Francisco Torreira

Martine Adda-Decker

Mirjam Ernestus

The Nijmegen Corpus of Casual French

Keywords: corpus, casual speech, French

This article describes the preparation, recording and orthographic transcription of a new speech corpus, the Nijmegen Corpus of Casual French (NCCFr). The corpus contains a total of over 36 hours of recordings of 46 French speakers engaged in conversations with friends. Casual speech was elicited during three different parts, which together provided around ninety minutes of speech from every pair of speakers. While Parts 1 and 2 did not require participants to perform any specific task, in Part 3 participants negotiated a common answer to general questions about society. Comparisons with the ESTER corpus of journalistic speech show that the two corpora contain speech of considerably different registers. A number of indicators of casualness, including swear words, casual words, verlan, disfluencies and word repetitions, are more frequent in the NCCFr than in the ESTER corpus, while the use of double negation, an indicator of formal speech, is less frequent. In general, these estimates of casualness are constant through the three parts of the recording sessions and across speakers. Based on these facts, we conclude that our corpus is a rich resource of highly casual speech, and that it can be effectively exploited by researchers in language science and technology.

Introduction

French is one of the best documented languages in the world. Accordingly, researchers interested in spoken French have a choice among several speech corpora for their studies (e.g. ESTER [START_REF] Galliano | ESTER Phase II Evaluation Campaign for the Rich Transcription of French Broadcast Newshase II Evaluation Campaign for the Rich Transcription of French Broadcast News[END_REF], PFC [START_REF] Durand | Un corpus numérisé pour la phonologie du français[END_REF], see http://catalog.elra.info/ for more). However, no existing corpus of French contains the large amounts of casual speech necessary for detailed research on the characteristics of this register, including inter-and intra-speaker variability. This article describes a new corpus of European French that fills this gap.

The specific characteristics of a given corpus present advantages and disadvantages depending on the researcher's goals. For instance, the ESTER corpus, with around 90 hours of journalistic recordings, mainly comprises prepared speech, either planned or read, from several European and North-African French-speaking radio stations. It is a valuable source for researchers interested in journalistic speech covering a broad range of topics with a huge lexical variety, produced by a large population of professional and occasionally intervening speakers in various audio conditions.

The PFC (Phonologie du Français Contemporain) corpus, which is still under development, contains recordings of speakers from diverse geographic and social backgrounds in the French-speaking world. In the future, it will consist of a total of several hundred hours of speech of different registers, thus providing a reference corpus for linguists who are interested in social and regional language variation. Every informant in the PFC corpus contributes an average of 20 minutes of speech, including both read speech and conversations with the interviewer. The conversations differ in their degree of casualness, as the interviewers and informants are not all on familiar terms. So far, only a relatively small percentage of these data has been orthographically transcribed. The recordings, which are field data collections, are of variable acoustic quality and hence not always appropriate for detailed acoustic analysis.

The motivation behind the creation of the Nijmegen Corpus of Casual French (NCCFr from now on) was to provide large amounts of high-quality recordings of casual speech suitable for phonetic analysis. The uniqueness of our corpus can be characterized as follows:

• It contains large amounts of casual speech. All of the recorded speech has been orthographically transcribed.

• It contains high-quality recordings captured with head-mounted microphones in a sound-attenuated room.

• It contains speech from 46 speakers sharing the same geographic and educational background. This allows researchers to study inter-speaker variation in a corpus controlled in terms of regional and social variation.

• It contains large amounts of data for every speaker (around 90 minutes of recorded conversation for every pair of speakers). This allows researchers to study within-speaker variability.

• It contains audio as well as video data, which can be used to study facial and body gestures during verbal communication.

Information about how to obtain a copy of the corpus can be found online at http://mirjamernestus.ruhosting.nl/Ernestus/NCCFr.

The present article provides a detailed description of the creation and characteristics of our corpus (Sections 2 and 3). In Section 4 we provide evidence of the casual register of the speech contained in the corpus by comparing the NCCFr and the ESTER corpus in terms of several uncontroversial indicators of casualness (e.g. lexical items sensitive to register, double negation, disfluencies). We also assess the variability of these indicators throughout the different parts of the recordings (see below for details) and across speakers.

Corpus creation

Participants

The corpus creation was initiated in November 2007. Twenty-three confederates were recruited at the University of Paris 3 Sorbonne Nouvelle, either by e-mail or personally. These confederates were briefly interviewed and asked to find two friends willing to participate in recordings of natural conversations. These friends will be referred to as speakers from now on. Every recording consists of a conversation among these three participants: a confederate and two speakers. All participants complied with the following conditions:

• They knew the two other participants in the recording well.

• They were of the same sex as the two other participants in the recording.

• They had completed the secondary education cycle in France.

• They had been raised in Central/Northern France.

• They reported not suffering from any pathology related to speech or hearing.

In total there were 46 speakers (24 female and 22 male). Thirty-four speakers came from the Paris region. The remaining 12 came from other regions in Central and Northern France. Except for two female speakers in their fifties, all speakers were university students aged between 18 and 27. The gender, age and regional background of each speaker is provided in Table 1.

Recording set-up

The recording room was sound-attenuated and had an approximate size of 4 x 3 m. The participants sat on chairs around a table placed in the middle of the room. The confederate always sat on the south side of the table, while the speakers occupied the chairs on the north and west sides. Figure 1 shows the layout of the recording room.

For technical reasons, only two participants could be recorded. Given this limitation, we decided to dispense with the speech of the confederates, who, contrary to the speakers, were not naive about our goals and procedures. However, the confederates also wore a microphone in order to reinforce the speakers' impression that they did not have a special role in the conversation. Speakers were recorded in separate audio channels. The recording equipment consisted of an Edirol R-09 solid-state stereo recorder, Samson QV headmounted unidirectional microphones and a stereo microphone preamplifier. Microphones were placed at an average distance of 5 cm from the left corner of the speakers' lips. The sampling rate used was 48 KHz, while quantization was set to 32 bits.

The conversations were filmed using a Canon XM2 Mini-DV video camera. The camera was placed on a tripod in a corner of the recording room as shown in Figure 1. The positioning of the camera allowed us to film the two speakers, but not the confederate. This is illustrated in Figure 2. Since awareness of being filmed could compromise the casualness of the conversations, we tried to make the speakers believe that the camera was turned off during the recordings. As a first step, a small piece of duck tape was placed on each of its lights. Additionally, an unplugged cable was left hanging from the camera in order to reinforce the impression that it was turned off. It should also be noted that there were several other objects in the room, including a desktop computer, several loudspeakers and other audio equipment. Our camera may have then appeared to be merely another piece of unused electronic equipment in the recording room.

Speaker

Recording procedure

The recording procedure was established after a series of pilot recordings was run. During these pilot recordings, we noticed that it was difficult to obtain casual speech for long periods in the absence of any explicit task or changes in the recording setting. We also noticed that the speech recorded during the initial moments of the session was often far from casual. In order to obtain lively casual speech from our speakers for 90 minutes, we divided the session into three different parts. In the first part, in order to elicit highly casual speech right from the beginning of the recording session, the two speakers were unexpectedly left alone on the false grounds that the confederate's microphone was defective. In the second part, the confederate returned to the booth and all participants engaged in free conversation. In the third part, participants were explicitly asked to perform a communicative activity in which they had to express and negotiate their views on real issues.

We now describe the recording preparations and each of these three parts in more detail. The recordings were conducted by the first author (FT from now on). FT is not a native speaker of French, but is highly proficient in this language.

Preparations: Confederates arrived at the Institut de Linguistique et Phonétique Générales et Appliquées (ILPGA) thirty minutes earlier than their friends. At this time, FT informed the confederates that it was their task to elicit natural speech from their friends, by raising familiar topics whenever the conversation seemed to approach a dead end. In order to maximize the amount of recorded speech from the speakers, confederates were instructed to try not to monopolize the conversations. The confederates were also informed that the conversations would be filmed, and where to sit so that only the other participants would appear in the film. They were asked not to unveil any of these details to their friends until the end of the recording. Finally, they were briefly instructed about the activity planned for the third part of the recording (see below for details). Moreover, they were asked to inform their friends that the instructions for this activity were the only reason for coming to the ILPGA earlier than them. At the end of the instruction section, confederates were asked to wait for the other participants in the entrance hall of the ILPGA.

At the time of the appointment, FT met the three participants at the entrance hall and asked them to wait while he got the keys of the recording room. He then returned to the recording room, started the video recording, turned off the lights and locked the door. Back at the entrance hall, he invited the participants to follow him to the recording room, making sure that the confederate would be the first person to enter in order to prevent the other participants from taking the confederate's seat. Once in the room, participants were asked to stay seated and not to touch their microphones or play with any other object (e.g. keys, watch) during the recording.

Part 1 : After adjusting the recording volume during the first two minutes of the conversation, FT entered the recording room and informed the participants that the confederate's microphone was not working properly. He then asked the confederate to come out of the room in order to test a new microphone. At this moment, the speakers left in the room did not know with certainty whether they were being recorded. It was precisely then that the recording was started. In our opinion, this situation elicited very natural speech from the beginning of the recording (see Section 4 below).

Part 2 : After a period of ten to thirty minutes depending on the liveliness of the conversation, confederates were asked to go back into the room and join their friends. The conversation then held by the three friends constituted the second part of the recordings. The topics addressed during this part were usually a follow-up to those addressed in the first part, but with the novelty of a new participant. Among the conversation topics addressed by the speakers during this part were their college exams, the ongoing strike, parties, and travel plans. No instructions were provided about the topics to be discussed during this part of the conversation.

Part 3 : After a period of thirty to forty minutes, FT entered the room and provided the participants with a sheet of paper describing the activity for the remaining part of the recording session. The participants were asked to choose at least five questions about political and social issues from a list (see Appendix), and then negotiate a unique answer for every question. In order to encourage them to negotiate rather than just discuss their views, we informed that they would have to write down their answers at the end of the recording session. The average duration of this part was around forty minutes.

At the end of the recording, we revealed our procedures to the participants and paid 30 euros to each of the speakers and 45 euros to the confederate as a compensation for their time. We then handed them a consent form and explained to them that they should only sign it if they fully agreed with its content, and that refusing to sign it would not cause them any trouble. Furthermore, we offered participants the opportunity to add restrictions to the distribution of the corpus. All of the participants signed the consent form. Two participants required that their recordings be not distributed online.

Orthographic transcription 2.4.1. Transcription protocol

The corpus was orthographically transcribed by two professional transcribers using the Transcriber software [START_REF] Barras | Transcriber: development and use of a tool for assisting speech corpora production[END_REF] following transcription guidelines developed at LIMSI (Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur) in line with the French GARS conventions [START_REF] Blanche-Benveniste | Le français parlé, études grammaticales[END_REF]. The transcribers were recruited on the basis of earlier transcription experience in several French and European projects with interactive spontaneous speech (e.g. the ESLO/ESLO2 project [START_REF] Serpollet | A Large Reference Corpus for Spoken French: ESLO 1 and 2 and Its Variations[END_REF], the SNCF Recital project (see http://recherche. sncf.com/uk/projets/uk_recital.html), the Arise project [START_REF] Lamel | The LIMSI ARISE System[END_REF]).

The speech of each speaker was orthographically transcribed in a separate annotation file using mono-channel audio streams. The audio stream was manually segmented, separately for each speaker, into small chunks of a few seconds. Most chunks contain either speech or long silent pauses, but some consist entirely of speaker noises (e.g. laughter). The transcription guidelines stated that speech in a chunk should have a clear degree of syntactic and semantic coherence and contain no long stretches of silence. In total, over 83 000 chunks were marked, with an average duration of 3.12 seconds.

Transcribers were asked to provide standard orthographic transcriptions following the French Robert dictionary (Le Petit Robert, 2007) wherever possible. Hence all pronunciation variants of the same word (e.g. those resulting from the addition of final schwas [START_REF] Fagyal | Le retour du e final en français parisien: changement phonétique conditionné par la prosodie[END_REF])) were annotated with the same orthographic form. However, not all speech events can be handled by a normative written language dictionary. Transcription problems arise for mispronounced words, words with an uncertain spelling (proper names, neologisms, onomatopoeia, slang...) and for unintelligible parts. The guidelines provided a series of special symbol affixes to annotate these speech events. Although the Transcriber tool proposes a list of specific noise labels, our transcribers were encouraged to fall back to a generic noise label [b] for all noises except for frequent and easily identifiable noises such as respiration and laughter. The label [r] was used for respiration noises and the label [rire] ('laughter') for laughter. These three labels (i.e. [rire], [r] and [b] ) account for 87% of all noise labels in the NCCFr corpus.

Transcribers were asked to restore common elisions and contractions to their full orthographic forms. For instance, the guidelines specified that expressions characteristic of casual speech such as y a 'there is' or j'sais pas 'I don't know' should be transcribed in their full forms as il y a and je sais pas. The reason for requiring standard full forms is that providing detailed transcriptions is very time consuming and error prone [START_REF] Ernestus | Voice assimilation and segment reduction in Dutch: A corpus-based study of the phonology-phonetics interface[END_REF]. Moreover, non-standard transcriptions make searching for particular lexical items difficult. However, one exception was made to this rule: the guidelines recommended that cases of obvious ne deletion (in the French double negations, such as ne . . . pas and ne . . . plus, see Section 4.4) should not be restored in the transcription. In case of doubt the ne particle should be transcribed.

Figure 3 shows an excerpt of a conversation with transcribed chunks of various relatively small lengths. To restore the conversation structure, the individual speaker transcription streams have been merged in the figure. The produced transcription files are in a machine readable XML mark-up language format, and are also available in Praat TextGrid format [START_REF] Boersma | Praat: doing phonetics by computer (version 5.1.18)[END_REF].

Transcription quality check

The quality and consistency of manual transcripts can be assessed via automatic alignment with the acoustic signal: successfully aligned parts of the corpus guarantee a good fit between the manual transcripts and the recorded speech signal. We followed this approach in order to check the quality of our transcriptions. We first created a pronunciation dictionary containing all words in the corpus and their canonical pronunciations, which were then used in an automatic alignment with the speech signal.

The corpus contains 15 919 distinct word types, including over 10% of word fragment types (truncated pronunciations). About 14 000 entries already existed in the LIMSI transcription system vocabulary (which comprises around 200 000 entries). The additional 2 000 items were checked and added to the system vocabulary with appropriate pronunciations. Among these new entries, around 1 000 correspond to word fragment types. The other entries include verlan words, interjections, onomatopeia and apocopes.

We then segmented the audio stream into words given the orthographic transcription and the pronunciation dictionary using the LIMSI recognition system (Gauvin et al., 2005). If a given transcription does not fit with the corresponding audio chunk, the alignment system will tend to reject the chunk without producing the alignment. The quality of the transcriptions can therefore be measured via chunk rejection rates. Only 41 speech chunks out of around 83 000 were rejected, corresponding to less than three minutes of speech. This strongly suggests that the orthographic transcription is of a high quality.

Transcribers often feel uncomfortable with the transcription rule prescribing the restoration of omitted and contracted words. For this reason, we also checked the extent to which the transcribers followed this rule by manually examining the two most common types of restoration: (1) il y a 'there is' and morphologically-related word sequences (e.g. il y avait 'there was'), and (2) the pronoun tu 'you' followed by a verb starting with an /a/ vowel (e.g. tu as 'you have'), in which the tu subject pronoun tends to be pronounced as [t], becoming a homophone with the object pronoun t'. Whereas for il y a both transcribers observed the rule in almost 100% of the cases, instances of tu followed by an /a/-initial verb were only restored in less than a third of the occurrences (842 out of 2 316). A possible explanation for this tendency might be that t' exists as an orthographically correct form for the object pronoun: il t'a vu ('he has seen you') is perfectly correct, but t'as vu le film ('you have watched the film') is not correct in written French. The manual transcripts have been updated to restore these elisions and contractions.

Corpus contents

The NCCFr consists of 23 recordings involving a total of 69 participants (23 confederates and 46 speakers). As explained in Section 2.2, only the speech of the two speakers was recorded. In most cases, however, the speech of the confederate was captured by the speakers' microphones and can be well interpreted from the speakers' recordings.

Table 3 shows the amount of speech contained in the corpus, both in total and averaged by recording. Effective speech includes all stretches of the recording containing speech by one of the two speakers, or by both at the same time (overlapping speech). This was calculated by adding the durations of all chunks in the transcriptions of each speaker containing at least one lexical item and subtracting the duration of overlapping speech. Overlapping speech was calculated by summing up the durations of stretches of conversation where both speakers spoke simultaneously. Overlapping speech involving a confederate and a speaker could not be estimated, since the speech of the former was not transcribed. Non-effective-speech includes stretches of conversation not containing effective speech by any of the two speakers. It does not only include silence, laughter and other speaker noises, but also nonoverlapping speech from confederates. Overall, the corpus contains over 36 hours of recorded conversations, with over 26 hours of effective speech, over 3 hours of overlapping speech and around ten hours of non-effective-speech including silence and speech from confederates. The considerable amount of overlapping speech indicates that the corpus contains highly interactive speech [START_REF] Schegloff | Overlapping talk and the organization of turn-taking for conversation[END_REF].

Table 4 shows the total and average durations of each of the three parts of the recorded conversations, along with their average amounts of effective speech and non-effective-speech. Notice that non-effective speech in Part 1 refers to stretches of the conversations containing silence, laughter or other speaker noises, while non-efective-speech in Parts 2 and 3 also contains speech turns from confederates (remember that confederates were not recorded and only participated in Parts 2 and 3). It can be seen from this table that Parts 2 and 3 appear very similar in the percentages of effective speech that they contain, and that the inclusion of a confederate in these two parts leads to a similar decrease in effective speech with respect to Part 1. This was confirmed by a series of two-tailed t-tests showing that the percentage of effective speech in Part 1 differed significantly from those of Parts 2 (t = 3.06, p < .005) and 3 (t = 3.6, p < .001), but it did not differ between the Total Average Effective Speech Non-effective-speech Part 1 7h 32' 07" 19' 39" 16' 40" (85%) 2' 58" (15%) Part 2 12h 52' 11" 33' 34" 23' 22" (70%) 10' 13" (30%) Part 3 15h 48' 09" 41' 13" 28' 05" (69%) 13' 08" (31%)

Table 4: Duration of each recording part in the corpus and on average per recording, along with average amounts of effective speech and non-effective-speech for each part.

Non-effective-speech includes speech from confederates.

latter two (t = 0.33, p = .74).

The right-most column in Table 1 shows the total amount of recorded speech for every speaker. These amounts ranged from roughly twenty to sixty minutes, with an average of 38 minutes and 27 seconds and a standard deviation of 10 minutes.

Assessing casualness

In spite of our efforts to create an informal atmosphere during the recording sessions (for instance by inviting groups of friends), it is possible that speakers felt intimidated or inhibited by the awareness of being recorded. Therefore, in the absence of any proof to the contrary, the casualness of the speech contained in our corpus may be legitimately questioned. In this section we examine several indicators of spontaneity and casualness that can be extracted automatically from an orthographic transcription, and compare their values in our corpus and in the ESTER corpus of journalistic speech.

Disfluency words

We believe that genuine casual speech should be, among other things, unprepared and spontaneous. For this reason, we first quantify the incidence of disfluencies by identifying transcribed filled pauses (e.g. euh, hum, ben), which are known to be more frequent in spontaneous speech than in more careful and formal styles (e.g. [START_REF] Clark | Repeating words in spontaneous speech[END_REF][START_REF] Shriberg | To 'errrr' is human: ecology and acoustics of speech disfluencies[END_REF]Tree, 1995;[START_REF] Clark | Using Language[END_REF]. Following [START_REF] Jousse | Caractérisation et détection de parole spontanée dans de larges collections de documents audio[END_REF], we measured the frequencies of the most common word types used by transcribers to annotate filled pauses and hesitations, that is ben, euh and hum. These words will be referred to as disfluency words from now on. annotation of filled pauses, and we have not noticed salient differences in the transcription of filled pauses between the two corpora. Therefore, we assumed that the transcribers of both corpora annotated filled pauses with the same accuracy and following similar principles. The first three lines in Table 5 suggest that the NCCFr corpus contains considerably more filled pauses and hesitations than the ESTER corpus, and thus confirm our expectations.

Word repetitions

We also counted the number of word bigrams and trigrams consisting of identical words occurring in each corpus. Following [START_REF] Jousse | Caractérisation et détection de parole spontanée dans de larges collections de documents audio[END_REF], we assume that word repetitions mostly result from breakdowns during online speech planning and are therefore characteristic of spontaneous speech. The word bigrams vous vous and nous nous, which form grammatical sequences (e.g. vous vous voyez 'you see yourself', nous nous connaissons 'we know each other'), were excluded from the repetition bigram count. It should be also noticed that repetitions can be used as a stylistic device to intensify the meaning of a word (e.g. trop, trop 'very, too much', partout, partout, partout 'everywhere'), or as a backchannel utterance (e.g. oui, oui... 'yes'). Importantly, however, the latter two types of word repetitions are also characteristic of casual speech. We therefore did not exclude these sequences from our counts. The last two rows in Table 5 show that sequences of repeated words are more frequent in our corpus than in the ESTER corpus. Again, these numbers suggest that the NCCFr contains more spontaneous speech than the ESTER corpus.

Lexical items

An obvious way of assessing the casualness of a corpus is to check the extent to which it contains lexical items typical of casual speech. In order to do this, we examined the frequency of occurrence of swear words and verlan (see below for details), and also compared the use of informal and formal words with a similar meaning. We determined which casual words and swear words would be considered for analysis by asking four native speakers of French to provide two lists. The first list should contain a subjective choice of the ten most common French swear words, while the second should consist of formal and informal content words having similar meanings (e.g. chose / truc 'thing'). The lists of swear words were very similar, as six terms were present in all of them. On the other hand, only two pairs of formal and informal words were present in all of the second lists.

From the first lists, we selected for analysis those swear words that occurred at least ten times in either the NCCFr or the ESTER corpus. The threshold was set at ten so that interpretable comparisons could be made (comparisons of very low frequencies, say three and one, would have been hard to interpret). This threshold also allowed for a reasonable number of comparisons between the corpora. Table 6 shows the frequency of occurrence for each of these swear words in both corpora. We were surprised to find out that swear words were highly frequent in our corpus (e.g. on average, putain occurs roughly once every six minutes of conversation). In our view, such a frequent usage of swear words constitutes strong evidence of the casual speech register of our recordings [START_REF] Eggins | Analysing Casual Conversation[END_REF].

From the second lists, we only retained those pairs of which each member appeared at least ten times in one of the two corpora. When two pairs shared the same formal word, they were reorganized into a triplet (e.g. formal: garçon; informal: mec, gars 'lad'). We added two pairs of function words (i.e. cela / ça and oui / ouais) which in our opinion are very good indicators of register as well. Notice that our subjects had been asked to provide pairs of content words, and had therefore not mentioned any of these two function words. Table 7 shows the frequencies of occurrence of these words in both corpora. This table shows that all casual words are more frequent in the NCCFr than in the ESTER corpus. Moreover, some casual words in our corpus are more frequent than their more formal synonyms (e.g. ça, ouais, truc and mec occur more often than cela, oui, chose and garçon). So far, these facts lead us to conclude that our speakers did not generally aim at a formal register of speech during the conversations.

NCCFr ESTER chier

. 23 (110) .00 (0) con .21 (102) .00 (2) cul .06 (31) .00 (0) merde .32 (152) .00 (1) putain .79 (370) .00 (0) We also checked the usage of verlan in our corpus. Verlan is a language game typically consisting in the inversion of segments and syllables in a word, often accompanied by other changes, affecting for instance the quality of vowels. The name verlan /vEKlÃ/ itself is an example of such inversion, as it comes from l'envers /lÃvEK/ 'the inverse'. Importantly for our purposes, the use of verlan can be used as an indicator of casualness, as it is common in slang and youth language (Valdman, 2000). Verlan word types used in the NCCFr were identified on the basis of the prefix ˆˆin the orthographic transcriptions (see Section 2.4.1). There was a total of 14 word types and 232 tokens of verlan words. The most frequent ones (n > 10) are listed in Table 8 with their number of occurrences. It should be noticed that none of these words appeared in the ESTER corpus. The occurrence of verlan in the NCCFr corpus constitutes further evidence that it contains highly casual speech.

Double negation

Negation in French requires the use of two grammatical particles, the first of which must be ne (or its contracted form n' before a vowel). For instance, in the utterance Je ne veux pas dormir 'I don't want to sleep', the negation particle pas appears after the verb veux, while the negative particle ne precedes it. In the same way, the word ne occurs along other negative particles such as rien 'nothing', jamais 'never' or aucun 'any'. Importantly for our purposes, casual French is characterized by the frequent elision of the particle ne [START_REF] Coveney | Variability in Spoken French. A Sociolingistic Study of Interrogation and Negation[END_REF][START_REF] Armstrong | The influence of linguistic and social factors on the recent decline of French ne[END_REF]. For instance, in informal settings Je veux pas 'I don't want' is often heard instead of Je ne veux pas.

Word

NCCFr ESTER Gloss ami(s)

.13 (65) .14 (94) pote(s)

. We investigated how often negation occurred in both corpora without the first element ne. Our goal was to identify rough differences in the use of double negation between the two corpora, rather than make our estimates of double negation as accurate as possible. Therefore, instead of checking every instance of double negation manually, we automatically extracted the frequency of ne in each corpus and compared these with the automatically extracted frequencies of negation particles pas 'not', rien 'nothing', jamais 'never' and aucun(e) 'any'. Negation particles whose orthographical form may also occur with other meanings (e.g. personne 'person' and 'nobody'; que 'that' and 'only') were not examined. An exception was made for pas, since it occurs far more often as a negative particle ('not') than as a noun ('step').

Table 9 shows the frequencies of occurrence of ne and of other negation particles in both the NCCFr and the ESTER corpus. An estimate of the percentage of double negation usage was computed by dividing the number of ne occurrences by the total number of occurrences of the other negation particles. As expected, double negation turned out to be very infrequent in our corpus (6.7%), suggesting that the register of the recorded conversations was highly casual and informal. On the other hand, the ESTER corpus exhibits a high rate of double negation (89%), confirming that a more formal register was used in the journalistic speech materials.

Homogeneity across parts

Tables 45678show that the NCCFr contains highly casual speech in spite of the fact that speakers were conscious of being recorded. Since the recordings consisted of three different parts, we investigated whether these parts differed in their degree of casualness. Part 3 contained less casual speech, since it involved discussing a number of prescribed topics. We therefore examined the distribution of lexical and disfluency indicators across the different parts.

In previous subsections in which we compared the NCCFr and the ESTER corpus, we examined indicators that occurred at least ten times in one of the two corpora. The same restriction cannot be applied to a comparison of the three parts in our recordings, since frequencies slightly above ten are too low to obtain interpretable differences in this case (e.g. an indicator with four occurrences in Part 1, two occurrences in Part 2 and six occurrences in Part 3 does not provide information about whether the three parts are different). We therefore decided to investigate only those indicators that appeared in our corpus at least 100 times (chier, con, merde, putain, cela / ça, garçon(s) / gars / mec(s), oui / ouais, très / vachement, ben, euh, hum, word repetitions). The percentage of double negation, which could be reasonably well estimated for each part, was also included in this comparison.

Table 10 shows our findings. The usage of swear words and casual words does not exhibit significant differences across parts. The only exception perhaps is the word garçon, which was over twenty times more frequent in Part 3 than in Parts 1 and 2 combined. This increase may be explained by the fact that one of the questions included in the activity performed during Part 3 explicitly mentioned the word garçon (Pourquoi les garçons et les filles ne sont-ils pas éduqués de la même manière? 'Why aren't boys and girls raised in the same way?'). As in the case of swear words and casual words, word repetitions and double negation appear to be equally distributed across the three parts.

We tested for systematic differences in the frequency of casualness indicators across the three parts by fitting a mixed-effects linear model with log normalized frequency as the predicted variable, recording part as predictor and casualness indicator (e.g. ça, truc(s), chier, euh) as random factor. Since double negation was estimated as a percentage, it was not included in the analysis. From the pairs and triplets of formal and informal words, only informal words were retained for analysis. No statistical effect of recording part on log normalized frequency was identified (F (2, 36) = 0.79, p > .1), suggesting that parts did not differ systematically in their degree of casualness.

Homogeneity across speakers

We finally assessed the distribution of indicators of casual speech across speakers. Our goal was to check if the casual characteristics of the NCCFr revealed by our previous analyses were due only to a small group of speakers. Figures 4 and5 show kernel density plots 1 of within-speaker estimates for every indicator of casualness.

The top left panel of Figure 4 shows that a few speakers used more swear words than the rest, but overall the distribution of swear word frequencies is skewed only very slightly. Importantly, only five out of the 46 speakers did not pronounce any of the five swear words we selected for analysis.

Casual word use (use of the casual members of casual/non-casual word pairs) was estimated following a procedure different from the one used in the previous section. This time we added up the total number of tokens of casual and formal content words listed in Table 7 pronounced by each speaker, and then calculated the percentage of casual words over this total. The reason for doing this was that, in order to plot the data, we needed a single score for each speaker, rather than multiple scores corresponding to different formal/informal pairs and triplets. Function words (i.e. oui / ouais and cela / ça) were considered separately from other casual words and are 1 Kernel density plots display the estimated probability density function (y-axis) of a continuous random variable (x-axis), and have a purpose similar to that of histograms. However, whereas histograms group observations into a discrete number of bins, kernel density plots provide a continuous estimate of the distribution of a variable. The kernel density plots shown here were computed using the density function in the statistical software R with default parameters. For further details, see the R manual (R Development Core Team, 2008) and [START_REF] Sarkar | Lattice: Multivariate Data Visualization with R[END_REF]. not included in the figure, since they were overwhelmingly more frequent than content words and would have had too big an impact on the measure. Casual word use ranged from 0% to 92%. Only 8 speakers did not pronounce any of the casual words considered for analysis and therefore scored very low on this indicator of casualness. With respect to the function words, the word ça was used by all speakers, while the few occurrences (n = 6) of the more formal variant cela were shared by three speakers. The word ouais showed more variability, with 32 speakers showing a use between 30% to 95%, with a mean of 69.8%, and 14 speakers not using ouais at all. Interestingly, these 14 speakers used oui as often as the other participants. Verlan was used by 60% of the speakers. The other indicators also showed that most speakers used casual speech. Double negation use was generally low across speakers, as expected from our previous analyses, with only a small number of significantly deviant speakers: three speakers displayed double negation rates between 15% and 30%, and two showed surprisingly high rates (38.9% and 55.8%). Furthermore, all speakers exhibited at least five repetition bigrams per thousand words, and disfluency words were used by all except two speakers.

We finally checked whether speakers with low scores for a specific indicator of casualness also exhibited low scores for other indicators. This appeared to be the case only for one speaker who pronounced zero casual words, two swear words and displayed a high percentage of double negations (55.88%). Notice, however, that this speaker's double negation percentage was still much lower than that found in the ESTER corpus (89%). All other speakers who happened to display a low score for one indicator did not have particularly low scores for the other indicators. We therefore conclude that, in spite of individual differences in terms of specific indicators, the vast majority of speakers produced highly casual speech.

Discussion

In the previous sections we have described a new speech corpus, the Nijmegen Corpus of Casual French. The corpus contains a total of over 36 hours of orthographically-transcribed recordings involving 23 pairs of speakers with similar social and geographical backgrounds. These numbers should make it possible to model and study in detail the characteristics of spontaneous speech and inter-and intra-speaker variation. Our corpus can also be used to study gender differences, since gender was explicitly controlled for in our selection of speakers.

Our comparison of the NCCFr and the ESTER corpus of journalistic speech in terms of several indicators of casualness shows that our new corpus contains speech of a more casual nature. The high frequencies of swear words, casual words, verlan, disfluency words and word repetitions along with the low usage of double negation suggests that speakers generally aimed at a casual speech register in spite of the awareness of being recorded. The analyses in Sections 4.5 and 4.6 further suggest that this casual register was present throughout the different parts of each recording and in all speakers (excepting perhaps one male speaker). The NCCFr can therefore be used as a resource to investigate all sorts of linguistic phenomena related to casual speech, such as speech reduction [START_REF] Ernestus | Voice assimilation and segment reduction in Dutch: A corpus-based study of the phonology-phonetics interface[END_REF][START_REF] Johnson | Massive reduction in conversational American English[END_REF], disfluencies [START_REF] Clark | Repeating words in spontaneous speech[END_REF], or the prosodic and syntactic characteristics of Every recording session was divided into three parts so that natural speech could be for long periods of time. A welcome consequence of this division is that specific parts of the corpus can be used to study specific phenomena. For instance, Part 1, in which speakers were left alone unaware of being recorded, is a good resource for researchers interested in talker interaction, turn-taking and conversation analysis in general (e.g. [START_REF] Nouveau | Variable domains and variable relevance: interpreting phonetic exponents[END_REF][START_REF] Local | Phonetic detail and the organisation of talk-in-interaction[END_REF][START_REF] Plug | From words to actions: the phonetics of eigenlijk in two communicative contexts[END_REF]. Parts 2 and 3 can also be used for the same purposes, but the presence of a confederate, whose speech was not directly recorded, may complicate the study of these subjects. Part 3, in which participants were asked to choose and discuss specific topics, can be used to study argumentation and strategies used by speakers to convince their interlocutors. It can also be used to study the phonetics of specific content words, since many groups of speakers produced the same content words while discussing the same questions during Part 3. The description of the corpus provided in this article should allow researchers to judge which part best suits their purposes.

Finally, we hope that the corpus will be of use for researchers in different fields of speech technology. For instance, given the challenge that spontaneous speech presents to ASR systems [START_REF] Moore | A comparison of the data requirements of automatic speech recognition systems and human listeners[END_REF][START_REF] Moore | Cognitive informatics: The future of spoken language processing[END_REF], annotated resources such as the NCCFr may help to improve current technology.

In conclusion, the Nijmegen Corpus of Casual French is a rich source of high-quality speech data that will help researchers to study spontaneous speech from many perspectives.

Figure 2 :

 2 Figure 2: Snapshot extracted from one of the films in the corpus.

Figure 3 :

 3 Figure 3: Manual transcription sample illustrating the segmentation and transcription steps. The two speaker streams are merged to restore the conversation structure.

Figure 4 :

 4 Figure 4: Kernel density plots of within-speaker frequencies of swear words (putain, merde, chier, con and cul ) and verlan (normalized per thousand words), and percentages of casual content words and of double negation. Circles represent individual speakers. Except for double negation, higher values indicate higher degrees of casualness. NORM. # stands for normalized number

Figure 5 :

 5 Figure 5: Kernel density plots of within-speaker frequencies of disfluency words (euh, hum, ben) and repetition bigrams and trigrams (normalized per thousand words). Circles represent individual speakers. NORM. # stands for normalized number

Table 1 :

 1 Gender, age, regional background (region of longest residence) and total amount of recorded speech (minutes:seconds) for every speaker in the corpus. Speaker code: M = male, F = female; L = left channel, R= right channel. The number in the speaker code indicates the recording number.

	Unused	Speaker	Unused
	equipment		equipment
			Speaker
		Table
			Door
		Confederate
	Camera
	Figure 1: Layout of the recording room

Table 2 :

 2 Transcription symbols.

  Table2lists the most important ones. Notice that the same affix was used for proper names with an uncertain spelling and verlan words (for an explanation of the term verlan see Section 4.3 below). Since proper names always start with a capital letter, this convention does not lead to confusion between these two types of words.

Table 3 :

 3 Amounts of effective speech, overlapping speech and non-effective-speech in the corpus, along with averages per recording, plus standard deviations and ranges. Noneffective-speech includes speech from confederates.

  The transcription guidelines of the NCCFr and the ESTER corpus do not differ in how they specify the

		NCCFr	ESTER
	ben	2.77 (1 292) .26	(176)
	euh	24.77 (11 546) 8.14 (5 452)
	hum	9.42 (4 391) .11	(73)
	Rep. bigrams 12.94 (6 034) 3.76 (2 522)
	Rep. trigrams 1.74	(815) .49	(333)

Table 5 :

 5 Frequencies of euh, hum, ben and repetition bigrams and trigrams in the two corpora per thousand words. Numbers within brackets indicate absolute numbers of occurrences.

Table 6 :

 6 Frequencies of occurrence per thousand words for five swear words in the NCCFr and the ESTER corpus. Numbers within brackets indicate absolute numbers of occurrences.

Table 7 :

 7 Frequencies per thousand words for casual (in bold) words and their standard variants in the two corpora. Numbers in brackets indicate absolute numbers of occurrences.

		16	(87) .00	(1)	friend(s)
	argent tune(s)	.21 .05	(98) .11 (29) .00	(74) (0)	money
	cela ça	.01 17.75 (8 276) 1.72 (1 152) (6) .55 (369)	that (Pron.)
	chose(s) truc(s)	1.25 3.01 (1 400) .00 (587) .53	(358) (1)	thing(s)
	fille nana(s)	1.13 .11	(531) .07 (52) .00	(51) (0)	girl(s)
	fou dingue	.15 .08	(71) .02 (39) .00	(18) (2)	crazy
	garçon(s)	.58	(271) .02	(20)
	gars	.48	(226) .00	(2)	lad(s)
	mec(s)	.67	(315) .00	(2)
	livre(s) bouquin(s)	.05 .01	(27) .14 (48) .00	(97) (2)	book(s) (N)
	mange(r) bouffe(r)	.17 .08	(81) .03 (41) .00	(24) (3)	eat(s) (V)
	oui ouais	6.32 (2 949) .83 17.89 (8 343) .02	(558) (15)	yes
	travail boulot	.19 .08	(90) .35 (38) .00	(235) (4)	work (N)
	très vachement	1.33 .30	(622) 1.64 (1 099) (141) .00 (0)	very
	(V = verb; N = noun; Pron. = pronoun)

Table 8 :

 8 Frequent verlan words and their numbers of occurrences in the NCCFr.

Table 9 :

 9 It might be expected, for instance, that Frequencies of negation particles in the two corpora per thousand words, and estimated percentage of double negation (Double Neg. %). Numbers within brackets indicate absolute numbers of occurrences.

		NCCFr	ESTER
	ne/n'	1.32	(676) 3.10 (3 664)
	pas	19.31 (9 001) 4.55 (3 503)
	rien	1.19	(557) .28	(193)
	jamais	.68	(321) .26	(179)
	aucun(e)	.21	(97) .35	(239)
	Double Neg. %	6.7			89.0

Table 10 :

 10 Frequencies of casualness indicators per thousand words within each recording part (lexical items, disfluency words, word repetitions) and percentage of double negation. Numbers within brackets indicate absolute numbers of occurrences. Double negation was estimated as explained in Section 4.2. Only lexical items that appeared at least 100 times in the NCCFr were included in this table. Rep. stands for repetition.

		Part 1	Part 2	Part 3
	chier	.10	(13)	.14	(24)	.35	(73)
	con	.26	(32)	.17	(30)	.19	(40)
	merde	.38	(47)	.26	(45)	.28	(60)
	putain	1.21	(151)	.72	(124)	.45	(95)
	cela	.00	(1)	.00	(2)	.00	(3)
	ça	15.87 (1 984) 15.19 (2 633) 17.36 (3 655)
	chose(s)	.99	(124)	.91	(157) 1.45	(306)
	truc(s)	3.58	(448) 2.76	(479) 2.25	(473)
	garçon(s)	.10	(12)	.00	(2) 1.22	(257)
	gars	.30	(37)	.64	(111)	.37	(78)
	mec(s)	.46	(57)	.70	(121)	.65	(137)
	oui	6.44	(805) 4.91	(851) 6.14 (1 293)
	ouais	18.32 (2 290) 15.66 (2 715) 15.85 (3 338)
	très	1.15	(144) 1.49	(259) 1.04	(219)
	vachement	.46	(58)	.20	(35)	.23	(48)
	ben	2.07	(259) 2.47	(428) 2.87	(605)
	euh	24.11 (3 014) 22.02 (3 817) 22.38 (4 713)
	hum	1.05	(131)	.76	(132)	.65	(136)
	Rep. bigrams	11.29 (1 412) 11.99 (2 080) 12.07 (2 542)
	Rep. trigrams	1.43	(179) 1.58	(275) 1.71	(361)
	Double negation	4.9%	6.5%	7.9	%

Acknowledgments

Our thanks to Cécile Fougeron, Coralie Vincent, Christine Meunier, Ton Wempe, the staff at ILPGA and the participants for their help during the recording of the corpus in France. We also want to thank Lou Boves and Christopher Stewart for helpful comments and discussion. This work was funded by a European Young Investigator Award to the third author. It was presented at the 6 th Journées d' Études Linguistiques of Nantes University in June 2009.

ACCEPTED MANUSCRIPT

Tree, J. E. F. (1995). The effects of false starts and repetitions on the processing of subsequent words in spontaneous speech. Journal of Memory and Language, 34:709-738. Valdman, A. (2000). La langue des faubourgs et des banlieues : de l'argot au français populaire. The French Review, 73(6):1179-1192.

A. Appendix: Activity sheet (English translation of French original)

Now you will answer at least five from the following questions:

• What do you think about Nicolas Sarkozy's divorce and the way it has been dealt with by the media?

• In your opinion, why did Ségolène Royal lose the presidential election?

• What do you think about applying affirmative action in the government and in the workplace?

• What do you think about the smoking ban in public spaces (restaurants, bars, trains, planes)?

• What do you think about the legalization of soft drugs?

• Why aren't boys and girls educated in the same way?

• Do you think that Al Gore deserves his Peace Nobel Prize?

• What do you think about strikes in France?

• What do you think about special regimes?

• How would you improve the higher education system?

For every question, you will try to negotiate a common answer. Once the recording has finished, one of you will write down your common answers about each of the chosen questions. You will therefore need to clearly determine your common answers as well as any point for which an agreement was not possible.


Mattias Olsson
email: mattias.olsson@kau.se

John J Cox
email: jjcox@uky.edu

Jeffery L Larkin
email: larkin@iup.edu

Anders Olovsson

P Widén

Space and habitat use of moose in southwestern Sweden

Keywords: Alces alces, Global positioning system, Habitat, Home range, Moose, Radiotelemetry

Increasingly, wildlife managers and land managers are challenged to maintain the viability of large mammal populations. Although the moose (Alces alces) is an ecologically, economically, and culturally important ungulate species found throughout most of Sweden, little is known about its ecology throughout the southern part of the country. We collected baseline ecological data on spatial and habitat use patterns in urbanized southwestern Sweden by fitting 22 adult moose (13 F, nine M) with global positioning system (GPS) radio collars. Home range size of cows did not differ among seasons (P>0.10); however, bulls had larger home ranges during fall than all other seasons (P<0.010). Mean home range size of males during fall and spring was larger than females during any season (P<0.010). We used a Euclidean distance-based approach to analyze multi-scale habitat selection by moose. Moose of both sexes and during all seasons selected boreal forest and mires when establishing a home range (P<0.10). Moose had seasonal differences in habitat selection within their home range (P0.001), and generally selected clear-cuts and early successional forests, mature coniferous forests, and glades, but avoided agricultural areas and open water. Habitat and space use characteristics of moose in our urbanizing study area were similar to characteristics reported for moose in forest-dominated landscapes of Fennoscandia.

Introduction

Characterization of space and habitat use patterns of large, mobile mammals is an important research goal in areas with intense human land use patterns, where urbanization and competing land uses increasingly challenge wildlife managers to maintain connectivity within a population [START_REF] Davies | Habitat fragmentation: consequences, management, and future research priorities[END_REF][START_REF] Harveson | Impacts of urbanization on Florida key deer behavior and population dynamics[END_REF]. This is the case particularly in areas where human development and areasensitive wildlife populations interface [START_REF] Meegan | Landscape conservation and regional planning for the Florida panther[END_REF][START_REF] Maehr | Florida panther dispersal and conservation[END_REF][START_REF] Harveson | Impacts of urbanization on Florida key deer behavior and population dynamics[END_REF]). Exurban development is increasing throughout much of the developed world [START_REF] Hilty | Corridor ecology: the science and practice of linking landscapes for Biodiversity conservation[END_REF]. In fact, the number of suburban residents in some European countries has increased threefold over the past 50 years [START_REF] Hilty | Corridor ecology: the science and practice of linking landscapes for Biodiversity conservation[END_REF]. Fragmentation and habitat loss associated with permanent landscape-scale alterations such as roads, agri-culture, and urban areas can inhibit habitat connectivity, reduce carrying capacity, and isolate wildlife populations [START_REF] Saunders | Biological consequences of ecosystem fragmentation: a review[END_REF]. These conditions can affect survival, daily and season movements, dispersal, the use of otherwise available habitat, and ultimately result in local extinction. [START_REF] Saunders | Biological consequences of ecosystem fragmentation: a review[END_REF][START_REF] Mills | Conservation of wildlife populations: demography, genetics, and management[END_REF].

Increased noise levels and human activities associated with human development and supporting infrastructures are known to have negative impacts on large mammal populations. For example, avoidance of areas due to highway disturbances have been documented for black bear (Ursus americanus), gray wolf (Canis lupus), and bobcat (Felis rufus) (Brody and Pelton 1989;[START_REF] Thurber | Gray wolf response to refuge boundaries and roads in Alaska[END_REF][START_REF] Lovallo | Bobcat movements and home ranges relative to roads in Wisconsin[END_REF][START_REF] Mladenoff | Predicting gray wolf landscape colonization: logistic regression models vs. new field data[END_REF][START_REF] Orlando | The ecology and behavior of an isolated black bear population in west-central Florida[END_REF]. Additionally, urban development was reported as the greatest threat to Florida key deer (Odocoileus virginianus clavium) population viability [START_REF] Lopez | Survival, mortality, and life expectancy of Florida key deer[END_REF], but the threshold level of urbanization had not yet been reached [START_REF] Harveson | Impacts of urbanization on Florida key deer behavior and population dynamics[END_REF]). Nonetheless, effects of risks associated with urbanizing landscapes may threaten the viability of large mammal populations unless appropriate land use planning is employed [START_REF] Meegan | Landscape conservation and regional planning for the Florida panther[END_REF][START_REF] Larkin | Landscape linkages and conservation planning for the black bear in west-central Florida[END_REF]). An important requirement for creating regional land use plans that consider wildlife conservation is the identification of threshold levels of human development that, if surpassed, have potentially unsustainable consequences for wildlife populations [START_REF] Harveson | Impacts of urbanization on Florida key deer behavior and population dynamics[END_REF].

The moose (Alces alces) is the largest member of family Cervidea and inhabits boreal forest-dominated regions of North America, Europe, and Asia [START_REF] Franzmann | Ecology and management of the North American moose[END_REF]. The species was nearly extirpated from Sweden during 1800s due to over-harvest, but hunting regulations prevented the loss of moose from the Swedish landscape (Lavslund et al. 2003). Habitat improvements created by modern forestry techniques, changes in sex-and age-specific harvest regulations, and lack of native predators such as the wolf and brown bear (Ursus arctos) have been identified as important factors that have been responsible for dramatic increases in Swedish moose population since the 1960s (Lavslund et al. 2003). However, in southwestern Sweden human population growth and concomitant pressures from infrastructure and development in or near coastal areas encroach upon moose habitat.

The goal of our study was to evaluate whether current levels of human development and associated infrastructure in an area of southwestern Sweden were intense enough to have impacted local moose ecology. We used GPS telemetry and GIS technology to characterize moose space and habitat use in an urbanizing area of coastal southwestern Sweden, where anthropogenic pressures increasingly threaten to fragment and isolate local moose populations. [START_REF] Hundertmark | Home range, dispersal and migration[END_REF] hypothesized that moose living in habitats characterized by relatively poor productivity (lower carrying capacity) would have larger home ranges than conspecifics in more productive habitats. As such, we predicted that moose resource selection and space use in our urbanizing study area would differ from values reported for moose populations in more forested regions of Fennoscandia if the human development threshold for the species had been surpassed. Information gained from our study provides wildlife managers and land use planners insight that can be used to develop more effective conservation plans that promote viable moose populations in this region.

Materials and methods

Study area

Our study was conducted in coastal southwestern Sweden between the cities of Uddevalla and Munkedal (Fig. 1). We defined the 320 km 2 study area by generating a 100% minimum convex polygon [START_REF] Mohr | Table of equivalent populations of North American mammals[END_REF], modified to exclude ocean, around all moose telemetry locations using the Animal Movement Extension [START_REF] Hooge | Animal movement extension to Arcview[END_REF] in ArcView 3.3 (ESRI, Redlands, CA). A 15 km section of European Highway 6 (E6) spanned the study area and also conveniently delineated the approximate boundary between boreonemoral and nemoral ecoregions (Abrahamsen et al. 1977). The landscape in this region was comprised of a mosaic of cover types including mature coniferous forest (46.0%) agriculture (19.0%), deciduous forest (10.0%), early successional forest (9.2%), glade (7.4%), mires (3.6%), open freshwater (2.7%), and human development (2.0%). The dominant tree species in the mature coniferous forest were Norway spruce (Picea abies) and Scots pine (Pinus sylvestris), with an intermixture of birch (Betula spp.), aspen (Populus tremula), willow (Salix spp.), and other deciduous species. The mature coniferous forest had a dwarf-shrub layer dominated by bilberry (Vaccinium myrtillus), cowberry (Vaccinium vitis-idaea), or heather (Calluna vulgaris). The deciduous forest stands were dominated by birch, rowan (Sorbus aucuparia), willow, common aspen, common alder (Alunus glutinosa), and pendunculate oak (Quercus robur). The early successional stages of forest after logging had a high abundance of birch, rowan, willow, and other deciduous species, with an herbaceous layer of wavy hair grass (Deschapsia flexuosa). However, within 3 years after logging, these stands were planted (or self generated) with either Norway spruce or Scots pine and thereafter managed to favor those species. Agricultural areas were comprised of hay and pastureland composed of a mosaic of grasses that commonly included perennial rye (Poa pretensis), quackgrass (Elytrigia repens), orchardgrass (Dactylis glomerata), and timothy (Phleum pratense), and crops that primarily included wheat (Triticum aestivum), barley (Avena sativa), oats (Horedelymus vulgare), and rye (Secale cereal).

Elevation within the study area ranged between 0-169 m above sea level. The most important human activities thought to influence biota in the study area were forestry, agriculture, infrastructure, and urban development. A helicopter inventory of moose density and sex/age classes conducted in February 2004 indicated an average moose density of 0.83 moose/km 2 in the study area (Anonymous 2004).

Capture and radio-collaring

We used a helicopter-based aerial platform to shoot and immobilize 24 moose (14 F, ten M) with a dart containing Large Animal Immobilon™ (Etorfin hydrochlorid 2.45 mg/ml, Acepromazin 10 mg/ml, and Xylazine 100 mg/ml; C-vet Ltd. Leyland, UK) in a 55 km 2 area during February 2002, 2003, and 2004. Each captured moose was equipped with a non-differentially-corrected GPS collar (GPS-SIMPLEX™; Televilt Positioning AB Inc., Lindesberg, Sweden) programmed to obtain a geographical location every 2 h and equipped with a pre-programmed electronic breakaway device. Data collected with each location included date, time, satellite geometry, and fix status based on communication with GPS satellites. Mean position accuracy of non-differentially-corrected GPS-SIMPLEX™ collars were tested in similar forest habitats in France. The mean location error for 2D locations with DOP<5 was 13.1 m (SE=±1. [START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF]. Summer period was adjusted to the vegetation period and the calving season that starts in the middle of May. The fall period was adjusted to the rut.

Data analysis

Moose were located approximately every 2 months from the ground to download radio-collar data. GPS collar locations with 2D fixes and a DOP>7 (n=1402) were removed from the dataset. We used a Euclidean distancebased analysis (EDA) to measure actual Euclidean distances to land cover types classified on digitized land cover maps [START_REF] Conner | Using Euclidean distances to assess nonrandom habitat use[END_REF][START_REF] Cox | Florida panther habitat use: new approach to an old problem[END_REF] We initially generated moose home ranges via the kernel method, but the resulting home ranges excluded areas where radio-collared moose were observed. As such, after visual comparison with kernel-based methods, we determined that the 100% minimum convex polygon (MCP) was the appropriate method to delineate moose home ranges. According to the resource selection literature it is more correct to include unused areas than to exclude areas that are known to be used by moose [START_REF] Porter | Effects of environmental pattern on habitat preference analysis[END_REF][START_REF] Manly | Resource selection by animals[END_REF][START_REF] Land | Florida panther habitat selection of concurrent GPS and VHF telemetry data[END_REF]. Excluding areas known to be used by radio-collared individuals is problematic from a resource selection perspective [START_REF] Porter | Effects of environmental pattern on habitat preference analysis[END_REF][START_REF] Manly | Resource selection by animals[END_REF]. Thus, we generated 100% MCP seasonal home ranges (n=133) and a composite home range using all location data for moose moni-tored≥1 year (n=16) using the Animal Movement Analysis [START_REF] Hooge | Animal movement extension to Arcview[END_REF] for ArcView 3.3 (ESRI, Redlands, California) (Table 1). Home ranges were generated only for time periods with≥50 locations per season. Mean seasonal home range sizes were calculated across years and resulted in 82 seasonal home ranges used in the statistical analysis. A Wilcoxon signed-rank test for matched pairs was used to test for differences in moose annual home range size between consecutive years (n=12); males (n=2) were pooled with females (n=10) due to low sample size of the former. A Mann-Whitney U test was used to test for differences in annual composite home range size between sexes. We used a two-way analysis of variance (ANOVA) to test for seasonal differences of home range size between sexes, among seasons, or within a sex× season interaction.

We estimated second order (selection of the home range) and third-order (selection within the home range) habitat selection following [START_REF] Johnson | The comparison of usage and availability measurements for evaluating resource preference[END_REF]. Our Euclidean distance-based habitat analysis was conducted as follows. Firstly, we used the random point generator of the Animal Movement Extension for ArcView 3.3 to create 50,000 random locations throughout the moose study area and 1,000 random locations within each moose home range. We then used the Nearest Feature Extension (Jenness Enterprises 2004) to calculate the Euclidean distance (m) of each random point and moose location to the nearest polygon of each land cover class. Points were valued as 0 m if they occurred within a habitat. To determine second order habitat selection, we created 8 distance ratios (1 per habitat type) for each moose by dividing the average distances from random locations within each individual home range by the average distances from random locations throughout the study area. To determine thirdorder habitat selection, we created 8 distance ratios for each moose by first calculating an average distance of moose locations to each habitat, and then dividing it by the average distances from random locations within each individual home range. We used ANOVA with multiple explanatory variables in program SAS version 8.2 (SAS Institute, Cary, North Carolina) to test the hypothesis that overall habitat selection did not differ from random with sex and season as main effects and individual moose as the experimental unit. When season or the sex×season interaction was not found as a significant main effect, we tested habitat use differences between sexes based on the composite home range for each individual moose. If our model was significant, univariate t tests were used to determine which habitats were used disproportionately. Habitat types with distance ratios significantly <1 were selected, and those significantly >1 were avoided. Habitat types were ranked by performing pairwise mean comparisons using univariate t tests [START_REF] Conner | Using Euclidean distances to assess nonrandom habitat use[END_REF][START_REF] Perkins | Habitat use of fox squirrels in southwestern Georgia[END_REF]). We considered statistical significance for all analyses at P≤0.10.

Results

Home range size

We analyzed 22 adult moose (13 F, nine M) to determine sex, season (n=133), and sex×season interaction effects on home range size. We found a significant sex × season interaction effect on moose home range size (F 7,125 = 6.93, P<0.001). Home range size of females did not differ among seasons (P>0.10), however, males had larger home ranges during fall than all other seasons (P < 0.010) (Table 1). Mean home range size of males during fall and spring was larger than females during any season (P<0.010).

Adult moose (ten F, two M) did not differ in annual home range size between consecutive years (T=23, P=0.21). Males (n=6; 52.2 km 2 ±10.9 km 2 ) had larger mean composite home ranges than females (n=10; 15.6 km 2 ±2.6 km 2 ) (U=3, P<0.05; Table 1).

Habitat use

We determined season and sex×season interaction effects on second and third-order habitat selection of 22 (13 F, nine M) adult moose. Season (F 24, 183 =0.76, P=0.779) and the sex × season interaction (F 24, 183 =0.42, P=0.992) did not affect second order habitat selection, and consequently, we pooled data across seasons within the composite home range of each individual and examined sex effects on second order habitat selection. Although we found no differences between sexes (F 8, 13 =1.26, P=0.341), moose home ranges included some habitats more than expected (F 8, 14 = 6.15, P=0.002) (Table 2). There were more mature coniferous forest (t 21 =-2.71, P=0.013) and mires (t 21 =-2.37, P=0.027) in home ranges compared with the overall landscape, but no difference between these two habitats was found (P=0.805).

Season (F 24, 183 =1.59, P=0.047) was found to affect third-order habitat selection, but the sex×season interaction did not (F 24, 183 Moose used mature coniferous forest (F 3,74 = 3.51, P=0.020), agriculture (F 3,74 =4.99, P=0.003), glades (F 3,74 = 2.60, P=0.058), and urban areas (F 3,74 =2.82, P=0.045) differently by season (Table 2). Post-hoc analysis revealed that differences in seasonal habitat selection occurred in use of mature coniferous forest (P=0.020) and urban areas (P=0.070) during spring and fall, in use of mature coniferous forest (P=0.096), agriculture (P= 0.002), glades (P=0.091), and urban areas (P=0.090) during spring and summer, and in use of glades (P=0.087) during spring and winter.

We also examined third-order habitat selection of 16 moose (ten F, six M) using composite home ranges for those individuals with at least one complete year of telemetry data. We pooled data between sexes because the number of males was less than the number of habitat variables. Moose selected habitats within their home ranges (F 8,8

Discussion

Home range size Despite our predictions, habitat and space use characteristics of moose in our urbanizing study area were similar to characteristics reported for moose in forest-dominated landscapes of Fennoscandia. Female composite home range sizes were similar to those reported in other regions of Sweden [START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF][START_REF] Cederlund | Home-range size in relation to age and sex in moose[END_REF]. Male composite home range sizes appeared to be relatively large compared to other Fennoscandian studies [START_REF] Cederlund | Home-range size in relation to age and sex in moose[END_REF], but the low sample size (n=6) precluded statistical comparison. Home range sizes of cervids typically differ between sexes because of different food requirements related to body size, predator avoidance strategies, and rearing of young [START_REF] Cederlund | Home-range size in relation to age and sex in moose[END_REF]Bowyer 2004). In this study, males had composite home range sizes more than three times larger than females, a pattern also observed by [START_REF] Cederlund | Home-range size in relation to age and sex in moose[END_REF]. Female home ranges did not differ among seasons but it did for males. Male home ranges during fall were more than four times larger than home ranges during winter. During winter, movements may be reduced to conserve energy [START_REF] Moen | Energy conservation by white-tailed deer in the winter[END_REF]) and be restricted by accumulated snow [START_REF] Van Ballenberghe | Radiotelemetry studies of moose in northeastern Minnesota[END_REF]. However, snow cover during the study never exceeded the amount that would impede moose movements [START_REF] Kelsall | Structural adaptations of moose and deer for snow[END_REF][START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF]. In addition to the potential need for conservation of thermal energy, moose in this study may have reduced winter movements because important foraging habitats such as clear-cuts and early successional forests [START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF][START_REF] Nikula | Habitat selection of adult moose (Alces alces) at two spatial scales in central Finland[END_REF]) were common and evenly distributed throughout the study area.

Habitat use

Previous studies conducted in Fennoscandia have documented moose habitat selection at landscape [START_REF] Nikula | Habitat selection of adult moose (Alces alces) at two spatial scales in central Finland[END_REF]) and home range scales [START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF][START_REF] Hjeljord | Choice of feeding sites by moose during summer, the influence of forest structure and plant phonology[END_REF]) using VHF-telemetry. Recently, other studies [START_REF] Van Beest | Comparative space use and habitat selection of moose around feeding stations[END_REF] have assessed multi-scale habitat selection of moose using the potentially higher resolving technologies that GPS telemetry can provide.

When selecting home ranges, moose equally selected areas with more mature coniferous forest and mires than what was found on average in the study area. In general, moist coniferous forests and complexes of marsh-land have been identified as important moose habitats containing food and cover during snow-free [START_REF] Markegren | The moose in Fennoscandia[END_REF]Bergström and Hjeljord 1987) and snow-covered periods (Bergström and Hjeljord 1987). Coniferous forest has been repeatedly shown to be important in providing shelter and forage for moose [START_REF] Markegren | The moose in Fennoscandia[END_REF]Bergström andHjeljord 1987, Nikula et al. 2004). During the 1960s, mires were first described as important winter habitat for moose (Bergström and Hjeljord 1987). Since that time, however, the emergence of young forests, and an increase in moose population densities and concomitant over-browsing of low-productive habitats are thought to have altered moose habitat preferences (Bergström and Hjeljord 1987) as reflected in a recent study which found that moose avoided mires when selecting a home range [START_REF] Nikula | Habitat selection of adult moose (Alces alces) at two spatial scales in central Finland[END_REF]). The selection of mires in our coastal study area might have occurred because of the strong correlation of boreal forest and mire habitats (r 2 =0.73), and because of the high relative proportion of agricultural land compared with other habitat types, especially west of highway E6. [START_REF] Cederlund | Home-range size in relation to age and sex in moose[END_REF] hypothesized that the intensive forestry that creates evenly distributed patches of clear-cuts with different successional stages at a scale smaller than a moose home-range would increase moose philopatry. In this study, moose did not prefer early successional forests when selecting a home range, a finding that may be a result of the relatively even distribution of that cover type throughout the study area. Important factors of moose habitat selection include quality and quantity of palatable browse, predator avoidance, thermal protection, and snow depth (Bergström and Hjeljord 1987;[START_REF] Nikula | Habitat selection of adult moose (Alces alces) at two spatial scales in central Finland[END_REF]). Moose selected habitats differently within seasonal home ranges and also selected habitats among seasons (Table 2), but no differences in seasonal habitat use were found between sexes. Moose selected early successional forests during all seasons and selected it over other habitat classes in summer and fall. In contrast to [START_REF] Nikula | Habitat selection of adult moose (Alces alces) at two spatial scales in central Finland[END_REF], who observed that moose used early successional pine-dominated plantations more in winter than summer, we found no difference in use of early successional forests among seasons. Clear-cut logging has historically created plant species communities similar to those found after forest fires [START_REF] Peek | Habitat relationships[END_REF]. Young forests in these timbered areas, particularly those dominated by pine, will remain an important component of moose diet, especially during winter [START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF][START_REF] Nikula | Habitat selection of adult moose (Alces alces) at two spatial scales in central Finland[END_REF]. In Fennoscandia, Scots pine is generally the most abundant forage resource during winter, and thus is usually most commonly browsed by moose [START_REF] Cederlund | Foods of moose and roe deer at Grimsö in central Sweden-results of rumen content analyses[END_REF]Bergström and Hjeljord 1987). In this study, coniferousdominated clear-cuts and early successional forests were not classified separately in the land cover data which may have reduced our ability to detect seasonal differences in use of this land cover type as found in previous studies. [START_REF] Markegren | The moose in Fennoscandia[END_REF] considered mature forests important during snow-free periods because of the presence of palatable food plants in the shrub layer. [START_REF] Cederlund | Home range and habitat use of adult female moose[END_REF], however, reported no habitat selection of mature forest over other cover types. [START_REF] Hjeljord | Choice of feeding sites by moose during summer, the influence of forest structure and plant phonology[END_REF] addressed the importance of mature coniferous forest to moose in late summer, and hypothesized that the delayed phenological changes in selected food plants was the primary reason for this habitat selection pattern. In contrast, we observed that moose used mature coniferous forest significantly more during spring than in summer or fall (Table 2). Spring is often a crucial season for moose that seek to replenish energy reserves as typically evidenced in the sharp dietary shifts from less palatable winter forage to more palatable and nutritious spring forage as species become available after snow melt [START_REF] Cederlund | Foods of moose and roe deer at Grimsö in central Sweden-results of rumen content analyses[END_REF]. Bilberry is an important early spring food for moose that is found in mature coniferous forest and that becomes available shortly after snow melt. Consumption of bilberry by moose in this study may explain our observations as to why mature coniferous forest was used more by moose in spring than other seasons.

We also found seasonal differences in habitat use of glade, agriculture and urban areas. Glades were selected during spring but not during other seasons, a pattern that may reflect increased selection of heather and juniper (Juniperus communis) in spring diet, coupled with summer and winter avoidance of these areas due to high temperatures and increased snow depth, respectively. Although agriculture was not selected relative to other cover types during any season, it was used at random during summer and significantly avoided during other seasons (Table 2). Oat-laden agricultural fields often attract moose during late summer and may be an important and nutritious food resource during this period (Bergström and Hjeljord 1987).

Moose were found closer to urban areas during summer and fall than in spring. Selection of these areas reflected an increased moose activity in rural areas during this period, and not in high density urban areas that moose always tended to avoid. In rural areas of Sweden, moose commonly forage on apples grown in gardens during late summer and early fall, a behavior supported by the frequent presence of moose tracks we observed in these areas during field work.

Spatial heterogeneity has been found to be an important predictor of ungulate distribution and foraging patterns [START_REF] Turner | Landscape heterogeneity and ungulate dynamics: what spatial scales are important? In: Bissonette JA (ed) Wildlife and landscape ecology-effects of pattern and scale[END_REF][START_REF] Mysterud | Habitat selection by roe deer and sheep: does habitat ranking reflect recourse availability?[END_REF][START_REF] Kie | Landscape heterogeneity at differing scales: effects on spatial heterogeneity of mule deer[END_REF]. Our results support the findings of [START_REF] Hjeljord | Choice of feeding sites by moose during summer, the influence of forest structure and plant phonology[END_REF] that found a mix of older and younger forests to be important for moose. [START_REF] Hjeljord | Choice of feeding sites by moose during summer, the influence of forest structure and plant phonology[END_REF] observed that a heterogeneous mixture of clear-cuts, plantations and older forest may give moose an optimal choice of feeding sites during summer. Additionally, we found deciduous forest and non-forested (<30% forest cover) habitat such as glades to be seasonally important. Small scale forest management practices can create a dynamic mosaic of uneven-aged forest patches that could be more easily encompassed within the home range of moose and provide season-specific resources that can increase home range fidelity [START_REF] Cederlund | Summer movements of female moose and dispersal of their offspring[END_REF]) and decrease dispersal to new areas [START_REF] Gasaway | Dispersal of subadult moose from a low density population in interior Alaska[END_REF])-two potentially important management goals in areas where reductions in human-moose encounters and sustainability of moose populations are concurrent goals.

EDA has become a commonly used method to determine coarse-scale wildlife habitat use patterns [START_REF] Conner | Using Euclidean distances to assess nonrandom habitat use[END_REF][START_REF] Perkins | Habitat use of fox squirrels in southwestern Georgia[END_REF][START_REF] Cox | Florida panther habitat use: new approach to an old problem[END_REF]. EDA has been described as being more robust to telemetry error than classification-based analyses, but further evaluation of the type 1 error distribution, and the effects of spatial scaling, especially at the landscape level, is needed [START_REF] Conner | A comparison of distance based and classification-based analyses of habitat use[END_REF]. Given the continued trends in rural-urban land use conversion that will likely occur in south Sweden in the near future, we suggest that future analyses temporally match land cover and telemetry data as closely as possible, and that land cover data be integrated and updated with field surveys in critical habitat areas where greater resolution of vegetation types (e.g., forest stand age and composition) may be needed. In doing so, the relative importance of moose habitats at finer scales could be better determined and management more locally adapted to prevailing conditions and circumstances.

Moose will likely remain an important economic and nutritional resource for Fennoscandian and other Holoarctic human societies. Wildlife and land managers responsible for maintaining a viable and harvestable population of moose in increasingly urbanized and denatured landscapes face imposing challenges. Our study and previous findings support the management strategy of creating and maintaining a mosaic of differing forest age classes and some nonforest cover types that will optimize cover and forage for moose during all seasons. However, we also recommend that managers consider the ecological impacts to species more sensitive to timber harvest before implementing moose-centric management plans. We further recommend researchers investigate the relationships among moose occurrence, spatial heterogeneity, and specific landscape metrics such as patch size of important cover types.

We also suggest that future work incorporate survivor and reproduction metrics in order to more adequately evaluate urbanization effects of moose viability. We examined habitat and space use relations, but ultimately the demographic characteristics of such populations must be examined.

Integrity of research and reporting

Research on moose was in accordance with an approved animal welfare protocol (Gothenburg, Dnr 323-2001). The author declares that they have no conflicts of interest.

  Fig. 1 GPS-telemetry locations of moose in southwestern Sweden, from 5 Feb 2002 thru 15 Dec 2005. Shaded polygons represent major city boundaries

  . The digital land use map used in our analyses was developed by Swedish National Land Survey using Landsat Thematic Mapper Satellite Data collected from 2000-2002 and contained 57 land use classes at a pixel size of 25 m× 25

m and a classification accuracy >75%

(Anonymous 1999;[START_REF] Engberg | Produktspecifikation av svenska corine marktäckedata[END_REF]

. Our study area contained 34 of the original 57 land use classes. We reclassified the study area land cover data map into eight general cover types most likely to influence moose. Reclassified cover types included mature coniferous forest, mature deciduous forest, early successional forest (including clear-cuts), agriculture, urban areas, open water, mire, and glades (bare rock-upper elevated areas with shallow soils and rock outcrops dominated by heath (Calluna vullgaris) and lichens with <30% tree cover) (Appendix).

  =1.27, P=0.189), and consequently, we pooled sexes within season. Moose selected habitats within their home ranges during each season (spring, F 8, 14 =12.84, P<0.001; summer, F 8, 12 =4.30, P=0.012; fall, F 8, 10 =3.08, P=0.050; winter, F 8, 10 =30.57, P<0.001) (Table 2). During spring, moose selected mature coniferous forest (t 21 =-4.00, P<0.001) over glades (t 21 =-5.63, P < 0.001) and early successional forest (t 21 = -3.88, P<0.001) and avoided agriculture (t 21 =4.92, P<0.001). During summer, moose selected early successional forest (t 19 =-5.14, P<0.001) over deciduous forest (t 19 =-2.35, P=0.030) and avoided open water (t 19 =2.25, P=0.037).

	During fall, moose selected early successional forest
	(t 17 = -3.98, P < 0.001) over urban areas (t 17 = -1.77,
	P=0.094) and avoided mires (t 17 =1.88, P=0.077) and
	agriculture (t 17 =1.81, P=0.088). During winter, moose
	selected early successional forest (t 17 =-5.12, P<0.001)
	over other habitats but avoided mires (t 17 =1.87, P=0.079)
	and agriculture (t 17 =-4.00, P<0.001).

  =6.54, P=0.008). Moose equally selected early successional forest (t 21 =-7.70, P < 0.001) and mature coniferous forest (t 21 = -4.71, P<0.001) over glades (t 21 =-2.03, P=0.061), but avoided open water (t 21 =2.08, P=0.060) (Table 2).

	Table 1 Seasonal and composite minimum convex	Mean home
	polygon (100%) home range sizes of moose in southwestern	Sex	Number of moose seasons	Time period	Range size (km 2 )	S E
	Sweden, 2002-2005
		Females	26	Spring	10.6	12.0
			22	Summer	7.0	3.6
			19	Fall	12.5	17.0
			25	Winter	5.7	5.1
			10	Composite a	15.6	2.6
	Mean seasonal home ranges across years per individual	Males	11 9	Spring Summer	20.6 17.6	21.2 10.0
	moose were used to eliminate		9	Fall	34.2	21.0
	pseudoreplication		12	Winter	7.7	5.7
	a Only included moose with at		6	Composite a	52.2	10.9
	least 1 year of data

Table 2

 2 [START_REF] Johnson | The comparison of usage and availability measurements for evaluating resource preference[END_REF] second-and third-order habitat selection by moose in southwestern Sweden, 2002-2006 SU summer, FA fall, WI winter, CFR mature coniferous forest, AGR agriculture, DFR deciduous forest, ESF early successional forest, GLD glade, MIR mire, URB urban areas, WAT open water, (>) a rank-order difference with P≥0.10, (>>) P≤0.10

	Habitat selection order Season Habitat ranking
	2nd	-	MIR (0.73)>CFR (0.75)>AGR (0.90)>ESF (0.97), GLD (0.97)>WAT (0.98) >>DFR (1.05)>URB (1.07)
	3rd a	SP	CFR (0.67) >>GLD (0.84)>ESF (0.85) >>WAT (0.99)>MIR (1.01)>DFR (1.04)>URB (1.08) >>AGR (1.38)
		SU	ESF (0.73) >>DFR (0.90) >>CFR (0.93)>URB (0.94)>GLD (1.00)>AGR (1.01)>MIR (1.06)>WAT (1.07)
		FA	ESF (0.82) >>URB (0.92)>GLD (0.93)>DFR (0.94)>CFR (1.00)>WAT (1.07) >>MIR (1.13)>AGR (1.15)
		WI	ESF (0.79)>CFR (0.92)>URB (0.96)>DFR (0.99)>GLD (1.00)>WAT (1.06)>MIR (1.08)>AGR (1.15)
	3rd b	-	ESF (0.69)>CFR (0.70) >>GLD (0.89)>DFR (0.94)>URB (0.99)>MIR (1.03)>AGR (1.11)>WAT (1.13)
	Habitat types in bold had a distance ratio (in parentheses) that differed significantly (P≤0.10) from 1.00
	SP spring,

a Using seasonal home ranges b Using composite home ranges

Eur J Wildl Res (2011) 57:241-249

Acknowledgements We thank the Swedish National Road Administration for funding this project (Vägverket Borlänge and Vägverket Region Väst), and Per-Arne Lemnell, Bengt Evertsson and Hans Skatter of TVP Positioning AB for technical advice.

Appendix References

Abrahamsen J, Jakobsen NK, Kalliola R, Dahl