Michel Génard
email: michel.genard@inrae.fr

Françoise Lescourret

Census of breeding birds in the Pyrenees in the early 1980s: A publicly available dataset for ecological research

Keywords:

a b s t r a c t

The Pyrenees is a mountain range in south-western Europe that supports a rich diversity of bird species. In 1981, point count surveys of breeding birds (passerines and picidae) were carried out in the Vanera valley, a valley in the eastern Pyrenees, resulting in a data set of 228 counts. These data provide valuable information on the distribution and abundance of bird populations on 5350 ha of heterogeneous land (including cropland, grasslands, heaths and river banks, and pine forest) at altitudes ranging from 1100 to 2600 meters. Additional point count surveys were carried out in the pine forest from 1982 to 1985, resulting in a data set of 144 counts. Habitat descriptors (percentage of herbaceous and ligneous plant cover at different heights -0-1m, 1-4m and more than 8m; vegetation type) and altitude were assessed around each point count. This dataset provides a complete picture of the breeding bird community in a typical valley of eastern Pyrenees in the early 1980s, which could be compared with future censuses to contribute to a variety of research questions, such as quantifying changes in birds between the early 1980s and now in mountain areas, understanding the effects of climate change on bird populations, examining the effects of habitat frag-mentation and land-use change, and identifying priority areas for conservation and management. These data could inspire new research and contribute to our collective understanding of bird ecology in the Pyrenees.

©

Value of the Data

• These data give a picture of the bird communities in the Pyrenees in the early 1980s. They are useful for differentiating bird communities in different habitats and according to altitude. They are also useful for analyzing the stability of pine communities over 5 years. • In addition to birds, these data indicate the altitude, vegetation type and vegetation cover at different heights, which characterize the habitats surveyed • These data can be useful for researchers working on bird communities and biodiversity, but also on typical mountain species such as the Common Crossbill. • These data should be of interest to researchers concerned with the evolution of biodiversity or the abundance of species of interest since the 1980s in Mediterranean mountain areas.

Each point count is positioned on a map and new counts could easily be carried out at the same locations. • These data should be useful for biogeographical comparisons of bird communities with other mountain or lowland sites.

Objective

The surveys carried out give a good picture of the bird communities living in the different environments of a valley in the eastern Pyrenees, the Vanera valley, in the 1980s. The climate was colder then, and the region has experienced frequent heat waves and droughts in recent decades. The land cover is also slightly different today from what it was in the 1980s, due to changes in human activities. Our data could be used as a reference (possibly together with others collected at other sites in the Pyrenees in the same years) for studies on the evolution of bird communities as a result of global changes that have taken place in recent decades.

Data Description

The data presented here consist of records of breeding birds from fields, grasslands, heaths and forests at altitudes between 110 0 and 260 0 m in the Vanera valley, a typical valley in the eastern Pyrenees ( Fig. 1 ). A total of 60 species and 5305 individuals were recorded ( Table 1 ). In 1981, 228 bird counts were carried out on 5350 ha of heterogeneous land ( Fig. 2 ). In 1982In , 1983In , 1984In and 1985, 75, 22, 75, 22, 26 and 21 bird counts respectively were made only in the pine forest (30% of the study area). The percentage of herbaceous and ligneous plant cover at different heights (0-1 m, 1-4 m and more than 8 m) was assessed within a 50 m radius of the bird count site. In addition, altitude was recorded and nine vegetation types were defined: cropland, hill heath and river banks, montane heath, Scots pine (Pinus sylvestris L.) forest, montane mountain pine (Pinus uncinata Ram) forest, subalpine mountain pine forest, subalpine heath, subalpine grassland, and alpine grassland ( Fig. 2 ).

Experimental Design, Materials and Methods

Birds were sampled using the point-count technique with unlimited distance [START_REF] Blondel | Point counts with unlimited distance[END_REF] . Singing passerines and picidae were recorded for 20 min in spring mornings. The bird species were identified by expertise ornithologist (F.L. and M.G.).

Point-counts were conducted in the centre of 0.025 km ² square cells in fair weather (no wind or rain). The cells were mainly situated on a grid that covered the study area ( Figs. 34567). Habitat descriptors were evaluated within a 50 m radius of the point-count site. Plants cover were estimated through comparison with reference drawings depicting imaginary cover levels of 5%, 10%, and so on [START_REF] Prodon | Breeding avifauna of a Mediterranean succession: the holm oak and corn oak series in the eastern Pyrenees. 1[END_REF] . The altitude was measured using an altimeter and the IGN map at 1:50,0 0 0 scale.

Fig. 1 .

 1 Fig. 1. Location of the Eastern Pyrenees and the study area in blue on the topographic map provided by openstreet map. Forested areas are shown in green.

Fig. 2 .

 2 Fig. 2. Vegetation types found in the study area.

Fig. 3 .

 3 Fig. 3. Location of the 228 point counts surveyed in 1981 on the topographic map of the Vanera valley. The name of the grid points is 1XY (X = abscissa and Y = ordinate). For example, the first point on the top left of the grid is 1EA. The labels of the points outside the grid are shown on the map.

Fig. 4 .

 4 Fig. 4. Location of the 75 point counts surveyed in 1982 on the topographic map of the Vanera valley. The name of the grid points is 1XY (X = abscissa and Y = ordinate). For example, the first point on the top left of the grid is 2EH.

Fig. 5 .

 5 Fig. 5. Location of the 22 point counts surveyed in 1983 on the topographic map of the Vanera valley. The name of the grid points is 1XY (X = abscissa and Y = ordinate). For example, the first point on the top left of the grid is 1NL.

Fig. 6 .

 6 Fig. 6. Location of the 26 point counts surveyed in 1984 on the topographic map of the Vanera valley. The name of the grid points is 1XY (X = abscissa and Y = ordinate). For example, the point on the top of the grid is

  2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

	Specifications Table
	Subject	Biology
	Specific subject area	Biodiversity
	Type of data	Table
	How the data were acquired	Bird point counts with unlimited distance. Each count lasts 20 mn. Within
		50 m of each point count, altitude and the type of vegetation were
		recorded and the percentage cover of different vegetation strata were
		estimated by comparison with reference drawings representing imaginary
		cover levels of 5%, 10%, etc.
	Data format	Raw
	Description of data collection	One year of sampling in a mountain valley characterised by 9 vegetation
		types. 5 years of sampling in the pine forest (30% of the study area). Birds
		were counted in the morning in spring and habitat descriptors were
		measured after each point count.
	Data source location	INRAE
		Vanera valley, Eastern Pyrenees
		France
		42 °23' 14''N 2 °2' 7''E (Latitude: 42.3872; Longitude: 2.0352) for the
		village of Valcebollère ( Fig. 1 )
	Data accessibility	Repository name: Data INRAE

Table 1

 1 Total number of individuals recorded per bird species per year during point counts in the Vanera valley, Eastern Pyrenees.

	Bird species	1981	1982	1983	1984	1985	Sum
	Parus major	79	0	0	0	0	79
	Cyanistes caeruleus	15	0	0	0	0	15
	Periparus ater	421	210	52	52	59	794
	Lophophanes cristatus	87	63	11	16	16	193
	Sitta europaea	6	0	0	0	0	6
	Certhia brachydactyla	47	32	5	13	11	108
	Troglodytes troglodytes	59	28	6	12	9	114
	Turdus viscivorus	11	21	2	4	1	39
	Turdus philomelos	38	29	9	6	21	103
	Turdus merula	152	4	0	0	2	158
	Saxicola rubicola SRB	18	0	0	0	0	18
	Luscinia megarhynchos	63	0	0	0	0	63
	Erithacus rubecula	140	116	18	27	17	318
	Sylvia atricapilla	92	0	0	0	0	92
	Sylvia borin	57	4	0	0	0	61
	Sylvia communis	50	1	0	0	0	51
	Phylloscopus collybita	12	5	0	0	0	17
	Phylloscopus bonelli	34	0	0	0	0	34
	Regulus regulus	85	70	22	29	24	230
	Prunella modularis	207	41	8	9	9	274
	Anthus trivialis	67	20	1	5	1	94
	Carduelis carduelis	11	0	0	0	0	11
	Carduelis cannabina	21	0	0	0	0	21
	Serinus serinus	34	3	0	0	0	37
	Pyrrhula pyrrhula	32	24	1	2	0	59
	Fringilla coelebs	294	122	46	61	29	552
	Emberiza citrinella	31	1	0	0	0	32
	Alauda arvensis	296	17	2	1	3	319
	Turdus torquatus	20	12	1	3	5	41
	Saxicola rubetra	14	0	0	0	0	14
	Serinus citrinella	243	74	53	34	29	433
	Loxia curvirostra	138	162	38	43	22	403
	Emberiza hortulana	5	0	0	0	0	5
	Emberiza cia	43	0	0	0	0	43
	Phoenicurus ochruros	25	6	1	4	5	41
	Lullula arborea	31	4	0	1	1	37
	Anthus spinoletta	30	4	0	0	0	34
	Emberiza calandra	15	0	0	0	0	15
	Oenanthe oenanthe	29	0	0	0	0	29
	Prunella collaris	11	0	0	0	0	11
	Aegithalos caudatus	1	0	0	0	0	1
	Sturnus vulgaris	5	0	0	0	0	5
	Emberiza cirlus	3	0	0	0	0	3
	Certhia familiaris	3	0	0	0	0	3
	Spinus spinus	3	0	0	2	0	5
	Dendrocopos major	32	29	9	13	9	92
	Oriolus oriolus	5	0	0	0	0	5
	Garrulus glandarius	8	1	0	1	0	10
	Monticola saxatilis	2	0	0	0	0	2
	Hypolais polyglotta	1	0	0	0	0	1
	Jynx torquilla	6	0	0	0	0	6
	Motacilla cinerea	4	0	0	0	0	4
	Lanius senator	1	0	0	0	0	1
	Lanius collurio	2	0	0	0	0	2
	Petronia petronia	10	0	0	0	0	10
	Picus viridis	23	0	0	0	0	23
	Upupa epops	10	0	0	0	0	10
	Coturnix coturnix	9	0	0	0	0	9
	Columba palumbus	21	7	6	2	0	36
	Cuculus canorus	78	0	1	0	0	79
	Sum	3290	1110	292	340	273	5305

Acknowledgments

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data identification number: doi:10.57745/YUESL8 Direct URL to data: https://entrepot.recherche.data.gouv.fr/dataset.xhtml?persistentId=doi: 10.57745/YUESL8 Related research article M. Génard, F. Lescourret, Combining Niche and Dispersal in a Simple Model (NDM) of Species Distribution, PLoS ONE. 8 (2013) e79948. https://doi.org/10.1371/journal.pone.0079948

Data Availability

Census of breeding birds in a typical valley of Eastern Pyrenees (Original data) (Recherche Data Gouv).

Ethics Statements

This work meets the ethical requirements for publication. It did not involve human subjects, laboratory animals or disturbance of wild animals.

CRediT Author Statement

Michel Génard: Data curation, Writing -original draft; Françoise Lescourret: Data curation, Writing -original draft.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Maryama Dufrénot

Louis Dagneaux

Celine Fernando

Patrick Chabrand

Matthieu Ollivier

Franc ¸ois Lintz

Three-dimensional biometrics using weight-bearing imaging shows relationship between knee and hindfoot axial alignment

Background: Existence of a relationship between knee and hindfoot alignments is commonly accepted, but not clearly proven. While studied in the coronal plane using 2D imaging, axial alignment has not been studied yet, likely requiring 3D measurements. We aimed to investigate how knee and hindfoot rotational alignments are related using 3D biometrics and modern 3D weight-bearing technologies. Hypothesis: Hindfoot alignment is correlated with femoral and tibial torsions. Patients and methods: All patients who underwent both weight-bearing CT (WBCT) and low dose biplanar radiographs (LDBR) were selected in this retrospective observational study, resulting in a cohort of 157 lower limbs from 99 patients. Patients' pathologies were stratified in subgroups and those with a history of trauma or surgery affecting lower limb alignment were excluded. Foot Ankle Offset was calculated from WBCT; femoral and tibial torsions and coronal alignment were calculated from LDBR, respectively. Results: Overall, mean Foot Ankle Offset was 1.56% (SD 7.4), mean femoral anteversion was 15.6 • (SD 9.5), and mean external tibial torsion was 32.6 • (SD 7.6). Moderate negative correlation between Tibial Torsion and Foot Ankle Offset was found in the whole series (rho = -0.23, p = 0.003) and for non-pathologic patients (rho = -0.27, p = 0.01). Linear models to estimate Tibial Torsion with Foot Ankle Offset and conversely were found, with a low adjusted R 2 (3% < R 2 < 7%). No relationship was found between FAO and femoral torsion. Discussion: External tibial rotation was associated with varus hindfoot configuration in the group without pathologies, suggesting that compensatory mechanisms may occur between knee and hindfoot alignments. In pathological cases, however, the same relationship wasn't found, raising concerns about compensatory failure in spite of the numbers available. We didn't find similar correlations with the femur possibly because the hip has a degree of liberty in the axial plane. Level of evidence: III, retrospective comparative study.

Introduction

Normal function in any lower limb joint requires biomechanical adaptations at distinct levels to ensure motion and stability under load. Muscles, tendons, ligaments, and bones must adjust, leading to compensatory mechanisms. As such, it is commonly accepted that knee and hindfoot alignment are related [START_REF] Okamoto | Clinical usefulness of hindfoot assessment for total knee arthroplasty: persistent postoperative hindfoot pain and alignment in pre-existing severe knee deformity[END_REF][START_REF] Jeong | Following the correction of varus deformity of the knee through total knee arthroplasty, significant compensatory changes occur not only at the ankle and subtalar joint, but also at the foot[END_REF]. A recent study highlighted a correlation in coronal plane between knee valgus and hindfoot valgus for patients without surgery or trauma that could affect knee or hindfoot alignment [START_REF] Dagneaux | Three-dimensional biometrics to correlate hindfoot and knee coronal alignments using modern weightbearing imaging[END_REF]. However, the mechanism of this relationship remains unclear, as well as its existence in other subsets of patients. Relationships between knee and foot rotational alignment have not been investigated yet.

Two-dimensional methods were considered the gold standard for lower-limb alignment measurement, regardless of their biases, which influence measurements and their interpretations (patient positioning, projections, fan effect) [START_REF] Kawakami | Effects of rotation on measurement of lower limb alignment for knee osteotomy[END_REF][START_REF] Baverel | Influence of lower limb rotation on hindfoot alignment using a conventional twodimensional radiographic technique[END_REF]. Bones and joints are 3D objects; thus, 3D biometrics are necessary to fully understand ongoing interactions. This point is even more important when measurements are used for pre-or postoperative assessment [START_REF] Barbotte | Coronal knee alignment measurements differ on long-standing radiographs vs. by navigation[END_REF]. Recently, 3D weight-bearing imaging using Cone Beam CT or stereoradiography have enabled measurements (biometrics) with low dose exposure. Biplanar stereoradiography is an alternative to conventional radiography, which reduces dose exposure and allows for lower limb rotational alignment assessment, avoiding the use of CT-scan. Weight-bearing CT (WBCT) imaging is an alternative to conventional CT, with an irradiation comparable to conventional plain radiographs series for the foot. Three-dimensional weightbearing acquisition also helps to refine diagnosis, as joints space and bones position are modified compared to supine position [START_REF] Thawait | Extremity cone-beam CT for evaluation of medial tibiofemoral osteoarthritis: initial experience in imaging of the weightbearing and non-weight-bearing knee[END_REF][START_REF] Segal | Diagnostic performance of 3D standing CT imaging for detection of knee osteoarthritis features[END_REF][START_REF] Richter | Results of more than 11,000 scans with weightbearing CT -impact on costs, radiation exposure, and procedure time[END_REF].

The aim of this study was to investigate relationships between hip, knee, and foot axial alignments using 3D biometrics and modern weight-bearing technologies. We hypothesized that external tibial rotation should correlate with hindfoot varus, and, or, femoral anteversion.

Patients and methods

Patients

Patients who underwent bilateral Weight-Bearing CT and Low-Dose Biplanar Radiography (LDBR) in 2017 as part of standard of care follow-up, were selected retrospectively (Fig. 1). Indications were by order of frequency: preoperative assessment for foot or ankle fusion, ankle instability, fractures, foot or ankle undetermined pain (Table 1). All healthy or asymptomatic contralateral limbs were included too. Mean age was 51 years (standard deviation (SD) 16), mean body mass index (BMI) was 26 kg/cm 2 (SD 5), 52% being females (Table 2).

Methods

Weight-bearing CT images were acquired using a PedCAT TM® unit (CurveBeam LLC, Hatfield, PA, USA), while patients were standing still in a comfortable position. A standardized imaging protocol The EOS System (EOS imaging, Paris, France) was used for lowerlimb LDBR imaging, including pelvic rim. Patients placed one foot slightly anterior to the other and lower limb neutral position was controlled relative to patellar position. Bone 3D surface reconstruction was performed in the SterEOS software (EOS Imaging, Paris, France) by one of the author (MD) [START_REF] Yan | Femoral and tibial torsion measurements based on EOS imaging compared to 3D CT reconstruction measurements[END_REF].

Methods of assessment

Hindfoot alignment was assessed on WBCT images using the Foot Ankle Offset (FAO), a fully 3D measurement in the axial plane [START_REF] Lintz | 3D biometrics for hindfoot alignment using weightbearing CT[END_REF][START_REF] Zhang | 3D biometrics for hindfoot alignment using weightbearing computed tomography[END_REF]. To calculate the FAO, 4 landmarks were identified on the PedCAT images (Fig. 2): centermost point of the talar dome, first (M1) and fifth (M5) metatarsal head lowest points and calcaneus lowest point (C). The last 3 points defined a plane, on which the talar point was projected (T). The FAO was the ratio of the distance between T and the middle line of the foot (connecting C and the middle of [M1M5]), divided by the length of the same line, given in percentage. In the axial plane, it gives an indication about the ankle offset relatively to the foot: it can be a medial or lateral. If foot and ankle are perfectly aligned, FAO = 0%.

One of the authors positioned the landmarks (LD, Fig. 2) and the FAO was calculated using TALAS TM® , a semi-automatic software (CurveBeam, Hatfield, PA USA).

Tibial Torsion and Femoral Torsion were calculated from EOS views in SterEOS (Fig. 2). Conventionally, femoral anteversion and external tibial torsion were considered positive.

Coronal alignments and pathology sorting was performed. Alignment subgroups were constituted as previously described, taking into account combinations of knee varus/valgus and neutral alignment, assessed using Hip Knee Angle (HKA) and hindfoot varus/valgus based on published boundaries [START_REF] Dagneaux | Three-dimensional biometrics to correlate hindfoot and knee coronal alignments using modern weightbearing imaging[END_REF][START_REF] Gaumétou | EOS analysis of lower extremity segmental torsion in children and young adults[END_REF][START_REF] Nam | Evaluation of the 3-dimensional, weight-bearing orientation of the normal adult knee[END_REF][START_REF] Siboni | Coronal and sagittal alignment of the lower limb in Caucasians: analysis of a 3D CT database[END_REF]:

• neutral knee alignment: -3 • < HKA < 3 • ;
• knee varus and hindfoot varus: HKA < -3 • and FAO < 2.3%;

• knee varus and hindfoot valgus: HKA < -3 • and FAO > 2.3%;

• knee valgus and hindfoot varus: HKA > 3 • and FAO < 2.3%;

• knee valgus and hindfoot valgus: HKA > 3 • and FAO > 2.3%.

Regarding foot and ankle pathology, 4 subgroups were constituted (Table 1): medial laxity pathology and/or lateral arthrosis (medial laxity), lateral laxity pathology and/or medial arthrosis (lateral laxity), other pathology, non-pathologic (lower limbs without knee, ankle and foot pathology) [START_REF] Perera | Clinical and radiographic evaluation of the cavus foot[END_REF][START_REF] Boerum | Biomechanics and pathophysiology of flat foot[END_REF][START_REF] Czajka | Ankle sprains and instability[END_REF].

Statistical analysis

Statistics were done using R 1.2.5001 (R project for statistical computing https://www.r-project.org/foundation/),with alpha = 0.05.

Normality was assessed using the Shapiro-Wilk test. Subgroup variables distribution was compared using Kruskal-Wallis and Kruskal-Nemenyi post hoc tests. When Kruskal-Wallis and Kruskal-Nemenyi post hoc tests were significant, Pearson's rho (parametric) or Spearman's rho (non-parametric) correlation test was performed. Correlation variables were FAO and Tibial Torsion. In subgroups with significant correlation, simple linear regression models were calculated. Linear relationships were studied for the whole group and subgroups.

Proper results analysis required post hoc power calculation for correlation and adjusted R-squared (R 2 ) calculation for regression. The latter allowed regression models comparison and power estimation.

Results

Variables distributions are presented in Table 2 (whole series) and in Online material (subgroups). Kruskal-Nemenyi post hoc test was significant for Tibial Torsion and FAO (Table 3, 0.01 < p < 0.04). Tibial Torsion was significantly higher for men than women (Table 3, Wilcoxon test, p = 0.04). Kruskal-Wallis test for Femoral Torsion wasn't significant (p = 0.05), so it wasn't considered for correlation nor regression. Moderate negative correlation between Tibial Torsion and FAO and linear models were found (Fig. 3, rho = -0.23, p = 0.003 and rho = -0.27 p = 0.01).

In the whole series and the non-pathologic group, when distal tibia rotates externally relative to proximal tibia, hindfoot varus increases. In the whole series, 3% of FAO changes can be predicted by Tibial torsion modifications, and 6% of Tibial Torsion changes can be predicted by FAO modifications. In the non-pathologic group, 3% of FAO changes can be predicted by Tibial Torsion modifications, and 7% of Tibial Torsion changes can be predicted by FAO modifications.

Discussion

In this study, linear negative correlation between Tibial Torsion and FAO and significant regression models were found. Our hypothesis was partially confirmed. We didn't find relationship between axial hip and knee nor hindfoot alignments.

In literature, studies about knee and foot alignment can be found in the context of total knee arthroplasty and supramalleolar osteotomy [START_REF] Jeong | Following the correction of varus deformity of the knee through total knee arthroplasty, significant compensatory changes occur not only at the ankle and subtalar joint, but also at the foot[END_REF][START_REF] Cho | Changes in hindfoot alignment after total knee arthroplasty in knee osteoarthritic patients with varus deformity[END_REF][START_REF] Desai | Effect of foot deformity on conventional mechanical axis deviation and ground mechanical axis deviation during single leg stance and two leg stance in genu varum[END_REF]. These findings can't be compared to our study because we focused on relationship for which natural degenerative processes were at work. For patients without surgery, previous studies using conventional radiographs always considered knee and hindfoot alignments in the coronal plane, because their axial components can only be assessed using 3D imaging modalities (Table 4). Desai et al. showed no difference in axial knee alignment for patients with primary symptomatic flatfoot compared to control subject, which is consistent with the absence of correlation in the medial laxity group of our study [START_REF] Desai | Effect of foot deformity on conventional mechanical axis deviation and ground mechanical axis deviation during single leg stance and two leg stance in genu varum[END_REF]. Norton et al. found a regression model for which 10% of the variance in the overall hindfoot angle could be explained by changes in the ankle line convergence angle [START_REF] Norton | Correlation of knee and hindfoot deformities in advanced knee OA: compensatory hindfoot alignment and where it occurs[END_REF]. This last angle considered a coronal axis that could be affected by changes in Tibial Torsion, as distal tibia shape on X-ray images depends on tibia rotation. In our study, 3% to 7% of FAO or Tibial Torsion variance could be explained by modifications in the other one. These findings can be compared bearing in mind that our results also accounted for non-pathologic patients, which weren't included in their study. Tibial torsion in the population is known to be higher in men than female, which was confirmed in the present study. It does not have an influence in our findings: for a same value of FAO, Tibial Torsion would be equivalent for men and women, and conversely. Nejima et al. investigated knee tortional and coronal alignments using Tibial Torsion, Femoral Torsion, HKA, and two other angles, but they didn't include foot alignment. They didn't find correlation between Femoral Torsion, Tibial Torsion and HKA, as in the present study [START_REF] Nejima | Relationship between lower limb torsion and coronal morphologies of the femur and tibia in patients with medial knee osteoarthritis[END_REF]. The absence of correlation with Femoral Torsion could be explained by the fact that hip has an important range of motion in the axial plane, unlike knee and hindfoot [START_REF] Polkowski | Hip biomechanics[END_REF]. Thus, knee has to adapt to foot, but it doesn't have to adapt to hip. Dagneaux et al. used the FAO to investigate knee and foot coronal alignment [START_REF] Dagneaux | Three-dimensional biometrics to correlate hindfoot and knee coronal alignments using modern weightbearing imaging[END_REF]. In our study, FAO was used for hindfoot both coronal and axial alignment. It's a recent measurement of hindfoot varus/valgus, which is known to be a coronal deformity, while measured in the axial plane and considering foot rotation, which makes it is comparable to Tibial and Femoral Torsions. It's a reliable measurement with intra-and inter-class correlation coefficient of 0.99 and 0.97 respectively [START_REF] Zhang | 3D biometrics for hindfoot alignment using weightbearing computed tomography[END_REF]. Mean FAO in population with neutral alignment is 2.3% ± 2.9%.

Knee and foot relationships are multidimensional, occurring simultaneously in all planes (coronal, axial, sagittal). We focused on the axial plane, while coronal alignment combinations were considered to create subgroups. As such, our statistical approach was multi-dimensional, integrating both coronal and axial components. Moreover, our results highlighted that relationships between Tibial Torsion and FAO are small, meaning that knee and hindfoot relationships cannot be explained using bone biometrics only. It is reasonable to hypothesize that knee and hindfoot alignments interactions aren't linear and could be affected by other parameters, like soft tissue laxity or BMI, for example. Innovative multidimensional method for nonlinear analysis would give the opportunity to fully investigate these relationships and provide more data on limits between physiologic and pathologic conditions.

We acknowledge several limitations in the present study. First, sample size is a weakness given the number of subjects in specific subgroups other pathology (n = 8), Valgus Knee/Varus Hindfoot (n = 8) and Varus Knee/Varus Hindfoot (n = 5). It could explain why no correlations were found in these subgroups. 3. Linear correlation and regression results. Moderate negative correlations were found between tibial torsion (TT) and Foot Ankle Offset (FOA) in whole series (rho = -0.23, power = 3%) and non-pathologic group (rho = -0.27, power = 71%). Linear models to estimate FAO using TT and conversely were found, with low adjusted R 2 (3% < R 2 < 7%). Another explanation may be that the standard model by which a correlation exists in asymptomatic or normal patients may not apply once symptoms or pathology is installed. With 3D imaging democratization, further studies should allow to include more patients in subgroups and explore relationships with sufficient statistical power. When considering 157 lower limbs and looking at normal knee alignment (n = 115) and non-pathologic (n = 84) subgroups, representative of a healthy knee and hindfoot population, we found a good correlation power (83%) between FAO and Tibial Torsion in the whole series and slightly less in the non-pathologic group (73%). It could be interesting to compare our results with those of a subset of healthy volunteers but exposing them to unnecessary radiation raises ethical concerns. Secondly, 3D EOS reconstructions were used to assess tibia and femur rotational alignment. It uses 3D parametric models and statistical inference to approximate bones shape based on two orthogonal 2D X-rays [START_REF] Boerum | Biomechanics and pathophysiology of flat foot[END_REF], which does not exactly represent real 3D bones shape. The automatically generated model can be manually re-adjusted to get closer to actual bones configuration, but the bone's shape doesn't affect its axis. It has been applied in clinical practice and is widely used for bones deformity assessment (including pediatrics) [START_REF] Delin | Ionizing radiation doses during lower limb torsion and anteversion measurements by EOS stereoradiography and computed tomography[END_REF]. The EOS measurements are reliable, with an inter-and intraclass correlation coefficients of 0.82 and > 0.83 for Tibial Torsion and 0.84 and > 0.79 for Femoral Torsion, respectively [START_REF] Gaumétou | EOS analysis of lower extremity segmental torsion in children and young adults[END_REF][START_REF] Chaibi | Fast 3D reconstruction of the lower limb using a parametric model and statistical inferences and clinical measurements calculation from biplanar X-rays[END_REF]. Correlation with those measured on conventional CT-scanner has also been shown [START_REF] Buck | Femoral and tibial torsion measurements with 3D models based on low-dose biplanar radiographs in comparison with standard CT measurements[END_REF]. This might change in the future, with WBCT emergence as high as knee and hip level, which should allow more precise evaluation and correlation.

Conclusion

Our results confirm that tibia external rotation from proximal to distal is associated with a more varus hindfoot configuration in the group without pathologies and the whole series. This seems to confirm that compensatory mechanisms exist between knee and hindfoot. However, no correlation was highlighted in specific pathologic populations, possibly because these mechanisms fail when pathologies are installed. Further studies should include larger cohorts and more variables to investigate axial alignment relationships in pathologic subgroups with sufficient statistical power. It would allow to determine if, in clinical practice, tibial nor femoral rotation should be considered in foot realignment procedures, and conversely. We didn't find similar correlations with the femur, possibly because the hip has an important range of motion in the axial plane.

Ethical review committee statement

All procedures performed satisfied the ethical standard of the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study also followed STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines.

The ethical approval from Ramsay Santé Institutional Ethics Committee was obtained. IRB number: COS-RGDS-2018-05-002-Avis IRB-LINTZ-F.

Disclosure of interest

MD is a paid employee of Newclip technics. LD is a paid consultant of Newclip technics. MO is a paid consultant of Newclip technics. PC has contracts with Newclip Technics, RLC Systems, Selenium medical.

FL is a paid consultant of CurveBeam LLC, is a board/committee member of AFCP, EFAS, International WBCT Society and took out a patent for TALAS TM® .

The CF author declares that he has no competing interest.

Fig. 1 .

 1 Fig. 1. Flow chart.

Fig. 2 .

 2 Fig. 2. Weight-bearing lower limb imaging. Low dose biplanar radiography (A: sagittal, B: coronal) and 3D reconstruction to measure femoral (C1) and tibial (C2) torsions. Weightbearing CT to measure Foot Ankle Offset (D).

Fig.

  Fig.3. Linear correlation and regression results. Moderate negative correlations were found between tibial torsion (TT) and Foot Ankle Offset (FOA) in whole series (rho = -0.23, power = 3%) and non-pathologic group (rho = -0.27, power = 71%). Linear models to estimate FAO using TT and conversely were found, with low adjusted R 2 (3% < R 2 < 7%).

Table 1

 1 Patients' pathologies.

	Pathology	Number of	Pathology group
		feet
	Ankle lateral instability	19 (50%)	Lateral laxity and/or
	Ankle medial arthrosis	4 (11%)	medial arthrosis
	Talonavicular arthrosis	1 (3%)	n = 38 (55%)
	Cavus, varus and cavovarus foot	5 (13%)
	Tarsometatarsal arthrosis 2/3	1 (3%)
	Fibular tendinopathy	1 (3%)
	Talar dome articular lesions	3 (8%)
	Lateral chronic laxity	2 (5%)
	Varus knee	2 (5%)
	Flat foot	19 (56%)	Medial laxity and/or
	Posterior tibial tendinopathy or instability 2 (6%)	lateral arthrosis
	Calcaneonavicular synchondrosis	1 (3%)	n = 34 (49%)
	Subtalar arthrosis	1 (3%)
	Brown Sequard syndrome	1 (3%)
	Hallux valgus	5 (71%)	Other
	Haglund syndrome	2 (29%)	n = 7 (1%)
	One pathology per patient was considered for clarity. Number of cases and percent-
	age over the considered group (bold) and whole series (italic) are presented.

Table 3

 3 Kruskal-Wallis, Kruskal-Nemenyi post hoc and Wilcoxon tests p-values (significant are colored).

		Kruskal-Wallis test		Wilcoxon test
		Knee and hindfoot	Pathology	Sex
		coronal alignment
	Foot Ankle Offset	< 0.001 a	< 0.001 a	0.54
	Tibial torsion	0.07	0.63	0.04 a
	Femoral torsion	0.57	0.05	0.90
	Kruskal-Nemenyi post
	hoc test for Foot Ankle
	Offset by coronal
	alignment
		Knee	Normal	Varus	Varus	Valgus
		Hindfoot		Varus	Valgus	Varus
	Knee	Hindfoot
	Varus	Varus	0.08
	Varus	Valgus	0.02 a	< 0.01 a
	Valgus	Varus	0.22	0.99	< 0.01 a
	Valgus	Valgus	0.05	0.01 a	0.93	< 0.01 a
	Kruskal-Nemenyi post
	hoc test for Foot Ankle
	Offset by pathology
		Non-pathologic	Medial laxity	Lateral laxity
	Medial laxity	< 0.01 a
	Lateral laxity	0.23	< 0.01 a
	Other	0.99	0.04 a	0.90

a p-values that are significant.

Table 4

 4 Literature review regarding knee and foot alignment relationships without surgery.

	Authors	Year	Biometric		Group	Results
			Knee	Foot
	Dagneaux et al. [3]	2020	2D	3D	OA: K/L < 3	Correlation: hindfoot valgus and knee
						valgus (rho = 0.53, p = 0.01)
	Burssens et al. [21]	2020	2D	2D	OA: Takakura ≥ 1	Correlation: hindfoot valgus and knee
						varus (rho = -0.38, p < 0.0001)
					OA: Takakura = 0	Correlation: hindfoot
						varus and knee varus
						(rho = 0.46, p < 0.0001)
						Hindfoot valgus and
						knee valgus (rho = 0.4,
						p < 0.0001)
	Mansur et al. [22]	2020	2D	2D	OA: AOFAS score > 54	Correlation: hindfoot varus and knee
					(hindfoot)	valgus (rho = 0.56, p < 0.05)
						Association between knee valgus and
						hindfoot varus
	Ohi et al. [23]	2017	2D	2D	OA: K/L ≥ 1	Linear model: knee valgus and
						pronation angle of the calcaneus
						(regression coefficient 0.33 per degree,
						p = 0.005)
	Norton et al. [24]	2015	2D	2D	OA:	Correlation: knee valgus and hindfoot
					K/L ≥ 3	varus (rho = -0.03, p < 0.0012)
						Knee varus and hindfoot valgus
						(rho = -0.35, p > 0.0001)
						Correlation was stronger in patients
						with larger deformities
						Linear model: 10% of variance in
						hindfoot angle can be explained by
						changes in ankle convergence angle

OA: osteoarthritis; K/L: Kellgren-Lawrence.

Funding

This research didn't receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.