Skip to main content
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2015 Dec 14;22(2):875–888. doi: 10.1111/gcb.13096

Does canopy nitrogen uptake enhance carbon sequestration by trees?

Richard K F Nair 1,, Micheal P Perks 2, Andrew Weatherall 3, Elizabeth M Baggs 4, Maurizio Mencuccini 1,5
PMCID: PMC4738422  PMID: 26391113

Abstract

Temperate forest 15N isotope trace experiments find nitrogen (N) addition‐driven carbon (C) uptake is modest as little additional N is acquired by trees; however, several correlations of ambient N deposition against forest productivity imply a greater effect of atmospheric nitrogen deposition than these studies. We asked whether N deposition experiments adequately represent all processes found in ambient conditions. In particular, experiments typically apply 15N to directly to forest floors, assuming uptake of nitrogen intercepted by canopies (CNU) is minimal. Additionally, conventional 15N additions typically trace mineral 15N additions rather than litter N recycling and may increase total N inputs above ambient levels. To test the importance of CNU and recycled N to tree nutrition, we conducted a mesocosm experiment, applying 54 g N/15N ha−1 yr−1 to Sitka spruce saplings. We compared tree and soil 15N recovery among treatments where enrichment was due to either (1) a 15N‐enriched litter layer, or mineral 15N additions to (2) the soil or (3) the canopy. We found that 60% of 15N applied to the canopy was recovered above ground (in needles, stem and branches) while only 21% of 15N applied to the soil was found in these pools. 15N recovery from litter was low and highly variable. 15N partitioning among biomass pools and age classes also differed among treatments, with twice as much 15N found in woody biomass when deposited on the canopy than soil. Stoichiometrically calculated N effect on C uptake from 15N applied to the soil, scaled to real‐world conditions, was 43 kg C kg N−1, similar to manipulation studies. The effect from the canopy treatment was 114 kg C kg N−1. Canopy treatments may be critical to accurately represent N deposition in the field and may address the discrepancy between manipulative and correlative studies.

Keywords: 15N labelling, C sequestration, canopy fertilization, canopy nitrogen uptake, isotope trace, Nitrogen deposition, Picea sitchensis, soil fertilization

Introduction

Large differences exist among some estimates of the effect of nitrogen (N) deposition (NDEP) on temperate forest carbon (C) uptake in the northern hemisphere. These forests are a net C sink [0.6–0.7 Pg C yr−1 (Goodale et al., 2002)] and are also typically nitrogen limited (Vitousek et al., 2002; Lebauer & Treseder, 2008). Anthropogenic inputs of N from the atmosphere (Vitousek et al., 1997; Holland et al., 1999; Galloway et al., 2004) may enable extra C uptake (Thornley & Cannell, 1996) in these regions. However, estimates of C uptake due to NDEP (henceforth referred to as ΔC/ΔN) from N additions tend to be low. Stable isotope tracer experiments where 15N is directly applied to the forest floor find that soil, litter and microbial biomass (SMB) are major sinks of N (70–80% of NDEP), while only ~20% of this 15N can be traced into trees and even less (< 5%) into woody components (Nadelhoffer et al., 1999; Templer et al., 2012a). As little N is recovered from high C/N biomass, the implied ΔC/ΔN is around 50 kg C kg N−1, which equates to only around 20% of net C uptake (Nadelhoffer et al., 1999). Other methodologies scaling measurements such as canopy N budgets or photosynthetic rates also tend to give low estimates of ΔC/ΔN [e.g. De Vries et al., 2006; Fleischer et al., 2013)], and one particular 15N amendment and modelling synthesis from Harvard Forest (Currie et al., 2004) found a ΔC/ΔN effect as small as < 5 kg C kg N−1, with most N for forest growth derived from natural abundance mineral soil as opposed to 15N deposition inputs applied to the soil.

Several correlational studies have since produced higher ΔC/ΔN estimates based on relationships between NDEP and various indices of forest productivity. This was first raised by Magnani et al. (2007) who, from an estimate of C accumulation based on a comparison of European forest net ecosystem productivity found a strong influence of total (i.e. wet and dry) NDEP at the continental scale, indicating an effect around 120–150 kg C kg N−1 (Magnani et al., 2008) when revised. These findings have variously been attributed to covariance of C uptake and N deposition with factors such as soil N capital and site history (De Vries et al., 2008; Högberg, 2012), climate or dry NDEP contributions (De Vries et al., 2008; Sutton et al., 2008). Other studies using similar methodologies at the continent (Thomas et al., 2009) or country scale (Etzold et al., 2014; Ferretti et al., 2014) using forest inventory data have since implied similarly large effects. For such a large sink, NDEP needs to be accumulated in trees and sequestered in high C/N, long‐lived bolewood (Townsend et al., 1996), which contradicts the results of manipulative experiments and 15N budgets.

An alternative explanation for these differences is that important real‐world processes included in correlative studies are not accurately represented in conventional deposition experiments. 15N amendment experiments (e.g. Nadelhoffer et al., 1999) typically apply 15N directly to the soil, and, while uptake of N by foliage has been considered for some almost 30 years (see early work; Garten et al., 1988; Hanson & Garten, 1992; Norby et al., 1989), such studies assume interactions with the canopy are of minimal importance. However, canopy N uptake (CNU) is now well documented (Sparks, 2009) and if substantial amounts of N are obtainable across leaf or branch surfaces this may substitute for, or supplement nutrition by soil pathways. Soil‐targeted studies could therefore underestimate the total ΔC/ΔN effect due to their assumption that only minimal amounts of N can be acquired by the canopy. CNU may also increase allocation to wood to 10 or 15% of total NDEP (Sievering, 1999), which may influence the strong woody response implied by growth rates of some species across North America (Thomas et al., 2009). When incorporated into a recent modelling study, Dezi et al. (2010) found that forest management, CNU and induced changes in litter quality significantly raised the predicted ΔC/ΔN effect up to 121 kg C kg N−1.

Various potential mechanisms for CNU have been suggested, across both foliage and twigs, via ion exchange (Bowden et al., 1989; Boyce et al., 1996; Sparks, 2009) and simple diffusion (Klemm et al., 1989). These may vary in their absorption of specific N species (Wilson & Tiley, 1998) due to varying transport and metabolic costs to reduce N for biological incorporation, as well as internal cell N concentrations, and varying in their degree of incorporation into actively cycling pools within the plant (Sparks, 2009). In forests, estimates of CNU can be high, and some canopy N budgets (NDEP – throughfall) suggest 50–80% of NDEP is retained by the canopy (e.g. Sievering et al., 2007). 15N tracer recovery‐based methods tend to suggest lower CNU, from 50% maximum uptake across the canopy (MacKlon et al., 1996) to 25–30% (Friedland et al., 1991; Ammann et al., 1999) or as low as 2–5% (Lumme, 1994; Wilson & Tiley, 1998). These estimates are often difficult to interpret because of varying application methods, experimental systems, NDEP magnitudes (Chiwa et al., 2004) and timescales, as well as species and site specific effects. They are also rarely compared against equivalent soil‐targeted deposition, making the separation of causative factors difficult [(see Lumme, 1994) for the only exception we could identify, albeit in an artificial microcosm]. Similarly, only a single study (Dail et al., 2009) reports a field‐scale 15N canopy fertilization. In their study, 15N recovery was high in plants (31% of 15N‐NH4, 61% of 15N‐NO3), but the implied ΔC/ΔN was modest due to high recovery in low C/N compartments such as bark (apparent retention in this pool is also complicated by the potential for abiotic retention on bark surfaces and incorporation into bark surface mosses and lichens). The C/N stoichiometry of this pool also varies between species (Allison, 1965), and hence, C effects from retention in bark may vary. Finally, both 15N isotope trace and unlabelled N addition experiments frequently apply a total N concentration far in excess of ambient NDEP concentrations. This means it is difficult to interpret the effects of such experiments due to both positive and negative concentration‐dependent effects on ecosystem health as cumulative N inputs move towards N saturation (McNulty et al., 1996) as well as those specifically on canopy physiology (Maurice & Crang, 1986; Wellburn, 1990; Sievering et al., 2007; Wortman et al., 2012). Physiological effects on the canopy may occur earlier under foliar N loads due to CNU, especially if N inputs are in rare, high concentration events.

A second limitation to conventional 15N deposition treatments is that these typically apply a mineral 15N, typically NH4NO3, over the short term. In the real world, such inputs typically provide a minority of total N nutrition to plants in natural systems. Even under heavy NDEP, internal litter mineralization remains the major source of N nutrition (Schulze, 2000; Högberg, 2012). Plant N uptake was historically thought to require complex organic precursors to be decomposed fully to NH4+ and NO3, but there is now substantial evidence [see Näsholm et al. (2009) for a review] for organic N uptake by plants. Therefore, we were also interested if N from this source was partitioned in the same way as N from deposition.

We designed an experiment utilizing Sitka spruce [Picea sitchensis, (Bong.) Carr.] saplings, where a 15N signal could be traced from CNU, from conventional direct‐to‐soil mineral fertilization sources and also from labelled litter. We aimed to apply sustained N deposition inputs more regularly and for a longer duration than the few month durations and occasional inputs typical of other foliar 15N experiments. We applied very low total concentrations of N at high 15N enrichments in order to study the system at close to background N deposition levels. We utilized treatments with an artificial litter layer with high 15N enrichment and unlabelled N deposition to trace 15N from the litter under our deposition treatments.

We aimed to test the hypotheses that (i) the total return of 15N from deposition in aboveground parts of trees would be greater when 15N was applied to the canopy, rather than the soil; (ii) the proportional recovery of 15N in different tree organs (foliage, branches, stems and roots) and soil pools (SMB and bulk soil) would differ because of these two forms of application; and iii) 15N released from litter mineralization would have a greater recovery in plant pools compared to 15N applied in soil fertilizer treatments due to increased plant uptake of N from this source.

Materials and methods

Study site

Our study consisted of 3‐year‐old Sitka spruce saplings, located at Forest Research Northern Research Station, Scotland (55°86′N, 3°20′W). Thirty selected individuals from a cold‐stored (4 °C, lifted January 2011) batch of 2‐year‐old saplings were potted in 60 L pots on a mix of 90% homogenized stagnohumic gley topsoil (Clement, 2004) and 10% low N/P/K compost. The soil was collected from Griffin Forest, a Sitka spruce plantation in central Scotland (56°37′N, 3°47′W) and after mixing had a mean N content of 0.64% by dry weight. The C/N ratio of the soil mix was 24:1. In June 2011, the seedlings were randomly arranged in a 0.5 m spaced grid of 5 by six trees, surrounded in an overall 9 by 6 grid by an additional 60 trees which served to provide an edge around all treatment groups, and left to establish until summer 2012. Annual precipitation at the site was 704 mm, while mean monthly temperatures varied between 1 and 19°C. The trees remained in the initial configuration for the duration of the experiment.

Experimental treatments

Individual trees were assigned to six treatments stratified based on current basal diameter and height as well as a series of soil CO2 efflux measurements made over spring and summer 2012 with an a EGM‐4 CO2 IRGA (PP Systems, Amesbury, MA, USA), as a proxy for differences in below‐ground nutrient cycling potential. Due to an aphid infestation in spring 2012, six trees had lost some of the 2011 cohort of needles and were each assigned to different treatments to avoid systematic biases. This stratification was designed to ensure an even mixture of tree size and apparent health in each treatment (n = 5 per treatment). In August 2012, we assigned the trees to their treatment groups and applied a layer of artificial litter to the soil. This artificial litter was obtained from the Gisburn Forest tree species trial, Lancashire, UK (54_01′30″N, 2_22′57″W) where 6–7 m tall Sitka spruce trees had been stem injected with 13C and 15N double‐labelled aspartic acid (n = 3, see Churchland et al., 2012). The labelled trees were felled in November 2010, and three natural abundance control trees were harvested from the same site in January 2011. All biomass was dried in a 70 C oven until needles were easily separated from the branches, then stored in paper sacks in a dry polytunnel until deployment. A random sample of 100 needles from each of the trees was measured for 14/15N and 12/13C isotope ratios 1 month before deployment, using the same methodology as later samples (see below). In the control trees, δ 15N was at natural abundance (0%). The labelled trees had mean foliar 15N atom % excess of 0.263, 0.850 and 1.231% over natural abundance, and a mean foliar N content of 1.12 ± 0.2 (SD) % and foliar C content of 48.88 ± 5.3 (SD) %. Total N and C concentrations were not significantly different (anova) among the source trees nor between injected and uninjected trees. Each potted mesocosm tree received 0.8 kg of litter (either 15N enriched or natural abundance), from a single randomly assigned source tree [to reduce the potential for interactive effects of litter mixing, for example Gartner & Cardon (2004); Smith & Bradford (2003)], in a single 4–5 cm deep layer. This amount of litter was selected to provide a reasonably deep and mixable litter layer across the pot surface. The six treatments (Table 1, Fig. 1) were designed to test a unique combination of 15N source and deposition type to the trees, varying in (a) litter type; either natural abundance or 15N‐enriched (indicated in treatment names by the superscript LITTER); (b1) deposition type; either, NDEP to the soil (SNU; soil nitrogen uptake) or NDEP to the canopy (CNU; canopy nitrogen uptake); and (b2) level of 15N enrichment of the deposition treatment; either water control applied directly to the soil, (CONTROL), natural abundance 0.3663 atom % 15N (in the case of the LITTER treatments) or 98 atom % 15N (the source of 15N in all treatments without the LITTER prefix). All treatments had a single enriched 15N source (e.g. the LITTERSNU treatment contained 15N‐labelled litter paired with an unlabelled NDEP treatment to the soil), with the exception of the water control on unlabelled litter, which had no enriched 15N source.

Table 1.

Treatment descriptions for the six experimental treatments. Total NDEP for all deposition treatments was 54 g N ha−1 yr−1 applied as NH4NO3, and 15N‐enriched treatments were 98 atom % 15N as 15NH4 15NO3

Treatment ID Litter Type of application to soil Type of application to canopy
CONTROL Natural abundance Water
LITTERC 15N‐enriched Water
SNU Nat. abun. 15N‐enriched NDEP
CNU Nat. abun. 15N‐enriched NDEP
LITTERSNU 15N‐enriched Nat. abun. NDEP
LITTERCNU 15N‐enriched Nat. abun. NDEP

Figure 1.

Figure 1

Treatment descriptions for the six experimental treatments. Each treatment received 0–1 sources of enriched 15N, either no enrichment (CONTROL), 15N‐enriched litter (LITTERCONTROL,LITTERSNU,LITTERCNU) or 98% double‐labelled 15N in deposition, that is 15 NH 4 15 NO 3 (SNU, CNU). All deposition treatments received a total of 54 g N ha−1 yr−1 in deposition (as 15 NH 4 15 NO 3 or NH 4 NO 3).

The simulated N deposition applied to 4 of the 6 treatments was equivalent to approximately 54 g N ha−1 yr−1 in excess of background NDEP of either 98 atom % 15N as 15NH4 15NO3, or unlabelled NH4NO3. We aimed to keep bulk NDEP almost unaltered from ambient deposition and at the same magnitude in all N amendment treatments to allow a direct comparison between the foliar‐applied 15N label and the soil wet 15N deposition treatment with minimal effect of total N abundance relative to controls. Ammonium nitrate was chosen for the simulated NDEP, as it contains both mineral ions typically found in N deposition. This treatment was applied in deionized (DI) water solution every 3–6 weeks from February 2013 until March 2014 as either a 0.5 L (SNU applications), or a solution of 10–15 mL (CNU application), the canopy solution being increased in volume (but not in N or 15N content) in summer 2013 to match increases in the canopy biomass of the trees (based on observed growth). On average, each month, each treatment tree receiving a labelled deposition treatment (CNU and SNU) received 81 μg 15N and each treatment tree with 15N‐litter (LITTERCNU and LITTERSNU) received 81 μg N at natural abundance. Soil treatments were sprayed onto the litter surface using a pressurized hand sprayer, while foliar applications were applied directly onto needles and twigs using a brush presoaked with treatment solution. This began at the top of the tree and continued on each branch in turn down through the canopy until the solution was exhausted, and visible drips of the solution onto the soil/litter during application were not observed. The bottle was then washed out with 10 ml rainwater and poured directly down the stem of the tree. Control water treatments (CONTROL and LITTERC) were applied directly to the litter surface in the same manner and volume as the soil applications.

Routine biomass measurements and maintenance

Routine measurements of tree growth were made every 2 months during the growing season and every 3 months outside the growing season. At each occasion, tree height was measured with a plumbline marked in centimetres, and basal diameter was measured as the mean of two calliper measurements at right angles across the stem at the litter surface. At each of these instances, deciduous leaf litter not derived from the experimental trees was removed and weeds growing in the pot were uprooted, manually shredded, and left on the soil surface, so none of the 15N in their foliage was removed from the potted system. The pots were free draining, so any 15N exported in flow through the pot was not retained.

Time series measurements

Twenty‐five needles per tree were collected from the entire canopy on 13 occasions between August 2012 and May 2014, 10 of these being after the deposition treatments began in February 2013. This number of needles was chosen as a representative sample to avoid detrimental effects of cumulative defoliation on the trees. After bud burst in May 2013, a harvest of the 2013 needle cohort was made alongside the general harvest, which specifically targeted the 2011–2012 cohorts of needles. In the first instance (May 2013), the 2013 cohort sample was a single, entire bud, but subsequent harvests were taken from the entire current cohort of biomass in the same manner as the general needle harvest. For the May 2014 measurement (when the trees were destructively sampled), this sample was taken from the entire harvested needle biomass and contained more (~100) needles. All samples were collected immediately before application of the regular N deposition treatments, to allow as much time as possible for movement of the assimilation products within the tree (in contrast to short‐term foliar 15N recovery (e.g. Wilson & Tiley, 1998), and to allow maximum system retention of the 15N remaining on leaf surfaces by either canopy uptake or washing into the soil by rain events. The harvested needles were immediately transported to the laboratory and either immediately processed (see below), or frozen at −4°C until it was convenient to dry them (usually within 7 days).

Branch and twig samples were collected twice (October 2013 and at the end of the experiment in March 2014), but only analysed in March 2014. In October, two random branches were removed per tree from (i) the current year cohort and (ii) the oldest age class of branches (which contained biomass from the 2011, 2012, 2013 and 2014 growing seasons). In March, three branches were selected from each of these two sections from the total harvest mass of the whole tree. Three – 0.75‐cm‐diameter discs containing the entire radial section (bark included) were cut from the entire length of each branch and used for isotope analysis, while the whole branch was dried to obtain dry weight. In March 2014, a similar method was used, but radial discs were collected from three different branches. Litter samples were collected every 3 months as a scoop from the litter surface and were a small fraction (< 5%) of the total litter in the pots.

Destructive sampling

The experiment was terminated at the end of March 2014, prior to the commencement of the year's growing season. After recording basal diameter and height, the mainstem was cut at the base to kill the tree and the branches immediately removed with clippers at their junction with the stem, then separated into the two age classes (2013 and older cohorts). The stem was also separated into these two sections by cutting at the divide between annual growth stages. This resulted in sections which contained the vertical growth achieved during each year but did not separate the radial growth occurring across the whole stem length. All biomass was dried in paper sacks inside a 80 °C oven until mass loss had ceased (3 days). After drying, the needles were separated from the branches and each section was weighed. The litter layer on the surface of each pot was removed using a trowel and a 7‐cm‐diameter, 20‐cm‐deep (to the base of the pot) soil core was taken from each pot at a random location between the main stem and the edge of the pot. The soil cores were separated into root and soil components while moist, and the soil was homogenized. Roots were treated as a single pool irrespective of age class, unlike above‐ground biomass. Fifteen grams of homogenized soil was dried in an 80 °C oven to prepare the soil for total 14/15N measurement as well as water content calculations based on mass loss. A further 15 g dry weight, moist subsample was fumigated for 3 days with chloroform in a vacuum oven, then extracted in 45 mL 0.05 M K2SO4 for 3 h on a 220 rpm shaker along with an unfumigated control. The extract solution was freeze‐dried, and subsamples of the salt were analysed on a CN analyser for C and N content. The remaining salt was rehydrated, if necessary adjusted in volume to deliver an appropriate amount of N for mass spectrometry when dried, and concentrated via diffusion using the PTFE‐enclosed acidified paper discs method (Stark & Hart, 1996). These discs were analysed on a SerCon Ltd. isotope ratio mass spectrometer (University of Aberdeen) for 14/15N ratio and N concentration.

Soil microbial biomass (SMB) N was calculated using N content and a KEN conversion factor of 0.54 (Brookes et al., 1985), where SMB N was (total N extracted from fumigated soil/total N extracted) * KEN. Microbial 15N was calculated from these measurements along with δ 15N of the control and fumigated pools by:

δ15NSMB=δ15NfumigatedNfumigatedδ15NunfumigatedNunfumigatedNfumigatedNunfumigated (1)

Sample processing

All biomass samples (needles, wood and roots) were washed in distilled water to remove remaining surface residues and dried in a 80 °C oven until mass loss had ceased (usually 1–2 days). Needles on the branches and twigs were removed after drying and before milling. The samples were milled on a Retch MM‐200 ball mill, in metal capsules with a single ball, until a fine powder was produced, except for the needle samples between August 2012 and February 2014, which, due to their small volume, were milled in plastic microtest tubes with two small ball bearings. A subsample of this powder (∼3 mg) was analysed for [N], 14/15N, [C] and 12/13C on the isotope ratio mass spectrometer, along with standards of known isotope abundance.

Experimental calculations and statistical analyses

We used the dry masses of the whole tree sections from March 2014 to calculate growth metrics to compare trees and to calculate an aboveground mass balance at the termination of the experiment. Rather than compare raw mass of the tree compartments, we calculated four metrics, bulking the labelled and unlabelled N deposition type combinations together to produce three treatments for bulk N regime with n = 10 [water control (CONTROL), foliar deposition (CNU), soil deposition (SNU)] to test these growth effects. The metrics calculated were above‐ground biomass (AGB, the sum of both the 2011–2012 and 2013 needle, branch and stem cohorts), AGB % Canopy (the percentage of the total biomass made up by the canopy), Canopy % Foliage (the percentage of the canopy biomass that was foliage) and height increment (length of leader at the end of the 2013 growing season as a percentage of height of tree at the end of the 2012 growing season).

The isotope analyses were performed on all six treatments where the source of 15N enrichment differed, initially with five replicates (i.e. n = 5 each, but reducing to 4 for the two treatments (CONTROL and LITTERSNU) where one plant was removed). Differences in δ 15N were analysed as linear mixed effect models where the fixed effects were time and treatment while individuals were random effects. We fitted an autoregressive moving average correlation structure to account for autocorrelation of individuals through time, using the REML method due to small sample sizes. We also allowed for a greater variation in 15N concentration later in the experiment (due to the greater cumulative application of N) by implementing a variance structure. Comparisons between treatments in these models were performed by the Tukey HSD post hoc test, and models were compared with the modified AIC (Akaike information criterion) for small sample sizes, AICc.

The mass balance was calculated using the March 2014 biomass [N], and 15N measurements, assuming that all enrichment above natural abundance was derived from the experimental treatments. Belowground compartments (litter, soil, roots, microbial extracts) were not included in the mass balance as they were not fully harvested at completion of the experiment leaving some uncertainty over their absolute masses. The mass balance calculation was made by subtracting the atom % 15N in CONTROL from observed atom % in the five 15N‐enriched treatments, to calculate 15Nexcess, using the total mass of 15N added in the deposition treatments, or estimated to be released from the litter based on a separate litterbag experiment (R.K.F. Nair et al., unpublished data), 15Nadded and the average N mass of the pool in question (N). We used equation 2 to work out the total 15N recovery, 15Nrecovery (%), with uncertainty propagated fully to take into account uncertainty in original measurements and averages.

15Nrecovery(%)=15NexcessN15Nadded100 (2)

Overall ΔC/ΔN calculations

To calculate ΔC/ΔN from our treatments, we modified the calculations from the (Nadelhoffer et al., 1999) meta‐analysis of tracer studies. These calculations estimate an overall C effect of Ndep by partitioning total NDEP inputs between different ecosystem pools based on observed 15N tracer return. The NDEP assigned to each pool was multiplied by the C/N ratio of the pool to generate an overall C effect due to the Ndep inputs, which can be divided by the total Ndep to estimate a ΔC/ΔN effect. We used the same C/N values as (Nadelhoffer et al., 1999), which are generous towards tree pools (tending to be high), and applied them to simple, generalized (woody, nonwoody and soil) biomass pools. We altered the N assignment among tree and soil pools to match the values we calculated in the mass balance for the canopy‐targeting (CNU) and soil‐targeting (SNU) 15N deposition treatments, defining woody biomass as all stem wood and 2011–2012 branches, and nonwoody biomass as all needles and 2013 branches. We split the remaining N not acquired by the tree in the same ratio (7:1) between soil, and leaching and gaseous losses as found in Nadelhoffer et al. (1999). In the case of the CNU treatment, this assumed that exposure of the canopy to excess 15N did not affect soil partitioning of the isotope (due to background ambient NDEP, all treatments received a canopy load of N) and that expressed isotope abundance in the tree in this treatment included contributions from both potential canopy uptake and via the roots from the soil.

Results

Needle time series

Differences in 15N concentrations between the 15N‐labelled NDEP treatments (CNU and SNU) and the water control were apparent within 1 month of the deposition treatments beginning (Fig. 2). The δ 15N of needles in cohorts present before initiation of the experiment (2011–2012) in the 15N deposition treatments increased over time, to about 120% (CNU) or 38% (SNU) by April 2014, while the CONTROL treatment remained consistently close to natural abundance (~−3.5%). Over this period, the corresponding needles in the 15N litter treatments (LITTERC, LITTERSNU, LITTERCNU) did not display a trend in enrichment, although variability was very high in these treatments, especially early in the growing season. Treatment, date and the treatment:date interaction were all significant (P < 0.001) in explaining changes in 15N enrichment. CNU (post hoc Tukey HSD, P < 0.001) was significantly different than all other treatments, and SNU (P < 0.05) was significantly different from the CONTROL, but not the other 15N treatments (Table 2). In the most parsimonious model, the correlation structure did not improve the model fit.

Figure 2.

Figure 2

δ 15N (%) of needles older than the 2013 cohort from 15N‐labelled deposition treatments (a) and 15N‐labelled litter treatments (b). CONTROL is shown on both plots (white circles); on (a), plot treatments are CNU (red circles) and SNU(orange circles); and on (b), plot treatments are LITTERCNU (dark blue triangles), LITTERSNU (light blue triangles) and LITTERC (grey triangles). Error bars show standard error of the mean (n = 5).

Table 2.

Tukey HSD comparisons among treatments in the most parsimonious mixed effect model for the 2011–2012 cohort needles 15N abundance over time

CONTROL LITTERC LITTERSNU LITTERCNU SNU
LITTERC 0.06 / / / /
LITTERSNU 0.16 −0.11 / / /
LITTERCNU 0.08 0.02 0.08 / /
SNU 0.42 * 0.36 0.25 0.33 /
CNU 1.08*** 1.02*** 0.91*** 0.99*** 0.66***

The numbers in the table give the mean difference between each set of treatments (columns–rows).

Significance at P < 0.05 level indicated by *, at P < 0.001 level by***.

N concentration of the 2011–2012 needles fluctuated with an overwinter peak in N concentration in both 2013 and 2014, although peak [N] was not as great in the second year. This periodicity was not observed in the 2013 cohort of needles, which had their highest N concentration (~0.75%) soon after budburst, but did not peak over the winter (Fig. 3).

Figure 3.

Figure 3

N content by dry mass (%) of needles from all treatments from 2013 cohort (a) and 2011–2012 cohort (b). While a yearly cycle is observed, this does not differ between treatments. Treatments are shown with same symbology as Fig. 2. Error bars show standard error of the mean (n = 5).

In the 2013 cohort of needles, the 15N enrichment was greater than the CONTROL in both CNU and SNU (Fig. 4a), and also in LITTERCNU (Fig. 4b), although in this latter treatment this was due to a single individual which consistently displayed a high needle 15N enrichment. While this difference between treatments in the 2013 cohort of needles was significant (P < 0.05) along with time (P < 0.0001), there was no interaction term or correlation structure in the model with the lowest AICc, and the high variation in 15N concentration meant that only the SNU vs. CONTROL comparison was significant (post hoc Tukey HSD, P = 0.008) (Table 3).

Figure 4.

Figure 4

δ 15N (%) of 2013 needle cohort from 15N‐labelled deposition (a) and 15N‐labelled litter treatments (b). CONTROL is shown on both plots (white circles); on (a), treatments are CNU (red circles), and SNU (orange circles); and on (b), plot treatments are LITTERCNU (dark blue triangles), LITTERSNU (light blue triangles) and LITTERC (grey triangles). Error bars show standard error of the mean (n = 5).

Table 3.

Tukey HSD comparisons among treatments in most parsimonious mixed effect 15N abundance model for 2013 cohort needle 15N abundance over time

CONTROL LITTERC LITTERSNU LITTERCNU SNU
LITTERC 0.003 / / / /
LITTERSNU 0.004 0.001 / / /
LITTERCNU 0.013 0.009 0.009 / /
SNU 0.023** 0.02a 0.020b 0.011 /
CNU 0.017 0.014 0.019 0.014 −0.006

The numbers in the table give the mean difference between each set of treatments (columns–rows).

Significance at P < 0.01 level indicated by**.

Borderline significant differences are represented by a, indicating P = 0.086, and b, P = 0.072.

Destructive harvest

The two trees which died were in the CONTROL, and LITTERSNU, reducing their sample size to 4 from autumn 2013 until the destructive harvest. At harvest, there were no significant differences among the groupings of N treatments (CONTROL LITTERCONTROL n = 9, SNU/LITTERSNU n = 9, CNU LITTERCNU n = 10) in any of the four above‐ground biomass variables. Across the whole experiment, above‐ground biomass was 370 ± 119 g (SD) per tree, 74 ± 5 (SD) % of this being canopy, while the canopy was 38 ± 2 (SD) % needles by mass. The trees gained on average 12.4 ± 5.8 (SD) % of their initial height over the 2013 growing season, while litter mass at the end of the experiment was 65.5 ± 33.3 (SD) % of the original dry mass applied.

The 15N content of the major above‐ground biomass components (Table 4 and Table 5) varied among treatments. There were significant treatment effects in both 2013 (P < 0.005) and 2011–2012 (P < 0.001) needle cohorts, stem cohorts (P < 0.001, P < 0.001) and the 2013 branch cohort (P < 0.005), but not the 2011–2012 branch cohort. CNU significantly differed from the other treatments in the stem and branch sections (P < 0.001), as well as the 2011–2012 needles (P < 0.001). In both the 2011–2012 and the 2013 needle cohorts, all five 15N labelled treatments were significantly different from the CONTROL (P < 0.001) at harvest.

Table 4.

Mean δ 15N % in 2011–2012 cohort tree compartments after 16 months

Needles Branches Stem Roots
CONTROL 0.2 ± 2a 0.5 ± 0a 27.5 ± 5a 4.6 ± 3
LITTERC 8.1 ± 2b 13.6 ± 13a 45.9 ± 11a 27.4 ± 4
LITTERSNU 36.5 ± 12b 4.5 ± 4a 268.2 ± 8 6a 77.7 ± 24
LITTERCNU 15.5 ± 5b 8.7 ± 5a 32.6 ± 7a 41.1 ± 46
SNU 36.4 ± 13b 0.4 ± 0a 111 ± 25a 67.5 ± 40
CNU 117.2 ± 17b 18.1 ± 13b 354.1 ± 77b 22.8 ± 10

Values shown ± standard deviation (n = 5).

Lowercase letters indicate significant differences (Tukey HSD) among treatments for the same pool at the P < 0.05 level or higher.

Table 5.

Mean δ 15N % in 2013 cohort tree compartments after 16 months

Needles Branches Stem
CONTROL 4.7 ± 3a 4.2 ± 3a 3.9 ± 1a
LITTERC 9.5 ± 3b 48.0 ± 35a 19.7 ± 21a
LITTERSNU 25.4 ± 4b 48.5 ± 26a 59.4 ± 44a
LITTERCNU 53.4 ± 25b 25.7 ± 16a 23.9 ± 10a
SNU 97.7 ± 32b 32.5 ± 32a 100.1 ± 64a
CNU 74.9 ± 9b 221 ± 37b 569.1 ± 167b

Values shown ± standard deviation (n = 5).

Lowercase letters indicate significant differences (Tukey HSD) among treatments for the same pool at the P < 0.05 level or higher.

Root δ 15N was not statistically different among treatments [mean N % was 0.55 ± 0.15 (SD), mean δ 15N 40 ± 36% (SD)], and although P was > 0.05, the lowest mean δ 15N was found in the CONTROL [4 ± 3% (SD)] and the highest δ 15N in the N manipulation (SNU, CNU, LITTERSNU, LITTERCNU) treatments (Table 4). Likewise, total soil δ 15N did not statistically differ among treatments [mean soil δ 15N was 38.1 ± 37% (SD)], but mean δ 15N % was lower in the CONTROL [δ 15N 16.9 ± 20 (SD)] than the labelled treatments [combined mean δ 15N 42.9 ± 39% (SD)]. Individually, CNU δ 15N [41.4 ± 48% (SD)] was lower than SNU δ 15N [59.2 ± 21% (SD)], but this difference was small and nonsignificant.

There were no statistical differences in total N extractable from 0.05 M K2SO4 unfumigated extracts between treatments (mean = 0.010 mg g−1 dry soil), nor between the N content of microbial biomass (P > 0.05), which was highly variable and estimated at 0.041 ± 0.03 mg g−1 soil. Microbial δ 15N calculated from the fumigations was very variable and was not related to treatment, and there was also no statistical difference between treatments in bulk soil 15N.

Mass balance estimates of aboveground 15N recovery

The highest above‐ground recoveries of the 15N label from the mass balance were 60.14 ± 5.7% (SD) in CNU and 20.28 ± 6.9% in SNU. These two treatments recovered quantities of 15N significantly (P < 0.001 CNU, P < 0.01 SNU, respectively) greater than CONTROL (Table 6). 15N recovery was highest in the 2013 and 2011–2012 needles, and 2011–2012 stems in these treatments.

Table 6.

15N recovery as % of total applied 15N in the aboveground sections (n = 5 for each section) of the two labelled deposition treatments

CNU SNU
2013 Needles 7.17 ± 3.04% 9.50 ± 3.40%
2011–2012 Needles 13.41 ± 2.40% 3.94 ± 2.66%
2013 Branches 20.77 ± 2.86% 4.82 ± 3.46%
2011–2012 Branches 3.12 ± 0.14% 0.02 ± 0.07%
2013 Stem 1.04 ± 0.04% 0.21 ± 0.02%
2011–2012 Stem 14.64 ± 3.15% 2.78 ± 4.04%
Total Woody Biomass 18.80 ± 3.15% 3.01 ± 4.04%
Total Above Ground 60.14 ± 5.75% 21.28 ± 6.85%

Also presented are total accountancy in woody sections (stem and 2011–2012 branches, but not 2013 branches) and total 15N recovery aboveground. Errors terms are standard deviation obtained by propagating the error in measurements of different pools while total recovery and error are obtained by summing the recovery and propagating the error of individual pools making up the total.

When we calculated litter N release based on field litterbag decomposition rates (R.K.F. Nair et al. unpublished data) and total mass of litter applied, calculated 15N recovery was very low and never significantly different from the CONTROL. Even when we revised these low rates based on more conservative literature values (Titus & Malcolm, 1999; van Huysen et al., 2013), these remained small, displaying a low gross aboveground 15N return and high uncertainty (LITTERC 9.62 ± 6.54%, LITTERSNU 12.59 ± 6.4% and LITTERCNU 11.52 ± 6.1%) and were not taken forward to calculate ΔC/ΔN, nor shown in Table 6.

ΔC/ΔN calculations

When propagated, the overall C sink effect from SNU was 44.2 ± 18 kg C kg N−1, split between trees and soil (Table 7). This sink was similar to that from Nadelhoffer et al. (1999) and had a large standard deviation (18 kg C kg N−1), which was mainly due to the high uncertainty on stem assignment in this treatment (Table 6). In contrast, the ΔC/ΔN estimate from CNU was 113.9 ± 16 kg C kg N−1, more than double the estimates from Nadelhoffer et al. (1999), and more than 2.5 times the one drawn from our soil treatment. This was due to a high overall N return (46% of N in nonwoody pools and 18% in woody pools, Table 6), and an assumption of correspondingly lowered 15N assignment to the soil, resulting in a slightly smaller soil ΔC/ΔN.

Table 7.

Values of calculated ΔC/ΔN effect following (Nadelhoffer et al., 1999) and from the results of the two labelled deposition treatments of this experiment

Meta‐analysis of soil 15N applications (Nadelhoffer et al., 1999) Soil deposition (SNU) Canopy deposition (CNU)
Tree 28.8 23.8 ± 18 104.6 ± 16
Soil 21 20.4 ± 2 9.4 ± 2
Total 49.8 44.2 ± 18 113.9 ± 16

The overall budgets presented in Nadelhoffer et al. (1999) were adjusted by altering the woody and nonwoody pools to match the values measured in our experiment (Table 6), with additional N drawn proportionally from soil (forest floor + mineral) and leaching + gaseous losses. Our woody pools were both stem pools, and 2011–2012 branches, while our nonwoody pools were the needle pools and 2013 branches. Errors are standard deviations from our study propagated with C/N ratios of Nadelhoffer et al. (1999).

Discussion

In this controlled mesocosm study, we find canopy‐targeted N fertilization (and hence ambient rates of CNU) can result in around three times as much 15N tracer recovery aboveground as soil‐targeted N fertilization. Within trees, we find a four times higher 15N retention in wood (Table 6), indicating that N from CNU may favour this high C/N biomass. Otherwise, 15N recovery in our soil‐targeted treatment is similar to meta‐analyses showing about 20% above‐ground 15N recovery, with < 5% in wood in field experiments (Nadelhoffer et al., 1999; Templer et al., 2012a) as represented in global models which build on or closely reproduce such isotope‐derived data (e.g. Thomas et al., 2013). Thus, our results show that by omitting canopy uptake of N at ambient deposition rates, common methodologies could substantially underestimate a woody response to NDEP.

Contribution of canopy nitrogen uptake to ΔC/ΔN

We are aware of only one study (Dail et al., 2009) using a 15N tracer in the field at the forest canopy scale. Results from most other experiments must be carefully interpreted as NDEP interacts with multiple leaves and branches as it passes through the canopy (Boyce et al., 1996), and N partitioning between biomass pools with different C/N ratios may occur on alongside phenological cycles in nutrient content (Millard & Grelet, 2010). Many CNU experiments last less than a year (Bowden et al., 1989; Eilers et al., 1992; Wilson & Tiley, 1998), consider limited microcosm systems (e.g. Lumme, 1994) or single branches (e.g. Vose & Swank, 1990; MacKlon et al., 1996). Elsewhere ‘natural experiments’ with an ambient 15N source (Friedland et al., 1991; Ammann et al., 1999) may not recover 15N from the whole tree, preventing inference of total 15N recovery. Notably, Dail et al. (2009) found bark (including epiphytic mosses and lichen) to be a major sink (45% recovery of 15NO3), rather than higher C/N bolewood and calculated a low C effect (8 kg kg N−1). We could not reliably separate bolewood from bark due to the size of our trees, but high 15N recoveries were observed in the stem when most of the CNU treatment was applied to the canopy. A small amount of the isotope solution was washed down the stem by both the dilution of any residue left in the treatment bottles (to add the entire 15N dose to the system) as well as from the canopy by ambient rainfall, but we expect this to be only a small part of the total 15N added. Therefore, mobilization of N from CNU within the tree, rather than bark surface absorption (c.f. Reiners & Olson, 1984; Dail et al., 2009) likely contributed to this stem response.

Needle N dynamics and mobilization to the active internal N cycling pool are phenologically controlled in species such as Sitka spruce (Millard & Grelet, 2010). In conifers, N is stored overwinter in the previous year's needles (Millard & Proe, 1992), while deciduous species store N in stems and roots or inner bark (Millard & Grelet, 2010). Remobilization of this N may contribute 9–46 % of N for new shoot growth (Millard & Proe, 1992), independent of soil N supply (Millard & Proe, 1993; Weatherall et al., 2006b). As our needle N was relatively conserved over the 2013–2014 winter in both needle age cohorts (Fig. 3), the high endpoint stem recovery in CNU was unlikely to be due to seasonally mobilized 15N in the phloem rather than actual assignment to this pool. The high ΔC/ΔN from this treatment (113.9 kg C kg N−1) assumes transport within the tree and N attribution to wood growth where high C/N ratios drive the response.

For our ΔC/ΔN calculations, we clumped canopy interception and CNU together, assuming that all NDEP was intercepted on canopy surfaces and could be acquired across the canopy. N not acquired by the canopy was assumed available for uptake via root pathways and allocated between soil and losses (leaching) as in SNU. This discounted uptake of 15N washed out of the canopy in the CNU treatment and subsequently taken up the roots as we could not distinguish these pathways via 15N isotope recovery. Total CNU would scale with canopy cover and NDEP interception, which in our canopy treatment was effectively ~ 100%, and so, we may overestimate the ΔC/ΔN effect of wet deposition. Dezi et al. (2010) used 60% N retention by the canopy (Chopping et al., 2008) and 80% uptake of this N by CNU (Sievering et al., 2007) to incorporate CNU into the G'DAY model, while Gaige et al. (2007) calculated a canopy N retention of > 70%. The 114 kg C kg N−1 for CNU would drop to 78 kg C kg N−1 with 60% N retention by the canopy; approximately 60% increase over SNU. Additional sensitivity analyses of the 114 kg C kg N−1 ΔC/ΔN are robust to the assumptions made in modifying calculations from Nadelhoffer et al. (1999) by changing the gross 15N uptake observed and overall within‐tree partitioning, and are shown in supplementary materials S1.

Soil system and litter 15N recovery

The canopy harvest at the close of the experiment indicated that some litter 15N had been taken up by trees as total 15N recoveries in both 2011–2012 and 2013 needles that were significantly greater than CONTROL in all three LITTER treatments. However, over time the LITTER 15N recovery above ground was low, with a large heterogeneity early in the experiment. This did not correlate with individual source trees nor treatment replicates, but LITTER 15N may have been more heterogeneously distributed between biomass age classes than CNU or SNU and unable to be captured by the lower number of needle replicates at this time and lower cumulative 15N additions. Nonetheless, Weatherall et al. (2006a) found only < 2.5% of N released from litter was retained in Sitka Spruce seedlings and other experiments using labelled litter are sparse (Hatton et al., 2012), but find similar aboveground recoveries, for example 2% of Fagus sylvatica litter 15N (Zeller & Colin‐Belgrand, 2001) over 4 years. 15N‐labelled litters from evergreen species cannot be collected in a single seasonal litterfall event, and, in this study, were harvested from felled trees labelled in a previous experiment. This methodology produces litters that have not naturally senesced and hence may have higher C:N ratios than natural litterfall. Our litters were harvested in November and may have also been N enriched due to storage (Millard & Grelet, 2010). It is unknown how these differences in litter stoichiometry may have affected systematic 15N recovery.

Similarly, despite strong aboveground 15N response from CNU and SNU, our deposition 15N inputs were not statistically detectable in the soil or roots. Between SNU and CNU, this was particularly surprising as it was expected that more 15N would have been taken up by roots when applied directly to the soil. However, plant N is usually transported as amino acids and is present in the xylem because of remobilization from N stores such as needles (Millard, 1996), senescence or because of xylem–phloem–xylem recycling in the roots (Marschnert et al., 1997). CNU‐obtained N may therefore have been transported to the roots for recycling leading to similar 15N concentrations in the CNU and SNU treatments.

How general are the results?

The low NDEP magnitude employed here was chosen to match 15N release from litter and inorganic applications and allowed a 15N trace at concentrations close to ambient nitrogen deposition. Physiological effects of NDEP are well known (Schaberg et al., 1997; Elvir et al., 2006), but understanding the C response is difficult at ambient NDEP levels. N manipulations usually raise N inputs so a response can be detected, and even with doses close to ambient total inputs, application rates differ from ambient deposition (Lovett & Goodale, 2011; Thomas et al., 2013). Our treatment (54 g N ha−1 yr−1) was several orders of magnitude less than typical experimental N treatments (e.g. Wallenstein et al., 2006; Gaige et al., 2007; Metcalfe et al., 2013) and was designed to avoid physiological responses to the treatment. Templer et al. (2012a) found a negative correlation between N addition rate and 15N recovery, but the sum of our total (ambient + manipulation) N inputs is less than the smallest N amendment in this study making comparisons difficult. This may have led to our trees being N deficient; Binns et al. (1980) suggest that healthy spruce needles are > 1.2% N by dry mass, and needle N concentrations were lower in the second winter of our experiment (Fig. 3), although there were no signs of deficiency (such as needle decolouration) in most individuals. Hence, high recovery of 15N under CNU could be a result of low N availability and a relatively high ability to respond in biomass N content without limits imposed by other factors (Fleischer et al., 2013). Conifers may also only respond in photosynthetic capacity to N at deposition rates up to 8 kg ha−1 yr−1 (Fleischer et al., 2013), which if applicable to our trees, mean CNU could be replacing, rather than supplementing ambient N nutrition. We assumed that this response was not limiting in our calculations, and even if a limit on photosynthesis response is reached, ΔC/ΔN may still increase via other mechanisms. For example, below‐ground C allocation may decrease under N deposition (Nadelhoffer, 2000; Janssens et al., 2010) as N scavenging becomes more efficient. Testing differences in allocation would be possible using a CNU treatment where all throughfall is removed before reaching the soil system so only a canopy 15N source is available.

Both 15N studies (Templer et al., 2012a) and forest inventory data (Thomas et al., 2009; Templer et al., 2012b) also suggest that N effects on growth are species specific, and potentially limited in evergreen needleleaf trees (Thomas et al., 2009). This contrasts with the large inferred effect of CNU the Picea sitchensis saplings in our study. Proportion of woody biomass increases with tree age (Helmisaari et al., 2002; Peichl & Arain, 2007), but the annual growth increment is a progressively smaller proportion of total biomass (Stephenson et al., 2014). Thus, similar strong CNU ΔC/ΔN effects in mature trees depend on sustained allocation in the observed pattern as trees age.

Also, comparatively little is known about dry NDEP, and it is also difficult to assess how CNU of wet and dry forms of N additions may compare if they differ in canopy interception and uptake capacity. Canopy uptake of these forms is likely to depend both on type of N input as well as individual species physiology; in the case of diffusion of 15 NH4+ or 15 NO3 ions, this depends on leaf cuticle charge and/or stomatal conductance [see Sparks (2009)]. Differing rates of incorporation among tissues, such as between needle age classes in our experiment, could also be explained by differences in these factors. Future experiments with only labelled cations or anions, physiological stresses or alternate deposition methodologies could give further insight over these mechanisms.

Implications for regional and global C sequestration

Aside from methodological concerns, we can still question how accurately uptake rates from experiments on single species can be scaled to compare with correlative analyses (e.g. Magnani et al., 2007; Thomas et al., 2009) and global models (e.g. Thomas et al., 2013). Most research on CNU has focused on wet deposition on evergreen conifers (e.g. Eilers et al., 1992; Lumme, 1994; Dail et al., 2009) and often on young trees (Bowden et al., 1989; Eilers et al., 1992; Lumme, 1994), and high correlative ΔC/ΔN responses come from widely distributed forests containing both broadleaf and evergreen trees, which may substantially differ in many relevant physiological traits (Adriaenssens et al., 2010).

Process‐based models provide a useful tool to upscale physiological understanding of mechanisms. Available global models representing the N effects on C uptake differ in their representation of plant N acquisition, with N uptake being driven by plant stoichiometry (Thornton et al., 2007), C assignment to roots (Zaehle & Friend, 2010) and N availability in soil pools. N uptake also occurs after soil immobilization demands are met (Gerber et al., 2010; Thomas et al., 2013). Such models are typically calibrated against long‐term N tracer and fertilization experiments where N is added to the soil (e.g. Thomas et al., 2013). These models may represent the fraction of N which reaches the soil surface, but if CNU is as substantial as indicated in our study, they may overestimate the size of NDEP inputs to the soil, and simultaneously underestimate the total N acquired by trees. If this is the case the expected root uptake decreases (due to reduced soil N availability), but total tree N uptake increases via CNU (as this N is first available to trees). In addition, we showed that this N may be assigned to high C:N wood, enhancing the C sequestration effect from this alternative source of N over conventional patterns of allocation. Aside from variation due to species, deposition type and dosage effects, constraints on CNU may be stoichiometric or depend on physiological drivers (e.g. of ion exchange) and require additional work to fully understand.

Nonetheless, our study demonstrates experimentally that CNU may account for at least some of the increased C effect of N deposition shown in correlative studies (Magnani et al., 2007; Thomas et al., 2009; Ferretti et al., 2014) over conventional 15N experiments (Nadelhoffer et al., 1999; Templer et al., 2012a) and understanding N deposition purely in terms of its effect on the soil system may substantially underestimate ecosystem‐level N effects. We recommend that CNU be investigated at realistic levels and across representative species to understand its potential importance in forest C sequestration and the necessity to include this in large scale models. To properly assess the impact of N deposition on C sequestration, it is vital that real‐world conditions are represented in the experiments which inform this understanding.

Supporting information

Appendix S1 Materials.

Acknowledgements

We thank Archie Crofton and Radina Atanasova (University of Edinburgh), as well as Colin McEvoy and Carina Convery (Forest Research, UK) for field and technical assistance. We would like to thank Bill Mason (Forest Research UK) for access to the Gisburn Forest tree species trial. Isotope analyses were performed by Nick Morley at the University of Aberdeen, UK. This work was funded by the UK Natural Environment Research Council (NERC), grant NE/G00725 X/1 and Forestry Commission, UK. Funding to pay the open access cost of this publication was provided by NERC.

References

  1. Adriaenssens S, Staelens J, Wuyts K et al (2010) Foliar nitrogen uptake from wet deposition and the relation with leaf wettability and water storage capacity. Water, Air & Soil Pollution, 219, 43–57. [Google Scholar]
  2. Allison FE (1965) Decomposition of Wood and Bark Sawdusts in Soil, Nitrogen Requirements and Effects on Plants. US Dept. of Agriculture, Washington, DC. [Google Scholar]
  3. Ammann M, Siegwolf R, Pichlmayer F (1999) Estimating the uptake of traffic‐derived NO2 from 15N abundance in Norway spruce needles. Oecologia, 118, 124–131. [DOI] [PubMed] [Google Scholar]
  4. Binns WO, Mayhead G, MacKenzie JM (1980) Nutrient Deficiencies of Conifers in British Forests an Illustrated Guide – Forestry Commisson Leaflet 76. HM Stationary Office, London. [Google Scholar]
  5. Bowden R, Geballe G, Bowden W (1989) Foliar uptake of 15N from simulated cloud water by red spruce (Picea rubens) seedlings. Canadian Journal of Forest Research, 19, 382–386. [Google Scholar]
  6. Boyce RL, Friedland AJ, Chamberlain CP, Poulson SR (1996) Direct canopy nitrogen uptake from 15N‐labelled wet deposition by mature red spruce. Canadian Journal of Forest Research, 26, 1539–1547. [Google Scholar]
  7. Brookes P, Landman A, Pruden G, Jenkinson D (1985) Chloroform fumigation and the release of soil nitrogen: a rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biology and Biochemistry, 17, 837–842. [Google Scholar]
  8. Chiwa M, Crossley A, Sheppard LJ, Sakugawa H, Cape JN (2004) Throughfall chemistry and canopy interactions in a Sitka spruce plantation sprayed with six different simulated polluted mist treatments. Environmental Pollution, 127, 57–64. [DOI] [PubMed] [Google Scholar]
  9. Chopping M, Moisen GG, Su L, Laliberte A, Rango A, Martonchik JV, Peters DPC (2008) Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro‐Radiometer. Remote Sensing of Environment, 112, 2051–2063. [Google Scholar]
  10. Churchland C, Weatherall A, Briones MJI, Grayston SJ (2012) Stable‐isotope labeling and probing of recent photosynthates into respired CO2, soil microbes and soil mesofauna using a xylem and phloem stem‐injection technique on Sitka spruce (Picea sitchensis). Rapid Communications in Mass Spectrometry, 26, 2493–2501. [DOI] [PubMed] [Google Scholar]
  11. Clement R (2004) Mass and energy exchange of a plantation forest in Scotland using micrometeorological methods. Unpublished PhD Thesis, University of Edinburgh. [Google Scholar]
  12. Currie WS, Nadelhoffer KJ, Aber JD (2004) Redistributions of 15N highlight turnover and replenishment of mineral soil organic N as a long‐term control on forest C balance. Forest Ecology and Management, 196, 109–127. [Google Scholar]
  13. Dail DB, Hollinger DY, Davidson EA, Fernandez I, Sievering HC, Scott NA, Gaige E (2009) Distribution of nitrogen‐15 tracers applied to the canopy of a mature spruce‐hemlock stand, Howland, Maine, USA. Oecologia, 160, 589–599. [DOI] [PubMed] [Google Scholar]
  14. De Vries W, Reinds GJ, Gundersen P, Sterba H (2006) The impact of nitrogen deposition on carbon sequestration in European forests and forest soils. Global Change Biology, 12, 1151–1173. [Google Scholar]
  15. De Vries W, Solberg S, Dobbertin M et al (2008) Ecologically implausible carbon response? Nature, 451, E1–E3; discussion E3‐4. [DOI] [PubMed] [Google Scholar]
  16. Dezi S, Medlyn BE, Tonon G, Magnani F (2010) The effect of nitrogen deposition on forest carbon sequestration: a model‐based analysis. Global Change Biology, 16, 1470–1486. [Google Scholar]
  17. Eilers G, Brumme R, Matzner E (1992) Above‐ground N‐uptake from wet deposition by Norway spruce (Picea abies Karst.). Forest Ecology and Management, 1, 239–247. [Google Scholar]
  18. Elvir JA, Wiersma GB, Day ME, Greenwood MS, Fernandez IJ (2006) Effects of enhanced nitrogen deposition on foliar chemistry and physiological processes of forest trees at the Bear Brook Watershed in Maine. Forest Ecology and Management, 221, 207–214. [Google Scholar]
  19. Etzold S, Waldner P, Thimonier A, Schmitt M, Dobbertin M (2014) Tree growth in Swiss forests between 1995 and 2010 in relation to climate and stand conditions: recent disturbances matter. Forest Ecology and Management, 311, 41–55. [Google Scholar]
  20. Ferretti M, Marchetto A, Arisci S et al (2014) On the tracks of Nitrogen deposition effects on temperate forests at their southern European range – an observational study from Italy. Global Change Biology, 20, 3423–3438. [DOI] [PubMed] [Google Scholar]
  21. Fleischer K, Rebel KT, Van Der Molen MK et al (2013) The contribution of nitrogen deposition to the photosynthetic capacity of forests. Global Biogeochemical Cycles, 27, 187–199. [Google Scholar]
  22. Friedland A, Miller E, Battles J, Thorne J (1991) Nitrogen deposition, distribution and cycling in a subalpine spruce‐fir forest in the Adirondacks, New York, USA. Biogeochemistry, 14, 31–55. [Google Scholar]
  23. Gaige E, Dail DB, Hollinger DY et al (2007) Changes in canopy processes following whole‐forest canopy nitrogen fertilization of a mature Spruce‐Hemlock forest. Ecosystems, 10, 1133–1147. [Google Scholar]
  24. Galloway J, Dentener F, Capone D (2004) Nitrogen cycles: past, present, and future. Biogeochemistry, 70, 153–226. [Google Scholar]
  25. Garten CTJ, Bondietti EA, Lomax RD (1988) Contribution of foliar leaching and dry deposition to sulfate in net throughfall below deciduous trees. Atmospheric Environment, 22, 1425–1432. [Google Scholar]
  26. Gartner TB, Cardon ZG (2004) Decomposition dynamics in mixed‐species leaf litter. Oikos, 104, 230–246. [Google Scholar]
  27. Gerber S, Hedin LO, Oppenheimer M, Pacala SW, Shevliakova E (2010) Nitrogen cycling and feedbacks in a global dynamic land model. Global Biogeochemical Cycles, 24, GB1001. [Google Scholar]
  28. Goodale C, Apps M, Birdsey R (2002) Forest carbon sinks in the Northern Hemisphere. Ecological Applications, 12, 891–899. [Google Scholar]
  29. Hanson PJ, Garten CT (1992) Deposition of H15NO3 vapor to white oak, red maple, and loblolly pine foliage: experimental observations and a generalized model. New Phytologist, 122, 329–337. [DOI] [PubMed] [Google Scholar]
  30. Hatton P‐J, Kleber M, Zeller B et al (2012) Transfer of litter‐derived N to soil mineral–organic associations: evidence from decadal 15N tracer experiments. Organic Geochemistry, 42, 1489–1501. [Google Scholar]
  31. Helmisaari HS, Makkonen K, Kellomaki S, Valtonen E, Malkonen E (2002) Below‐ and above‐ground biomass, production and nitrogen use in Scots pine stands in eastern Finland. Forest Ecology and Management, 165, 317–326. [Google Scholar]
  32. Högberg P (2012) What is the quantitative relation between nitrogen deposition and forest carbon sequestration? Global Change Biology, 18, 1–2. [Google Scholar]
  33. Holland E, Dentener F, Braswell B, Sulzman J (1999) Contemporary and pre‐industrial global reactive nitrogen budgets. Biogeochemistry, 46, 7–43. [Google Scholar]
  34. van Huysen TL, Harmon ME, Perakis SS, Chen H (2013) Decomposition and nitrogen dynamics of 15N‐labeled leaf, root, and twig litter in temperate coniferous forests. Oecologia, 173, 1563–1573. [DOI] [PubMed] [Google Scholar]
  35. Janssens IA, Dieleman W, Luyssaert S et al (2010) Reduction of forest soil respiration in response to nitrogen deposition. Nature Geoscience, 3, 315–322. [Google Scholar]
  36. Klemm O, Kuhn U, Beck E et al (1989) Leaching and uptake of ions through above‐ground Norway spruce tree parts In: Forest Decline And Air Pollution: A Study of Spruce (Picea abies) on Acid Soils (ed. Schulze ED.), pp. 210–237. Springer Verlag, London, Berlin. [Google Scholar]
  37. Lebauer D, Treseder K (2008) Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. Ecology, 89, 371–379. [DOI] [PubMed] [Google Scholar]
  38. Lovett GM, Goodale CL (2011) A new conceptual model of nitrogen saturation based on experimental nitrogen addition to an oak forest. Ecosystems, 14, 615–631. [Google Scholar]
  39. Lumme I (1994) Nitrogen uptake of Norway spruce (Picea abies Karst.) seedlings from simulated wet deposition. Forest Ecology and Management, 63, 87–96. [Google Scholar]
  40. MacKlon AES, Sheppard LJ, Sim A, Leith ID (1996) Uptake of ammonium and nitrate ions from acid mist applied to Sitka spruce [Picea sitchensis (Bong.) Carr.] grafts over the course of one growing season. Trees, 10, 261–267. [Google Scholar]
  41. Magnani F, Mencuccini M, Borghetti M et al (2007) The human footprint in the carbon cycle of temperate and boreal forests. Nature, 447, 848–850. [DOI] [PubMed] [Google Scholar]
  42. Magnani F, Mencuccini M, Borghetti M et al (2008) Magnani et al. reply. Nature, 451, E‐3. [Google Scholar]
  43. Marschnert H, Kirkby EA, Engels C (1997) Importance of cycling and recycling of mineral nutrients within plants for growth and development Botanica Acta, 110, 265‐273. [Google Scholar]
  44. Maurice C, Crang R (1986) Increase in Pinus strobus needle transectional areas in response to acid misting. Archives of Environmental Contamination and Toxicology, 82, 77–82. [Google Scholar]
  45. McNulty SG, Aber JD, Newman SD (1996) Nitrogen saturation in a high elevation New England spruce‐fir stand. Forest Ecology and Management, 84, 109–121. [Google Scholar]
  46. Metcalfe DB, Eisele B, Hasselquist NJ (2013) Effects of nitrogen fertilization on the forest floor carbon balance over the growing season in a boreal pine forest. Biogeosciences, 10, 8223–8231. [Google Scholar]
  47. Millard P (1996) Ecophysiology of the internal cycling of nitrogen for tree growth. Journal of Plant Nutrition and Soil Science, 159, 1–10. [Google Scholar]
  48. Millard P, Grelet G‐A (2010) Nitrogen storage and remobilization by trees: ecophysiological relevance in a changing world. Tree Physiology, 30, 1083–1095. [DOI] [PubMed] [Google Scholar]
  49. Millard P, Proe MF (1992) Storage and internal cycling of nitrogen in relation to seasonal growth of Sitka spruce. Tree Physiology, 10, 33–43. [DOI] [PubMed] [Google Scholar]
  50. Millard P, Proe MF (1993) Nitrogen uptake, partitioning and internal cycling in Picea sitchensis (Bong.) Carr. as influenced by nitrogen supply. New Phytologist, 125, 113–119. [DOI] [PubMed] [Google Scholar]
  51. Nadelhoffer K (2000) The potential effects of nitrogen deposition on fine‐root production in forest ecosystems. New Phytologist, 147, 131–139. [Google Scholar]
  52. Nadelhoffer KJ, Emmett BA, Gundersen P et al (1999) Nitrogen deposition makes a minor contribution to carbon sequestration in temperate forests. Nature, 398, 145–148. [Google Scholar]
  53. Näsholm T, Kielland K, Ganeteg U (2009) Uptake of organic nitrogen by plants. New Phytologist, 182, 31–48. [DOI] [PubMed] [Google Scholar]
  54. Norby RJ, Weerasuriya Y, Hanson PJ (1989) Induction of nitrate reductase activity in red spruce needles by NO2 and HNO3 vapor. Canadian Journal of Forest Research, 19, 889–896. [Google Scholar]
  55. Peichl M, Arain MA (2007) Allometry and partitioning of above‐ and belowground tree biomass in an age‐sequence of white pine forests. Forest Ecology and Management, 253, 68–80. [Google Scholar]
  56. Reiners W, Olson R (1984) Effects of canopy components on throughfall chemistry: an experimental analysis. Oecologia, 63, 320–330. [DOI] [PubMed] [Google Scholar]
  57. Schaberg P, Perkins T, McNulty SG (1997) Effects of chronic low‐level N additions on foliar elemental concentrations, morphology, and gas exchange of mature montane red spruce. Canadian Journal of Forest Research, 1629, 1622–1629. [Google Scholar]
  58. Schulze E (2000) Carbon and nitrogen cycling in European forest ecosystems.
  59. Sievering H (1999) Nitrogen deposition and carbon sequestration. Nature, 400, 629–630. [Google Scholar]
  60. Sievering H, Tomaszewski T, Torizzo J (2007) Canopy uptake of atmospheric N deposition at a conifer forest: part I ‐canopy N budget, photosynthetic efficiency and net ecosystem exchange. Tellus Series B, 59, 483–492. [Google Scholar]
  61. Smith V, Bradford M (2003) Do non additive effects on decomposition in litter‐mix experiments result from differences in resource quality between litters? Oikos, 2, 235–242. [Google Scholar]
  62. Sparks JP (2009) Ecological ramifications of the direct foliar uptake of nitrogen. Oecologia, 159, 1–13. [DOI] [PubMed] [Google Scholar]
  63. Stark J, Hart S (1996) Diffusion technique for preparing salt solutions, Kjeldahl digests, and persulfate digests for nitrogen‐15 analysis. Soil Science Society of America Journal, 60, 1846–1855. [Google Scholar]
  64. Stephenson NL, Das AJ, Condit R et al (2014) Rate of tree carbon accumulation increases continuously with tree size. Nature, 507, 90–93. [DOI] [PubMed] [Google Scholar]
  65. Sutton MA, Simpson D, Levy PE, Smith RI, Reis S, Van Oijen M, Wim DV (2008) Uncertainties in the relationship between atmospheric nitrogen deposition and forest carbon sequestration. Global Change Biology, 14, 2057–2063. [Google Scholar]
  66. Templer PH, Mack MC, Chapin FS et al (2012a) Sinks for nitrogen inputs in terrestrial ecosystems: a meta‐analysis of 15N tracer field studies. Ecology, 93, 1816–1829. [DOI] [PubMed] [Google Scholar]
  67. Templer PH, Pinder RW, Goodale CL (2012b) Effects of nitrogen deposition on greenhouse‐gas fluxes for forests and grasslands of North America. Frontiers in Ecology and the Environment, 10, 547–553. [Google Scholar]
  68. Thomas RQ, Canham CD, Weathers KC, Goodale CL (2009) Increased tree carbon storage in response to nitrogen deposition in the US. Nature Geoscience, 3, 13–17. [Google Scholar]
  69. Thomas RQ, Bonan GB, Goodale CL (2013) Insights into mechanisms governing forest carbon response to nitrogen deposition: a model‐data comparison using observed responses to nitrogen addition. Biogeosciences Discussions, 10, 1635–1683. [Google Scholar]
  70. Thornley JHM, Cannell MGR (1996) Temperate forest responses to carbon dioxide, temperature and nitrogen: a model analysis. Plant, Cell & Environment, 19, 1331–1348. [Google Scholar]
  71. Thornton PE, Lamarque J‐F, Rosenbloom NA, Mahowald NM (2007) Influence of carbon‐nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Global Biogeochemical Cycles, 21, GB4018. [Google Scholar]
  72. Titus B, Malcolm D (1999) The long‐term decomposition of Sitka spruce needles in brash. Forestry, 72, 207–221. [Google Scholar]
  73. Townsend AR, Braswell BH, Holland EA, Penner JE (1996) Spatial and temporal patterns in terrestrial carbon storage due to deposition of fossil fuel nitrogen. Ecological Applications, 6, 806–814. [Google Scholar]
  74. Vitousek P, Aber J, Howarth R et al (1997) Human Alteration of the Global Nitrogen Cycle: Causes and Consequences. Ecological Society of America, Washington, DC. [Google Scholar]
  75. Vitousek PM, Hättenschwiler S, Olander L, Allison S (2002) Nitrogen and nature. Ambio, 31, 97–101. [DOI] [PubMed] [Google Scholar]
  76. Vose JM, Swank WT (1990) Preliminary estimates of foliar absorption of 15N‐labeled nitric acid vapor (HNO3) by mature eastern white pine (Pinus strobus). Canadian Journal of Forest Research, 20, 857–860. [Google Scholar]
  77. Wallenstein MD, McNulty S, Fernandez IJ, Boggs J, Schlesinger WH (2006) Nitrogen fertilization decreases forest soil fungal and bacterial biomass in three long‐term experiments. Forest Ecology and Management, 222, 459–468. [Google Scholar]
  78. Weatherall A, Proe MF, Craig J, Cameron AD, McKay HM, Midwood AJ (2006a) Tracing N, K, Mg and Ca released from decomposing biomass to new tree growth. Part I: a model system simulating harvest residue decomposition on conventionally harvested clearfell sites. Biomass and Bioenergy, 30, 1053–1059. [Google Scholar]
  79. Weatherall A, Proe MF, Craig J, Cameron AD, Midwood AJ (2006b) Internal cycling of nitrogen, potassium and magnesium in young Sitka spruce. Tree Physiology, 26, 673–680. [DOI] [PubMed] [Google Scholar]
  80. Wellburn A (1990) Tansley review No. 24. Why are atmospheric oxides of nitrogen usually phytotoxic and not alternative fertilizers? New Phytologist, 115, 395–429. [DOI] [PubMed] [Google Scholar]
  81. Wilson E, Tiley C (1998) Foliar uptake of wet‐deposited nitrogen by Norway spruce: an experiment using 15N. Atmospheric Environment, 32, 513–518. [Google Scholar]
  82. Wortman E, Tomaszewski T, Waldner P et al (2012) Atmospheric nitrogen deposition and canopy retention influences on photosynthetic performance at two high nitrogen deposition Swiss forests. Tellus Series B, 64, 1479–1486. [Google Scholar]
  83. Zaehle S, Friend AD (2010) Carbon and nitrogen cycle dynamics in the O‐CN land surface model: 1. Model description, site‐scale evaluation, and sensitivity to parameter estimates. Global Biogeochemical Cycles, 24, GB4018. [Google Scholar]
  84. Zeller B, Colin‐Belgrand M (2001) Fate of nitrogen released from 15N‐labeled litter in European beech forests. Tree Physiology, 21, 153–162. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix S1 Materials.


Articles from Global Change Biology are provided here courtesy of Wiley

RESOURCES