Biodiversity Data Journal :
Data Paper (Biosciences)
|
Corresponding author: Isabelle Lebert (isabelle.lebert@inrae.fr), Alain Butet (alain.butet@univ-rennes1.fr), Karen D. McCoy (karen.mccoy@ird.fr), Hélène Verheyden (helene.verheyden@inra.fr)
Academic editor: Jenő Kontschán
Received: 14 Jan 2020 | Accepted: 27 Apr 2020 | Published: 05 May 2020
© 2020 Isabelle Lebert, Albert Agoulon, Suzanne Bastian, Alain Butet, Bruno Cargnelutti, Nicolas Cèbe, Amélie Chastagner, Elsa Léger, Bruno Lourtet, Sébastien Masseglia, Karen McCoy, Joël Merlet, Valérie Noël, Grégoire Perez, Denis Picot, Angélique Pion, Valérie Poux, Jean-Luc Rames, Yann Rantier, Hélène Verheyden, Gwenael Vourc'h, Olivier Plantard
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Lebert I, Agoulon A, Bastian S, Butet A, Cargnelutti B, Cèbe N, Chastagner A, Léger E, Lourtet B, Masseglia S, McCoy KD, Merlet J, Noël V, Perez G, Picot D, Pion A, Poux V, Rames J-L, Rantier Y, Verheyden H, Vourc'h G, Plantard O (2020) Distribution of ticks, tick-borne pathogens and the associated local environmental factors including small mammals and livestock, in two French agricultural sites: the OSCAR database. Biodiversity Data Journal 8: e50123. https://doi.org/10.3897/BDJ.8.e50123
|
|
In Europe, ticks are major vectors of both human and livestock pathogens (e.g. Lyme disease, granulocytic anaplasmosis, bovine babesiosis). Agricultural landscapes, where animal breeding is a major activity, constitute a mosaic of habitat types of various quality for tick survival and are used at different frequencies by wild and domestic hosts across seasons. This habitat heterogeneity, in time and space, conditions the dynamics of these host-vector-pathogen systems and thus drives acarological risk (defined as the density of infected ticks). The principal objective of the OSCAR project (2011-2016) was to examine the links between this heterogeneity and acarological risk for humans and their domestic animals. Here, we present the data associated with this project.
This paper reports a database on the distribution and densities of I. ricinus ticks - the most common tick species in French agricultural landscapes - and the prevalence of three tick-borne pathogens (Anaplasma phagocytophilum, Borrelia spp. and Babesia spp.) in two sites in north-western (“Zone Atelier Armorique”: ZA site) and south-western (“Vallées et Coteaux de Gascogne”: VG site) France. The distribution and density of ticks along a gradient of wooded habitats, as well as biotic variables, such as the presence and abundance of their principal domestic (livestock) and wild hosts (small mammals), were measured from forest cores and edges to more or less isolated hedges, all bordering meadows. Ticks, small mammals and information on local environmental conditions were collected along 90 transects in each of the two sites in spring and autumn 2012 and 2013 and in spring 2014, corresponding to the main periods of tick activity. Local environmental conditions were recorded along each tick and small mammal transect: habitat type, vegetation type and characteristics, slope and traces of livestock presence. Samples consisted of questing ticks collected on the vegetation (mainly I. ricinus nymphs), biopsies of captured small mammals and ticks fixed on small mammals. In the VG site, livestock occurrence and abundance were recorded each week along each tick transect.
A total of 29004 questing ticks and 1230 small mammals were captured during the study across the two sites and over the five field campaigns. All questing nymphs (N = 12287) and questing adults (N = 646) were identified to species. Ticks from small mammals (N = 1359) were also identified to life stage. Questing nymphs (N = 4518 I. ricinus) and trapped small mammals (N = 908) were analysed for three pathogenic agents: A. phagocytophilum, Borrelia spp. and Babesia spp.
In the VG site, the average prevalence in I. ricinus nymphs for A. phagocytophilum, Borrelia spp. and Babesia spp. were, respectively 1.9% [95% CI: 1.2-2.5], 2.5% [95% CI: 1.8-3.2] and 2.7% [95% CI: 2.0-3.4]. In small mammals, no A. phagocytophilum was detected, but the prevalence for Borrelia spp. was 4.2% [95% CI: 0.9-7.5]. On this site, there was no screening of small mammals for Babesia spp. In ZA site, the average prevalence in nymphs for A. phagocytophilum, Borrelia spp. and Babesia were, respectively 2.2% [95% CI: 1.6-2.7], 3.0% [95% CI: 2.3-3.6] and 3.1% [95% CI: 2.5-3.8]. In small mammals, the prevalence of A. phagocytophilum and Borrelia spp. were, respectively 6.9% [95% CI: 4.9-8.9] and 4.1% [95% CI: 2.7-5.9]. A single animal was found positive for Babesia microti at this site amongst the 597 tested.
Ticks, Ixodes ricinus, small mammals, Apodemus sylvaticus, Myodes glareolus, prevalence, Anaplasma, Borrelia, Babesia, France, forest, agricultural landscapes, livestock, zoonotic disease
In agricultural landscapes, where livestock production occupies a large proportion of the surface area, pastures often adjoin different semi-natural ecosystems (forests, woods, hedges). This type of landscape mosaic implies that areas exploited by livestock are also frequently used by a diverse range of wild fauna. Many parasites and pathogens are shared amongst these animal species, even in the absence of direct contact and some may be transmitted between agricultural and semi-natural systems via common arthropod vectors. In France, ticks are major vectors for both human (e.g. Borrelia burgdorferi s.l., the agent of Lyme disease) and livestock pathogens (e.g. Anaplasma phagocytophilum, inducing granulocytic anaplasmosis or Babesia divergens, causing bovine babesiosis), with Ixodes ricinus being the most commonly-involved vector.
I. ricinus is a three-stage tick that feeds on a wide variety of vertebrate hosts (
Agricultural landscapes constitute a mosaic of habitat types that vary in quality for tick survival and host use. The habitat composition of a given plot and its connection with other habitats will determine its use by wild vertebrates and will thus shape local tick-host interactions (
The main goal of the OSCAR project (Outil de Simulation Cartographique à l’échelle du paysage Agricole du Risque acarologique / Simulation Tool for Mapping Acarological Risk in Agricultural Landscapes) was to explore the relationships between landscape structure and acarological risk. The study was carried out in two agricultural sites that are part of the International Long-Term Ecological Research (ILTER) network (Zones Ateliers network in France http://www.za-inee.org/en/node/804) and encompass the intrinsic diversity of agricultural landscape features: one LTER site - the “Zone Atelier Armorique” (“ZA site” hereafter) - in north-western France and the second in south-western France in the region of “Vallées et Coteaux de Gascogne” (“VG site” hereafter, belonging to the recently labelled “Zone Atelier PyGar"). Before conducting analyses, the initial task of the OSCAR project consisted of mapping the distribution of ticks, pathogens and the principal domestic (cattle) and wild (small mammals and roe deer) hosts, along a gradient of landscape fragmentation, from forest cores and edges to more or less isolated hedges, all bordering meadows. This paper describes the collected datasets (Fig.
Type of collected data used to study the relationships between landscape structure and acarological risk (i.e. density of infected ticks). Dataset origins: in bold, datasets presented in the datapaper; (*) collected in the field or analysed in the laboratory; (+) calculated from field data; (o) obtained from independent databases. Data uses: [1] response variables: pathogen prevalence in ticks, tick densities, tick population structure; [2] explanatory variables.
Laboratories involved: § BIOEPAR, # CEFS, ¶ MIVEGEC, ‡ EPIA, | ECOBIO, 1 UMR CBGP Montpellier
Coordinator of the project: Plantard O. §
Task managers of the project: Vourc’h G. ‡ (Sampling, biological analyses and database constitution), McCoy K.D. ¶ (Empirical estimation of factors influencing acarological risk from field data), Hoch T. § (Simulating acarological risk maps according to environmental changes)
Site managers and contacts for samplings: Verheyden H. # for the VG (‘‘Vallées et Coteaux de Gascogne’’) LTER site and Butet A. | for the ZA (“Zone Atelier Armorique”) LTER site.
Data management and Geographic Information System (GIS): Agoulon A. §, Bastian S. §, Dorr N. ‡, Lebert I. ‡, Lourtet B. #, Mahé H. §, Rantier Y. |
Sample collection
VG site: Angibault J. #, Bailly X. ‡, Bard E. ‡, Bastian S. §, Cargnelutti B. #, Cebe N. #, Chastagner A. ‡, Delrue B. §, Lebert I. ‡, Léger E. ¶, Lourtet B. #, Mahé H. §, Masseglia S. ‡, McCoy K.D. ¶, Merlet J. #, Noël V. ¶, Perez G. §,|, Picot D. #, Pion A. ‡, Poux V. ‡, Quillery E. §, Toty C. ¶, Vaumourin E. ‡, Verheyden H. #, Vincent S. ‡, Vourc'h G. ‡
ZA site: Agoulon A. §, Al Hassan D. |, Armand F. §, Audiart J.-Y. §, Bastian S. §, Billon D. §, Bouju-Albert A. §, Boullot F. §,|, Bruneau A. §, Butet A. |, Daniel J. §, de la Cotte N. §, Delrue B. §, Faille F. §, Gonnet M. ‡, Hermouet A. §, Hoch T. §, Jambon O. |, Jouglin M. §, Lemine-Brahim M. §, Mahé H. §, Moreau E. §, Navarro N. §, Pavel I. §, Perez G. §,|, Plantard O. §, Quillery E. §, Rantier Y. |, Renaud J. §, Roy P. §
Identification of small mammals
VG site: Bastian S. §, Butet A. |, Cèbe N. #, Chastagner A. ‡, Cosson J. 1, Léger E. ¶, Masseglia S. ‡, McCoy K.D. ¶, Noël V. ¶, Perez G. §,|, Vaumourin E. ‡, Vourc'h G. ‡
ZA site: Butet A. |, Perez G. §,|, Agoulon A. §, Bastian S. §, Bouju-Albert A. §, Gonnet M. ‡, Hermouet A. §, Moreau E. §, Pavel I. §, Plantard O. §
Tick identification
VG site: Pion A. ‡, Poux V. ‡
ZA site: Agoulon A. §, Bouju-Albert A. §, Hermouet A. §, Plantard O. §
Laboratory analysis
VG site: Chastagner A. ‡, Masseglia S. ‡, McCoy K.D. ¶, Noël V. ¶, Léger E. ¶
ZA site: Bouju-Albert A. §, Daniel J. §, Faille F. §, Hermouet A. §, Jouglin M. §, Léger E. ¶, McCoy K.D. ¶, Noël V. ¶, Perez G. §,|, Quillery E. §
Livestock survey: (VG site only): Angibault J. #, Cargnelutti B. #, Lourtet B. #, Sevila J. #, Verheyden H. #
LTER site “Vallées et Coteaux de Gascogne” (VG site)
The VG site is a Long Term Ecological Research (LTER) site (referenced as zone atelier Pyrénées Garonne - PYGAR since 2016, https://pygar.omp.eu/), located 75 km from Toulouse in south-western France (
Map of the two studied sites in France: the “Vallées et Coteaux de Gascogne” LTER site (VG) and the “Zone Atelier Armorique” LTER site (ZA). Landscape types: LH, Agricultural landscapes with a Low Hedgerow network density; HH, Agricultural landscapes with a High Hedgerow network density; FE, Forest Edge; FC, Forest Core. A single label per landscape type was drawn on the map (LH, HH, FE, FC), but corresponds to several sampling points in the field. For example, for the FE label, 20 sampling points were designated around the forest (see Fig.
LTER site “Zone atelier Armorique” (ZA site)
The ZA site (https://osur.univ-rennes1.fr/za-armorique) (Fig.
The study was performed in the two LTER sites (ZA and VG) from 2012 to 2014. Questing ticks and small mammals were sampled during five field campaigns: spring and autumn 2012, spring and autumn 2013 and spring 2014. The sampling design is presented in Fig.
A Schematic representation of single and associated sampling transects of ticks and small mammals in the different landscape types.
B Details of:
- questing tick transect-lines, where the drag transect was subdivided into sub-transects
- small mammal trap-lines, which contained 34 traps spaced 3 m apart across the initial part of a subset of tick transects
Landscape types:
LH, Agricultural landscapes with a Low Hedgerow network density
HH, Agricultural landscapes with a High Hedgerow network density
FE, Forest Edge
FC, Forest Core
The sampling zones (n = 60) were located in 4 landscape types: Agricultural landscapes with a Low Hedgerow network density (LH); Agricultural landscapes with a High Hedgerow network density (HH); Forest Edge (FE); and Forest Core (FC) (Fig.
Questing ticks were sampled in all 60 zones (including the 24 zones for small mammal sampling). In each zone, one or two transect-lines were defined: 1) a single transect-line was sampled when found along hedgerows and in FC; 2) two transect-lines were run when situated at wood and forest edges (i.e. on either side of the ecotone: one in the meadow and one in the forest) (Fig.
The design was fully applied (60 sampling zones) in four campaigns (spring and autumn 2012, spring 2013 and 2014), but only 36 transect lines from the 24 zones used to quantify small mammal presence were sampled during autumn 2013, corresponding to an optimisation of the sampling effort during a less favourable period of tick activity.
Recording local environmental conditions
Georeferencing of sampling locations of ticks (Table
Field |
Description |
Type |
ECHT_ID |
Identifier for tick sub-transect line: campaign - site - landscape type - transect line number - sub-transect line number |
Text (50 c.) |
X_CENTRE |
X coordinate of the sub-transect centroid (RGF93_Lambert_93, EPSG 2154) |
Real (19, 11) |
Y_CENTRE |
Y coordinate of the sub-transect centroid (RGF93_Lambert_93, EPSG 2154) |
Real (19, 11) |
ECHT_ECHLT |
Identifier for the transect: campaign - site -landscape type - transect line number |
Text (50 c.) |
LENGTH |
Length of the sub-transect (metres) |
Real (13, 11) |
LATITUDE |
Decimal Latitude of the sub-transect centroid (WGS84; EPSG 4326) |
Real (10, 7) |
LONGITUDE |
Decimal Longitude of the sub-transect centroid (WGS84; EPSG 4326) |
Real (10, 7) |
Field |
Description |
Type |
X_CENTRE |
X coordinate of the trap-line centroid (RGF93_Lambert_93, EPSG 2154) |
Real (18, 11) |
Y_CENTRE |
Y coordinate of the trap-line centroid (RGF93_Lambert_93, EPSG 2154) |
Real (18, 11) |
LENGTH |
Length of the trap-line (metres) |
Real (12, 11) |
ECHLM_ID |
Identifier of the trap-line: campaign - site - landscape type - trap-line number |
Text (15 c.) |
LATITUDE |
Decimal Latitude of the sub-transect centroid (WGS84; EPSG 4326) |
Real (10, 7) |
LONGITUDE |
Decimal Longitude of the sub-transect centroid (WGS84; EPSG 4326) |
Real (10, 7) |
Field description of the dataset including the characteristics of the tick transect lines. c., characters.
Field |
Description |
Type |
ZONE_ID |
Identifier of the LTER site (VG or ZA) |
Text (5 c.) |
SECT_CODE |
Identifier for the landscape type: forest core (FC, CF in table), forest edge (FE, LF in table), agricultural landscape with a high hedgerow network density (HH, BD in table), agricultural landscape with a low hedgerow network density (LH, BO in table) |
Text (5 c.) |
LTIQ_ID |
Identifier for the transect line: site - landscape type - transect line number |
Text (20 c.) |
ECHLT_ID |
Identifier for the transect line: campaign - site - landscape type - transect line number |
Text (20 c.) |
ECHT_ID |
Identifier for tick sub-transect line: campaign - site - landscape type - transect line number - sub-transect line number |
Text (30 c.) |
ECHLT_DATE |
Sampling date for a transect |
Date/Time |
ECHLT_SAISON |
Identifier for campaign (1 = spring 2012, 2 = autumn 2012, 3 = spring 2013, 4 = autumn 2013, 5 = spring 2014) |
Integer |
ECHLT_HDEB |
Starting hour of tick sampling in the transect |
Date/Time |
ECHLT_HFIN |
Ending hour of tick sampling in the transect |
Date/Time |
ECHLT_SOL |
Land use: 1 = meadow, 2 = wood, 3 = forest, 4 = meadow/hedge, 5 = meadow/wood, 6 = meadow/forest |
Boolean |
ECHLT_PHERBH |
Average height of the grass in the meadow landscape (cm) |
Integer |
ECHLT_BHERBH |
Average height of the grass in the wood landscape (cm) |
Integer |
ECHLT_FHERBH |
Average height of the grass in the forest landscape (cm) |
Integer |
ECHLT_FTYPE |
Forest type: 1 = deciduous, 2 = coniferous, 3 = mixed |
Boolean |
ECHLT_HHERB |
Wet grass: 1 = yes, 0 = no |
Boolean |
ECHLT_ANIP |
Presence of livestock on the pasture: 1 = yes, 0 = no |
Boolean |
Field description of the dataset including characteristics of tick sampling in each tick sub-transect. c., characters.
Field |
Description of the sub-transect |
Type |
ECHT_ID |
Identifier for the tick sub-transect |
Text (30 c.) |
ECHT_ECHLT_ID |
Key to Table 3 |
Text (20 c.) |
ECHT_TIR |
Identifier of sub-transect |
Text (3 c.) |
ECHT_HERB_MOY |
Average height of the grass in the sub-transect (cm) |
Boolean |
ECHT_HERB_DENS |
Grass in the sub-transect: 1 = none, 2 = sparse, 3 = dense |
Boolean |
ECHT_SOL_HUM |
Soil humidity: 1 = dry, 2 = slightly wet, 3 = presence of water |
Real |
ECHT_HERB_VER |
Green colour of the grass: V = green on 2/3 of the sub-transect, J = yellow on 2/3 of the sub-transect, M = mixed, NP = not relevant if no grass |
Text (3 c.) |
ECHT_PFEUIL |
Presence of dead leaves: 1 = yes, 0 = no |
Boolean |
ECHT_JONC |
Presence of rush: 1 = yes, 0 = no |
Boolean |
ECHT_RONC |
Presence of bramble: 1 = yes, 0 = no |
Boolean |
ECHT_IND_VEG |
Vegetation index (hedge or wood): 1 = no hedge, 2 = discontinuous hedge, 3 = continuous hedge not deeper than 2 m, 4 = deeper hedge, between 2 and 5 m, 5 = hedge deeper than 5 m or wood |
Boolean |
ECHT_PARASOL |
Misaligned parasol above sampling: A = no branches (no parasol), F = dense branches over less than 2/3 of the sub-transect, D = dense branches over more than 2/3 of the sub-transect |
Text (1 c.) |
ECHT_TALU |
Presence of a bank: 1 = yes, 0 = no |
Boolean |
ECHT_DT_TALU |
Distance between the bank and the sub-transect (metres) |
Real |
ECHT_HT_TALU |
Bank height (metres) |
Real |
ECHT_NB_LIRLA |
Number of Ixodes ricinus larvae |
Boolean |
ECHT_NB_LIRNY |
Number of Ixodes ricinus nymphs |
Boolean |
ECHT_NB_LIRADM |
Number of Ixodes ricinus male adults |
Boolean |
ECHT_NB_LIRADF |
Number of Ixodes ricinus female adults |
Boolean |
ECHT_NB_LIFNY |
Number of Ixodes frontalis nymphs |
Boolean |
ECHT_NB_IRADND |
Number of adult Ixodes ricinus ticks (male or female) |
Boolean |
Field description of the dataset including characteristics of the small mammal trap-lines. c., characters.
Field |
Description |
Type |
ZONE_ID |
Identifier of the LTER site (VG or ZA) |
Text (5 c.) |
SECT_CODE |
Identifier of the landscape type: forest core (FC, CF in table), forest edge (FE, LF in table), landscape with high hedgerow network density (HH, BD in table), landscape with low hedgerow network density (LH, BO in table) |
Text (5 c.) |
ECHLM_ID |
Identifier of the trap-line: campaign - site - landscape type - trap-line number |
Text (30 c.) |
ECHLM_DATE |
Sampling date for placing the traps |
Date/Time |
ECHLM_SITLIG |
Trap-line place (interface): 1 = meadow/hedge, 2 = meadow/wood, 3 = meadow/forest, 4 = forest |
Boolean |
ECHLM_TYP_PRAI |
Meadow type: 1 = grasses, 2 = mowing meadow, 3 = other |
Boolean |
ECHLM_HCONT |
Continuity of the hedge: 1 = continuous, 2 = not continuous |
Boolean |
ECHLM_HDENS |
Hedge density: 1 = dense, 2 = slightly dense |
Boolean |
ECHLM_HBERB |
Presence of herbaceous layer in hedge: 1 = yes, 0 = no |
Boolean |
ECHLM_HARBU |
Presence of shrub layer in hedge: 1 = yes, 0 = no |
Boolean |
ECHLM_HARBO |
Presence of arborescent layer in hedge: 1 = yes, 0 = no |
Boolean |
ECHLM_HLSOL |
Width of the hedge at the level of the ground, in the hedge (metres) |
Integer |
ECHLM_HLCAN |
Width of the canopy above the hedge (metres) |
Boolean |
ECHLM_BHERB |
Presence of a herbaceous layer in the woods: 1 = yes, 0 = no |
Boolean |
ECHLM_BARBU |
Presence of shrub layer in the woods: 1 = yes, 0 = no |
Boolean |
ECHLM_BARBO |
Presence of arborescent layer in the woods: 1 = yes, 0 = no |
Boolean |
ECHLM_BDENS |
Wood density: 1 = dense, 2 = slightly dense |
Boolean |
ECHLM_BTYPE |
Wood type: 1 = deciduous, 2 = coniferous, 3 = mixed |
Boolean |
ECHLM_FHERB |
Presence of herbaceous layer in forest: 1 = yes, 0 = no |
Boolean |
ECHLM_FARBU |
Presence of shrub layer in forest: 1 = yes, 0 = no |
Boolean |
ECHLM_FARBO |
Presence of arborescent layer in forest: 1 = yes, 0 = no |
Boolean |
ECHLM_FDENS |
Forest density: 1 = dense, 2= slightly dense |
Boolean |
ECHLM_FTYPE |
Forest type: 1 = deciduous, 2 = coniferous, 3 = mixed |
Boolean |
ECHT_ID |
Identifier for small mammal trap-line and checking number |
Text (30 c.) |
ECHT_REL_COD |
Identifier of trap checks: R1 = 24 h, R2 = 48 h |
Text (5 c.) |
ECHT_DATE |
Day of trap check |
Date/Time |
ECHT_NUAGE |
Cloud cover: 0 = blue sky, 1 = 1/4 cloud cover, 2 = half covered, 3 = 3/4 covered, 4 = completely covered |
Integer |
ECHT_VENT |
Presence of wind: 0= no wind, 1 = light wind, 2 = discontinuous, 3 = strong |
Boolean |
ECHT_ANIM |
Presence of livestock in the field: 1 = yes, 0 = no |
Boolean |
ECHT_ESP |
Animal types: 1 = cattle, 2 = sheep, 3 = horse, 4 = other |
Boolean |
ECHT_NB_ANI |
Number of animals in the field |
Boolean |
ECHT_PRES_MAM |
Small mammal sign: 1 = yes, 0 = no |
Boolean |
ECHT_PIEGE_NOT_OK |
Traps disturbed or closed without capture: 1 = yes, 0 = no |
Boolean |
ECHT_PIEGE_NB |
Number of traps disturbed or closed without capture (between 1 and 34) |
Integer |
Field description of the dataset concerning small mammal sampling and identification. c., characters.
Field |
Description |
Type |
MAM_ID |
Identifier of the trapped small mammals: campaign - site - landscape type - trap-line number - small mammal number |
Text (30 c.) |
MAM_ECHM_ID |
Identifier for small mammal trap-line and check number |
Text (30 c.) |
MAM_DATE |
Autopsy day |
Date |
MAM_SEXE |
Identifier for sex: 1 = Male, 2 = Female |
Boolean |
MAM_SANG |
Blood sampling: 1 = yes, 0 = no |
Boolean |
MAM_SMETHO |
Blood sampling method: IC = intracardiac, RO = retro-orbital |
Text (2 c.) |
MAM_PDSENT |
Small mammal weight before autopsy (g) |
Integer |
MAM_STAD |
Small mammal stage: 1 = juvenile, 2 = sub-young, 3 = adult |
Boolean |
MAM_LTEST |
Testicule length |
Boolean |
MAM_GESTANT |
Pregnant female: 1 = yes, 0 = no |
Boolean |
MAM_NB_F |
If pregnant = yes, number of fœtuses |
Boolean |
MAM_ALLAIT |
Lactating female: 1 = yes, 0 = no |
Boolean |
MAM_PRELEV_ORE |
Ear sample: 1 = yes, 0 = no |
Boolean |
MAM_PRELEV_FOIE |
Liver sample: 1 = yes, 0= no |
Boolean |
MAM_PRELEV_RNA |
RNA sample from spleen: 1 = yes, 0 = no |
Boolean |
MAM_PRELEV_RATE |
Spleen sample: 1 = yes, 0 = no |
Boolean |
MAM_CARC_PDIS |
Carcass partially dissected and frozen: 1 = yes, 0 = no |
Boolean |
MAM_NB_TIK |
Total number of ticks on the small mammal |
Boolean |
MAM_NB_TIK_LA |
Total number of larvae on the small mammal |
Boolean |
MAM_NB_TIK_NY |
Total number of nymphs on the small mammal |
Boolean |
MAM_NB_TIK_AD |
Total number of adult ticks on the small mammal |
Boolean |
MAM_TYP_ECTO |
Ectoparasitic species: fleas, mites, lice, fleas + mites, fleas + lice, mites + lice, fleas + mites + lice, ectoparasite species not specified, none |
Text (50 c.) |
LMAM_NOM_LAT |
Species name (Latin) |
Text (50 c.) |
LMAM_NOM_FR |
Species name (French) |
Text (50 c.) |
MAM_ID |
Identifier of the trapped small mammals: campaign - site - landscape type - trap-line number - small mammal number |
Text (30 c.) |
MAM_ECHM_ID |
Identifier for small mammal trap-line and check number |
Text (30 c.) |
Sampling of questing ticks
Questing ticks (Fig.
Field description of the dataset concerning the analyses of tick DNA for infectious agents. c.: characters
Field |
Description |
Type |
ECHLT_ID |
Identifier of the transect: season-site-landscape-transect number - Identifier for campaign (1 = spring 2012, 3 = spring 2013) |
Text (20 c.) |
ECHLT_DATE |
Sampling date for a transect |
Date/Time |
ECHT_ID |
Identifier for the tick transect -subtransect: campaign - site - landscape - transect number - sub-transect number |
Text (30 c.) |
TIQ_ID |
Identifier for a tick |
Text (30 c.) |
ANA_RESULT1 |
Result method 1: detection of Anaplasma from tick DNA (yes = 1, no = 0) |
Boolean |
ANA_RESULT2 |
Result method 2: detection of Anaplasma from tick DNA (yes = 1, no = 0) |
Boolean |
ANA_CO_SEQ |
Sequencing analysis: obtained sequence for Anaplasma (yes = 1, no = 0) |
Boolean |
BOR_RESULT |
Result: detection of Borrelia from tick DNA (yes = 1, no = 0) |
Boolean |
BOR_CO_SEQ |
Sequencing analysis: obtained sequence for Borrelia (yes = 1, no = 0) |
Boolean |
BOR_REM |
Remark: assignment to a species |
Memo |
BAB_RESULT |
Result: detection of Babesia by PCR from tick DNA (yes = 1, no = 0) |
Boolean |
BAB_CO_SEQ |
Sequencing analysis: obtained sequence for Babesia (yes = 1, no = 0) |
Integer |
BAB_CO_REM |
Remark: assignment to a species |
Memo |
Sampling of small mammals
The 100 m trap-line contained 34 INRAE live-traps, fitted with dormitory boxes and baited with a mixture of seeds and fresh apple. After placement, the traps were checked in the morning 24- and 48-hours after setup (Figs
Molecular analyses
Field description of the dataset concerning the analyses of infectious agents from small mammals. c.: characters.
Field |
Description |
Type |
ECHLM_ID |
Identifier of the trap-line: campaign - site - landscape type - trap-line number |
Text (30 c.) |
ECHLM_DATE |
Sampling date for the placement of traps |
Date/Time |
MAM_ID |
Identifier of the trapped small mammals: campaign - site - landscape type - trap-line number - small mammal number |
Text (30 c.) |
LMAM_NOM_LAT |
Species name |
Text (50 c.) |
BOOR_RESULT_PCR |
Result: detection of Borrelia from small mammal ear DNA: 1 = yes, 0 = no |
Boolean |
BOOR_SEQ |
Sequencing analysis of Borrelia: 1 = yes, 0 = no |
Boolean |
BOOR_SP |
Species name of Borrelia |
Memo |
ANR_RESULT_QPCR |
Result: detection of Anaplasma from spleen DNA: 1 = yes, 0 = no |
Boolean |
ANR_RA_SEQ |
Sequencing analysis: obtained sequence for Anaplasma (1 = yes, 0 = no) |
Integer |
Livestock survey in VG site
Livestock abundance was measured in the VG site on the pasture adjoining each tick transect-line in 2012 and 2013 (Table
Field description for livestock dataset. c., characters. Heads.day refers to the number of individual animals that were counted in a pasture on a given day.
Field |
Description |
Type |
LTIQ_ID |
Identifier for the transect line: site - landscape type - transect line number |
Text (20 c.) |
BET_ID |
Identifier for livestock |
Text (30 c.) |
BET_SAISON |
Season: spring (week 17 to 26), summer (week 27 to 35), autumn (week 36 to 44) |
Text (10 c.) |
BET_ANNEE |
Year |
Integer |
BET_CUMUL |
Sum of livestock heads.day at pasture over the considered season (spring 70 days, summer 63 days, autumn 63 days) |
Integer |
LBET_ESPECE |
Species name: bovine, caprine, equine, ovine |
Text (20 c.) |
DataBase
All the data of Tables
Relational model for small mammals: relationships between tables concerning small mammal sampling and analyses. Similar colour corresponds to similar data present in two tables. Key is primary key. ECHLM_*, Identifier code for small mammal trap-line; MAM_*, Identifier code for captured small mammal.
The data presented in this dataset are detailed by campaign and by site in Table
Summary of available data in the present dataset according to campaign and site. Identifier for campaigns: 1 = spring 2012, 2 = autumn 2012, 3 = spring 2013, 4 = autumn 2013, 5 = spring 2014.
Site |
VG | ZA | ||||||||
Campaign |
1 |
2 |
3 |
4 |
5 |
1 |
2 |
3 |
4 |
5 |
Local environmental conditions |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
Number of tick transect lines |
90 |
90 |
90 |
36 |
90 |
89 |
89 |
90 |
36 |
90 |
Tick identification |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
Pathogens analysis in ticks |
yes |
no |
yes |
no |
no |
yes |
no |
yes |
no |
no |
Number of small mammal trap-lines |
24 |
24 |
24 |
24 |
24 |
24 |
24 |
24 |
24 |
24 |
Small mammal identification |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
yes |
Pathogens analysis in small mammals |
yes |
yes |
yes |
yes |
no |
yes |
yes |
yes |
yes |
no |
Identification of small mammals ticks |
yes |
yes |
yes |
yes |
no |
yes |
yes |
yes |
yes |
no |
Livestock |
yes |
yes |
yes |
yes |
no |
no |
no |
no |
no |
no |
Variables not included in the datapaper
Information on the infection rate and movement of roe deer in some of the studied habitat types were recorded at the VG site (see, for exemple,
Weather data were obtained from Météo-France weather stations close to ZA (Broualan, Rennes-St Jacques, Pontorson) and VG (Boussan, Fabas, Palaminy) sites. Additional weather data were measured near the VG site at the meteorological weather station (INRAE in SAMAN), located at the UMR DYNAFOR (INRAE-INPT) in Saint-André (F-31420) or near the ZA site at the COSTEL meteorological weather station (CNRS in COSTEL), located in the LEGT RENNES. According to the location, the weather stations were equipped with sensors to measure air and ground temperatures, air humidity, pluviometry, wind speed and direction, relative humidity, atmospheric pressure and light intensity. The data (2011-2014) are available upon request to the corresponding author.
Additional variables were calculated to measure landscape heterogeneity around the sampling locations. These data and their production (ecotone length between wooded habitat and meadows, proportion of woodland cover, grassland cover and crops, mean distance between wooded patches, perimeter-area ratio of wooded patches, connectivity of wooded habitat patch) are presented in
top left 43°22'11,59''N, 0°43'59,17''E;
bottom right: 43°11'41,25''N, 0°59'15,61''E
top left 48°34'20,83''N, 1°19'21,26''W;
bottom right: 48°25'20,46''N, 1°29'56,85''W
Creative Commons CC-BY 4.0
The data concerning questing tick sampling are presented in the 3 following tables.
Table
Table
Table
The date format ISO 8601 (YYYY-MM-DD) was used.
The data concerning small mammal sampling are presented in the 3 following tables.
Table
Table
Table
The date format ISO 8601 (YYYY-MM-DD) was used.
Field description for the livestock dataset (Table
Two tables describing the sample locations for questing ticks (Table
(Associated files: TickTransect.shp and SmallMammalsTrapLine.shp)
We provide a quick description of the results in the following section. A total of 29004 questing ticks and 1230 small mammals were collected during the study at the two sites and over the five campaigns. All questing nymphal (N = 12311) and adult ticks (646) were identified to species. Ticks from small mammals (N = 1359) were also identified to the stage.
During the five campaigns (from spring 2012 to spring 2014), 16047 larvae, 12287 I. ricinus nymphs, 646 I. ricinus adults and 24 Ixodes frontalis nymphs were collected on the vegetation (Table
Number of collected ticks per campaign and per site. No, number; IR, Ixodes ricinus; IF, Ixodes frontalis. Identifier for campaigns: 1 = spring 2012, 2 = autumn 2012, 3 = spring 2013, 4 = autumn 2013, 5 = spring 2014.
Campaign |
Site |
No sampled transect-lines |
No larvae |
No IR nymphs |
No IR adults |
No IF nymphs |
1 |
VG |
90 |
24 |
1588 |
59 |
1 |
1 |
ZA |
89 |
5214 |
2622 |
109 |
7 |
2 |
VG |
90 |
758 |
143 |
11 |
0 |
2 |
ZA |
89 |
3649 |
277 |
22 |
7 |
3 |
VG |
90 |
69 |
932 |
85 |
0 |
3 |
ZA |
90 |
1508 |
3196 |
164 |
0 |
4 |
VG |
36 |
27 |
16 |
8 |
0 |
4 |
ZA |
36 |
867 |
330 |
20 |
4 |
5 |
VG |
90 |
25 |
848 |
69 |
0 |
5 |
ZA |
90 |
3906 |
2335 |
99 |
5 |
Total |
16047 |
12287 |
646 |
24 |
Fig.
Over the study, 335 small mammals were trapped in the VG site (Table
Species name |
Number of captured individuals |
Apodemus sylvaticus |
250 |
Myodes glareolus |
37 |
Crocidura russula |
18 |
Microtus arvalis |
14 |
Sorex coronatus |
11 |
Microtus agrestis |
4 |
Microtus pyrenaicus |
1 |
Total |
335 |
In the VG site, the forest type was mainly deciduous (N = 41) with one mixed forest (including coniferous trees). In the ZA site, collections were performed in 33 deciduous forest type and eight mixed forests. Table
Summary values of local environmental conditions for transects and sub-transects in VG and ZA sites for the 5 field campaigns (1 to 5). Description of the fields are given in Tables
Transects and sub-transects |
Site |
VG |
ZA |
||||||||
Campaign |
1 |
2 |
3 |
4 |
5 |
1 |
2 |
3 |
4 |
5 |
|
Number of tick transect lines |
90 |
90 |
90 |
36 |
90 |
89 |
89 |
90 |
36 |
90 |
|
ECHLT_PHERBH |
Median |
20 |
10 |
50 |
20 |
30 |
45 |
20 |
30 |
13,5 |
60 |
Min |
5 |
5 |
15 |
10 |
5 |
10 |
10 |
10 |
0 |
0 |
|
Max |
60 |
120 |
105 |
50 |
50 |
110 |
50 |
160 |
100 |
110 |
|
ECHLT_BHERBH |
Median |
20 |
15 |
30 |
20 |
30 |
20 |
10 |
10 |
7,5 |
20 |
Min |
5 |
0 |
5 |
5 |
10 |
0 |
5 |
0 |
5 |
0 |
|
Max |
40 |
35 |
60 |
40 |
50 |
80 |
100 |
30 |
15 |
100 |
|
ECHLT_FHERBH |
Median |
20 |
25 |
30 |
22,5 |
25 |
15 |
17,5 |
15 |
10 |
20 |
Min |
0 |
5 |
15 |
5 |
10 |
5 |
5 |
0 |
0 |
5 |
|
Max |
30 |
30 |
55 |
40 |
60 |
20 |
20 |
50 |
30 |
30 |
|
Number of sub-transect |
900 |
900 |
900 |
360 |
900 |
890 |
890 |
900 |
900 |
900 |
|
ECHT_HERB_DENS |
1 |
172 |
161 |
93 |
83 |
64 |
291 |
293 |
254 |
117 |
176 |
2 |
304 |
311 |
282 |
105 |
178 |
193 |
129 |
226 |
97 |
231 |
|
3 |
424 |
428 |
524 |
172 |
657 |
404 |
468 |
420 |
146 |
492 |
|
ND |
0 |
0 |
1 |
0 |
1 |
2 |
0 |
0 |
0 |
1 |
|
ECHT_SOL_HUM |
1 |
282 |
721 |
133 |
344 |
189 |
684 |
807 |
685 |
331 |
731 |
2 |
514 |
141 |
665 |
15 |
634 |
156 |
71 |
195 |
27 |
154 |
|
3 |
104 |
38 |
101 |
0 |
76 |
35 |
12 |
20 |
2 |
14 |
|
ND |
0 |
0 |
1 |
1 |
1 |
15 |
0 |
0 |
0 |
1 |
|
ECHT_HERB_VER |
J |
31 |
224 |
2 |
43 |
0 |
0 |
78 |
61 |
15 |
23 |
M |
147 |
339 |
15 |
59 |
54 |
7 |
134 |
89 |
64 |
34 |
|
ND |
0 |
0 |
1 |
0 |
1 |
14 |
0 |
0 |
0 |
1 |
|
NC |
3 |
14 |
24 |
26 |
1 |
79 |
92 |
103 |
89 |
63 |
|
V |
719 |
323 |
858 |
232 |
844 |
790 |
586 |
647 |
192 |
779 |
|
ECHT_PFEUIL |
0 |
321 |
171 |
433 |
108 |
318 |
385 |
404 |
388 |
118 |
497 |
1 |
579 |
729 |
467 |
252 |
581 |
488 |
473 |
512 |
242 |
403 |
|
ND |
0 |
0 |
0 |
0 |
1 |
17 |
13 |
0 |
0 |
0 |
|
ECHT_JONC |
0 |
878 |
887 |
892 |
354 |
879 |
809 |
789 |
798 |
327 |
761 |
1 |
22 |
13 |
7 |
5 |
20 |
59 |
90 |
102 |
33 |
139 |
|
ND |
0 |
0 |
1 |
1 |
1 |
22 |
11 |
0 |
0 |
0 |
|
ECHT_RONC |
0 |
679 |
627 |
544 |
169 |
574 |
669 |
571 |
684 |
265 |
659 |
1 |
211 |
273 |
353 |
190 |
322 |
200 |
289 |
214 |
94 |
241 |
|
ND |
10 |
3 |
1 |
4 |
21 |
30 |
2 |
1 |
0 |
||
ECHT_IND_VEG |
1 |
6 |
7 |
7 |
1 |
7 |
22 |
13 |
23 |
1 |
16 |
2 |
65 |
69 |
23 |
5 |
22 |
101 |
66 |
99 |
17 |
72 |
|
3 |
37 |
75 |
53 |
15 |
27 |
62 |
62 |
108 |
46 |
112 |
|
4 |
119 |
73 |
98 |
21 |
83 |
68 |
75 |
37 |
8 |
31 |
|
5 |
603 |
596 |
715 |
317 |
679 |
637 |
663 |
633 |
288 |
668 |
|
ND |
70 |
80 |
4 |
1 |
82 |
0 |
11 |
0 |
0 |
1 |
|
ECHT_PARASOL |
A |
247 |
258 |
255 |
82 |
244 |
122 |
151 |
210 |
47 |
123 |
D |
387 |
383 |
483 |
207 |
173 |
327 |
412 |
465 |
205 |
530 |
|
F |
266 |
119 |
162 |
71 |
201 |
370 |
224 |
225 |
104 |
246 |
|
ND |
0 |
140 |
0 |
0 |
282 |
71 |
103 |
0 |
4 |
1 |
|
ECHT_TALU |
0 |
819 |
817 |
828 |
349 |
774 |
698 |
526 |
561 |
169 |
420 |
1 |
81 |
82 |
70 |
10 |
126 |
191 |
295 |
338 |
189 |
477 |
|
ND |
0 |
1 |
2 |
1 |
0 |
1 |
69 |
1 |
2 |
3 |
The livestock survey was performed in the VG site: livestock occurred on 28 of the 90 questing tick transect-lines, cattle being the main species present in pastures (Table
Results of livestock survey in the VG site: sum of heads.day by species at pasture over the considered season (spring = 70 days, summer = 63 days, autumn = 63 days). Transect name (site - landscape type - transect number). Identifier for the landscape type: BD (bocage dense) = agricultural landscape with a high hedgerow network density (HH), BO (bocage ouvert) = agricultural landscape with a low hedgerow network density (LH), LF (Lisière de forêt) = forest edge (FE)
Livestock |
Transect name |
Spring |
Summer |
Autumn |
Total |
bovine |
VG-BD-L002 |
0 |
322 |
413 |
735 |
VG-BD-L004 |
0 |
0 |
56 |
56 |
|
VG-BD-L006 |
420 |
378 |
378 |
1176 |
|
VG-BD-L015 |
0 |
0 |
168 |
168 |
|
VG-BD-L020 |
0 |
0 |
112 |
112 |
|
VG-BD-L032 |
420 |
378 |
378 |
1176 |
|
VG-BD-L033 |
0 |
546 |
364 |
910 |
|
VG-BD-L034 |
0 |
567 |
637 |
1204 |
|
VG-BD-L035 |
112 |
168 |
77 |
357 |
|
VG-BD-L036 |
0 |
126 |
0 |
126 |
|
VG-BD-L044 |
56 |
224 |
56 |
336 |
|
VG-BD-L046 |
0 |
21 |
224 |
245 |
|
VG-BD-L048 |
140 |
77 |
56 |
273 |
|
VG-BD-L050 |
0 |
322 |
560 |
882 |
|
VG-BD-L069 |
147 |
147 |
56 |
350 |
|
VG-BO-L105 |
0 |
126 |
56 |
182 |
|
VG-BO-L109 |
0 |
0 |
182 |
182 |
|
VG-BO-L113 |
0 |
0 |
161 |
161 |
|
VG-BO-L136 |
0 |
0 |
182 |
182 |
|
VG-BO-L140 |
0 |
56 |
0 |
56 |
|
VG-BO-L142 |
0 |
112 |
56 |
168 |
|
VG-BO-L145 |
0 |
0 |
56 |
56 |
|
VG-LF-L201 |
1470 |
1260 |
1400 |
4130 |
|
VG-LF-L202 |
1848 |
567 |
0 |
2415 |
|
VG-LF-L206 |
0 |
0 |
21 |
21 |
|
VG-LF-L207 |
1274 |
742 |
1323 |
3339 |
|
VG-LF-L210 |
210 |
119 |
126 |
455 |
|
VG-LF-L215 |
1321 |
882 |
1358 |
3561 |
|
total |
7418 |
7140 |
8456 |
23014 |
|
caprine |
VG-BD-L002 |
84 |
21 |
84 |
189 |
VG-BO-L145 |
0 |
0 |
21 |
21 |
|
total |
84 |
21 |
105 |
210 |
|
equine |
VG-BD-L002 |
0 |
42 |
63 |
105 |
VG-BD-L033 |
0 |
42 |
63 |
105 |
|
VG-BO-L109 |
56 |
0 |
0 |
56 |
|
total |
56 |
84 |
126 |
266 |
|
ovine |
VG-BD-L002 |
105 |
0 |
105 |
210 |
VG-BO-L145 |
0 |
0 |
21 |
21 |
|
VG-LF-L207 |
56 |
0 |
0 |
56 |
|
total |
161 |
0 |
126 |
287 |
A selected subset of questing nymphs (N = 4518 I. ricinus) and 908 trapped small mammals (N = 300 in VG site and N = 608 in ZA site) were analysed for the three pathogenic agents: A. phagocytophilum, Borrelia spp. and Babesia spp. (Table
Results of A. phagocytophilum, Borrelia spp. and Babesia spp. in nymphs from field campaigns 1 to 3 and in small mammals from field campaigns 1 to 4. No Babesia-positive small mammals were found. n/N, number of positive samples/number of analysed samples; Prev, prevalence in %; 95% CI, in [], 95% Confidence Interval for prevalence.
Questing nymphs |
Small mammals |
|||||
Site |
Pathogens |
A. phagocytophilum |
Borrelia spp. |
Babesia spp. |
A. phagocytophilum |
Borrelia spp. |
VG |
n/N |
35/1891 |
47/1891 |
51/1891 |
0/300 |
6/143 |
Prev 95%CI |
1.9 [1.2-2.5] |
2.5 [1.8-3.2] |
2.7 [2.0-3.4] |
0.0 |
4.2 [0.9-7.5] |
|
ZA |
n/N |
57/2627 |
78/2627 |
82/2627 |
42/608 |
26/606 |
Prev 95%CI |
2.2 [1.6-2.7] |
3.0 [2.3-3.6] |
3.1 [2.5-3.8] |
6.9 [4.9-8.9] |
4.1 [2.7-5.9] |
Pathogen results in I. ricinus nymphs. A. phagocytophilum was detected, respectively in 1.9% and 2.2% of questing I. ricinus nymphs from VG and ZA. Six species of Borrelia (B. afzelii, B. burgdorferi sensu stricto, B. garinii, B. valaisiana, B. spielmani, B. turdi or B. lusitaniae) were identified in nymphs in the two sites (Table
Species |
VG |
ZA |
Borrelia afzelii |
8 |
16 |
Borrelia burgdorferi sensu stricto |
15 |
13 |
Borrelia garinii |
6 |
20 |
Borrelia valaisiana |
10 |
14 |
Borrelia spielmani |
0 |
1 |
Borrelia turdi or B. lusitaniae |
0 |
1 |
Co-infection |
4 |
6 |
Non exploitable sequence |
4 |
7 |
Total |
47 |
78 |
Pathogen results in small mammals (Table
We thank the French National Research Agency, which funded the OSCAR project (ANR-11-AGRO-001-04). The OSCAR project website can be accessed at: https://www6.inrae.fr/oscar. This study benefited from the help of the “Zone Atelier Armorique” and the Zone Atelier “Vallées et Coteaux de Gascogne”. We are grateful to Dominique L’Hostis, Sylvie Cocaud, Nathalie Morcrette, Esther Dzalé, Anne-Sophie Martel, members of the pole DigitaIST (INRAE) and Nathalie Gandon, Unité Ingénierie Numérique en Recherche (INRAE), for their help preparing this data paper and all the colleagues who have participated to the OSCAR project (see the “Personnel” mentioned in the section “Project description”).
Publications, using the presented data, are available on the OSCAR project website: https://www6.inrae.fr/oscar/Reperes/Publications/Publications-Internationales-revues-a-comite-de-lecture.