Correlating phosphorus extracted by simple soil ...

J. Plant Nutr. Soil Sci. 2018, 000, 1–10

DOI: 10.1002/jpln.201700536

1

Correlating phosphorus extracted by simple soil extraction methods with foliar phosphorus concentrations of Picea abies (L.) H. Karst. and Fagus sylvatica (L.) Hadi Manghabati1§*, Michael Kohlpaintner1§, Rasmus Ettl1, Karl Mellert1, Uwe Blum2, and Axel Go¨ttlein1 1 2

Fachgebiet fu¨r Walderna¨hrung und Wasserhaushalt, Technische Universita¨t Mu¨nchen, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising Bayerische Landesanstalt fu¨r Wald und Forstwirtschaft, Abteilung Boden und Klima, Hans-Carl-von-Carlowitz-Platz 1, 85354 Freising

Abstract Phosphorus (P) concentrations in needles and leaves of forest trees are declining in the last years in Europe. For a sustainable forest management the knowledge of site specific P nutrition/ availability in forest soils is vital, but we are lacking verified simple methods for the estimation of plant available P. Within this study, four soil P extraction methods [water (PH2 O ), double-lactate (Plac), citric acid (Pcit), and sodium bicarbonate (PHCO3 )], as well as total P content of the soil (Ptot) were tested to investigate which method is best correlated with foliar P concentrations of spruce [Picea abies (L.) H. Karst.] and beech [Fagus sylvatica (L.)]. Mineral soil samples from 5 depth levels of 48 forest sites of the Bavarian sample set of the second National Forest Soil Inventory (BZE II) were stratified according to tree species (spruce and beech) and soil pH (pH < 6.2 and > 6.2), covering the whole range of P nutrition. The extractable amount of P per mass unit of soil increased in the order PH2 O 6.2 (R2 up to 0.57). Plac produces adequate models only for beech on high pH soils (R2 up to 0.64), while PH2 O did not produce acceptable regression models. Ptot seems suitable to explain the P nutrition status of beech on acidic (R2 up to 0.62) and alkaline soils (R2 up to 0.61). Highest R2s are obtained mostly in soil depths down to 40 cm. As PHCO3 and Pcit showed good results for both investigated tree species, they should be considered preferentially in future studies. Key words: beech / citric acid / extraction / forest soil / phosphorus / sodium bicarbonate / spruce

Accepted April 06, 2018

1 Introduction P is one of the essential elements for plant growth and therefore a critical element in many natural, agricultural, and silvicultural systems throughout the world. The reason is its low bioavailability (Holford, 1997). Compared to nitrogen and sulfur, P has no relevant gaseous atmospheric component involved in its biogeochemical cycle (Schlesinger and Bernhardt, 2013) and thus, in unfertilized soils it is supplied almost completely by the recycling of organic P compounds and by weathering of parent material (Walker and Syers, 1976; Belyazid and Belyazid, 2012). P bioavailability in forest ecosystems might limit ecosystem productivity and succession (Prietzel et al., 2013). Several foliar nutrition studies (Khanna et al., 2007; Mellert and Go¨ttlein, 2012; Mellert and Ewald, 2014) showed that P nutrition seems to be a substantial problem in German forests. Results

of the second National Forest Soil Inventory (BZE II) show that almost 25% of the spruce stands and more than 50% of the beech stands in German forests are below the thresholds of normal nutrition (Wellbrock et al., 2016). Decreasing foliar P concentrations and hence increasing P limitation was also observed in Swiss forests for beech and spruce (Braun et al., 2010). These trends were recently also confirmed at the European scale (Jonard et al., 2015; Talkner et al., 2015). However, most natural forest ecosystems, which do not suffer from P export by harvesting, are adapted to low P supply (Hinsinger et al., 2011). Harvesting biomass removes organically bound nutrients from forests, which might lead to deficiencies in the next tree generation on sites with low nutrient availability. Hence, for sustainable forest management we need to know the site-

* Correspondence: H. Manghabati; e-mail: [email protected] §These authors equally contributed to this work.

ª 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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Manghabati, Kohlpaintner, Ettl, Mellert, Blum, Go¨ttlein

specific nutrient availability to be able to foresee possible limitations induced by excessive nutrient export. For nitrogen, as well as for the important cations calcium, magnesium, and potassium, there exist well-established methods to assess plant available pools (e.g., C/N-ratio, cation exchange capacity, extracts with water, etc.). These methods are utilized by the BZE I (Wolff et al., 1999) and II (Wellbrock et al., 2016). In contrast, there are no such well-established methods to determine plant available P in forest soils. The cycling of P in soils is very complex. A large proportion of P in forest soils is poorly soluble and, thus, insufficiently available for plant uptake (Becker-Dillingen, 1939). This is true for phosphate, which gets increasingly insoluble above pH 6.5 (Ca-phosphates) and below pH 6 (Fe-, Al-phosphates), as well as for organic forms (Amberger, 1996). In addition, phosphates and phytates, which are the main organic P form in soil (Tarafdar and Claassen, 1988; Belyazid and Belyazid, 2012), are subject to sorption and, thus, immobilization on the surface of oxides, hydroxides, and clay minerals (Amberger, 1978). For this reason soil total P content, which is a standard parameter measured in the BZE, is not a good proxy for P availability at a given site (Khanna et al., 2007). Many authors (Morgan, 1937; Bray and Kurtz, 1945; Olsen et al., 1954; Fox and Kamprath, 1970; Barrow and Shaw, 1976; Mehlich, 1984) have proposed P-extraction methods (PEMs) using chemical extractants with different extractive power to define plant-available P. The approaches involve the simple extraction with water, mild extractants using anions [e.g., the lactate method by Egne´r et al. (1960) or the bicarbonate method by Kuo (1996)], strong extractants such as the fluoride methods by Bray and Kurtz (1945), acid methods by Mehlich (1984), as well as several other procedures described by Kuo (1996). Some extraction methods are developed only for calcareous or for acidic soils, and others are very complex and laborious and not suitable for large numbers of samples like the Hedley fractionation scheme (Hedley et al., 1982). Most of these methods have been developed with focus on agricultural soils, in which contents of easily soluble P are in general high due to organic and mineral fertilization. In contrast, in forest soils the amount of soluble P is low and forest trees may use other strategies for P acquisition compared to agricultural crops (Leinweber et al., 1993). In agricultural systems it is easy to harvest the whole plant, determine the P uptake during the growing season and relate it to extractable soil P. In silvicultural systems it is very difficult to measure the yearly P uptake of trees. Therefore, the P concentration of the current year foliage is widely used as an indicator for P-nutrition (e.g., Fiedler et al., 1973). As sampling of the foliage is elaborate and costly, it would be of great advantage to have a soil analytical parameter that reflects the actual P-nutrition. Hence, there is an urgent need for an easy to handle method for the assessment of P bioavailability in forest soils that allows a high sample throughput. Therefore, we selected and tested four simple PEMs that were already applied to forest soil samples and total P content, which is a standard parame-


J. Plant Nutr. Soil Sci. 2018, 000, 1–10 ter measured in BZE II, and correlated them with the P concentration of the current year foliage of Norway spruce and beech. The aim of this study, based on data of the BZE II, was to find PEMs that (1) are easy to handle and allow high sample throughput, (2) correlate well with foliar P concentrations, (3) are suitable for a wide variety of forest soils from very acidic to alkaline soils, and (4) work for coniferous as well as for deciduous trees. Therefore we base our study design on the following hypotheses: 1. 2. 3.

4.

5.

Different PEMs yield different amounts and fractions of P. The results of PEMs are largely modified by the soil pH (calcareous soils versus non-calcareous soils). The tested PEMs can explain the actual tree nutrition and hence the availability of P better than other routinely measured parameters like, e.g., Ptot. The P stocks (kg ha–1) in the soil correlate stronger with foliar P concentration than P contents (mg kg–1) in the soil. A sampling strategy focusing on the topsoil layers yields most efficient results in estimating the P availability for a stand (see also Lang et al., 2017).

2 Material and methods A mayor criterion for the selection of soil PEMs was a certain practicability for larger sample sizes. Thus, exchange methods and sequential extraction were not considered. Based on extensive literature review and preliminary results, we decided to test the extractants water, calcium double lactate, sodium bicarbonate, citric acid, and total P content obtained by aqua regia. Tab. 1 shows the five selected PEMs and their abbreviations in the following text as well as their application procedure in the laboratory. There are five basic ways by which P can be extracted from the solid phase and dissolved: dissolution of water soluble P, anion exchange, complexation and precipitation of P-binding cations, acid attack, and dissolution of P-containing organic matter (Tab. 1). Water (PH2 O ) is the mildest extractant used within this study and only readily soluble P is solved with this method. PH2 O dissolves very little of adsorbed P and of mineral phosphate forms. Citric acid (Pcit) and double lactate (Plac; buffered at pH 3.6) can dissolve phosphate containing minerals by acid dissolution. The citrate and lactate anions further form water soluble complexes with potentially P precipitating cations like Al, Ca, and Fe. They also can release phosphate due to anion exchange and ligand exchange from soil colloids and from oxides and hydroxides of Al and Fe (Hoffmann, 1991; Ko¨nig et al., 2005). Sodium bicarbonate (PHCO3 ; buffered at pH 8.5 with 1 M NaOH) extracts inorganic and organic P. P solubility is increased as Ca ions are precipitated as CaCO3 and soluble Al and Fe are precipitated or transformed into hydroxides by the reaction with HCO3 -, CO32–- and/or OH–-ions (Olsen et al., 1954). Furthermore, the high pH decreases the number of anion sorption places on soil colloids and on oxides of Fe

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complete dissolution of organic substances and minerals with strong acids

and Al by deprotonation of their functional groups (Sims, 2000). Due to the high solubility of humic acids in slightly alkaline solutions, part of the organic P fraction is also dissolved by this extractant (Tiessen and Moir, 2008). For P extraction we used soil samples from BZE II, conducted in the years of 2006–2008. In Bavaria, BZE II sampled at 378 points based on an 8 · 8 km grid covering about 2.4 million ha of forest. At these sites, the results of standard soil analyses according to Ko¨nig et al. (2005), including total P content in soil and the P concentrations of the current year foliage of spruce and beech, were already available and could be used within this study.

12 h of cold digestion, 2 h of boiling under reflux, filtration after cooling

Ko¨nig et al. (2005)

The selection of the sites used in this study was based on knowledge about P nutrition and soil parameters of all Bavarian BZE plots. Preliminary results showed that it is advantageous to divide the sites in carbonate containing and carbonate free soils. Additionally, we tried to cover the whole range of P nutrition within the collective of the Bavarian BZE sites. In total 48 forest sites were selected according to the following scheme. First the 368 Bavarian BZE II sites were divided into two pH groups using a threshold of pH 6.2 (measured in water), because above this value soils may contain free calcium carbonate (Wellbrock et al., 2016). As P in soils with high Ca content behaves different as compared to acidic soils we used this pH value for splitting. Within each pH group for each tree species, the foliar P concentrations of the respective Bavarian BZE II points were ranked by foliar concentration and then divided into 12 equal-sized subgroups. One BZE point was randomly selected from each subgroup for testing the selected PEMs. Figure 1 one shows the foliar P concentrations of the selected sites categorized by tree species and soil pH.


adjustment to pH 8.5 with 1 M NaOH. adjustment to pH 3.6 with 1 M HCl. bpH

apH

2 Ptot Aqua regia

HNO3 : HCl ratio 1:3

5 mL HNO3 + 15 mL HCl

dissolution of water soluble P Van der Paauw (1971), Ko¨nig et al. (2005) next day after shaking again for 1 h 10 PH2 O Water

_

20

12 h

anion exchange acid dissolution of P-containing minerals complexing of P-binding cations Hoffmann (1991) immediately 90 min 4 Plac Double lactateb

1.2%

250

anion exchange precipitation of P-binding cations dissolution of P-containing humic acids Olsen et al. (1954), Ko¨nig et al. (2005) immediately 30 min 4 PHCO3 Sodium bicarbonatea

0.5 M

80

complexing of P-binding cations acid dissolution of P-containing minerals Hoffmann (1991), Ko¨nig et al. (2005) 10 Pcit Citric acid

1%

100

120 min

after 12 h and shaking again for 30 min

major processes of PO34 -release Literature Filtration Shaking time Soil (g) Abbreviation

solution concentration

Extractant (mL)

Phosphorus extraction 3

Extractant

Table 1: Phosphorus extraction methods, their abbreviations in the text, their application in the laboratory, and the underlying major processes of P release into the extraction solution.


P extraction was done for all of the 5 mineral soil depth levels sampled during BZE (0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, and 40–80 cm) but not for the forest floor. All extracts were membrane filtered (0.45 mm, celluloseacetate-filter, Schleicher & Schuell) and the filtrate was analyzed for dissolved P using an inductively coupled plasma spectrometer (producer Spectro, type Genesis). Total P content (Ptot) in the mineral soil was determined by acid digestion of the soil samples with aqua regia (HNO3 and HCl at a ratio of 1:3) as described in Ko¨nig et al. (2005). Ptot in the organic layer was determined after acid digestion with nitric acid according to Ko¨nig et al. (2005). Foliar sampling and analyses during the BZE campaign were done according to Ko¨nig et al. (2005). Beech leaves were sampled between 15th of July and 15th of August and spruce needles during dormancy between 15th of October and 1st of March of the following year. Samples were taken from the upper third of the crown (between the 7th and the 15th whorl in the case of spruce) from light facing branches. Samples were dried (60°C), milled, and analyzed for their nutrient concentration after acid digestion with nitric acid (Rautio, 2009). P concentration in the www.plant-soil.com



–1

Pneedle/leaves (mg kg )

4

Spruce

Beech

Figure 1: P concentrations in needles and leaves of the selected study sites (circles) compared to all Bavarian BZE II sites (box plots without median, outliers and extreme values), stratified according to tree species and pH group. Grey shaded areas represent the range of normal P nutrition according to Go¨ttlein (2015).

digested and diluted solution was measured with an inductively coupled plasma spectrometer.

among PEMs. Statistical analyses were done using SPSS 22 and the open source program R.

2.1 Statistics

3 Results

Prior to our statistical analyses, we removed outliers from the data set relying on Tukey’s criteria (Tukey, 1977). Based on visual inspection of box-plots, outliers and extreme values have been identified for each sub-collective (n = 12), grouped according to tree species, pH group, PEM, and soil depth. In total 50 box plots were inspected for each soil profile (five for each PEM, multiplied by five for each depth level and multiplied by two for content and depth level aggregated stocks of extractable P). If the extractable amount of P within one soil profile appeared more than 20-times as an outlier or extreme value in this procedure it was discarded from further analysis. As a result, 3 soil profiles with their corresponding P extracts were excluded from the further analysis. As P contents and aggregated stocks showed a right-skewed frequency distribution, values were log transformed. Log transformed values were nearly normally distributed and thus more appropriate to apply parametric statistics (linear regression, ANOVA). In a first step we checked whether the statistical study design (stratification into: tree species, pH-type, PEM, and depth level) is appropriate to distinguish P concentration values based on an analysis of variance (ANOVA). Additionally, we applied depth level specific ANOVAs to test PEM and pH differences in each depth level. For PEM Ptot was used as reference category within ANOVA. We used linear regression models with extracted P amounts to estimate the foliar P concentration. Analysis was carried out for extracted P contents in each depth level as well as for depth level aggregated extractable P stocks. Based on this analysis, we identified the variables showing the highest R2


3.1 Forest floor As we found no significant correlation between Ptot in the forest floor and foliar P concentration, we do not consider Ptot of the forest floor in the following.

3.2 Foliar P concentrations of the selected forest sites The foliar P concentrations of spruce and beech of the sites selected within this study are shown in Fig. 1, categorized by tree species and pH group. They covered the whole range of observations during the BZE II (see box plots in Fig. 1) and the nutritional range from deficiency to normal nutrition or surplus (only in the case of spruce on acidic soils) according to Go¨ttlein (2015). For spruce the values covered the range between 1050 and 2896 mg kg–1 on acidic soils and between 1042 and 1849 mg kg–1 on soils with pH > 6.2. P concentrations of beech leaves ranged between 879 and 1473 mg kg–1 on acidic soils and 835 and 1238 mg kg–1 for soils with pH > 6.2. Figure 2 also shows that foliar P concentrations on soils with pH > 6.2 are lower than on soils with pH < 6.2.

3.3 Results of the ANOVAs The ANOVA revealed that all factors used to stratify the data set (pH-type, PEM, and depth level) are statistically meaningful (p £ 0.01 according to F-Test; detailed results of ANOVA tables are not shown). The standard deviation bars show a high variability within the investigated soil depths. As a consequence, pH stratification was only statistically significant for depth level 1 and 5 according to the depth level specific

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Phosphorus extraction 5

pH > 6.2

pH < 6.2

Citric acid showed the highest extractive power in acidic soils with 7.4 to 10.5% of Ptot. In calcareous soils it showed comparable results to sodium bicarbonate with decreasing extracting power with depth.

0-5 cm % of Ptot 10.2 5.2 0.6

10.5 4.9

5.4

2.3 3.7

3.6

3.9

Even though soils with high pH showed higher Ptot contents down to 40 cm, the extracted percentages and absolute amounts were lower compared to acidic soils and reached a maximum of only 5.4% for citric acid in the upper soil layer.

0.3

3.8

9.4 0.2

10-20 cm

8.7 0.2

2.8

5.2 0.2

1.8

2.9

2.9

20-40 cm

7.7 0.1

2.0 2.9

0.1

1.1 2.1

2.1

0.1

1.1 1.2

2.3

40-80 cm

7.4 0.0

1.7 1.9

PH2O Plact PHCO3 Pcit Ptot

3.5 Linear regression models

–1

0.3

7.5

Average Ptot ± 1 sd (mg kg )

–1

Average extractable P ± 1 sd (mg kg )

5-10 cm

PH2O Plact PHCO3 Pcit Ptot

Figure 2: Arithmetic mean values of extractable P amounts and Ptot depending on PEM, pH class, and soil depth level with standard deviation (sd); the percentage of average extracted P relative to mean Ptot is given for each sub-collective; scale of Ptot on the right, scale of the other extracts on the left.

ANOVA. Extracted P contents were significantly lower as Ptot in all depth levels (p £ 0.01).

3.4 Average extractable amounts of P compared to average Ptot Averages of Ptot ranged from 357 to 518 mg kg–1 in soils with pH < 6.2 and from 302 to 624 mg kg–1 in soils with pH > 6.2 and decreased with depth (Fig. 2). Measured Ptot values were between 106 and 1624 mg kg–1. Water had the lowest extractive power and dissolved only between 0 and 0.6% of Ptot. Double lactate extracted up to 5.2% of Ptot in the topsoil with decreasing amounts in deeper layers and with lower proportions in soils with high pH. Up to 10.2% of Ptot was extracted by sodium bicarbonate from acidic soils where extractable P was around twice as high down to 20 cm compared to calcareous soil. Extractive power decreased strongly with depth.


Table 2 and 3 show the correlations of extractable and total P as soil contents as well as soil stocks down to 80 cm depth with P in first year needles for spruce (Pneedle) respectively leaves for beech (Pleaves). Data were stratified in acidic (pH < 6.2) and calcareous soils (pH > 6.2). 3.5.1 Spruce For spruce (Tab. 2) growing on soilspH 6.2, none of the PEMs could explain a significant part of Pneedle. Stocks of PHCO3 and Pcit explained a significant part of the variation of Pneedle for all aggregated depth levels on acidic soils. Here, the stocks of PHCO3 down to 40 cm (R2 = 0.66) and of Pcit down to 10 cm (R2 = 0.49) showed the best models. Plac and PH2 O did not show any significant model for Pneedle and Ptot explained only a small part of the variation for the depth of 0–10 cm. For PHCO3 and partly for Pcit stocks of extractable P showed higher R2 than contents. Again for soils with pH > 6.2 none of the PEMs could explain a significant part of Pneedle (Tab. 2). 3.5.2 Beech In the case of beech (Tab. 3) on soilspH 6.2 in the case of PHCO3 (3 depth levels), Plac, (2 depth levels), PH2 O , and Ptot (each 1 depth level) with the highest R2 consistently shown in the depth of 20–40 cm. In this depth level Plac had the highest R2 (0.64). Stocks of PHCO3 and Pcit explained a significant part of the variation of Pleaves for most aggregated depth levels in acidic soils. While R2 for stocks was highest for Pcit (0.55) in 0–20 cm, it was highest for PHCO3 and Plac in 0–10 cm.

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Table 2: Results of a linear regression (adj. R2) using different soil PEMs (Pextractant) to explain Pneedle concentration; regressions using logarithmic data were calculated for spruce, differentiated in soil pH < 6.2 and pH > 6.2, soil concentrations (0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, 40–80 cm) and stocks down to 80 cm depth. Asterisks indicate significance levels of the correlation (*p £ 0.05; **p £ 0.01; ***p £ 0.001). Gray shaded cells indicate the best explanation comparing the different extractions in the corresponding soil depth. Bold cells show best R2 within each PEM. Pextractant

Spruce—Pneedle Pcit

pH < 6.2 (n = 11)

PHCO3

adj. R2

F

adj. R2

Soil Depth (cm)

F

0–5

8.776

0.437*

9.399

0.457*

5–10

12.144

0.527**

9.783

0.468*

10–20

8.920

0.442*

11.639

0.515**

20–40

7.200

0.383*

13.650

0.559**

6.867

0.370*

40–80 soil content

Plac F

PH2 O

adj. R2

F

7.183 7.399

0.390*

9.933

0.472*

adj. R2

Ptot F

adj. R2

0.382*

all soil depths—n.s.

0–5 5–10 pH > 6.2 (n = 11)

10–20


20–40 40–80

pH < 6.2 (n = 11)

soil stock

0–5

9.563

0.461*

15.675

0.595**

0–10

10.714

0.493*

18.076

0.631**

0–20

8.914

0.442*

20.205

0.658**

0–40

8.578

0.431*

20.487

0.661**

0–80

7.080

0.378*

18.472

0.636**

5.623

0.316*


0–5 0–10 pH > 6.2 (n = 11)

0–20


0–40 0–80

In alkaline soils, R2 was consistently highest for the first 3 PEMs in 0–80 cm (up to 0.57 for PHCO3 ), while for Ptot it was again highest in the upper part of the soil (R2 = 0.61 in 0–10 cm). Stocks of PH2 O did not show any significant model for both soil groups (Tab. 3).

ple throughput and correlated the extracted amounts of P with the P concentrations of the first year needles of spruce and leaves of beech. Thus, we used foliar P concentration as a proxy for site specific plant availability.

4 Discussion

4.1 Hypothesis 1—different PEMS yield different P amounts and fractions

In the last years declining foliar P concentrations of spruce, beech, and other tree species have been observed by many researchers (Braun et al., 2010; Hinsinger et al., 2011; Jonard et al., 2015; Talkner et al., 2015). Compared to agriculture, for which there are established procedures to determine site specific P availability, such methods are missing for forest stands (Khanna et al., 2007). Trying to close this gap, we tested 4 simple P extraction methods applicable for high sam-

As assumed in the introduction, the extracted amount of P per mass unit of soil varied considerably between the investigated P extraction methods (PEMs). It increased in the order of PH2 O 6.2, soil concentrations (0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, 40–80 cm) and stocks down to 80 cm depth. Asterisks indicate significance levels of the correlation (*p £ 0.05; **p £ 0.01; ***p £ 0.001). Gray shaded cells indicate the best explanation comparing the different extractions in the corresponding soil depth. Bold cells show best R2 within each PEM. Pextractant

Beech – Pleaves Pcit F

0–5

8.593

0.432*

6.779

0.366*

5–10

12.031

0.525**

9.682

0.465*

9.020

14.836

0.580**

10.118

0.477*

10.802

8.532

0.430*

8.122

40–80 soil content

F

Plac

adj.

R2

Soil Depth (cm)

pH < 6.2 10–20 (n = 11) 20–40

adj.

PHCO3 R2

F

adj.

PH2 O R2

F

adj.

Ptot R2

F

adj. R2

17.278

0.619**

14.500

0.574**

12.612

0.537**

0.416*

12.752

0.540**

8.137

0.416*

5.545

0.312*

5.128

0.273*

7.926

0.386*

7.922

12.629

0.514**

20.700

14.305

0.547**

9.026

0.445*

8.473

0.428*

6.949

0.373*

11.667

0.492**

18.248

0.611**

11.781

0.495**

8.831

0.416*

0.445* 0.495** 6.761

0.366*

0–5 5–10 pH > 6.2 10–20 (n = 12) 20–40

all soil depths— n.s.

0.386* 0.642** 5.444

0.288*

40–80

pH < 6.2 (n = 11)

0–5

8.108

0.415*

5.904

0.329*

0–10

9.225

0.451*

9.042

0.446*

0–20

13.083

0.547**

8.482

0.428*

0–40

11.847

0.520**

7.232

0.384*

5.715

0.320*

8.231 10.485

0–80 soil stock

0–5

5.358

0.284*

0–10 pH > 6.2 (n = 12)

0–20

5.363

0.304*

5.159

0.294*

0.397*

7.874

0.385*

0.463**

6.925

0.350*

12.448

0.510**

8.477

0.405*

0–40

5.743

0.301*

13.163

0.525**

9.999

0.450*

0–80

9.123

0.425*

15.830

0.574**

13.206

0.526**

and, hence, the extracted amounts of PH2 O are very low and sometimes even below the detection limits. Double lactate extracted less P than sodium bicarbonate and citric acid. Leinweber et al. (1993) already stated the very low extractive power of double lactate for forest soils, resulting usually in extracts having P concentrations below the detection limit. In the investigated soils with pH > 6.2, citric acid and sodium bicarbonate showed roughly the same extractive power, but in acidic soils citric acid extracted more than the double the amount of P in soil layers deeper than 10 cm. In acidic soils large parts of Ptot are associated with Al and Fe ions as well as oxides and hydroxides of these ions (e.g., Brady and Weil, 2008; Prietzel et al., 2016). Preferential complex forming of these ions with citrate might release higher amounts of phosphate ions into the extraction solution. The lower differences in 0–5 and 5–10 cm depth between Pcit and PHCO3 might be explained by the higher potential of bicarbonate to solve




organic matter and the organic P associated with it (Khanna et al., 2007).

4.2 Hypothesis 2—Results of PEMs are largely modified by soil pH The pH-value of the soil clearly influenced the results of the PEMs. Although the amount of Ptot in soils pHH2 O > 6.2 was generally higher, the extracted amount of P was higher in acidic soils. The reason for this might be the high P-fixing capacity of calcite rich soils. High amounts of calcium in soils with pH > 6.2 led to the precipitation and accumulation of sparingly soluble forms of organic (e.g., calcium phytate) and inorganic P (e.g., hydroxylapatit minerals) (Celi et al., 2000; Wan et al., 2016), which could not be dissolved by the extraction agents used in this study. Prietzel et al. (2016) showed that in soils derived from limestone and dolostone generally www.plant-soil.com

8



more than half of Ptot is present as calcium bound organic P (probably mostly as calcium inositol hexakisphosphate) and apatite-P. This shows that the stratification of the sample collective into soils with pH higher and lower than pH 6.2 was meaningful. Additionally, it is well known that the highest P availability is in the range of pH 6 to 6.5 and declines either with further increasing or decreasing pH (Blume et al., 2002; Brady and Weil, 2008).

While Plac and Ptot deliver only good results for beech, Pcit and PHCO3 can explain a substantial part of the P nutrition for both tree species. This is advantageous, especially for large surveys with standardized methods, as the results should be applicable for several tree species. A further benefit is that these extraction methods are already described as methods for forest soils in the German Handbook of Forest Analytics (Ko¨nig et al., 2005).

4.3 Hypothesis 3—Tested PEMs can explain the actual tree nutrition better than Ptot

4.4 Hypothesis 4—P stocks correlate stronger with foliar P concentrations than P contents

None of the tested PEMs could explain the actual nutrition of all tested tree species and soil pH groups satisfactorily. While PHCO3 delivered best results for sprucepH 6.2 and contents on acidic soils (pH < 6.2) showed best results. The heterogeneity of the results shows the need to test the PEMs with a larger sample set to get clearer results.

It is well known that mycorrhizal associations play a major role in the P nutrition of trees (Smith and Read, 2008; Marschner, 2012). According to Agerer (1987), these associations are very different for spruce compared to beech, which may result in different uptake strategies. Also the vertical and horizontal fine root distribution (e.g., Heinze et al., 2001) and the seasonal input pattern of litter are different between the species and might influence P uptake. Different P uptake strategies are also supported by the results of the BZE II (Riek et al., 2016). They found that along a gradient of increasing acidification the P nutrition of oak decreased, but augmented for beech. Here, oak seems to use P acquisition strategies which are more efficient on non-acidified soils than those of beech.

The vertical distribution of P in developed soils in a humid climate is different from other macronutrients, particularly base cation availability patterns (Ko¨lling et al., 1996; Prietzel et al., 2016), which usually increase along the vertical gradient in the mineral soil. During the post glacial soil development, large amounts of substrate derived P got lost and remaining P has been gradually converted into organic binding forms via plant uptake and accumulation of residuals at the soil surface (Chapin III et al., 2011; Lang et al., 2016). As a result, P availability is normally inverse to base cation availability (Prietzel et al., 2016). Therefore we assumed that the topsoil layers, which also have higher fine root densities and hence higher uptake capacities (O layer and A horizon, particularly Ah), might be sufficient for estimating P nutrition. The best correlation between foliar and soil P was found with PHCO3 extracts in the depth of 20–40 cm. This implies that especially within the spruce plots showing a lower average total P stock (median total P stock: spruce 4.2 t ha–1 vs. beech 5.3 t ha–1) the upper mineral soil (B horizon) is important for P nutrition besides the uppermost horizons (O layer and organic A layer). However, for beech the best correlation was achieved already in a soil depth up to 20 cm. In all, these results do not contradict our assumption that upper layers are better predictors for P nutrition than the subsoil, as the correlation of foliar P concentrations and soil contents or stocks were systematically higher in the topsoil layers compared to the lower layers (> 40 cm). However, our results show that besides P in the O and Ah layers also P in the upper mineral soil significantly contributes to P nutrition of trees at our study sites. In contrast to agricultural soils, where fertilization improves the nutrient availability and hence also nutrient uptake primarily in the upper 10 cm, low P contents in forest soils force trees to acquire nutrients also form deeper soil layers.

Foliar P concentration do not only depend on P uptake by plants from soil but also on the internal recycling of P. Netzer et al. (2017) showed that in beech trees the resorption of P, its storage in bark and wood, and its reuse at the beginning of the next growing season was of higher significance on sites with extremely low P availability in soil. This intensification of the internal P recycling might be an explanation why sites with a very low soil availability of P may show normal P-nutrition. Missong et al. (2017) found that the P content of water extractable colloids is up to 16-times higher compared to bulk soil. Although our extracts were passed through a 0.45-mm membrane filter, very small organic and inorganic colloids may still be present in the extraction solution containing P which is not directly available for plants. Especially during the extraction with bicarbonate organic matter is dissolved due to the high pH of the extraction solution. The role of the plant availability of this P bound in colloids is still under debate and might also inflate the unexplained variance of Pfoliage.


4.5 Hypothesis 5—Sampling of upper soil layers yields most efficient results

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5 Conclusions This study shows that Pcit and PHCO3 extract more P from soils than Plac und PHCO3 and can explain a substantial part of the variation in P-nutrition of spruce and beech. This makes these simple extraction methods a promising tool for monitoring and/or predicting actual P availability in forest soils. The soil pH influences the results of the PEMs and should be considered when extracting phosphorous from soil. Sampling depths above 40 cm delivered generally best R2 and suggests topsoil layers being most appropriate for the determination of available P. Whether contents or stocks of extractable P are more suitable for the prediction of P nutrition and availability could not be finally determined within this study.

6 Outlook We suggest to test Pcit and PHCO3 on a larger number of sites and soil/needle samples. Possibly, larger data sets allow to derive tree specific threshold values for extracted P amounts indicating P shortage. Additionally, further important European tree species like scots pine, common, and sessile oak should be included. Also the question of whether stocks or contents and which exact depth levels are most suitable for generally explaining P concentration of leaves and needles of forest trees should be clarified.

Acknowledgments We thank the Bayerisches Staatsministerium fu¨r Erna¨hrung Landwirtschaft und Forsten (StMELF) for funding the laboratory work.

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