Ivan Ineich
email: ivan.ineich@mnhn.fr

Addison Wynn

Christophe Giraud

Van Wallach

Indotyphlops braminus (Daudin, 1803): distribution and oldest record of collection dates in Oceania, with report of a newly established population in French Polynesia (Tahiti Island, Society Archipelago) 1

The authors provide a general review of the first collection date or first literature publication date for Indotyphlops braminus from all Oceanian archipelagos and/or islands from where it has been reported. This terrestrial worm-like snake (Typhlopidae) is reported here for the first time as having been introduced, most likely accidentally, to Tahiti Island. The snake will certainly rapidly spread over most islands of the five archipelagos of French Polynesia.

French Abstract-Les auteurs établissent une révision générale des dates de première collecte ou de première mention aussi précises que possible pour l'introduction du serpent terrestre vermiforme Indotyphlops braminus (Typhlopidae) sur toutes les îles et archipels océaniens. L'introduction probablement accidentelle de ce serpent est ici signalée pour la première fois sur l'île de Tahiti. Ce reptile va très certainement étendre rapidement sa répartition à l'ensemble des cinq archipels de Polynésie française.

Introduction

Indotyphlops braminus (Daudin, 1803), also known as the Brahminy blindsnake or flowerpot snake, is a small worm-like snake often mistaken for an earthworm. It is always among the smallest snakes wherever it occurs. Its mean total length is between 100-130 mm with a weight of 0.75 gm [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF].

Based on the presence of retrocloacal sacs (indicated as "retro-cloacal formations") as well as unique features of the hemipenes, [START_REF] Robb | The generic status of the Australasian typhlopids (Reptilia: Squamata)[END_REF] showed that the genus Ramphotyphlops Fitzinger, 1843 had to be revalidated to accommodate certain Australasian species. Later [START_REF] Mcdowell | A catalogue of the snakes of New Guinea and the Solomons, with special reference to those in the Bernice P. Bishop Museum, Part 1. Scolecophidia[END_REF] noted that braminus could be assigned to the genus Typhlina Wagler, 1830 (a synonym of Ramphotyphlops) based on similarities with the head scale pattern of "Typhlina erycina." A complete nomenclatural history of the species (as R. braminus) can be found in [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF], who indicated that a new genus has to be proposed for that species. The new genus Indotyphlops (type species Typhlops pammeces Günther, 1864) was later created by [START_REF] Hedges | A taxonomic framework for typhlopid snakes from the Caribbean and other regions (Reptilia, Squamata)[END_REF] to accommodate 22 species. Note, however, that [START_REF] Pyron | Systematics of the blindsnakes (Serpentes: Scolecophidia: Typhlopoidea) based on molecular and morphological evidence[END_REF] only considered 20 species in the genus. That new genus was included in the new subfamily Asiatyphlopinae [START_REF] Hedges | A taxonomic framework for typhlopid snakes from the Caribbean and other regions (Reptilia, Squamata)[END_REF] which comprised 10 genera from southern and eastern Asia, the Malay Archipelago, Australasia, and islands of the western and southern Pacific. [START_REF] Pyron | Systematics of the blindsnakes (Serpentes: Scolecophidia: Typhlopoidea) based on molecular and morphological evidence[END_REF] only recognized seven genera in that subfamily. Indotyphlops braminus is the most successful species in the entire family, spreading on all continents most often in recent years but also sometimes earlier through human involuntary introduction through trading and movement of people and goods around the Indian Ocean and beyond. The snake is, however, not present in South America, and arid, high latitude and high altitude areas. According to numerous changes in its taxonomic history, some geographic records related to I. braminus appear under Typhlina bramina, Typhlops braminus or Ramphotyphlops braminus.

Indotyphlops braminus is generally present in relatively moist places like under flower pots, detritus, stones or dead trees, and also in the moist layers at the base of young coconut trees most often to as high as 50 cm (II pers. obs.). It is often abundant and easy to find under objects deposited beneath houses, particularly in villages recently colonized by the snake. The species is terrestrial, but some specimens have been observed in arboreal habitats [START_REF] Bazzano | Herpetological inventory in West Hawai'i national parks: Pu'uhonua o Honaunau National Historical Park, Koloko-Honokohau National Historical Park, and Pu'ukoholà Heiau National Historic Site[END_REF]. [START_REF] Ota | Morphological variation, karyotype and reproduction of the parthenogenetic blind snake, Ramphotyphlops braminus, from the insular region of East Asia and Saipan[END_REF] estimated clutch size of this snake as 1-8, but [START_REF] Kamosawa | Reproductive biology of the Brahminy blind snake (Ramphotyphlops braminus) from the Ryukyu Archipelago, Japan[END_REF] pointed out their possible overestimation and provide a more reliable range of 1-6. Incubation period is of up to 58 days [START_REF] Ota | Morphological variation, karyotype and reproduction of the parthenogenetic blind snake, Ramphotyphlops braminus, from the insular region of East Asia and Saipan[END_REF]. Parthenogenesis, first suspected [START_REF] Mcdowell | A catalogue of the snakes of New Guinea and the Solomons, with special reference to those in the Bernice P. Bishop Museum, Part 1. Scolecophidia[END_REF][START_REF] Nussbaum | The brahminy blind snake (Ramphotyphlops braminus) in the Seychelles Archipelago: distribution, variation, and further evidence for parthenogenesis[END_REF], was demonstrated by [START_REF] Wynn | Apparent triploidy in the unisexual Brahminy Blind Snake, Ramphotyphlops braminus[END_REF] and [START_REF] Ota | Morphological variation, karyotype and reproduction of the parthenogenetic blind snake, Ramphotyphlops braminus, from the insular region of East Asia and Saipan[END_REF]. Its populations only comprise triploid females that reproduce through obligate parthenogenesis, a characteristic unique among snakes [START_REF] Booth | The emerging phylogenetic pattern of parthenogenesis in snakes[END_REF]. Indotyphlops braminus is likely the product of hybridization between two (or more) parental species of Indotyphlops, possibly through two distinct hybridization events due to its triploidy. Some or all parental species could now be extinct through competition with their most successful hybrid descendants.

Indotyphlops braminus feeds primarily on the soft parts of ants and termites, sometimes on earth worms and caterpillars [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF][START_REF] Geniez | Serpents d'Europe[END_REF]. Recently [START_REF] Mizuno | A blindsnake that decapitates its termite prey[END_REF] showed that it decapitates its termite prey and consumes only the thorax and abdomen in about half the specimens it eats. Heads often remain undigested in the feces. Decapitation can allow the snake to avoid consuming termite heads which are of poor nutritive value or to escape chemical defense of termites by non-ingestion of toxic compounds mostly located in their heads.

General reviews of the natural distribution and spreading of I. braminus based on literature record synthesis can be found in [START_REF] Mcdiarmid | Snake species of the world. A taxonomic and geographic reference[END_REF], [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF] and [START_REF] Kraus | Alien Reptiles and Amphibians -a Scientific Compendium and Analysis[END_REF]. I. braminus is most likely a native of India or Sri Lanka and probably spread (naturally or through man) to other nearby southern Asian countries like Bangladesh, Nepal, and Pakistan, and perhaps also to southeast Asian countries like Cambodia, Laos, Myanmar, Singapore, Thailand, Vietnam, and West Malaysia, or east Asian countries like China (including Hainan, Hong Kong, and Macau) and Taiwan [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF][START_REF] Hedges | A taxonomic framework for typhlopid snakes from the Caribbean and other regions (Reptilia, Squamata)[END_REF][START_REF] Pyron | Systematics of the blindsnakes (Serpentes: Scolecophidia: Typhlopoidea) based on molecular and morphological evidence[END_REF]. The snake was, however, recently introduced in many regions and countries including the West Indies (e.g. [START_REF] Censky | Geographic distribution: Serpentes. Ramphotyphlops braminus (Brahminy Blind Snake). Lesser Antilles: Anguilla[END_REF][START_REF] Wallach | Range extensions and new island records for Ramphotyphlops braminus (Serpentes: Typhlopidae)[END_REF]) and Cuba [START_REF] Díaz | First record of the Brahminy Blindsnake Indotyphlops braminus (Squamata: Typhlopidae), in Cuba[END_REF], Borotto-Paez et al. 2015), Asia (including Japan [e.g. [START_REF] Ota | Morphological variation, karyotype and reproduction of the parthenogenetic blind snake, Ramphotyphlops braminus, from the insular region of East Asia and Saipan[END_REF]), Australia (e.g. Cogger 2014), most Indian Ocean Islands (e.g. [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF]), Near-and Middle-East (e.g. Safaei-Mahroo et al. 2015), Africa (including northern arid countries like Egypt [e.g. [START_REF] Venchi | Annotated checklist of the reptiles of the Mediterranean countries, with keys to species identification. Part 2 -Snakes (Reptilia, Serpentes). Annali del Museo Civico di Storia Naturale "Giacomo Doria[END_REF][START_REF] Ibrahim | The Herpetology of the Suez Canal Zone, Egypt[END_REF]), and Madagascar (e.g. [START_REF] Nagy | Molecular systematics and undescribed diversity of Madagascan scolecophidian snakes (Squamata: Serpentes)[END_REF]. The snake was also reported from numerous peripheral islands and archipelagos all over the world (e.g. [START_REF] Wallach | Range extensions and new island records for Ramphotyphlops braminus (Serpentes: Typhlopidae)[END_REF]) in Africa and on Atlantic oceanic islands (e.g. de Urioste & Mateo 2011[START_REF] Jesus | First record of Ramphotyphlops braminus (Daudin, 1803) on Madeira Island (Portugal)[END_REF] or Asia (e.g. [START_REF] Kaiser | The herpetofauna of Timor-Leste: a first report[END_REF][START_REF] Qing | Additions to the Reptile and Amphibian Fauna of Nan Ao Island: A Chinese Treasure Trove of Biogeographic Patterns[END_REF]. It also was introduced to Central America (e.g. [START_REF] Dixon | The wormsnakes (family Typhlopidae) of the neotropics, exclusive of the Antilles[END_REF][START_REF] Mccranie | Geographic Distribution. Ramphotyphlops braminus (Brahminy Blindsnake). Honduras[END_REF] and North America (Mexico; USA: Alabama, Arizona, California, Florida, Georgia, Louisiana, Massachusetts, Minnesota, North Carolina, Ohio, Texas, and Virginia [e.g. [START_REF] Wallach | Range extensions and new island records for Ramphotyphlops braminus (Serpentes: Typhlopidae)[END_REF][START_REF] Hegan | Alien herpetofauna pathway, invasions, current management practices and control methods ethics: A review of some significant problems in the USA[END_REF]). Indotyphlops braminus has not yet invaded South America [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF]. The snake was even recently introduced to the Canary Islands, and to Europe in the Balearic Islands and southern Spain mainland (e.g. [START_REF] Mateo | Los anfibios y reptiles naturalizados en Espana; historia y evolucion de una problematica creciente[END_REF][START_REF] Rato | A molecular assessment of European populations of Indotyphlops braminus (Daudin, 1803)[END_REF])!

Materials and Methods

The recent spread of I. braminus has also included many islands in Oceania [START_REF] Zug | Reptiles and Amphibians of the Pacific Islands -a comprehensive guide[END_REF]. We here provide a complete summary of the distribution of I. braminus in Oceania and its earliest known report date based on literature examination and/or museum collections. We also report the first record of I. braminus on Tahiti Island (Society Archipelago, French Polynesia) based on two recently collected snakes. at prehuman levels of strata. However, it cannot be excluded that those fossil remains belong to another species, extinct or still unnoticed, and not to I. braminus. In the Caroline Islands, not far from the Marianas, two endemic species were recently described [START_REF] Wynn | The unexpected discovery of blind snakes (Serpentes: Typhlopidae) in Micronesia: two new species of Ramphotyphlops from Caroline Islands[END_REF], Ramphotyphlops hatmaliyeb and Ramphotyphlops adocetus. A first hypothesis could be that Pregill's fossil remains from the Mariana Islands derive from one of those species or other endemic species related to them. All of those remains should most likely belong to the genus Ramphotyphlops native radiation as recently redefined (see above) and not to the genus Indotyphlops. [START_REF] Pregill | Squamate reptiles from prehistoric sites in the Mariana Islands[END_REF] identification of the fossil vertebrae attribute them to typhlopids based on their morphology and to I. braminus (as R. braminus) only because there was no other species known from the area at that time. Morphological differences allowing separation of vertebrae of Ramphotyphlops from those of Indotyphlops are unknown, thus our above statement is only hypothetical. One early report (A.M.C. Duméril & Bibron 1844) of a specimen from the Mariana Islands (Guam) collected by Jean René Constant Quoy and Joseph Paul Gaimard in 1819 during the Freycinet Expedition was referred to I. braminus. That specimen, MNHN-RA 6332 is available in Paris Natural History Museum (MNHN) collections. We first thought that it could be referable to the endemic Micronesian Ramphotyphlops radiation with 22 midbody scale rows [START_REF] Wynn | The unexpected discovery of blind snakes (Serpentes: Typhlopidae) in Micronesia: two new species of Ramphotyphlops from Caroline Islands[END_REF], which could explain its early occurrence in the area. Examination of that specimen confirms it is I. braminus, having 20 midbody scale rows and typical head scales. Two additional old specimens dated prior to 1889 (MNHN-RA 1889.0543-544) from the same location also belong to I. braminus. Thus, those MNHN-RA specimens are the earliest verified occurrence (vouchers) of that species in Oceania, later confirmed by [START_REF] Cagle | Typhlops braminus in the Marianas Islands[END_REF], [START_REF] Downs | Amphibians and reptiles of Tinian Island[END_REF], and [START_REF] Dryden | Reptiles from the Mariana and Caroline islands[END_REF] in Micronesia. The situation in Micronesia is particularly interesting and needs further study since I. braminus seems to have been present on those islands for a long time (the oldest verified occurrence in Oceania is dated from the early 19 th century). However, I. braminus may have also occurred there with an endemic radiation of the genus Ramphotyphlops. If Pregill's (1998) fossil vertebrae from the Marianas are from an extinct endemic typhlopid (genus Ramphotyphlops), the species may have gone extinct before or just after I. braminus arrived on the islands, and the two may not have occurred there together. Alternatively, the endemic species could still exist and remains undetected, which is unlikely due to the changes in faunal composition (numerous introduced predators and competitors which are often more threatening to endemic than alien species) and habitat modifications on the Marianas. A second hypothesis could be that those remains really belong to I. braminus and thus such an early occurrence of the species could be related to colonization events originating from Asia prior to human arrival. Establishment of osteological characters allowing separation of Indotyphlops from Ramphotyphlops based on vertebrae from modern well identified specimens would be mandatory to clarify the question of the past occurrence and distribution of these genera in Micronesia.

Concerning the date of arrival of I. braminus in Oceania (Table 1), the oldest record is from the Marianas (1819; A.M.C. Duméril & Bibron 1844), followed by a record from Manokwari in west of New Guinea [START_REF] Barbour | A contribution to the zoogeography of the East Indian Islands[END_REF], and the Hawaiian Islands dated prior to 1930 [START_REF] Slevin | A note on the discovery of the genus Typhlops in the Hawaiian Islands[END_REF]. The snake could have been introduced to Hawaii early in the XXth century. Note that I. braminus occurred in the Indian Ocean for a much longer period of time. The Paris Natural History Museum catalogues refer to specimens collected at La Réunion Island before 1862 (MNHN-RA catalogues; specimens collected by Maillard but not found in collections; Ineich, pers. obs.) and Zanzibar in 1884 (MNHN-RA 1884.0061; Ineich, pers. obs.) and those were probably voluntarily introduced at the same time as several other lizards and snakes now indigenous to La Réunion (e.g. the agamid lizard Calotes versicolor and the colubrid snake Lycodon aulicus) which most likely originated from India where they are common species. 1). The snake has not been reported from Tonga [START_REF] Gill | Notes on the birds, reptiles and mammals of Tongatapu and 'Eua (Tonga)[END_REF][START_REF] Gill | Records of birds and reptiles from Tonga[END_REF][START_REF] Gill | Records of wildlife from Tonga, especially Vava'u[END_REF][START_REF] Gill | Records of reptiles from Tonga[END_REF][START_REF] Steadman | Conservation status of forests and vertebrate communities in the Vava'u Island Group, Tonga[END_REF][START_REF] Zug | Reptiles and Amphibians of the Pacific Islands -a comprehensive guide[END_REF], Atherton et al. 2015) where it most likely has not been introduced for the moment. There are also no published records for Rotuma [START_REF] Boulenger | On the reptiles of Rotuma Island, Polynesia[END_REF][START_REF] Zug | The vertebrates of Rotuma and surrounding waters[END_REF]), Wallis and Futuna [START_REF] Gill | Notes on the land reptiles of Wallis and Futuna, south-west Pacific[END_REF], Tuvalu (Waite 1897), Tokelau [START_REF] Whitaker | A note on the lizards of the Tokelau Islands, Polynesia[END_REF][START_REF] Clapp | Additional records of lizards from the Tokelau Islands, Polynesia[END_REF]), Niue [START_REF] Wodzicki | A preliminary survey of rats and other land vertebrates of Niue Island, South Pacific[END_REF], the Cook Islands [START_REF] Mccann | Reptiles from Manihiki Atoll[END_REF][START_REF] Clapp | Notes on the vertebrate fauna of Tongareva Atoll[END_REF][START_REF] Crombie | The lizards of Rarotonga and Mangaia, Cook Island Group, Oceania[END_REF][START_REF] Gill | Records of Cook Island lizards[END_REF], and the Pitcairn Island Group [START_REF] Gill | The lizards of the Pitcairn Island group, South Pacific[END_REF][START_REF] Edgar | The Amphibians and Reptiles of the UK Overseas Territories, Crown dependencies and Sovereign Base Areas -Species Inventory and Overview of Conservation and research Priorities[END_REF].

Indotyphlops braminus has not been reported in Eastern Polynesia, but its probable introduction was highly suspected in French Polynesia [START_REF] Ineich | Le peuplement herpétologique de Polynésie française. Adaptations et aléas[END_REF], 1989). French Polynesia comprises about 130 islands distributed in five archipelagos dispersed throughout a marine area similar in size to Europe.

We report here the first verified case of the most likely accidental introduction of I. braminus on Tahiti Island in French Polynesia, attested to by two recently collected vouchers deposited in the Muséum National d'Histoire Naturelle (Paris) collections (MNHN-RA) (Fig. 1). The larger specimen, MNHN-RA 2015.0057, has a total length of 132 mm and 20 scale rows around midbody. Its gular area is whitish contrary to other body parts, which are all greyish brown (Fig. 2). It was collected on Tahiti Island, in a heap of earth in a construction site at Punaauia on 11 November 2014. It was first frozen and later placed in 75% ethanol, therefore never in contact with formalin. The second and smaller specimen, MNHN-RA 2015.0058, has a total length of 114 mm and also 20 scale rows around midbody. It was collected on 30 November 2015 in works at the Music Conservatory site of Papeete also on Tahiti Island, in rubble originating from Pirae. It was first kept in a terrarium, and then placed in the freezer, and subsequently in ethanol. Both specimens fully agree with morphometric and scalation characters indicated by [START_REF] Wallach | Ramphotyphlops braminus (Daudin): a synopsis of morphology, taxonomy, nomenclature and distribution (Serpentes: Typhlopidae)[END_REF] and we refer them to I. braminus.

According to the separate geographic origin of our two specimens and the huge colonization capacities of I. braminus, it is more likely that several populations are now present and well established on Tahiti Island and most likely on other islands and atolls of French Polynesia. Tahiti is the main island of French Polynesia and most if not all air and sea travels passes through it, thus facilitating the spread of the snake from one island to another. The current precise distribution of I. braminus in French Polynesia, like that of the introduced gecko Hemidactylus frenatus, is incompletely known, but most likely covers several archipelagos at present [START_REF] Ineich | Lizards of Niau Atoll, Tuamotu Archipelago, French Polynesia[END_REF].

Discussion

The introduction of I. braminus to French Polynesia will not have direct visible consequences. It can however have a hidden impact either on its prey populations (mainly ants and termites) or by introduction of internal parasites (viruses, bacteria, worms, hemogregarines) able to infect other reptiles or even other animals. I. braminus also can carry mites. Such external parasites could potentially be introduced in addition to internal parasites and be hosts of pathogens such as bacteria and viruses. There is no native or fossil terrestrial snake in French Polynesia, from where all terrestrial snakes were previously absent. This is attested to by all previous intensive collections, which lack any terrestrial snake [START_REF] Ineich | Distribution des Reptiles terrestres en Polynésie orientale[END_REF]). The situation is not the same in some parts of Micronesia (Carolines) where confusion of I. braminus is possible with unnoticed and unprotected species only recently described [START_REF] Wynn | The unexpected discovery of blind snakes (Serpentes: Typhlopidae) in Micronesia: two new species of Ramphotyphlops from Caroline Islands[END_REF]. Competition between endemic species and the alien I. braminus is possible there and certainly could have an impact on the survival of endemic biota [START_REF] Fisher | Considering native and exotic terrestrial reptiles in island invasive species eradication programmes in the Tropical Pacific[END_REF]. [START_REF] Ineich | Le peuplement herpétologique de Polynésie française. Adaptations et aléas[END_REF] suspected the introduction of I. braminus in French Polynesia about 30 years ago. Finally the snake was discovered later than expected, contrary to the gecko H. frenatus, another alien species widespread in the Pacific, which arrived just before 1988 to Tahiti [START_REF] Petren | Mechanisms in the competitive success of an invading sexual gecko over an asexual native[END_REF]. Let us hope that the brown tree snake, Boiga irregularis, a snake with a dramatic and serious impact on the native bird populations of Guam (Hegan 2014), will not follow those introduced species and accidentally colonize French Polynesia.

Figure 1 .

 1 Figure 1. Two introduced specimens of Indotyphlops braminus from Tahiti Island in French Polynesia. MNHN-RA 2015.0058 above and MNHN-RA 2015.0057 below. Scale bar: 1cm. Picture: I. Ineich.

Figure 2 .

 2 Figure 2. Anterior ventral area of Indotyphlops braminus MNHN-RA 2015.0057 showing the whitish gular coloration. Picture: I. Ineich.

Table 1 .

 1 Earliest known arrival dates of the snake Indotyphlops braminus on the Oceanian islands and archipelagos according to publications or collection vouchers.Indotyphlops braminus was reported as occurring on Pohnpei by 1936 and in the Marshall Islands in 1954. It was only reported from NewCaledonia and Vanuatu around 1970, and from Fiji in 1983 (Table

	Country	Earliest date Reference
	Mariana Islands	1819	A.M.C. Duméril & Bibron 1844
	Mariana Islands, Guam	1819	A.M.C. Duméril & Bibron 1844
	New Guinea	1912	Barbour 1912
	Hawai'i	1930	Slevin 1930
	Carolines (Pohnpei)	1936	Buden 2000
	Mariana Islands, Tinian	1945	Cagle 1946
	Mariana Islands, Saipan	1945	Cagle 1946
	Marshall Islands	1954	Knight 1984
	Palau (Belau)	1955	Crombie & Pregill 1999
	Solomon Isl.	1961	McDowell 1974
	Vanuatu	1971	Medway & Marshall 1975
	Bonin Island	1971	Shigei 1971
	New Caledonia	1974	Ineich & Bauer 1992
	Fiji	1983	Clunie 1983
	Mariana Islands, Rota	1987	Wiles et al. 1990
	Loyalty Islands	1991	Shea & Wallach 2000
	American Samoa	1992	CAS 195919
	Midway Atoll	1998	Wallach 2008
	Nauru	2007	Buden 2008
	Kiribati (Gilbert Isl.)	2007	Craven & Shea 2010
	Western Samoa	2009	Bonin & Shea 2009
	Tahiti Island, French Polynesia	2014	This paper

See discussion in McDowell (1974) about New Guinea records prior to Second World War.

Acknowledgements

The authors thank Hidetoshi Ota for his review of an earlier version of this paper. Thanks also to Glenn Shea for sharing information.

Results

Indotyphlops braminus was reported from New Guinea 3 (Barbour 1912, Kopstein 1926, Brongersma 1934, McDowell 1974, Room 1974, Heatwole 1975, McCoy 1980, Nussbaum 1980, O 'Shea 1996, Kraus & Allison 2004, Kraus 2013); Bonin Islands (Shigei 1971); Palau, (Fehlmann 1960 [not seen], McDowell 1974, Crombie & Pregill 1999, Zug 2013); the Mariana Islands and Guam (A.M.C. Duméril & Bibron 1844, Safford 1905, Van Denburgh 1917, Cagle 1946 [Guam, Tinian, Saipan, Aguiguan, Anatahan], Downs 1948 [Tinian], Tanner 1948 [Guam], Oliver & Shaw 1953 [Tinian], Brown 1956, Dryden & Taylor 1969 [Saipan, Guam], McDowell 1974 [Saipan, Guam], Wiles et al. 1989 [Tinian], Wiles et al. 1990 [Rota], Rodda & Dean-Bradley 2001 [Guam]); Federated States of Micronesia (Vollbrecht 1945 [Carolines], McDowell 1974 [Pohnpei], Thomas 1997 [Pohnpei], Buden 2000 [museum specimens dated 1936 from Pohnpei], Wood & Law 2010 [Kosrae], Zug 2013 [Kosrae, Pohnpei, Yap], Buden & Taborosi 2016 [? for a specimen observed on Ulithi Atoll (Falalop), but its identity not ascertained, identification confirmed on Kosrae, Pohnpei, and Yap]); the Marshall Islands (Knight 1984, Lamberson 1987, Vander Velde 2003, Zug 2013); Nauru (Buden 2008, Zug 2013); the Solomon Islands (McDowell 1974, McCoy 1980, 2006); Vanuatu (Medway & Marshall 1975, Anonymous 1981, Cranbrook 1985, Allison 1996, Shea & Wallach 2000, Jennings 2004, de Pous & Dingemans 2008, Ineich 2009, 2011, Zug 2013); New Caledonia and the Loyalty Islands (Bauer 1987, Ineich & Bauer 1992, Bauer 1999, Shea & Wallach 2000); New Zealand (not established in New Zealand and known only from a single intercepted stowaway according to Gill et al. [2001]); Fiji (Clunie 1983, Morrison 2003, Watling et al. 2010, Zug 2013); Kiribati (Gilbert Islands [Craven & Shea 2010]); Western Samoa (Bonin & Shea 2009); American Samoa (voucher Calif. Acad. Sciences CAS 195919 collected 1992, Trail 1993, Craig 2002, Goldin 2002, Kraus 2009, Zug 2013 [Samoa only, no precision]); Hawaii (Slevin 1930 [Oahu], Tinker 1938, Fisher 1948 [Oahu], Oliver & Shaw 1953 [Oahu], Hunsaker & Breese 1967 [Maui Isl.], Liebermann & Liebermann 1970 [Hawaii Isl.], McKeown 1978, Jones 1979, McCoy 1980, Nussbaum 1980, Kraus 2005 [Hawaii Isl.], Bazzano 2007, Zug 2013); and Midway Island (Wallach 2008, Taylor et al. 2009).

Introduction dates on those Pacific islands remain unclear since the snake could have been undetected long after its arrival. However, natural occurrence on some north-western Oceania islands has been suggested by Pregill (1998). He showed that snake remains attributed to I. braminus occur at archeological sites on Aguiguan and Tinian islands in the Marianas, presumably


Blanche Collard
email: blanche.collard.inra@gmail.com

Philippe Tixier
email: tixier@cirad.fr

Dominique Carval
email: dominique.carval@cirad.fr

Claire Lavigne
email: claire.lavigne@inrae.fr

Thomas Delattre
email: thomas.delattre@inrae.fr

Collard

; Tixier

; Carval

; Lavigne

; Delattre

Assessing the effect of complex ground types on ground-dwelling arthropod movements with video monitoring: Dealing with concealed movements under a layer of plant residues

Keywords: Tracking movements in complex ground types Insect, Mesocosm, Monitoring, Movement ecology, Spatial heterogeneity, Video tracking Tracking movements in complex ground types

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Ground type quality and spatial configuration are key factors for managing the spatial distribution of organisms for conservation purposes or improving the efficacy of conservation biological control. At the landscape scale, the effect of ground type and spatial distribution on dispersal have been extensively studied [START_REF] Baguette | Landscape connectivity and animal behavior: functional grain as a Tracking movements in complex ground types key determinant for dispersal[END_REF][START_REF] Haddad | Habitat fragmentation and its lasting impact on Earth's ecosystems[END_REF], resulting in the development of management practices like movement corridors [START_REF] Peng | Urban ecological corridors construction: A review[END_REF][START_REF] Russell | Increasing the conservation value of powerline corridors for wild bees through vegetation management: an experimental approach[END_REF].

In contrast, at the patch scale, foraging movements of ground-dwelling arthropods [START_REF] Bell | Searching Behaviour -The behavioural ecology of finding ressources, Chapman and hall animal behaviour series[END_REF] have primarily been studied in relation with the distribution of trophic resources [START_REF] Kareiva | Swarms of Predators Exhibit "Preytaxis" if Individual Predators Use Area-Restricted Search[END_REF][START_REF] Valeix | How key habitat features influence large terrestrial carnivore movements: waterholes and African lions in a semi-arid savanna of north-western Zimbabwe[END_REF] but not the ground type distribution. Yet, there is evidence that ground type could influence the foraging movement of ground-dwelling arthropods, by providing a wider and more complex range of resources, such as favourable microclimatic conditions or protection from predators, or by deterring movement by increasing its risks and costs. A typical example is the reluctance of biological control agents to move inside the agricultural plot despite the presence of trophic resources, a frequently proposed explanation for failures in conservation biological control [START_REF] Hassan | Does the presence of grassy strips and landscape grain affect the spatial distribution of aphids and their carabid predators?[END_REF][START_REF] Albrecht | The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis[END_REF]. Individual-based models and a meta-analysis suggest that the interaction between movement behaviour and ground type spatial distribution could solve this problem [START_REF] Albrecht | The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis[END_REF][START_REF] Collard | Spatial organisation of habitats in[END_REF]Delattre et al., 2019). Therefore, new data on the effect of ground type on patch-scale foraging movement are necessary for improving conservation biological control at this scale.

Analysing movements inside an agricultural plot requires collecting high-resolution data on a small spatial scale, which raises technical obstacles. Mark-Recapture (M-R) studies may provide insights on inter-patch movements but generally lack the resolution needed to document intra-patch movements especially for small ground-dwelling species (e.g., arthropods) that represent a high proportion of species of agronomic interest. M-R techniques using radio frequency identification (RFID) active tags are limited to the relatively large species that can handle the chip weight (1 to 0.2 g; [START_REF] Kissling | Challenges and prospects in the telemetry of insects[END_REF]. Moreover, these techniques provide coarse-grained data [START_REF] Kissling | Challenges and prospects in the telemetry of insects[END_REF][START_REF] Noskov | A Review of Insect Monitoring Approaches with Special Reference to Radar Techniques[END_REF][START_REF] Vinatier | Radiotelemetry unravels movements of a walking insect species in heterogeneous environments[END_REF]. Harmonic radar seems to hold the best promises for the future, with small Tracking movements in complex ground types tags (6-20 mg; [START_REF] Kissling | Challenges and prospects in the telemetry of insects[END_REF] and high-resolution data over a 1 km range. However, this technique has yet to be proven functional in complex vegetation covers (Daout et al., 2017;[START_REF] O'neal | Tracking Insects with Harmonic Radar: a Case Study[END_REF]. Its complex development process strongly reduces its immediate availability.

An alternative to in-situ remote sensing techniques resides in mesocosm studies, in which one or several ground types (e.g., earthy soil, sand, plants) can be replicated in an enclosed arena, and the behaviour of the target organism is monitored by video [START_REF] Reynolds | Remote-sensing, telemetric and computer-based technologies for investigating insect movement: a survey of existing and potential techniques[END_REF]. Since mesocosm studies allow for high-resolution data collection, they are well suited for studying foraging behaviours.

However, they generally focus on diurnal movements on a uniform and light background to preserve a high contrast with the targets and allow automatic movement tracking. Some more advanced computing methods such as deep learning have been employed to track individuals in more complex or in-situ environements and simultaneously track several individuals [START_REF] Bernardes | Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis[END_REF][START_REF] Imirzian | Automated tracking and analysis of ant trajectories shows variation in forager exploration[END_REF][START_REF] Romero-Ferrero | idtracker.ai: Tracking all individuals in large collectives of unmarked animals[END_REF]. Nevertheless, to our knowledge, the slightly more heterogeneous and realistic backgrounds were studied in open areas with no vegetation layer, filmed in a rather tight shot allowing only short movements to be recorded [START_REF] Bjerge | Real-time insect tracking and monitoring with computer vision and deep learning[END_REF][START_REF] Kindvall | Movement behaviour of the pine weevil Hylobius abietis in relation to soil type: an arena experiment[END_REF] and rarely addressed nocturnal movements (but see [START_REF] Imirzian | Automated tracking and analysis of ant trajectories shows variation in forager exploration[END_REF].

Observing the effect of diverse ground types on movements using heterogeneous mesocosms and video monitoring is challenging, because not all ground types provide good contrast, especially at night-time, with some concealing parts of the movement paths. Thus, the difficulties of these types of studies resides in (1) separating the target animal from the background by image analysis and (2) reconstructing and analysing the scattered paths caused by complex three-dimensional strata (e.g., shelters above ground).

In this study, we developed a method to track ground-dwelling arthropods in mesocosms that mimic real agricultural ground types including one with two strata that conceals them periodically. This method aimed to investigate how their movement could be affected by the ground type quality, i.e.

whether it can cause a difference in their sinuosity or their speed. Because the upper stratum could directly affect the movement of these arthropods, even more so if it conceals them, special attention Tracking movements in complex ground types has been given to consider the concealed movements in the analyses. We applied this method to analyse movements of the earwig Euborellia caraibea (Hebard), an endemic polyphagous predator of Cosmopolites sordidus (Germar) in the Caribbean islands [START_REF] Brindle | The Dermaptera of the Caribbean[END_REF][START_REF] Carval | Cover cropping reduces the abundance of the banana weevil Cosmopolites sordidus but does not reduce its damage to the banana plants[END_REF][START_REF] Mollot | Cover cropping alters the diet of arthropods in a banana plantation: a metabarcoding approach[END_REF] in mesocosms mimicking two banana field ground types, bare soil and banana plant residues. Preliminary experiment showed that E. caraibea is nocturnal (Appendix A) and seems to prefer the banana plant residues (Collard, pers. data), likely due to the humidity and shelter they provide [START_REF] Burr | Modern work on earwigs[END_REF]. By using infrared light, different temporal resolutions and different hypotheses on the behaviour of concealed earwigs, we were able to address the problem of night-time and partially concealed earwig movements.

Materials and methods

The movement of 17 and 18 E. caraibea (including five males per group) were tracked one at a time on one of two ground types: bare soil and banana plant residues, respectively. In this study, the recording of one individual on one ground type represents a replicate.

Capture and laboratory maintenance of Euborellia caraibea

E. caraibea adults were caught in a field at the Petit Morne site in Martinique (14°37'N, 60°58'W).

Species and sex determinations of individuals were performed according to [START_REF] Brindle | The Dermaptera of the Caribbean[END_REF]. Before its movements were tracked, each individual was kept in a 6 cm diameter non-hermetic boxes at 25 °C (12:12, Light:Dark) in the laboratory for 5 to 34 days. Each box contained a shelter constructed of corrugated cardboard wrapped around a vegetable sponge soaked with distilled water to maintain a constant level of humidity and a water resource. A 1 cm 3 cube of food (based on [START_REF] Guennelon | Progrès réalisés dans l'élevage permanent du Carpocapse (Laspeyresia pomonella L.) sur milieu artificiel[END_REF] was provided once a week.

This device allowed us to keep E. caraibea earwigs alive for a relatively long time compared to the duration of the experiments. Out of the 67 earwigs kept in the lab until the end of the experiment -35 of which were used for this study -only 12 died.

Experimental mesocosms design

Tracking movements in complex ground types Two 1 x 1 m arenas were built from a square base of 1 m² expanded PVC and 20 cm high Plexiglas edges (Fig. 1a) set up at the CIRAD facilities in Martinique (CAEC ; 14°37'N, 60°58'W). One arena mimicked a ground with banana plant residues (hereafter referred to as "residues"; Fig. 1b and1d), and the second arena mimicked a ground of bare soil (hereafter referred to as "bare soil"; Fig. 1c and1e).

Each arena contained 22 x 22 cells of 4.5 cm side length made from seedling plates, filled with potting soil and sprinkled with soil from a CIRAD insecticide-free experimental banana field ("Rivière lézarde" site, 14°39' N, 60°58' W) sifted with a 0.5 cm mesh. In order to prevent the earwigs from escaping, seedling plates were sealed together and connected to the tops of the Plexiglas edges using transparent plastic sheetings coated with talcum powder. For the "residues" arena, 3 × 3 cm units of overlaid dried banana leaves were placed evenly over the bare soil and fixed to a 1 × 1 m wire mesh, with free space between them to allow the detection of the earwig's movement (Fig. 1a and1d). Only solvent-free hot glue, wire and tape were used in both arenas. Circular white platforms of 6.5 cm diameter were positioned in the centre of each arena to accommodate the earwig in its shelter at the beginning of the experiment.

Each arena was placed under one Trendnet TV-IP310PI infrared camera (3.2 megapixels, 2048 × 1536), and four projectors containing 48 infrared LED each, were placed on the corners of each arena to provide more uniform lighting (Fig. 1a). Red or infrared lights are commonly used to observe the behaviour of earwigs (Diehl and Meunier, 2018) or other nocturnal insects, as they are considered invisible to insects (Dias et al., 2012;Drees et al., 2008;[START_REF] Heise | Sensitivity of mayfly nymphs to red light: implications for behavioural[END_REF]. Infrared lights were preferred, as they are even less likely to have an impact on nocturnal insect behaviours [START_REF] Allema | Effect of light quality on movement of Pterostichus melanarius (Coleoptera: Carabidae)[END_REF]. The two arenas, video devices and infrared lights were placed in a climatic chamber maintained at 25 °C and equipped with white light LEDs (Linear power led, 25W/4000 K, 2500 LM, Lamentin) providing a 12:12 (L:D) photoperiod (Fig. 1a). The light spectrum of similar white light LED can be found in [START_REF] Sharakshane | Whole high-quality light environment for humans and plants[END_REF]. The two cameras filmed the arenas in parallel using a network switch, a Synology DS216 NAS and its Surveillance Station software.

Tracking movements in complex ground types

The cameras created an image distortion depending on their distance from the arenas. It was estimated that 1 cm of the object corresponded to an average of 6.82 pixels over the entire arena with a standard error of ±0.01 cm (see details in Appendix B).

Movement monitoring

Individuals were chosen following their order of capture to homogenise the time spent in captivity.

Each day of experiment, two earwigs were randomly assigned to the two arenas.

The shelter containing the chosen individual was placed on the white platform in its arena at 5:00 pm on the day of the experiment. The cameras then filmed the arenas from 5:30 pm to 8:00 am (i.e., including the entire night period, which started at 6:00 pm and ended at 6:00 am). This period corresponds to the estimated activity period for E. caraibea under natural outdoor lighting conditions (see the preliminary experiment in Appendix A). The earwigs left the departure platform at various times between 6:06 p.m. and 9:14 p.m., always after the light had been switched off. Since we tracked 17 individuals on bare soil and 18 individuals on residues, we obtained 35 × 14.5 hours of videos

Tracking movements in complex ground types (resolution 1024 × 768 pixels; 1 frame.s -1 ) between April 26 and May 29, 2017. Only night-time recordings were used in the rest of this study.

Each tested individual was tagged with a 1 × 1 mm square of reflective material (~1 mg, SKU Ref.

HEBBR09001, Lecyclo, France) to allow the infrared light reflection enhancing the visibility of the individuals in the arena. The tag was fixed to the earwig's pronotum with a strong adhesive (cyanoacrylate, Super Glue®) at least 24 hours before testing (Fig. 2; see detailed tagging protocol in

Appendix C

). The tagged earwigs showed no visible changes in movements, survival (all tagged earwigs that were recovered after the experiment survived for at least 8 days) and reproduction (some tagged females laid eggs). The day after the experiment, the arenas were transferred outdoors, the residue grid was removed (for the "residues" treatment), and the bare soil was exposed to the sun to remove or, at a last resort, kill individuals from previous experiments and any organisms that might have entered the arena. A total of 28 earwigs were removed: 14 out of 17 on the bare soil and 14 out of 18 on the residue arenas.

Trajectories extraction from videos

We developed a method to extract trajectories from videos to characterise the movements (i.e., speed, sinuosity, and earwig activity) in both ground types (Fig. 3a and3b). The trajectories are defined as a

Tracking movements in complex ground types time series of locations of one individual (= points), and each point is characterised by its coordinates and time. Points were grouped into a given trajectory if separated by less than a time gap tg and a distance gap dg (hereafter referred to as junction criteria) [START_REF] Tinevez | TrackMate: An open and extensible platform for single-particle tracking[END_REF].

Tracking movements in complex ground types

The experimental design of this study posed some specific problems that made the extraction of trajectories from the videos difficult, including (i) significant background noise caused by heterogeneous backgrounds and the infrared light and (ii) the simultaneous presence of several individuals in an arena for some replicates where a previous individual had not been found and removed. This methodological problem was a consequence of the presence of soil in the arenas, making it difficult to recover individuals at the end of the experiment. To account for these issues, we used (i) a technique to subtract background and residual noise from the videos and (ii) semi-automated cleaning of the trajectories in R to eliminate conflicting and interacting trajectories. After video treatments, the trajectories were extracted using ImageJ2, an image processing software [START_REF] Schindelin | Fiji: an open-source platform for biological-image analysis[END_REF]version 1.51) and its TrackMate plugin [START_REF] Tinevez | TrackMate: An open and extensible platform for single-particle tracking[END_REF]version 3.6.0).

TrackMate plugin use a DoG detector algorithm (Difference of Gaussian) and a Simple LAP tracker algorithm (Linear Assignment Problem) (based on [START_REF] Jaqaman | Robust single-particle tracking in live-cell time-lapse sequences[END_REF]. DoG detector allows the detection of small moving points from their size (3 pixels) and a quality threshold (15) (Tinevez et al., Tracking movements in complex ground types 2017). The Simple LAP tracker then associates the points within trajectories (i.e. the junction), one time step after the other, according to the junction criteria dg (30 pixels, i.e. ≃ 4.3 cm), and tg (5 s) without signal.

A semi-automated cleaning treatment (see diagram in Appendix E) was performed with the R software (R Core Team, 2018; version 3.6.3) to eliminate conflicting and interacting trajectories.

Conflicting trajectories are trajectories that occur simultaneously and that are either false positive (being derived from residual background noise) or real trajectories from other earwigs moving simultaneously. The treatment involved basic automated processes for removing conflicting points under certain circumstances (e.g., when the number of conflict points was small) and, visual observations and manual editing of trajectories to remove residual conflicting trajectories otherwise.

For example, when trajectories of several earwigs were observed in an arena, the trajectory which was the most consistent with the anterior and posterior trajectories was retained (except in one case where two trajectories, distant from each other by less than 5 cm, were both deleted). Most of conflicting trajectories were removed with automated processes and only few trajectories had to be cleaned manually per individual (mean ± standard deviation : 2.0 ± 5.4 % of trajectories; max of 34 trajectories). This indicated that most of the conflicting trajectories were generated by residual background noise. Once the conflicts were removed and the confusion between individuals and noise was no longer observed, the trajectories were reconstructed with less restrictive junction criteria (dg = 50 pixels and tg = 10 s) (Fig. 3b and Fig. 4).

Estimating movement variables

We developed a method to estimate comparable movement variables, i.e. the time-series of distances and turning angles calculated from segments with identical durations, in both ground types (Fig. 3c and 3d). Two successive points within a trajectory define a segment. A distance is the length of a segment. A turning angle is calculated between the direction of a segment and the direction of the previous segment. Therefore, it takes two successive segments to obtain a turning angle. Due to the disappearance of the tag and missing points within the trajectories in the "residues" arena, segments with an identical duration were rare. The method relies on the design of different procedures to obtain segments of identical duration. These procedures varied in their time resolution and were based on different hypotheses on the behaviour of concealed earwigs. Each procedure resulted in a set of movement variables for each individual.

Removing near-edge movements

To estimate movement variables that were not biased by the arena's edges, we removed all trajectory points within 35 pixels (≈ 5.1 cm) of the arena borders (Fig. 3). This treatment split some trajectories into several trajectories. This operation was always performed after conducting the junction operation for specific time and distance gaps (see next paragraph).

Tracking movements in complex ground types

Procedures to obtain segments of identical duration

A procedure transformed the extracted trajectories into movement variables by means of three different operations: a junction, an interpolation and a rediscretisation of the trajectories (cf. Fig. 4 and [START_REF] Semenishchev | Stitching of IR images into a single content based on data which analysis obtained by an optical camera[END_REF]. Each procedure has a corresponding parameter value for each operation (e.g. Fig. 3c and3d) . All operations were performed with the R software (R Core Team, 2018; version 3.6.3) and the adehabitatLT package [START_REF] Calenge | The package "adehabitat" for the R software: A tool for the analysis of space and habitat use by animals[END_REF]version 0.3.25).

The junction operation consisted of reconstructing trajectories with a less restrictive junction time gap (tg) (Fig. 4). The interpolation operation involved placing one point for each missing point within trajectories (Fig. 5), utilising linear interpolation between the previous and following extracted points (see interpolation function proposed by adehabitatLT). By filling in the missing trajectory points, interpolation allowed the disappearance periods to be included in the speed calculation. The rediscretisation operation consisted in modifying the fixed duration of the segments required to estimate the movement variables within each trajectory. In the absence of interpolation, the segments with identical duration were selected from successive direct observations corresponding to the selected rediscretisation time (Fig. 5a andc). If there were no observations exactly at the next re-discretisation time, the segment and consequently the distance and the turning angle were not calculated. In the case of interpolation (Fig. 5b andd), rediscretisation consisted of placing all missing points with interpolation and selecting the segments corresponding to the chosen rediscretisation times. Therefore, each dataset of movement variables obtained by a specific procedure was based on a specific way of obtaining segments with identical duration.

Sensitivity of movement variables to operation values

Choices made for the three main operations used to obtain segments of identical duration (junction,

Tracking movements in complex ground types

To investigate those potential effects, we tested the impact of procedures on movement variables with all combinations of the following values: (i) junctions (tg) of 10 s, 30 s, 1 min and 5 min; (ii) rediscretisations of 1, 5, 10, 20, 30, 40, 50 and 60 s, (iii) with and without interpolation.

Comparison between ground type

Individual activity

The activity during the night of the experiment was considered only for individuals that were known to have been alone in the arena and which were found at the end with their tag still in place. This represented 9 and 7 individuals for bare soil and residues, respectively. The activity was measured from the entire recorded movements, i.e. all "cleaned" trajectories (Fig. 3).

We calculated the amount of movements per night per individual (= number of seconds an individual was observed in movement, later termed "apparent intensity of activity"), the number of minutes that an individual was observed with movement (at least one second recorded, termed "estimated intensity of activity") and the time elapsed between the first and last movement of an individual (termed "total activity period"). As residues potentially concealed a significant portion of the movements, the two last measures were performed to limit this information loss bias and better compare activity between the two ground types.

Statistical analysis of movement variables

We tested the effect of residues on travel speed and sinuosity by comparing the movement variables of trajectories (distances and turning angles) between the two ground types. We considered the autocorrelation of successive segments in our analyses by testing the effect of ground types for different rediscretisation values (i.e., at different time scales) and taking an individual resolution for our statistical analyses (Fieberg et al., 2010). Individuals released the same day were considered as independent because they could not interact and external conditions were controlled by the climatic chamber. Individuals that had too little data to have a correct estimate of their movement variables were removed from analyses (see below).

Tracking movements in complex ground types Distances were compared between ground types using datasets of all procedures with at least 10 individuals with at least 10 distance records per ground type. Statistical analyses were performed using mixed linear models (package lme4; [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF]version 1.1-26) with individuals as a random effect and a square root transformation of distances expressed in pixels ( ) to address the 𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 overdispersion of the model residuals. Model residuals were inspected for dispersion, uniformity and outliers with the "DHARMa" R package [START_REF] Hartig | DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models[END_REF]version 0.3.3.0). The effect of the individual's sex and its interaction with ground type were removed from the model since they had no significant effect on distance (see analysis in Appendix F).

Turning angles were compared between ground types for all procedures without interpolation and with a junction of 10 s comprising at least 10 individuals with at least 10 turning angles records per ground type. Only one junction time gap was tested because, in absence of interpolation, the junction time gap does not affect the turning angles used for analysis (Fig. 6b). Individual-based statistics were used to test the effect of ground type on the concentration of turning angles (1 -the variance of turning angles around the mean). Concentration is a measure of the sinuosity of a trajectory, ranging from 0 to 1, with low values corresponding to sinuous trajectories. Statistics developed on R by [START_REF] Pewsey | New Tracking movements in complex ground types York[END_REF] were used. These analyses rely on the non-parametric test statistics of [START_REF] Wallraff | Goal-oriented and compass-oriented movements of displaced homing pigeons after confinement in differentially shielded aviaries[END_REF] and allow the comparison of two circular statistical distributions for the concentration. A randomization test was performed on the test statistics. The statistical distribution under H 0 was constructed by calculating 1000 statistics obtained after random permutations of the individuals between the ground types to account for the differences in numbers of calculated angles among individuals. The p-values were calculated by comparing the observed statistics with the statistical distribution under the null hypothesis H 0 of similar values in the two ground types.

Results

Activity

The apparent intensity of activity appeared to be lower on average on the residues than on the bare soil (inter-individual mean ± standard deviation, Residues: 1.5 ± 0.8 hours, Bare soil: 2.5 ± 2.0 hours). We Tracking movements in complex ground types found no such large difference when comparing the estimated intensity of activity (inter-individual mean ± standard deviation, Residues: 5.9 ± 2.1 hours, Bare soil: 5.1 ± 2.7 hours) or the total activity period (inter-individual mean ± standard deviation, Residues: 9.4 ± 2.1 hours, Bare soil: 10.0 ± 1.0 hours). All measures of activity revealed a highly variable activity pattern (intensity and distribution over time) depending on the earwig's identity and not linked to ground type. The detailed activities of each individual are presented in Appendix G.

Movements variables

Samples generated according to procedures

The trajectories selected for the movement analysis (i.e. excluding near-edge movements) represented 31.9 ± 18.6 % of the total seconds of movement (inter-individual mean ± standard deviation).

We did not get enough distances to allow statistical comparison of distances for 23 (over 64) procedures (Fig. 6a). The average number of segments sampled (= distances) per earwig varied largely depending on the procedure (from 5.6 to 3454.5 segments ; Fig. 6a). The number of segments was larger for porcedures with short rediscretisation values, interpolation and long time gaps for junction (tg) (starting at tg = 30 s). The number of segments was also very variable among the earwigs (from 5 to 1268 segments per earwig for the reference procedure). Segment statistics per individual and per ground type corresponding to data used for statistical analyses for all procedures are given in Appendix H. Similar effects of procedures on the number of turning angles were found with the difference that interpolation was not used and turning angles were always fewer (Fig. 6b). We did not obtain enough data to allow statistical comparison of turning angles for 24 (over 32) procedures, only procedures with rediscretisation values of 1 and 5 s analysed.

Tracking movements in complex ground types

Speed

Speeds were calculated from distances as the ratio between distances and the rediscretisation value and are presented to simplify the comparison between the different rediscretisation values. During their Tracking movements in complex ground types movements, earwigs reached a maximum velocity of 2.19 ± 0.84 cm.s -1 (inter-individual mean ± standard deviation calculated from trajectories with rediscretisation at 1 s without interpolation), with a maximal speed of 4.93 cm.s -1 registered for an individual on residues.

All statistical analyses, regardless of the procedure, show a significant effect of ground type on distances (all p-values < 10 -3 ). The earwigs' mean speeds were estimated 2.3 to 4.2 times slower on residues than on bare soil (Fig. 7; see detailed statistical results in Appendix I). For example, the mean speed was 0.36 ± 0.11 cm.s -1 (inter-individual mean ± standard deviation) on residues vs 0.85 ± 0.27 cm.s -1 on bare soil, for a procedure with few assumptions, i.e., junction of 10 s, without interpolation and rediscretisation of 5 s. Estimated slowdowns on residues varied depending on the procedure (Fig. 7b). Stronger slowdowns were estimated with long time gaps for junction (starting from 1 min), intermediate rediscretisations (10 to 30 s) and interpolation. Junction only affected slowdown for procedures with interpolation. In particular, allowing a junction of 5 min with interpolation strongly increased the estimated slowdown. Rediscretisation had different effects with and without interpolation. Without interpolation, rediscretisations of 5 s and more increased the estimated slowdown. With interpolation, increasing rediscretisation values (starting from 30 s) tended to decrease slowdown. The standard error associated with model estimates also increased for high rediscretisation values (see Appendix I).

Tracking movements in complex ground types

Discussion

Analysing foraging movement of small organisms at a fine scale, over long periods and on realistic ground is crucial for understanding their spatial and temporal dynamics and help managing them in Tracking movements in complex ground types real agricultural environments. Based on generic video and trajectory processing, we developed a method that made it possible to detect more sinuous and slower movements of the nocturnal earwig E. caraibea walking on soil covered by banana leaf residues rather than on bare soil.

Tracking earwigs' movements with an experimental mesocosm and video recording.

Our experimental device made it possible to monitor several hours of movement on both ground types.

A crucial step of the method was to distinguish earwigs from the background. The use of reflective material on earwigs' pronotum was decisive in increasing the earwigs' contrast. In addition to background and noise subtraction, semi-automatic cleaning of trajectories was necessary to suppress the remaining noise and to make robust choices between some simultaneous trajectories. The reflective material and video treatments have made the manual editing more manageable given the number of hours, and the movement resolution registered.

The experimental device developed in this study appeared to be more efficient for calculating speeds and highlighting differences in earwig movements for the fine temporal grains (rediscretisation ≤ 30 s). Indeed, we observed a decreasing trend in the estimated slowdown in the residues arena when the values of rediscretisation increased (starting at 30 s) with interpolation (Fig. 7b). Above 30 s, the dimensions of the arena (< 1 m²) were probably too small, biasing the sampling of distances towards shorter distances than they might be in open ground. This limitation should be considered when extrapolating the study results to larger spatial and temporal scales, as the distances travelled do not change linearly with sampling time (Morales & Ellner, 2002). This experimental device opens up the possibility for future analyses on the effects of a wide variety of ground types on the movement of ground-dwelling arthropods. Additional video treatments or improved tracker algorithms (e.g., [START_REF] Assali | Raking the ocean surface: new patterns of coordinated motion in seabirds[END_REF]) may be required in more complex environments, such as plant cover, where background noise management for trajectory extraction and individual recovery is challenging. In all cases, the spatial distribution of the cover units that could hide individuals should be set to allow the brief but regular appearance of the target species. Previous knowledge of the species, their maximum and mean speed can help optimise the cover design.

Tracking movements in complex ground types Similarly to our case, studying cryptic species would probably require improving the contrast between the target and the cover. Thus, choosing an appropriate tag is critical and depends on the species targeted, the ground type tested, and the camera device chosen. In the case of diurnal species, there are more possibilities for distinguishing individuals from the background. Indeed, recording in visible light results in less noise than infra-red light [START_REF] Semenishchev | Stitching of IR images into a single content based on data which analysis obtained by an optical camera[END_REF] and standard cameras under visible light return three values per pixel, providing more possibilities to find colours (not just intensities) that distinguish individuals from the background [START_REF] Sebastian | Colour Space Effect on Tracking in Video Surveillance[END_REF]Wu et al., 2020 preprint). The standard infra-red camera used in this experiment returns only one value per pixel (intensity), suggesting that reflective material is probably the best option for nocturnal species.

In recent years, advances in computational methods, such as deep learning, have enabled advances in insect tracking, resulting in significant progress in counting, species recognition and movement tracking [START_REF] Bjerge | Real-time insect tracking and monitoring with computer vision and deep learning[END_REF][START_REF] Høye | Deep learning and computer vision will transform entomology[END_REF]. However, these methods are still time-consuming to develop and require a large amount of data, specific to the particular conditions of a given experiment, to train the algorithm. Although in the future we can hope for an improvement and greater transferability of the algorithms developed to a wider range of experiments, the use of simpler but faster methods, such as those developed in this study, still seem to us to be of great relevance.

Characterising movements with trajectories containing missing points

Most trajectories included times where the location of the earwig was not known (missing points).

Even on bare soil, missing points were rare but existed (Appendix J). Missing values within trajectories in our experiment could have several explanations: (i) the individual hid under the soil, (ii) the individual movements were not captured by our device or (iii) the individuals were concealed by the residues. Since individuals hiding under the soil (situation i) were rarely observed, and situation (ii) corresponded to a short and random loss of the earwig's tag tracking (e.g., bad inclinations of the tag toward infrared LED), those missing points should not have significantly influenced the quantification of movement on bare soil.

Tracking movements in complex ground types

We were interested in the period during which movements were concealed by residues (situation iii) because they could be the source of significant differences in movement variables between the two ground types. Because situation (ii) could also happen on residues, the time with missing points on residues did not exactly match the time individuals spent under residues (situation iii). However, in our experiment, the missing points between residues are unlikely to have affected the estimation of movement variables, particularly slowdown. Indeed, if we had lost track of individuals moving between two or more residues, resulting in an artificially long concealed period, these individuals probably travelled distances larger than the distance gap of 7.3 cm, such that the next data point would be the beginning point of a new trajectory. Herein, we used long time gaps for trajectory junction, long rediscretisations of trajectories and interpolation to include concealed movements in the trajectories used to quantify movement variables.

The duration of junction time gaps determined the maximum duration of concealed movements included in the trajectories. Long junction time gaps were necessary to account for long concealed movements (up to 5 min). These long junction time gaps affected the quantification of speed and sinuosity only when (i) they were combined with interpolation (because numerous successive interpolated points were added), and (ii) rediscretisation was longer than the junction time gaps (because concealed periods shorter than this time gap could be included within a segment).

Varying the rediscretisation value without interpolation allowed to include concealed movements while making few assumptions, because only observed movements were taken into account. Short rediscretisations were adapted to analyse speeds and sinuosity on a fine time scale (1 to 5 s, Fig. 7 and Fig. 8) because they provided enough data to perform statistical analyses without interpolation (Fig. 6a). Some slightly longer rediscretisations (10 and 20 s) generated enough data to compare speeds between ground types including longer concealed movements in trajectories (up to 19 s). However, because the inclusion of these longer concealed movements was only possible for long rediscretisation, it was not possible to disentangle the effects of concealed movement from those of time scale on speed and sinuosity. Notably, it has been proposed that each time scale can reflect different behaviours [START_REF] Nathan | A movement ecology paradigm for unifying organismal movement research[END_REF][START_REF] Owen-Smith | Foraging theory upscaled: the behavioural ecology of herbivore movement[END_REF]. For example, individuals showing Tracking movements in complex ground types (i) a high sinuosity at a time scale but (ii) straight movement at a slightly longer time scale could have indicated a local avoidance of residues (i) while quickly crossing the arena (ii).

Interpolation was another means to include long concealed movements when calculating speeds (and not turning angles). In contrast to long rediscretisation, interpolation allowed for the analysis of the concealed movement effects regardless of time scale because it could be combined with both short or long rediscretisation values. This approach relies on the ability of the device to successfully track individual movements between residues and proved relevant for the analysis of speeds on larger time scales (5 to 30 s). The comparison of the speeds estimated with interpolation with speeds from another experiment should be done only under the same data handling procedure because linear interpolation may underestimate real speeds over each ground type.

Missing values are a common problem in animal movement tracking. Even the most advanced techniques such as small remote sensing tags [START_REF] O'neal | Tracking Insects with Harmonic Radar: a Case Study[END_REF] or deep learning algorithms [START_REF] Høye | Deep learning and computer vision will transform entomology[END_REF] can lose track of the individual when it is hidden by a complex ground cover such as vegetation. By reconstructing trajectories with different temporal resolutions and with different hypotheses on the behaviour of concealed earwigs, our method suggests a way to address this problem directly.

Slower and more sinuous movements on the residues

Our study shows that the ground type strongly affected the movement of the earwig E. caraibea.

Earwigs moved significantly slower on the residues, with speeds estimated to be two to four times slower than on bare soil (Fig. 7b). These results are particularly robust because they have been found for all the procedures carrying enough data, whether with interpolated or observed trajectories, long or short junction and long or short rediscretisation values.

An increase in the sinuosity of visible movements on residues was also observed for short rediscretisations times of 1 to 5 s (Fig. 8a), i.e., the fine movements of the earwig were more sinuous between (or over) the residues than on bare soil. The residues, therefore, seem to have affected the fine Tracking movements in complex ground types

Conclusion

To our knowledge, the method described in this study is the first to track the movement of nocturnal ground-dwelling arthropods in a realistic environment, with a high temporal resolution, an intermediate spatial extent (1 m²), and over an entire activity cycle. It allowed us to estimate the slowdown and increase in sinuosity of earwig movements on a complex ground cover. The technical solutions we set-up aimed to investigate how a terrestrial arthropod was affected by different ground types. Because they are based on generic principles, we think they are of great interest for the recent growing field of video monitoring and movement ecology. The relatively low cost of the cameras and the free software made it an inexpensive solution, easy to set up and replicate.

Fig. 1 :

 1 Fig. 1: Experimental design for monitoring E. caraibea movements in heterogeneous environments: a. arena diagram, b. and d. photos of the "residues" arena, c. and e. photos of the "bare soil" arena. d. and e. images extracted from infrared night-time videos.

Fig. 2 :

 2 Fig. 2: Picture of a tagged earwig E. caraibea (personal picture)

Fig. 3 :

 3 Fig. 3: The successive steps to extract trajectories and estimate movement parameters. Each step is illustrated with a 30 minute-long data selection from both "residues" and "bare soil" treatments. a. Images representing the maximum intensity obtained for each pixel over a video of 30 min after stationary background and background noise subtraction. b. Locations extracted via the TrackMate plugin and after cleaning with R software. Examples of trajectories obtained with a specific procedure: c. a short junction (criteria 10 s, 50 pixels) with a rediscretisation at 1 s without interpolation , and d. a long junction between trajectories (criteria 5 min, 50 pixels) and a rediscretisation at 5 s with interpolation ( for definitions, see section 2.4).

  The videos were treated twice to increase contrast between the moving individuals and the heterogeneous background. The first treatment consisted in subtracting an image of the stationary background from each image of the video. Images summarizing the background were created by calculating the median value (intensity) of each pixel over every 30 minutes of video. This treatment produced images with the tag of moving individuals in light grey -white on a black background.Those images still contained residual noise in the background that may have been caused by microvariations in light intensity, micromovements in the substrate, or by noise in the camera's infrared light sensors. The second treatment consisted in subtracting an image of this background noise, approximated from the sum of pixel intensities over every 30 minutes of video. The sum of intensities reached a high value for the pixels that frequently recorded low intensities (dark grey static background noise) and a low value for the pixels that remained black or exhibited rare periods with high intensities (light grey moving individuals). This treatment thus preserved more contrasting black and white images by decreasing pixel intensities mostly for background noise and only slightly for moving individuals (see Fig.3aand videos extracts in Appendix D).

Fig. 4 :

 4 Fig. 4: Diagram of the junction of two trajectories according to junction criteria dg (distance gap) and tg (time gap)

Fig. 5 :

 5 Fig. 5: Trajectory procedure scheme for rediscretisation at 1 or 5 s, with or without interpolation. The segments for calculating distances and examples of turning angles are shown for each procedure. Interpolation was performed before rediscretisation. Consequently, point 15 (Fig. 5d) is taken from the interpolated point 15 (Fig. 5b) and not by linear interpolation between points 10 and 20.

  interpolation, rediscretisation) may affect the values of movement variables describing the paths (i.e., distances and turning angles). Long junction values (tg) allow the inclusion into the trajectories of longer times spent under the residues but may lead to a higher occurrence of missing values within the trajectories. Every rediscretisation value reveals the individual movement at a different scale and requires a different interpretation. Short rediscretisation values indicate the detailed individual trajectory and permit the calculation of mobility parameters like maximum velocity. Long rediscretisation values reveal individual net displacement over the corresponding period, allowing the inclusion into the trajectories of longer times spent under the residues in the limits permitted by the dimensions of the arena. Linear interpolation makes it possible to keep all the information in a trajectory but artificially translates time spent under the residues into a straight displacement of equivalent velocity. This can cause underestimation of average speed and sinuosity, for short rediscretisation in particular. Because of the strong impact interpolation can have on sinuosity, the calculation of turning angles was only performed on trajectories without interpolation.

Fig 6 :

 6 Fig 6: Average number of movement variables sampled per individual according to ground type (colour) and procedure. a. and b. show the number of distances and turning angles, respectively. The grey banner of the four subsections indicates the junction time gaps. The full circles represent the procedures that were used for the statistical comparison. The plus symbols represent the procedures with too few individuals with enough values of movement variables.

Fig. 8 :

 8 Fig. 8: Effect of ground type and rediscretisation (1 or 5 s) on the earwig's turning angles distribution (procedures without interpolation and a junction at 10 s). a. inter-individual mean (± standard errors) of turning angles concentration according to ground type (colour) and rediscretisation value. The significance of the ground type effect on the concentration is represented by:"***" p < 0.001. The circular plots b., c., d. and e. indicate inter-individual median, first quartile and third quartile of the number of turning angles per earwig for each 10°according to ground type and rediscretisation value. Turning angles are expressed in radians which means that positive value are left and negative values are right.

Acknowledgements

This work was supported by INRAE (French National Research Institute for Agriculture, Food and Environment), CIRAD (French Agricultural Research Centre for International Development), and the STRADIV project (n° 1504-003) funded by the Agropolis foundation.

We want to thank the CIRAD centre in Martinique for providing us with equipment and several rooms and the many researchers, engineers, and technicians from the Centre who took the time to answer our many questions.

Data Accessibility

Cleaned trajectories : CIRAD dataverse, doi: https://doi.org/10.18167/DVN1/NPWMUP

Tracking movements in complex ground types

Turning angle

The sinuosity of a trajectory increases as the concentration of turning angles decreases. Trajectories obtained for short rediscretisation (1 and 5 s) showed significantly higher sinuosities on the residues than the bare soil, caused by smaller concentrations (Fig. 8). For the 5 s rediscretisation, concentrations were almost twice as large on bare soil (inter-individual mean ± standard deviation: 0.40 ± 0.16 on residues and 0.77 ± 0.14 on bare soil, p-value < 10 -3 , statistic = 219.81; Fig. 8a). movements of the earwigs, speeds, and sinuosity, even when earwigs were visible and not hidden under residues.

Furthermore, a larger slowdown on residues was estimated when concealed movements were included in the speed's calculation (large rediscretisation values, Fig. 7b or interpolated trajectories with long junctions, Fig. 7b), confirming that accounting for concealed movements matters. Earwigs seem to move slower or more sinuously (or both) under the residues than between them. Although procedures with long junction and interpolation must be interpreted with more care, the highest estimated slowdown of the earwigs (up to four times; Fig. 7b) obtained for the procedure with interpolation and with the longest junction value (5 min) indicates that earwigs likely stayed hidden for more than 1 min and that this stay strongly slowed down their exploration of the arena. Since the residues hid the earwig's movement from the camera, we expected longer concealed periods on residues. However, the signal loss caused by residues could not account for the strong slowdown by itself (see detailed analysis in Appendix J). Those long periods under residues suggest that residues have not simply slowed down the movements of earwigs as mere obstacles to movement (i.e., a barrier effect) but have caused a behaviour change, possibly related to the perception of safety (shelter).

The slowdown and sinuosity of earwigs on residues observed in the present study are consistent with findings on mammals [START_REF] Beisner | Movement ecology in a captive environment: the effects of ground substrate on movement paths of captive rhesus macaques, Macaca mulatta[END_REF][START_REF] Morales | Extracting more out of relocation data: building movement models as mixtures of random walks[END_REF], birds (Da Silveira et al., 2016) and flying insects [START_REF] Schtickzelle | Quantitative analysis of changes in movement behaviour within and outside habitat in a specialist butterfly[END_REF] that show more sinuous and slower movements in their habitats in comparison to unsuitable environments. Such behaviour is also supported by the optimal foraging theory according to which animals slow down in food rich areas to maximise their yield of food [START_REF] Andersson | Optimal foraging area -size and allocation of search effort[END_REF][START_REF] Bell | Searching Behaviour -The behavioural ecology of finding ressources, Chapman and hall animal behaviour series[END_REF] or by the effect of random patterns on animal cognition that increase exploratory behaviour [START_REF] Anselme | Enhanced exploratory activity in woodlice exposed to random visuo-tactile patterns[END_REF]. That increased slowdown and sinuosity observed in absence of food resources suggests that ground type quality per se can have a strong effect on the movement of ground-dwelling arthropods and confirms the importance to consider the effect of more realistic ground types on their movement. Such knowledge, combined with modelling, can be of great importance to optimise the spatial distributions of their habitats for pest management practices such as conservation biological control [START_REF] Collard | Spatial organisation of habitats in[END_REF].

Conflicts of interest statement

The authors declare no conflicts of interest.

Authors contribution statements

BC, TD, PT, DC and CL conceived the ideas and designed methodology; BC collected the data; BC and TD analysed the data; BC and TD led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication.