How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod and plant communities

STOTEN-24241; No of Pages 10 Science of the Total Environment xxx (2017) xxx–xxx

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How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod and plant communities Lorenzo Lazzaro a,⁎,1, Giuseppe Mazza b,1, Giada d'Errico c,d, Arturo Fabiani e, Claudia Giuliani f, Alberto F. Inghilesi g, Alessandra Lagomarsino e, Silvia Landi b, Lorenzo Lastrucci a, Roberta Pastorelli e, Pio Federico Roversi b, Giulia Torrini b, Elena Tricarico g, Bruno Foggi a a

Department of Biology, University of Florence, via G. La Pira 4, I-50121 Florence, Italy CREA-DC, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria, Research Centre for Plant Protection and Certification, via di Lanciola 12/A, I-50125, Cascine del Riccio, Florence, Italy c Department of Agricultural Sciences, University of Naples Federico II, via Università 100, 80055 Portici, Italy d CNR - Istituto per la Protezione Sostenibile delle Piante (IPSP), via Università 133, 80055 Portici, Naples, Italy e CREA-AA, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria, Research Centre for Agriculture and Environment, via di Lanciola 12/A, I-50125, Cascine del Riccio, Florence, Italy f Department of Pharmaceutical Sciences, University of Milan, via Mangiagalli 25, I-20133 Milan, Italy g Department of Biology, University of Florence, via Romana 17, I-50125 Florence, Italy b

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• We analysed the impacts of Robinia pseudoacacia invasion. • We analysed impacts on soil chemical properties, plant and soil biotic communities. • We found qualitative and quantitative changes in all components analysed. • We detected soil nitrification and acidification in stands invaded by black locust. • Changes (mostly biodiversity reduction) were observed in biotic communities.

a r t i c l e

i n f o

Article history: Received 30 August 2017 Received in revised form 2 October 2017 Accepted 3 October 2017 Available online xxxx Editor: Elena Paoletti Keywords: Black locust Community ecology Impact

a b s t r a c t Biological invasions are a global threat to biodiversity. Since the spread of invasive alien plants may have many impacts, an integrated approach, assessing effects across various ecosystem components, is needed for a correct understanding of the invasion process and its consequences. The nitrogen-fixing tree Robinia pseudoacacia (black locust) is a major invasive species worldwide and is used in forestry production. While its effects on plant communities and soils are well known, there have been few studies on soil fauna and microbes. We investigated the impacts of the tree on several ecosystem components, using a multi-trophic approach to combine evidence of soil chemical properties and soil microbial, nematode, microarthropod and plant communities. We sampled soil and vegetation in managed forests, comparing those dominated by black locust with native deciduous oak stands.

⁎ Corresponding author. E-mail address: lorenzo.lazzaro@unifi.it (L. Lazzaro). 1 Both authors contributed equally to the study.

https://doi.org/10.1016/j.scitotenv.2017.10.017 0048-9697/© 2017 Elsevier B.V. All rights reserved.

Please cite this article as: Lazzaro, L., et al., How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod ..., Sci Total Environ (2017), https://doi.org/10.1016/j.scitotenv.2017.10.017

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Invasion ecology Invasive alien species Below-ground interactions

We found qualitative and quantitative changes in all components analysed, such as the well-known soil nitrification and acidification in stands invaded by black locust. Bacterial richness was the only component favoured by the invasion. On the contrary, abundance and richness of microarthropods, richness of nematodes, and richness and diversity of plant communities decreased significantly in invaded stands. The invasion process caused a compositional shift in all studied biotic communities and in relationships between the different ecosystem components. We obtained clear insights into the effects of invasion of managed native forests by black locust. Our data confirms that the alien species transforms several ecosystem components, modifying the plant-soil community and affecting biodiversity at different levels. Correct management of this aggressive invader in temperate forests is urgently required. © 2017 Elsevier B.V. All rights reserved.

1. Introduction Biological invasions are a major threat to biodiversity (CBD decision VI/23, 2014; McNeely et al., 2001). Invasive alien species can impact ecosystems, causing a decrease in species richness and diversity (Hejda et al., 2009; McNeely et al., 2001), reduction of distinctiveness of local biological communities (Olden and Rooney, 2006) and alteration of ecosystem processes (Ehrenfeld, 2010; Vilà et al., 2011). They also have major economic impacts related to direct and indirect financial costs, and can be detrimental to human health (Mazza et al., 2014; McNeely et al., 2001). At local scale, non-native plants can decrease plant and animal species richness, also inducing cascade effects with severe consequences for invaded ecosystems (Vilà et al., 2014). Plant invasions change the composition and structure of vegetation, subsequently altering animal communities and ecosystem processes (Litt et al., 2014). The North-American black locust (BL), Robinia pseudoacacia L. (Fabaceae, Papilionoideae), is a major invasive plant in Europe (Kleinbauer et al., 2010). It has spread to 42 European countries (Pyšek et al., 2009) and is classified as highly invasive across the continent (Vítková et al., 2017). It acts as a ‘transformer’, replacing native forest vegetation (Vítková et al., 2017), completely changing the physical substrate and stand conditions, thus severely impacting understory vegetation and epiphytes (Nascimbene et al., 2015). The impacts of BL are often related to association with nitrogen-fixing bacteria that can greatly enrich soil nitrogen stores (e.g. Macedo et al., 2008), leading to an alteration of plant communities, especially in nutrient-poor stands, where it causes a sharp increase in productivity (Kleinbauer et al., 2010). These changes in ecosystem properties usually have many impacts on plant forest diversity and species composition (Vítková et al., 2017). In Italy, rapid expansion of the species is causing progressive decline of native forests, with loss of species richness and diversity and a shift in species composition towards nitrophilous plants, particularly in central regions (Benesperi et al., 2012). However, although it is generally demonstrated that invasion by BL may give rise to plant communities very different from those dominated by native trees, its effects on biodiversity are still debated (Vítková et al., 2017). The impacts of BL on plant communities are generally well-known, but despite the recognized links between above-ground and belowground biotic communities, little data is available on its effects on soil fauna, particularly nematodes and microarthropods. Soil animal communities can be altered by changes in the composition and structure of plant communities (Litt et al., 2014), with various effects. These impacts may be due to changes in soil nutrients, moisture, salinity and pH, or to alteration of mutualistic and antagonist interactions (Gratton and Denno, 2005). Hulme et al. (2013) pointed out that most studies on the impacts of invasive alien species focus on a single or very few response variables. More integrated approaches, assessing the effects of invasive plants on several response variables across various ecosystem components are needed for a correct understanding of the invasion process and its consequences. Evaluation of quantitative impacts on less studied components of ecosystems, such as soil fauna, is also urgently needed (Hulme et al., 2013). Such data is a valuable source of information as it provides a

more comprehensive scenario of plant invasion and is useful for risk assessment. The present study evaluates the multiple impacts of BL invasion on soil chemical properties, soil microbial, microarthropod and nematode communities and understory plant communities. Soil and vegetation were sampled in stands completely invaded by BL and in native semi-deciduous oak (Quercus spp.) forest stands free of BL in central Italy. The aims were: 1) to determine whether BL exerts impacts across different ecosystem components; 2) to assess whether communities differ in taxa compositions after BL invasion; and 3) to evaluate possible relationships between the changes in ecosystem components observed. 2. Materials and methods 2.1. Study area and sampling design The study was carried out in foothill areas of the northern Tuscan Apennines (central Italy, 43.971° N, 10.944° E; Supplementary materials, Fig. A1). The altitude of the study area is 100–900 m; mean annual temperature is 14.4–9.4 °C and mean annual rainfall 1300–1900 mm. The landscape is dominated by cultivated (olive groves and vineyards) and managed forested areas. The latter consisted primarily of native deciduous oaks (i.e. Quercus pubescens and Quercus cerris), which today have been replaced by BL as a result of forest management (Benesperi et al., 2012). Indeed, in this area, forests are mostly managed on a 20–30 year rotation. At the end of each period, they are usually clear cutted and allowed to grow back spontaneously (Benesperi et al., 2012). This management have facilitated the invasion by BL, which is a very fast-growing species, leading to a total substitution of the dominant species in the managed stands after the clear-cutting. To compare soil and plant communities of managed stands dominated by native oaks (NOS – native oaks stands) with those dominated by BL (BLS – black locust stands), we selected stands with similar tree size, consistent with the medium size for mature coppiced native and invaded stands (about 70 cm in circumference, as already reported by Benesperi et al., 2012). As a preliminary step towards identifying suitable sampling sites, we combined the vegetation and soil maps of the area (Gennai, 2011; Costantini et al., 2012) in order to select NOS and BLS with homogeneous parent material. The study area was homogeneous in terms of geological substrate, classified as Endoskeletic Cambisols, developed on formations composed of alternating pelitic-arenitic, arenitic-marly and areniticpelitic rocks (Costantini et al., 2012). We randomly selected 13 plots (10 × 10 m) per invasion status (i.e. NOS and BLS, for a total of 26 plots), scattered in a multiple forest landscape. In each plot, we sampled understory vascular plants and collected soil samples for further analysis. For physical, chemical and microbiological analysis, soil was collected following the protocol described in Lazzaro et al. (2014). For microarthropod analysis, three random soil samples were collected with a special 10 cm cubic corer for mesofauna sampling. For plant parasitic and free-living nematodes, six soil samples were collected randomly with a hand auger (5 cm internal diameter) at a depth of 15 cm in the top layer of bulk soil, after removing surface residues; they were mixed

Please cite this article as: Lazzaro, L., et al., How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod ..., Sci Total Environ (2017), https://doi.org/10.1016/j.scitotenv.2017.10.017

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to form a composite sample. Six further soil samples were sampled randomly as above to isolate and identify entomopathogenic nematode strains. Soil samples were placed in plastic bags, labelled and stored at 4 °C until analysis. Data was collected in June 2015, the month of maximum activity for all the organisms studied. 2.2. Data collection and preparation As a preliminary step, we assessed soil texture, a fundamental trait for soil biota components (e.g. Ettema, 1998; Lauber et al., 2008; Villani et al., 1999; Vreeken-Buijs et al., 1998). Hence, we excluded plots with dissimilar soil texture (i.e. samples with a high percentage of sand), to avoid bias in assessing the effects of BL invasion (13 NOS and 11 BLS plots; Supplementary materials Table A1). We then selected a number of abiotic and biotic indices associated with different ecosystem components (Table 1). 2.2.1. Physical and chemical soil analysis Soil physical and chemical properties were determined according to the analytical methodology approved by the National Observatory for Pedology and Soil Quality (Mipaaf, 2000). Soil texture was determined by the Bouyoucos hydrometer method with the USDA taxonomic guide. Soil pH was determined in water with a 1:25 extraction ratio. Total C (TC), total organic C (TOC) and total N (TN) contents of bulk soil were measured by dry combustion in a Thermo Flash 2000 CN soil analyzer: 20–40 mg soil was weighed into Ag-foil capsules for TC and TN and pre-treated with 10% HCl until complete removal of carbonates − for TOC. N-NO− 3 and N-NH4 were extracted by shaking 20 g of fresh soil in 100 ml of 2 M KCl solution for 1 h. Soil extracts were analysed with the FIAstar 5000 Auto Analyzer system (FOSS Höganäs) for N-NO− 3 and N-NH− 4 concentrations. 2.2.2. Microbiological analysis Microbiological communities (bacteria and fungi) were investigated by DNA extraction and Denaturing Gradient Gel Electrophoresis (DGGE) from the soil samples. DNA was extracted using FastDNA®SPIN Kit for Soil (MP Biomedicals, Solon OH). Extracted DNA was amplified in a T100 Thermo Cycler (Biorad, CA, USA) using universal primer sets for bacterial 16S and fungal 18S rDNA (986F-UNI1401R, Nübel et al., 1996

and EF390-FR1, Vainio and Hantula, 2000, respectively). DGGE was carried out in a DCode™ DGGE System apparatus (BioRad) according to Lazzaro et al. (2014). Evaluation of band migration distance and intensity in each DGGE profile was performed using Gel Compare II software v 4.6 (Applied Maths, Saint-Martens-Latem, Belgium). Richness and diversity indices (Shannon H') were calculated according to Pastorelli et al. (2011). The banding patterns, extracted as quantitative band-matching tables, were standardized by calculating the relative intensity of each band (ratio of intensity of each band to the total band intensity). 2.2.3. Microarthropod and nematode communities Microarthropods were extracted from 10 cm3 soil samples using modified Berlese-Tullgren funnels, following the standard methodology (Parisi et al., 2005) and determined to the order level. The edaphic microarthropod community was characterized using: i) individual abundance; ii) richness determined by counting the number of taxa; and iii) QBS-ar index according to Parisi et al. (2005). This index is based on the life-form approach and its values are the sum of EMI (Eco-Morphological Index) scores, which range from 1 to 20, depending on an organism's adaptation to its edaphic habitat. Plant-parasitic and free-living nematodes were isolated from 100 ml of soil sample using the cottonwood filter extraction method (Greco and Carletti, 2014). Nematodes were extracted for 48 h at 20 ± 3 °C. Each nematode suspension was sieved through a 25 μm sieve and the nematodes were counted under the stereomicroscope (50× magnification). Nematodes were mounted on temporary slides and identified to genus or family level using keys from Mai and Lyon (1962), Bongers (1988) and Marinari-Palmisano and Vinciguerra (2014). Taxonomic families were assigned to a trophic grouping based on Yeates et al. (1993). The presence of entomopathogenic nematodes was assessed using the Galleria bait method (Bedding and Akhurst, 1975). The soil samples were placed in plastic containers, and a steel mesh pocket containing two last larval instars of Galleria mellonella (Lepidoptera) was placed in each container and kept at 20 ± 3 °C. Cadavers with nematodes were placed on modified White traps (Kaya and Stock, 1997). Juveniles emerging from the G. mellonella larvae were collected and stored in distilled water in 50 ml tubes at 12 °C. Some were placed on temporary slides and observed under the microscope for identification to the genus level.

Table 1 Abiotic and biotic indices describing the different components of the ecosystems. Ecosystem component

Index

Symbol

Description and references

Soil chemical properties

Soil pH Total organic carbona Total nitrogena Inorganic nitrogen (ammonium cation) Inorganic nitrogen (Nitrate)a

pH TOC TN NH+ 4 NO− 3

Bacterial richness

16S_Rich

Describes acidity or basicity of soil samples Total organic carbon present in the sample Total nitrogen present in the sample Cation inorganic fraction of nitrogen Nitrate inorganic fraction of nitrogen Number of 16S bacterial-DGGE bands (proxy for number of dominant bacterial species in the community) 16S bacterial_DGGE band diversity expressed as Shannon H' Number of 18S fungal-DGGE bands (proxy for number of dominant fungal species in the community) 18S fungal_DGGE band diversity expressed as Shannon H' Microarthropod individual abundance Taxa richness of microarthropods Index based on adaptation to edaphic habitat; sum of EMI (Eco-Morphological Index) scores (Parisi et al., 2005) Nematode individual abundance Taxon richness of nematodes Index calculated as sum of weighted relative abundances of families classified in the colonizer-persister (cp) scale for free living nematodes (Bongers, 1990) Index calculated as sum of weighted relative abundances of families classified in the colonizer-persister (cp) scale for plant parasitic nematodes (Bongers, 1990) Food web indicators: this index highlights extreme colonizers (Ferris et al., 2001) Food web indicators: this index highlights persisters (Ferris et al., 2001) Number of plant species retrieved from the plot Plant species diversity expressed as Shannon H'

Bacterial communities

Fungal communities

Microarthropod communities

Nematode communities

Plant communities a

Bacterial diversity

16S_Div

Fungal richness

18S_Rich

Fungal diversity Microarthropods abundancea Microarthropods richness QBS-ar

18S_Div Arth_Ab Arth_Rich QBS-ar

Nematodes abundancea Nematodes richnessa Maturity index

Nem_Ab Nem_Rich MI

Plant parasitic indexa

PPI

Enrichment indexa Structure indexa Plant species richness Plant species diversity

EI SI Pl_Rich Pl_Div

3

Marks variables log-transformed in the statistical analysis.

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Nematode communities were characterized using: i) abundance of individuals; ii) richness, determined by counting the number of taxa; iii) Maturity and Plant Parasitic indices (MI and PPI) after Bongers (1990), calculated as the sum of the weighted relative abundances of families classified in the cp scale for free-living and plant-parasitic nematodes; and iv) food web indicators (EI, enrichment index; SI, structure index) after Ferris et al. (2001). EI was calculated as the weighted relative abundance of functional guilds responsive to nutrient enrichment in cp groups 1 and 2, while SI was calculated as the weighted relative abundance of functional guilds responsive to physical disturbance in cp groups 3, 4, and 5. 2.2.4. Plant communities In each plot, we recorded the complete list of vascular plants and estimated their cover using a continuous percentage scale. We distinguished three main vegetation layers, namely the canopy of trees (3 to 15 m), the shrub layer (1 to 3 m) and the herbaceous/lower stratum (0 to 1 m). The cover of some species and in general the total cover of each plot could therefore be N 100%. Plant nomenclature followed online nomenclatural databases The Plant List (http://www.theplantlist.org/). Plant species diversity was calculated using the Shannon H' diversity index.

the compute.es package version 0.2-2 (Del Re, 2013). Correlation analysis was performed with the cor.test function in the stat package. Graphs were drawn using ggplot2 package version 2.1.0 (Wickham, 2016) and igraph package version 1.0.1 (Csardi and Nepusz, 2006). Multivariate analysis was performed using Canoco 5 for Windows (vers. 5.04; Ter Braak and Šmilauer, 2012). 3. Results 3.1. Differences in abiotic and biotic indices Soil pH was significantly lower in BLS than NOS, whereas no differences were found for TC, TOC, TN and total inorganic N contents. Soil NO− 3 was significantly higher in invaded than in non-invaded soils. Bacterial community richness was higher in BLS than in NOS. Fungal communities did not differ (Fig. 1; mean values and results of t-test analyses are reported in Supplementary materials Table A2). Soil microarthropod communities were affected by BL invasion, with a significant loss of abundance and richness (Fig. 1). The distribution of taxa differed between NOS and BLS: 18 taxa were identified in the native stands, while only 12 were found in invaded ones. Protura, Opilionida, Isopoda, Thysanoptera and Psocoptera were only present in native

2.3. Statistical analysis The differences in soil chemical features and biotic indices between BLS and NOS were analysed by means of Univariate Statistical Analyses (t-test with Welch correction for degree of freedom) and compared using Hedges' g as a measure of the Standardized Effect Size (Del Re, 2013). Hedges' g is an estimate of Cohen's d that is not biased by small sample sizes. It is a unit-free index ranging from −∞ to +∞, in this case used to estimate the size of the difference between BLS and NOS. Hedges' g is comparable across all indices irrespective of the original scale of measure and magnitude, and allows comparison of effects among very different variables. Zero g values indicate no difference in the variable measured between invaded and uninvaded plots. Positive and negative g values imply a general increasing and decreasing trend, respectively, following invasion. When necessary, explanatory variables were log-transformed to achieve normality of residuals (Table 1). We then used multivariate analysis to evaluate how community composition was affected by invasion status and by the other biotic and abiotic indices derived from the sampled data. Thus, band composition for bacteria and fungi and the community matrices of microarthropods, nematodes and plant species composition were used as response variables in a multivariate framework. We compared Principal Component Analysis (PCA) and Redundancy Analysis (RDA) to check the efficiency of the explanatory variables in capturing dataset variance. All indices that varied significantly between BLS and NOS, but were not directly linked to the biotic community analysed, were used in RDA as explanatory variables. Their effect on response variable composition was tested with a permutation test using 9999 unrestricted permutations, and the significance of each variable was assessed to obtain adjusted P-values for False Discovery Rate (FDR, as described by Benjamini and Hochberg, 1995) for the simple and conditional effects of each variable (Ter Braak and Šmilauer, 2012). Plant cover percentages were arcsinetransformed, while a log transformation was used for the other community matrices. As already done in the univariate analysis, the explanatory variables were log-transformed to allow use of the parametric multivariate analysis, when necessary. Spearman's rho non-parametric rank correlation analysis was performed to investigate the relationships between biotic and abiotic indices significantly affected by invasion status, also testing for significance of the correlation via the asymptotic t approximation (Hollander and Wolfe, 1973). Outcomes are provided in a network graph. Univariate and correlation analysis was performed in R environment vers. 3.3.1 (R Core Team, 2016). Effect size analysis was performed using

Fig. 1. Mean effect size (Unbiased Hedges' g) of differences in abiotic and biotic indices between invaded (BLS) and native stands (NOS). The bars represent 95% confidence intervals. A mean effect size is significantly different from zero when its 95% confidence intervals do not bracket zero. Negative mean effect sizes indicate that the BLS had smaller values on average for a particular index than NOS. Sample size: NOS n = 13 and BLS n = 11. For abbreviations of variables, see Table 1.

Please cite this article as: Lazzaro, L., et al., How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod ..., Sci Total Environ (2017), https://doi.org/10.1016/j.scitotenv.2017.10.017

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stands (Supplementary materials Table A3). Microarthropod soil biological quality index, QBS-ar, showed values typical of forest soils (133.5 ± 8.3) in NOS, while it was closer to values typical of disturbed soils (98.4 ± 8.1) in BLS. Nematodes richness was significantly lower in invaded plots (Fig. 1). Nineteen different genera, belonging to fourteen plant parasitic and freeliving nematode families, were identified in the soil samples. The families Cephalobidae and Aphelencoidae were only found in BLS, while the family Trichodoridae was only present in NOS (Supplementary materials Table A4). The proportion of nematodes in the feeding groups was similar for bacterial feeders (the major group), fungal feeders, omnivores and predators in both stands. Thirteen isolates emerged from G. mellonella larvae: they belonged to the genus Steinernema (Steinernematidae), prevalent in NOS (8 isolates), and to the genus Oscheius (Rhabditidae), present only in BLS (3 isolates, Supplementary materials Table A4). We sampled 139 plant species, belonging to 105 genera and 49 families (Supplementary materials Table A5). The most represented family was Poaceae (15 taxa), followed by Lamiaceae (11 taxa) and Rosaceae (nine taxa). Ten families included only two taxa and 24 families were present with only one taxon. NOS were significantly richer and more diverse than BLS (Fig. 1). Sixty-two taxa were present only in NOS, while 27 were exclusive to BLS. Among the taxa exclusive to NOS, we found that shrubs typical of the native vegetation (such as Erica spp. and Emerus major) were replaced by nitrophilous and synanthropic species such as Rubus spp. and Sambucus nigra in BLS. Most of the species exclusive to NOS showed a scattered distribution, being found in few plots. On the other hand, the species exclusive to BLS plots are plants common in and typical of disturbed habitats (i.e. Bromus sterilis) or of N-rich soils (such as Urtica dioica). 3.2. Differences in biotic community composition Multivariate analysis on the composition of biotic communities resulted in a complex network of relationships between the latter and abiotic soil features (Fig. 2, Table 2). Regarding bacteria, none of the indices studied significantly affected community composition making RDA relatively inefficient (Supplementary materials Fig. A2; Table 2). By contrast, fungi were strongly influenced by invasion status (Table 2) with the two RDA axes (Supplementary materials Fig. A3) well capturing dataset variability. Microarthropods were slightly affected by invasion status, though only for simple effects and with low RDA efficiency (Supplementary materials Fig. A4). Microarthropod community composition was also significantly affected by bacterial richness, which showed to be an important variable in shaping the microarthropods taxa abundance (Table 2). On the other hand, no effect of invasion status could be detected for nematodes, which only appeared affected by indices related to microarthropod communities, with low RDA efficiency (Supplementary materials Fig. A5). Regarding plants, invasion status and pH proved to be the main factors shaping communities, with NO− 3 only significant for simple effects. The RDA axis (Supplementary materials Fig. A6) showed high efficiency (Table 2). 3.3. Analysis of correlations between indices significantly affected by invasion A significant correlation between variables was found in 13 out of 36 possible combinations of indices significantly affected by invasion status (Table 3). We were able to identify some strong and rather obvious correlations within the ecosystem components we analysed, but connections between compartments were more interesting even if most of them of moderate/low magnitude (Fig. 3). Bacterial richness was correlated positively with NO− 3 content and negatively with microarthropods. Nematode richness was correlated positively with microarthropod richness, QBS-ar index and pH. Plant richness and diversity were both negatively correlated with soil NO− 3 content.

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4. Discussion Our study reveal the multiple impacts of Robinia pseudoacacia, for the first time providing evidence of its effects on nematodes and microarthropods. Most of the ecosystem components examined differed in invaded and native stands, with invasion by BL decreasing the biodiversity of all biotic communities except bacteria. Soil nitrification and litter accumulation may lower pH in invaded soils (Van Miegrot and Cole, 1984; Vítková et al., 2015). Khan et al. (2010) found that BL leaves had a significant effect on several physical and chemical properties of soil, also decreasing pH. As expected, we too recorded an increase in N nutrient availability under BL, since this species is associated with nitrogen-fixing bacteria. N2 fixation in stands with BL is an important input for the nitrogen cycle (Vítková et al., 2015). Indeed BL is usually associated with increasing nitrogen inputs in soils. Accordingly, Medina-Villar et al. (2016) reported that BL field soils had greater phosphomonoesterase (PME) activity, total N and net ammonification rate and Rice et al. (2004) also reported elevated levels of P and Ca. Moreover, BL colonization of floodplains can exacerbate the problems associated with increasing nitrogen inputs into the riparian area and river ecosystems (Buzhdygan et al., 2016). Increased nitrogen, phosphorus and potassium may be due also to flower fall in late spring (Lee et al., 2011). Decomposing leaves and other parts of BL enrich soil in organic colloids and nutrients (especially nitrogen), as highlighted in the poor sands of Poland (Rahmonov, 2009). We found higher bacterial richness in invaded soils, which is presumably an effect of higher N availability, in line with the general increasing trend of microbial activity following plant invasions highlighted by Vilà et al. (2011). The role of N cycle dynamics (Rasche et al., 2011) and plant species composition (Grayston and Prescott, 2005) in shaping microbial community structure is well-known in forest soils. Furthermore, soil microbial communities have been described to be strongly correlated with differences in soil chemistry, such as texture, TOC, TN, and pH (Fierer and Jackson, 2006; Lauber et al., 2008). Our results seem consistent with those general findings, even if soil bacterial richness was positively correlated only with the changes in soil NO− 3 . The microarthropod soil biological quality index, QBS-ar, showed values typical of forest soil in NOS, while in BLS we recorded different degrees of soil disturbance. In contrast with the findings of Longcore (2003) and Levin et al. (2006), the greater amount of litter and decaying vegetation did not favour microarthropod detritivores. Changes in soil condition, as well as in vegetation community composition and structure caused by BL invasion, affected soil microarthropods. Furthermore Nasiri et al. (2005) proved that substances released during decomposition of BL litter has an allelopathic activity which could limit microarthropod richness and abundance. A decrease in hemiedaphic and euedaphic microarthropod groups, such as Protura, Acarina, Collembola, Diplopoda, Coleoptera and Thysanoptera, was observed in BL soils. These results are in line with the conclusion of Litt et al. (2014), who claim that the total abundance and taxon richness of arthropods decreased in response to plant invasion, with a general reduction in the functional groups of predator and herbivore arthropods. Several species belonging to Hemiptera, Thysanoptera and Coleoptera orders are considered host-specific during some or all of their life stages and these taxa may be severely affected by an increased abundance of invasive plants. Moreover, invasive plants, such as BL, can produce different secondary metabolites that are released into the soil through secretion systems of living tissues and after decomposition of their debris (Rahmonov, 2009). Indeed, BL has several toxic components, including toxalbumins, robin and phasin (Hui et al., 2004) that could discourage certain arthropods and nematodes. However, no experiments have yet been carried out to clarify this issue. Nematode taxon richness, mainly plant parasitic nematodes, decreased in BL soils. Indeed, fewer taxa of root-feeding specialist nematodes, such as those of the families Longidoridae and Trichodoridae, were found in BLS, in line with other cases of plant invasion (Jobin et

Please cite this article as: Lazzaro, L., et al., How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod ..., Sci Total Environ (2017), https://doi.org/10.1016/j.scitotenv.2017.10.017

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Fig. 2. Ordination diagrams for multivariate analysis on biotic communities: a) bacteria; b) fungi; c) arthropods; d) nematodes, and e) plants. Empty squares indicate BLS; empty circles NOS. Arrows indicate supplementary explanatory variables; big squares indicate invaded (BLS) and native stands (NOS). For abbreviations of variables, see Table 1.

al., 1996; Reinhart and Callaway, 2006; Wolfe et al., 2004). The Tylenchidae family was dominant among plant parasitic nematodes in invaded soil, possibly because of its high capacity for colonization and survival under less favourable circumstances (Bongers, 1990). Our results also underlined a positive correlation between taxon richness and soil pH. Soil acidification affected many nematode families, especially those that are plant parasites. Entomopathogenic nematodes were also affected by BL invasion: identification of nematodes emerging from sentinel G. mellonella larvae indicated a reduction in the specialized Steinernema genus in BLS soils and an increase in the opportunistic Oscheius genus.

In line with the findings of Read et al. (2006), microarthropod predators showed a significant impact on nematode population dynamics and composition. Wilson and Gaugler (2004) found a positive correlation between the rate of nematode population decline and abundance of soil mites and collembolans. Nevertheless, the relative contributions of bottom-up (food resources) and top-down (especially predation) relationships that may link arthropods, nematodes and bacteria in a complex food web are still poorly understood (Read et al., 2006). The results of our study suggest a positive correlation between richness of nematodes (prey) and arthropods (predators) linked to a bottom-up process. However, we did not find any significant direct correlation between the

Please cite this article as: Lazzaro, L., et al., How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod ..., Sci Total Environ (2017), https://doi.org/10.1016/j.scitotenv.2017.10.017

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Table 2 Comparison of Principal Component Analyses (PCA) and Redundancy Analyses (RDA) on biotic communities. Significance of explanatory variables in RDAs is given for simple and conditional effects of each single variable. For abbreviations of variables, see Table 1.

Total variation Comparison

Simple Term Effects

Conditional Term Effects

Fungi

Microarthropods

Nematodes

Plants

1360.53

1920.00

131.47

142.42

38.79

Axis 1 17.12 11.04 64.49

Axis 2 12.83 9.00 70.19

Axis 1 10.39 9.33 89.75

Axis 2 9.26 6.78 73.25

Axis 1 40.83 23.11 56.60

Axis 2 12.82 6.40 49.93

Axis 1 43.86 29.94 68.25

Axis 2 19.97 9.84 49.28

Axis 1 29.77 26.98 90.64

Axis 2 16.88 13.99 82.87

Var. Expl. (%)

P(adj)

Var. Expl. (%)

P(adj)

Var. Expl. (%)

P(adj)

Var. Expl. (%)

P(adj)

Var. Expl. (%)

P(adj)

7.2 7.2 6.3 5.5 . 5.3 3.9 4 4.3 7.8 6.9 6.7 6.7 5 4.1 . 5.1 3.6 3.7 2.3 7.8 6.6

0.066 0.066 0.124 0.244 . 0.255 0.613 0.613 0.551 0.066 0.067 0.076 0.076 0.317 0.645 . 0.317 0.666 0.666 1.000 0.076 0.076

7.6 7.6 5.4 5.1 4.6 4.7 4.6 4.5 5.6 5.5 6.1 7.6 7.6 3.9 3.5 3.4 4.7 3.6 4.9 4.4 3.8 6.1

0.001** 0.001** 0.181 0.308 0.409 0.409 0.409 0.409 0.158 0.165 0.054 b0.001*** b0.001*** 0.721 0.721 0.721 0.503 0.721 0.475 0.638 0.721 0.062

12.3 12.3 6.5 3.1 17.8 . . . 10.5 4.7 3.8 3.5 3.5 3.2 3 17.8 . . . 4.6 4.4 2.2

0.034* 0.034* 0.228 0.671 0.011* . . . 0.056 0.437 0.568 0.823 0.823 0.823 0.823 0.008** . . . 0.737 0.737 0.931

8.1 8.1 10.2 1.5 8.6 13.8 20 22.3 . 5.5 1.8 6.6 6.6 4.7 4.1 1.2 3.6 4.4 22.3 . 3.9 1.5

0.131 0.131 0.096 0.938 0.131 0.031* 0.005** 0.003** . 0.321 0.938 0.412 0.412 0.459 0.459 1.000 0.459 0.459 0.003** . 0.459 1.000

24.5 24.5 11.7 4.5 3.5 4.1 2.8 2.7 1.5 . . 24.5 24.5 11.7 4.5 3.5 4.1 2.8 2.7 1.5 . .

b0.001*** b0.001*** 0.005** b0.001*** 0.059 0.185 0.118 0.236 0.154 . . b0.001*** b0.001*** b0.001*** 0.117 0.327 0.143 0.641 0.641 0.978 . .

Var. Expl. by PCA axis [%] Var. Expl. by RDA axis [%] Efficiency of RDA axis [%]

Variable

Bacteria

Status.BLS Status.NOS pH NO316S_Rich Arth_Ab Arth_Rich QBS-ar Nem_Rich Pl_rich Pl_div Status.BLS Status.NOS pH NO316S_Rich Arth_Ab Arth_Rich QBS-ar Nem_Rich Pl_rich Pl_div

most representative group of bacteriophagous nematodes (predators) and bacteria (prey) which could be the first connection in this soil food web. This may be due to the relative inaccuracy of DNA methods for bacteria and the knowledge gap regarding soil nematodes and their population density and trophic interactions (Read et al., 2006). Moreover, approximative taxonomic identification historically affects studies focused on soil food webs (Brose and Scheu, 2014). In line with top-down limitation of intraguild populations due to predation, an inverse correlation between bacterial richness and arthropods was found. These top-down processes could be due to direct impact on detritivorous animals, and to the indirect effect involving nematodes, such as those feeding on bacteria, revealed in arthropod communities. However, the relative contributions of the opposite processes of resource limitation (bottom-up) and limitation of populations by predation (topdown) in the soil ecosystem are still unclear and controversial (e.g. Chen and Wise, 1999; Brose and Scheu, 2014). Data on plant communities confirms the trends already shown in Benesperi et al. (2012), with a series of negative effects linked to the decrease in species richness, diversity and composition. The main cause of changes in local flora clearly appears to be the significant increase in N

pools in BLS, as demonstrated by the importance of N and pH for changes in species composition and by the inverse correlation between soil nitrate content and species richness and diversity. The role of soil nitrification in the impact of invasive nitrogen-fixing trees has been well documented for several species (Acacia dealbata: Lazzaro et al., 2014; Lorenzo et al., 2010; Acacia pycnantha: Lazzaro et al., 2015; Myrica faya: Ehrenfeld, 2010) as well as for BL (Vítková and Kolbek, 2010; Vítková et al., 2017). Nitrification generally drives a shift in species composition, with selection of species more competitive in enriched soils, often leading to low-diversity communities dominated by few abundant and opportunistic species. Nevertheless, the effect of BL invasion may also be related to changes in vegetation structure and dominant tree canopy cover. Indeed, as reported by Vítková et al. (2017) and confirmed in our case study, BLS canopy cover is generally lighter compared to native forests, with both the shrub and herb layers generally denser, resulting in conditions that are unfavourable for the establishment of shade-tolerant native tree seedlings. These changes in canopy condition may determine a loss in microhabitats and in ground condition variability (i.e. light and nutrients), as already suggested by Sitzia et al. (2012), affecting also soil fauna. It is generally accepted that an increase in light

Table 3 Correlation matrix indicating Spearman's rho values. Among variables significantly affected by the invasion status. Significant values are in bold. Asterisks in brackets express statistical significance: P value b0.001 = ***; P value b0.01 = **; P value b0.05 = *. For abbreviations of variables, see Table 1.

pH NO3− 16S_Rich Arth_Ab Arth_Rich QBS-ar Nem_Rich Pl_Rich Pl_Div

pH

NO3−

16S_Rich

Arth_Ab

Arth_Rich

QBS-ar

Nem_Rich

Pl_Rich

Pl_Div

–

0.272 –

−0.235 0.425(*) –

0.01 −0.31 −0.503(*) –

0.304 −0.263 −0.441(*) 0.7(***) –

0.221 −0.238 −0.46(*) 0.758(***) 0.946(***) –

0.407(*) 0.055 −0.31 0.351 0.437(*) 0.498(*) –

−0.307 −0.521(**) 0.358 −0.031 −0.034 −0.1 −0.377 –

−0.1 −0.695(***) 0.003 0.1 0.275 0.1 −0.059 0.785(***) –

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Fig. 3. Network graph showing correlations between biotic and abiotic indices. Dotted lines indicate non-significant linkages; solid lines indicate significant linkages. Black lines indicate negative correlations and red lines positive ones. Line width only reflects the absolute value of the correlation in the case of significant correlations. For abbreviations of variables, see Table 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

and temperature (e.g. by the removal of trees by clear cutting, or other methods) have a significant effect on the invertebrate fauna of the forest floor, even if effects on arthropod communities are complex and difficult to analyse (Huhta et al., 1967). Moreover, it has been demonstrated that changes in microhabitat complexity may influence species richness of several animal taxa, including arthropods (Gardner et al., 1995; Hansen, 2000). Our data showed once more that BL poses a severe threat to ecosystems, decreasing local biodiversity of microarthropods, nematodes and plant communities, especially in areas where it becomes a dominant species. In our case it replaces nutrient-poor oak forests, many of which are habitats considered worthy of conservation in Europe (Habitats Directive, 92/43 ECE). As underlined by Motta et al. (2009), correct management of BL is urgently required, especially since it is commonly used in forestry production. Indeed the current applied coppice management consisting in repeated clear cuttings each 20–30 years is the main cause of BL invasion of native forests (Radtke et al., 2013). This facilitation of BL invasion is linked to two main processes: the regular clearcuts firstly create light-abundant sites (which are suitable for the first colonization by BL), and secondarily facilitate the generative and vegetative regeneration of this invasive tree species (Radtke et al., 2013). To conclude, our study demonstrates the effects of the invasive BL on several components of the invaded ecosystem, specifically elucidating several new traits for soil nematode and microarthropod communities but more and more studies are needed to assess the many possible cascading effects of this widespread controversial invasive species.

Authors' contributions L.Laz. and G.M. conceived the idea, the sampling design and led the writing of the manuscript. L.Laz., G.M., L.Las., C.G., A.L., S.L., G.d'E., R.P., A.I., G.T., A.F designed the sampling methodology and participated to the field data collection and to the subsequent data analyses for the different abiotic and biotic ecosystem components. L.Laz. performed the statistical analyses. All authors critically contributed to the papers and approved the last version for publication. Data accessibility Data are accessible at https://figshare.com/s/7cadd78bc93afbd0b2b6 (doi: 10.6084/m9.figshare.5469142). Acknowledgements We thank Helen Jane Ampt for the English revision and Niccolò Orlandi for his help during the laboratory work. We also thanks the two anonymous referee for the precious suggestions that greatly improved the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2017.10.017.

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References Bedding, R.A., Akhurst, R.J., 1975. A simple technique for the detection of insect parasitic nematodes in soil. Nematologica 21:109–110. https://doi.org/10.1163/ 187529275X00419. Benesperi, R., Giuliani, C., Zanetti, S., Gennai, M., Mariotti Lippi, M., Guidi, T., Nascimbene, J., Foggi, B., 2012. Forest plant diversity is threatened by Robinia pseudoacacia (black-locust) invasion. Biodivers. Conserv. 21:3555–3568. https://doi.org/10.1007/s10531012-0380-5. Benjamini, Y., Hochberg, Y., 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat Methodol. 57, 289–300. Bongers, T., 1988. De nematoden van Nederland: een identificatietabel voor de in Nederland aangetroffen zoetwater-en bodembewonende nematoden. In: Vereniging, K.N.N. (Ed.), Stichting Uitgeverij Koninklijke Nederlandse Natuurhistorische Vereniging. Bongers, T., 1990. The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia 83, 14–19. Brose, U., Scheu, S., 2014. Into darkness: unravelling the structure of soil food webs. Oikos 123:1153–1156. https://doi.org/10.1111/oik.01768. Buzhdygan, O.Y., Rudenko, S.S., Kazanci, C., Patten, B.C., 2016. Effect of invasive black locust (Robinia pseudoacacia L.) on nitrogen cycle in floodplain ecosystem. Ecol. Model. 319, 170–177. CBD decision VI/23, 2014. [internet: cited 2014 Feb 15]. Available from: http:// www.cbd.int/doc/decisions/cop-06-dec-23-en.pdf. Chen, B.R., Wise, D.H., 1999. Bottom–up limitation of predaceous arthropods in a detritusbased terrestrial food web. Ecology 80, 761–772. Costantini, E.A.C., L'Abate, G., Barbetti, R., Fantappié, M., Lorenzetti, R., Magini, S., 2012. Soil Map of Italy, Scale 1:1.000.000. S.EL.CA, Firenze, Italia. Csardi, G., Nepusz, T., 2006. The igraph software package for complex network research. InterJournal, Compl. Syst. 1695, 1–9. Del Re, A.C., 2013. compute.es: Compute Effect Sizes. R Package Version 0.2-2. Ehrenfeld, J.G., 2010. Ecosystem consequences of biological invasions. Annu. Rev. Ecol. Evol. Syst. 41:59–80. https://doi.org/10.1146/annurev-ecolsys-102209-144650. Ettema, C.H., 1998. Soil nematode diversity: species coexistence and ecosystem function. J. Nematol. 30, 159–169. Ferris, H., Bongers, T., De Goede, R., 2001. A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Appl. Soil Ecol. 18:13–29. https://doi.org/ 10.1016/S0929-1393(01)00152-4. Fierer, N., Jackson, R.B., 2006. The diversity and biogeography of soil bacterial communities. Proc. Natl. Acad. Sci. U. S. A. 103:626–631. https://doi.org/10.1073/pnas.0507535103. Gardner, S.M., Cabido, M.R., Valladares, G.R., Diaz, S., 1995. The influence of habitat structure on arthropod diversity in Argentine semi-arid Chaco forest. J. Veg. Sci. 6 (3), 349–356. Gennai, M., 2011. Il paesaggio vegetale della Provincia di Pistoia. (PhD thesis). University of Florence. Gratton, C., Denno, R.F., 2005. Restoring of arthropod assemblages in a Spartina Salt Marsh following removal of the invasive plant Phragmites australis. Restor. Ecol. 13:358–372. https://doi.org/10.1111/j.1526-100X.2005.00045.x. Grayston, S.J., Prescott, C.E., 2005. Microbial communities in forest floors under four tree species in coastal British Columbia. Soil Biol. Biochem. 37:1157–1167. https:// doi.org/10.1016/j.soilbio.2004.11.014. Greco, N., Carletti, B., 2014. Estrazione, allevamento e conservazione dei nematodi. In: Ambrogioni, L., d'Errico, F.P., Greco, N., Marinari-Palmisano, A., Roversi, P.F. (Eds.), Nematologia Agraria generale e applicata. Società Italiana di Nematologia, Bari, pp. 117–153. Hansen, R.A., 2000. Effects of habitat complexity and composition on a diverse litter microarthropod assemblage. Ecology 81 (4):1120–1132. https://doi.org/10.1890/ 0012-9658(2000)081[1120:EOHCAC]2.0.CO;2. Hejda, M., Pyšek, P., Jarošík, V., 2009. Impact of invasive plants on the species richness, diversity and composition of invaded communities. J. Ecol. 97:393–403. https://doi.org/ 10.1111/j.1365-2745.2009.01480.x. Hollander, M., Wolfe, D.A., 1973. Nonparametric Statistical Methods. John Wiley, New York. Huhta, V., Karppinen, E., Nurminen, M., Valpas, A., 1967. Effect of silvicultural practices upon arthropods, annelid and nematode populations in coniferous forest soil. Ann. Zool. Fenn. 4 (2), 87–145. Hui, A., Marraffa, J.M., Stork, C.M., 2004. A rare ingestion of the Black Locust tree. J. Toxicol. Clin. Toxicol. 42:93–95. https://doi.org/10.3109/15563650.2013.806660. Hulme, P.E., Pyšek, P., Jarošík, V., Pergl, J., Schaffner, U., Vila, M., 2013. Bias and error in understanding plant invasion impacts. Trends Ecol. Evol. 28:212–218. https://doi.org/ 10.1016/j.tree.2012.10.010. Jobin, A., Schaffer, U., Nentwig, W., 1996. The structure of the phytophagous insect fauna on the introduced weed Solidago altissima in Switzerland. Entomol. Exp. Appl. 79:33–42. https://doi.org/10.1111/j.1095-8312.1994.tb01011.x. Kaya, H.K., Stock, P., 1997. Techniques in insect nematology. In: Lacey, L.A. (Ed.), Manual of Techniques in Insect Pathology. Academic Press, London, pp. 281–324. Khan, B., Ablimit, A., Mahmood, R., Qasim, M., 2010. Robinia pseudoacacia leaves improve soil physical and chemical properties. J. Arid. Land 4, 266–271. Kleinbauer, I., Dullinger, S., Peterseil, J., Essl, F., 2010. Climate change might drive the invasive tree Robinia pseudoacacia into nature reserves and endangered habitats. Biol. Conserv. 143:382–390. https://doi.org/10.1016/j.biocon.2009.10.024. Lauber, C.L., Strickland, M.S., Bradford, M.A., Fierer, N., 2008. The influence of soil properties on the structure of bacterial and fungal communities across land-use types. Soil Biol. Biochem. 40:2407–2415. https://doi.org/10.1016/j.soilbio.2008.05.021. Lazzaro, L., Giuliani, C., Fabiani, A., Agnelli, A.E., Pastorelli, R., Lagomarsino, A., Benesperi, R., Calamassi, R., Foggi, B., 2014. Soil and plant changing after invasion: the case of Acacia dealbata in a Mediterranean ecosystem. Sci. Total Environ. 497−498:491–498. https:// doi.org/10.1016/j.scitotenv.2014.08.014.

9

Lazzaro, L., Giuliani, C., Benesperi, R., Calamassi, R., Foggi, B., 2015. Plant species loss and community nestedness after leguminous tree Acacia pycnantha invasion in a Mediterranean ecosystem. Folia Geobot. 50:229–238. https://doi.org/10.1007/s12224-0159222-z. Lee, Y.C., Nam, J.M., Kim, J.G., 2011. The influence of black locust (Robinia pseudoacacia) flower and leaf fall on soil phosphate. Plant Soil 341:269–277. https://doi.org/ 10.1007/s11104-010-0642-5. Levin, L.A., Neira, C., Groshilz, E.D., 2006. Invasive cordgrass modified wetland trophic function. Ecology 87, 419–432. Litt, A.R., Cord, E.E., Fulbright, T.E., Schuster, G.L., 2014. Effects of invasive plants on arthropods. Conserv. Biol. 28:1532–1549. https://doi.org/10.1111/cobi.12350. Longcore, T., 2003. Terrestrial arthropods as indicators of ecological restoration success in coastal sage scrub (California, USA). Restor. Ecol. 11:397–409. https://doi.org/ 10.1046/j.1526-100X.2003.rec0221.x. Lorenzo, P., González, L., Reigosa, M.J., 2010. The genus Acacia as invader: the characteristic case of Acacia dealbata Link in Europe. Ann. For. Sci. 67 (1):101. https://doi.org/ 10.1051/forest/2009082. Macedo, M.O., Resende, A.S., Garcia, P.C., Boddey, R.M., Jantalia, C.P., Urquiaga, S., Campello, E.F.C., Franco, A.A., 2008. Changes in soil C and N stocks and nutrient dynamics 13 years after recovery of degraded land using leguminous nitrogen-fixing trees. For. Ecol. Manag. 255:1516–1524. https://doi.org/10.1016/j.foreco.2007.11.007. Mai, W.F., Lyon, H.H., 1962. Pictorial key to genera of plant parasitic nematodes. Plates Reproduced by Art Craft of Ithaca, Inc. Ithaca, New York. Marinari-Palmisano, A., Vinciguerra, M., 2014. Classificazione dei nematodi. In: Ambrogioni, L., d'Errico, F.P., Greco, N., Marinari-Palmisano, A., Roversi, P.F. (Eds.), Nematologia Agraria generale e applicata. Società Italiana di Nematologia, Bari, pp. 23–42. Mazza, G., Tricarico, E., Genovesi, P., Gherardi, F., 2014. Biological invaders are threats to human health: an overview. Ethol. Ecol. Evol. 26:112–129. https://doi.org/10.1080/ 03949370.2013.863225. McNeely, J.A., Mooney, H.A., Neville, L.E., Schei, P., Waage, J.K., 2001. Global Strategy on Invasive Alien Species. IUCN on behalf of Global Invasive Species Program, Gland, Switzerland. Cambridge, UK. Medina-Villar, S., Rodríguez-Echeverría, S., Lorenzo, P., Alonso, A., Pérez-Corona, E., CastroDíez, P., 2016. Impacts of the alien trees Ailanthus altissima (Mill.) Swingle and Robinia pseudoacacia L. on soil nutrients and microbial communities. Soil Biol. Biochem. 96, 65–73. Mipaaf, 2000. Ministero delle Politiche Agricole, Alimentari e Forestali. Osservatorio Nazionale Pedologico e per la Qualità del Suolo. Metodi di Analisi Chimica del Suolo. Franco Angeli, Milano. Motta, R., Nola, P., Berretti, R., 2009. The rise and fall of the black locust (Robinia pseudoacacia L.) in the “Siro Negri” Forest Reserve (Lombardy, Italy): lessons learned and future uncertainties. Ann. For. Sci. 66:410–420. https://doi.org/10.1051/forest/ 2009012. Nascimbene, J., Lazzaro, L., Benesperi, R., 2015. Patterns of β-diversity and similarity reveal biotic homogenization of epiphytic lichen communities associated with the spread of black locust forests. Fungal Ecol. 14:1–7. https://doi.org/10.1016/j.funeco.2014.10.006. Nasiri, H., Iqbal, Z., Hiradate, S., Fujii, Y., 2005. Allelopathic potential of Robinia pseudoacacia L. J. Chem. Ecol. 31:2179–2192. https://doi.org/10.1007/s10886-005-6084-5. Nübel, U., Engelen, B., Felske, A., Snaidr, J., Wieshuber, A., Amann, R.I., Ludwig, W., Backhaus, H., 1996. Sequence heterogeneities of genes encoding 16S rRNAs in Paenibacillus polymyxa detected by temperature gradient gel electrophoresis. J. Bacteriol. 178: 5636–5643. https://doi.org/10.1128/jb.178.19.5636-5643.1996. Olden, J.D., Rooney, T.P., 2006. On defining and quantifying biotic homogenization. Glob. Ecol. Biogeogr. 15:113–120. https://doi.org/10.1111/j.1466-822X.2006.00214.x. Parisi, V., Menta, C., Gardi, C., Jacomini, C., Mozzanica, E., 2005. Microarthropod communities as a tool to assess soil quality and biodiversity: a new approach in Italy. Agric. Ecosyst. Environ. 105:323–333. https://doi.org/10.1016/j.agee.2004.02.002. Pastorelli, R., Landi, S., Trabelsi, D., Piccolo, R., Mengoni, A., Bazzicalupo, M., Pagliai, M., 2011. Effects of soil management on structure and activity of denitrifying bacterial communities. Appl. Soil Ecol. 49:46–58. https://doi.org/10.1016/j.apsoil.2011.07.002. Pyšek, P., Lambdon, P.W., Arianoutsou, M., Kühn, I., Pino, J., Winter, M., 2009. Alien vascular plants of Europe. In: DAISIE (Ed.), Handbook of Alien Species in Europe. Springer, Netherlands, pp. 43–61. R Core Team, 2016. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Radtke, A., Ambraß, S., Zerbe, S., Tonon, G., Fontana, V., Ammer, C., 2013. Traditional coppice forest management drives the invasion of Ailanthus altissima and Robinia pseudoacacia into deciduous forests. For. Ecol. Manag. 291, 308–317. Rahmonov, O., 2009. The chemical composition of plant litter of black locust (Robinia pseudoacacia L.) and its ecological role in sandy ecosystems. Acta Ecol. Sin. 29: 237–243. https://doi.org/10.1016/j.chnaes.2009.08.006. Rasche, F., Knapp, D., Kaiser, C., Koranda, M., Kitzler, B., Zechmeister-Boltenstern, S., Richter, A., Sessitsch, A., 2011. Seasonality and resource availability control bacterial and archaeal communities in soils of a temperate beech forest. ISME J. 5:389–402. https:// doi.org/10.1038/ismej.2010.138. Read, D.S., Sheppard, S.K., Bruford, M.W., Glen, D.M., Symondson, O.C., 2006. Molecular detection of predation by soil micro-arthropods on nematodes. Mol. Ecol. 15:1963–1972. https://doi.org/10.1111/j.1365-294X.2006.02901.x. Reinhart, K.O., Callaway, R.M., 2006. Soil biota and invasive plants. New Phytol. 170: 445–457. https://doi.org/10.1111/j.1469-8137.2006.01715.x. Rice, S.K., Westerman, B., Federici, R., 2004. Impacts of the exotic, nitrogen-fixing black locust (Robinia pseudoacacia) on nitrogen-cycling in a pine–oak ecosystem. Plant Ecol. 174 (1), 97–107. Sitzia, T., Campagnaro, T., Dainese, M., Cierjacks, A., 2012. Plant species diversity in alien black locust forests: a paired comparison with native stands across a north-

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Mediterranean range expansion. For. Ecol. Manag. 285:85–91. https://doi.org/ 10.1016/j.foreco.2012.08.016. Ter Braak, C.J.F., Šmilauer, P., 2012. Canoco Reference Manual and User's Guide: Software for Ordination, Version 5.0. Microcomputer Power, USA. Vainio, E.J., Hantula, J., 2000. Direct analysis of wood-inhabiting fungi using denaturing gradient gel electrophoresis of amplified ribosomal DNA. Mycol. Res. (8):927–936 https://doi.org/10.1017/S0953756200002471. Van Miegrot, H., Cole, D.W., 1984. The impact of nitrification on soil acidification and cation leaching in red alder ecosystem. J. Environ. Qual. 13, 586–590. Vilà, M., Espinar, J.L., Hejda, M., Hulme, P.E., Jarošík, V., Maron, J.L., Pergl, J., Schaffner, U., Pyšek, P., 2011. Ecological impacts of invasive alien plants: a meta-analysis of their effects on species, communities and ecosystems. Ecol. Lett. 14:702–708. https://doi.org/ 10.1111/j.1461-0248.2011.01628.x. Vilà, M., Rohr, R.P., Espinar, J.L., Hulme, P.E., Pergl, J., Le Roux, J.J., Schaffner, U., Pyšek, P., 2014. Explaining the variation in impacts of non-native plants on local-scale species richness: the role of phylogenetic relatedness. Glob. Ecol. Biogeogr. 24:139–146. https://doi.org/10.1111/geb.12249. Villani, M.G., Allee, L.L., Diaz, A., Robbins, P.S., 1999. Adaptive strategies of edaphic arthropods. Annu. Rev. Entomol. 44:233–256. https://doi.org/10.1146/annurev.ento.44.1.233. Vítková, M., Kolbek, J., 2010. Vegetation classification and synecology of Bohemian Robinia pseudoacacia stands in a Central European context. Phytocoenologia 40:205–241. https://doi.org/10.1127/0340-269X/2010/0040-0425.

Vítková, M., Tonika, J., Müllerová, J., 2015. Black locust-successful invader of a wide range of soil conditions. Sci. Total Environ. 505:315–328. https://doi.org/10.1016/ j.scitotenv.2014.09.104. Vítková, M., Müllerová, J., Sádlo, J., Pergl, J., Pyšek, P., 2017. Black locust (Robinia pseudoacacia) beloved and despised: a story of an invasive tree in Central Europe. For. Ecol. Manag. 384:287–302. https://doi.org/10.1016/j.foreco.2016.10.057. Vreeken-Buijs, M.J., Hassink, J., Brussaard, L., 1998. Relationships of soil microarthropod biomass with organic matter and pore size distribution in soils under different land use. Soil Biol. Biochem. 30:97–106. https://doi.org/10.1016/S0038-0717(97)00064-3. Wickham, H., 2016. ggplot2: elegant graphics for data analysis. Springer. Wilson, M., Gaugler, R., 2004. Factors limiting short-term persistence of entomopathogenic nematodes. J. Appl. Entomol. 128:250–253. https://doi.org/10.1111/j.14390418.2004.00814.x. Wolfe, L.M., Elzinga, J.A., Biere, A., 2004. Increased susceptibility to enemies following introduction in the invasive plant Silene latifolia. Ecol. Lett. 7:813–820. https://doi.org/ 10.1111/j.1461-0248.2004.00649.x. Yeates, G., Bongers, T., De Goede, R., Freckman, D., Georgieva, S., 1993. Feeding habits in soil nematode families and genera in outline for soil ecologistis. J. Nematol. 25, 315–331.

Please cite this article as: Lazzaro, L., et al., How ecosystems change following invasion by Robinia pseudoacacia: Insights from soil chemical properties and soil microbial, nematode, microarthropod ..., Sci Total Environ (2017), https://doi.org/10.1016/j.scitotenv.2017.10.017