USA
(Heaton et al., 2004; Amougou et al., 2010; Dohleman
et al., 2012; Anderson-Teixeira et al., 2013; Zatta et al.,
2014).
With regard to root biomass distribution along soil
profile, it was observed that willow with 2.2 Mg ha
1
and miscanthus with 1.6 Mg ha
1
are characterized by
an high contribution of fine roots (41%) to whole root
biomass at deeper layers (30–60 cm). In a 6-year-old
multispecies experiment, Chimento & Amaducci, 2015
found that only 0.9 Mg ha
1
(17%) and 2 Mg ha
1
(23%) of the whole root mass was allocated respectively
by willow and miscanthus at 30–60 cm depth. These
results on rooting patterns clearly indicate how cultivat-
ing bioenergy crops along the field margins offers the
opportunity to intercept N loads from surrounding agri-
cultural fields at deeper soil layers compared to buffers
with spontaneous species. This would ultimately
increase the environmental performance of bioenergy
buffers in term of plant N removal from soil. Further-
more, as root biomass was shown to be a good indicator
of soil organic C sequestration (Chimento et al., 2016;
Chimento & Amaducci, 2015), our results suggest how
bioenergy buffers have a higher potential compared to
patches of adventitious plants to contribute to C storage
and GHG savings in the deep soil layers.
Biogeochemical processes governing N removal in plant–
soil–groundwater system
In addition to the role of vegetation, a series of biogeo-
chemical processes in soil and groundwater are recog-
nized as being important in determining N removal in
bioenergy 3 buffers. The patterns of dissolved O
2
, pH,
NO
2
-N, NO
3
-N and DOC in groundwater (Table 2,
Table S2 and Fig. 4) suggest that denitrification plays a
predominant role in the nitrate depletion observed in
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
12 A. FERRARINI et al.
bioenergy buffers. Suboxic conditions were found in
groundwater after the bioenergy buffers (Table S2); such
conditions are optimal for denitrification (Vidon & Hill,
2005). There was also a significant increase in the contri-
bution of NO
2
-N to DIN at the expense of NO
3
-N which
indicates that a rapid nitrate reduction occurred (Giles
et al., 2012; Butterbach-Bahl et al., 2013). The alkaline
pH of groundwater (Table S2) and of soil (Table S1) and
the average depth of the groundwater table (Fig. S1)
denote the presence of ideal conditions for soil
denitrifying communities (Groffman et al., 1991; Weier
et al., 1993; Rich & Myrold, 2004). Moreover, an increase
in the stock of DOC along the soil profiles of bioenergy
buffers (Fig. 5c) might have promoted the observed
enrichment of DOC in groundwater after the bioenergy
buffers (Table S2). DOC levels in groundwater after the
bioenergy buffers (>5 mg DOC L
1
) indicated that
incoming groundwater found suitable conditions for
denitrification under the bioenergy buffers (Cosandey
et al., 2003; Gumiero et al., 2011; Senbayram et al., 2012).
In comparison with spontaneous species, willow and
miscanthus, indeed, promoted an active zone of biologi-
cal removal of nitrate along the whole soil profile
because of their deep and dense root systems as
revealed by the positive relation between NRA and fine
root biomass (Fig. 7c). High soil moisture in sandy loam
soils has been shown to stimulate root exudation of
easily available C sources (DOC) for microorganisms,
thus triggering microbial activity (Dijkstra & Cheng,
2007). On this regard, the use of DOC and the incoming
nitrate, respectively, as donor and electron acceptor by
denitrifying microbial communities plays a key role in
the nitrate depletion observed in groundwater. A signif-
icant exponential negative relationship between DOC
and NO
3
-N was found along the groundwater soil con-
tinuum from the AF to the bioenergy buffers (Fig. 4).
This indicate that the shift in elemental stoichiometry
(DOC:NO
3
-N ratio) promoted the microbial N removal
by denitrification in bioenergy buffers by constraining
N accrual in groundwater. The presence of a confining
layer at a shallow depth (Fig. 1c) forces most of the
incoming oxic and enriched nitrate groundwater to flow
through the subsurface, DOC rich, soil layer of the
bioenergy buffers (Gold et al., 2002). As consequence,
the DOC:NO
3
-N ratio dropped below the range of 3–6
(Table S2) and triggered NO
3
-N removal by denitrifica-
tion (Taylor & Townsend, 2010), which is in agreement
with results available in literature (Groffman et al., 1992;
Hedin et al., 1998; Hill & Cardaci, 2000; Gold et al., 2002;
Cosandey et al., 2003; Senbayram et al., 2012).
The results discussed above indicate that the N
removal processes are strictly linked to the increase in
DOC in bioenergy buffers. Dissolved organic C com-
pounds are important drivers of denitrification in ripar-
ian soils (Hill et al., 2000). Easily available C for
microorganisms measured as DOC has been also
thought to be the main source of subsoil organic matter
(Rumpel & K€
ogel-Knabner, 2011) and under bioenergy
crops could be of relevance due to the their deep-root
systems (Agostini et al., 2015). In fact, the observed
increase in soil DOC in willow and miscanthus buffers
was found to be significantly correlated to fine root bio-
mass (R
2
=0.35, P=0.04). Through the release of exu-
dates of low molecular weight (the main source of
DOC), the root environment (the so called rhizosphere)
increases microbial activity through MB utilization of
new easily available C sources (Kuzyakov, 2002; Zhu
et al., 2014). The dual increase in DOC and MBC
observed along the soil profile in our bioenergy buffers
as compared to the AF (Fig. 5c, d) revealed that estab-
lishment of bioenergy crops with such dense and deep-
rooting systems triggered the soil microbial community.
The activities of soil C, N and P-acquiring enzymes such
as b-glucosidase, leucine aminopeptidase and alkaline
phosphatase have been observed to significantly
increase under bioenergy buffers at 0–30 cm depth (A.
Ferrarini & F. Fornasier, unpublished data). The rhizo-
sphere priming effect promotes N mining from SOM
and the mineralized N is retained by the microbial com-
munity through rapid immobilization (Kuzyakov, 2002;
Dijkstra et al., 2013; Kuzyakov & Xu, 2013; Blago-
datskaya et al., 2014; Chen et al., 2014; Zhu et al., 2014).
Microbial biomass N, indeed, significantly increased in
the top soil layers under the bioenergy buffers by com-
parison with the AF (Fig. 5b). Microbial N retention was
also observed in other perennial agroecosystems (Harg-
reaves & Hofmockel, 2013). However, elemental CN
ratio of microbial biomass (MB) along the soil profile
did not decrease because of MBN increase. A MB CN
ratio around 6 is close to that of the SOM that would be
decomposed (SOM CN of 8 at 0–60 cm) and this high-
lights how soil microbial biomass should not undergo
adjustments of microbial element use efficiency
(Mooshammer et al., 2014). As the stoichiometry of the
soil resource was balanced with that of the microbial
biomass, soil microbes could not excrete N in excess
and thus soil N is retained and N losses should have
been prevented (e.g. during winter period with potential
N leaching) (Manzoni et al., 2012; de Vries & Bardgett,
2012). Indeed, potentially leachable nitrate did not
increase significantly along the soil profile under the
bioenergy buffers compared to the AF after the begin-
ning of the second growing season (2014) (Fig. 5a).
Overall, the increase in easily available C for microor-
ganism (DOC), MBC and MBN confirmed the results of
Bengtson et al. (2012) and Paterson (2003) of a strong
coupling of root C release, SOM cycling and microbial
N cycling.
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
N REMOVAL BY BIOENERGY BUFFERS 13
In conclusion, herbaceous and woody bioenergy
crops have been confirmed as being effective in mitigat-
ing shallow groundwater N pollution when cultivated
as bioenergy buffers. Up to 50, 70 and 90% buffer strip
effectiveness in removing NO
3
-N could be reached by
creating bioenergy buffers 3, 9 and 15 m wide, respec-
tively. The use of ecological stoichiometry (DOC:NO
3
-
N) revealed that denitrification plays a key role in the
nitrate removal observed along the soil–groundwater
continuum. Deep-rooting systems of bioenergy crops
promoted the activation of soil microbial processes
involved in N removal from soil. Our findings also sug-
gest that biomass production and N removal through
multiple harvests further contributes to N retention in
bioenergy buffers compared to unmanaged buffer strips
with spontaneous species. Bioenergy crops placed along
watercourses in sandy loam soils with shallow ground-
water enhance ecosystem services and sustain soil func-
tioning such as water quality regulation and soil
microbial C and N cycling.
Acknowledgements
The authors gratefully acknowledge funding from the Italian
Ministry of Agriculture to the HEDGE-BIOMASS project. We
thank Francesca O’Kane for insightful comments on an earlier
version of our manuscript, Luigi Bisi for field maintenance,
Luca Poletti for laboratory assistance and field work, Marco
Barbieri for the help in the geological survey and Nicola Bal-
lerini for help in the installation of piezometers.
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Supporting Information
Additional Supporting Information may be found in the online version of this article:
Figure S1. Hydrological features of the field trial.
Figure S2. Relationship between elemental DOC:NO
3
-N ratio under bioenergy buffers and buffer strip effectiveness (BSE %) in
removing NO
3
-N from groundwater.
Figure S3. Soil NO3 reductase activity (NRA) under bioenergy buffers and agricultural field at different soil depths across the four
sampling seasons: (a) after buffers establishment (July 2013); (b) end of 1st growing season (Feb 2013); (c) end of 2nd growing sea-
son (Feb 2014); (b) middle of 3rd growing season (Aug 2015).
Figure S4. Harvestable biomass (black lines) and N removal via harvesting (grey bars) of willow (a) and miscanthus (b) for differ-
ent plant rows along the 10 m wide buffer transects.
Appendix S1. Lab protocol adopted for potential soil nitrate reductase activity (NRA).
Table S1. Main soil physical and chemical characteristics of the soil horizons.
Table S2. Average concentrations of groundwater chemical species after bioenergy buffers (BS- crop) and in agricultural field
(AF-crop).
Table S3. Mean values of NO3 removal rate as BSE (%), BSE per unit length (% m
1
) and mean mass of N removed per unit
length (mg NO3-N L
1
m
1
) for bioenergy buffers across the growing seasons.
Table S4. Results of the mixed model of repeated measures ANOVA used to investigate the effect of crop (C), depth (D) and grow-
ing seasons (S) on the stock (kg ha
1
) of soil inorganic N forms, C and N pools of dissolved organic matters (DOM) and microbial
biomass (MB) and the effects on potential soil nitrate reductase activity (NRA –lgNO
2
-N g
soil1
day
1
).
©2016 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd., doi: 10.1111/gcbb.12340
16 A. FERRARINI et al.