Advertisement

Microbial Ecology

, Volume 76, Issue 1, pp 92–101 | Cite as

Influence of Macrofaunal Burrows on Extracellular Enzyme Activity and Microbial Abundance in Subtropical Mangrove Sediment

  • Ling Luo
  • Ji-Dong Gu
Soil Microbiology

Abstract

Bioturbation and bioirrigation induced by burrowing macrofauna are recognized as important processes in aquatic sediment since macrofaunal activities lead to the alteration of sediment characteristics. However, there is a lack of information on how macrofauna influence microbial abundance and extracellular enzyme activity in mangrove sediment. In this study, the environmental parameters, extracellular enzyme activities, and microbial abundance were determined and their relationships were explored. Sediment samples were taken from the surface (S) and lower layer (L) without burrow, as well as crab burrow wall (W) and bottom of crab burrow (B) located at the Mai Po Nature Reserve, Hong Kong. The results showed that the burrowing crabs could enhance the activities of oxidase and hydrolases. The highest activities of phenol oxidase and acid phosphatase were generally observed in B sediment, while the highest activity of N-acetyl-glucosaminidase was found in W sediment. The enzymatic stoichiometry indicated that the crab-affected sediment had similar microbial nitrogen (N) and phosphorous (P) availability relative to carbon (C), lower than S but higher than L sediment. Furthermore, it was found that the highest abundance of both bacteria and fungi was shown in S sediment, and B sediment presented the lowest abundance. Moreover, the concentrations of phosphorus and soluble phenolics in crab-affected sediment were almost higher than the non-affected sediment. The alterations of phenolics, C/P and N/P ratios as well as undetermined environmental factors by the activities of crabs might be the main reasons for the changes of enzyme activity and microbial abundance. Finally, due to the important role of phenol oxidase and hydrolases in sediment organic matter (SOM) decomposition, it is necessary to take macrofaunal activities into consideration when estimating the C budget in mangrove ecosystem in the future.

Keywords

Extracellular enzyme activity Microbial abundance Crab burrow Mangrove sediment 

Introduction

In aquatic ecosystems, benthic macrofauna in sediment have attracted more and more attention of scientists. It is recognized that the burrows, consisting of macrofauna, including crabs, shrimps, polychaetes, larvae and so on, have great implications for the microbiological and biogeochemical processes in sediment [1, 2, 3, 4, 5]. Recently, numerous macrofauna has been proposed as ecosystem engineers because they can reshape the structure of aquatic sediment by digging burrows [3, 6, 7]. Moreover, they also play a key role in alterations of chemical and biological properties of the sediment through a wide range of activities such as secreting mucus, excreting feces, feeding, and so on [1, 3, 8, 9].

To date, there is an increasing evidence that the reworking of macrofauna in aquatic sediments can stimulate the nutrient cycling and the decomposition of sediment organic matter (SOM), thereby enhancing microbial activity [10, 11, 12, 13]. However, a negative relationship between bacteria and macrofauna/meiofauna has also been reported due to the competition for food between them [14]. It is well known that extracellular enzyme activities are linkages between the microbial community dynamics and the ecosystem perspectives because they can catalyze SOM decomposition and the recycling of nutrients such as nitrogen (N) and phosphorus (P) [3, 15, 16].

Extracellular enzyme activities not only are affected by environmental conditions but also reflect the available resources for microbial communities [16]. For example, phenol oxidase (PHO), an “enzymic latch” of carbon (C) storage, is able to degrade recalcitrant phenolics like lignin [17, 18, 19]. β-Glucosidase (GLU), hydrolyzing cellulose and polymeric saccharides to glucose, is the most commonly measured indicator for C dynamics [20]. N-Acetyl-glucosaminidase (NAG) and acid phosphatase (ACP) often serve as indicators for N and P acquisitions, respectively [21, 22]. Furthermore, the ratios of selective enzyme activities (i.e. enzymatic stoichiometry) are applied to estimate the recalcitrance of SOM and microbial nutrient acquisition [22, 23].

Mangrove ecosystems, along most tropical and subtropical coastlines, are highly productive due to the litter fall, debris production, trapping water suspension, and so on [6, 24, 25, 26]. Mangroves grow in seawater between land and sea and support a number of microbial, meiofaunal and macrofaunal communities [6, 10, 25]. In recent years, the importance of mangrove ecosystems in food source and global carbon budget has been recognized increasingly [6, 24, 25]. Compared to freshwater and marine sediments, the macrobenthos of mangroves are relatively poorly known [4, 8, 27]. The existing research mainly focuses on the distribution and abundance of macrofauna [27] across mangroves, their physical disturbance on sediment processes through burrowing [6], and the influence of macrofauna on the properties and availability of organic carbon by the foraging and feeding activities [24]. However, the effect of macrofauna on microbial diversity and activity in mangrove sediment is scarcely studied relative to freshwater and marine sediments. In mangrove forests, the benthic macrofauna is usually dominated by burrowing crabs which can be largely seen. Generally, the crabs are herbivores and act as workers who can retain, bury, macerate, and ingest litter [6, 24, 25, 28]. Based on the important role of crabs in participating in litter decomposition, therefore, it is plausible to assume that the crabs could affect the extracellular enzyme activity and microbial abundance in burrow sediment.

In this study, it aimed to explore how fiddler crabs influence the biogeochemical and microbiological parameters of sediment in mangrove. The physicochemical properties of burrow sediment, including pH, water content, soluble phenolics, total C, total N, and total P, were measured. Subsequently, the microbial abundance (both bacterial and fungal) was determined by quantitative polymerase chain reaction (qPCR) analyses, and the measurement of enzymatic activities (including PHO, GLU, NAG, and ACP involved in C, N, and P cycling) was used to analyze the microbial activities. Finally, we also explored which environmental variables correlated best with the changes of enzymatic and microbial parameters.

Materials and Methods

Study Site and Sampling Procedure

In January 2014, samples were collected from the intertidal mangrove at Mai Po Nature Reverse of Hong Kong, China. The Mai Po Nature Reserve (lying between 22° 29′ N and 22° 31′ N and between 113° 59′ E and 114° 04′ E) locates on the edge of Deep Bay at the North West New Territories of Hong Kong. It is the largest stand of mangrove in Hong Kong, covering an area of 130 ha [25, 26, 29]. The most prominent crab is fiddler crab, Uca sp., and their burrows can be easily seen under the mangrove [25]. The burrows of Uca sp. extend from 10 to 20 cm into sediment and their shapes look like a “J,” similar with our determination and observation [6].

Sediment from the burrows was assigned to one of the four categories: Surface (S) sediment was collected from the top 0–1 cm of the sediment 5 cm away from any burrows; lower layer (L) sediment, usually defined as anoxic sediment, was taken at a depth of 5–6 cm under surface; wall (W) sediment was sampled from the wall of burrow at a thickness of 0–0.5 cm; and bottom (B) sediment was collected from the bottom of burrows at a depth of 15–20 cm [1, 3, 4]. The burrows (approximately 15 burrows) were randomly selected to take sediment across the mangrove forest until the amounts of each sample were enough to conduct the following tests. Sediment subsamples were pooled together to form a composite sample (each type of sample consisting of 15 subsamples due to the small amounts of sediment sampling from each burrow) [3]. After collection, samples were immediately transported on ice to the laboratory and stored at −20 °C for further analyses.

Sediment Properties

The pH was measured by using an IQ180G Bluetooth Multi-Parameter System (Hach Company, Loveland, CO, USA). The water content was determined with the oven drying method to a constant weight (approximately 105 °C for 48 h). The procedures of determining the concentration of soluble phenolics were according to the method of Toberman et al. [17] (details of determining soluble phenolics are shown in supplementary information). Furthermore, elemental analyzer (Eurovector EA3028, UK) was employed to determine the content of TC and TN, while TP was measured according to an analytical protocol developed by the Standards Measurements and Testing Program of the European Commission (SMT protocol) [26].

Enzyme Assays

In this study, four enzymes involved in C, N, and P cycling were investigated, including phenol oxidase (PHO), β-glucosidase (GLU), N-acetyl-glucosaminidase (NAG), and acid phosphatase (ACP). The substrate and buffer used for enzyme assays are listed in Table 1, and all enzymes were assayed spectrophotometrically, following the protocols described elsewhere [30] (details of protocols are shown in supplementary information). All enzyme activity values were calculated on the basis of oven dry (105 °C) weight of sediment and expressed as μmol product released g−1 dry sediment h−1. The GLU/PHO ratio was applied as the indicator for the recalcitrance of SOM [22]. In addition, the ratios of GLU/NAG and GLU/ACP were calculated to represent N and P acquisitions relative to C, respectively [23].
Table 1

Substrate and buffer used for enzyme assay in sediment of this study

Enzyme

EC

Abbreviation

Substrate

Buffer

Phenol oxidase

1.14.18.1

PHO

l-3,4-Dihydroxyphenylalanine (10 mM)

Acetate buffer (50 mM, pH 5.0)

β-Glucosidase

3.2.1.21

GLU

p-Nitrophenyl-β-d-glucoside (50 mM)

MUB, pH 6.0

N-Acetyl-β-glucosaminidase

3.2.1.14

NAG

p-Nitrophenyl-N-acetyl-β-d-glucopyranoside (10 mM)

Acetate buffer (100 mM, pH 5.5)

Acid phosphatase

3.1.3.2

ACP

p-Nitrophenyl phosphate (50 mM)

MUB, pH 6.5

EC enzyme commission classification; MUB modified universal buffer prepared by dissolving 12.1 g of Tris (hydroxymethyl)aminomethane (THAM), 11.6 g of maleic acid, 14.0 g of citric acid, and 6.3 g of boric acid (H3BO3) in about 800 mL of 0.5 M sodium hydroxide (NaOH), adjusted to 1 L with 0.5 M NaOH and stored at under 4 °C

Quantitative PCR Analyses

Whole community DNA was extracted from 0.25 g sediment using MoBio PowerSoil DNA Isolation Kit (Carlsbad, CA, USA) and stored at −20 °C. qPCR assays were used to assess the gene abundance of the microbial communities. To estimate the bacterial abundance, the PCR primers Eub338 and Eub518 were applied to target the 16S rRNA gene [31]. For the fungal abundance, the PCR primers ITS1-F and 5.8S were used [31]. Tenfold serial dilutions of the plasmid DNA ranged from 109 to 103 were subjected to qPCR assay in triplicate to generate external standard curves, and negative control was also applied. Each sample was also determined in triplicate (details of qPCR procedures showed in supplementary information). In addition, the ratio of fungal-to-bacterial abundance (F/B) was estimated to reflect the robust microbial community composition [32].

Statistic Analyses

Origin 8.0 was applied to analyze significance of enzyme activity and microbial abundance among surface, wall, lower layer, and bottom sediments by one-way analysis of variance (ANOVA). In order to test the interrelationships among microbial abundance, enzyme activity, and environmental variables, Canoco 4.5 and SPSS 21.0 were employed to perform redundancy analysis (RDA) and Pearson’s correlation analysis, respectively. Moreover, Tukey’s test was used to determine significant differences among samples. Statistical significance was accepted at p < 0.05.

Results

Sediment Properties

Characteristics of these samples are summarized in Table 2. Highest water content and pH value were recorded in the bottom sediment, while the lowest were found in wall and lower layer sediments. The concentration of soluble phenolics ranged from 12.45 (L) to 35.51 (B) mg/kg dry sediment. Surface sediment showed highest TC (2.88 %) and TN (0.27 %) but lowest TP (0.19 %). Meanwhile, the lowest TC (2.01 %) and TN (0.19 %) were recorded in L sediment, and B sediment showed the highest value of TP (0.246 %) which was close to W (0.243 %).
Table 2

Physicochemical properties of sediment in Mai Po Nature Reserve, Hong Kong

 

Water content (%)

pH

Phenolics (mg/kg)

TC (%)

TN (%)

TP (%)

Surface

53.71

6.21

15.82

2.88

0.27

0.190

Lower

53.92

4.88

12.45

2.01

0.19

0.197

Wall

53.50

6.05

15.18

2.27

0.21

0.243

Bottom

59.33

6.37

35.51

2.48

0.21

0.246

Enzymatic Activity

Enzymatic responses to bioturbation of crabs were highly variable among different samples (Fig. 1a). Among them, mean activity of PHO ranged from 2.25 to 9.29 μmol product g−1 dry sediment h−1, and no significant differences of PHO activity were found (p > 0.05), with the exception of bottom sediment which showed extremely higher activity of PHO (p < 0.05). For GLU activity, maximal value was recorded in surface sediment (3.48 μmol product g−1 dry sediment h−1), while the lowest activity was observed in lower layer sediment (0.52 μmol product g−1 dry sediment h−1). Moreover, notable differences of GLU activity were detected among all samples (p < 0.05) except that between wall and bottom sediments (p > 0.05). Interestingly, NAG activity, ranging from 0.62 to 1.38 μmol product g−1 dry sediment h−1, showed a similar trend with GLU activity, and the only exception was that there was no significant difference between surface and bottom sediments (p > 0.05). And surprisingly, the trend of ACP activity was inconsistent with GLU and NAG activities. The value of ACP activity, with a range between 9.86 and 12.45 μmol product g−1 dry sediment h−1, ranked in a descending order of bottom > wall > lower layer > surface sediments. Meanwhile, significantly higher activity of ACP (p < 0.05) was presented in crab-affected sediment (i.e., wall and bottom) than non-affected sediment (i.e., surface and lower layer).
Fig. 1

Mean (±SD) of a extracellular enzyme activity and b enzymatic ratio in surface, wall, ambient, and bottom sediments. Statistical significance at p < 0.05 is shown by different alphabets

The enzymatic ratios were calculated and are shown in Fig. 1b. It is obvious that enzymatic ratios varied widely among these samples. The ratio of GLU/PHO ranged from 0.23 (lower layer) to 1.25 (surface), and significant differences (p < 0.05) were found among samples, with the exception of that between lower layer and bottom (p > 0.05). By contrast, the changing pattern of GLU/NAG (ranging from 0.84 to 2.50) and GLU/ACP (from 0.05 to 0.35) was similar with the highest value in surface sediment and the lowest value in lower layer sediment of the no burrow sediment. Similarly, apparent differences were evident among surface, wall, and lower layer sediments (p < 0.05), but no significant difference between wall and bottom of the burrowing area (p > 0.05).

Microbial Abundance

The changes of microbial abundance were analyzed and are shown in Fig. 2a. The bacterial abundance ranged from 1.95 × 1010 to 8.85 × 1010 copies g−1 dry sediment, while the range of fungal abundance was from 8.58 × 108 to 5.73 × 109 copies g−1 dry sediment. It is evident that bacterial abundance in surface sediment was considerably higher (p < 0.05) than the other three samples, and no differences were found among wall, lower layer, and bottom sediments (p > 0.05). The trend of fungal abundance was quite different from bacterial abundance and decreased in the order of surface > wall > lower layer > bottom sediments. Concomitantly, fungal abundance differed strongly from each other (p < 0.05). In Fig. 2b, F/B ratio varied with each other, and statistical significance was observed. The maximal value (0.116) was recorded in the wall, while the minimal value (0.044) was recorded in the lower layer which was close to the bottom sediment. In addition, the ratio in lower layer and bottom sediments were statistically different from that in surface and wall sediments (p < 0.05). Also, the F/B ratio in surface and wall sediments were evidently different (p < 0.05).
Fig. 2

Mean (±SD) of a microbial abundance and b fungi-to-bacteria (F/B) ratio in surface, wall, ambient, and bottom sediments. Statistical significance at p < 0.05 is shown by different alphabets

Interrelationships Among Sediment Properties, Enzymatic Activity and Microbial Abundance

The RDA and Pearson’s correlation analysis were adopted to explore the correlations relating environmental variables to enzyme activity and microbial abundance (Fig. 3; Tables 3 and 4). In Fig. 3a, NAG and GLU activities were closely related to TC, indicating a positive relationship, and the Pearson’s correlation coefficients (Table 3) supported that this positive relationship was statistically significant (p < 0.05). By contrast, PHO and ACP activities appeared to be more closely related to water content, phenolics, and C/N, and observably, positive relationships (p < 0.05) between these two-enzyme activity and the abovementioned environmental factors are observed in Table 2. Furthermore, fungal and bacterial abundances were approached to N/P and C/P, but only bacterial abundance showed markedly positive relationship with C/P and N/P (p < 0.05).
Fig. 3

Redundancy analyses a relating environmental factors to microbial abundance and enzyme activity, b relating environmental parameters to the ratios of enzyme activity and fungi-to-bacteria (F/B), and c correlating microbial parameters with enzymatic parameters

Table 3

Pearson’s correlation coefficients (r) relating environmental variables to microbial abundance as well as enzyme activity

 

Water content

pH

Phenolics

TC

TN

TP

C/N

C/P

N/P

PHO

0.994**

0.529

0.997**

0.190

−0.130

0.600

0.988*

−0.228

−0.380

GLU

0.150

0.801

0.310

0.963*

0.880

0.047

0.249

0.671

0.584

NAG

0.133

0.816

0.297

0.952*

0.872

0.072

0.241

0.650

0.565

ACP

0.958*

0.561

0.967*

0.027

−0.294

0.781

0.990**

−0.443

−0.582

Bacteria

−0.410

0.117

−0.339

0.786

0.926

−0.733

−0.441

0.988*

0.997**

Fungi

−0.643

0.244

−0.515

0.683

0.864

−0.469

−0.565

0.779

0.822

GLU/PHO

−0.550

0.463

−0.400

0.732

0.874

−0.321

−0.443

0.731

0.756

GLU/NAG

0.243

0.960*

0.411

0.894

0.771

0.246

0.371

0.508

0.411

GLU/ACP

−0.052

0.786

0.107

0.966*

0.950*

−0.120

0.041

0.772

0.713

F/B

−0.518

0.296

−0.386

0.027

0.129

0.350

−0.313

−0.149

−0.087

Pearson’s correlation coefficient (r) is given by \( r=\frac{\sum_i\left(\;{x}_i-\overline{x}\left)\right({y}_i-\overline{y}\right)}{\sqrt{\sum_i\left({x}_i-\overline{x}\right)\sqrt{{\left({y}_i-\overline{y}\right)}^2}}} \)

*p < 0.05; **p < 0.01

Table 4

Pearson’s correlation coefficient (r) relating microbial parameters to enzymatic parameters

 

PHO

GLU

NAG

ACP

GLU/PHO

GLU/NAG

GLU/ACP

Bacteria

−0.366

0.638

0.622

−0.559

0.800

0.475

0.763

Fungi

−0.569

0.656

0.664

−0.643

0.986*

0.554

0.797

F/B

−0.447

0.227

0.270

−0.267

0.565

0.309

0.283

Pearson’s correlation coefficient (r) is given by \( r=\frac{\sum_i\left(\;{x}_i-\overline{x}\left)\right({y}_i-\overline{y}\right)}{\sqrt{\sum_i\left({x}_i-\overline{x}\right)\sqrt{{\left({y}_i-\overline{y}\right)}^2}}} \)

*p < 0.05

The analyses relating environmental variables to enzymatic ratios and F/B ratios (Fig. 3b; Table 3) indicated that GLU/NAG was notably related to pH (p < 0.05), while GLU/ACP comparatively correlated with TC and TN (p < 0.05). Nevertheless, there was a statistically non-significant relationship between GLU/PHO and environmental conditions (p > 0.05) and so was the correlation between F/B and environmental variables (p > 0.05). The relationships between enzymatic and microbial parameters were also investigated with RDA and Pearson’s analysis (Fig. 3c; Table 4). A positive relationship was only observed between fungal abundance and GLU/PHO (p < 0.05), which emphasized the role of fungi in the decomposition of recalcitrant organic matter.

Discussion

By far the most attention has focused on the microbial activities in burrow walls compared with surrounding sediment, such as the rate of nitrification and denitrification [11], the distribution and diversity of ammonia-oxidizing microorganisms [33], the alteration of bacterial community structure [3, 4], etc. However, there are no reports exploring the influence of macrofauna on the activities of extracellular enzymes which are responsible for the decomposition of organic matter and the cycling of nutrients. It is widely acknowledged that the measures of extracellular enzyme activities and ratios of commonly measured enzyme potentials can be used as indicators of microbial nutrient demand [15, 23, 34]. Likewise, enzyme ratios can correlate the functional organization of microdecomposer communities to environmental conditions since extracellular enzyme activity not only is affected by environmental variables but also feeds back on microbial community composition [16]. Therefore, the information provided by extracellular enzyme activities could help in understanding the influence of crabs on the growth of microorganisms and the turnover of SOM.

In the current study, we have explored how fiddler crabs affect the microbiological and biogeochemical parameters of sediment in a subtropical mangrove ecosystem. Due to 5 cm far away from any openings of the burrows, surface and lower layer sediments were assumed as non-affected sediment, while wall and bottom sediments of burrows were considered as crab-affected ones. Our results showed that the characteristics of sediment were indeed altered by burrowing of fiddler crabs since the different characteristics of non-affected and crab-affected sediment were observed (Table 2). Interestingly, soluble phenolics and TP content, rather than TC and TN, were more affected by the burrows of fiddler crabs, which were largely neglected in previous studies.

The variations of C and N contents in burrow walls in relation to surface or lower layer sediment have attracted much research interest [1, 10, 11, 28, 33]. For instance, macrofauna (e.g., crab and earthworm) have been found to enhance TC and TN contents of burrow walls in comparison to surrounding sediment, and also lower content of TC and TN in burrow walls relative to surface sediment were reported [5, 12, 35]. Nevertheless, there is little information referred to P content of burrow walls in comparison to surface or surrounding sediment. Commonly, P has been accepted as the limiting factor in aquatic environments and is not readily replenished as P is derived primarily from weathering of rock and ecosystems that have a relative constant supply and utilization of P [12, 36, 37]. As observed in Table 2, TP contents in wall and bottom sediments, equal to each other, were higher than that of surface and lower layer sediments, which are in agreement with previous findings [12, 13]. In general, the main reason for the increase of P in burrow wall sediment might be the oxidation of Fe2+ into Fe3+ and the precipitation of P into Fe(OOH)-PO4 after the formation of Fe(OOH) [7, 12, 13]. On the other hand, the increase of P might be partially explained by the organic-rich secretions of crabs, such as fecal pellets, mucus linings, and so on [12, 38]. The feces and linings are usually rich in sulfate and phosphate [1, 24]. Therefore, it is plausible that the activities of burrowing crabs could directly impact the nutrient cycling in mangrove sediment, thereby accordingly changing the microbial activity including enzymatic activity and microbial abundance.

This study showed the considerably higher concentration of soluble phenolics in bottom sediment than the other three samples (Table 2). However, until now, no related studies have estimated or compared the concentration of soluble phenolics in surface, wall, lower layer, and bottom sediments. By comparing these four samples together, only bottom sediment had higher water content, which was consistent with the findings that crab burrowing increased soil water content [10]. Also, a markedly positive relationship between water content and soluble phenolics was observed in the current study (p < 0.05) (Table S1), which was in agreement with our previous finding that lower water content might reduce the leaching of phenolics from litter and plant materials [26]. Hence, the retention of tidewater in bottom sediment might explain the higher soluble phenolics. Moreover, it is well known that mangrove crabs play an essential role in the removal of leaf litter due to the foraging and feeding activity of crabs, thereby affecting the availability of leaf litter on the forest floor and its subsequent export. Beyond that, many crabs typically take the leaves down in their burrow for storage, where they continue to decompose [10, 24, 27, 39]. Considering both the higher concentrations of phenolics in leaf litter and the leaching of phenolics through the decomposition of leaf litter inside the burrows of crabs, it is reasonable that bottom sediment showed higher concentration of soluble phenolics [40].

Soluble phenolics have been proposed as inhibitors of hydrolase activities and thus contributing to the low rates of organic matter decomposition in several ecosystems (e.g., peatland soils) [41]. Unfortunately, it seems that there was non-significant relationship between soluble phenolics and hydrolase activities in the current study. Instead, markedly positive relationships between soluble phenolics and PHO as well as ACP activity were revealed (p < 0.05), and also between water content and these two enzyme activities (Table 3). At the same time, PHO activity was found to be positively associated with ACP activity (p < 0.05) (Table S2).

Based on the abovementioned mechanisms of the highest TP and soluble phenolics in bottom sediment, two possible reasons might be proposed to explain these evidently positive correlations among PHO, ACP, water content, and soluble phenolics. One is because crab activities could alter the oxidation reaction (such as oxidation of Fe2+) through transporting oxygen, solutes, or other oxidants from surface to burrow sediment [12, 13]. Due to the precipitation of P as Fe(OOH)PO4, microorganisms in wall and bottom sediments might acquire soluble reactive P, thus increasing the activity of ACP. On the other hand, the secretion of crabs probably contains high recalcitrant organic matter (e.g., phenolics) or is rich in P substrates, thereby accordingly inducing higher activity of PHO or ACP in bottom sediment [12, 38, 40, 42, 43]. Moreover, PHO has been considered as an independent reagent that catalyzes the oxidation of Fe2+, which presumably deciphered the remarkable interrelationship between PHO and ACP activities. Finally, the variations of sediment C/N were closely related with water content and soluble phenolics (Table S1); therefore, to some extent, this might account for the higher PHO and ACP activities in crab-affected sediment (especially bottom sediment).

GLU and NAG activities responded similarly to environmental variables and significantly correlated with TC (Table 2). Several studies have shown the correlations relating soil C to GLU and NAG, indicating the role of these enzymes in the conversion of total organic matter stock [42, 43]. Furthermore, we found that GLU was also remarkably related to NAG (Table S2), which is in accordance with the findings of Šnajdr et al. [44] and our previous study [26]. This result implies that the production of GLU often accompanies with NAG due to the maintenance of C/N ratio by microorganisms. Hence, the fluctuations of GLU and NAG occurred in concert and showed the same or similar trends along with the changes of environmental conditions. The same variations of ACP with GLU and NAG activities were observed according to both the nutrients needed by microorganisms and the nutritional condition of ecosystems [22, 26]. However, this is not the case in the current study due to the enhanced TP in burrow sediment through the activities of crabs.

In addition to investigating enzyme activity, the ratios of enzyme activity were calculated to estimate the relative recalcitrance of sediment (i.e., GLU/PHO) and the acquisition of N and P (GLU/NAG and GLU/ACP, respectively) in our study. With comparison to global mean GLU/PHO ratio of sediment (0.202), all of the four samples were greater (Fig. 1a), indicating that these sediment are more labile, especially surface sediment with a value of 1.25 [22]. In contrast, it is evident that the GLU/PHO ratio of wall sediment was higher than its surrounding sediment (lower layer). This implies that the lability of SOM was altered due to the mucoid secretions by crabs, which might be easily degradable [22, 45]. Furthermore, the analyses relating the ratio of GLU/PHO to environmental variables and microbial parameters showed no remarkable correlations in this research, except with fungi (Fig. 3b, c; Tables 2 and 3). This being said, fungi appear to play an important role in the labiality of mangrove SOM. And, coincidently, a strongly positive relationship between GLU/PHO ratio and fungal abundance was also found when the influence of mangrove roots on enzyme activity as well as microbial abundance in the same ecosystems (unpublished data) was studied. Collectively, therefore, the role of fungi in the labiality of SOM is substantially important and is manifested as the greater labiality along with higher fungal abundance increases rates of decomposition and microbial growth [22].

The ratios of GLU/NAG in surface, wall, and bottom sediments are approaching the global average of 2.08, except for lower layer sediment with a lower value of 0.84. Thus, it implies that microorganisms in the lower layer sediment might acquire more N for growth and cell maintenance compared to the other three compartments and also suggests that the activities of crabs might modify the N acquisition of sediment. Meanwhile, the alteration of GLU/ACP ratio indicates the similar trend with that of GLU/NAG but strikingly lower values than the mean of 1.64 in stream sediments [22], suggesting that all sediment are P limited. However, relatively speaking, the P availability of wall and bottom is observably higher than lower layer sediment, despite drastically lower than the surface sediment. Therefore, the enhanced P availability by crabs has been manifested and might stimulate the growth of microorganisms. Collectively, the enhanced N and P availabilities in wall and bottom sediments could result in a significantly increase of microbial growth [10].

Unexpectedly, in our study, a decreased bacterial abundance in burrow-affected sediment (wall and bottom sediments) relative to non-affected sediment (surface and lower layer sediments) was observed. It is inconsistent with previous findings that the abundance of microorganisms or at least certain functional groups in burrow-affected sediment was elevated relative to that of non-affected sediment, since burrow walls or linings, which have characteristics including alteration of oxic-anoxic conditions, organic/nutrient content, and sediment structures, could provide an attractive and beneficial environment for microorganisms living [1, 3, 8, 12]. Nevertheless, there are still several literatures reporting no enhancement or reduction of bacterial abundance in burrow walls. And according to several published literatures, it can be assumed that the possible reason for the lack of strong bacterial enrichment in the burrow wall might result from the extensive meiofaunal grazing along the burrow walls as well as the direct ingestion by macrofauna [1, 8, 9, 46]. Simultaneously, the results of analyses relating bacterial abundance to environmental conditions suggested that bacterial abundance closely correlated with C/P and N/P but not the content of TC, TN, and TP. This implies that what the bacteria require is not only the concentration of nutrient but also the equilibrium of sediment C/N/P ratio due to the different C/N/P ratios of specific microbial taxa [47].

By contrast to bacterial abundance, our results showed that fungal abundance was not strongly related to any environmental factors, suggesting that the variations in fungal community structure are probably caused by yet unknown environmental drivers and or by stochastic events in sediment habitats [48]. In reality, the robust alteration of microbial community composition (i.e., F/B ratio) was made up by the activities of crabs (Fig. 2b). The ongoing studies have established that macrofauna could alter the structure and diversity of microbial communities in coastal marine sediment or freshwater sediment [4, 8], which was in agreement with our findings, since the activities of macrofauna lead to the alterations in the microbial transformation of important nutrients at the sediment-water interface. Besides the abovementioned observations, no dominant environment factors showed any prominently relationships with the F/B ratio. After considering both the changes of microbial abundance and the possible reason for their variations, the grazing of bacteria by larger organisms might be attributed to the weak relationships of F/B ratio with environmental parameters [9]. Alternatively, the reason is similar to fungal abundance that the variations of F/B ratio are induced by yet unknown environmental drivers [48].

Results show that the burrowing crabs can change the nutrient cycling and quality of SOM, as revealed by the shifts of sediment elemental composition and extracellular enzyme activity in crab-affected sediment (wall and bottom) in comparison to non-affected sediment (i.e., surface and lower layer). Furthermore, this study shows that different extracellular enzyme activity was strongly related to different measured environmental factors, indicating that the changes of extracellular enzyme activity might be corresponded to the shifts of certain relevant environmental parameters. Although the meiofaunal grazing and macrofaunal ingestion presumably caused the underestimated microbial abundance, the alteration of microbial abundance and robust microbial community composition indeed emphasized the role of crabs in microbial growth and thus the biogeochemical cycling of mangrove sediment.

Until now, very little data exist with which to explore the extracellular enzyme activity and microbial abundance in crabs’ burrow sediment in mangrove ecosystems. The findings present here are novel but preliminary, and thus it requires further investigation over longer time periods to get more information. Additionally, it is worthy to conduct relative research that integrates the shift of functional groups (both diversity and abundance) with the nutrient cycling and degradation of burrow SOM. Hopefully, it is expected to provide valuable information for understanding C stock and estimating the contribution of macrofauna on climate changes in mangrove ecosystems.

Notes

Acknowledgments

This research project was supported by a Ph.D. studentship from Graduate School, The University of Hong Kong (LL) and financial support of Environmental Toxicology Education and Research Fund of this laboratory.

Supplementary material

248_2016_844_MOESM1_ESM.docx (96 kb)
ESM 1 (DOCX 95 kb)

References

  1. 1.
    Kristensen E, Kostka J (2005) Macrofaunal burrows and irrigation in marine sediment: microbiological and biogeochemical interactions. Interactions between macro-and microorganisms in marine sediment:125–157Google Scholar
  2. 2.
    Stief P (2007) Enhanced exoenzyme activities in sediment in the presence of deposit-feeding Chironomus riparius larvae. Freshw Biol 52(9):1807–1819CrossRefGoogle Scholar
  3. 3.
    Pischedda L, Militon C, Gilbert F, Cuny P (2011) Characterization of specificity of bacterial community structure within the burrow environment of the marine polychaete Hediste (Nereis) diversicolor. Res Microbiol 162(10):1033–1042CrossRefPubMedGoogle Scholar
  4. 4.
    Laverock B, Smith CJ, Tait K, Osborn AM, Widdicombe S, Gilbert JA (2010) Bioturbating shrimp alter the structure and diversity of bacterial communities in coastal marine sediment. ISME J 4(12):1531–1544CrossRefPubMedGoogle Scholar
  5. 5.
    Gutiérrez JL, Jones CG, Groffman PM, Findlay SE, Iribarne OO, Ribeiro PD, Bruschetti CM (2006) The contribution of crab burrow excavation to carbon availability in surficial salt-marsh sediment. Ecosystems 9(4):647–658CrossRefGoogle Scholar
  6. 6.
    Kristensen E (2008) Mangrove crabs as ecosystem engineers; with emphasis on sediment processes. J Sea Res 59(1):30–43CrossRefGoogle Scholar
  7. 7.
    Chapuis-Lardy L, Le Bayon R-C, Brossard M, López-Hernández D, Blanchart E (2011) Role of soil macrofauna in phosphorus cycling. In: Phosphorus in action. Springer, pp 199–213Google Scholar
  8. 8.
    Wieltschnig C, Fischer UR, Velimirov B, Kirschner AK (2008) Effects of deposit-feeding macrofauna on benthic bacteria, viruses, and protozoa in a silty freshwater sediment. Microb Ecol 56(1):1–12CrossRefPubMedGoogle Scholar
  9. 9.
    Witte U, Wenzhöfer F, Sommer S, Boetius A, Heinz P, Aberle N, Sand M, Cremer A, Abraham W-R, Jørgensen B (2003) In situ experimental evidence of the fate of a phytodetritus pulse at the abyssal sea floor. Nature 424(6950):763–766CrossRefPubMedGoogle Scholar
  10. 10.
    Wang JQ, Zhang XD, Jiang LF, Bertness MD, Fang CM, Chen JK, Hara T, Li B (2010) Bioturbation of burrowing crabs promotes sediment turnover and carbon and nitrogen movements in an estuarine salt marsh. Ecosystems 13(4):586–599CrossRefGoogle Scholar
  11. 11.
    Stief P (2013) Stimulation of microbial nitrogen cycling in aquatic ecosystems by benthic macrofauna: mechanisms and environmental implications. Biogeosciences 10(12):7829–7846CrossRefGoogle Scholar
  12. 12.
    Roskosch A (2011) The influence of macrozoobenthos in lake sediment on hydrodynamic transport processes and biogeochemical impacts. Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät IIGoogle Scholar
  13. 13.
    Heilskov AC, Holmer M (2001) Effects of benthic fauna on organic matter mineralization in fish-farm sediment: importance of size and abundance. ICES J Mar Sci 58(2):427–434CrossRefGoogle Scholar
  14. 14.
    Papageorgiou N, Moreno M, Marin V, Baiardo S, Arvanitidis C, Fabiano M, Eleftheriou A (2007) Interrelationships of bacteria, meiofauna and macrofauna in a Mediterranean sedimentary beach (Maremma Park, NW Italy). Helgol Mar Res 61(1):31–42CrossRefGoogle Scholar
  15. 15.
    Crowther TW, Jones TH, Boddy L, Baldrian P (2011) Invertebrate grazing determines enzyme production by basidiomycete fungi. Soil Biol Biochem 43(10):2060–2068CrossRefGoogle Scholar
  16. 16.
    Sinsabaugh R, Carreiro M, Repert D (2002) Allocation of extracellular enzymatic activity in relation to litter composition, N deposition, and mass loss. Biogeochemistry 60(1):1–24CrossRefGoogle Scholar
  17. 17.
    Toberman H, Evans CD, Freeman C, Fenner N, White M, Emmett BA, Artz RR (2008) Summer drought effects upon soil and litter extracellular phenol oxidase activity and soluble carbon release in an upland Calluna heathland. Soil Biol Biochem 40(6):1519–1532CrossRefGoogle Scholar
  18. 18.
    Fenner N, Freeman C, Reynolds B (2005) Observations of a seasonally shifting thermal optimum in peatland carbon-cycling processes; implications for the global carbon cycle and soil enzyme methodologies. Soil Biol Biochem 37(10):1814–1821CrossRefGoogle Scholar
  19. 19.
    Freeman C, Ostle N, Kang H (2001) An enzymic‘latch’on a global carbon store. Nature 409(6817):149–149CrossRefPubMedGoogle Scholar
  20. 20.
    Moscatelli M, Lagomarsino A, Garzillo A, Pignataro A, Grego S (2012) β-Glucosidase kinetic parameters as indicators of soil quality under conventional and organic cropping systems applying two analytical approaches. Ecol Indic 13(1):322–327CrossRefGoogle Scholar
  21. 21.
    Moorhead DL, Lashermes G, Sinsabaugh RL (2012) A theoretical model of C- and N-acquiring exoenzyme activities, which balances microbial demands during decomposition. Soil Biol Biochem 53:133–141CrossRefGoogle Scholar
  22. 22.
    Sinsabaugh RL, Shah JJF, Hill BH, Elonen CM (2012) Ecoenzymatic stoichiometry of stream sediment with comparison to terrestrial soils. Biogeochemistry 111(1–3):455–467CrossRefGoogle Scholar
  23. 23.
    Waring BG, Weintraub SR, Sinsabaugh RL (2014) Ecoenzymatic stoichiometry of microbial nutrient acquisition in tropical soils. Biogeochemistry 117(1):101–113CrossRefGoogle Scholar
  24. 24.
    Kristensen E, Bouillon S, Dittmar T, Marchand C (2008) Organic carbon dynamics in mangrove ecosystems: a review. Aquat Bot 89(2):201–219CrossRefGoogle Scholar
  25. 25.
    Qin P, Wong Y, Tam N (2000) Emergy evaluation of Mai Po mangrove marshes. Ecol Eng 16(2):271–280CrossRefGoogle Scholar
  26. 26.
    Luo L, Gu J-D (2015) Seasonal variability of extracellular enzymes involved in carbon mineralization in sediment of a subtropical mangrove wetland. Geomicrobiol J 32(1):68–76CrossRefGoogle Scholar
  27. 27.
    Lee SY (2008) Mangrove macrobenthos: assemblages, services, and linkages. J Sea Res 59(1):16–29CrossRefGoogle Scholar
  28. 28.
    Ashton EC (2002) Mangrove sesarmid crab feeding experiments in Peninsular Malaysia. J Exp Mar Biol Ecol 273(1):97–119CrossRefGoogle Scholar
  29. 29.
    Cao H, Li M, Hong Y, Gu J-D (2011) Diversity and abundance of ammonia-oxidizing archaea and bacteria in polluted mangrove sediment. Syst Appl Microbiol 34(7):513–523CrossRefPubMedGoogle Scholar
  30. 30.
    Dick RP (2011) Methods of soil enzymology. In: Soil Science Society of America MadisonGoogle Scholar
  31. 31.
    Rousk J, Bååth E, Brookes PC, Lauber CL, Lozupone C, Caporaso JG, Knight R, Fierer N (2010) Soil bacterial and fungal communities across a pH gradient in an arable soil. ISME J 4(10):1340–1351CrossRefPubMedGoogle Scholar
  32. 32.
    De Vries FT, Hoffland E, van Eekeren N, Brussaard L, Bloem J (2006) Fungal/bacterial ratios in grasslands with contrasting nitrogen management. Soil Biol Biochem 38(8):2092–2103CrossRefGoogle Scholar
  33. 33.
    Laverock B, Kitidis V, Tait K, Gilbert J, Osborn A, Widdicombe S (2013) Bioturbation determines the response of benthic ammonia-oxidizing microorganisms to ocean acidification. Philos Trans R Soc Lond 368(1627):20120441CrossRefGoogle Scholar
  34. 34.
    Sinsabaugh RL, Lauber CL, Weintraub MN, Ahmed B, Allison SD, Crenshaw C, Contosta AR, Cusack D, Frey S, Gallo ME (2008) Stoichiometry of soil enzyme activity at global scale. Ecol Lett 11(11):1252–1264CrossRefPubMedGoogle Scholar
  35. 35.
    Jégou D, Schrader S, Diestel H, Cluzeau D (2001) Morphological, physical and biochemical characteristics of burrow walls formed by earthworms. Appl Soil Ecol 17(2):165–174CrossRefGoogle Scholar
  36. 36.
    Sardans J, Rivas-Ubach A, Penuelas J (2012) The elemental stoichiometry of aquatic and terrestrial ecosystems and its relationships with organismic lifestyle and ecosystem structure and function: a review and perspectives. Biogeochemistry 111(1–3):1–39CrossRefGoogle Scholar
  37. 37.
    Hill BH, Elonen CM, Jicha TM, Kolka RK, Lehto LL, Sebestyen SD, Seifert-Monson LR (2014) Ecoenzymatic stoichiometry and microbial processing of organic matter in northern bogs and fens reveals a common P-limitation between peatland types. Biogeochemistry 120(1–3):203–224CrossRefGoogle Scholar
  38. 38.
    Gerbersdorf SU, Jancke T, Westrich B, Paterson DM (2008) Microbial stabilization of riverine sediment by extracellular polymeric substances. Geobiology 6(1):57–69PubMedGoogle Scholar
  39. 39.
    Thongtham N, Kristensen E, Puangprasan S-Y (2008) Leaf removal by sesarmid crabs in Bangrong mangrove forest, Phuket, Thailand; with emphasis on the feeding ecology of Neoepisesarma versicolor. Estuar Coast Shelf Sci 80(4):573–580CrossRefGoogle Scholar
  40. 40.
    Micheli F (1993) Feeding ecology of mangrove crabs in North Eastern Australia: mangrove litter consumption by Sesarma messa and Sesarma smithii. J Exp Mar Biol Ecol 171(2):165–186CrossRefGoogle Scholar
  41. 41.
    Freeman C, Ostle N, Fenner N, Kang H (2004) A regulatory role for phenol oxidase during decomposition in peatlands. Soil Biol Biochem 36(10):1663–1667CrossRefGoogle Scholar
  42. 42.
    Qin S, Hu C, He X, Dong W, Cui J, Wang Y (2010) Soil organic carbon, nutrients and relevant enzyme activities in particle-size fractions under conservational versus traditional agricultural management. Appl Soil Ecol 45(3):152–159CrossRefGoogle Scholar
  43. 43.
    Salazar S, Sánchez L, Alvarez J, Valverde A, Galindo P, Igual J, Peix A, Santa-Regina I (2011) Correlation among soil enzyme activities under different forest system management practices. Ecol Eng 37(8):1123–1131CrossRefGoogle Scholar
  44. 44.
    Šnajdr J, Valášková V, Merhautová V, Herinková J, Cajthaml T, Baldrian P (2008) Spatial variability of enzyme activities and microbial biomass in the upper layers of Quercus petraea forest soil. Soil Biol Biochem 40(9):2068–2075CrossRefGoogle Scholar
  45. 45.
    Papaspyrou S, Gregersen T, Kristensen E, Christensen B, Cox RP (2006) Microbial reaction rates and bacterial communities in sediment surrounding burrows of two nereidid polychaetes (Nereis diversicolor and N. virens). Mar Biol 148(3):541–550CrossRefGoogle Scholar
  46. 46.
    Reichardt W (1988) Impact of bioturbation by Arenicola marina on microbiological parameters in intertidal sediment. Mar Ecol Prog Ser Oldendorf 44(2):149–158CrossRefGoogle Scholar
  47. 47.
    Allison SD, Weintraub MN, Gartner TB, Waldrop MP (2011) Evolutionary-economic principles as regulators of soil enzyme production and ecosystem function. In: Soil enzymology. Springer, pp 229–243Google Scholar
  48. 48.
    Böer SI, Hedtkamp SI, Van Beusekom JE, Fuhrman JA, Boetius A, Ramette A (2009) Time-and sediment depth-related variations in bacterial diversity and community structure in subtidal sands. ISME J 3(7):780–791CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.College of Environmental SciencesSichuan Agricultural UniversityChengduPeople’s Republic of China
  2. 2.School of Biological SciencesThe University of Hong KongHong KongPeople’s Republic of China

Personalised recommendations