Fatima Zohra Benhamida

Yacine Challal
email: ychallal@hds.utc.fr

Mouloud Koudil
email: m_koudil@esi.dz

Efficient Adaptive Failure Detection for Query/Response based Wireless Sensor Networks

Keywords: failure management, wireless sensor networks, lossy links, process crash. I

we consider the problem of failure management in wireless sensor networks (WSN). In such networks, nodes can be subject to frequent failures due to energy depletion and the hostile deployment environment. Our work focuses on local crash process detection in WSN considering intermittent failures due to lossy radio links. As a part of this problem, we introduce a new type of Adaptive Neighborhood Failure Detection mechanism (ANFD) that relies on adaptive timers. Then we analyze properties of the introduced failure detection algorithm and determine how and when timers' update is necessary. We carried out intensive simulations using TinyOS-2 and evaluated the performance of our solution. Simulation results show that our solution improves failure detection rate and delay, and reduces fault positive detections and packet loss ratio. Moreover, we analyzed energy consumption using PowerTossimZ and results demonstrate that our solution does not induce extra energy consumption compared to other solutions in the literature.

INTRODUCTION

Wireless sensor networks (WSN) are prone to a variety of failures due to energy limitations, radio transmissions and close coupling with environment where network components may be not physically protected. Therefore, fault management is one of the critical issues in WSN. It requires new communication protocol considering the ability to cope with node failures. However, the design of these new approaches must respond to the following WSN constraints and properties: (1) a node does not necessarily know all the nodes of the network due to storage capacity limitations (2) the network is not fully connected because of radio range limitation, which means that a message sent by a node might be routed through a set of intermediate nodes until reaching the destination; (3) communication is data-centric: in most WSN applications, data is requested by a collector by sending a query based on certain attributes. Then, source nodes respond with packets containing required information. This Query/Response mechanism (denoted here by Q/R) is periodically invoked during the lifespan of the network; [START_REF] Boukerche | A fast and reliable protocol for wireless sensor networks in critical conditions monitoring applications[END_REF] links are prone to failures and may momentarily drop messages during transmission; [START_REF] Chandra | Unreliable failure detectors for reliable distributed systems[END_REF] nodes are equipped with limited energy batteries: communication protocols have to consider this limitation to maintain the network alive as long as possible.

Failure detection has been deeply investigated in the literature of distributed systems [START_REF] Chandra | Unreliable failure detectors for reliable distributed systems[END_REF]. However, the proposed failure detectors do not meet WSN constraints and requirements and rely on assumptions hardly verified in WSN. Indeed, most of proposed failure detection classes are based on an all-to-all communication approach where each process periodically sends a heartbeat message to all processes [START_REF] Devianov | Failure detector service for dependable computing[END_REF] [START_REF] Heinzelman | Energyefficient communication protocol for wireless microsensor networks[END_REF] [START_REF] Larrea | Optimal implementation of the weakest failure detector for solving consensus[END_REF]. As they usually consider a fully connected set of known nodes, these implementations are not adequate for dynamic and partially connected environments, such as WSN. Furthermore, failure detectors are usually based on packet acknowledgment [START_REF] Elliott | estimates of error rates for codes on burst-noise channels[END_REF] where the receiver sends back an acknowledgment to the source after every packet reception. Otherwise, the sender suspects the receiver of having crashed. Both heartbeat and acknowledgment mechanisms are not suitable for WSN where processes are limited in energy and communication bandwidth. In [START_REF] Levis | Tossim: "accurate and scalable simulation of entire tinyos applications[END_REF], a timer-free asynchronous failure detector has been proposed. It is based on an exchange of messages and assumes the knowledge of two values: f (the maximum number of processes that can crash) and n (the number of nodes in the system). Moreover, the computation model consists of a set of initially fully connected known nodes. Yet, this timer-free approach is not applicable to a partially-connected network such as WSN. Some works have been proposed which deal with the scalable nature of dynamic systems. Nonetheless, few of them tolerate links failures [START_REF] Aguilera | Heartbeat: A Timeout-Free Failure Detector for Quiescent Reliable Communication[END_REF] [START_REF] Gupta | On scalable and efficient distributed failure detectors[END_REF]. In most of works, they only considered systems where process crashes are permanent and links are reliable (i.e., they do not lose messages). This may increase the risk of mistakes, when the failure detector suspects a process of having crashed while the packets were lost because of intermittent transmission failure due to unreliable links.

In this paper, we define a new failure detection class tailored to the constraints and requirements of WSN, called ANFD (Adaptive Neighborhood Failure Detection). Indeed, our solution relies on adaptive timers to detect nodes crash while considering intermittent failures of radio links. The detection of process failures is based only on a local perception that the node has on the network and not on global exchanged information. The exchanged lists of failure suspicions and mistakes are piggybacked into Query/Response messages of the WSN application. Then we analyze the properties of the defined class in terms of completeness and accuracy of failure detection in typical WSN. Furthermore, we carry out simulations using TinyOS2 to evaluate the performance of the proposed solution. We particularly evaluate the induced energy consumption overhead using PowerTOSSIM-Z and demonstrate that in addition to the benefits of the proposed solution in terms of failure detection and recovery, and reducing packet loss ratio and fault positive detections, it does not introduce extra energy overhead compared to other solutions. The paper is organized as follows: after the introduction and state of the art presented in this section, we present an overview and motivation of the proposed solution in section II. In section III, we present the different models assumed for the operation of the proposed solution. Then we present a detailed description of the solution and its properties in section IV. We present simulation results using TinyOS-2 and PowerTOSSIM-Z and performance evaluation analysis and comparison in section V. We end up this paper with conclusions in section VI.

II. OVERVIEW

Let us consider the following simple configuration to illustrate the main issues and motivation behind our proposal. Consider a system of two processes (i.e. a network of two sensor nodes): a data collector P i and a data source P j . Process P i wants to inquire regularly some information from the network; it sends periodically a query to process P j . P j responds with a data packet containing required sensed data. This is known as a Q/R mechanism. Let us assume first that links are reliable which means that messages sent from correct processes are successfully transmitted to their destination. For process crash detection, we use a Failure Detection Timeout (FDT ij ): if FDT ij runs out before receiving the expected response, P i suspects that P j has crashed. Each FDT ij value is initiated according to application parameters; such as Q/R round trip delay, 1-hop transmission latency, etc.

However, the situation changes if, in addition to process crash, link failures may also occur. In fact, with the above FDT, P i may make some mistakes, when the process is still correctly working but some messages are lost because of lossy links (intermittent failures). For this reason, we need to update FDT ij value following the lossy pattern of radio links.

In this paper, we explore the use of adaptive FDT to circumvent this obstacle: we use a stochastic approach to determine FDT taking into consideration loss ratio, links state, transmission delay, etc. It is important to notice that FDT is defined between two consecutive neighbor sensors instead of any couple of nodes. This allows more accurate calculation of FDT that relies then on local predictable transmission delay without requiring knowledge about the entire system composition and network topology. Nevertheless, local suspicions and mistakes will propagate throughout the network and hence taken into consideration in route maintenance by the overall nodes of the WSN. We present thereby, a new failure management class for WSN, where each process can query a failure detection module that provides information about which process of its neighbors has crashed. This information is typically given in a form of a list of suspects (Suspected i , is the list of process P i containing its suspected neighbors). However, mistakes can be made: a process may be suspected though it has not crashed. Hence, in addition to the Suspected i list, each module has a list of Mistake i where it notifies previous mistaken suspicions and retrieves correct processes from Suspected i list. All these notifications are piggybacked on Q/R messages using neighborhood interaction to avoid extra overhead that would have been induced if dedicated signaling packets were used.

In Erreur ! Source du renvoi introuvable.we illustrate the interactions between the different modules with our failure detection module: ANFD uses the characteristics of the data gathering protocol (e.g. round delay) and the pattern of packet losses to determine a timer FDT for each neighbor. The neighboring list is given by the network module. Furthermore, the data gathering protocol sends (resp. receives) Q/R messages to (resp. from) ANFD module in order to update (resp. deliver) the lists of suspicions and mistakes. Thus, every Q/R message piggybacks information about nodes" crashes and mistaken suspicions. Moreover, both lists updates will lead to a new FDT refresh in order to give more accurate notifications in next rounds.

III. SYSTEM MODEL

A. Network model

We consider a sensor network consisting of a finite set V of n>1 processes, namely, V= {P 1 ,…,P n }. There is one process per node and they communicate by sending and receiving messages via a wireless network. Processes have no knowledge about V or n; but, they know a subset of V, composed of nodes with whom they previously communicated. The system can be represented by a communication graph G(V,E) in which V represents the set of nodes and E represents the set of radio links. If (P i ,P j )E then P i and P j are considered neighbors. Moreover, we suppose that the network is f-covering; i.e. the graph G(V,E) is (f+1) connected. This property ensures that there is always a route between any two nodes of the network in spite of f faults.

B. Failure model

We assume that sensor nodes of the WSN may crash, as it is commonly assumed in the literature [?, ?, …]. Moreover, links between two sensor neighbors are considered lossy: they may drop messages during transmission. This is commonly due to transmission link failure; which is intermittent by nature. Subsequently, if a process crashes, it will never belong to the network anymore; and has to be notified to all its neighbors. However, if it fails to send some packets, this loss should be considered as intermittent failure. Hence, even if ANFD may suspect a process of having crashed while actually the link is down it will be able to detect mistaken suspicions once the link is set back.

C. Data gathering model

We consider data-centric Q/R based routing protocols. In this kind of data gathering models a collector node (also known as a sink) periodically broadcasts a data Query to all nodes using a multi-hop routing scheme. Each intermediate node receives the query from an upstream neighbor, and then diffuses it to all its neighboring nodes. When a source observes a matching event, it sends back a Response to nodes which it should reply to. In the same way, intermediate nodes forward the Response until it reaches the sink. Without loss of generality, Directed Diffusion [START_REF] Intanagonwiwat | Directed diffusion: a scalable and robust communication paradigm for sensor networks[END_REF] is a scheme that matches this data gathering model, and we will show further how ANFD can improve DD to cope with failures and route recovery.

IV. ADAPTIVE NEIGHBORHOOD FAILURE DETECTION

We present hereafter ANFD algorithm for process P i . We suggest including ANFD as a module between the layer that manages the Q/R messages and the beneath layer. ANFD can interact with both layers using four main primitives, and a set of variables and procedures introduced in TABLE I. Statement that returns true if: Pl does not exist in the caller"s (Pi) suspect and mistake lists, or Pl exists in Pi"s lists but with smaller counter.

A. ANFD algorithm

We recall that we consider a Q/R data gathering model. The algorithm proceeds by rounds. At each Q/R round, a node (generally the collector) launches a query broadcast. Each node forwards the received Q/R message to the nodes in its range until it possibly crashes. The basic principle of our approach is to piggyback failure suspicion on the Q/R messages, and dispatch this information hop by hop. In addition to application data, we add up to each message two sets of nodes: Suspected i (the set of nodes that are suspected of being faulty), and Mistake i (the set of the mistakes; the nodes that were previously erroneously suspected of being faulty). Each node keeps a counter, which is incremented at every round. Any new information that is generated by this node about failure suspicions or correction of false suspicions (mistakes) within a round is tagged with the current value of such a counter. This tag mechanism avoids obsolete information to be taken into account by nodes.

ANFD module for process P i is described in Figure 2. It is composed of two main primitives and one procedure: The primitive ANFD.Send(msg) includes both of Suspected i and Mistake i sets in the message msg originated from the upper layer (line 4). After piggybacking the information, P i sends the new message to the downward layer (line 5) in order to forward it to the destination node. In addition, if the original message is a query, P i initializes a timer for every correct known neighbor; say FDT ij for node P j awaiting for a response to its query (lines 6-9). At the end of ANFD.Send, counter i is incremented by one. If any FDT ij runs out (line 19), Timer.Fire(P j ) is triggered; that is, P i suspects P j of being faulty. First, it checks if Mistake i list contains P j , so it is removed from it. The new suspicion information is then included in Suspected i with a tag which is equal to the current value of counter i or with a greater tag than the one associated with P f in Mistake i set if it was previously inside (lines 20-23). This suspicion will be included in the next Q/R message when ANFD.Send is executed again.

The second primitive ANFD.Receive(msg) aims to update suspected and mistake sets according to those piggybacked on the received message delivered from the downward layer. First, P i retrieves information, namely, both suspected and mistake sets with their source node P j (line 12), then it stops FDT ij , since the message was successfully delivered (line 13). P i checks then if P j (the source) was recently suspected in order to delete it from Suspected i set and insert it into Mistake i with current counter i (lines 14-16). After that, P i calls the UpdateLists procedure in order to treat the received information about suspicions and mistakes in P j "s message (line 17). Finally, QRLayer.Receive sends the new message msg to the upward layer (line 18). The two loops of procedure UpdateLists handle information about suspected (respectively erroneously suspected) processes. Thus, for each node P l included in Suspected j (resp. Mistake j ) set, P i includes P l in its Suspected i (resp. Mistake i ) set only if it received more recent information about P l status (faulty or mistaken of being faulty). In such a case, P i removes P l from its lists to insert the given more recent information in the corresponding set (lines 25-28& 29-32).

B. How to determine FDT (SetFDT function)

The Failure Detection Timeout (FDT) should be dynamically updated while taking into consideration transmission failures, communication protocol behavior and network dynamics in general. Notice that there is no general formula since it depends on the choice of the routing protocol and its parameters. We illustrate by an example in section V how to set its value for a specific protocol, namely Directed Diffusion. In general case, we need to consider the following factors:

 Transmission delay between 1-hop neighbors: to estimate the required time for a packet to be transmitted from source to destination in a direct link (i.e. 1-hop neighbors).  Round delay for the Q/R mechanism: ANFD should wait at least a round trip of the Q/R messages before suspecting any neighbor failure.  Tolerated Burst Loss (TBL) in link failure: to postpone the suspicion in order to tolerate intermittent failures due to packet loss (not process crash). Indeed, it has been demonstrated [START_REF] Elliott | estimates of error rates for codes on burst-noise channels[END_REF][9] that losses in wireless networks follow a bursty pattern. Therefore, FDT must be at least greater than the average value of the TBL.  Network activity statistics: network traffic may influence the effective delays for packet transmission, and packet losses. FDT has to take into consideration such actual network traffic and its impact on packet transmission delays and losses. Knowing that FDT is updated for 1-hop neighbor, it is then easy to use such parameter.

In the beginning, since there is no former communication to make statistics from, the first FDT value is initially set according to hypothetical values of transmission interval and latency. After which, FDT is updated using the effective loss rate regarding received Q/R messages. Moreover, after each mistaken suspicion, FDT must be increased in order to adapt the failure detection mechanism to the network activity and avoid notifying link failures (i.e. packet loss) as crashes.

C. Properties of the new failure detection class for WSN

Any failure detector FD is characterized by two properties: completeness and accuracy [START_REF] Chandra | Unreliable failure detectors for reliable distributed systems[END_REF]. Completeness requires that FD eventually suspects every process that actually crashed, while accuracy limits the mistakes FD can make. Since we have considered network and failure models tailored to WSN, we define new completeness and accuracy properties that better suite our network, failure and data gathering models:

Definition 1 (1-hop-Completeness):

There is a time after which every process P i that crashes is suspected by all its correct neighbors.

 Pi crashes,  PjNeighborsi, T:  t>, Pi  Suspectedj
This property satisfies strong completeness limited to 1-hop neighborhood.

Definition 2 (1-hop-Accuracy):

There is a time after which some correct processes are never suspected by any correct neighbor.

 Pi correct,  PjNeighborsi, Pj correct, T:  t>, Pj  Suspectedj
This property defines the eventual weak accuracy limited to 1-hop neighbors.

The merit of these new definitions is to provide adequate measurement tools of completeness and accuracy of failure detection tailored to the limitations and requirements of WSN. Indeed, if strong completeness and accuracy are mandatory in conventional distributed systems, in WSN 1hop-completeness and 1-hop-accuracy are enough for route update provided that the network remains connected (fcovering property). Therefore, due to energy, storage and bandwidth limitations, every node monitors only its direct neighbors, even though the information (Query resp. Response) is initiated by a further node (sink resp. source). Later, suspicion notifications sent initially to neighbor nodes will reach on-route nodes to the sink and hence update their routes consequently. Finally, notice that, using this local interaction is energy efficient as will be demonstrated in performance evaluation section through simulations using TinyOS2 and PowerTOSSIM-Z.

Proposition: ANFD guarantees the following properties:

-1-hop-completeness -1-hop-accuracy Proof:

V. PERFORMANCE EVALUATION

In this section, we present simulation results with respect to the adaptive FDT used in the new proposal ANFD. We will focus mainly on the outcome of using adaptive failure detection timer that allows, as we will see, to enhance failure detection with the presence of intermittent failures due to packet losses. We carried out the simulations using TinyOS2 [?] augmented with PowerTOSSIM-Z [?] for energy consumption profiling.

A. Simulation model

We will consider Directed Diffusion (DD); a Q/R based data gathering protocol, as a basis for our study. DD does not use any failure management mechanism; it relies instead on periodic diffusion of exploratory data to circumvent eventual faulty nodes. We have implemented DD in TOSSIM/TinyOS [START_REF] Levis | Tossim: "accurate and scalable simulation of entire tinyos applications[END_REF] environment. We consider a network composed of 50 to 100 nodes randomly deployed. We modeled packet loss using a two-state Markov chain [START_REF] Elliott | estimates of error rates for codes on burst-noise channels[END_REF] [START_REF] Gilbert | Capacity of a burst-noise channel[END_REF]. We simulate node crashes by running a python script that selects a subset of nodes to turn off (node i crashes at time t) following an exponential law. In order to illustrate the outcome of using adaptive failure detection, we considered several simulation scenarios using original DD without failure detection, Fat2D [?] (DD with constant FDT) and the proposed solution: DD augmented with ANFD (DD equipped with adaptive FDT). We were interested in four main metrics:

 the failure detection time which is the required period between failure occurrence and its detection.  The packet loss rate, defined by the proportion of lost data due to route breakdown after some node crashes. The performance of ANFD is greater when it can decrease the amount of lost data.

 The mistaken suspicions rate or false positive rate defined by the proportion of falsely suspected nodes due to intermittent failures. This allows evaluating the accuracy property.  Energy consumption which provides hint on the network lifespan and the overhead induced by introducing ANFD.

B. Simulated protocols parameters

In this section we present the considered configuration of the three simulated protocols using TinyOS2 that we analyze and compare at the end of this section.

1) Directed Diffusion (DD) [?]

Recall that in DD a source sensor sends sensed data each I r (reinforcement interval) time units to the upward node toward the sink. Besides, each I e (exploratory interval) time units, the source sensor broadcats data in order to discover eventual new routes and hence circumvent failed ones.

2) Fat2D [?] in this protocol, DD is augmented with a static failure detection timeout (FDT) calculated as follows:

……1

Where I r , I e are reinforcement (resp. exploratory) intervals, and TBL (Tolerated Burst Loss) is the average length of the burst loss due to intermittent radio transmission failure, Formula (1) means that FDT equals to the average length of a burst loss with lower and upper limits: the lower limit is the exploratory interval where DD naturally discovers new routes and circumvent failed ones, and the upper limit is two times the reinforcement interval beneath which we cannot suspect a loss since the source is not supposed has sent a new message.

3) ANFD

For ANFD, the initial FDT 0 is defined by formula [START_REF] Aguilera | Heartbeat: A Timeout-Free Failure Detector for Quiescent Reliable Communication[END_REF]. Then, for FDT update, we check the mistaken suspicions rate 2 after each round (cf. algorithm in fig. ?, line 3). If it exceeds a fixed threshold , we increase the TBL to tolerate more burst loss. For this reason, we increase the percentage of accepted burst loss (say by 10%), and then update TBL by using the cumulative distribution function (cf. algorithm in figure ?, lines 4&5). Once TBL is updated, we use formula [START_REF] Aguilera | Heartbeat: A Timeout-Free Failure Detector for Quiescent Reliable Communication[END_REF] to get the new FDT.

C. Simulation results

In this section we analyze the impact of implementing ANFD mechanism on DD, with respect to the following scenarios, and compare it to DD and Fat2D:

1) Impact of failure detection timer on detection period: we compare DD, Fat2D (equipped with a static failure detection timer) and ANFD that uses adaptive FDT. We vary the number of crashes randomly inserted during the experiment. Results in Erreur ! Source du renvoi introuvable.show that implementing a failure detection timer in DD has considerably decreased the required period for failure detection. Moreover, we clearly notice that using the new approach ANFD with adaptive timer results in a faster detection mean time. 2) Impact of adaptive FDT on packet loss rate: the second measurement was performed to evaluate the impact of failure detection on data loss. Since adaptive FDT allows a prompt detection and then a fast recovery, the new approach obviously decreases data loss. This is shown by the graph on Erreur ! Source du renvoi introuvable.where the packet loss rate in DD increases proportionally to the number of crashes. Notice that ANFD has considerably decreased this rate. Moreover, it gives the best results comparing to static FDT approach implemented in Fat2D. 3) Impact of failure detection timers on false positive suspicions: this measurement was performed on Fat2D vs. ANFD in order to evaluate the accuracy property. In this scenario there is no process crash (only intermittent failures are injected using a burst loss model based on a two state Markov chain). We vary simulation time in order to allow more intermittent failures for longer periods. For each experiment, the rate of false suspicions was measured. We notice in Erreur ! Source du renvoi introuvable.that the rate of mistaken suspicions is slightly greater in the case of constant timer (Fat2D), compared to the case of adaptive timer (ANFD). Actually, SetFDT function makes FDT updates after each round in order to tolerate more intermittent failures and prevent mistaken suspicions. This dynamic increasing offers better accuracy comparing to constant timer.

4) Impact of failure detection on energy consumption:

the final measurement was performed for the battery use. As energy consumption is a critical constraint for WSN, it"s important to evaluate the impact of implementing a failure detection mechanism on the amount of battery usage. We carried out the measurements using PowerTOSSIM-Z [?]. Results in Erreur ! Source du renvoi introuvable.show that, even though ANFD (or even Fat2D) implements an additional mechanism for failure detection, they actually consume energy less than DD. Indeed, while DD wastes a great amount of energy to send lost data on faulty routes (after nodes" crashes), ANFD detects failures sooner and hence saves energy consumption by prompt path recovery. Yet, even if the difference of battery use is small, this result is promising since the overhead due to implementing an additional technique for failure detection compensate the overhead that would have been induced because of useless transmissions after node failures. However, our adaptive failure detection technique has the merit to save sensed data through fast route recovery. Without failure detection mechanisms, DD either looses data which decreases the quality of decision making at the application level or relies on higher transport protocol for eventual retransmission which would induce great overheads (energy, bandwidth, storage, computation, etc.).

VI. CONCLUSION

In this paper, we have presented a new failure detection solution for WSN (ANFD); where processes interact only with their 1-hop neighbors using a Q/R scheme. The algorithm of ANFD is based on adaptive failure detection timer for crash suspicion. The proposed technique insures 1hop completeness and 1-hop accuracy, two properties that we have introduced in this paper to take into consideration requirements and constraints of WSN. We carried out simulations using TinyOS2, and energy profiling using PowerTOSSIM-Z. The simulation results show that our solution decreases the failure detection time, packet loss ratio and suspicion fault positives. Moreover, we demonstrated that augmenting directed diffusion with our adaptive failure detection scheme allows not only to save valuable sensed data through fast route recovery, but also does not induce extra energy consumption overhead.

Figure 1 .

 1 Figure 1. Different modules interaction.

Figure 3 .

 3 Figure 3. FDT update function for Directed Diffusion.

Figure 4 .

 4 Figure 4. Impact of failure detection timers on detection time.

Figure 5 .

 5 Figure 5. Impact of failure detection timers on packet loss rate.

Figure 6 .

 6 Figure 6. Impact of failure detection timers on accuracy property.

Figure 7 .

 7 Figure 7. Impact of failure detection on energy consumption.

TABLE I .

 I Round counter at node Pi. Counteri j is the round counter attributed to node Pj at node Pi. The round counter is used as a stamp for generated information.SuspectediSet of processes suspected by Pi of having crashed. Each element consists of a tuple <Px,counteri x >; Px is the suspected process at time counteri x .Inserts the new process id in the list set or updates the attributed ctr if it already exists with a smaller counter.

		Retrieve(msg,	reads and returns both suspected and mistake sets from
		suspected,	msg and their source
		mistake, source)
		Add(set, <id,
		ctr>)
		SetFDT(Pj)	evaluates and sets or updates the failure detection
			timeout for process Pj.
		Timer.schedule	triggers a timer FDTij for process Pj.
		(Pj, FDTij)
		Timer.stop(Pj)	stops timer FDTij for process Pj.
		Actual
		(<Pl, counter j	l>)
	Variable/	Presentation
	Procedure
	Neighborsi	List of Pi"s 1-hop neighbors updated outside our
		algorithm 1 .
	Counter i
	Mistakei	Set of nodes which were previously suspected of having
		crashed but such suspicions are currently considered to
		be false. Each element consists of a tuple <Px,counteri x >;
		where Px is a previously suspected process.
	QRLayer.Receive	Delivers messages to the layer managing Q/R messages
	(msg)
	DLayer.Send	sends messages to downward layer to be transmitted to
	(msg)	its destination
	Piggyback(msg,	adds to msg, both of suspected and mistake set, and the
	suspected,	source Pi
	mistake, Pi)

NOTATIONS AND TERMINOLOGY FOR ANFD.

We suppose that external module updates Neighbors i list each time P i receives a new message from unknown node P j .


MD Jos Boesten
email: jos.boesten@hag.unimaas.nl

MD Luc Harings

MD Bjorn Winkens

PhD; André Knottnerus

MD PhD Trudy Van Der Weijden

Defining antimicrobial prescribing quality indicators : what is a new prescription?

Keywords: Quality Indicators, Health Care, Primary health care, Prescriptions, Guideline Adherence 2

Since guidelines on antibiotic drug treatment often focus on appropriate first choice drugs, assessment of guideline adherence should only concentrate on the first drug prescribed, and not on subsequent antibiotics prescribed after failure of the first one.

Purpose: to determine a valid cut-off point for a definition of "first", or "new" prescription in indicators for the assessment of the quality of antibiotic drug treatment on the basis of pharmaceutical data.

Methods: Three possible definitions for the term "new prescription" were compared, based on three different periods of time, viz. more than 35, 28 or 21 days after starting a previous antibiotic. In an observational study, 1225 antimicrobial prescriptions from the medical files of five family practices were audited ("clinical classification") and compared with a classification based on the three definitions ("technical classification"). Agreement between these clinical and technical classifications was determined by calculating Cohen's kappa. The technical classification was analyzed as a diagnostic test, using the clinical classification as the gold standard, and sensitivity, specificity, likelihood ratios and post-test probabilities were calculated.

Results: Defining "new prescription" as "more than 35 days after a previous prescription was issued" resulted in a Cohen's kappa of 0.93 (95% CI 0.92-0.98). The diagnostic value of this definition was extremely high, with sensitivity of 0.976, specificity of 0.987, positive likelihood ratio of 77.7 and negative likelihood ratio of 0.02.

Conclusion:

We recommend using a cut-off value of 35 days since the last antimicrobial prescription in the definition of a "new prescription" when no diagnostic information is available, i.e. when using pharmaceutical data to assess the quality of antibiotic prescribing behavior.

Introduction

Resistance of micro-organisms to antimicrobials is an increasing problem worldwide, posing a potential threat to public healthcare [START_REF] Earss | Bilthoven: the European Antimicrobial Resistance Surveillance System[END_REF]. The European Surveillance of Antimicrobial Consumption (ESAC; www.ua.ac.be/ESAC) project, funded by the European Commission, has collected data on the use of antibiotics in Europe since 2001. Several of their studies found that higher consumption of antibiotics correlates strongly with high rates of resistance [START_REF] Goossens | Outpatient antibiotic use in Europe and association with resistance: a cross-national database study[END_REF]. General practitioners play a key role in fighting antimicrobial resistance, since they provide 80% of all prescriptions of antibiotics in human medicine [START_REF]Tweede Nationale Studie naar ziekten en verrichtingen in de huisartspraktijk. Kwaliteit huisartsenzorg belicht[END_REF]. In addition, veterinarian use of antibiotics in Western Europe is also accountable for a major part of the total volume of antibiotics used [START_REF] Maran- | Monitoring of Antimicrobial Resistance and Antibiotic Usage in Animals in the Netherlands in[END_REF], and it is especially the non-therapeutic use of antibiotics as growth promoters which may have played an important part in the development of antimicrobial resistance, although some authors doubt this [START_REF] Philips | Does the use of antibiotics in food animals pose a risk to human health? A critical review of published data[END_REF]. The use of antimicrobial growth promoters was prohibited in the beginning of 2006, but this issue is beyond the scope of the present article.

To minimize antimicrobial resistance, general practitioners are recommended to adhere to the clinical practice guidelines on antibiotics. Guidelines on prescribing antimicrobial drugs focus on the type of antibiotics that should be used as a treatment of first choice and the types which should be avoided as first choice treatment. Only a few guidelines also mention what choice should be made after failure of the initial treatment.

In situations where one evaluates individual prescriptions and with the availability of a diagnosis it might be possible to detect wether a prescription is the first one or a subsequent after failure of the first, and so whether the choices made are appropriate.

However, with the use of pharmaceutical database that lack information about diagnosis this is not possible. But when studying all prescriptions in a period, one could detect what proportion of the first prescriptions is in line with guidelines. This means that when assessing the guideline adherence in antibiotic drug treatment in a pharmaceutical database, only those prescriptions that represent the first antibiotic treatment for a disease/diagnosis ("first", or "new" prescriptions) should be taken into account.

In the context of a regional quality improvement project, we developed a set of quality indicators that measure guideline adherence regarding the prescription of antimicrobial drugs by general practitioners. Our indicators are derived from 12 guidelines by the Dutch College of general Practitioners and have been validated by a panel of experts using the RAND-UCLA method [START_REF]RAND/UCLA Appropriateness method[END_REF], covering face and content validity.

One option for assessing guideline adherence is to use pharmaceutical databases [START_REF] Andersen | Is it possible to measure prescribing quality using only prescription data?[END_REF]. Since these databases lack diagnostic information, however, we used a predefined minimum number of days between the current prescription and an earlier antibiotic prescription as a proxy measure to determine whether the current prescription should be regarded as first or new and should be taken into account when assessing the quality of prescribing.

The prescribing quality indicators are applied to a large pharmaceutical database containing PACT (prescribing analyses and cost) data. Pharmacists in the Netherlands charge all delivered drugs to health insurance companies. Their accounts include information about the patient (age and sex), the prescriber and the drug [START_REF] Campbell | Prescribing indicators for UK general practice: Delphi consultation study[END_REF][START_REF] Muijrers | Prescribing indicators. Development and validation of guideline-based prescribing indicators as an instrument to measure the variation in the prescribing behaviour of general practitioners[END_REF]. But general practitioners do not provide information on indications/diagnoses to pharmacists, due to autonomy considerations. We collected data from two major health insurance companies in the southern part of the Netherlands, which meant that huge quantities of information on all drugs supplied in one year were available for analysis.

In four of our indicators, we encountered problems relating to the definition of a "new prescription". [table 1]. If the period of time since the previous prescription that is used in our indicator is too short, many prescriptions that are in fact second choice prescriptions for the same indication/diagnosis, after failure of the first treatment, would incorrectly be labeled as "new prescriptions" by our indicator. If the period of time is too long, many new prescriptions will be missed in the calculation of the indicator score. In this study we therefore tried to determine after what period of time (21, 28 or 35 days) it is safe to assume that a prescription of antibiotics is new, i.e. it is the first prescription for a new indication. We investigated this by comparing the pharmaceutical data with information from the medical files of patients kept by five family practices.

Methods

Study design

In a cross-sectional observational study, a random sample of prescriptions of antimicrobial drugs was taken from patient files for 2008 kept by family physicians. We used these prescriptions to calculate how the four indicators containing the phrase "new prescription" [table 1] would classify each prescription, using different definitions of the period since the previous prescription (35 -28 -21 days).

Population

A total of 1225 antibiotics prescriptions were retrieved from 5 family practices in the south of the Netherlands. All practices are participating in a registration network for general practitioners (RNH) managed by the University of Maastricht [START_REF] Metsemakers | Computerized health information in the Netherlands: a registration network of family practices[END_REF]. Four of them were group practices including at least three doctors, both men and women, with varying years of clinical experience. One practice was run by a single female general practitioner.

Variables

The indications for the prescription of all examined antibiotics prescriptions were determined from the medical files. We also recorded whether the prescription was the first antibiotic treatment for the diagnosis ("clinical classification"). We then assessed how the three different definitions of "new prescription" [table 1] would have classified the prescription at stake ("technical classification").

Data collection

A senior medical student with sufficient medical knowledge visited the five practices. The electronic medical records were used to select antimicrobial drug prescriptions from 2008, taking a random sample from these lists of prescriptions, to limit the workload. For each prescription of an antimicrobial drug, the corresponding part of the medical record was extracted and made anonymous. the following items were recorded:

Is the prescription the first antimicrobial prescription for this diagnosis according to the medical judgment of the investigator? Would the indicator definitions have classified this antimicrobial prescription as new or not?

The first practice visited was used as a trial for the procedure, to see whether any problems would arise with the interpretation of the medical files. This meant that more prescriptions (n=505, about 1/3 of all 1792 antibiotic prescriptions for 2008) were audited in this first practice than in the other practices. All records were also assessed by the first author, a general practitioner with more than 20 years of experience. Since no unforeseen problems were encountered, the results of the first practice were included in the analysis.

A fixed total number of 180 prescriptions were audited in each of the remaining three practices. These included 90 prescriptions for indicators 1-3 (30 prescriptions for each indicator) and 90 for indicator 4. Since indicator 4 includes three different types of antibiotics, and we wanted to ensure sufficient numbers per subgroup (not analyzed in this paper), 30 files per antibiotic type were audited for this indicator, so 90 in all.

Analysis

The results of the scoring forms for all practices were pooled for each indicator and for each definition, and entered into a 2x2 table. Cohen's kappa and the corresponding 95% confidence interval were then determined to estimate the agreement between the "technical classification" (i.e. the calculation of an indicator score based on a pharmaceutical database) and the "clinical classification", based on knowledge of the medical file, as to whether a prescription should be seen as "new".

We also analyzed the data by considering the technical classification as a diagnostic test, using the clinical classification as the gold standard, and calculated the sensitivity, specificity, likelihood ratios and posttest probabilities of this technical classification.

Results

The audit of the first practice related to 505 prescriptions, those of the remaining practices to 720 prescriptions. For each of these 1225 prescriptions, we determined whether the indicator would classify them as "new" (first) or "not new" (not first).

According to the assessment of the medical files by the investigators, there were 962 new antimicrobial prescriptions for which the period of time after the previous prescription of an antibiotic drug was more than 35 days. There were only 2 prescriptions which had been issued more than 35 days after an earlier prescription but which were in fact not new (i.e. related to the same diagnosis as the previous prescription). These prescriptions were incorrectly classified as "new" by the indicators, regardless of which of the three definitions was used. Table 2 shows how these numbers changed when different periods of time were used in the definition of a "new" prescription. Extending the chosen period to 42 or even 49 days only added 2 new prescriptions that were missed otherwise.

The results of all practices were pooled for each indicator and for each period of time used in the definition, and a Cohen's kappa and 95% confidence interval could be determined (table 3). Results for each indicator showed that the classification of new prescriptions agreed best with the classification based on the medical data if the definition involved a minimum of 35 days after a previous antimicrobial drug prescription.

Of the 986 new prescriptions, 962 (97.6%) were correctly identified by the indicators as new, while 24 (2.4%) were incorrectly identified as not new. Of the 239 not-new prescriptions, 236 (98.7%) were correctly identified by the indicators as not new and 2 (1.3%) were incorrectly identified as new.

We also analyzed the data by considering the technical classification as a diagnostic test, using the clinical classification as a gold standard, and calculating sensitivity, specificity and likelihood ratios for the three different operationalisations (table 4) The 21-day definition had a sensitivity of 0.988, a specificity of 0.788, an LR+ of 4.6 and an LR-of 0.015. The 28-day definition had a sensitivity of 0.980, a specificity of 0.904, an LR+ of 10.2 and an LR-of 0.022. The 35-day definition had a sensitivity of 0.976, a specificity of 0.987, an LR+ of 77.7 and an LR-of 0.025. Given a pre-test probability of an antibiotic prescription being new of 80.5%, the posttest probabilities for positive test results were 94.9%, 97.6% and 99.7% for the 21-28-and 35-day definitions, respectively, and the posttest probabilities for negative test results were 0.38%, 0.55% and 0.61%, respectively.

Discussion

We developed a set of indicators of the quality of doctors' prescribing behavior, in the context of a regional project to measure guideline adherence in general practice, using a pharmaceutical database. The validity and accuracy of such quality indicators must be guaranteed to enable the quality of healthcare to be assessed. In addition to aspects such as face and content validity, problems arose with four of the indicators concerning the definition of the term "new prescription" in relation to antimicrobial drugs, in the sense that a "new" antimicrobial drug has to be the first treatment for a given diagnosis. This was defined as: there should be a certain minimum period of time between the "new" prescription and the time when the previous antimicrobial prescription was issued. We examined the effect of three different periods of time (35, 28 and 21 days) for this definition by auditing medical files in five family practices in the south of the Netherlands and calculating which period would best allow our indicators to classify antimicrobial prescribing behavior correctly. We found that our four indicators showed the best fit with reality if we defined a "new prescription" as being issued at least 35 days after the previous antimicrobial prescription was issued (Cohen's κ ≥ 0.90). This "clinical" classification (based on patient files) was compared with a "technical" classification, based on our indicators (which were to be applied to a pharmaceutical database). When analyzing the technical classification as a diagnostic test, the posttest probability also showed very high values. This high score legitimizes the use of 35 days as the cut-off value, with only a low rate of misclassification remaining. In fact, most misclassifications involved new prescriptions being classified as not new, which would mean they are not taken into account when calculating the score for a particular quality indicator.

Our study was subject to certain limitations. Firstly, the results might not be representative of all family practices in the Netherlands, since our study took place in the southern part of the country only, and only in 5 family practices. However, the population of practices included in the RNH registration network are generally well comparable to the Dutch population as a whole [START_REF] Metsemakers | Computerized health information in the Netherlands: a registration network of family practices[END_REF]. Secondly, the auditing of the medical files was done by a student and not by an experienced doctor. However, this was a senior medical student, who immediately after completing this research project received his medical degree and started vocational training in general practice. Furthermore, the student discussed all problematic classifications (3%) with the first author. The third limitation was that we only compared results for three periods of time: 35, 28 and 21 days, and not for periods longer than 35 days. Extending this period beyond 35 days would definitely improve the accuracy of the concept of "new prescription", but would incorrectly exclude from the numerator and denominator too many prescriptions that were in fact new, thus affecting the validity as well as the robustness of the indicator.

The strengths of our study were that the five practices we visited differed in terms of location, population and degree of urbanization, and that the medical files in these practices were audited by an independent senior medical student with no conflict of interest.

Unfortunately, we found no other studies on this subject at the time we performed our study to compare our results with.

To put these findings into perspective, it is essential to distinguish between the external and internal use of quality indicators. Indicators for external use are intended to be used by governments, patient organizations or health insurance companies, whereas internal indicators are mainly used by the health care providers themselves [START_REF] Andersen | Is it possible to measure prescribing quality using only prescription data?[END_REF][START_REF] Berg | Feasibility first: developing public performance indicators on patient safety and clinical effectiveness for Dutch hospitals[END_REF]. They can use the information generated by quality indicators to monitor the healthcare provided by themselves or the organization they belong to, and can investigate the potential and current problems by reflecting on these data [START_REF] Andersen | Is it possible to measure prescribing quality using only prescription data?[END_REF]. In the case of disappointing quality, the scores should be carefully analyzed to identify explanatory factors, and if the data are correct and concern modifiable factors, they can be used to improve the outcome. Given the different purposes of internal and external indicators, they need to meet different criteria [START_REF] Andersen | Is it possible to measure prescribing quality using only prescription data?[END_REF][START_REF] Berg | Feasibility first: developing public performance indicators on patient safety and clinical effectiveness for Dutch hospitals[END_REF]. External indicators need to have the highest validity, as they are used to judge the work of medical professionals. Internal indicators also need to be accurate, but since they are mainly used for self-reflection and their results have no major consequences, certain errors of measurement are acceptable. Our indicators have a high validity but are not infallible, and we recommend cautious application, merely for internal use.

In conclusion we can state that our indicators of the quality of prescribing behavior show good validity and accuracy for internal use if we define the term "new prescription" as a prescription issued 35 days (5 weeks) or more after the previous antimicrobial prescription was issued.

Table 2 : 2 x 2 tables of all prescriptions audited. All prescriptions in the selected patient files were compared with our indicators using three different definitions of "new prescription" ( > 35, >28 and > 21 days after the previous antimicrobial prescription).

 2

			Medical file:
	Classified by		New	Not new	Total
	indicator	New	962	3	965
	using 35 days	Not new	24	236	260
	definition
		Total	986	239	1225
			Medical file:
	Classified by		New	Not new	Total
	indicator	New	966	23	989
	using 28 days	Not new	20	216	236
	definition
		Total	986	239	1225
			Medical file:
	Classified by		New	Not new	Total
	indicator	New	974	51	1025
	using 21 days	Not new	12	188	200
	defintion
		Total	986	239	1225

Table 3 : Cohen"s kappa with confidence interval for each indicator, using 21, 28 and 35 days for the definition of "new prescription". n = number of prescriptions analysed

 3

			Cohen"s	95% CI	Cohen"s	95% CI	Cohen"s	95% CI
	No	Type of antibiotic	Kappa		Kappa		kappa
			21 days	28 days	35 days
	1	Amoxicillin with clavulanic acid (n = 197)	0.90	0.83-0.97	0.93	0.87-0.99	0.99	0,96-1.00
	2	Macrolides (n = 171)	0.76	0.63-0.89	0.87	0.78-0.96	0.93	0.82-1.00
	3	Quinolones (n = 176)	0.79	0.69-0.88	0.89	0.82-0.96	0.93	0.87-0.98
	4	Amoxicillin. doxycillin. nitrofurantoin (n = 681)	0.81	0.78-0.87	0.86	0.85-0.92	0.92	0.90-0.98
	1-4	Pooled antibiotics of indicators 1-4 (n = 1225)	0.83	0.77-0.88	0.89	0.86-0.94	0.93	0.92-0.98

Table 4 : Sensitivity. specificity. likelihood ratios for positive and negative results* and pretest and posttest probabilities for positive and negative results** using 21, 28 and 35 days as definition of "new prescription"

 4 The likelihood ratio incorporates both the sensitivity and specificity of the test and provides a direct estimate of how much a test result will change the odds of having a certain property. The likelihood ratio for a positive result (LR+) tells you how much the odds of the property increase when a test is positive. The likelihood ratio for a negative result (LR-) tells you how much the odds of the property decrease when a test is negative. ** pretest probability: the proportion of prescriptions which do or don't have the target characteristic ("first" or "not first" antibiotic) Post-test probability: the proportion of prescriptions with that particular test result who have the target characteristic

		21 days	28 days	35 days
	Sensitivity	0.987	0.980	0.976
	Specificity	0.787	0.903	0.987
	Likelihood ratio +	4.63	10.18	77.73
	Likelihood ratio -	0.02	0.02	0.02
	Pretest probability +	0.805	0.805	0.805
	Posttest probability +	0.948	0.976	0.997
	Pretest probability-	0.195	0.195	0.195
	Posttest probability -	0.003	0.005	0.006
	* likelihoodratio:

Acknowledgements:

We would like to thank the following general practitioners for allowing their medical files to be audited: Isabel Buijs, Stefan van der Eerden, Henk Jochems, Joep van Proosdij, Caroline Robertson.

The authors declare that they have no conflict of interest.


Maickel Armenteros

José Andrés Pérez-García

Alexei Ruiz-Abierno

; Lisbet Díaz-Asencio

Yusmila Helguera

Magda Vincx

; Wilfrida Decraemer

Effects of organic enrichment on nematode assemblages in a microcosm experiment

Keywords: nematodes, organic enrichment, microcosm, hypoxia, tropical, community composition, effects-community, Caribbean Sea

, we predict that further organic enrichment in sediments from Cienfuegos Bay may cause a phase shift into a strongly depleted benthic fauna and reduced conditions in water and sediments.

Introduction

Organic enrichment is an important ecological process in marine sediments [START_REF] Kelly | Experimental studies of the effect of organic deposition on the metabolism of a coastal marine bottom community[END_REF] and in coastal ecosystems it is related to the presence of fine sediment, a low hydrodynamic regime and low dissolved oxygen (Snelgrove and Butman, 1994). Benthic assemblages in those environments are dominated by deposit-feeding organisms that make use of both particulate organic matter and the associated bacterial biomass. The benthic response to organic enrichment has been documented by [START_REF] Pearson | Macrobenthic succession in relation to organic enrichment and pollution of the marine enviroment[END_REF]; their model clearly describes the ecological succession that takes place in soft bottoms when organic load increases and it has been widely applied. Particularly, in sediments where heavy organic pollution exist almost no macrofauna can be found and nematodes are the dominant metazoans [START_REF] Pearson | Macrobenthic succession in relation to organic enrichment and pollution of the marine enviroment[END_REF].

Free-living marine nematodes are the most abundant deposit feeders and play an important role in transforming organic matter in marine sediments [START_REF] Findlay | Effect of a free-living marine nematode (Diplolaimella chitwoodi) on detrital carbon mineralization[END_REF][START_REF] Li | Carbon flows through meiobenthic nematodes in the Westerschelde Estuary[END_REF][START_REF] Piepenburg | Benthic community patterns reflect water column processes in the Northern Water polynya (Greenland)[END_REF]. The content of organic matter can partially explain the spatial patterns of distribution of free-living nematodes in some habitats (e.g. [START_REF] Ólafsson | Seasonal dynamics of sublitoral meiobenthos in relation to phytoplankton sedimentation in the Baltic Sea[END_REF]Schratzberger et al., 2006).

Therefore, further investigations on the relationships between organic content and nematodes and the mechanisms underlying them are needed. At least several ecological factors such as type of habitat, origin of organic input and intensity of human disturbance affects these relationships [START_REF] Schratzberger | Nematode community dynamics over an annual production cycle in the central North Sea[END_REF].

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4 Two previous studies [START_REF] Armenteros | Biodiversity patterns of freeliving marine nematodes in a tropical bay: Cienfuegos, Caribbean Sea[END_REF][START_REF] Pérez-García | Spatial distribution of nematode assemblages in Cienfuegos Bay (Caribbean Sea), and their relationships with sedimentary environment[END_REF] on the distribution of nematode assemblages in several sites in the basin found considerable spatial heterogeneity on the scale of a few meters and that the dominant nematode species were tolerant of organic enrichment, such as Sabatieria pulchra and Terschellingia longicaudata. The spatial patterns were linked to organic matter and heavy metal content in sediments and to water depth. These correlations suggested alternative ecological mechanisms that could determine the distribution of nematode assemblages, for instance: toxic effects, limitation in benthic primary productivity, and hydrodynamic regime affecting both dispersion and transport of sediment. Since no causative mechanism could be clearly identified in these field studies, an experimental approach could help to obtain a more comprehensive idea of the ecological factors that drive the distribution of the assemblages. Organic pollution of water and sediments is one of the main stressors in the marine environment [START_REF] Diaz | Spreading dead zones and consequences for marine ecosystems[END_REF] and it is an important disturbance in semienclosed basins due to the limited water renewal time of these ecosystems [START_REF] Urban | Watersheds, bays, and bounded seas[END_REF]. Cienfuegos Bay is a semi-enclosed shallow bay in the Caribbean Sea, dominated by organically enriched, muddy bottoms, although mangroves, seagrass meadows and beaches also occur within the bay. Additionally, heavy metal and hydrocarbon pollution is widespread in the sediments of the bay from industrial activities and human settlements in the basin (Tolosa et al., 2009). Increasingly development of the petroleum-related industrial activities have been occurring in Cienfuegos Bay, including refinement of crude petroleum, storage and transport of gasoline and diesel fuel, and processing of derivates like plastics. That is why an

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increase of the risk of deleterious effects of organic enrichment is expected on this ecosystem due to diffuse and/or point oil spills which could originate from the petroleum industry. In this context, an experimental approach to test the effects of a putative increase of the organic loading on the benthic assemblages is very pertinent.

Effects of organic enrichment on meiofauna and/or nematodes in experimental microcosms have been analyzed by [START_REF] Sandulli | Effects of organic enrichment on meiofauna: A laboratory study[END_REF]Nicola-Giudici (1989), Sundbäck et al. (1990), [START_REF] Webb | Response of macro-and meiobenthos from a carbon-poor sand to phytodetrital sedimentation[END_REF], and Schratzberger and Warwick (1998); all of these studies were carried out in temperate regions. Extrapolation of these results to tropical regions remains inconclusive because at least two factors are different (see [START_REF] Alongi | The ecology of tropical soft-bottom benthic ecosystems[END_REF] for review): (1) high irradiance throughout the year leads to continuous high primary production, and (2) high temperature of shallow water enhances hypoxic conditions and stratification in the water column. In addition, a general lack of information on tropical ecosystems prevents across-region synthesis [START_REF] Gray | Effects of hypoxia and organic enrichment on the coastal marine environment[END_REF][START_REF] Gray | Effects of hypoxia and organic enrichment on the coastal marine environment[END_REF].

A study was then designed to test the effects of organic enrichment on nematode assemblages in microcosm ecosystems using sediment collected from Cienfuegos Bay. The aims of the experiment were twofold: to identify possible ecological mechanisms controlling the distribution of nematode assemblages in the ecosystem; and to show the possible effects of further organic enrichment due to pollution derived from industrial activities. We proposed, the following null hypothesis (H0): there will be no changes in the structure of assemblages in the treated microcosms compared to field and control samples; and an alternative hypothesis (H1): there will be changes in the structure in response to enrichment.

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Materials and methods

Field site

Surface sediments were collected subtidally in Cienfuegos Bay, Cuba, Caribbean Sea (N 22º07.970´ W80º29.824) in May 2007. The site was previously included in a study of spatial distribution of nematodes (station 5 in [START_REF] Pérez-García | Spatial distribution of nematode assemblages in Cienfuegos Bay (Caribbean Sea), and their relationships with sedimentary environment[END_REF]. The study site is characterized by: muddy sediments (87 % silt/clay), high organic content (47.3 mg C g -1 DW), 12 m depth, marine salinity (annual range: 34 -37), and tropical temperature (annual range: 24 -30 ºC). Historical data (1991 -2001) of dissolved oxygen in the bottom waters of this station was used for further comparison with values in microcosms. Only oxygen measures clearly belonging to wet season (when sediment was collected for the experiment) were selected for comparisons due to the seasonal fluctuations.

Collection and manipulation of sediment

Five plastic cores (2.6 cm internal diameter) were taken to 6 cm depth in the sediment: three for the description of the community structure and two for the estimation of organic content; all of these samples were labeled as field control. The same day and site, 5 -10 m apart, using SCUBA diving we carefully collected

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approximately 15 l of surface sediment (top 3 -4 cm) in glass flasks. The fresh sediment was transported to the lab, stored in two plastic containers with aeration for approximately 18 h; thereafter, the sediment was gently homogenized with a plastic spoon and finally transferred to the experimental units. Before transference, four random aliquots (= small spoons) of sediment were checked for the presence of living (= moving) nematodes. As nematodes appeared alive and healthy, it was assumed that manipulation of the sediment had little impact on the survival of the nematodes.

Microcosms

Microcosms consisted of 500-ml glass flasks, and each microcosm was considered to be an independent experimental unit. Approximately the same amount of homogenized fresh sediment (150 -180 ml) was added to each microcosm resulting in a layer of sediment of 2.0 -2.5 cm depth and surface area of ca. 20 cm 2 . Care was taken to avoid the inclusion of large macrofaunal animals (e.g. polychaetes) into the microcosms. However, one week after the onset of the experiment, holes and some bioturbation activity was evident in the microcosms. The flasks were carefully filled with filtered seawater and sealed with a 45 µm mesh to prevent upward migration of meiofauna. The 72 microcosms used in the experiment were placed into four tanks of 50 l capacity (18 per tank), maintained in darkness to avoid primary production; and left for 48 h for acclimatization before application of treatments. The tanks were

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completely filled with seawater and connected to the closed seawater circuit of the laboratory; this included the use of a biological filter, the control of water temperature (27 0 C at noon), saturation of dissolved oxygen (average 6.2 ± 0.1 mg O 2 l -1 ) and constant salinity (36 ppt) for the duration of the experiment.

Treatments

Values of readily oxidizable organic matter (hereafter referred to as organic matter) of 50 mg C g -1 DW sediment (range: 44.5 -61.8 mg C g -1 DW; n = 8) at the site where sediment was collected indicate organic enrichment. Unfortunately, the rate of natural input of organic matter to sediments is largely unknown for similar tropical ecosystems. Even in more studied ecosystems (i.e. temperate estuaries) estimates of organic input to sediments are not well documented and often underestimated [START_REF] Kendall | The response of two estuarine benthic communities to the quantity and quality of food[END_REF]. Other microcosm studies have applied doses of added organic matter as high as 200 or 400 g C m -2

, sometimes without responses of nematode assemblages (e.g. [START_REF] Austen | Effects of manipulation of food supply on estuarine meiobenthos[END_REF].

Therefore, in order to induce a significant disturbance on our microcosms we choose three treatments: 1) control: without addition of organic matter; 2) medium: addition of 25 mg C g -1 DW sediment, equivalent to 50 % of natural average organic content in sediment, ca. 400 g C m -2 sediment; and 3) high: addition of 50 mg C g -1 DW,

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equivalent to an increase of 100 % of natural average content, ca. 800 g C m -2 sediment. The organic matter was added as powder of Spirulina microalgae; the content of organic matter per weight of algae was determined (536 mg C g -1 Spirulina powder) by using the same technique as for the determination of organic content in sediments (see below). The averaged (± SD) dry weight of sediment in each microcosm was assessed (103 ± 9 g), and the quantity of Spirulina powder to add was calculated (medium treatment: 5 g of powder added; high treatment: 10 g added).

Experimental design

The microcosms were assigned to the tanks by using a systematic assignation in order to obtain a maximum of interspersion of treatments; i.e. each tank contained control and treatment microcosms. Within each tank the position of the microcosms was assigned at random. At day 0, four microcosms (one per tank) were extracted and processed (control at day 0). After that, the treatments were applied: each microcosm was extracted from the tank, the previously weighted aliquot of Spirulina powder was added, the flask re-sealed and placed again into the tank.

At days 4, 15 and 30, 18 microcosms (3 treatments x 6 replicates) were extracted at random with the restriction that a balanced number of microcosms per tank should be left; i.e. no more than two microcosms belonging to a same treatment could be

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removed from the tank. From six replicated microcosms, four were taken for the analysis of meiofaunal community structure and two for the determination of the content of organic matter. At day 30 the content of dissolved oxygen in the water inside the microcosms was measured.

Processing of samples

The content of each microcosm was sieved over a 45-µm mesh sieve using filtered water. Meiofauna was sorted from sediment by flotation in a high density solution of commercial sugar dissolved in water (1.17 g cm -3

); the sorting efficiency of meiofauna using this technique is ca. 95 % in our lab [START_REF] Armenteros | Efficiency of extraction of meiofauna from sandy and muddy marine sediments[END_REF]. Sorted meiofauna were counted under an stereomicroscope (36x) by using a counting dish, and 50 nematodes (when available) from each sample were removed for identification. Nematodes were mounted on microscope slides after the procedure by [START_REF] Vincx | Meiofauna in marine and freshwater sediments[END_REF] and identified to species level by using the pictorial keys by Platt andWarwick (1983, 1988), [START_REF] Warwick | Free-living marine nematodes[END_REF] and the NeMys Database [START_REF] Deprez | NeMys. World Wide Web electronic publication[END_REF].

Concentration of readily oxidizable organic matter in sediment was determined by the modified Walkley-Black wet titration method [START_REF] Loring | Manual for the geochemical analysis of marine sediments and suspended particulate matter[END_REF] ). Additionally, a time series of dissolved oxygen in the bottom water was included for comparison with experimental units; the data came from the same station where sediment was collected and in the same weather season (wet).

Measures of assemblages

Traditional measures of structure of assemblages (i.e. abundance and number of species of nematodes) were determined. Each nematode species was classified into a scale of coloniser/persister (c-p value) according to several aspects of the life-trait after [START_REF] Bongers | The maturity index: an ecological measure of environmental disturbance based on nematode species composition[END_REF] and [START_REF] Bongers | Interpretation of disturbanceinduced maturity decrease in marine nematode assemblages by means of the Maturity Index[END_REF]. The maturity index of the community was calculated on the basis of the score in the c-p scale. Nematode species were assigned to feeding types according to Wieser´s (1953) classification based on the morphology of the buccal cavity: selective deposit feeders (1A), non-selective deposit feeders (1B), epigrowth feeders (2A) and predator/omnivores (2B). The percentage of contribution of each feeding type to the total abundance was calculated for each sample. The four percentages (i.e. four feeding types) were pairwise significantly correlated each other; therefore only the most variable feeding type (non-selective deposit feeding, 1B) was subjected to statistical analysis because it putatively contains more interpretable information.

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Data analysis

Multi-and univariate techniques were used for data analysis using the software PRIMER 6.0.2 [START_REF] Clarke | Primer v6: User manual/tutorial[END_REF] and STATISTICA 6.0 from StatSoft. We tested the existence of statistical differences in six variables: organic matter, dissolved oxygen, number of nematodes, number of species, maturity index and percentage of 1B nematodes. Two graphical methods were performed before the application of a statistical test in order to know if data fulfil the premises of parametric analysis: scatter plots of mean versus standard deviation; and residual versus predicted mean. If needed, data were transformed and re-checked to know if parametric assumptions were applicable. Two types of comparisons were performed due to the fact that a full crossed design treatment x time could not include the field samples (no time).

(i) Comparisons between control groups in order to assess the "microcosm effect" using a one-way ANOVA with five levels: field control, microcosm controls at days 0, 4, 15, and 30. If ANOVA was significant, two planned comparisons using least square means (t-test) were performed: field versus day 0 to test differences between natural environment and experimental conditions; and day 0 versus 30 to test the temporal changes in the microcosm controls. The organic matter content was not measured at day 0, therefore the ANOVA levels were four and the following planned comparisons were performed: field versus day 4, and day 4 versus 30. The dissolved oxygen was measured only at day 30, so the comparison was done by means of one-way ANOVA

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between treatments with five levels: field, tank, control, treatment medium, treatment high.

(ii) Two-way crossed ANOVA was carried out in order to compare: treatment (main factor, 3 levels: control, medium, high), time (main factor, 3 levels: 4, 15, 30 days) and their interaction.

Non-parametric analysis of similarity (ANOSIM) was employed for testing differences in multivariate structure of assemblages. Data were square-root transformed for down weighting the contribution of dominant species to structure. Similarity matrices were built by using Bray-Curtis similarity index and they were used for the ANOSIM hypothesis test and for the numerical ordination of samples by non-metric multidimensional scaling. The SIMPER procedure was applied to look for species which contribute the most to find out similarity/dissimilarity across treatments and/or time.

Results

Visual description of microcosms

Clear changes in sediment and overlying water were observed in microcosms along the duration of the experiment. Control microcosms were apparently stable during the

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14 32 days of the study: with clear water, a relatively thick oxidized layer of sediment (ca.

5 mm) and presence of mounds and holes, presumably due to the activity of the small macrofauna. Two to three days after the addition of organic matter, treated microcosms showed a gradual trend of change for both sediment and water. At day 30, all treated microcosms showed high turbidity, smell of hydrogen sulfide, blackening of sediment and presence of mats (presumably bacteria) on the watersediment interface.

Abiotic factors

There were differences in the log-transformed values of organic matter among field and microcosm controls (one-way ANOVA, F 3,4 = 6.0, p = 0.06). Planned contrasts indicated significant differences between field and day 4 (t 2,4 = -3.8, p = 0.02) suggesting higher levels of organic matter in the field. No significant differences between controls at day 4 and 30 (t 2,4 = -0.74, p = 0.5) were detected; this indicates that levels of organic enrichment were stable in control microcosms (Figure 1). There were differences among treatments in the log-transformed values of organic matter (two-way ANOVA, F 2,9 = 235.9, p < 0.001) but there were neither among days (F 2,9 = 0.5, p = 0.6) nor in the interaction (F 4,9 = 0,9, p = 0.6). This indicated that the treatments were effective, thus increasing the amount of organic matter in microcosms and that the organic content was constant throughout the experiment (Figure 1).

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A comparison of values of dissolved oxygen among treatments (at day 30) and field did not show statistical differences (one-way ANOVA, F 3, 36 = 1.64, p = 0.20).

Measurements of dissolved oxygen indicated hypoxic conditions within the experimental units, with mean values less than 2 mg O 2 l -1 ; the field measurements showed a larger variability (Figure 1).

Abundance, number of species and maturity index

Thirty six species of free-living marine nematodes were recorded in our study (Table 1). A comparison of univariate measures of assemblages between field and control samples at day 0 could indicate how much the assemblages in the experimental conditions mimic the ones in the natural environment (Table 2, one-way ANOVA).

There were significant differences in the log-transformed number of nematodes.

Planned comparisons did not show any difference between field and control microcosms at day 0 (t 2, 38 = 0.6, p = 0.6), but they revealed significant differences between control microcosms at days 0 and 30 (t 2, 38 = 4.1, p < 0.001) with a lesser number of nematodes in controls at the end of the experiment (Figure 2). The number of species showed significant differences; but the post hoc comparisons detected differences neither between field and control microcosms at day 0 (t 2, 38 = -1.3, p = 0.2) nor between control microcosms at day 0 and 30 (t 2, 38 = 1.2, p = 0.2).

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The maturity index showed significant differences among field and controls (Table 2); however, the post hoc comparisons could not detect significant differences between field and control microcosms at day 0 (t 2, 38 = -1.4, p = 0.16), and between days 0 and 30 (t 2, 38 = -1.84, p = 0.07). Percentage of non-selective deposit feeding nematodes showed significant differences between field and control samples (Table 2). Planned post hoc comparison indicated no differences between field and control at day 0 (t 2, 38 = 0.88, p = 0.4), but they showed significant differences between controls at day 0 and 30 (t 2, 38 = 2.9, p = 0.006). In general, results of comparisons among controls suggest that univariate measures of nematode assemblages were similar in field and in control microcosms at day 0. However, several measures of assemblages changed significantly at the end of the experiment in comparison with day 0, indicating that experimental conditions affect the existence of the assemblages in enclosed conditions (i.e. microcosm effect). ( I suspect that the oxygen supply to the micrcosms through newal by water flow was less than that in the field)

A two-way crossed ANOVA for comparison among treatments (three levels: control, medium and high) and times (three levels: days 4, 15 and 30) shows the effects of the treatment itself on univariate measures of assemblages, but also about possible interaction. The results showed significant differences of log-transformed nematode abundance in factors: treatment, time and treatment x time (Table 2). A Tukey´s posthoc test detected significant differences among three groups of mean values: highest abundance (controls and medium treatment at day 4), intermediate abundance (medium treatment at days 15 and 30, and high treatment at 15), and lowest abundance (high treatment at day 30) (Figure 2).

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The number of species was different among times, but no significant change was observed among treatments, neither in the interaction (Table 2). A Tukey´s post-hoc comparison indicated that samples from day 30 had a significantly lower number of species than at days 4 and 15 (Figure 2). The maturity index showed significant differences in factors time and treatment, but not in the interaction (Table 2). The maturity index was higher in medium and high treatments at day 30, but for the controls no difference was observed (Figure 2).

Multivariate species composition of assemblages

Two different comparisons were carried out on the basis of multivariate composition of assemblages using the ANOSIM procedure: (i) one-way comparison of field versus control samples at several days (five levels: field, 0, 4, 15, 30 days); (ii) two-way crossed comparison of treatments (control, medium, high) and times (4, 15 and 30 days).

The field and control samples showed significant differences (ANOSIM, global test, R = 0.49, p = 0.001; 999 permutations). Most of the pair-wise comparisons between controls showed significant differences in the multivariate structure with R-values greater than 0.5; exception was control 0 versus control 4 (R = 0.22, p = 0.17, 35 perm.). This suggests the existence of a microcosm effect changing the structure of nematode assemblages. However, in the ordination, the pattern of dispersion among

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18 control samples is not so clear, and field samples showed the highest dispersion in the plot (Figure 3).

The SIMPER procedure indicated that the same species contribute to similarity within groups of samples: Terschellingia longicaudata, Metalinhomoeus filiformis, Sabatieria pulchra, and Terschellingia gourbaultae. Differences among groups were accounted by the presence/absence of rare species.

Significant differences were detected among controls at different times (R = 0.47; p = 0.001; 999 perm), indicating the presence of a microcosm effect. The differences among controls at day 0 and controls at subsequent times are mainly related to a decrease of abundance of some species such as Spirinia parasitifera, Metalinhomoeus filiformis and Terschellingia communis (Table 1).

The two-way crossed ANOSIM indicated significant differences among treatments in the multivariate structure of assemblages (R = 0.75; p = 0.001; 999 perm) and among times (R = 0.82; p = 0.001; 999 perm). All pair-wise comparisons (using 999 permutations) were significant at 0.05 probability level, and R-values were higher than 0.5. However, the ordination of the samples (Figure 3) and the absolute values of R statistic suggest an interaction between treatment and time.

In general, a reduction in the abundance of all species at days 15 and 30 was observed, although it was more pronounced in the treatment with high doses of organic matter (Table 1). The dominant species were the same in the field control as in microcosm controls. However, three of the four dominant species responded differently to the treatment over time (Table 1). The abundance of Spirinia parasitifera

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did not change upon addition of organic matter. Terschellingia longicaudata and Sabatieria pulchra showed a similar dominance in controls (days 0 and 4) and field; however, the depletion was stronger for the latter being nearly absent at day 30. T.

longicaudata persisted in all microcosms even in high doses of organic matter. Other dominant species such as Cienfuegia cachoi, Metalinhomoeus filiformis, and

Terschellingia gourbaultae were capable of persisting in treated microcosms, although with decreased abundance in regard to controls.

Trophic structure of assemblages

The classification of nematode species into feeding types allowed testing the effects of organic enrichment on trophic structure of assemblages. The abundance of nonselective deposit feeding nematodes (1B) among field samples and controls at day 0 did not differ significantly. Also the contribution of 1B type among controls at the four times was statistically non-significant (Table 2). However, the percentage of 1B type showed significant differences among treatment, time and interaction treatment x time (Table 2). There was a clear reduction of nematodes belonging to 1B type in microcosms subjected to medium and high doses of organic matter at days 15 and 30 from the onset of the experiment (Figure 4). This was related to the disappearance of Sabatieria pulchra, the most abundant species of feeding type 1B at day 30.

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Discussion

The integration of the results leads us to reject the null hypothesis of no changes in the structure of nematode assemblages subjected to experimental treatments.

Therefore, we will discuss our findings, in the following order, (i) the validity of our experimental setting, (ii) the possible explanations of the obtained results, and (iii) the extrapolation of data from the experiment to nature.

Validity of the experimental setting

The changes in the amount of organic matter in the microcosms suggest some loss from the particulate phyto-detritus pool due to mineralization and leaching as dissolved carbon into overlying water [START_REF] Webb | Response of macro-and meiobenthos from a carbon-poor sand to phytodetrital sedimentation[END_REF]. The concentration of dissolved oxygen in microcosms towards the end of the experiment was close to the recorded data from bottom water in the field; however, higher variability existed in data from the field due to the natural variability of dissolved oxygen and the relatively long period covered (1991 -2001). We consider the experimental set-up as successful in recreating an organically enriched environment although logical differences still remains compared to the field conditions.

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Changes observed in nematode abundance, and also in the multivariate structure of assemblages, indicated the existence of a "microcosm effect". Such an effect was recorded also by [START_REF] Sandulli | Effects of organic enrichment on meiofauna: A laboratory study[END_REF], and Schratzberger and Warwick (1999). The observed changes can be explained by the collection of surface sediment where nematodes are concentrated (thus higher abundance in microcosms) and due to the homogenization of sediment prior to setting of microcosms (thus lower variability in assemblage structure). Only four species out of 36 recorded from the field were not recorded in the microcosms, suggesting a good representation in the experimental conditions of the real diversity in nature.

The experimental set-up probably amplified the effects of treatments because the stagnant conditions avoid the exchange of water and replenishment of sediment (Sundbäck et al., 1990). However, interpretable results can still be obtained from the analysis of these laboratory communities, since important features of communities remain the same between field and control samples.

Possible explanations of the results

Apparently, negative species interactions were not exacerbated in the control microcosms; although evidence of significant interactions (i.e. predation and interference competition) with macrofauna has been recorded in comparable experiments (e.g. [START_REF] Widbom | Response of benthic meiofauna to nutrient enrichment of experimental marine ecosystems[END_REF]. The pool of particulate organic matter

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in sediments was large enough for the maintenance of nematode assemblages in control microcosms along the 32 days of the experiment.

Because the dominance of deposit feeding nematodes in the sediments from Cienfuegos Bay [START_REF] Pérez-García | Spatial distribution of nematode assemblages in Cienfuegos Bay (Caribbean Sea), and their relationships with sedimentary environment[END_REF] and the short generation time of some opportunistic species [START_REF] Heip | The ecology of marine nematodes[END_REF][START_REF] Moens | Temperature and salinity constraints on the life cycle of two brackish-water nematode species[END_REF] a positive response could be expected to the addition of phyto-detritus despite of the general deleterious effects of the organic enrichment. However, a sharp decrease in the nematode abundances was obtained. No evidence of feeding on the "fresh microbial mats" developed in the treated microcosms could be detected in our study in spite of the fact that deposit and epigrowth feeding nematodes can feed successfully on the microbial communities [START_REF] Jensen | Feeding ecology of free-living aquatic nematodes[END_REF]. This suggests that no food limitation occurs in the sediments, i.e., that organic matter was already available to nematode populations.

The increase of the maturity index as a response to organic load has been explained

by [START_REF] Moreno | An assessment of the spatial heterogeneity of environmental disturbance within an enclosed harbour through the analysis of meiofauna and nematode assemblages[END_REF] as the development of an assemblage characterized by species with low metabolic rate and tolerant to pollution. An artifact of the experimental microcosm could be the lack of recruitment of opportunistic species [START_REF] Sandulli | Effects of organic enrichment on meiofauna: A laboratory study[END_REF]. The maturity index is strongly dependent on the species abilities as colonizers, so in this kind of enclosed system its interpretation should be done with caution, since anomalous results can be obtained in comparison to field studies.

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Our results broadly agree with previous experimental studies about the effects of organic enrichment on nematodes and meiofauna despite the difference in habitats and regimes of primary production (Table 3); also results from field sites, reported negative effects of organic enrichment on nematodes (e.g. [START_REF] Mazzola | Fish-farming effects on benthic community structure in coastal sediments: analysis of meiofaunal recovery[END_REF]Sutherland et al., 2007). The mechanisms underlying the observed patterns in the mentioned studies have been the response of nematodes to hypoxic -reduced conditions in sediments and/or the synergistic effects of other stressors (e.g. metals or physical disturbances).

Based on our study, it is not possible to isolate any single factor causing the observed patterns. We would suggest that there were effects of chemical stressors related to reduced conditions in sediments, i.e. hypoxia, hydrogen sulfide and ammonia, which interact in a poorly known way and have deleterious effects on benthic assemblages [START_REF] Gray | Effects of hypoxia and organic enrichment on the coastal marine environment[END_REF]. Particularly, confusion on effects of hypoxia and bacterial byproducts often occurs [START_REF] Gray | Effects of hypoxia and organic enrichment on the coastal marine environment[END_REF]. Hypoxia was present in all treatments and also in the field controls, in similar levels, therefore we hypothesize that toxic bacterial byproducts (ammonia and hydrogen sulfide) would be more important stressors on assemblages than oxygen per se. Nematode assemblages can successfully cope with hypoxic and even temporal anoxic events using behavioral (e.g. migration to "oxygen islands" sensu [START_REF] Reise | A meiofaunal "thiobios" limited to the anaerobic sulfide system of marine sand does not exist[END_REF][START_REF] Wetzel | Oxygen/sulfide regime and nematode fauna associated with Arenicola marina burrows: new insights in the thiobios case[END_REF] stressors in soft bottoms [START_REF] Rzeznik-Orignac | Spatio-temporal structure of the nematode assemblages of the Brouage mudflat (Marennes Oléron, France)[END_REF]Schratzberger et al., 2006;Steyaert et al., 2007). Physiological and behavioral adaptations of the named species to poor-oxygenated environment include a low respiratory rate and slow movements [START_REF] Warwick | Ecological and metabolic studies on free-living marine nematodes from an estuarine mud-flat[END_REF][START_REF] Warwick | Community structure of estuarine meiobenthos[END_REF]. Deposition of insoluble metal sulphides in intracellular inclusions in the species Sabatieria wieseri and Terschellingia longicaudata has been suggested as a mechanism of detoxification of sulfide [START_REF] Nicholas | The mineral composition of intracellular inclusions in nematodes from thiobiotic mangrove mud-flats[END_REF]. We observed granules in the intestine of specimens from Cienfuegos Bay, which would perform this detoxification function but further research is needed to clarify this. Other strategy for detoxification in nematodes inhabiting thiobiotic habitats is a slender body shape which increase the body surface (Jensen, 1987a); however, the body shape was not related to the tolerance of nematodes in our experiment.

Our results suggest that S. pulchra is more sensitive to reduced conditions than Terschellingia longicaudata and Metalinhomoeus filiformis; the other dominant species, Spirinia parasitifera, showed a notable resistance to the effects of treatments. The species-specific response of nematode assemblages to organic enrichment has also been noted by [START_REF] Schratzberger | Nematode community dynamics over an annual production cycle in the central North Sea[END_REF]; it means that not all species populations deplete at the same rate.

A further point to be discussed is concerning to the identity of species. The dominant morpho-species mentioned above are not only tolerant to a variety of disturbances; but rather they have been also recognized as cosmopolitans. However, morphologically cryptic species complexes have been identified for Terschellingia longicaudata [START_REF] Bhadury | Evaluation of combined morphological and molecular techniques for marine nematode (Terschellingia spp.) identification[END_REF] and possibly exist also for the widely distributed

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species Sabatieria pulchra and Spirinia parasitifera. Further research is necessary in order to understand the relationships between the ecological distribution and molecular identity of the nematode species.

Extrapolation to field conditions

Caution should be exercised in the extrapolation of results from laboratory experiments to larger spatial scale in the field because that is one of the main sources of misleading conclusions [START_REF] Carpenter | Microcosm experiments have limited relevance for community and ecosystem ecology[END_REF]. However, the response of infauna to organic enrichment are governed primarily by the adaptations of species, thus extrapolation of responses from small-scale experiments to larger scale can be accepted (Zajac et al., 1998). We infer that in the muddy bottoms of Cienfuegos Bay the nematode assemblages are not food limited. A lack of positive response of nematode assemblages to food supply in organically enriched sediments has also been recorded by [START_REF] Moreno | An assessment of the spatial heterogeneity of environmental disturbance within an enclosed harbour through the analysis of meiofauna and nematode assemblages[END_REF] in a similar environment. Probably, the nematofauna can use the relatively high pool of organic matter already present in the sediment either as dissolved carbon [START_REF] Jensen | Feeding ecology of free-living aquatic nematodes[END_REF] or as particulate carbon [START_REF] Rudnick | Time lags between the deposition and meiobenthic assimilation of phytodetritus[END_REF].

The hypoxic conditions do not always lead to the production and accumulation of ammonium and hydrogen sulfide in water and sediments [START_REF] Gray | Effects of hypoxia and organic enrichment on the coastal marine environment[END_REF]. In Cienfuegos Bay the hydrodynamic regime from waves and tidal currents and the has been observed at the station where sediment was collected in Cienfuegos Bay (M. Armenteros, pers. obs.). However, this phenomenon appeared to be highly patchy probably reflecting the spatially variable deposition of detritus from the water column [START_REF] Levinton | Opposing organizing forces of deposit-feeding marine communities[END_REF].

A detailed study on the distribution of hydrocarbons petroleum-derived in Cienfuegos Bay concluded that the basin is subjected already to moderate/high level of organic pollution (Tolosa et al., 2009). Previous studies about the spatial and temporal distribution of meiofaunal nematodes [START_REF] Armenteros | Biodiversity patterns of freeliving marine nematodes in a tropical bay: Cienfuegos, Caribbean Sea[END_REF] and macrofauna (in preparation) suggest that the muddy bottoms in Cienfuegos Bay may suffer seasonal hypoxia with almost defaunation of macrofauna. This state was already described by [START_REF] Pearson | Macrobenthic succession in relation to organic enrichment and pollution of the marine enviroment[END_REF] regarding to soft bottoms subject to moderate/heavy organic pollution. As our results suggest, even the tolerant nematode species naturally living in these sediments may be depleted if the organic load is considerably increased. We suggest that a further organic enrichment in the muddy areas of Cienfuegos Bay may cause a drastic phase shift towards strongly reduced sediments with plenty of heterotrophic bacteria and relatively few tolerant species of nematodes.

Strong changes can be expected also in benthic metabolism in response to a putative increase of organic deposition [START_REF] Kelly | Experimental studies of the effect of organic deposition on the metabolism of a coastal marine bottom community[END_REF]. (ii) Dominant nematode species showed a different degree of sensitivity to reduced conditions, with Spirinia parasitifera as the least sensitive species, followed by Terschellingia longicaudata, Metalinhomoeus filiformis, and Sabatieria pulchra.

Conclusions

(iii) We predict a phase shift in sedimentary environment towards strongly reduced conditions and a depleted nematofauna if further high load of anthropogenic organic matter is added to these muddy bottoms.

Acknowledgements

  by using oxidation with K 2 Cr 2 0 7 and H 2 SO 4 . Concentration of dissolved oxygen in the water inside the microcosms (1 -2 cm above sediment) was measured with a Hanna DO

  probably contribute to a decrease of the reduced conditions of sediments. Presence of mats (presumably cyanobacteria) on sediments

  Nematode assemblages from naturally enriched sediments suffered deleterious changes when they were exposed to different loads of phyto-detritus in microcosms possibly due to the accumulation of byproducts of bacterial metabolism. Hypoxia per se probably was not the direct cause of depletion in the assemblages.

Figure 1 .

 1 Figure 1. Mean values and SD of abiotic factors measured from a field site and from

Figure 2 .

 2 Figure 2. Univariate measures (mean and SD, n = 4; except for field mean, n = 3) of

Figure 3 .

 3 Figure 3. Multidimensional scaling ordination of samples based on square root

Figure 4 .

 4 Figure 4. Average percentage (n = 4) except for field samples (n = 3) of feeding types

We thank the staff of the Centro de Estudios Ambientales de Cienfuegos, Cuba for their support to this research, particularly Raúl Fernández-Garcés and Carlos Duarte for their help with the field work and Aniel Guillén for measurements of organic matter. Erik Perera and Germán Saavedra provided us facilities at their laboratory for the experimental set-up, and Sergio Hernández helped us with oxygen measurements. We also thank J.I. Hernández for English corrections. M. Armenteros