Coastal reclamation alters soil microbial communities following different land use patterns in the Eastern coastal zone of China

Coastal reclamation seriously disturbs coastal wetland ecosystems, while its influences on soil microbial communities remain unclear. In this study, we examined the impacts of coastal reclamation on soil microbial communities based on phospholipid fatty acids (PLFA) analysis following the conversion of Phragmites australis wetlands to different land use types. Coastal reclamation enhanced total soil microbial biomass and various species (i.e., gram-positive bacterial, actinomycete, saturated straight-chain, and branched PLFA) following the conversion of P. australis wetland to aquaculture pond, wheat, and oilseed rape fields. In contrast, it greatly decreased total soil microbial biomass and various species following the conversion of P. australis wetland to town construction land. Coastal reclamation reduced fungal:bacterial PLFA, monounsaturated:branched PLFA ratios, whereas increasing gram-positive:gram-negative PLFA ratio following the conversion of P. australis wetland to other land use types. Our study suggested that coastal reclamation shifted soil microbial communities by altering microbial biomass and community composition. These changes were driven primarily by variations in soil nutrient substrates and physiochemical properties. Changes in soil microbial communities following coastal reclamation impacted the decomposition and accumulation of soil carbon and nitrogen, with potential modification of carbon and nitrogen sinks in the ecosystems, with potential feedbacks in response to climate change.

. The soil/sediment MBC:MBN ratio was highest in the town construction land between land use types (Fig. 2c). The P. australis wetland and oilseed rape field showed the lowest soil/sediment MBC:MBN ratio between land use types (Fig. 2c). The total soil/sediment PLFA content in the aquaculture pond increased 1.37-5.49-fold, compared to the P. australis wetland, wheat and oilseed rape fields, and town construction land (Fig. 3a). The contents of total, bacterial, gram-positive (gram + ) bacterial, actinomycete, and branched PLFA were highest in the aquaculture pond followed by the wheat and oilseed rape fields, the P. australis wetland, and town construction land (Figs. 3 and 4). The contents of soil fungal, monounsaturated, and arbuscular mycorrhizal fungal (AMF) PLFA were highest in the P. australis wetland between land use types ( Figs. 3 and 4). The lowest total, bacterial, fungal, gram + bacterial, actinomycete PLFA contents were found in the town construction land (Figs. 3 and 4a). The soil/sediment gram-negative (gram -) bacterial PLFA content in the aquaculture pond was significantly (P < 0.05) higher than that in P. australis wetland, wheat and oilseed rape fields, and town construction land (Fig. 3f). The soil/sediment grambacterial PLFA content in the P. australis wetland and wheat field was significantly (P < 0.05) higher than that in oilseed rape field and town construction land (Fig. 3f). The saturated straight-chain (SSC) PLFA content was highest in the aquaculture pond between land use types (Fig. 4b). The contents of actinomycete and SSC PLFA in wheat and oilseed rape fields was significantly (P < 0.05) higher than that in P. australis wetland and town construction land (Fig. 4a,b).
The highest soil fungal:bacterial (F:B) PLFA ratio was observed in the P. australis wetland between land use types (Fig. 3d). The soil F:B PLFA ratio in aquaculture pond, wheat field and town construction land was significantly (P < 0.05) lower than that in oilseed rape field (Fig. 3d). The gram + :gram -PLFA ratio was highest and lowest in the aquaculture pond and the P. australis wetland, respectively (Fig. 3g). The gram + :gram -PLFA ratio in wheat and oilseed rape fields was significantly (P < 0.05) higher than that in town construction land (Fig. 3g). The P. australis wetland and town construction land exhibited a higher monounsaturated:branched PLFA ratio, relative to the aquaculture pond and the wheat field (Fig. 4f). The bacterial stress index was highest in the aquaculture pond followed by the wheat and oilseed rape fields, and town construction land, which was lowest in the P. australis wetland (Fig. 4c).

Relationships between soil microbial communities and soil properties. Seven soil property vari-
ables that were present in the ordination explained 87.2% of the total variability of the PLFA (Fig. 5). The PLFA variations were significantly (P < 0.05) related to SOC (F = 13.05, P = 0.0020), salinity (F = 33.20, P = 0.0020), WSOC (F = 4.29, P = 0.0100) (Fig. 5). Pearson's correlation analysis indicated that MBC, MBN, total PLFA, bacterial, gram + bacterial, gram − bacterial, actinomycete, saturated straight-chain, and branched PLFA had obviously positive correlations with soil moisture, SOC, WSOC, and SON, which had a negative correlation with soil pH (Table 2). Soil AMF PLFA was highly related to soil salinity and pH ( Table 2). The soil F:B PLFA ratio was inversely associated with the SOC and SON ( Table 2). The soil gram + :gram − PLFA ratio was highly correlated with soil moisture, SOC, WSOC, and SON (Table 2). However, there was a significant negative correlation between the gram + :gram − PLFA ratio and soil pH ( Table 2). The soil monounsaturated:branched PLFA ratio had a negative correlation with soil moisture (Table 2).

Discussion
Coastal reclamation enhanced the total microbial biomass (MBC, MBN and total PLFA) (Figs. 2 and 3a), and the quantities of vast majority of microbial community composition following the conversion of P. australis wetland to aquaculture pond, wheat, and oilseed rape fields (Figs. 3 and 4). Whereas, the MBC, MBN, bacterial, fungal, grambacterial, AMF, actinomycete, and monounsaturated PLFA substantially decreased following the  www.nature.com/scientificreports/ conversion of P. australis wetland to town construction land (Figs. 2, 3 and 4). These variation trends of soil microbial communities following coastal reclamation was in according with the results of our previous study showing that coastal reclamation enhanced the accumulation of soil total, labile and recalcitrant organic C and N following conversion of P. australis salt marsh into fishpond, wheat and rapeseed fields 21 . Whereas, coastal reclamation decreased the sequestration of soil total, labile and recalcitrant organic C and N following conversion of P. australis salt marsh into town construction land 21 . Previous studies reported that the SOC and SON  www.nature.com/scientificreports/ concentrations were determined by organic detritus input, sequestered C and N via bio-chemical and physical processes, loss of organic C and N through SOM decomposition, and erosion and leaching 22 . Chen et al. 23 showed that approximately 30% of the fish food introduced into aquaculture pond was not consumed, which eventually settled into the sediment of aquaculture pond through a series of decomposition processes in the Jiangsu coast. It was reasoned that SOC, WSOC, and SON were highest in the aquaculture pond between land use types, that were largely due to the substantial amount of organic detritus (e.g., organism feces, feed remnants, and partial residual bodies) inputting into the sediment of the aquaculture pond, and ultimately promoted sediment organic C and N sequestration in the aquaculture pond (Table 1) 21,23 . In addition, sediment in the aquaculture pond was immersed in water which provided an anaerobic environment in the sediment. We deduced that high sediment moisture and anaerobic environment in the aquaculture pond were beneficial for sediment organic C and N accumulation over the long-term (Table 1) 21,24 , as SOM accumulated under anaerobic and/or waterlogged conditions (e.g., aquaculture pond) exhibited a lower decomposition rate 25 .
High alkalinity and salinity are basic features of coastal wetlands 20 , which are the primary limiting factors for agricultural production in coastal zones 5,26 . Grybos et al. 27 reported that high soil pH can lead to insufficient nutrients for crop growth owing to promoting the immobilization of manganese, iron, and zinc in soils. Krishnamoorthy et al. 28 documented that high soil salinity severely restricted plant growing, which caused physiological drought to plants, cell toxicity, and nutrient imbalance for crops. Currently, fresh water irrigation has been regarded as a very effective measure to dealkali and desalinate the soil to accommodate the growth of crops following the reclamation of coastal wetlands 5,20,21 . In this study, we found that SOC and SON levels greatly increased following conversion of P. australis salt marsh into wheat and rapeseed fields ( Table 1). This result is consistent with previous studies, which revealed that reclaimed farmlands effectually promoted SOC and SON sequestration by altering hydrological regimes from ditch drainage, diking, and irrigation, and lower soil pH and salinity relative to coastal wetlands 11,21 . It was inferred that greatly decreased soil pH and salinity, and increased inputs of aboveground biomass, as well as the application of chemical fertilizers contributed to greater SOC and SON accumulation in the wheat and oilseed rape fields compared to P. australis wetland (Table 1) 21 . Conversely, SOC, WSOC, and SON levels were lowest in town construction land (Table 1), which may have been owing to the loss of vegetative cover and without exogenous organic detritus entering the soil.
Coastal reclamation greatly shifted soil/sediment microbial biomass and community composition (Figs. 2, 3 and 4). In this study, the redundancy analysis (RDA) clearly showed that the variations in soil microbial community were the most intimately related to SOC, salinity, and WSOC (Fig. 5), which further demonstrated that soil nutrient substrates (e.g., SOC, WSOC, and SON) were the overarching driving factors for soil microbial communities 29 , especially for soil bacteria and fungi 30,31 , as they provided a great quantity of available nutrients for soil microbes 32 , and played crucial roles in altering the composition of microbial communities for resource competition 33 . Additionally, previous studies demonstrated that high soil salinity has a considerable effect on growth 34 , quantity and structure 17 of soil microbes, as well as inhibited extracellular enzyme activity through altering the habitat of soil microbes 35 . Aside from SOC, soil salinity, and WSOC, the Pearson's correlation analysis indicated that the total and the vast majority of soil microbial compositions were highly correlated with soil moisture, which were significantly negatively related to soil pH ( Table 2). This finding was supported by previous studies suggesting that soil pH and moisture played vital roles in altering soil microbial biomass and community composition 15,18,19 . Thus, we extrapolated that greatly increased soil/sediment microbial biomass (MBC, MBN and total PLFA), as well as various microbial community composition (i.e., gram-positive bacterial, actinomycete, saturated straight-chain, and branched PLFA) following the conversion of P. australis wetland to aquaculture pond, wheat, and oilseed rape fields were primarily attributed to the higher level of soil nutrient substrates, and decreased soil salinity and pH which lifted the restriction of high salinity and alkalinity on the growth of soil microbial communities in aquaculture pond, wheat, and oilseed rape fields (Tables 1 and 2; Figs. 2, 3, and 4).
Among soil microbes, AMF community plays a crucial role in enhancement of nutrient uptake and the tolerance of their host plants to various environmental stresses 36,37 . Interestingly, we found that the quantity of AMF PLFA substantially reduced following the conversion of P. australis wetland to other soil land use types (Fig. 3h). This result was supported by Cui et al. 37 exhibiting that coastal reclamation negatively affects AMF community structure and diversity in coastal saline-alkaline lands during the past 30 years of reclamations. Previous studies demonstrated that soil salinity and pH were the dominant factors driving structure and the distribution of soil AMF community 37,38 . Our Pearson's correlation analysis displayed that soil AMF PLFA was highly related to soil salinity and pH ( Table 2). Coastal wetland is the buffer zone between the sea and land, and it is characterized by its high salinity, high pH, low nutrient substrates, varied temperatures, and an unstable sandy substrate 39 . It was deduced that AMF community played a vital role in the coastal wetlands ecosystem, and the most enriched AMF community in P. australis wetland can provide more nutrient elements (e.g., N and P) for P. australis community, and assist P. australis community to adapt oligotrophic and extreme environment with multiple stresses (Table 1 and Fig. 3h) 36,37 . When soil properties tended to be stable and the needed nutrients for plant growth raised (Table 1), the role of AMF community altered and their quantity became less (Fig. 3h) 37 .
The F:B PLFA ratio is considered to be a key index for evaluating the responses of fungal and bacterial biomass to environmental variabilities 32,40 . Interestingly, coastal reclamation significantly (P < 0.05) increased soil bacterial PLFA following the conversion of P. australis wetland to aquaculture pond and wheat field (Fig. 3b), whereas soil fungal PLFA and the F:B PLFA ratio substantially decreased following coastal reclamation (Fig. 3c,d).
Previous studies have documented that the availability of soil nutrient is the dominating factor that impacts the F:B PLFA ratio 32 . The responses of soil bacterial and fungal communities to the availability of soil nutrient can entirely differ 32,[41][42][43] . Generally, soil bacterial communities with higher organic matter inputs, combined with plentiful available nutrients are more remarkably abundant compared with fungal communities 32,43 . Soil fungal communities have the capacity to degrade more recalcitrant organic materials and prefer nutrient-poor environments 41 www.nature.com/scientificreports/ soil nutrient availability. Thus, the highest quantity of soil fungal PLFA and F:B PLFA ratio in the P. australis wetland may have been primarily attributed to low nutrient availability which promoted the growth of fungi rather than bacteria, as bacteria favor nutrient-rich conditions 45 , while fungi prefer conditions with low nutrient levels (Fig. 3c,d) 46 . The gram + :gram -PLFA ratio is recognized as an important indicator for microbial community structures and ecological functions 47 . In this study, the gram + :gram -PLFA ratio ranged from 0.52 to 1.90 between land use types (Fig. 3g), which exhibited that gram − bacteria dominated in the P. australis wetland, and gram + bacteria dominated in the reclaimed land use types. Coastal reclamation greatly raised gram + :gram -PLFA ratio following the conversion of P. australis wetland to other land use types (Fig. 3g). Previous studies have reported that gram + bacteria are considered as oligotrophic K-strategists 44,48 , which prefer to utilize recalcitrant soil C (e.g., SOM-derived C) as an energy source, with slow growing rates 49 . Conversely, gram − bacteria favor soils with easily degradable organic substances (e.g., plant materials and fungal exudates) as carbon sources 42 , which are viewed as copiotrophic r-strategists 44,48 . However, our the Pearson's correlation analysis showed that the gram + :gram − PLFA ratio was positively correlated with SOC, WSOC, and SON (Table 2), which was consistent with the results presented by Xu et al. 47 and Luo et al. 50 . Further, earlier study reported that soil pH plays a crucial role in modifying the composition of bacterial communities 51 . Rousk et al. 15 confirmed that grambacteria biomass increases, while gram + bacteria biomass decreases, in response to higher soil pH. It may be presumed that the lowest gram + :gram -PLFA ratio in the P. australis wetland may be partly the result of the highest soil pH in the P. australis wetland, which promoted grambacteria growth (Fig. 3g) 15,52 . This deduction was supported by our finding that the gram + :gram − PLFA ratio exhibited a significant negative correlation to soil pH (Table 2). Typically, the bacterial stress index may be employed to indicate the physiological status of grambacteria communities 53 . A high bacterial stress index represents a slow growth phase a slow rate of growth and slow turnover of grambacteria, as the result of being affected by various stresses, such as low pH 54,55 . The bacterial stress index was highest in the aquaculture pond (Fig. 4c), which suggested that a low rate of growth and slow turnover of grambacteria was observed in the aquaculture pond relative to gram + bacteria due to high stress from the lowest soil pH (Table 1; Figs. 3g and 4c).
The soil monounsaturated:branched PLFA ratio can indicate the relative ratio of aerobic to anaerobic microbes 32,54,56 . The soil monounsaturated:branched PLFA ratio was highest in the P. australis wetland (Fig. 4f), which implied that P. australis wetland possessed the highest proportion of aerobic microbes between land use types. This was tightly associated with the lowest soil moisture and high soil aeration in the P. australis wetland (Table 1). Contrarily, the lowest soil monounsaturated:branched PLFA ratio was observed in the aquaculture pond (Fig. 4f), which indicated that it had the highest proportion of anaerobic microbes between land use types. This result was likely caused by high anaerobic state (i.e., flooded conditions) of the sediment in the aquaculture pond (Table 1), which is beneficial for the growth of anaerobic microbes (Fig. 4e). The highest proportion of anaerobic microbes were accompanied by high anaerobic environment can slow down the decomposition of SOM (Fig. 4e) 24 , and promote SOC and SON sequestration in the aquaculture pond (Table 1) 32 .
In conclusion, this study emphasized the shifts in soil microbial biomass and community composition in P. australis wetland that have been converted to different land use types in the Eastern coastal zone of China. Our study suggested that coastal reclamation altered the soil microbial biomass and community composition through the modification of soil nutrient substrates (SOC, WSOC, and SON) and physiochemical properties (e.g., soil salinity, pH and moisture) of the soil. Coastal reclamation greatly altered the F:B PLFA, gram + :gram -PLFA, and monounsaturated:branched PLFA ratios. These changes in microbial community structures were involved in regulation of SOC and SON decomposition and accumulation. This study offers new insights toward a better understanding of the consequences of coastal reclamation to ecosystem processes and functions, as well as the further elucidation of variations in, and drivers of, soil microbial communities.

Methods
Study site and sampling. This study was conducted in the Yancheng Yellow Sea coast of Jiangsu Province, China (Fig. 1). Specific sampling transects were located next to the Dafeng Nature Reserve (32°00′-33°15′ N, 120°40′-121°00′ E; Fig. 1). This area has an annual average temperature of 14.4 °C and an annual average precipitation of 1088 mm. The natural vegetations of the Yancheng Yellow Sea coast are listed from sea to inland: Spartina alterniflora, Suaeda salsa, Imperata cylindrica, and P. australis communities (Fig. 1) 32 . Over the last century, the wetlands of the Jiangsu coast have undergone intensive reclamation 11 . At present, most of coastal wetlands have been reclaimed and converted to aquaculture ponds, farmlands, and town construction lands, particularly in Dafeng and Sheyang counties (Fig. 1). Wheat (Triticum aestivum L.) and oilseed rape (Brassica campestris L.) fields are widely distributed along the middle Jiangsu coast. P. australis wetlands are the easiest to reclaim to other land use types due to their growing further inland, as they are farthest from the sea, relative to S. alterniflora, S. salsa, and I. cylindrica salt marshes (Fig. 1) 21 .
In June 2016, four sample transects of 40 m × 40 m were selected in each land use type, i.e., P. australis wetland (control), aquaculture pond, wheat field, oilseed rape field, and town construction land (Fig. 1), respectively, where there was a distance of 100 m between any two adjacent sample transects in each land use type. Satellite images (1975, 1991, 2000, 2006, 2010, and 2013 year) from the Landsat Thematic Mapper and historical records of the Yancheng Yellow Sea coast of Jiangsu Province were analyzed to identify the reclamation time of land use types and the types of natural salt marsh prior to coastal reclamation in the sampling region. The aquaculture ponds, wheat fields, and oilseed rape fields in the sample transects had been reclaimed for approximately 25 years, and were originally P. australis wetlands 21 . The aquaculture ponds in the sample transects were mainly used for raising silver carps. The wheat fields in the sample transects were used to plant winter wheats, and the oilseed rape fields in the sample transects were planted with winter oilseed rapes, and their yields or biomass had www.nature.com/scientificreports/ reached the maximum due to the sampling time is the ripe season for winter wheats and winter oilseed rapes. The town construction lands in the sample transects had been established for 6 years, which suffered continual coastal reclamation from P. australis wetlands in 1975, to aquaculture ponds in 1991, and were further converted to town construction lands in 2010 21 . The town construction lands in the sample transects were selected in the open spaces around the buildings of the urban construction, and the open spaces were the lands rather than cement or brick floors, and the open spaces were little vegetation cover due to intensive artificial disturbance. Due to the significant extent of P. australis wetlands being reclaimed to farmlands, aquaculture ponds, and town construction lands, only a small area of P. australis wetland remained in the sampling region (Fig. 1). For this study, we randomly selected three 2 m × 2 m plots in each transect, and three sites were selected for the collection of soil samples from each plot. Subsequently, soil samples from each plot were thoroughly mixed to yield a final soil sample. We randomly established three 0.5 m × 0.5 m quadrats to gather all aboveground plant materials and dug three soil blocks (0.15 m long × 0.15 m wide × 0.30 m deep) to gather all of the roots from each transect of the P. australis wetland, wheat field, and oilseed rape field.
Analysis of plant and edaphic properties. Each root-sampling block was put through a 0.15 mm sieve and repeatedly flushed with water; the roots remaining in the sieve were then collected 9 . The aboveground plant materials and roots were carefully cleaned and oven-dried at 65 °C to a constant weight to determine the plant biomass. The soil BD was determined using a cutting ring method. Fresh soil subsamples were oven-dried at 105 °C to a constant weight to measure the soil moisture 32 . Plant debris, soil fauna, and rocks in the soil samples were removed, which were then fully mixed and separated into three subsamples. The first subsample was airdried and sifted using 1 mm sieve to analyze the soil pH, salinity, SOC, and SON. The second subsample was sifted using a 2 mm sieve and stored at 4 °C to examine WSOC, MBC and MBN. The third subsample was sifted using a 2 mm sieve and stored at -80 °C after freeze-drying and was used to determine the PLFA. The soil pH was determined in a 1:2.5 soil to water suspension using a digital pH meter. The soil salinity was determined in a 1:5 soil to water suspension. The SOC and SON concentrations were quantified using a CN elemental analyzer (Vario Micro CHNS analyzer, Germany), where prior to determination, the soil samples were added to 1 M HCl to eliminate inorganic C and N. The determination of WSOC proceeded according to the technique described by Yang et al. 32 . The PLFA analysis was used to determine soil microbial biomass and community composition 58 . The PLFA was determined in accordance with the procedure previously described by Bossio and Scow 58 and Yang et al. 32 . Briefly, 8 g of a dry weight-equivalent of the soil subsamples was extracted in 23 mL of a chloroform: methanol: phosphate buffer mixture (1:2:0.8, v/v/v). The extraction was decanted into a separatory funnel and added to 12 mL of CHCl 3 and 12 mL of phosphate buffer following centrifugation. The separatory funnel was shaken for 2 min., and the extracts were layered overnight. The CHCl 3 layer was collected and dried under N 2 at 32 °C, whereas the lipids were re-dissolved in chloroform and fractionated on a 0.5-g silica gel solid-phase extraction column (Supelco, Bellefonte, PA). Neutral and glycol lipids were eluted by 5 mL of CHCl 3 and 10 mL of acetone. Polar lipids were collected via 5 mL of methanol, dried under N 2 at 32 °C, and then subjected to a mild-alkali methanolysis to recover the PLFA as methyl esters. The samples were re-dissolved in 200 mL of hexane solvent containing nonadecanoic acid methyl ester (19:0) as an internal standard. The samples were analyzed using a Hewlett-Packard 6890 Gas Chromatograph equipped with an Ultra 2-methylpolysiloxane column with N 2 as the carrier gas, and H 2 and air to support the flame. A 2-μL injection of the above dilution with a 1:50 split was employed at 250 °C for the injector and 300 °C for the detector. The oven temperature was ramped from 170 °C to 300 °C at 5 °C/min -1 and was maintained for 12 min.. The peaks were identified using bacterial fatty acid standards and MIDI peak identification software (Version 6.2, MIDI Inc., Newark, DE, US, URL link: http:// midi-inc. com/ index. html). The quantities (ng g -1 dry soil) of the PLFA in each sample were analyzed using an internal standard (19:0, 5 μg mL -1 ). The quantities of the PLFA in each sample were expressed as ng PLFA g -1 dry soil and were used to estimate the microbial biomass. The bacterial biomass was indicated by the biomarkers i14:0, i15:0, a15:0, 15:0, i16:0, i17:0, a17:0, 17:0, cy17:0, 14:1ω5c, 15:1ω6c, 16:1ω7c, and 18:1ω7c 44,56,58,59 . Indicators of gram + bacteria included i13:0, i14:0, i15:0, a15:0, i16:0, a16:0, i17:0, and grambacteria included 14:1ω5c, 15:1ω6c, 16:1ω7, 16:1ω9c, 17:1ω8c, 18:1ω7c, 12:0 2OH, 15:0 3OH, 16:1 2OH, cy17:0, cy19:0 ω8c, and 18:1ω7c 11-methyl 32,56,60 . The fungal biomass was quantified by the sum of the PLFA 18:1ω9c, 18:2ω6,9c, and 20:1ω9c 59,60 . The AMF biomass was assessed by the PLFA 16:1ω5c 9,56,60 . The 10me 16:0 and 10me 17:0 biomarkers were used as representatives of the Actinomycete biomass 54  www.nature.com/scientificreports/ the fungal PLFA, gram + bacterial PLFA, grambacterial PLFA, AMF PLFA, actinomycete PLFA, SSC PLFA, and 20:4ω6,9,12,15c. The F:B PLFA, gram + :gram -PLFA, and monounsaturated:branched PLFA ratios were calculated from the above PLFAs. Bacterial stress indexes, indicating the microbial physiological status under environmental stresses, were typically represented by cy17:0:16:1ω7c 9 .

Analyses of soil microbial biomass and community composition.
Statistical analyses. One-way analysis of variance (ANOVA) was employed to analyze the impacts of coastal reclamation on soil and plant characteristics, SOC, SON, microbial biomass, and various types of PLFA using SPSS statistical software (Version 24.0, URL link: https:// www. ibm. com/ produ cts/ spsss tatis tics? lnk= STW_ US_ STESCH_ P1_ BLK& lnk2= trial_ SPSSs tat& lot= 1& pexp= def& psrc= none& mhsrc= ibmse arch_a&mhq = spss). Pearson's correlation analysis was used to evaluate the relationship between the C and N fractions of the soil, and microbial biomass with soil physiochemical properties. Linear regression analysis was performed to determine the relationship between soil C and N, and the soil microbial biomass with plant biomass between the P. australis wetland, wheat field, and oilseed rape fields. The relationships between the soil microbial communities (all types of PLFA) and soil properties were conducted using RDA with CANOCO software (Version 4.5, URL link: http:// canoco. softw are. infor mer. com/4. 5/). The statistical significance of the RDA was tested using the Monte Carlo permutation test (499 permutations; P < 0.05). The map in the Fig. 1 was generated using the ArcGIS software (Version 9.3, URL link: http:// deskt op. arcgis. com/ zh-cn/ deskt op/).