Thomas Coudert

Aurélien Delphin

Jan M Warnking

Benjamin Lemasson

Emmanuel Luc Barbier

Thomas Christen

Searching for an MR Fingerprinting sequence to measure brain oxygenation without contrast agent

We propose to use numerical simulations and Monte Carlo approaches to test 40 MR ngerprinting sequences for their to quantify the BOLD e ect and provide maps of baseline blood oxygen without the need contrast agent injection. Our results suggest that several sequences can produce SO2 maps with less 3% error on average even in the presence of B1 and B0 T2 and blood vessel radius could also be estimated with the same acquisitions.

Introduction

The Magnetic Resonance (MRF) framework has the possibility to use unconventional MR sequences (such as random succession of FA and TR) for tissue relaxometry. This type of approach should also be suited to quantify the BOLD e ect as it has been shown balanced SSFP sequences and their transient-states are highly sensitive to magnetic elds inhomogeneities . Following our previous work on vascular MRF , we propose to use these types of sequences to obtain blood oxygenation saturation maps without the need for contrast agent injection. We used numerical simulations and a

Monte Carlo method to assess the e ciency of numerous MRF sequences based on 3 types of acquisitions [START_REF] Ma | resonance ngerprinting[END_REF] For the three sequence types, about 15 trials were made with di erent combinations of TR and FA (see Fig. 2). Sequence evaluation was performed in two steps with a Monte-Carlo method (thermal noise with a normal distribution (μ=0, σ=Signal/SNR, with SNR = 20), parameter and error evaluations performed 2000 times on 50 entries equally distributed in the parameter space) to obtain mean error values on the estimation of each parameter of interest.

Results

Fig. 1 shows examples of sequence diagrams as well as signal evolutions for the 3 types of sequences tested. One can notice the di erent signal responses to di erent SO2 baseline values (blue to red colors), highlighting the importance of the transient-state in terms of SNR and sensitivity. Amongst all the MR sequences tested (Fig. 2), several combinations of parameters seemed to provide acceptable (<10% average) errors on SO2 estimates, and 2 particular candidates (Type2:Seq4 and Type3:Seq1) were chosen (based on overall error and signal evolutions) for further evaluation. Sequence diagrams and signal responses to SO2 variations are shown in Fig. 3 for Type2:Seq4. The initial pattern was repeated 4 times in order to reduce the in uence of low SNR in the steady-state part of the signal, leading to an acquisition time of 9s per slice. 3D plots of signal standard deviations under variation of SO2, for di erent values of BVf and R, are also shown to highlight the cross-talk between the dimensions of the dictionary. Finally, it can be seen that the MC approach predicts low errors for SO2 and T2 estimates as well as acceptable estimates of blood vessel radius for this particular pattern. Similar results were obtained for the random pattern Type3:Seq1 (not shown). New simulations were performed in order to test the sensitivity of the 2 sequences to B1 and B0 o set artefacts. Results are presented in Fig. 4, where it can be seen that Type2:Seq4 still performs well under such conditions with only a small increase in SO2 error due to B0 o set. Signal variations (Fig. 4 d-e) are also shown to highlight the changes of patterns due to the 2 new dimensions. Results obtained with Type3:Seq1 were more impacted by B1 artefacts with 10% average error on SO2 estimates and concomitant increase in standard deviation.

Conclusion

to numerical simulations, several MRF sequences be able to provide accurate measurements of baseline blood oxygenation saturation without the need for contrast agent injection and in a clinically acceptable scan time. While it is not easy to automatically optimize vascular MRF sequences due to the computational load of the numerical simulations (magnetic susceptibility e ects + water di usion + relaxation in a ne microvascular geometry), new optimization approaches could further improve the sequence's e ciencies . In vivo data are now required to eventually validate our ndings.

Figures

Figure 1 :

 1 Figure 1: of pulse parameters for one sequence of 1 Transient-state/bSSFP: FA = 60°, TR = 40ms (b) one sequence of Type 2 Transient-state/bSSFP/phase OSSI: FA = 25°, TR = 5ms and phase cycling starting at the 41st pulse, (c) one sequence of Type 3 Transient-state/random pattern: 45° < FA < 90°, 11ms < TR < 15ms. (d),(e),(f) Respective signal responses for di erent values of SO2.

Figure 2 :

 2 Figure 2: Monte-Carlo SO2 error estimation (Mean and Standard deviation) for di erent (a) Transient-state/bSSFP sequences, (b) Transient-state/bSSFP/phase OSSI sequences, (c) Transient-state/random pattern sequences.

Figure 3 :

 3 Figure 3: Detailed results obtained with the Type2:Seq4 sequence. (a) Sequence parameters. (b) MR signal responses for di erent SO2 values. (c) 3D plots of signal standard deviations under variation of SO2, for di erent values of cerebral blood volume (CBV) and vessel radius (R). (d) MC error estimation (mean and std) for di erent parameters of the model.

Figure 4 :

 4 Figure 4: MC error estimation (Mean and Standard deviation) for di erent parameters of the model for the Type2:Seq4 sequence. (a) without artefact, (b) with frequency o set artefacts, (c) with B1 artefacts. (d) Signal responses for one value SO2 and B0 o sets. Zoom on the steady-state part of the signal. (e) responses for one value of and multiple B1 values. Zoom on the steady-state part of the signal.

  bSSFP with acquisition of transient-state[START_REF] Ganter | O -resonance e ects in the transient response of SSFP sequences[END_REF] bSSFP with oscillations of RF phases (OSSI ), in order to shift frequency o set patterns, and (3) succession of random TR and FA. Our numerical results suggest that several MRF sequences can produce SO2 maps with less that 3% error on average. T2 and blood vessel radius could also be estimated with the same acquisitions.Type 1 (transient-state/bSSFP): constant FA, TR, TE=TR/2, no phase cycling, Fig.1a 1d.Type 2 (transient-state/bSSFP/phase OSSI): constant FA, TR, TE=TR/2, no phase cycling for 40 pulses, followed by 110 pulses with a phase cycling to establish an oscillating steady-state, Fig.1b1e. Type 3 (transient-state/random pattern): Random FA, random TR, TE=TR/2, no phase cycling, Fig. 1c, 1f.

	Materials and methods
	simulations were performed on Matlab (The MathWorks Inc., Ma, USA) with MRVOX software . Blood vessels were in 2D with uniform oxygenation. Variations of Blood Volume fraction
	(BVf [1,10]%), mean vessel radius (R [2,10]µm), blood oxygen saturation (SO2 [35,90]%) and T2 ([40,110]ms) were considered to create the MRF dictionaries. For 2 particular sequences (see below), variations of
	B1 ([0.7,1.3]) and B0 o set frequencies ([0,75]Hz) were added.
	3 types of sequences were tested (150 pulses each):

Proc. Intl. Soc. Mag.Reson. 30 (2022)

Acknowledgements supported by ANR MRFUSE [ANR-20-CE19-0030]


Minh Hieu Nguyen

Jimmy Armoogum

; Cédric

#86 -IMPUTING TRANSPORTATION MODES FROM GPS DATA IN A MOTORCYCLE-DEPENDENT AREA

Mode detection methods are the key to deploying GPS in travel demand survey.

Little, however, is known about the potential and barriers to mode imputation from GPS in developing countries. This study aims to impute travel modes from GPS data in combination with socio-demographics of respondents in Hanoi (Vietnam) -a motorcycle-dependent city.

Introduction

Experimental description

Methodologies and results

Conclusions

Our related publications

University of Transport and Communications

Nguyen, M.H., Armoogum, J., 2020. Hierarchical process of travel mode imputation from GPS data in a motorcycledependent area.

Post-processing to further detect:

Bike/motorcycle: A bike/motorcycle segment was classified as a bike one in case the traveler came from a household with at least one bicycle. Car/motorcycle: In case the user had a car driving license, the car/motorcycle segment was labelled as a car segment. If not, it was categorized as a motorcycle one. Bus/motorcycle/car: First, in case both the starting time and ending time of a bus/motorcycle/car segment felt into the operational time of bus services, this segment was then checked by two criteria. In case the user had a monthly pass or both origin and destination of this segment was close to bus stops, it was classified as a bus segment. By contrast, it was next treated as a motorcycle/car segment.

Mode imputation results (Tab 1.)

Reasonable overall accuracy of 84.8%. Motorcycles are the main source of misclassification. Imputations of bus and bike are poorer (see precision and recall)

Future direction

Improving the detection of bus and bike using machine learning

Fig

  Fig 2. Process of travel mode imputation

Tab 1. Confusion matrix of imputation results

			Walk	Bike	Bus	Predicted Motorbike	Car	Total	Recall
		Walk	719	9	0		28	2	758	94.9%
		Bike	4	75	0		23	2	104	72.1%
	Actual	Bus Motorbike	0 48	2 33	72 36		21 1058	2 70	97 1245	74.2% 85.0%
		Car	11	5	10		117	444	587	75.6%
		Total	782	124	118		1247	520	2791
		Precision	91.9% 60.5% 61.0%	84.8%	85.4%	Acc.	84.8%

Travel Behav. Soc. 21, 109-120. https://doi.org/10.1016/j.tbs.2020.06.006 Nguyen, M.H., Armoogum, J., Adell, E., 2021. Feature Selection for Enhancing Purpose Imputation using Global Positioning System Data without Geographic Information System Data: Transp. Res. Rec. 2675, 75-87. https://doi.org/10.1177/0361198120983006 Nguyen, M.H., Armoogum, J., Madre, J.-L., Garcia, C., 2020. Reviewing trip purpose imputation in GPS-based travel surveys. J. Traffic Transp. Eng. Engl. Ed. 7, 395-412. https://doi.org/10.1016/j.jtte.2020.05.004 Among first studies of detecting travel modes from GPS data in a motorcycle-dependent city of a developing country. Inclusion of motorcycle increases the difficulty of mode detection challenge.


Leslie Morrison Vila
email: leslie.morrison@catie.ac.cr

Matthieu Ménager
email: matthieu.menager@univ-avignon.fr

Bryan Finegan
email: bfinegan@catie.ac.cr

Diego Delgado
email: ddelgado@catie.ac.cr

Fernando Casanoves
email: casanoves@catie.ac.cr

Luis Ángel

Aguilar Salas

Marvin Castillo
email: mcastillo@itcr.ac.cr

Luis Gustavo

Hernández Sánchez

Yoryineth Méndez

Henry Sánchez Toruño
email: henry.sanchez.toruno@una.cr

Vila Morrison

Leslie

Ménager Matthieu

Finegan Bryan

Delgado Diego

Casanoves Fernando

Castillo Marvin

Hernández Sanchez
email: gustavo.hernandez.sanchez@una.cr

Mendez Yoryineth

Toruno Sanchez

Henry

Solano Gilbert

Zúñiga Pedro

Ngo Bieng

Marie Ange

Above-ground biomass storage potential in primary rain forests managed for timber production in Costa Rica

Keywords: Primary forests, sustainable forest management, climate change mitigation, permanent sampling plots, plot spatial distribution, variation partitioning, soil fertility

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

INTRODUCTION

Tropical forests are expected to play a fundamental role in mitigating climate change and achieving the global temperature rise target set as part of the 2015 Paris Agreement. Indeed, tropical forests are crucial systems for regulating the climate and mitigating climate change [START_REF] Baccini | Tropical forests are a net carbon source based on aboveground measurements of gain and loss[END_REF][START_REF] Sullivan | Long-term thermal sensitivity of Earth's tropical forests[END_REF][START_REF] Griscom | National mitigation potential from natural climate solutions in the tropics[END_REF]. These forests can sequester up to 30% of anthropogenic carbon dioxide (CO2) emissions and represent at least 59% of global carbon stocks [START_REF] Yguel | Beyond species richness and biomass: Impact of selective logging and silvicultural treatments on the functional composition of a neotropical forest[END_REF]. They store approximately 470 billion tonnes of CO2 in above and below ground biomass [START_REF] Oksanen | A large and persistent carbon sink in the wolrd´s forests[END_REF][START_REF] Huntingford | Simulated resilience of tropical rainforests to CO2 -induced climate change[END_REF][START_REF] Pugh | Role of forest regrowth in global carbon sink dynamics[END_REF]. Interest in tropical forests specifically is therefore thoroughly justified since they are the ecosystems with the most potential for storing additional terrestrial carbon [START_REF] Griscom | National mitigation potential from natural climate solutions in the tropics[END_REF].

On the other hand, one of the greatest sources of greenhouse gas emissions stems from the tropical deforestation [START_REF] Griscom | National mitigation potential from natural climate solutions in the tropics[END_REF]. These ecosystems display greater and more rapid changes in land use than any other ecosystem, as a result of anthropogenic deforestation and degradation (Chazdon et al. 2016, Poorter et al. 2016[START_REF] Mitchard | Consequences of Environmental Service Payments for Forest Retention and Recruitment in a Costa Rican Biological Corridor[END_REF]. Net decreases in the area of tropical forests were enormous during the decade 2010-2020, mainly in Africa (3.9 million ha) and South America (2.6 million ha) (FAO, 2020).

Deforestation leads to numerous sources of emissions as well as cryptic sources that occur more gradually and include the edge effect in fragmented forests [START_REF] Maxwell | Degradation and forgone removals increase the carbon impact of intact forest loss by 626%[END_REF]. Newly accessible forests will be earmarked for a first selective conventional logging , which could result in substantial carbon emissions [START_REF] Pearson | Carbon emissions from tropical forest degradation caused by logging[END_REF][START_REF] Maxwell | Degradation and forgone removals increase the carbon impact of intact forest loss by 626%[END_REF]. Conventional selective logging in tropical forests for timber and/or fuelwood is usually a source of forest degradation, since the loss of live biomass as a result of harvesting practices is, in general, greater than the accumulation of biomass through regrowth over many years [START_REF] Pearson | Carbon emissions from tropical forest degradation caused by logging[END_REF]. The loss of biomass is mainly related to damage caused by the felling of harvested trees, incidental damage to neighbouring trees and damage caused by unplanned log extraction [START_REF] Pearson | Carbon emissions from tropical forest degradation caused by logging[END_REF]. This study, therefore, focuses on how selective logging affects the mitigation potential of tropical production forests. More specifically, we are interested in sustainable logging and its impact on biomass storage in tropical production forests.

Various improved reduced-impact logging (RIL) techniques have been developed. They seek to balance environmental protection with timber production in tropical production forests. RIL, in addition to mitigating the damage caused by log extraction reduces the loss of carbon stocks in the remaining vegetation, thereby providing a natural climate solution [START_REF] Ellis | Forest Ecology and Management[END_REF]. Natural climate solutions are made up of discrete and quantifiable actions that avoid the emission of greenhouse gases or increase carbon sequestration in forests, savannah, agricultural lands and wetlands [START_REF] Griscom | National mitigation potential from natural climate solutions in the tropics[END_REF]. In this context, many studies have reported that RIL in tropical forests could eventually reduce carbon emissions equivalent to 29-50% of the net emissions caused by tropical deforestation and changes in land use [START_REF] Cerullo | Actively restoring resilience in selectively logged tropical forests[END_REF][START_REF] Sasaki | Sustainable Management of Tropical Forests Can Reduce Carbon Emissions and Stabilize Timber Production[END_REF]. Moreover, the relatively small net emission of CO2 by RIL hides the high potential for CO2 storage in the form of biomass [START_REF] Houghton | A role for tropical forests in stabilizing atmospheric CO2[END_REF].

Our research seeks to contribute knowledge about the potential of sustainable management for maintaining carbon storage in production forests. We specifically study above-ground biomass (AGB) storage in production forests submitted to sustainable logging techniques. Knowing more about AGB storage in production forests will enable sustainable logging to be promoted as a natural climate solution in the tropics, where only a small area of forest is currently subject to sustainable management (FAO, 2020). Comparing biomass stocks in recovering production forests with those of primary forests (forests with no known recent human intervention) makes it possible to demonstrate how logging impacts carbon storage.

The current research applies to primary rain forests in Costa Rica, where sustainable forest management and forest conservation take place on private farms within a landscape matrix that is highly fragmented (e.g. [START_REF] Schedlbauer | Rain forest structure at forest-pasture edges in northeastern Costa Rica[END_REF], Morse et al. 2009). The objective of this research was to estimate the above-ground biomass (AGB) in production forests under sustainable management and to compare it with the AGB in primary forests. This estimation is made for the period 2000-2015, and used data collected from permanent sampling plots established in different areas of Costa Rica by the Costa Rica Forest Ecosystems Observatory (Observatorio de Ecosistemas Forestales de Costa Rica, OEFo). We also examined the relationship between AGB and i) the spatial distribution of the plots, ii) climate variables, and iii) soil variables. To conclude, we discuss the results, focusing on the potential of sustainable management as a natural climate solution, through potential for storage of AGB in production forests.

MATERIALS AND METHODS

Area of study

The research was carried out with data from primary and production forests in Costa Rica. Costa Rica is located at between latitudes 08°02'26'' N and 11°13'12''N and between longitudes 82°33'48'' W and 85°57'57'' W, being a country situated within the tropical belt (ING, 2005). Costa Rica's mountain ranges divide the territory into five climatically defined regions, two on the Caribbean or Atlantic slope, and three on the Pacific slope (Figure 1). According to the bioclimatic Holdridge Life Zone System, Costa Rica is further divided into 12 life zones and 12 transition zones [START_REF] Quesada | Estudio poblacional de especies forestales en el Área de Conservación Tempisque, cantones de Nicoya, Hojancha y Nandayure[END_REF].

Experimental plots and data

The permanent sampling plots selected for this research are part of the Costa Rica Forest Ecosystems Observatory (Observatorio de Ecosistemas Forestales de Costa Rica, OEFo) (Morrison 2020). The OEFo is a group of institutions with a network of over 400 permanent sampling plots (PSPs). Its main objective is to evaluate the status and dynamics of forest ecosystems according to their level of disturbance and to build knowledge about the ecosystem services that they provide. For the purposes of this research, we selected 171 PSPs on private farms, located in nine life zones and transition zones (Holdridge 1966[START_REF] Quesada | Los Bosques de Costa Rica[END_REF]) (Table 1, Figure 1). The area of monitoring plots varied between 0.2 ha and 1 ha. In all plots, trees with diameter at breast height (BDH, 1.3 m) were measured. Most trees were identified by genus and family and in many at the level of species. The identification was carried out by qualified staff and botanists.

Life zone

Palms (family Arecaceae) were excluded from the study since they were only taken into account in the monitoring of a few plots. Moreover, palm trees do not exhibit growth in their diameter so it is difficult to estimate their contribution to productivity [START_REF] Goodman | Amazon palm biomass and allometry[END_REF]. Lianas were also excluded from the analysis since there was no consistent data relating to them.

Environmental variables

In order to characterise the relationship between climate-related factors with AGB, annual precipitation and mean temperatures in all the plots were considered. We obtained precipitation and temperature data from Chelsa (Climatologies at high resolution for the earth's land surface areas) database [START_REF] Karger | Climatologies at high resolution for the earth's land surface areas[END_REF][START_REF] Karger | Data from : Climatologies at high resolution for the earth ' s land surface areas 1-9[END_REF], through interpolation with the location coordinates of the plots, using R software (R Core Team 2019).

In addition to temperature and rainfall, soil data were obtained from the Centre for Agricultural Research (Centro de Investigaciones Agronómicas, CIA) of the University of Costa Rica [START_REF] Mata | Buenas prácticas en la elaboración de mapas de suelos[END_REF]. This database draws on 1500 soil sampling locations distributed throughout Costa Rica. The values of soils characteristics used in analyses were chosen according to the proximity of the CIA sampling locations to PSPs and by life zones. We used values for 0-40 cm soil depth [START_REF] Sesnie | Landscape-Scale Environmental and Floristic Variation in Costa Rican Old-Growth Rain Forest Remnants[END_REF][START_REF] Santiago-García | Soil is the main predictor of secondary rain forest estimated aboveground biomass across a Neotropical landscape[END_REF]. The following variables were taken into account: pH in water, acidity, Ca, Mg, K, Zn, P, Cu, Fe, Mn, effective cation exchange capacity (ECEC), organic carbon (OC) and the percentage of sand, loam and clay in the soil. These variables are considered to be attributes of soil fertility by [START_REF] Mata | Buenas prácticas en la elaboración de mapas de suelos[END_REF].

Estimation of above-ground biomass

For the estimation of AGB, data were selected for the period 2000-2015 covered by the selected plots. During this period, some plots were measured only once and others up to seven times (Appendix 1).

The BIOMASS package (computeAGB function) was used to estimate the AGB (Mg ha -1 ) of the trees (Réjou-Méchain et al. 2017), using R software (R Core Team 2019). This function uses the pantropical equation of Chave et al. (2014), to estimate AGB using DBH, species wood density and tree height, as follows: AGB = 0.0673 * (WD * H * D^2) ^0.976 WD was obtained from the getWoodDensity function of the BIOMASS package. The estimate is based on the taxonomy of the trees, or similar, using the global wood density database [START_REF] Chave | Regional and Phylogenetic Variation of Wood Density across 2456 Neotropical Tree Species Published by : Ecological Society of America REGIONAL AND PHYLOGENETIC VARIATION OF WOOD DENSITY ACROSS 2456 NEOTROPICAL TREE SPECIES[END_REF], Réjou-Méchain et al. 2017), which returns a value for each species that represents dry mass divided by dry volume (g cm -3 ). For trees that were not identified by species, the BIOMASS package averages wood density values by taxonomical level (genus) or assigns mean values by sub-plot.

Tree height H was estimated using the retrieveH function, also from the BIOMASS package, which uses the general model of Chave et al. (2014). In their model, H is estimated on the basis of tree dbh and plot bioclimatic variables that include climatic water deficit as well as temperature and precipitation seasonality. The geographic coordinates of the plots were used to obtain these bioclimatic variables.

Plot AGB was obtained from the sum of the biomasses of all trees in each plot (Mg ha -1 ). For plots with two or more enumerations, an average plot AGB was obtained from the set of enumerations.

Statistical analysis

In order to compare AGB between the production and primary ANOVA (analysis of variance) was carried out with a linear mixed model using InfoStat software (Di [START_REF] Rienzo | Centro de Transferencia InfoStat[END_REF]. The fit,of a model with no random factor was better than that of a model with plot set as the random factor according to the AIC and BIC criteria. Assumptions of normality and variance homogeneity were evaluated using QQ-plots and residuals versus predicted plots respectively (Appendix 2).

Spatial variables: Principal coordinates of neighbour matrices (PCNM) analysis

Principal coordinates of neighbour matrices (PCNM) analysis was used to calculate spatial variables to evaluate the effect of plot spatial distribution on AGB. This was calculated by using a log transformation of the spatial coordinates of each plot, resulting in a Euclidean distance matrix of the distances between the plots. In order to detect and quantify spatial patterns, the logarithmic values were truncated to create a second matrix of eigenvalues which were submitted to a principal component analysis (PCA). The result is a set of eigenvectors known as PCNMs (Bocard & Legendre 2002[START_REF] Dray | Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM)[END_REF]). These represent the spatial relationships among plots at different scales. The analysis was carried out in R software (R Core Team 2019) using the Vegan library and the PCNM function [START_REF] Oksanen | A large and persistent carbon sink in the wolrd´s forests[END_REF].

Spatial, soil and climate variables affecting AGB

In order to evaluate the relationship of AGB to spatial and environmental variables, the climate and soil variables were standardised. A forward selection (R Core Team 2019) was then carried out for each of the three matrices of explanatory variables, which selected the variables most closely associated with the response matrix (AGB) through a process of permutation using residuals from the reduced model [START_REF] Blanchet | Forward selection of explanatory variables[END_REF]. For the PCNM matrix the hypothesis test was based on 1,000 permutations using α = 0.01. The hypothesis test for the soil matrix was based on 999 permutations with α = 0.05.

In order to verify that a high correlation between the selected variables and the climate variables did not exist as a result of forward selection, Pearson's correlation coefficient was applied (Appendix 4).

Variation partitioning analysis

We used variation partitioning (VARPART, [START_REF] Jones | Explaining variation in tropical plant community composition: Influence of environmental and spatial data quality[END_REF] to evaluate the explanation of AGB variation by matrices of climate (annual mean temperature and precipitation), soil and spatial variables (PCNM) VARPART combines redundancy analysis and partial redundancy analysis by dividing the variation in the matrix of the response variable (AGB) into explanatory or predictive matrices. This VARPART allowed the pure and joint effects of the three matrices to be identified, as well as the overall variance explained by the set of three matrices. For this analysis, the varpart function was used from the Vegan package [START_REF] Oksanen | A large and persistent carbon sink in the wolrd´s forests[END_REF].

The adjusted R 2 (R 2 adj) values indicate the proportion of variation in AGB that is explained by each explanatory matrix. The significance of fractions from the VARPART analysis (p ≤ 0,05) was confirmed with a redundancy analysis (RDA) test.

Linear regressions

To establish the effect of each explanatory variable on the AGB, the variables were standardised.

Linear mixed model regressions were then carried out between the dependent variable (AGB) and the explanatory variables selected for the VARPART analysis. Life zone and the institution responsible for PSPs were used as random effects to take into account variations in plot size and in the number of plots between forest type. The t-statistic value and Mallows' Cp criterion for prediction were the statistics used to identify the explanatory variables with most influence on AGB. These analyses were carried out using InfoStat software (Di [START_REF] Rienzo | Centro de Transferencia InfoStat[END_REF]).

RESULTS

Above-ground biomass

The above-ground biomass (AGB) of 58,661 trees from 812 taxa was estimated, distributed across 141 plots. 86% of individuals were identified to species. Mean AGB varied significantly between the two types of forest (p ˂ 0.0001). Production forests stored more AGB (329.3 Mg ha -1 ± 90.9) than the intact primary forests (296.3 Mg ha -1 ± 75.9) ( and standard error (SE).

Influence of spatial, soil and climate variables on AGB

The variables selected for the soil matrix were K, %OM (organic matter), %silt and Cu. For the spatial matrix, PCNM58, PCNM16, PCNM3, PCNM138, PCNM127, PCNM131 were selected.

These represent the spatial relationship between plots both at the local scale (PCNM138) and on the regional scale (PCNM3); (Appendix 3).

A Pearson correlation test verified that the regional-scale spatial relationship represented by PCNM3 was independent of climate and soils variables (Appendix 4).

VARPART showed that the combined effects soil, climate and spatial matrices explained 44% of variation in AGB (Table 3). Space, soil and climate, alone and in interaction, had Radj 2 values of =0.35 and 0.15, respectively (p<0.001). Climate did not have a significant effect on AGB. The explanation in AGB variation caused by spatial distribution and soil, alone and in interaction, was significant (p < 0.001). The individual effect of space was highly significant and that of soil significant but small (R 2 adj=0.058). shown for all the fractions measured for space (Sp), soil (So) and Climate (Cli). The individual effect of a matrix after removal of the effects of others is indicated by the symbol ¨|¨. Overall model R2adj was 0.44.

Multiple regression analysis

Linear regression enabled the variables with most influence on variability in AGB to be identified (Table 4), according to the Mallows' Cp values obtained from the regression<n: the variables with higher values are those that exert a greater influence on biomass variation. Plot spatial distribution was found to influence AGB variation strongly, and potassium was among the soil fertility variables that was also associated with AGB variation.

Variables

DISCUSSION

Tropical forests play a fundamental role in changes to atmospheric carbon concentrations in the industrial era. They act as a carbon sink that varies from year to year and can revert, becoming a source of carbon in drought years or as a result of anthropic disturbances. Monitoring and evaluation of current carbon stocks in biomass in disturbed tropical forests is important for understanding their contribution to climate change mitigation. Several studies involving monitoring of field plots show large variations in carbon sequestration and storage which could be related to the degree of previous disturbance [START_REF] Poorter | Biomass resilience of Neotropical secondary forests[END_REF][START_REF] Mitchard | Consequences of Environmental Service Payments for Forest Retention and Recruitment in a Costa Rican Biological Corridor[END_REF].

The objective of our study was to characterise the AGB of Costa Rican rain forests, determine whether AGB in production forests is different from that in primary forest, and to determine the effects of spatial and environmental variables on AGB. We found that plot spatial distribution was the factor that best explained variability in biomass, followed by soil fertility. Climate variables were shown to have no effect. These results are based on 290,000 measurements of trees from 141 plots which were enumerated up to seven times in a period of 15 years.

The quantity of biomass in a forest determines the potential quantity of carbon (1 Mg of biomass = 0.5 Mg of carbon) [START_REF] Brown | Aboveground biomass estimates for tropical moist forests of the Brazilian Amazon[END_REF]) that has been sequestered from the atmosphere and stored. On this basis, between 2000 and 2015 the intact primary forests studied in this research would have stored on average 148.15 Mg C per hectare and production forests, 164.65 Mg C per hectare.

Production forests contain greater AGB than intact primary forests

Plots in primary production forests had higher mean AGB ha -1 than intact primary forests during the period 2000-2015. This result demonstrates the potential of sustainable management as a natural climate solution i.e. that decreases the emission of greenhouse gases or increases carbon sequestration in forests. Sustainable logging techniques are already recognised for their potential to reduce carbon emissions resulting from forest logging [START_REF] Ellis | Forest Ecology and Management[END_REF]. Numerous studies have demonstrated that in forests subject to reduced-impact logging (RIL) under sustainable management plans, the biomass retained was substantially greater than in forests that were conventionally logged [START_REF] Putz | Sustaining conservation values in selectively logged tropical forests: The attained and the attainable[END_REF][START_REF] Sasaki | Sustainable Management of Tropical Forests Can Reduce Carbon Emissions and Stabilize Timber Production[END_REF][START_REF] Cerullo | Actively restoring resilience in selectively logged tropical forests[END_REF]. Also, a study in Amazonian forests demonstrated that AGB recovers more quickly after RIL than after conventional logging [START_REF] Rutishauser | Rapid tree carbon stock recovery in managed Amazonian forests[END_REF].

Unfortunately, records of logging intensity in the production forests we studied are not now available. However, in the Costa Rican forest management context, production forests are subject to RIL and a very low logging intensity under a strict forest management protocol (Alice-guier et al.

2020

), in accordance with article 20 of the Ley Forestal (Forestry Law) No. 7575 from 1996. Finegan and Camacho (1999), in a typical example, recorded the cutting of four trees per hectare for a mean volume of 10m 3 ha -1 in rain forest at an experimental site in the north of the country. RIL can be translated into a reduction of 50% or more of the impact caused by collateral damage [START_REF] Putz | Improved tropical forest management for carbon retention[END_REF][START_REF] Sasaki | Sustainable Management of Tropical Forests Can Reduce Carbon Emissions and Stabilize Timber Production[END_REF][START_REF] Cerullo | Actively restoring resilience in selectively logged tropical forests[END_REF].

Our study suggests that under certain circumstances, AGB in production forests can be greater than that in intact primary forests. AGB resilience in neotropical secondary forests is well-studied [START_REF] Poorter | Biomass resilience of Neotropical secondary forests[END_REF]) but the potential for AGB storage in production forests has been less reported in the literature. The regeneration of fast-growing long-lived tree species in logging gaps could contribute more biomass to the system [START_REF] Herault | Growth responses of neotropical trees to logging gaps[END_REF] though this is probably unlikely under the low-intensity harvesting that typifies forest management in Costa Rica. However, carbon stock enhancement after sustainable logging could be converted into carbon credits for initiatives such as REDD+ [START_REF] Cerullo | Actively restoring resilience in selectively logged tropical forests[END_REF].

Another possible explanation for our results is that edge effects due to forest fragmentation are in fact impacting AGB of primary forests, as has been shown at an Amazonian site by [START_REF] Laurance | RAIN FOREST FRAGMENTATION AND THE[END_REF]. Both production and primary forests in our study are located on private farms in fragmented landscapes, as documented by Morse et al. (2009) for the northern zone of the country. While pasture was for many years the main agricultural land use, agricultural intensification, for example the spread of pineapple agroindustry, is a recent trend, potentially exacerbating edge effects in the remaining forest [START_REF] Shaver | Coupled social, economic and ecological outcomes of agricultural intensification in Costa Rica and the future of biodiversity conservation in tropical agricultural regions[END_REF]. However, [START_REF] Schedlbauer | Rain forest structure at forest-pasture edges in northeastern Costa Rica[END_REF] showed that AGB was not affected by proximity to forest edges in north eastern Costa Rica, where most of the sample plots of the present study are located, and changes in understorey vegetation at edges are minimal (Bouroncle and Finegan 2012).

Influence of spatial, soil and climate variables on above-ground biomass

AGB and biomass productivity depend on environmental conditions in terms of resource availability (water, nutrients and light) and on forest attributes, in terms of quality and quantity of vegetation [START_REF] Lohbeck | Biomassis the main driver of changes in ecosystem process rates during tropical forest succession[END_REF][START_REF] Poorter | Biodiversity and climate determine the functioning of Neotropical forests 1423-1434[END_REF]. Furthermore, the resilience of tropical forests to long-term and discrete disturbances is defined by various dynamic processes that in turn are shaped by different drivers that act simultaneously. Climate variation (precipitation and temperature) is one of these drivers. Indeed, numerous studies have associated climate and soil with AGB at the local and regional scale, suggesting a potential role on a global scale [START_REF] Malhi | The regional variation of aboveground live biomass in oldgrowth Amazonian forests[END_REF][START_REF] Slik | Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics 1261-1271[END_REF].

However, our study showed a null effect of climate variables on variation of AGB and demonstrated that the effect of plot spatial distribution was the most relevant factor in explaining this variability.

Although our study covered four climate regions, it is probable that the range of precipitation and temperature covered by our sample plots is not as great as in other studies [START_REF] Lewis | Above-ground biomass and structure of 260 African tropical forests[END_REF], Poorter et al. 2015), the results of which indicate that climate-related factors have the most influence on biomass variability.

AGB variation in our study was more strongly explained by plot spatial distribution than by soil fertility or climate-related variables. As is the case for forest composition and species diversity [START_REF] Legendre | Partitioning beta diversity in a subtropical broad-leaved forest of China[END_REF], the relationship between AGB and plot spatial distribution may be influenced by dispersal limitation and regional biogeography, if different dominant species have different potentials for accumulation of AGB due to differences in key functional traits such as maximum adult height [START_REF] Shaver | Coupled social, economic and ecological outcomes of agricultural intensification in Costa Rica and the future of biodiversity conservation in tropical agricultural regions[END_REF]. The species composition of the forests we studied varies both within landscapes, for example in the northeast of the country [START_REF] Sesnie | Landscape-Scale Environmental and Floristic Variation in Costa Rican Old-Growth Rain Forest Remnants[END_REF]) and between forests in the northeast and those of the southwest (compare [START_REF] Sesnie | Landscape-Scale Environmental and Floristic Variation in Costa Rican Old-Growth Rain Forest Remnants[END_REF][START_REF] Cornejo | Phytogeography of the trees of the Osa Peninsula, Costa Rica[END_REF]. Within-landscape and regional variation in species composition could generate the effects on AGB of the spatial variables PCNM 138 (within landscapes) and PCNM 3 (regionally). [START_REF] Chisholm | Scale-dependent relationships between tree species richness and ecosystem function in forests[END_REF] reported that species richness and AGB were positively related across forest sites at small spatial scales and this could be attributed to the local variation in stem density, more than to the effect of species, niche complementarity or facilitation [START_REF] Chisholm | Scale-dependent relationships between tree species richness and ecosystem function in forests[END_REF]. Therefore, forests that share geographical locations would share similar environmental conditions, potentially displaying a similar composition and structure and AGB.

The relationship between soil and AGB often shows mixed and conflictive results in the literature. Often this is because different studies use slightly different sampling methodologies (for example, depth and intensity of the sample), which will include different nutrients and differ between each other if the sample represents the available quantity or the total quantity of these nutrients. We took soils data from a national soil database [START_REF] Mata | Buenas prácticas en la elaboración de mapas de suelos[END_REF], in contrast to studies like Poorter et al. (2016), who used CEC from a gridded global soils database as an estimate of fertility. Therefore, different methodologies for obtaining this data could be a factor influencing results.

In our study, potassium was the soil variable with most influence on biomass variability. K was correlated with local AGB distribution in a 50 ha forest plot in central Panamá [START_REF] Ledo | Lianas and soil nutrients predict fi ne-scale distribution of above-ground biomass in a tropical moist forest 1819-1828[END_REF] and with AGB in secondary rain forests across north eastern Costa Rica (Santiago et al. 2009). Also, when added with N in a tropical moist forest fertilization experiment, K increased tree growth rates [START_REF] Wright | Potassium, phosphorus, or nitrogen limit root allocation, tree growth, or litter production in a lowland tropical forest[END_REF]). Our study complements the cited work suggesting that soil K plays a role in regulating forest AGB at multiple scales [START_REF] Ledo | Lianas and soil nutrients predict fi ne-scale distribution of above-ground biomass in a tropical moist forest 1819-1828[END_REF].

Research perspectives

The percentage of variation in AGB not explained by climate, soil and spatial variables (44%) in our research could be related to indirect effects of underlying drivers such as the structural attributes of the forests: tree diameter, tree density and specific leaf area. These attributes might vary between communities (due to disturbances) and across communities (due to environmental gradients) [START_REF] Poorter | Diversity enhances carbon storage in tropical forests[END_REF]. For example, the study by [START_REF] Shaver | Coupled social, economic and ecological outcomes of agricultural intensification in Costa Rica and the future of biodiversity conservation in tropical agricultural regions[END_REF] reported that, in primary tropical forests, AGB was positively correlated with community-weighted mean adult height. Furthermore, the relationship between the richness of species and AGB may vary along environmental gradients. The richness of species could also be associated with a selection effect where highly productive species, or species of large size which store a lot of biomass, are included in the forest [START_REF] Poorter | Diversity enhances carbon storage in tropical forests[END_REF].

It is therefore recommended that functional traits, species composition and species diversity be included in this kind of research, since functional traits play an important role in increasing carbon stocks and forest productivity, leading to a better biomass dynamic.

Climate Change Mitigation

The climate-related sensitivity of tropical forest carbon is a key uncertainty in predicting the global effects of climate change. Although it is known that droughts and the short-term increase in temperature affect forests, there is uncertainty as to whether these effects will translate into long-term responses [START_REF] Sullivan | Long-term thermal sensitivity of Earth's tropical forests[END_REF]. In addition to the effects of climate change on tropical forests, they are continually threatened by deforestation and degradation that are estimated to contribute to between 8 and 15% of global anthropogenic carbon emissions, which exacerbates climate change (Chazdon et al. 2016). It is in this context that sustainable tropical forest management is emerging as a mechanism in response to global efforts to mitigate carbon emissions.

Our research showed that production forests (managed in a sustainable way) under some circumstances, can accumulate more biomass than primary forests. This potential for carbon sequestration and storage in production forests suggests the resilience of these forests to discrete disturbances. The latter may push these ecosystems from a stable steady-state to a state of instability which, without major disturbances, will transition back to their initial state. This displacement will depend on the type, scale, intensity, and duration of the disturbance. If it is large, frequent or novel, the return of the ecosystem to its original state is unlikely [START_REF] Ghazoul | Conceptualizing Forest Degradation[END_REF]. Therefore, these forests may function as carbon sources or sinks, depending on the type of management to which they are subjected (Piponiot et al. 2016a). According to our results, production forests in Costa Rica would be acting as carbon stores and possibly sinks because of the sustainability of the logging techniques applied.

CONCLUSIONS

The overall objective of our research was to estimate above-ground biomass (AGB) in sustainably logged production forests and to compare it to above-ground biomass in intact primary forests. Furthermore, we examined the relationship between AGB and i) the spatial distribution of the plots, ii) climate variables, and iii) soil fertility variables, to see if these had any effect on biomass storage potential. Combining analysis of all plots according to type of forest, production forests were, on average, those that accumulated most AGB in the period 2000-2015. Furthermore, the spatial distribution of the plots was the factor that best explained the variability of biomass, followed to a lesser degree by soil fertility, while climate variables were shown to have no effect.

Although we did not find an effect of climate on AGB variation, the effect of water availability on vegetation growth resulting in the accumulation of more biomass over time is undeniable. It is probable that research on a regional or continental scale would provide evidence of the effect of climate patterns on biomass variability.

Even though it is well known that tropical forests are the richest in carbon and the most productive of the forest biomes, they are constantly under threat, which means that mechanisms need to be found to support their sustainable management and conservation. The productivity, conservation and mitigation potential of production forests makes them important ecosystems that can enhance tropical forests resilience in relation to climate change. Sustainable forest management, in addition to encouraging an important service by providing sustainable timber, could also be a natural climate solution, and a strategy for restoring the mitigation potential of tropical forests in the current climate context.

Figure 1 .

 1 Figure 1. Map of the distribution of the study plots across Holdridge Life Zones in Costa Rica.

Altitudinal Tier Altitudinal Range (masl) Mean annual precipitation (mm) Mean annual temperature (°C) No. of plots Type of forest

	Tropical wet forest,	Lowland	0 -700	4000 -8000	24 -30	6	production
	transition to
	premontane
	Premontane		Premontane 700 -1400	8000 +	18 -24	7	primary (3
	rainforest							plots)
								production (4
								plots)
	Tropical moist forest Lowland Premontane Premontane 700 -1400 0 -700	2000 -4000 8000 +	24 -30 18 -24	8 4	primary production
	Premontane moist rainforest transition	Premontane 700 -1400	2000 -4000	18 -24	1	primary
	forest, transition to to lowland
	lowland
	127	Table 1 Distributions of primary and production forest study plots by life zones.
	Tropical moist forest,	Lowland	0 -700	2000 -4000	24 -30	2	primary
	transition to 128
	premontane
	Tropical wet forest	Premontane 700 -1400	4000 -8000	18 -24	1	primary
	Premontane wet	Premontane 700 -1400	4000 -8000	18 -24	18	primary (1
	forest, transition to						plot)
	lowland							production
								(17 plots)
	Tropical wet forest	Lowland	0 -700	4000 -8000	24 -30	94	primary (54
								plots)
								production
								(40 plots)

Table 1 .

 1 Table 2). Descriptive statistics for AGB in primary and production forests. Standard deviation (SD)

	Type of forest	No. of	Mean AGB	SD	SE	Min	Max
		plots	(Mg ha -1 )
	primary	70	296.3	90.9	10	123.1	530.8
	Production	71	329.3	75.9	9.9	160.3	496.8

Table 2

 2

	Variable	R 2 Adj	F	P
	Sp	0.35	13.98	0.001
	So	0.15	7.44	0.001
	Cli	0.02	2.62	0.071
	All variables	0.44	10.19	0.001
	Sp|So,Cli	0.28	12.29	0.001
	So|Sp,Cli	0.058	4.42	0.001
	Cli|Sp,So	0.004	1.49	0.239

. Variation partitioning of above-ground biomass of 141 plots explained by spatial and environmental variables. The values for adjusted R 2 , the F statistic and P value for significance are

Table 3 .

 3 Values from multiple regression statistics for the explanatory variables according to the value of Mallows' Cp criterion for prediction.

		T	Mallows' Cp	P
	PCNM58	-4.72	33.26	<0.001
	PCNM16
		-4.51	31.32	<0.001
	PCNM127	-3.46	23	<0.001
	K	2.65	18.03	0.01
	PCNM131	2.64	17.95	0.01
	PCNM3	2.46	17.06	0.02
	%MO	1.86	14.44	0.07
	Silt	1.75	14.05	0.08
	Cu	1.44	13.06	0.15
	PCNM138	-1.26	12.58	0.21
	Temperature	-1.25	12.55	0.21
	Precipitation	1.04	12.07	0.3

ACKNOWLEDGEMENTS

We are grateful for the support provided by the postgraduate school of the Tropical Agricultural Research and Higher Education Centre (Centro Agronómico Tropical de Investigación y Enseñanza, CATIE), for our research.

To the Costa Rica Forest Ecosystems Observatory (Observatorio de Ecosistemas Forestales de Costa Rica, OEFo), whose data and information were key to carrying out the research. This publication was made possible thanks to funding from the CGIAR Research Program on Forests, Trees and Agroforestry (FTA).

We would like to thank all the funding partners who supported this research through their contributions to the CGIAR Fund.

For the list of donors to the Fund, please visit: http://www.cgiar.org/about-us/our-funders/ <http://www.cgiar.org/about-%20us/our-funders/> We would also like to thank our English language scientific editor, Kate Roberts, for her thorough review of our manuscript.


Qian He

Qianqian Hou

Lu Hong

Xiaoning Lu

Isabelle Ziegler-Devin

Laurent Chrusciel

Arnaud Besserer

Nicolas Brosse
email: nicolas.brosse@univ-lorraine.fr

Effect of highly efficient steam explosion treatment on beech, poplar and spruce solid wood physicochemical and permeable performances.1 1

Keywords: steam explosion, solid wood, morphology, color, chemical changes, compression, permeability

The effect of steam explosion treatment (SE) on the appearance and water permeability of solid beech, poplar, and spruce wood was investigated. Wooden test specimens were steam blasted after water or acid impregnation at 10 ~ 16 bar for 5 ~ 15 minutes, and their chemical composition was determined by chromatographic analysis after hydrolysis and infrared spectroscopy. Macro/micro cracks with shrinkage and reduced sphericity after drying were observed by scanning electron microscopy. Darker color and more severe changes in colorimetric parameters were measured spectrophotometrically for SE treated samples, especially under acidic conditions or higher severity factors (SF). To some extent, the physicochemical and permeability properties of SE treated wood samples could be simulated by considering the correlations of the different factors. No significant deterioration in chemical content, longitudinal compressive modulus of elasticity (MOE // ) and modulus of rupture (MOR // ) was observed in SE specimens treated with water. Higher permeability was obtained under a mild condition of 180°C-5 min for poplar and a higher SF condition for beech and spruce. Therefore, SE could be an efficient method for modifying solid wood to improve its permeability and functionality.

Introduction

An increasing interest is given to wood material because of its renewable, ecological and inexpensive characteristics [START_REF] Souza | Wood-based composite made of wood waste and epoxy based ink-waste as adhesive: A cleaner production alternative[END_REF][START_REF] Akpan | Eco-friendly and Sustainable Processing of Wood Based Materials[END_REF].

However, due to the composition of the cell wall of wood, which consists of cellulose, hemicellulose, and lignin, some disadvantages have been identified, including rotting and poor fire resistance indoors and outdoors [START_REF] Can | Physical, biological and chemical characterisation of wood treated with silver nanoparticles[END_REF]. Different types of preservatives or flame retardants have been used to modify the wood to obtain a high-performance material [START_REF] Zelinka | Corrosiveness of Thermally Modified Wood[END_REF][START_REF] Pondelak | Improving the flame retardancy of wood using an eco-friendly mineralisation process[END_REF].

Marco/micro-porous structures provide an opportunity for these functional reagents to penetrate the wood by impregnation [START_REF] Taghiyari | Penetration of Different Liquids in Wood-Based Composites: The Effect of Adsorption Energy[END_REF]. Macroscopic pores in tracheids or vessels are the main penetration channels in the longitudinal direction of the wood while pits and rays are the microscopic pores connecting the transverse channels between tracheids or vessels [START_REF] Tarmian | Treatability of wood for pressure treatment processes: a literature review[END_REF]. However, some of chemical constituents such as extracts or thylose and the structure of the aspirated pits in the wood have a negative influence on the wood penetrability [START_REF] Monteiro | Importance of Pits in Corymbia Citriodora (Hook.) K.D. Hill & L.A.S. Johnson (Myrtaceae) Wood Permeability[END_REF][START_REF] Zhang | Mechanism for De-aspirating Pits in Subalpine Fir by Steam Explosion Prior to Drying[END_REF].

Many physicochemical methods have been used in the pretreatment of wood to improve its penetrability. It has been shown in previous studies that acidic, alkaline and organic or inorganic reagents can allow the formation of microscopic pores and flow channels in the anatomical structure of wood while causing the degradation of chemical contents such as hemicellulose, lignin and extracts [START_REF] Nicholas | Chemical Methods of Improving the Permeability of Wood[END_REF][START_REF] Stamm | Effect of Chemical Treatment on Wood Permeability[END_REF][START_REF] Qu | Effects of aluminum sulfate soaking pretreatment on dimensional stability and thermostability of heat-treated wood[END_REF]. Humar et al. have investigated the effect of swelling agents including triethanolamine and formic acid on the penetration of copper-ethanolamine based preservatives into wood and significant improvement of permeability of preservatives was observed with negatively affecting their high leachability [START_REF] Humar | Influence of wood swelling agents on penetration and copper leaching of copper-ethanolamine based wood preservatives[END_REF]. James et al. demonstrated that the permeability of alkali-treated wood chips was greatly increased by saponification of the esters and the weakening of the intercellular region of the wood structure [START_REF] Minor | Improved penetration of pulping reagents into wood[END_REF]. Xu et al. explored the influence of supercritical carbon dioxide (SC-CO 2 ) on the permeability of hardwood and found highly improved penetration efficiency due to the reduction of tyloses involved in the vessels [START_REF] Xu | Effect of Supercritical Carbon Dioxide Treatment on Gas Permeability of Paulownia Fortunei Heartwood and Sapwood[END_REF].

Physical methods such as ultrasonic, cryogenic freezing and hydrothermal treatments have also been widely utilized to improve wood permeability as well [START_REF] Tanaka | A preliminary study on ultrasonic treatment effect on transverse wood permeability[END_REF][START_REF] Yorur | Improving Impregnation and Penetration Properties of Refractory Woods Through Cryogenic Treatment[END_REF]. Hydrothermal treatments play a significant role in the improvement of permeability and the appearance of wood, attributing to the degradation of hemi-cellulose and polysaccharide decomposition under the release of acetic acid and other substances [START_REF] Esteves | Heat-induced colour changes of pine ( Pinus pinaster ) and eucalypt ( Eucalyptus globulus ) wood[END_REF]. Steam explosion (SE) treatment is one of the specific hydrothermal treatments and has been applied in biomass modification, which is characterized by its facility, high efficiency and environmental friendliness [START_REF] He | Lignin-First Integrated Steam Explosion Process for Green Wood Adhesive Application[END_REF]. The lignocellulosic material is subjected to steam at high temperature and pressure for a certain period of time, and then the pressure is suddenly released [START_REF] Martino | Steam explosion pretreatment used to remove hemicellulose to enhance the production of a eucalyptus organosolv dissolving pulp[END_REF][START_REF] Donaldson | Ultrastructure of steam-exploded wood[END_REF].

In general, studies have focused almost exclusively on fractionated wood (sawdust and chips) in order to increase the accessibility of cellulose to biocatalysts. Seidel et al. has investigated the enzymatic digestibility of different biomasses under SE treatment and a positive influence on the enzymatic digestibility of softwood and hardwood species was observed, especially with high enzyme dosage [START_REF] Seidel | The influence of the explosive decompression in steam-explosion pretreatment on the enzymatic digestibility of different biomasses[END_REF]. Balan et al. studied the most desired conditions of the enzymatic hydrolysis reaction in order to optimize the pretreatment for a certain biomass [START_REF] Balan | Steam Explosion Pretreatment of Beechwood. Part 1: Comparison of the Enzymatic Hydrolysis of Washed Solids and Whole Pretreatment Slurry at Different Solid Loadings[END_REF]. Simangunsong et al. have investigated the effect of particle size and severity factors on the xylan recovery of beech wood under SE treatment and the high degradation extent of hemicellulose was obtained for the smallest particle size of biomass with incomplete autohydrolysis at the largest particle sizes [START_REF] Simangunsong | Steam Explosion of Beech Wood: Effect of the Particle Size on the Xylans Recovery[END_REF].

In the literature, very little work has been done on the steam explosion of solid wood and the morphological impact of the process on the structure of the wood. Some works described an increase in the permeability of solid exploded wood by steam explosion but at low pressure (2~7 bars). It has been shown that low pressure SE treatment can induce an extension on lumina volume, a destruction on the obstacles and aspirated pits among wood structure, leading to the increase of wood permeability [START_REF] Kanagaw | Improvement of dryability by local steam explosion for Japanese cedar[END_REF]. Kang et al. explored the effect of SE at low pressure on wood cell walls and higher permeability with the observation of better sound absorption coefficient [START_REF] Kang | Steam exploded wood cell walls reveals improved gas permeability and sound absorption capability[END_REF]. Kang et al. also discussed the effects of SE treatment on the appearance, anatomical features, permeability and sound absorption capability (SAC) of yellow poplar with improvement in permeability and SAC along the grain direction. [START_REF] Muzamal | Mechanistic study of microstructural deformation and stress in steam-exploded softwood[END_REF] described the formation of microcracks in wood cell walls following actual steam explosion of softwood (14 bars, 10 min). They showed that the largest deformations and damages in the radial cell wall were observed in earlywood cells [START_REF] Muzamal | Mechanistic study of microstructural deformation and stress in steam-exploded softwood[END_REF].

Therefore, a better understanding of the phenomena induced by SE on the macro/micro-morphology, the redistribution of chemical contents and the physical properties of wood seems therefore important for future applications. However, the physicochemical and permeable properties of SE treated solid wood has not been investigated in detail.

In this study, three solid wood species were selected including spruce, poplar and beech in order to investigate the physicochemical and permeable properties of SE treated solid wood. The color difference parameters, macro-graphs, anatomical features, mass loss, pH value of liquid phase, chemical contents, FTIR measurement mechanical properties, and impregnation rate were explored for solid wood samples under varied severity factors (SF) of SE treatment. The comparison of physicochemical and permeability characteristics of SE-treated solid wood was conducted among different species and varied SFs of SE treatments.

Materials and methods

Solid wood material

Spruce (Picea glauca), poplar (Populus alba) and beech (Fagus sylvatica) wood species harvested in Frace were used in this study. The density of the wood species was 0.43, 0.46 and 0.70 g/cm 3 , respectively and the dimension of the wood samples were 200 mm (longitudinal) × 20 mm (radial) × 20 mm (tangential). None visible defects and decay were found for solid wood samples. Then, they were half cut to the dimension of 100 mm (longitudinal)× 20 mm (radial)× 20 mm (tangential) and half of them were reserved as the controls. All the specimens were oven-dried at 103°C for 24h to achieve absolute dry mass.

Steam explosion (SE) treatment

The specimens were immersed in the distilled water or 1% H 2 SO 4 (dilute sulfuric acid, by vol.) for 15 h at 25°C under vacuum condition and the pressure was released every 15 min (-0.09 MPa). After immersion, all the specimens were drained off and put into the reactor of SE equipment. Four kinds of severity factors (SFs) of SE treatment were selected as shown in Table 1 [START_REF] Vroom | The H Factor: A Means of Expressing Cooking Times and Temperatures as a Single Variable[END_REF][START_REF] He | Lignin-First Integrated Steam Explosion Process for Green Wood Adhesive Application[END_REF]. After SE treatment, the liquid phase was collected and treated solid wood specimens were oven-dried at 103°C for 24h to achieve absolute dry mass. Eight repetitions were conducted for each condition. Some details for the SE treatment: The main equipment involved in SE treatment included a steam generator, a high-pressure reactor (the volume of the reactor is 4L) and a discharge tank to receive the specimens after SE explosion. During the SE process, the saturated steam with high pressure was prepared by the steam generator.

Then, the steam went continuously into the high-pressure reactor with the wood specimens in it for a duration. The wood specimens were put into the reactor in advance. After that, a sudden pressure drop (300 ms) occurred and the vapor expanded into the wood specimens. Finally, the treated specimens went into the discharge tank [START_REF] Simangunsong | Steam Explosion of Beech Wood: Effect of the Particle Size on the Xylans Recovery[END_REF][START_REF] Ziegler-Devin | Steam Explosion Pretreatment of Lignocellulosic Biomass: A Mini-Review of Theorical and Experimental Approaches[END_REF].

Mass loss and pH measurement

The mass loss was tested according to the equation (1) based on the mass of dried solid wood specimens before and after SE treatment. pH value of liquid phase was measured by an acid-base testing device (PH-25/3C, Want Balance Instrument Co., Ltd., P.R.China). Three repetitions were conducted for each condition.

Mass loss (%)=(mass untreated -mass treated )/mass untreated ×100%]

(1)

Color difference

The parameters of surface color difference for solid wood specimens were measured by a spectrophotometer (CM-600d, Konica Minolta Co. Ltd., Japan). ∆L*, ∆a*, ∆b* and ∆E are the intensity of brightness to darkness, greenness to redness, blueness to yellowness and the total color difference, respectively. The parameters were recorded and compared between the control and treated specimens. The methodology of colour difference calculation was listed in the supplementary material.

Chemical contents measurement

Free extracts of milled wood powder (1g, 60 mesh) prepared from the control and treated specimens were utilized to test the contents of acid-insoluble lignin and monomeric sugars based on TAPPI T222 om-02 and NREL/TP-510-42618~c42622

standard by high-performance liquid chromatography (HPLC, ICS-3000 Dionex).

ATR-FTIR spectra

Milled wood powder (60 mesh) prepared from the control and treated specimens was measured by a Fourier transform infrared device (NICOLET 6700). The recording range was from 400 to 4000 cm -1 and the resolution for the device is 4 cm -1 .

Micro-structure measurement

The scanning electron microscope was used to observe micro-structure of solid wood specimens (TM-1000, Hitachi, Japan). The gold layer was deposited on the wood surface under vacuum condition prior to the observation. The sphericity for the shapes of lumina (or tracheids) and wood fiber cells was calculated by Matlab with the comparison of the circle shape (value = 1). The methodology of sphericity calculation was listed in the supplementary material.

Mechanical measurement

The longitudinal compression modulus of elasticity and modulus of rupture (parallel to the grain, MOE // and MOR // ) were measured by a universal testing machine according to the standard ASTM D4761-05. The dimension of specimens was 60 mm (longitudinal) × 20 mm (radial) × 20 mm (tangential). The specimens after SE treatment were oven-dried at 103°C for 24h to achieve absolute dry mass and they were sealed in the plastic bags for two weeks in the lab (20°C/65%RH) before the mechanical measurement. The loading speed was 2mm/min and the failure was achieved in 1min. Three repetitions were conducted for each condition.

Impregnation rate measurement

The control and treated solid wood specimens were put into an impregnation tank.

After closing the tank, the air was pumped out under a pressure of -0.09 MPa for 30min. Then, water was pumped into the tank under a pressure of 10 bar for 20 min.

After impregnation, all the specimens were put out and drained off. The change ratios of mass before and after impregnation were measured for all the specimens according to the equation (2). Three repetitions were conducted for each condition.

[Impregnation ratio (%)=(mass after -mass before )/mass before ×100%]

(2)

Where Mass before representing the mass for dried samples and mass after representing the mass of samples after impregnation process.

Results and discussions

Wooden test specimens (100 mm × 20 mm × 20 mm) have been steam-exploded after water or acid impregnation according to the procedure described in section 2.2 and in Table 1.

Macro-/micro-morphology properties

The graphs of macro-morphology for solid wood specimens before and after SE and their color differences are shown in Figure 1. Darken color was observed for the treated specimens, especially for the higher SF or for the acidic conditions. The color difference parameters were further measured and calculated (Figure 2). For beech, poplar and spruce specimens, higher change ratios were observed for ∆L and ∆E compared with other parameters. ∆L highly decreased while the total color difference of ∆E increased after SE treatment. The highest change ratios (∆L, ∆E, ∆a and ∆b)

were observed for the acid treatment because of hydrolytic and oxidative coloring reactions among wood components during SE treatment [START_REF] Sikora | Impact of thermal modification on color and chemical changes of spruce and oak wood[END_REF]. As stated in previous studies, degradation of cell wall components occurred during the thermal treatment, leading to deacetylation of hemicelluloses, modification of lignin network and production of chromophores [START_REF] Sundqvist | Color response of Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and birch (Betula pubescens) subjected to heat treatment in capillary phase[END_REF][START_REF] Nimz | Wood-chemistry, ultrastructure, reactions[END_REF]. As a result, oxidation and hydrolysis products such as quinones, acetic acid and other substances are the main reason for the color variation under hydrothermal process. In addition, it was observed that the degree of darkening of the wood surface depended on the wood species. For the SE-treated specimens with distilled water immersion, significant liner relationship between SF and color difference parameters (∆L and ∆E) was found for each wood species with high correlation coefficient of more than 90% (Figure 2d and2e).

Some cracks were also observed in the cross-section of the hardwood specimens as shown in Figure 1. These cracks, which resembled honeycombs, occurred mainly along the rays of the wood. As investigated in previous studies, wood rays presented maximum tensile stress during the initial drying stage. Then, cracks appeared and spread in the radial direction, frequently between or along the rays, associated with wavy folds on the wood surface. These cracks which increased with the duration of SE treatment were attributed to high moisture content involved during the cooking phase of SE and to high temperature used in the drying process [START_REF] Oltean | Influence of temperature on cracking and mechanical properties of wood during wood drying -A review[END_REF][START_REF] Simpson | Dry kiln operator's manual Chap.2 Kiln types and features[END_REF]. The softwood displayed a different behavior as seen in Figure 1c.

The spruce specimens have a highly modified surface and wood bundles were obtained after pressure release of SE treatment. This result was attributed to the different anatomical characteristic, chemical components and macropolymers involved in different wood species. Beech and poplar mainly consisted of wood fiber cells and lumen, which play a significant role in the resisting to the impact. While, spruce mainly consisted of the tracheids structure and the stress concentration could affect the whole structure during the impact.

The micro-structure was investigated as well for different wood specimens and compared with the control as shown in Figure 3, Figure S1, S2 and S3. For the control, the specimens show morphology consistent with hardwood (Figure 3a and 3b) or softwood (Figure 3c) respectively. For beech, poplar and spruce specimens (Figure S1a, S2a andc S3a), the spiral thickening and pits structure were completely involved in smooth cell walls from longitudinal direction. Besides, the scalariform perforation plates between the vessels were naturally long with many partitions. Some local cracks were observed from both sections as well and these could be attributed to the samples preparation [START_REF] Bekhta | Anatomical study of short -term thermomechanically densified alder wood veneer with low moisture content[END_REF].

After SE treatment, in cross section visible deformations and axial cracks were observed for vessels or tracheids. For beech, poplar and spruce, some fibers, vessels and tracheids shranked considerably and the deformations were uneven, accompanied by an obvious reduction in lumen size especially for the condition of 180°C and 15 min (Figure 3). The shapes displayed in different colors of lumen (or tracheid) and wood fiber cell were selected from the micrographs of the control and SE-treated specimens. The sphericity for these shapes was calculated based on the circle shape and the correlation between the SF and sphericity for different wood species was as shown in Figure 4. Significant decrease of sphericity was obtained for the treated specimens compared with the control, especially with the higher SF=3.53 (180°C and 15 min) for hardwoods and SF=3.64 for spruce. Besides, the lowest sphericity was achieved for the treated poplar sample under the condition of SF=3.53 as indicated in

Figure 3b

. Nonlinear correlation of the SF and sphericity of cellular structure was observed for spruce specimens with the correlation coefficent of 85.98% while no significant relationship was for beech and poplar specimens. From longitudinal direction (Figure S1 to S3), some cell walls peeled and the surface morphology is irregular. The scalariform perforation plates between vessels were significantly deformed with broken partitions inside as labeled in figures. Another obvious feature of cell wall wrinkling was observed for SE-treated specimens under higher severity factor and acidic condition. These wrinkles were accompanied, especially for acidic specimens, by cracks and collapses for vessel structure, annual rings, and fibers.

These broken features were mainly attributed to two factors, the explosive decompression of SE treatment and the drying process, as shown in Figure 1. In addition, some droplets appeared on the surface of cell wall after SE treatment, especially for high SE severities. These results could be attributed to the well-known migration or condensation reaction of lignin and the hydrolysis reaction of hemi-cellulose during SE treatment [START_REF] He | Lignin-First Integrated Steam Explosion Process for Green Wood Adhesive Application[END_REF][START_REF] Nader | Lignocellulosic Micro and Nanofibrillated Cellulose Produced by Steam Explosion for Wood Adhesive Formulations[END_REF].

Mass loss and chemical characteristics

Mass loss of SE treated wood specimens is an important feature to evaluate the treatment. As shown in Figure 5a, a significant increase in mass loss was observed with severity and in the presence of acid catalysis for the different wood species after SE. For beech specimens, the mass loss ranged from 8.04±0.80 to 16.55±4.89; for poplar, the mass loss was from 2.68±0.51 to 13.45±1.87; for spruce, the mass loss ranged from 6.83±0.58 to 12.91±0.34. This loss of mass is mainly related to the degradation of hemicelluloses according to well-known mechanisms of autohydrolysis or acid hydrolysis and the trends observed were in accordance with previous study [START_REF] Gündüz | The Influence of mass Loss on the Mechanical Properties of Heat-treated Black Pine Wood[END_REF]. A greater increase in mass loss was found for the beech specimens. For the spruce specimens at 180°C-10 min, higher standard deviation was observed compared with other conditions. This result was due to the fact that the specimens were broken into bundles during the pressure release.

Even, some part of the specimen was lost especially for the condition of 180°C-15 min. From Figure 5b, a decrease in the pH values of the liquid phase was observed for the different species after the SE treatment, especially for the acidic condition.

This result could be attributed to the fact that more acidic products were generated during autohydrolysis or acid hydrolysis. For beech and poplar, there was no significant variation among the conditions of 180°C-5 min, 180°C-10 min and 200°C-5 min. While, for spruce, the increase of pH at 200°C-5 min could be due to the short duration of SE treatment. These results also indicated that the temperature, duration and SF should be considered together for different wood species under SE treatment.

Furthermore, the variations of main contents of cell wall components in terms of monomeric sugars (after total hydrolysis) and lignin were analyzed (Figure 6). As expected, after glucose, xylose was the dominant monosaccharide in beech and poplar while mannose was the most important in spruce. As stated in previous studies, a decrease in hemicellulose content was obtained especially for higher SF or acidic condition, associated with a relative increase in lignin [START_REF] He | Lignin-First Integrated Steam Explosion Process for Green Wood Adhesive Application[END_REF][START_REF] Ziegler-Devin | Steam Explosion Pretreatment of Lignocellulosic Biomass: A Mini-Review of Theorical and Experimental Approaches[END_REF]. However, the result for SE-treated solid wood specimens was different from sawdust and chips. After SE treatment, the slight decrease of hemicellulose for the specimens was observed for different wood species with higher decrement for the acidic condition. Furthermore, increased xylose was obtained for beech specimen at 200°C-5 min. These results could be attributed to the inhomogeneous distribution of chemical contents among the solid wood specimens after SE treatment. The slight decrease of chemical content also has a positive effect on the mechanical property for SE-treated solid wood specimens.

In order to further investigate the hydrothermal reactions during SE treatment, the FTIR spectra of different wood species were performed as shown in Figure 7. The assignments of the mainly FTIR signals are listed in Table 2. For beech control specimens, the band at 1235 cm -1 , 1505 cm -1 , 1650 cm -1 and 1738 cm -1 were respectively attributed to the C-O stretching vibration, aromatic skeletal vibration plus C=O stretching, absorbed O-H with conjugated C=O and the stretching of C=O in unconjugated ketones, carbonyls and in ester groups. For poplar, the peaks of 1508 cm -1 ,1618 cm -1 and 1745 cm -1 were assigned to C=C-C aromatic ring stretching vibration, aromatic skeletal vibration of C=O stretching with adsorbed O-H and C=O stretching vibration. For spruce, the bands at 1200 cm -1 , 1517 cm -1 , 1600 cm -1 and 1730 cm -1 were attributed to O-H in plane bending vibration, aromatic skeletal vibration, ring stretch vibration related to quinone formation and C=O groups to carboxylation of polysaccharides, respectively [START_REF] Gonzalez-Peña | Rapid assessment of physical properties and chemical composition of thermally modified wood by mid-infrared spectroscopy[END_REF][START_REF] Zhuang | Observation of Potential Contaminants in Processed Biomass Using Fourier Transform Infrared Spectroscopy[END_REF][START_REF] Müller | FTIR spectroscopy in combination with principal component analysis or cluster analysis as a tool to distinguish beech ( Fagus sylvatica L.) trees grown at different sites[END_REF].

After SE treatment, changes in spectra were observed. The band at ≈ 3362 cm -1 attributed to O-H stretching vibration increased and then decreased with increasing duration of SE treatment for different species. This is due to the fact that the degradation of hemicellulose occurred at the initial stage of the SE treatment and then the drop in pH of the liquid phase led to dehydration reactions resulting in a reduction of hydroxyl content [START_REF] Wang | Effect of Saturated Steam Heat Treatment on Physical and Chemical Properties of Bamboo[END_REF]. The band at 1730 ~ 1745 cm -1 assigned to C=O stretching vibration decreased for beech and poplar specimens treated under acidic condition, because of deacetylation reactions involved in the hemicellulose molecules during SE treatment [START_REF] Tjeerdsma | Chemical changes in hydrothermal treated wood: FTIR analysis of combined hydrothermal and dry heat-treated wood[END_REF].

In addition, the correlations of chemical components and beech lignin main inter-unit linkages contents respectively with ∆E, sphericity and mass loss were obtained for the control and SE-treated specimens as shown in Figure 8. High correlation coefficient of 95.45% involved in nonlinear correlation was observed for spruce specimens between lignin content and ∆E parameter while no obvious relationship was found for lignin content of different wood species with ∆E, sphericity and mass loss change rate, respectively (Figure 8a). Furthermore, as detected from Figure 8b, significant nonlinear correlations of hemicellulose content with ∆E and mass loss rate respectively were obtained for poplar specimens without any correlation coefficient found of hemicellulose content with ∆E and mass loss for the other two species. Moreover, no significant relationship was observed as well between hemicellulose content and sphericity for different wood species. As described in Figure 8c, no obvious correlation coefficient was obtained in the relationship of cellulose content with ∆E, sphericity and mass loss change rate, respectively. Better nonlinear correlations of the correlation coefficients ≥ 80% were observed for the beech lignin main linkages with ∆E, sphericity and mass loss change rate, respectively (Figure 9). In this study, SE treatment and the measurements were conducted from solid wood specimens while the composition of lignin was determined in a previous study from beech sawdust [START_REF] He | Lignin-First Integrated Steam Explosion Process for Green Wood Adhesive Application[END_REF]. As a result, reservations can be made about the correlations made based on the different samples (sawdust and solid wood)

and further detailed investigation should be conducted. To some extent, these results provided a great possibility to simulate the morphology, chemical contents, color parameters and mass loss for wood specimens after SE treatment.

Mechanical and impregnation measurements

Mechanical properties of hydrothermally treated wood are strongly affected by the micro-morphology and chemical composition [START_REF] Percin | The effect of heat treatment on the some physical and mechanical properties of beech (Fagus orientalis lipsky) wood[END_REF]. As described in were conducted for treated solid wood specimens compared with the control ones. For the control specimens, higher compressive MOE// and MOR// values were observed for beech and spruce species than that of poplar. This result was due to the different chemical components and anatomical characteristic involved in different wood species.

After SE treatment, for beech and poplar specimens, changes in compressive modulus and strength were obtained depending on the conditions of SE treatment. For beech specimens, higher MOR// and MOE// values were found under the condition of 180°C-15 min compared with the control and other conditions. Moreover, no significant variation was obtained for beech specimens under acidic condition. As referred to poplar species, no significant change was statistically observed for treated specimens under varied SE conditions based on the Origin significance analysis (at the level of 0.05), except for the acidic-treated ones with the lowest MOR // . For spruce, treated specimens were broken easily under higher SFs with no significant variation for the condition of 180°C-5 min as well. As proposed in previous studies, the decrease in mechanical properties observed after hydrothermal treatment is due to the degradation of hemicellulose and the appearance of macro/microcracks during heat treatment. These changes are known to be strongly dependent on wood species, temperature and duration of treatments [START_REF] Oltean | Influence of temperature on cracking and mechanical properties of wood during wood drying -A review[END_REF][START_REF] Poncsak | Effect of high temperature treatment on the mechanical properties of birch (Betula papyrifera)[END_REF]. In this study, SE treatment did not induce a significant decrement on mechanical properties of wood specimens, especially for beech specimens under 180°C-15 min condition and water-treated conditions for poplar and spruce with the comparison of previous research [START_REF] Kubojima | Bending strength and toughness of heat-treated wood[END_REF]. This result could be attributed to no significant hemicellulose degradation observed for SE-treated solid wood species as

shown in Figure 6.

The impregnation measurement was then tested for different specimens and the results were shown in Figure 11. As the spruce specimens were easy to be broken after SE treatment, the fragments recovered were kept and used only for the impregnation test. For the control specimens, the lowest impregnation ratio was found for beech species and high standard deviations were detected for poplar and spruce species, which were due to nonuniformity of cellular microstructure and the anisotropy among wood species. After SE treatment, for beech and poplar specimens, higher impregnation ratios were obtained under the condition of 200°C-5 min and 180°C-5 min, respectively with the comparison of other SE conditions. The highest impregnability was observed for spruce species at 180°-15 min condition (Figure 11a). These results indicate that the previously mentioned SE-induced morphological and chemical changes have a significant effect on the permeability of solid wood specimens. Interestingly, to some extent, the most effective conditions do not systematically correspond to the most severe conditions. Also, acidic conditions are not conducive to an increase in wood permeability. It was further verified by the fact that no significant relationship between the SF and impregnation ratio for different wood species was observed; for poplar and beech specimens, the peak value of impregnation ratio was at the sphericity of ≈ 0.7 while lower values occurred at higher or lower sphericities; for spruce specimens, negative correlation was found between the sphericity and impregnation ratio (Figure 11b). This result can be explained by the decomposition reactions of chemical contents in cell wall components and soft cell wall obtained; on the other hand, low cell wall strength and a higher degree of deformation of the cell lumina, resulted in significant shrinkage of the wood lumina after drying with decreased sphericity values, as indicated by the micro-morphology measurement above. These results indicated that a mild condition (180°C-5 min) was only for poplar solid wood while higher SF condition for beech and spruce solid wood to obtain higher permeability for different wood species.

Conclusions

The appearance and permeability of solid wood were significantly changed by SE treatment. Macro-/micro-cracks were observed with the shrinkage and decreased sphericity for solid wood specimens. Darker tone and higher color parameters of ∆L and ∆E were obtained for higher SF and acidic conditions. No significant decrease in compressive MOE // and MOR // was observed for different wood species except for acidic-treated poplar specimens. The correlations of different factors including SF, chemical content, ∆E, sphericity and mass loss, to some extent, provided a great possibility to simulate the physicochemical and permeable performances for wood specimens after SE treatment. On the other hand, a higher permeability could be obtained under a mild condition of 180°C-5 min for poplar and higher SF condition for beech and spruce species but resulting to significant spruce wood damage.

Thus, SE treatment appears to be an attracting and high-efficient method for solid hardwood treatment to improve its permeability properties. It also provides a positive possibility to further functionally modify natural wood. These high-value solid wood would possess longer period of service and be more widely utilized.

However, SE treatment conditions also induced an increase in multi-scale cracks on the wood structure after the drying process. Thus, an appropriate drying method should be proposed to preserve the morphology of SE-treated specimens.

Figure 10 ,

 10 Figure 10, the mechanical properties of longitudinal compressive MOE // and MOR //

Figure 1 .

 1 Figure 1. Macro-morphology of SE treated specimens from longitudinal direction and transverse section including (a) beech, (b) poplar and (c) spruce under varied SE conditions.

Figure 2 .

 2 Figure 2. Color difference parameters of SE treated samples including (a) beech, (b) poplar and (c) spruce under varied SE conditions. The correlations of SF with (d) ∆E and (e) ∆L.

Figure 3 .

 3 Figure 3. Micro-graphs for (a) beech, (b) poplar and (c) scpruce samples from the cross section under SE condition of 180°C and 15 min with the comparison of control samples. The cellular structures of lumina, wood fiber or tracheids selected from untreated and treated samples, respectively.

Figure 4 .

 4 Figure 4. The correlations of varied SFs with the sphericity of cellular structure for different species.

Figure 5 .

 5 Figure 5. (a) pH value for liquid phase under SE varied conditions for different wood species. (b) Mass loss for SE treated samples under SE varied conditions.

Figure 6 .

 6 Figure 6. Chemical contents for SE treated samples including (a) beech, (b) poplar and (c) spruce under varied SE conditions. The numbers represented the chemical contents for different species including lignin, cellulose and hemicellulose, respectively.

Figure 7 .

 7 Figure 7. FTIR spectra for SE treated samples including (a) beech, (b) poplar and (c) spruce under varied SE conditions.

Figure 8 .

 8 Figure 8. The correlations of (a) lignin, (b) hemicellulose and (c) cellulose contents for the control and SE-treated specimens, respectively with ∆E, sphericity and mass loss.

Figure 9 .

 9 Figure 9. The correlations of the contents of lignin main linkages including β-O-4, β-5 and β-β, respectively with (a) ∆E, (b) sphericity and (c) mass loss for the control and SE-treated beech specimens.

Figure 10 .

 10 Figure 10. Compressive MOE // and MOR // for SE treated samples including (a) beech, (b) poplar and (c) spruce under varied SE conditions.

Figure 11 .

 11 Figure 11. Impregnation ratio of SE treated samples depending on (a) SE conditions and (b) sphericity of cellular structures.

Table 1 .

 1 Conditions for SE treatment.

	Temperature (°C) Pressure (bar) Treatment duration (min) Severity factor Immersion agent
	180	10	5	3.05	distilled water
	180	10	5	3.05	1% H 2 SO 4
	180	10	10	3.36	distilled water
	180	10	15	3.53	distilled water
	200	16	5	3.64	distilled water

Table 2 .

 2 FTIR spectra assignments for SE-treated samples.

	Band (cm -1 )	Vibration and assignment

Acknowledgement

The authors are appreciated for the funding from the Jiangsu Province Postdoctoral Science Foundation [grant number: 2021K474C]. LERMAB is supported by the French National Research Agency through the Laboratory of Excellence ARBRE (ANR-12-LABXARBRE-01) as well. The first author also appreciated for the grand from the China Scholarship Council (CSC).