Maria Caron
email: mechicaron@gmail.com

Mercedes

Florian Zellweger

Kris Verheyen

Baeten

Lander

Guillaume Decocq

Sandra Díaz

Bogdan Jaroszewicz

Martin Kopecký

Jonathan Lenoir

Thomas A Nagel

Perring Michael P 21

Kamila Reczyńska

Wolfgang Schmidt

Monika Wulf

De Frenne

Maria Mercedes

Thermal differences between juveniles and adults increased over time in European forest trees

Keywords: climate change, forestREplot, microclimate, plant functional traits, resurvey, temperate tree species, ontogenetic shift

Abstract

1. Woody species' requirements and environmental sensitivity change from seedlings to adults, a process referred to as ontogenetic shift. Such shifts can be increased by climate change. To assess the changes in the difference of temperature experienced by seedlings and adults in the context of climate change, it is essential to have reliable climatic data over long periods that capture the thermal conditions experienced by the individuals throughout their life cycle.

2. Here we used a unique cross-European database of 2195 pairs of resurveyed forest plots with a mean intercensus time interval of 37 years. We inferred macroclimatic temperature (free-air conditions above tree canopiesrepresentative of the conditions experienced by adult trees) and microclimatic temperature (representative of the juvenile stage at the forest floor, inferred from the relationship between canopy cover, distance to the coast, and belowcanopy temperature) at both surveys. We then address the long-term, large-scale, and multitaxa dynamics of the difference between the temperatures experienced by adults and juveniles of 25 temperate tree species.

3. We found significant, but species-specific, variations in the perceived temperature (calculated from presence/absence data) between life stages during both surveys. Additionally, the difference of the temperature experienced by the adult versus juveniles significantly increased between surveys for eight of 25 species. We found evidence of a relationship between the difference of temperature experienced by juveniles and adults over time and one key functional trait (i.e. leaf area). Together, these results suggest that the temperatures experienced by adults vs juveniles became more decoupled over time for a subset of species, probably due to the combination of climate change and a recorded increase of canopy cover between the surveys resulting in higher rates of macroclimate than microclimate warming. 4. Synthesis. We document warming and canopy-cover induced changes in the difference of the temperature experienced by juveniles and adults. These findings have implications for forest management adaptation to climate change such as the promotion of tree regeneration by creating suitable species-specific microclimatic conditions. Such adaptive management will help to mitigate the macroclimate change in the understory layer.

Introduction

Accelerated climate change [START_REF] Smith | Near-term acceleration in the rate of temperature change[END_REF] is impacting global biodiversity [START_REF] Díaz | Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services[END_REF][START_REF] Petr | A spatial and temporal drought risk assessment of three major tree species in Britain using probabilistic climate change projections[END_REF][START_REF] Segan | A global assessment of current and future biodiversity vulnerability to habitat lossclimate change interactions[END_REF][START_REF] Shepherd | Status and Trends in Global Ecosystem Services and Natural Capital : Assessing Progress Toward Aichi Biodiversity Target 14[END_REF][START_REF] Urban | Accelerating extinction risk from climate change[END_REF]. Documented impacts of climate change on plants include changes in community composition, species richness, population dynamics, physiology, phenology, and species distribution (e.g. [START_REF] Lenoir | A Significant Upward Shift in Plant Species Optimum Elevation During the 20th Century[END_REF][START_REF] Steinbauer | Accelerated increase in plant species richness on mountain summits is linked to warming[END_REF][START_REF] Dusenge | Tansley review Plant carbon metabolism and climate change : elevated CO 2 and temperature impacts on photosynthesis , photorespiration and respiration[END_REF][START_REF] Kuhn | Highlighting declines of cold-demanding plant species in lowlands under climate warming[END_REF][START_REF] Piao | Plant phenology and global climate change : Current progresses and challenges[END_REF]. Macro-scale redistributions of organisms, including trees, in response to climate change depend on dispersal and establishment in previously uncolonized areas [START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF]. However, the species' environmental requirements and tolerances (in terms of e.g. temperature, humidity and light requirements) can change from seedlings to adult life stages [START_REF] Grubb | The maintenance of species-richness in plant communities: the importance of the regeneration niche[END_REF]Parrish & Bazzaz, 1985a), a process referred to as ontogenetic shift [START_REF] Bertrand | Niches of temperate tree species converge towards nutrient-richer conditions over ontogeny[END_REF][START_REF] Eriksson | Ontogenetic niche shifts and their implications for recruitment in three clonal Vaccinium shrubs : Vaccinium myrtillus , Vaccinium vitis-idaea , and Vaccinium oxycoccos[END_REF][START_REF] Miriti | Ontogenetic shift from facilitation to competition in a desert shrub[END_REF][START_REF] Parrish | Ontogenetic niche shifts in old-field annuals[END_REF][START_REF] Werner | The ontogenetic niche and species interactions in sizestructured populations[END_REF]. Therefore, sites with environmental conditions suitable for adults might be less suitable for their offspring, and vice versa.

In general, early stages of plant's life cycle (i.e. seedlings and juveniles) are considered more sensitive than adults of the same species to environmental factors such as heat, frost and drought [START_REF] Bennett | Larger trees suffer most during drought in forests worldwide[END_REF][START_REF] Lloret | Plant community changes induced by experimental climate change : Seedling and adult species composition[END_REF][START_REF] Mérian | Size-mediated climategrowth relationships in temperate forests : A multi-species analysis[END_REF]. Hence, it is likely that climate change will differently impact adults and juveniles of the same species. Therefore, it is essential to further our understanding of how environmental change affects plants along their entire life cycle. The capacity to disperse, colonize and successfully persist in new suitable areas and therefore the species' capacity to change their distribution tracking novel climatic conditions is influenced by (i) the speed at which an individual can produce offspring and regenerate, (ii) morphological (e.g. leaf-height-seed) and physiological traits (e.g. maximum photosynthesis capacity, leaf nitrogen content) and (iii) species properties (e.g. shade tolerance, grazing tolerance) [START_REF] Burke | An experimental study of plant community invasibility[END_REF][START_REF] Bussotti | Functional traits and adaptive capacity of European forests to climate change[END_REF][START_REF] Díaz | The global spectrum of plant form and function[END_REF][START_REF] Dobrowski | Forest structure and species traits mediate projected recruitment declines in western US tree species[END_REF][START_REF] Sádlo | Plant dispersal strategies: a new classification based on the multiple dispersal modes of individual species Strategie[END_REF]. It is expected that species resistance and resilience to climatic variability is affected by the presence of certain functional traits (e.g. leaf mass per area is linked to the responses of plants to drought, high light and scarcity of nutrients; [START_REF] Bussotti | Functional traits and adaptive capacity of European forests to climate change[END_REF][START_REF] Lohbeck | Functional trait strategies of trees in dry and wet tropical forests are similar but differ in their consequences for succession[END_REF]. The environment, including temperature, can strongly affect all the phases of plant species' regeneration from dormancy break until seedling establishment and survival [START_REF] Carón | Latitudinal variation in seeds characteristics of Acer platanoides and A. pseudoplatanus[END_REF][START_REF] Carón | Divergent regeneration responses of two closely related tree species to direct abiotic and indirect biotic effects of climate change[END_REF][START_REF] De Frenne | Temperature effects on forest herbs assessed by warming and transplant experiments along a latitudinal gradient[END_REF][START_REF] Fay | Germination, survival, and growth of grass and forb seedlings: Effects of soil moisture variability[END_REF][START_REF] González-Rodríguez | Maternal influences on seed mass effect and initial seedling growth in four Quercus species[END_REF][START_REF] Shevtosova | Critical periods for impact of climate warming on early seedling establishment in subarctic tundra[END_REF][START_REF] Walck | Climate change and plant regeneration from seed[END_REF]. Therefore, regeneration responses to climate change vary among species with contrasting functional traits.

Differences in the distribution range along elevational and latitudinal gradients between life stages (i.e. adults and juveniles of the same species) are frequently linked to the associated environmental conditions and climate change (e.g. [START_REF] Lenoir | Differences between tree species seedling and adult altitudinal distribution in mountain forests during the recent warm period (1986 -2006)[END_REF][START_REF] Woodall | An indicator of tree migration in forests of the eastern United States[END_REF][START_REF] Rabasa | Disparity in elevational shifts of European trees in response to recent climate warming[END_REF][START_REF] Zhu | Dual impacts of climate change : forest migration and turnover through life history[END_REF][START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF]. However, despite that many studies link these differences to climate change there is a disparity in the direction of the reported shifts. For example, [START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF] showed that, across 46 temperate forest tree species in the United States of America, the mean annual temperature of the range of seedlings was 0.120°C colder than that of the range of adults. This difference was attributed to climate change because most species' seedlings' distributional ranges showed a consistent shift towards colder environments than mature trees.

Conversely, [START_REF] Zhu | Dual impacts of climate change : forest migration and turnover through life history[END_REF] showed that most (77%) of the juveniles of 65 tree species in the eastern United States have higher optimal temperature (in relation to the species abundance), than the adults. Across species, they detected relatively more abundant juveniles than adults of the same species in warmer climates, again relating this pattern to climate change. However, other studies attributed the differences between seedling and adult distributions to ontogenetic shifts. For instance, seedlings were growing in warmer and drier conditions than adults of the same species, in 12 tree species in Slovakia (Central Europe) [START_REF] Máliš | Life stage, not climate change, explains observed tree range shifts[END_REF]. Hence, there is evidence suggesting that the differences in the environmental conditions experienced by seedlings vs adults from a given species can be due to ontogenetic shifts, climate change or both acting together (ontogenetic shifts enhanced by climate change).

To accurately study thermal ontogenetic shifts in the context of climate change, and to better understand the relative importance of ontogenetic shifts and climate change on the contrasting thermal conditions experienced by adults and juveniles, it is essential to have precise and accurate data on the actual temperatures experienced by the individuals throughout their different life stages: from tree seedlings to adult trees and over long time periods. Temperature conditions in forest systems can vary substantially near the ground surface (understory conditions where juveniles grow) compared to the conditions at the canopy to which the leaves of adult trees are exposed (De Frenne, Zellweger, Rodríguez-Sánchez, Scheffers, Hylander, Luoto, Vellend, Verheyen, & Lenoir, 2019;[START_REF] Zellweger | Forest microclimate dynamics drive plant responses to warming[END_REF].

Forest canopy cover, structure and composition strongly influence the microclimatic conditions at the forest floor including light, humidity and temperature, thereby impacting seedling regeneration, early survival and growth [START_REF] George | The Fern Understory as an Ecological Filter : Emergence and Establishment of Canopy-Tree Seedlings[END_REF] with long-term effects in forest composition, structure and functioning [START_REF] Royo | On the formation of dense understory layers in forests worldwide : consequences and implications for forest dynamics , biodiversity , and succession[END_REF]. Across biomes, the temperature difference between free-air conditions (macroclimate) and the understory (microclimate) can vary between 1 -4 °C resulting in less extreme and less variable conditions below the canopy (De Frenne, Zellweger, Rodríguez-Sánchez, Scheffers, Hylander, Luoto, Vellend, Verheyen, & Lenoir, 2019). Therefore, the combined influence of climate change and forest management on forest canopy cover can strongly alter the microclimatic temperature as perceived by seedlings and juveniles on the forest floor. In some temperate European forests, an increase in tree growth and forest densities has been reported as a consequence of decreasing sulphur pollution at the end of the 1980s, an increase in soil nitrogen availability since the 1950s and changes in forest management practices over the past decades including a decrease in management intensity. As a matter of fact, many forest sites in Europe have become either unmanaged or experienced lower management intensities [START_REF] Baeten | A model-based approach to studying changes in compositional heterogeneity[END_REF][START_REF] Depauw | Light availability and land-use history drive biodiversity and functional changes in forest herb layer communities[END_REF][START_REF] Gold | The development of European forest resources, 1950 to 2000[END_REF][START_REF] Luyssaert | The European carbon balance . Part 3 : forests[END_REF][START_REF] Mcgrath | Reconstructing European forest management from 1600 to 2010[END_REF][START_REF] Norby | Forest response to elevated CO2 is conserved across a broad range of productivity[END_REF][START_REF] Pretzsch | Forest stand growth dynamics in Central Europe have accelerated since 1870[END_REF][START_REF] Rautiainen | A National and International Analysis of Changing Forest Density[END_REF]. In many parts of Europe, logging and natural losses of tree biomass have been significantly lower than annual increments, resulting in approximately doubled standing stocks of trees per hectare in 2000 compared to the stocks recorded in 1950 [START_REF] Gold | The development of European forest resources, 1950 to 2000[END_REF]. This increase in canopy density produced cooler and darker conditions in the understory. These changes have the potential to mitigate or even reverse the effects of recent warming in the understory (De Frenne et al. 2013;[START_REF] De Frenne | Global buffering of temperatures under forest canopies[END_REF][START_REF] Zellweger | Forest microclimate dynamics drive plant responses to warming[END_REF]. Therefore, it is likely that adults and juveniles of tree species have experienced different levels of climate warming: macroclimate warming vs. microclimate warming (sensu [START_REF] Zellweger | Forest microclimate dynamics drive plant responses to warming[END_REF].

Despite the importance of considering the differences between overstory and understory temperatures, many ecological studies focusing on forest systems still rely on gridded macroclimate data (Worldclim: Fick & Hijmans 2017; CHELSA; [START_REF] Karger | Climatologies at high resolution for the earth's land surface areas[END_REF]and TerraClimate;[START_REF] Abatzoglou | Terraclimate, a highresolution global dataset of monthly climate and climatic water balance from 1958-2015[END_REF] based on weather stations located outside forests above short grass. Such weather stations only reflect macroclimatic conditions misrepresenting the sub-canopy climatic conditions (i.e. microclimatic conditions). However, a correct representation of the temperature at the understory is key, especially for forest regeneration studies. Indeed, the mismatch between the environmental requirements of tall adults vs. juveniles on the forest floor is extremely important in that respect [START_REF] Geiger | The climate near the ground[END_REF][START_REF] Lenoir | Climatic microrefugia under anthropogenic climate change: implications for species redistribution[END_REF][START_REF] Uvarov | Insects and climate[END_REF][START_REF] Zellweger | Forest microclimate dynamics drive plant responses to warming[END_REF]. Fortunately, recent advances have made it possible to use local forest microclimatic data obtained from a network of microclimate sensors located in forest understories across Europe. Based on that information, a relationship between macroclimate, forest cover and microclimate was established (see [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF]. To correctly evaluate the impacts of climate change on the adult and juvenile life stages (i.e. ontogenetic shifts in the context of climate change), it is necessary to have repeated records (resurveys) of both layers (canopy and understory) in undisturbed forest and with sufficient time between records (several decades) in order to capture the effects of climate warming on species occurrences. Moreover, if resurveys with long intervals between surveys are combined, with accurate records of temperature over multiple regions, it is possible to increase the representativeness, and thus generality, of the results [START_REF] Verheyen | Combining Biodiversity Resurveys across Regions to Advance Global Change Research[END_REF].

Here we specifically address the long-term, large-scale, multitaxa dynamics of the difference between the temperatures perceived by adults and juveniles, for 25 of the most common European temperate forest tree species. To this end, we took advantage of a unique database containing 2195 pairs of resurveyed plots in 48 regions (12 countries) across Europe. Our database contains species presence and cover data (visual estimates of percentage ground cover by each species) of adults and juveniles <1.3 m) with a mean time interval between the baseline survey and the resurvey of 37 years.

For both surveys, we extracted macroclimatic temperatures from global climate grids and calculated microclimate temperatures in the forest understory (representative of the juvenile layer) across the continent using, for the first time at such scale, the established relationship between macroclimatic temperature, tree canopy cover and the temperature offset inside the forest (see [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF]. This relationship was fitted by calculating the difference of temperature outside and inside the forest by combining microclimate data obtained from a sensor network with weather station records across Europe. We determined: (i) the degree of warming as perceived by the canopy of the adult (macroclimate temperature) and juvenile (microclimate temperature) layers between the baseline and resurvey period (thermal shift over time for each life stage); (ii) the difference in the perceived temperature between the adult and juvenile layers during each survey (ontogenetic shift); (iii) whether the difference in temperature as experienced by adults and juveniles changed over time (ontogenetic shift over time) and (iv) whether any difference in ontogenetic shift over time was correlated with species properties and key morphological and physiological traits important for dispersal and establishment and for coping with environmental conditions (i.e. LHS -leaf-height-seed traits and species' shade tolerance).

Our overarching hypothesis is that both life stages (adults and juveniles) experienced warming between surveys due to climate change. However, we expect lower sub-canopy than above-canopy warming, caused by a canopy-induced offset of maximum daytime temperatures. Therefore, we expect that a climate change-induce increase in canopy cover increased the thermal decoupling between both layers. Additionally, we expect that if there are changes over time in the differences between the perceived temperature of the adults and juveniles such changes will be species-specific and linked to key functional traits and to species' shade tolerance. Traits are known to influence species' migration rates and therefore the species' capacity to track suitable environmental conditions but also the species' capacity to successfully establish and develop under changing environmental conditions such as warming, drought and shading [START_REF] Burke | An experimental study of plant community invasibility[END_REF][START_REF] Bussotti | Functional traits and adaptive capacity of European forests to climate change[END_REF][START_REF] Dobrowski | Forest structure and species traits mediate projected recruitment declines in western US tree species[END_REF]. Hence, traits affect the range of environmental conditions that both phases (adults and juveniles) are able to tolerate. We expect that species with small seeds, large leaves and high shade tolerances will exhibit higher thermal differences between adults and juveniles. We expect this to be linked to (i) changes in distribution of the juveniles due to the higher dispersal capacity and (ii) to higher tolerances to shadier and cooler environments at the forest floor caused by denser canopies.

Materials and methods

Database characterization and plots selection

We used data from the forestREplot database [START_REF] Verheyen | Combining Biodiversity Resurveys across Regions to Advance Global Change Research[END_REF]. This database contains species presence and cover data (percentage of ground cover by the canopy of each species estimated consistently, in both surveys, in the same plots) from forest resurveys in permanent or quasi-permanent plots (no pseudoreplicates) with variable plot sizes (between 1 m 2 and 1000 m 2 but in most cases the plots were either a 10×10 m or a 9m radius plot) located in natural or semi-natural forests in temperate deciduous forests across Europe (see details of the database at www.forestreplot.ugent.be). The vast majority of the plots in this database are in ancient and mainly undisturbed or very low-managed forests (between surveys).

We selected 2195 pairs of non-overlapping (in space) plots contained in 48 resurveyed datasets (hereafter regions). These plots have a broad spatial distribution across Europe (Fig. 1a) and were selected because they have accurate records of the adult layer (>7 m height) and the juvenile layer (seedlings and saplings < 1m or <1.3 m height depending on the region considered) during either the baseline survey or resurvey (see [START_REF] Perring | Global environmental change effects on plant community composition trajectories depend upon management legacies[END_REF]) (Fig. 1b, Fig. 1c and Table S1).

The first surveys (hereafter referred to as "baseline survey") were carried out between 1933 and 1994 while the resurveys of the same plots (hereafter referred to as "resurvey") were carried out between 1987 and 2017. The time intervals between the two surveys ranged between 12 and 66 years (with a mean of 37 years; Fig. 1b and Table S1).

For this study, we selected the 25 most common forest tree species spread across this plot network.

All the selected species were present in at least 2.5 % of the plots available in the forestREplot database.

Temperature data

Recorded and estimated macroclimate and microclimate temperatures, respectively, during both surveys (baseline and resurvey) were used for the analysis. The macroclimate above-canopy temperature used was the mean daily maximum summer temperature (June, July and August) extracted for each plot mainly from TERRACLIMATE (http://www.climatologylab.org/terraclimate.html) while the Climate Research Unit -CRU (https://crudata.uea.ac.uk/cru/data/hrg/) was used for 224 plots of the baseline survey plots for which TERRACLIMATE information was not available. The TERRACLIMATE database was complemented when needed with the CRU database because they correlated strongly (in the baseline survey R=0.69, p<0.001 and in the resurvey R=0.81, p=<0.001 for overlapping data points). The extracted maximum summer temperatures were averaged per plot for the five years preceding each survey (baseline surveys and resurveys) (Fig. 1c).

The microclimate temperature within the understory layer (where juveniles grow) at the baseline survey and resurvey were calculated at the plot level for plots where each species was present in either the baseline or the resurvey. To compute microclimate temperatures near the forest floor at both time periods, we used the information of canopy cover at each plot (visual estimates of percentage ground cover by each species) recorded in situ when each survey (baseline and resurvey) took place (reflecting all the conditions that influenced the canopy cover e.g. management, soil nutrient, rainfall variability, CO2 and Nitrogen deposition) and the empirical relationship established by [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF] between macroclimate temperature, canopy cover, distance to the cost and sub-canopy temperature. The microclimatic information used by [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF] was obtained from a network of sensors installed in ten plots representing a regional gradient of canopy cover distributed in ten regions across Europe (all included in this study). The air temperature at 1m above the ground was recorded hourly from February 2017 to February 2018, then, aggregated to minimum (Tmin), mean (Tmean) and maximum (Tmax) daily temperature. Next, the temperature offset values were calculated as the difference between the daily temperature statistics (Tmin, Tmean, Tmax) recorded inside the forest and the respective temperature statistic recorded by the closest weather station (macroclimate above-canopy temperature). Finally, the daily temperature offsets were aggregated to calculate monthly means [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF].

The data obtained was used to build a set of models that analysed the temperature offset as function of two groups of explanatory variables i) local canopy structure and composition and ii) landscape structure and topography. Next, the best performing model (R 2 =0.33, RMSE gamm 0.92) with local canopy cover and distance to the coast as predictors was selected after evaluation using the crossvalidation approach such that a model was calibrated based on data from nine out of 10 regions and validated based on the remaining one ('leave one out' approach). This model developed by [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF] was used to calculate the below-canopy (juvenile layer) maximum temperature during summer of the five years precedent to the year of each survey (to iron out any extremes that happen during the year of the survey) as it was proven to correctly predict the temperature offset in summer.

Additionally, this model reflects principal physical mechanisms for driving the radiation regime below the canopy, which is a key determinant of the below canopy temperature offsets. During warm and clear days, a large part of the incoming short-wave radiation is absorbed and reflected by the canopy, while increasing evapotranspirative cooling, resulting in a cooling of the understory maximum temperature [START_REF] De Frenne | Forest microclimates and climate change : Importance , drivers and future research agenda[END_REF]De Frenne, Zellweger, Rodríguez-Sánchez, Scheffers, Hylander, Luoto, Vellend, Verheyen, Lenoir, et al., 2019). Moreover, as the variables used to fit the model are the plot-specific distance to the coast (invariable), the canopy cover (in situ recorded at the moment of each survey, in 100 plots included in this study) and the macro maximum summer temperatures extracted from TERRACLIMATE or CRU (extracted for each survey), and the model relies on the physics of radiative transfers through vegetation canopies, the model despite its limitations, can be used to estimate the temperature at the juvenile layer during both surveys.

These analyses resulted in a database that contained mean daily maximum above-canopy temperatures during the summer extracted from weather stations close to the forests and mean daily maximum sub-canopy temperatures during the summer for each plot and averaged for the five years preceding each survey (baseline surveys and resurveys) (Fig. 1c).

The maximum summer macroclimate and microclimate temperatures were selected for the analysis because (i) canopy structure and composition play a key role in regulating the offset of maximum summer temperatures [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF] and (ii) local maximum temperatures are of paramount importance for the response of organisms to climate warming due to its relationship with speciesspecific heat tolerances and fitness [START_REF] Macek | Maximum air temperature controlled by landscape topography affects plant species composition in temperate forests[END_REF]. We do not interpret our results in terms of optimal niche locations since the distribution of our plots is not indicative of the species full distribution range or species performance.

Data analyses

Plots where juveniles and adults of the selected species were recorded (presence/absence data) in either the baseline survey or the resurvey were used to extract the estimated maximum temperature data for juveniles (maximum microclimate temperature) and maximum temperature data for adults (maximum macroclimate temperature). These data were used to calculate: (i) temperature changes between surveys (thermal shifts over time for each life stage); (ii) temperature variations between life stages (thermal ontogenetic shifts during both the baseline survey and the resurvey); and (iii) the change between surveys of the difference in the temperature as perceived by adults and juveniles (temperature at the adult layer minus the temperature at the juvenile layer; thermal ontogenetic shift over time) (Fig 1d).

We analysed: i) changes in temperature between surveys for the adult and juvenile layers separately using the temperature at each layer (adult temperature and juvenile temperature) as a response variable and the survey (baseline vs. resurvey) as explanatory fixed variable.

ii) variations of temperature between layers for each survey separately (baseline and resurvey) using the temperature at both layers (adult and juvenile temperatures) as a response variable and the layer as explanatory fixed variable (adult vs. juveniles).

iii) changes between surveys of the difference between the temperature experienced by the adult layer and the juvenile layer using the difference between the temperature experienced by the adults minus the temperature experienced by the juveniles as response variable while the survey was used as explanatory variable.

Generalized mixed-effect models for all the species together included species nested in region as random intercept, and models for each species separately (species-specific models) included only the region as random intercept to account for the nested nature and spread of the data within regions (Table 1). Additionally, to test that there was not pseudo-replication linked to the plot where the species were recorded i.e. more than one species could be recorded in the same plot, the same analysis was done with species nested in region and plot (see results in Table S6). Finally, to test that the results were not biased due to the presence of an adult individual adjoining but not inside the plot and therefore that plot was recorded as only containing juveniles, the same analyses were repeated assuming that all the plots where seedlings were present also had an adult individual (see results in Table S7). All the models were fitted using the lme4 package in R version 3.5.2 (R Core [START_REF] Core | R: A language and environment for statistical computing[END_REF] and in all cases the significance of the explanatory variable was assessed based on likelihood ratio tests [START_REF] Zuur | Mixed effects models and extensions in ecology with R[END_REF].

Next, to be able to understand and link the temperature responses to changes in forest canopy, changes in cover and frequency (number of times a plant species occurs) over time were analysed for all the species together and for each species separately using cover and frequency as a response variable, respectively, and survey as explanatory variable (see results in Tables S3 andS4). The models for all the species together included species nested in region as random intercept and the species-specific models included only the region as random intercept. The contribution of the explanatory variable was assessed based on the likelihood ratio tests [START_REF] Zuur | Mixed effects models and extensions in ecology with R[END_REF].

Finally, for all 25 species and then also for the 8 species that showed significant changes in thermal ontogenetic shifts between surveys (i.e. analysis iii), we correlated this difference (one value per species) with a shade tolerance index, and the mean and the standard deviation of key functional traits (leaf mass area, leaf area, plant height and seed mass, Table S2) [START_REF] Westoby | A leaf-height-seed ( LHS ) plant ecology strategy scheme[END_REF][START_REF] Díaz | The global spectrum of plant form and function[END_REF]. Pearson correlation was used for height while Spearman correlations were used for leaf mass area, leaf area and seed mass due to the non-normality of those data. The values of the key functional traits were extracted from [START_REF] Díaz | The global spectrum of plant form and function[END_REF]. The functional trait values provided by [START_REF] Díaz | The global spectrum of plant form and function[END_REF] are the geometric mean extracted from the Plant Trait Database TRY (https:// www.trydb.org) supplemented by published data not included in TRY and a small number of original unpublished data [START_REF] Díaz | The global spectrum of plant form and function[END_REF]. All data were standardized and subjected to error detection and quality control (see details in [START_REF] Díaz | The global spectrum of plant form and function[END_REF]. The standard deviation values were calculated from the individual records of traits values available in the TRY database. The number of observations per trait and species range from a single one (in the case of rare, geographically restricted species) to hundreds (in the case of common species with broad ranges; [START_REF] Díaz | The global spectrum of plant form and function[END_REF]. The shade tolerance index for each species was extracted from [START_REF] Niinemets | Tolerance to shade, drought, and waterlogging of temperate Northern Hemisphere trees and shrubs[END_REF].

Results

Across all species, the adult layer temperature increased by 1.56 °C ± SD 0.53 (0.38 °C/decade) between the baseline and the resurvey while the juvenile layer temperature increased by 1.34°C ± SD 0.42 (0.35 °C/decade) between surveys (Table S3 and Table S12). However, the rate of temperature change in both layers was species-specific (Table S3, Fig. 2 and Table S12). In the adult layer, Quercus rubra experienced the highest degree of warming (3.59 °C, i.e. 0.78 °C/decade) while Tilia cordata exhibited the strongest warming in the juvenile layer (2.19 °C, i.e. 0.67°C/decade) (Table S3, Fig. 2 and Table S12).

The adult layer experienced significantly higher temperatures than the juvenile layer in both the baseline survey (+2.19 °C ± SD 0.74) and the resurvey (+2.41 °C ± SD 0.73) across species (Table S3). However, the difference between the temperature experienced by the adults and juveniles was again species-specific (Table S3, Fig. 2 and Table S12). In the baseline survey, the highest difference between the temperature experienced by the adults and the juveniles was recorded in Populus tremula (+3.84 °C) and in the resurvey in Tilia platyphyllos (+3.92 °C) (Table S3, Fig. 2 and Table S12).

Temperature differences between adults and juveniles changed significantly between surveys when all the species are considered together (Table S3). We found that the temperature difference experienced by adults vs juveniles increased over time for 17 (68%) of the 25 analysed European tree species. However, this difference was significant for eight out of 25 species only (Table S3 and Fig. 3). These eight species exhibited an average increase of 0.18°C in the temperature difference between adult and juvenile layers when comparing the baseline survey to the resurvey (Fig. 3). In other words, the thermal ontogenetic shift between putative "mothers" and "daughters" significantly increased over time for eight tree species. The only species in which this temperature difference significantly decreased, by 0.14 °C, was Acer campestre (Fig. 3).

Finally, we tested for relationships between thermal ontogenetic shifts and tree species traits. The evidence for the relationship between thermal ontogenetic shifts over time and traits was weak; when all 25 species were analysed together, there were no significant correlations between any analysed trait or their standard deviation and temporal temperature differences between adult and juvenile layers (correlation ranged from -0.38 to 0.36; Table S11). The difference between the temperature experienced by adult and juvenile layers over time slightly increased (non-significantly) with the shade tolerance index (correlation= 0.24, p-value= 0.239; Table S11). A significant positive correlation (correlation= 0.83, p-value=0.015) was detected between the leaf area, and the difference between surveys of the variation in the temperature experienced by adults and juveniles, but only for those eight species exhibiting a significant positive thermal ontogenetic shift over time (Fig. 4 and Table S10). However, significant positive thermal ontogenetic shifts were not related to leaf mass area, seed mass, shade tolerance, nor height or their standard deviation (correlations ranged from -0.64 to 0.41; Table S10).

Discussion

The temperature experienced by the studied tree species of temperate European forests, in both the adult and juvenile layers, changed significantly between surveys. In other words, we detect a shift in the thermal conditions experienced by both life stages over time. The observed unequal warming of both layers over time is in line with our expectations of lower sub-canopy than above-canopy warming, due to a canopy-induced offset of maximum daytime temperatures [START_REF] Davis | Microclimatic buffering in forests of the future: the role of local water balance[END_REF]De Frenne, Zellweger, Rodríguez-Sánchez, Scheffers, Hylander, Luoto, Vellend, Verheyen, & Lenoir, 2019;[START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF]. Considering that the juvenile layer might express current conditions while the distribution of adults rather expresses past conditions [START_REF] Lenoir | Differences between tree species seedling and adult altitudinal distribution in mountain forests during the recent warm period (1986 -2006)[END_REF][START_REF] Urbieta | Mediterranean pine and oak distribution in southern Spain : Is there a mismatch between regeneration and adult distribution[END_REF][START_REF] Woodall | An indicator of tree migration in forests of the eastern United States[END_REF], the divergence in temperatures might also be influenced by the colonization of new areas (this in turn, is affected by species' dispersal capacity). However, due to the warming recorded in the juvenile layer, our results suggest that species did not manage to shift their distributions to maintain the same thermal conditions in the resurvey as recorded in the baseline, and likely adapted to the new warmer conditions. The higher difference in thermal conditions between surveys in adults than juveniles suggest that adult trees are lagging more behind macroclimate change than their conspecific juveniles.

We trust that our estimates of the juvenile layer temperatures are reliable because the model incorporates canopy cover (in situ recorded by experienced forest ecologists at the moment of each survey) and macroclimate which are the major drivers of below-canopy temperature offsets [START_REF] De Frenne | Forest microclimates and climate change : Importance , drivers and future research agenda[END_REF]De Frenne, Zellweger, Rodríguez-Sánchez, Scheffers, Hylander, Luoto, Vellend, Verheyen, Lenoir, et al., 2019) and relies on the physics of radiative transfers through vegetation canopies. Nonetheless, there are no old forest microclimate measurements in our plots so our estimates of the baseline temperature at the juvenile layer remain uncertain but are, to the best of or knowledge, the only ones available. Additionally, although this is carefully avoided in resurvey studies [START_REF] Verheyen | Journal of Vegetation Science Observer and relocation errors matter in resurveys of historical vegetation plots[END_REF], possible differences in the way canopy cover was recorded in the baseline and the resurvey and the methods used by [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF] could affect the estimated temperatures at the juvenile layer. Moreover, there is a part of variability that remains unexplained by the model used here and it is possible that the variability of the estimated below canopy temperatures might be lower than the variation of the real observed data.

The warming recorded here in both layers is in line, but slightly higher than, the global mean land surface air temperature increase of 1.29 °C measured between 1940 and 2016 (the time period considered in this study) (IPCC, 2019). The higher degree of warming recorded in this work is likely due to the fact that we analysed maximum summer temperatures. The detected temperature increase was species-specific and, considering the close relationship between latitude and observed and projected temperatures [START_REF] De Frenne | Latitudinal gradients as natural laboratories to infer species' responses to temperature[END_REF][START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF], it is likely that recorded species-specific warming is also linked to the spatial distribution of a species and its dispersal and establishment capacity (Table S8) despite the fact that our database did not cover the complete distribution of the species. This species-specific response, might also be linked to the species-specific crown architecture (e.g. Betula species transmit more light to the forest floor than for example Abies alba). However, the influence of crown architecture on the change in the temperature over time is beyond the scope of this work but should be considered in future studies. The observed species-specific pattern of temperature increase between surveys should be considered with caution because the estimates are based on temperature datasets that have a relatively coarse resolution (~4x4 km for TERRACLIMATE). In our study focused on thermal shifts, we only consider one of the multiple factors that influence the presence of an individual, i.e. temperature, while other factors and processes could also influence the establishment of new individuals including masting, herbivory, the past legacy of human interventions and forest management (Lombaerde et al., 2020).

Among both surveys, thermal ontogenetic shifts were detected: in the baseline survey the adult layer experienced 2.19 °C warmer temperatures than the juveniles and in the resurvey this difference increased by 0.22 °C, reaching 2.41 °C. Differences in the temperatures experienced by adults and the juveniles were recorded in other forest types and regions including in the USA [START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF][START_REF] Zhu | Dual impacts of climate change : forest migration and turnover through life history[END_REF] and the Mediterranean [START_REF] Urbieta | Mediterranean pine and oak distribution in southern Spain : Is there a mismatch between regeneration and adult distribution[END_REF]. In some cases, these thermal differences between life stages have been linked to shifts in distribution as a response to climate change, namely younger life stages shifting towards currently cooler conditions compared to adults' distribution mirroring past climatic conditions (e.g. [START_REF] Lenoir | Differences between tree species seedling and adult altitudinal distribution in mountain forests during the recent warm period (1986 -2006)[END_REF][START_REF] Woodall | An indicator of tree migration in forests of the eastern United States[END_REF][START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF]. Others found that the range shifts among tree life stages were more consistent with ontogenetic differences in environmental requirements than with responses to climate change [START_REF] Máliš | Life stage, not climate change, explains observed tree range shifts[END_REF]. The latter conclusion was supported by the fact that the authors used recent and historical data reflecting conditions before current warmer period and identified similar differences between adults and juveniles in both time periods, driven by warmer growing conditions of seedlings than adults. [START_REF] Máliš | Life stage, not climate change, explains observed tree range shifts[END_REF] analysed changes in distribution and linked these distributional changes with mean macroclimatic conditions calculated for each plot using a network of local meteorological stations while we used maximum summer macro-and microclimatic temperatures estimated for each plot using global databases and the relationship between the canopy cover and the understory temperature. The model used here despite its limitations (see above) correctly predict the temperature offset in summer [START_REF] Zellweger | Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe[END_REF]. Additionally, the use of the average of the five years presiding each survey avoids the bias linked to possible abnormal warm or cold summers.

Other authors (e.g. [START_REF] Lenoir | Differences between tree species seedling and adult altitudinal distribution in mountain forests during the recent warm period (1986 -2006)[END_REF][START_REF] Woodall | An indicator of tree migration in forests of the eastern United States[END_REF][START_REF] Monleon | Evidence of Tree Species' Range Shifts in a Complex Landscape[END_REF] reported results in the same direction as our findings (i.e. seedlings growing in colder conditions than adults) but linked these observations to climate warming-induced distributional shifts with seedlings or juveniles colonizing cooler locations and not to ontogenetic shifts. Using the macroclimatic (adult layer) and microclimatic (juvenile layer) temperatures, we detected thermal ontogenetic shifts in the studied tree species independently of the origin of the species and the time period considered (baseline survey and resurvey). Indeed, non-native species such as Prunus serotina and Quercus rubra (introduced from the North America) had similar thermal ontogenetic shifts as native European species of the same genera.

The thermal difference experienced by the adults and juveniles (i.e. ontogenetic shift) increased over time for 17 (68%) of the 25 analysed European tree species. However, this shift was only significant for eight out of 25 species. Thus, the temperature experienced by the individuals at the two layers became increasingly decoupled over time for a subset of the studied species. This increased decoupling is likely caused by the higher warming rates at the canopy layer compared to the forest floor due to canopy-induced temperature offset. Indeed, the mean canopy cover increased between surveys in six out of the eight species where we observed increased decoupling between the temperature experienced by the adults and the juveniles (Table S4, Table S5 and Table S13). The significant decrease in the difference of the temperature experienced by adults and juveniles over time reported for one species (Acer campestre) might be linked to a decrease in cover in certain plots caused by mortality of adults of this species, potentially due to an exceedance of physiological tolerances due to macroclimate warming. Nevertheless, it is possible that the decoupling might also be linked to species making small local shifts in their ranges and differences in the ability of the juvenile stages to keep up with the velocity of climate change. It is even likely that these mechanisms are occurring simultaneously. The increased difference of temperature between the adult and juvenile layers between surveys partially compensated (0.18°C) macroclimate warming (De Frenne, Zellweger, Rodríguez-Sánchez, Scheffers, Hylander, Luoto, Vellend, Verheyen, & Lenoir, 2019). This means that for species that experienced an increase of the difference of temperature between the adult and juvenile layer between the baseline and recent surveys, the warming was less strong than for the other species.

Our trait-based analyses shed light on the causes of the divergent responses in the difference of the temperature experienced by adults vs. juveniles between surveys. Large-leafed species exhibited an increase of the difference between the temperature experienced by adults vs. juveniles over time, likely because large leaves provide competitive advantages in dealing with the darker conditions of the understory [START_REF] Bequet | Leaf area index development in temperate oak and beech forests is driven by stand characteristics and weather conditions[END_REF][START_REF] Li | Picea seedlings show apparent acclimation to drought with increasing altitude in the eastern Himalaya[END_REF]. Seedlings with larger leaves can overtop neighbouring vegetation and get better access to light at the forest floor [START_REF] Leishman | The Evolutionary Ecology of Seed Size[END_REF][START_REF] Poorter | Light-dependent changes in the relationship between seed mass and seedling traits: A meta-analysis for rain forest tree species[END_REF]. Additionally, larger leaves have usually a thicker boundary layer that slows sensible heat exchange with the surrounding air, developing larger leaf-toair temperature differences than smaller leaves. The wider leaf-to-air temperature differences of larger leaves may allow them to more quickly heat up during cool mornings to favourable temperatures for photosynthesis, what might allow for higher photosynthetic returns [START_REF] Wright | Global climatic drivers of leaf size[END_REF]. The intraspecific variability of leaf area, included in our analysis as the traits' standard deviation, apparently, does not affect the difference between the temperature experienced by adults vs.

juveniles over time (no significant correlation). Leaf traits as well as other species traits and properties (e.g., shade tolerance) can vary not only intraspecifically but also along the species life cycle (i.e., ontogenetic shift in traits values). This variation of traits along the species life cycle is somehow present in our standard deviation analysis as the traits' database used here combines adult and juveniles' traits values as well as data collected in controlled experiments and in nature. However, a detail analysis of how ontogenetic changes in functional traits affect the difference between the temperature experienced by juveniles vs. adults is beyond the scope of this work. Finally, we did not find a significant relationship between the shade tolerance of the species and the changes in the adults vs. juveniles thermal differences among surveys. We had, however, a relatively small species sample size (n= 25 or n= 8) [START_REF] Wasserstein | The ASA's Statement on p -Values: Context, Process, and Purpose[END_REF] and further analysis should be done with larger sample size to confirm these results.

Conclusions

In sum, the significant differences between the temperature experienced by adults vs. juveniles indicate that the different phases of the life cycle can differ in their thermal requirements and/or tolerances, in line with the ontogenetic shift theory [START_REF] Bertrand | Niches of temperate tree species converge towards nutrient-richer conditions over ontogeny[END_REF][START_REF] Eriksson | Ontogenetic niche shifts and their implications for recruitment in three clonal Vaccinium shrubs : Vaccinium myrtillus , Vaccinium vitis-idaea , and Vaccinium oxycoccos[END_REF][START_REF] Máliš | Life stage, not climate change, explains observed tree range shifts[END_REF][START_REF] Miriti | Ontogenetic shift from facilitation to competition in a desert shrub[END_REF][START_REF] Parrish | Ontogenetic niche shifts in old-field annuals[END_REF]. These findings highlight the importance of studying the impacts of climate change on different phases of the plant life cycle using reliable climatic information for each phase and layer. Moreover, our findings suggest that the capacity to deal with climate change varies with the trees' life stages and with species identity. Adults are more likely to cope with warming by persisting locally for a long time while juveniles are less likely to do so and thus more likely to track the shifting isotherms thereby increasing the thermal ontogenetic shifts.

By disentangling the impacts of climate change on different phases of plants' life cycle, our work sheds light onto the ontogenetic changes across large geographical and temporal scales in the context of climate change. This information is key to advance our understanding of the ecology and dynamics of temperate forests in the face of climate warming. Our findings could also assist forest managers in predicting future species composition based on climatic projections, and in promoting tree regeneration by creating suitable tree species-specific microclimatic conditions, helping to mitigate, at least partially, the change at the understory level driven by changes in macroclimate.

Fig. 1

 1 Fig. 1: a) Locations of the datasets used for the analysis, b) Histogram of number of plots with years of the baseline survey and resurvey and c) Histogram showing number of plots with given maximum summer temperature in the adult (i.e. macroclimate) and juvenile (i.e. microclimate) layer at the time of the baseline (top) and resurvey (bottom), vertical lines represent the means of each layer d) Scheme of the study design: we first calculate the thermal shift over time for each life stage as the difference in temperatures between resurvey and baseline survey. Second, we calculated ontogenetic thermal shift as the temperature of the canopy (adult layer) vs forest floor (juvenile layer). Finally, we merged both approaches and calculated the ontogenetic thermal shift difference over time integrating the first and second calculation.

Fig. 2 :

 2 Fig. 2: Juvenile layer temperature (subcanopy microclimate temperature) and adult layer temperature (above-canopy macroclimate temperature) for the 25 most common tree species in the baseline survey and resurvey. Vertical lines represent the species means of each layer and survey.

Fig. 3

 3 Fig. 3: a) Difference between the adult layer temperature and the juvenile layer temperature (calculated as adult layer minus juvenile layer such that positive values reflect warmer temperatures for the overstory trees) in the baseline survey (red) and the resurvey (yellow); error bars denote standard errors. b) Model estimates of the difference between the adult and juvenile layers temperatures over time. Full circles indicate significant differences and open circles insignificant differences, error bars denote two standard errors.

Fig. 4 :

 4 Fig. 4: Positive relationship between the temperature difference of adults minus juvenile trees over time (resurvey minus baseline survey) and leaf area (mm²). Shown here only for the eight species with a significant change in the ontogenetic thermal niche over time (n = 8).

Table 1 :

 1 Mixed-effect models used for the analysis of thermal shift between surveys and layers and the change in the difference between the temperature experienced by adults (macroclimate) and juveniles (microclimate) over time across and within species

		Models across species
		Response variable	Fixed effects	Random effects
	For the adult layer	Macroclimate temperature	Survey	Region x sp + sp
	For the juvenile layer	Microclimate temperature	Survey	Region x sp + sp
		Temperature (macroclimate	Layer	Region x sp + sp
	For the baseline survey	temperature & microclimate
		temperature)
		Temperature (macroclimate	Layer	Region x sp + sp
	For the resurvey	temperature & microclimate
		temperature)
	For the complete database	∆ Temperature (macroclimate	Survey	Region x sp + sp
	(baseline and resurvey	temperature -microclimate
	including adults and juveniles)	temperature
		Species-specific models
		Response variable	Fixed effects	Random effects
	For the adult layer	Macroclimate temperature	Survey	Region
	For the juvenile layer	Microclimate temperature	Survey	Region
		Temperature (macroclimate	Layer	Region
	For the baseline survey	temperature & microclimate
		temperature)
		Temperature (macroclimate	Layer	Region
	For the resurvey	temperature & microclimate
		temperature)
	For the complete database	∆ Temperature (macroclimate	Survey	Region
	(baseline and resurvey	temperature -microclimate
	including adults and juveniles)	temperature)

Acknowledgements

Mercedes Caron was supported by FONCyT PICT-2017-2245 and by CESAM Visiting Staff Platform (2019) -Ghent University Florian Zellweger received funding from the Swiss National Science Foundation (project 172198 and 193645) Kris Verheyen and Michael Perring were supported by the European Research Council (ERC) UnderSCORE grant #861957 Sandra Díaz was supported by FONCyT PICT-2017-1084 Radim Hédl, Martin Macek, Petr Petřík, and Martin Kopecký were supported by the long-term research development project No. RVO 67985939 of the Czech Academy of Sciences. František Máliš was funded by Slovak Research and Development Agency grant No. APVV-19-0319. Pieter De Frenne received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC Starting Grant FORMICA 757833).

Data Availability statement: All vegetation data used in this paper is available in the forestREplot database (www.forestreplot.ugent.be). Macro and micro temperature data available from the Dryad Digital Repository https://doi.org/10.5061/dryad.rfj6q57bh [START_REF] Caron | Data From: Thermal differences between juveniles and adults increased over time in European forest trees Dryad Digital Repository[END_REF]. The rest of the data is available in the cited references or presented in the tables or figures.

Conflict of Interest:

The authors declare that they don't have any conflict of interest.

Author Contributions statement: MMC and PDF designed the study. MMC performed the analysis.

FZ provided the climatic database. KV, LB, RH, MB-R, IB, JB, GD, TD, TD, TH, BJ, MK, JL, MM, MM, MF, NTA, PP, KR, RP, WS, KS, BT, MW and PDF collected the vegetation information available in the ForestREplot database. FZ, LB, SD, JL, MPP and PDF contributed to the initial discussion of the paper design. All the authors provided comments.


Adrian Alles

Zhongben Pan

Pavel Loiko

Josep Maria Serres

Sami Slimi

Shawuti Yingming

Kaiyang Tang

Yicheng Wang

Yongguang Zhao

Elena Dunina

Alexey Kornienko

Patrice Camy

Weidong Chen

L I Wang

Uwe Griebner

Valentin Petrov

Rosa Maria Solé

Magdalena Aguiló

Francesc Díaz

Xavier Mateos
email: xavier.mateos@urv.cat

Tm 3+ -doped calcium lithium tantalum gallium garnet (Tm:CLTGG): novel laser crystal

Introduction

An ordered crystal is an ideal solid state material exhibiting lattice periodicity in all directions.

The certain arrangement of atoms in the unit-cell is repeated forming a translationally invariant crystal structure in the long-range. A disorder of the structure denotes some deviation from a perfect crystalline order. Weak disorder can be represented as a perturbation of the crystalline structure, e.g., caused by dopants, defects, vacancies and / or dislocations. Strong disorder is a pronounced departure from the crystalline order. The length scale over which order, or disorder persists is also relevant. The local disorder can be revealed at a length of several unit-cells.

In laser physics, structurally disordered crystals constitute an important class of gain materials [START_REF] Cano-Torres | Comparative study of crystallographic, spectroscopic, and laser properties of Tm 3+ in NaT(WO 4 ) 2 (T = La, Gd, Y, and Lu) disordered single crystals[END_REF]. In such crystals, one or several host-forming cations are randomly distributed over two or more different crystallographic sites. Two situations for the dopant (laser-active) ions can be thus distinguished: (i) the dopant ions are distributed over several lattice sites [START_REF] Cano-Torres | Comparative study of crystallographic, spectroscopic, and laser properties of Tm 3+ in NaT(WO 4 ) 2 (T = La, Gd, Y, and Lu) disordered single crystals[END_REF] or (ii) they are present at one site while other cations experience a random site distribution [START_REF] Lupei | The nature of nonequivalent Nd 3+ centers in CNGG and CLNGG[END_REF].

In both cases, the spectral bands of dopant ions will experience an inhomogeneous broadening either due to the presence of several crystal-fields or due to the different cation multi-ligands around the dopant ions. Such spectral broadening is favorable for broad tuning of the laser wavelength and / or the generation of ultrashort pulses in mode-locked (ML) lasers. Note that there also exists compositional disorder in "mixed" (solid-solution) materials A 1-x B x , even when the parent compounds (A and B) are ordered [START_REF] Jing | Synthesis, spectroscopy, and efficient laser operation of "mixed" sesquioxide Tm:(Lu,Sc) 2 O 3 transparent ceramics[END_REF]. This also results in spectral broadening.

The main drawback of disordered crystals is the deterioration of their thermal properties which justifies the search for such crystals with high thermal conductivity.

Among the host crystals for doping with laser-active rare-earth ions (RE 3+ ), cubic multicomponent garnets with general chemical formula {A} 3 [B] 2 (C) 3 O 12 where A = Y, Gd, Lu or Ca, Mg, Fe, Sr, etc., and B and C = Al, Sc, Ga, Ta, etc., occupy a special position. Note that the ordered garnet Y 3 Al 5 O 12 (YAG) is the most widespread laser host crystal. Crystals belonging to the cubic garnet family combine good thermo-mechanical behavior with attractive spectroscopic properties of the dopant RE 3+ ions. They are optically isotropic. Finally, cubic garnets can be grown by the well-developed Czochralski (Cz) method.

Among the structurally disordered multicomponent garnets, calcium niobium gallium garnet (CNGG) is one of the best known representatives [START_REF] Yu | Calcium niobium gallium and calcium lithium niobium gallium garnets doped with rare earth ionseffective laser media[END_REF][START_REF] Castellano-Hernández | Na modification of lanthanide doped Ca 3 Nb 1.5 Ga 3.5 O 12 -type laser garnets: Czochralski crystal growth and characterization[END_REF]. The structure disorder of CNGG originates from a random distribution of Nb 5+ and Ga 3+ cations over [B] and (C) lattice sites leading to a significant inhomogeneous broadening of the emission bands of the RE 3+ dopant ions. The latter are expected to replace for the divalent Ca 2+ cations; the charge compensation is provided by vacancies [START_REF] Yu | Raman scattering of light in crystals and melt of calcium-niobium gallium garnet[END_REF] or by intentional codoping by univalent alkali ions (Na + , Li + or their combination) [START_REF] Serrano | Design of Yb 3+ optical bandwidths by crystallographic modification of disordered calcium niobium gallium laser garnets[END_REF][START_REF] Pan | Comparative study of the spectroscopic and laser properties of Tm 3+ , Na + (Li + )-codoped Ca 3 Nb 1.5 Ga 3.5 O 12 -type disordered garnet crystals for mode-locked lasers[END_REF] further affecting the spectral broadening [START_REF] Álvarez-Pérez | A roadmap for laser optimization of Yb:Ca 3 (NbGa) 5 O 12 -CNGG-type single crystal garnets[END_REF].

Recently, CNGG-type crystals doped with thulium (Tm 3+ ) [START_REF] Pan | Generation of 84-fs pulses from a mode-locked Tm:CNNGG disordered garnet crystal laser[END_REF] and holmium (Ho 3+ ) [START_REF] Pan | Sub-80 fs mode-locked Tm,Hocodoped disordered garnet crystal oscillator operating at 2081 nm[END_REF] ions have proven to be very suitable for the generation of sub-100 fs pulses at ~2 µm owing to their smooth and very broad gain profiles extending beyond the structured water vapor air absorption [START_REF] Pan | Disordered Tm 3+ , Ho 3+ -codoped CNGG garnet crystal: Towards efficient laser materials for ultrashort pulse generation at ∼2 μm[END_REF] which is essential for the broadband ML laser performance. Pan et al. reported on a Tm,Na:CNGG (Tm:CNNGG) laser mode-locked by a single-walled carbon nanotube saturable absorber (SA) delivering 84-fs pulses at 2018 nm [START_REF] Pan | Generation of 84-fs pulses from a mode-locked Tm:CNNGG disordered garnet crystal laser[END_REF]. In the continuous-wave (CW) regime, a broad tuning range of 1879 -2086 nm was achieved in the same work [START_REF] Pan | Generation of 84-fs pulses from a mode-locked Tm:CNNGG disordered garnet crystal laser[END_REF]. Zhao et al. achieved shorter pulses (67 fs, i.e., 10 optical cycles at 2083 nm) from a Tm,Ho,Li:CNGG (Tm,Ho:CLNGG) laser ML by the same SA utilizing the combined gain bandwidths from both active ions [START_REF] Zhao | 67-fs pulse generation from a mode-locked Tm,Ho:CLNGG laser at 2083 nm[END_REF].

There exists another disordered multicomponent garnet similar to CNGG, namely calcium tantalum gallium garnet (CTGG) [START_REF] Ma | Spectroscopic, thermal, and laser properties of disordered garnet Nd:CLTGG crystal[END_REF]. Ma et al. have shown that CTGG exhibits higher thermal conductivity (κ = 3.76 Wm -1 K -1 ) as compared to its niobium counterpart [START_REF] Ma | Spectroscopic, thermal, and laser properties of disordered garnet Nd:CLTGG crystal[END_REF]. CTGG-type crystals doped with Nd 3+ and Yb 3+ ions have been studied for laser operation at ~1 µm [START_REF] Xie | Diode-pumped passively modelocked Nd:CTGG disordered crystal laser[END_REF][START_REF] Lou | Diode-pumped passively mode-locked femtosecond Yb:CTGG laser[END_REF].

However, no lasing in the ~2 µm spectral range has been reported so far.

In the present work, we reveal the potential of Tm 3+ , Li + -codoped CTGG (abbreviated Tm:CLTGG) as a broadband laser gain material at ~2 µm and beyond.

Crystal growth

A Tm : CLTGG single crystal was grown by the Czochralski (Cz) method in an iridium crucible using argon atmosphere. The starting materials, CaCO 3 (purity: 4N), Ta 2 O 5 , Ga 2 O 3 , Li 2 CO 3 and Tm 2 O 3 (purity: 5N), were weighed according to the following chemical formula: The raw materials were mixed, ground and heated at 900 ℃ for 10 h in a platinum crucible to decompose CaCO 3 . After cooling down the crucible to room temperature (RT, 20 ℃), the mixture was pressed into tablets and reheated at 1200 ℃ for 15 h to form the cubic garnet phase through a solid-state reaction. The synthesized polycrystalline material was placed in an iridium crucible and melted by an intermediate-frequency heater. The first crystal was grown using an

[111] oriented seed from undoped YAG. From this first crystal, another seed with the same orientation was cut and used for the growth of laser-quality crystals. During the crystal growth, the pulling rate varied from 0.5 to 1.0 mm/h and the crystal rotation speed was kept at 8 to 15 revolutions per minute. Once the growth was completed, the crystal was removed from the melt and cooled down to RT at a stepped rate of 15 to 25 ℃/h. The crystal was annealed in air, the maximum temperature was 1200 ℃ and the hold duration was 24 h, the heating and cooling rates were about 50 ℃/h. By using X-ray fluorescence, the actual concentration of Tm 3+ ions was measured to be 3.17 at.% with respect to Ca 2+ ions (N Tm = 5.03×10 20 cm -3 ) leading to a segregation coefficient K Tm of 0.67. The targeted doping concentration of ~3 at.% Tm was selected due to the spectroscopic considerations. It could be further increased by changing the Tm content in the growth batch considering the determined K Tm value.

Crystal structure

X-ray diffraction

The X-ray powder diffraction (XRD) pattern was measured at RT using a Bruker D2 Phaser diffractometer, Cu Kα1 radiation (1.54184 Å) with a step size of 0.02° and a step time of 1.0 s, in the range of 2θ from 10° to 90°. The measured diffraction pattern, Fig. 2 1. The Tm 3+ ions replace for the Ca 2+ ones (the corresponding ionic radii are R Ca = 1.12 Å and R Tm = 0.994 Å for VIII-fold oxygen coordination). In the 5+ and Ga 3+ at 16a sites) and by six tetrahedra (Ga 3+ , Ta 5+ and Li + at 24d sites), two of them sharing edges, and the remaining four being connected by shared corners.

Raman spectroscopy

The Raman spectrum of Tm:CLTGG was measured using a Renishaw inVia confocal Raman microscope with a ×50 Leica objective and an Ar + ion laser (514 nm). It is shown in Fig. 4. In the same figure, for comparison, we also show the Raman spectrum of its niobium isomorph, Tm:CLNGG. A total of 18 bands are resolved in the Raman spectrum of Tm:CLTGG. Among them, the vibrations at high frequencies (700-900 cm -1 ) forming two broad bands are typically analyzed as they are sensitive to the alteration of the structure of multicomponent garnets [START_REF] Yu | Calcium niobium gallium and calcium lithium niobium gallium garnets doped with rare earth ionseffective laser media[END_REF][START_REF] Castellano-Hernández | Na modification of lanthanide doped Ca 3 Nb 1.5 Ga 3.5 O 12 -type laser garnets: Czochralski crystal growth and characterization[END_REF].

They are assigned to internal vibrations (symmetric stretching modes, ν s ) of [M2O 4 ] tetrahedra (M2 = Ga2 and Ta2). In our case, the tetrahedral sites (24d) are occupied by Ta 5+ and Ga 3+ This highlights the positive role of Li + ions in the charge compensation.

Thermal properties

The specific heat C p and the thermal diffusivity λ were measured using a laser flash apparatus (NETZSCH LFA457). For this, a squared wafer with dimensions of 4×4×1 mm 3 was cut from the Tm:CLTGG crystal along the [111] direction and double side coated with graphite.

The dependence of the specific heat (C p ) of Tm:CLTGG on temperature is shown in Fig. 5(a). The C p value increases monotonously with temperature, from 0.57 to 0.66 J g -1 K -1 , when the temperature is increased from 298.2 K to 571.9 K. Figure 5 At room temperature, it amounts to 4.33 Wm -1 K -1 , which is larger than for CNGGtype crystals [START_REF] Yu | Calcium niobium gallium and calcium lithium niobium gallium garnets doped with rare earth ionseffective laser media[END_REF][START_REF] Guo | Growth and characterizations of calcium tantalum gallium garnet single crystal[END_REF]. The value of thermal conductivity for Tm:CLTGG is higher than that for undoped CTGG (3.76 Wm -1 K -1 ) [START_REF] Ma | Spectroscopic, thermal, and laser properties of disordered garnet Nd:CLTGG crystal[END_REF]. We refer this to the effect of Li + codoping on eliminating the cationic vacancies and increasing the thermal conductivity. This effect seems to overcome the negative role of rare-earth doping which typically tends to decrease κ.

Optical spectroscopy

Optical absorption

The absorption spectrum was measured using a Varian CARY 5000 spectrophotometer. The cubic Tm:CLTGG is optically isotropic. The unpolarized RT absorption spectrum of Tm:CLTGG is shown in Fig. 6(a). In the spectrum, the well-resolved absorption bands are related to transitions of Tm 3+ ions from the ground-state ( 3 H 6 ) to excited-states (from 3 F 4 to 1 D 2 , in increasing energy order). This represents the effect of inhomogeneous broadening caused by the structural disorder and, in particular, the different cationic distributions around the Tm 3+ ions, cf. Fig. 3(b).

The absorption spectrum of Tm:CLTGG reveals no significant absorption in the visible from color centers related to cationic vacancies. This indicates charge compensation via Li + doping. Figure 6(c) shows the Tauc plot for the determination of the UV absorption edge (assuming indirect transitions). The optical bandgap energy E g is 4.88 eV (0.254 µm). At the onset of the host absorption, weak absorption bands due to transitions of Tm 3+ ions to higherlying 1 I 6 and 3 P 0-2 states are found.

Judd-Ofelt analysis

The transition intensities for Tm 3+ ions were calculated from the absorption spectrum using the standard Judd-Ofelt (J-O) theory [START_REF] Judd | Optical absorption intensities of rare-earth ions[END_REF][START_REF] Ofelt | Intensities of crystal spectra of rare-earth ions[END_REF], and its modification accounting for configuration interaction (mJ-O theory) [START_REF] Loiko | Spectroscopy of Tb 3+ ions in monoclinic KLu(WO 4 ) 2 crystal: application of an intermediate configuration interaction theory[END_REF]. This formalism was used to determine the contributions of electric dipoles (ED). The magnetic dipole (MD) contributions for transitions with ΔJ = J -J' = 0, ±1 were calculated independently within the approximation of Russell-Saunders on the wave functions of Tm 3+ under an assumption of a free-ion. The refractive index of CLTGG was taken from [START_REF] Guo | Growth and characterizations of calcium tantalum gallium garnet single crystal[END_REF].

The detailed procedure of the J-O calculations for Tm 3+ -doped crystals is described in detail elsewhere [START_REF] Walsh | Branching ratios, cross sections, and radiative lifetimes of rare earth ions in solids: Application to Tm 3+ and Ho 3+ ions in LiYF 4[END_REF]. Here, we only discuss the main approximations. For the standard J-O theory, the ED line strengths of the J → J' transition are given by:

ED (k) calc k k 2,4,6 ( ') , S JJ U = =   (1a) (k) n k n 2 (4f ) || || (4f ) ' ' ' U SLJ U S L J =   . (1b)
Here, U (k) are the reduced squared matrix elements which were calculated using the free-ion parameters from [START_REF] Peijzel | 4f n-1 5d→4f n emission of Ce 3+ , Pr 3+ , Nd 3+ , Er 3+ , and Tm 3+ in LiYF 4 and YPO 4[END_REF] and Ω k are the intensity (J-O) parameters (for both, k = 2, 4, 6).

In the mJ-O theory, it is assumed that only the excited configuration of opposite parity 4f n- 1 5d 1 contributes to the configuration interaction. The ED line strengths are then [START_REF] Loiko | Spectroscopy of Tb 3+ ions in monoclinic KLu(WO 4 ) 2 crystal: application of an intermediate configuration interaction theory[END_REF]:

ED (k) calc k k 2,4,6 ( ') S JJ U = =   , ( 2a
) 0 k k J J' f [1 2 ( 2 )]
.

E E E   =  + + - (2b)
In other words, the intensity parameters k  are linear functions of energies (E J and E J' ) of the two multiplets, where E f 0 is the mean energy of the 4f n configuration and α ≈ 1/(2Δ) where Δ ≈ E(4f n-1 5d 1 ) -E(4f n ) is the average energy difference between the fundamental and first excited configurations. and Ω 2 = 5.185, Ω 4 = 0.650, Ω 6 = 1.068 [10 -20 cm 2 ] and α = 0.171 [10 -4 cm] (mJ-O theory). The latter theory provides lower root mean square (rms) deviation between the experimental and calculated f values, so that it was selected for further analysis.

The probabilities of spontaneous radiative transitions A calc (JJ'), the luminescence branching ratios B(JJ') and the radiative lifetimes of the excited-states τ rad were calculated using the mJ-O theory, the results are shown in Table 3. For the 3 F 4 and 3 H 4 states, τ rad is 5.33 ms and 0.55 ms, respectively.

Luminescence (emission spectra and lifetime)

The RT luminescence spectrum was measured using an optical spectrum analyzer (AQ6375B, Yokogawa) for which the spectral response was calibrated using a 20 W quartz iodine lamp.

The pump source was a 795 nm Ti:Sapphire laser (excitation to the 3 H 4 state). The luminescence spectrum is shown in Fig. 7(a). The broad and intense band at 1.6 -2.3 µm is due to the 3 F 4 → 3 H 6 transition, while the weaker band at 1.35 -1.55 µm originates from the 3 H 4 → 3 F 4 transition.

The luminescence decay was studied at RT using an optical parametric oscillator (Horizon, Continuum), a 1/4 m monochomator (Oriel 77200), an InGaAs detector and an 8 GHz digital oscilloscope (DSA70804B, Tektronix). The sample was finely powdered to avoid the effect of radiation trapping. The decay curve from the 3 F 4 state is well fitted using a single-exponential law yielding a luminescence lifetime τ lum of 4.93 ms (for the powdered sample), Fig. 7(b). It is only slightly shorter than the radiative one, revealing a relatively high quantum yield η q = τ lum /τ rad = 92%. For the bulk sample, τ lum = 6.50 ms due to the strong reabsorption. The decay from the 3 H 4 state is not single-exponential revealing the effect of cross-relaxation for neighboring Tm 3+ ions. The mean decay time <τ lum > = 0.159 ms, Fig. 7(c).

Low-temperature spectroscopy

The low temperature (LT, 10 K) absorption and luminescence spectra were measured using a cryostat (Oxford Instruments, model SU 12) with helium-gas close-cycle flow. In CLTGG, Tm 3+ ions replace for the Ca 2+ ones in dodecahedral sites with D 2 symmetry. These sites are distorted due to the presence of univalent Li + cations serving for charge compensation and various cation coordinations around the {A} sites, cf. Fig. 3. Each 2S+1 L J multiplet with integer J is thus split into 2J + 1 Stark sub-levels. For brevity, in Fig. 8, we only show the absorption and luminescence spectra revealing the splitting of the 3 F 4 and 3 H 6 states relevant for ~2 µm laser operation. The assignment of electronic transitions is after the work of Lupei et al. for ordered Tm 3+ -doped Gd 3 Ga 5 O 12 (GGG) garnet [START_REF] Lupei | Crystal-field levels of Tm 3+ in gadolinium gallium garnet[END_REF]. Figure 8 reveals a significant inhomogeneous broadening of the absorption and luminescence bands of Tm 3+ ions even at 10 K when the electron-phonon interaction is suppressed, which is a fingerprint of the structure disorder. The experimental energy-levels of Tm 3+ ions in CLTGG are listed in Table 4 for the multiplets from 3 H 6 to 1 D 2 . For the 3 F 4 → 3 H 6 transition of interest for ~2 µm laser operation, the zero-phonon line (ZPL), i.e., the transition between the lowest Stark sub-levels of both multiplets, occurs at 1806 nm (E ZPL = 5538 cm -1 ). The partition functions for the ground-state and the excited-state, calculated at RT, amount to Z 1 = 4.786 and Z 2 = 2.402, respectively, so that their ratio Z 1 /Z 2 = 1.992.

Transition cross-sections

The absorption cross-section spectrum for the 3 H 6 → 3 F 4 transition is shown in Fig. 9(a), the maximum σ abs reaches 0.25×10 -20 cm 2 at 1699 nm.

For the 3 F 4 → 3 H 6 transition, the stimulated-emission (SE) cross-section, σ SE , spectra were calculated by two methods: the Füchtbauer-Ladenburg (F-L) equation [START_REF] Aull | Vibronic interactions in Nd:YAG resulting in nonreciprocity of absorption and stimulated emission cross sections[END_REF] and the reciprocity method (RM) [START_REF] Payne | Infrared cross-section measurements for crystals doped with Er 3+ , Tm 3+ , and Ho 3+[END_REF]. For the F-L equation, the luminescence spectrum was used, cf. Fig. 7(a), the radiative lifetime of the 3 F 4 state was determined from the mJ-O theory (τ rad = 5.33 ms) and the refractive index of the crystal (n ≈ 1.92) was taken from [START_REF] Guo | Growth and characterizations of calcium tantalum gallium garnet single crystal[END_REF]. For the RM, we used the measured absorption spectrum and the determined crystal-field splitting, cf. Table 4. The results of both methods are shown in Fig. 9(a). They are in good agreement with each other.

The maximum σ SE reaches 0.35×10 -20 cm 2 at 1866 nm and at longer wavelengths where laser operation is expected, σ SE reaches 0.18×10 -20 cm 2 at 1992 nm (both values correspond to the F-L method).

The ~2 µm Tm laser represents a quasi-three-level scheme with reabsorption. Thus, gain The measured pump absorption was ~47%. The residual pump was filtered out using a long pass filter (FEL1000, Thorlabs). The spectra of the laser output were measured using a spectrometer (WaveScan, APE). The profile of the laser mode in the far-field was captured using a FIND-R-SCOPE near-IR camera (model 85726).

Laser performance

The input-output dependences of the diode-pumped Tm:CLTGG laser are shown in Fig. 11(a).

The laser generated a maximum output power of 1. A summary of output characteristics of CW lasers based on Tm 3+ -doped disordered gallium garnets is presented in Table 5.

Conclusions

To conclude, Tm:CLTGG is a promising crystal for ultrashort pulse generation (sub-100 fs) in the eye-safe spectral range of ~2 µm. It exhibits a structural disorder related to a random site distribution of Ta 5+ , Ga 3+ and Li + cations over the same lattice sites, octahedral (16a) and tetrahedral (24d), which leads to a significant inhomogeneous broadening of the absorption and emission bands of Tm 3+ ions confirmed at low temperature (10 K). At room temperature, due to a combination of the inhomogeneous broadening and electron-phonon interaction, Tm:CLTGG exhibits smooth and very broad gain profiles owing to the phonon-assisted 3 F 4 → 3 H 6 transition extending up to at least ~2.2 µm. From X-ray diffraction, Raman spectroscopy and optical transmission, it is evident that Li + ions provide charge compensation during the heterovalent doping (as Tm 3+ ions are replacing Ca 2+ ones) and almost eliminate the presence of cationic vacancies. Finally, Tm:CLTGG exhibits attractive thermal properties (for a disordered crystal) being superior to those of the CNGG-type crystals.

Ca 3

 3 Ta 1.88 Li 0.20 Ga 2.80 O 12 ·0.05Tm 3 Ga 5 O 12 . To compensate the volatilization of Ga 2 O 3 during the synthesis of the polycrystalline material and the crystal growth, an excess of 1.0 wt% Ga 2 O 3 was used. Larger excess of Ga 2 O 3 violates the composition of the crystal and affects its optical quality. The equation of the chemical reaction reads: 3CaCO 3 + 0.94Ta 2 O 5 + 1.525Ga 2 O 3 + 0.075Tm 2 O 3 + 0.1Li 2 CO 3 → Ca 3 Ta 1.88 Li 0.20 Ga 2.80 O 12 ·0.05Tm 3 Ga 5 O 12 + 3.1CO 2 ↑.

Fig. 1 .

 1 Fig. 1. (a) Photograph of the as-grown Tm:CLTGG crystal boule, the growth direction is [111]; (b) photograph of a polished laser element.

Figure 1

 1 Figure 1 shows a photograph of an as-grown Tm:CLTGG crystal boule. It has a cylindrical shape (diameter: 20 mm, length of the central part: 30 mm). The crystal does not contain cracks and inclusions and no scatter centers are seen under illumination by a He-Ne laser indicating good optical quality. The as-grown crystal shows a light greenish coloration. The surface of the boule is translucent probably due to the volatilization of Ga 2 O 3 during the crystal growth (it may attack the surface of the crystal that is pulled over the melt). The internal part of the crystal exhibits excellent transparency, Fig. 1(b).

  (a), agrees well with the theoretical one for cubic Al 1.23 Ca 3 Fe 0.99 Hf 2 Si 0.99 O 12 garnet (Crystallography Open Database (COD) card #96-901-3967). No other phases are found. The structure of Tm:CLTGG was refined using the Rietveld method. The Match3! software was used and a total of 196 reflections were analyzed. The obtained reliability factors are R p = 4.94%, R wp = 6.38%, R exp = 2.21% and the reduced chi squared χ 2 = (R wp /R exp ) 2 = 8.37. Tm:CLTGG crystallizes in the cubic class (sp. gr. 3 Ia d , No. 230) with a lattice constant a = 12.5158(0) Å, the volume of the unit-cell is V = 1960.54 Å 3 , the calculated density is ρ calc = 5.893 g/cm 3 and the number of formula units in the unit-cell is Z = 8. The fractional atomic coordinates, the site occupancy factors (O.F.) and the isotropic displacement parameters obtained during the Rietveld refinement are listed in Table

Fig. 2 .

 2 Fig. 2. X-ray powder diffraction study of Tm:CLTGG: (a) XRD pattern, (hkl) are Miller's indices, vertical barstheoretical pattern for Al 1.23 Ca 3 Fe 0.99 Hf 2 Si 0.99 O 12 garnet; (b) Rietveld structure refinement: experimental (black), calculated (red) and differential (blue) XRD profiles, vertical dashes mark the Bragg reflections.

Table 1 .Tm

 1 Fractional Atomic Coordinates, Occupancy Factors and Isotropic Displacement Parameters for Tm:CLTGG is illustrated in Fig. 3. This crystal belongs to the family of multicomponent garnets with a general formula {A} 3 [B] 2 (C) 3 O 12 , where {A}, [B], and (C) stand for dodecahedral (Wyckoff symbol: 24c), octahedral (16a) and tetrahedral (24d) sites, respectively [5]. The stoichiometric CTGG, in analogy to CNGG [4], is expected to have a chemical formula of Ca 3 Ta 1.5 Ga 3.5 O 12 which is equivalent to {Ca 3 }[Ta 1.5 Ga 0.5 ](Ga 3 )O 12 . The composition of the real crystal (even undoped) deviates from the stoichiometric one. The Ca 2+ cations are located in the {A} sites.

Fig. 3 .

 3 Fig. 3. Crystal structure of Tm:CLTGG: (a) a fragment of the crystal structure within one unitcell (dashed lines) in projection to the a-c plane; (b) the variety of cationic distributions around Ca 2+ | Tm 3+ ions occupying the dodecahedral 24c sites: nearest-neighbor cations at: (i) dodecahedral 24c sites, (ii) octahedral 16a sites and (iii) tetrahedral 24d sites.

  cations. The band at lower frequencies with two local maxima at 748 cm -1 (C 1 ) and 772 cm -1 (C 2 ), is assigned to the [Ga2O 4 ] groups and it is only slightly distorted with respect to that in the Tm:CLNGG crystal. The band at higher frequencies, at 842 cm -1 (C 4 ), is due to the [Ta2O 4 ] groups. The latter does not split, possesses much weaker intensity and is shifted to higher frequencies as compared to that in Tm:CLNGG crystal with [Nb2O 4 ] groups. The lack of the long-frequency component of the second band indicates weak structural distortion of the [Ta2O 4 ] tetrahedra and weak content of cationic vacancies, in agreement with the XRD study.

Fig. 4 .

 4 Fig. 4. Unpolarized RT Raman spectrum of the Tm:CLTGG crystal, λ exc = 514 nm. Numbers indicate the band frequencies in cm -1 . The Raman spectrum of Tm:CLNGG is given for comparison.

  Fig.5(c). At room temperature, it amounts to 4.33 Wm -1 K -1 , which is larger than for CNGG-

Fig. 5 .

 5 Fig. 5. Thermal properties of the Tm:CLTGG crystal as a function of temperature: (a) specific heat; (b) thermal diffusivity; (c) thermal conductivity.

Fig. 6 .

 6 Fig. 6. Absorption of the Tm:CLTGG crystal: (a) RT absorption spectrum; (b) absorption crosssections, σ abs , for the 3 H 6 → 3 H 4 Tm 3+ transition; (c) Tauc plot for the evaluation of the optical bandgap (E g ). The absorption cross-sections σ abs for the 3 H 6 → 3 H 4 Tm 3+ transition which is suitable for pumping of laser crystals by AlGaAs diode lasers emitting at ~0.8 µm are shown in Fig. 6(b). The maximum σ abs is 0.31×10 -20 cm 2 at 795.0 nm and the absorption bandwidth (full width at half maximum, FWHM) is 26.7 nm. Compared to the widespread Tm:Y 3 Al 5 O 12 garnet crystal, Tm:CLTGG exhibits smoother and broader absorption at the expense of lower cross-section.

Fig. 7 .

 7 Fig. 7. Near-infrared emission properties of the Tm:CLTGG crystal: (a) luminescence spectrum, λ exc = 795 nm; (b,c) luminescence decay curves from the (b) 3 F 4 and (c) 3 H 4 Tm 3+ states.

Fig. 8 .

 8 Fig. 8. Low-temperature (LT, 10 K) absorption and emission spectra for Tm 3+ ions in the CLTGG crystal: (a) absorption, 3 H 6 → 3 F 4 transition; (b) emission, 3 F 4 → 3 H 6 and 3 H 4 → 3 H 6 transitions. The symbol "+" marks the assigned electronic transitions. Vertical dashescrystalfield splitting in Tm:GGG after [23].

  cross-sections are usually calculated, σ gain = σ SE -(1 -β)σ abs , where β = N 2 ( 3 F 4 )/N Tm is the inversion ratio. They are useful to conclude about the possible laser wavelength (in the freerunning regime), the potential tuning range as well as the gain bandwidth in ML lasers. The gain spectra for Tm:CLTGG are shown in Fig. 9(b). The gain profiles of this disordered crystal are smooth and broad. For small and moderate inversion ratios (β < 0.16), a single local peak is observed in the spectra centered at ~1.99 µm. The gain bandwidth (FWHM) for an intermediate β = 0.12 is as broad as 130 nm. The gain profiles extend well beyond 2 µm owing to the large total ground-state splitting (ΔE( 3 H 6 ) = 668 cm -1 ) for Tm 3+ ions and strong electronphonon (vibronic) interaction with phonons of the host matrix. The longest purely electronic transition (neglecting the inhomogeneous broadening) for Tm 3+ ions is 2053 nm.

Fig. 9 . 6 . Diode-pumped laser operation 6 . 1

 9661 Fig. 9. 3 H 6 ↔ 3 F 4 transition of Tm 3+ ions in CLTGG: (a) absorption, σ abs , and stimulated emission (SE), σ SE , cross-sections; (b) gain cross-sections, σ gain = σ SE -(1 -β)σ abs , where β = N 2 ( 3 F 4 )/N Tm is the inversion ratio.6. Diode-pumped laser operation 6.1 Laser set-up Figure 10(a) shows the scheme of the compact diode-pumped Tm:CLTGG laser. The laser element was cut along the [111] direction. It had an aperture of 3.05×3.09 mm 2 and a thickness of 8.19 mm. Both end faces of the element were polished to laser quality and left uncoated. To remove the heat released during pumping, the element was wrapped in indium foil and fixed in a Cu-holder cooled by circulating water; the water temperature was 12 °C.The laser cavity consisted of a flat pump mirror (PM) coated for high transmission (HT) at 0.80 µm and high reflection (HR) at 1.8-2.1 µm and a set of flat output couplers (OCs) having transmissions T OC of 1.5%, 3%, 5% or 9% at the laser wavelength. Both mirrors were placed

Fig. 10 .

 10 Fig. 10. (a) Scheme of the diode-pumped compact Tm:CLTGG laser: LDlaser diode, PMpump mirror, OCoutput coupler, Fcut-on filter; (b) far-field output profile of the laser mode, T OC = 5%, P abs = 4.0 W.

  08 W at 1995 and 2003 nm with a slope efficiency η of 23.8% (with respect to the absorbed pump power) and a laser threshold of 0.91 W (for T OC = 5%). At the maximum incident pump power of 11.7 W, the optical-to-optical conversion efficiency η opt amounted to 9.2%. Further power scaling was limited by the thermal roll-over in the output dependences. With increasing the output coupling, the laser threshold increased from 0.68 W (T OC = 1.5%) to 1.46 W (T OC = 9%).

Fig. 11 .

 11 Fig. 11. Diode-pumped Tm:CLTGG laser: (a) input-output dependences, ηslope efficiency; (b) typical spectra of unpolarized laser emission measured at maximum P abs .

  a P out -output power, λ L -laser wavelength, η -slope efficiency, P th -laser threshold.The laser generated unpolarized emission. The typical spectra of the laser emission are shown in Fig.11(b). With increasing T OC from 1.5% to 9%, a blue shift of the emission wavelength was observed from 2012 and 2017 nm to 1994 and 2002 nm. This shift is due to the decreasing reabsorption losses in the crystal typical for quasi-three-level Tm lasers. It also agrees with the gain spectra of Tm:CLTGG, cf. Fig.9(b). The dual-wavelength emission was due to the etalon effect at the crystal / mirror interface and the broad and smooth gain profile.The laser mode in the far-field, Fig.10(b), was nearly circular.

  [Ca|TmO 8 ] dodecahedrons, there are four shorter (2.3966(2) Å) and four longer (2.5577(0) Å) metal-to-oxygen (M-O) interatomic distances. The Ta 5+ and Ga 3+ cations are randomly distributed over the [B] and (C) sites with

	VI-fold and IV-fold oxygen coordination, respectively, according to the occupancy factors
	listed in Table 1. The M-O bond lengths are 1.990(0) Å (×6) and 1.8526(1) Å (×4), respectively.
	The Li + ion incorporation in this garnet takes place only at 24d sites. The charge compensation
	is ensured by both, Li + ions and cationic vacancies □ in the 24c and 24d sites. Their calculated
	percentages are 0.6% and 2.8%, respectively. The chemical formula of the crystal can be thus
	expressed as follows:
	{Ca 2.889 Tm 0.093 □ 0.018 }[Ta 1.32 Ga 0.68 ](Ga 2.367 Ta 0.204 Li 0.345 □ 0.084 )O 12 .
	In the Tm:CLTGG structure, each [Ca|TmO 8 ] dodecahedron shares edges with four other
	dodecahedra where the shortest interatomic distance Ca|Tm-Ca|Tm is 3.8321(1) Å, and it is
	surrounded by four corner-sharing octahedra (Ta

Table 2 . Measured and Calculated Absorption Oscillator Strengths of Tm 3+ ions in CLTGG crystal a

 2

	Transition	<E>,	Г,	f exp ,	f Σ calc , 10 -6
	3 H 6 → 2S+1 L J	cm -1	nm×cm -1 10 -6	J-O	mJ-O
	3 F 4	5823	215.51	1.641	1.649 ED	1.583 ED
	3 H 5	8363	76.642	1.211	1.317 ED +0.534 MD	1.058 ED +0.534 MD
	3 H 4	12628 51.696	1.859	2.139 ED	2.810 ED
	3 F 3,2	14568 44.848	2.137	3.073 ED	2.521 ED
	1 G 4	21182 7.750	0.791	0.568 ED	1.101 ED
	1 D 2	27686 10.607	1.849	1.815 ED	1.783 ED
	1 I 6 + 3 P 0 + 3 P 1	35239 13.677	3.811	1.690 ED +0.029 MD	3.017 ED +0.029 MD
	3 P 2	38067 6.665	2.166	1.958 ED	2.270 ED
	r.m.s. dev.				1.078	0.689
	a <E> -"center of gravity" of the absorption band, Г -integrated absorption coefficient,
	f exp and f Σ calc -experimental and calculated absorption oscillator strengths, respectively,

ED electric-dipole, MD -magnetic-dipole.

Table 2

 2 summarizes the experimental and calculated absorption oscillator strengths f (the latter are determined by both the J-O and mJ-O theories from the corresponding line strengths).The intensity parameters are Ω 2 = 1.715, Ω 4 = 0.943 and Ω 6 = 0.963 [10 -20 cm 2 ] (J-O theory)

Table 3 . Calculated Probabilities of Spontaneous Radiative Transitions of Tm 3+ ions in CLTGG crystal (Obtained from the mJ-O Theory) a

 3

	Excited	Terminal	λ em ,	A calc (JJ'),	B(JJ'),	A tot ,	τ rad ,
	state	state	nm	%	%	s -1	ms
	3 F 4	3 H 6	1717.3 63.62 ED	1	187.51	5.33
	3 H 5	3 F 4	3937.0	8.81 ED +0.24 MD	0.027	329.09	3.03
		3 H 6	1195.7	212.78 ED +107.26 MD	0.973
	3 H 4	3 H 5	2344.7	16.59 ED +10.34 MD	0.015	1801.71	0.55
		4 F 4	1469.5	154.95 ED +25.61 MD	0.100
		3 H 6	791.9	1594.22 ED	0.885
	3 F 2 + 3 F 3	3 H 4	5154.6	22.24 ED +0.32 MD	0.005	4760.78	0.36
		3 H 5	1611.6	818.37 ED	0.172
		3 F 4	1143.5	1191.94 ED +74.14 MD	0.266
		3 H 6	686.4	2653.77 ED	0.557
	1 G 4	3 F 2 + 3 F 3	1511.9	28.52 ED	0.030	4524.78	0.22
		3 H 4	1169.0	103.11 ED +4.17 MD	0.142
		3 H 5	780.1	600.49 ED +39.18 MD	0.359
		3 F 4	651.1	1468.80 ED +156.71 MD	0.063
		3 H 6	472.1	273.22 ED +12.88 MD	0.406
	1 D 2	1 G 4	1537.5	563.86 ED	0.008	72495.29 0.01
		3 F 2 + 3 F 3	762.3	5710.24 ED +183.16 MD	0.081
		3 H 4	664.1	5340.29 ED	0.074
		3 H 5	517.5	218.16 ED	0.003
		3 F 4	457.4	50840.29 ED	0.701
		3 H 6	361.2	9639.29 ED	0.133

a λ em  -mean emission wavelength, A calc (JJ')probability of radiative spontaneous transition, B(JJ')luminescence branching ratio, A tottotal probability of radiative transitions, τ rad -radiative lifetime, ED electric-dipole, MD -magnetic-dipole.

Table 4 . Experimental Energy Levels of Tm 3+ ions in CLTGG crystal

 4

	Multiplet	E, cm -1
	3 H 6	0; 42; 91; 126; 160; 187; 206; 342; 433; 484; 522; 549; 668
	3 F 4	5538; 5713; 5760; 5813; 5952; 6067; 6091; 6101; 6138
	3 H 5	8299; 8314; 8396; 8412; 8426; 8458; 8567; 8606; 8683; 8773; 8809
	3 H 4	12577; 12594; 12632; 12703; 12739; 12774; 12916; 12994; 13026
	3 F 3	14552; 14573; 14621; 14644 (3 missing)
	3 F 2	15096; 15129; 15149; 15230 (1 missing)
	1 G 4	21071; 21116; 21205; 21284; 21304; 21461; 21489; 21648; 21707
	1 D 2	27662; 27826; 27940; 28044; 28102

Table 5 . Laser Performances a of Tm 3+ -doped Gallium Garnets

 5

	Crystal	Tm, at.% P out , W	λ L , nm	η, %	P th , W	Ref.
	Tm:CLTGG	3.17	1.08	1995, 2003	23.8	0.91	This work
	Tm:CNNGG	3.2	1.05	2008	35.0	0.39	[8]
	Tm:CLNGG	3.6	1.32	2002	45.8	0.30	[8]
		~3	1.6	1985-2015	37	~1	[26]
	Tm:CNGG	2.0	0.17

Funding. This work was supported by Spanish Government, Ministry of Science and Innovation (project No. PID2019-108543RB-I00) and by Generalitat de Catalunya (project No. 2017SGR755). National Natural Science Foundation of China (52072351); Foundation of the President of China Academy of Engineering Physics (YZJJLX2018005); Foundation of Key Laboratory of Optoelectronic Materials Chemistry and Physics, Chinese Academy of Sciences (2008DP173016); Foundation of State Key Laboratory of Crystal Materials, Shandong University (KF2001).

Disclosures.

The authors declare no conflicts of interest.

Data Availability. Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.