A Vasques
email: vasques@euc.eur.nl

M Baudena

R Vallejo

S Kéfi

S Bautista

V M Santana

J J Keizer

M Rietkerk

Post-fire regeneration traits of understorey shrub species modulate successional responses to high severity fire in Mediterranean pine forests

Recurrent fires can impede the spontaneous recruitment capacity of pine forests.

Empirical studies have suggested that this can lead to a prolonged replacement of pine forest by shrubland, especially if shrub species are pyrophytic. Modelbased studies, however, have suggested that post-fire succession of pine forest under current climatic conditions will eventually tend towards the dominance of oaks, even under high fire recurrence. These previous modelling studies did not address the role of the various post-fire regeneration traits of the understory shrub species. Considering the dichotomy of obligate seeder vs. resprouter species, either obligate or facultative resprouter, we hypothesized that when the shrubs present are post-fire seeders, the oaks steadily occupy the forest, whereas resprouter shrub species might compete with oaks and delay or arrest post-fire succession.

To test this hypothesis, we developed a dynamic, cellular automaton model for simulating post-fire successional transitions in pine forests, including shrubs, pines and oaks, and stochastic fires of regular frequency.

Our results showed a strong tendency towards oak dominance as final model state and a very reduced role of fire recurrence in this final state, with low yearly acorn input delaying oak dominance. Most relevantly, and in line with our hypothesis, the trend towards oak dominance depended markedly on the two types of shrub species, being delayed by resprouter species, which extended the shrub-dominated succession stage for several centuries. Our simulation results supported the view that the type of understorey species should be a key consideration in post-fire restoration strategies aiming to enhance ecosystem resilience.

Keywords

Empirical studies have suggested that this can lead to a prolonged replacement of pine forest by shrubland, especially if shrub species are pyrophytic. Modelbased studies, however, have suggested that post-fire succession of pine forest under current climatic conditions will eventually tend towards the dominance of oaks, even under high fire recurrence. These previous modelling studies did not address the role of the various post-fire regeneration traits of the understory shrub species. Considering the dichotomy of obligate seeder vs. resprouter species, either obligate or facultative resprouter, we hypothesized that when the shrubs present are post-fire seeders, the oaks steadily occupy the forest, whereas resprouter shrub species might compete with oaks and delay or arrest post-fire succession.

To test this hypothesis, we developed a dynamic, cellular automaton model for simulating post-fire successional transitions in pine forests, including shrubs, pines and oaks, and stochastic fires of regular frequency.

Our results showed a strong tendency towards oak dominance as final model state and a very reduced role of fire recurrence in this final state, with low yearly acorn input delaying oak dominance. Most relevantly, and in line with our hypothesis, the trend towards oak dominance depended markedly on the two types of shrub species, being delayed by resprouter species, which extended the shrub-dominated succession stage for several centuries. Our simulation results supported the view that the type of understorey species should be a key consideration in post-fire restoration strategies aiming to enhance fire resilience.

Introduction

In the past fifty years, Mediterranean landscapes experienced intense changes that led to abandonment of marginal croplands, on the one hand, and, on the other hand, to extensive afforestation with pine plantations (Pausas and others 2004;Vallejo and others 2012 ab). These changes have contributed to intensifying fire regimes in the Mediterranean Basin, which in turn, can have pronounced effects on the composition and long-term resilience of its plant communities (Diaz-Delgado and others 2002;Vallejo and others 2012 ab).

According to the classical view on succession, species replacement in the absence of disturbance is driven by facilitation mechanisms, with early successional species creating conditions that are less favourable for themselves than for late successional species [START_REF] Clements | Plant Succession: An Analysis of the Development of Vegetation Carnegie Institute of Washington Washington[END_REF][START_REF] Connell | Mechanisms of succession in natural communities and their role in community stability and organization[END_REF]. In line with this theory, undisturbed Mediterranean pine forests are considered to foster successional processes, in particular by creating conditions under their canopy that are favourable for the establishment of late successional species (e.g. Quercus ilex; Zavala and others 2000). Most Mediterranean plant species are well adapted to fire occurrence, responding to fire through three main regeneration strategies (also called plant functional types, PFT): i) plant survival through the resistance of below-ground buds to fire, followed by resprouting of the above-ground tissues (obligate resprouters), and recruitment is produced in the intervals between fires (Keeley and others 2012), ii) plant mortality with survival of the seeds (obligate seeders) or iii) a combination of both mechanisms (facultative shrub species; according to Pausas andothers 2004 andPaula and[START_REF] Paula | Burning seeds: germinative response to heat treatments in relation to resprouting ability[END_REF]. Studies of post-fire dynamics have shown that plant communities dominated by resprouter species (which are usually late successional) are more resilient to both short and long fire intervals than communities dominated by seeder species [START_REF] Keeley | Resilience of Mediterranean shrub communities to fires In: Resilience in Mediterranean-Type Ecosystems[END_REF]), yet important questions remain on how the various plant functional types interact in shaping the post-fire community development.

The resilience of pine forests to frequent fires is largely limited by pine seed production. This means that the occurrence of high recurrent repeated fires in a short interval of time or of a single fire in a young pine forest can cause the local eradication of pines (immaturity risk; Moreira and others 2011;De las Heras and others 2012). This eradication gives rise to the dominance of other species, which could either be early or late successional, depending on the species composition of the understory before the fire (Rodrigo and others 2004). In this context, several studies indicate that high wildfire frequency can favour the replacement of pine and oak forests by fire-prone shrublands (Acácio andothers 2009, 2010;Santana and others 2010;Santana andothers 2010, 2014). Furthermore, the colonization of late successional species, such as resprouter oak trees, in fireprone shrublands can be limited by several factors related to seed dispersal and micro-climate conditions (Acácio and others 2007;[START_REF] Pons | Acorn dispersal estimated by radiotracking[END_REF].

These recruitment limitations could arrest successional processes, locking the system in a shrubland state, i.e. plant communities that lack a tree layer and are dominated by fire-prone shrub species (Acácio and others 2007(Acácio and others , 2009(Acácio and others , 2010;;Santana and others 2010). The dominance of fire-prone shrublands can markedly reduce the resilience of the ecosystem by, for example, increasing erosion risk and decreasing biodiversity (Mayor and others 2016;Van del Elsen and others 2020). Despite this, oak tree species can also become dominant in former pine forests where pines have been eradicated as a result of recurrent fires [START_REF] Keeley | Resilience of Mediterranean shrub communities to fires In: Resilience in Mediterranean-Type Ecosystems[END_REF][START_REF] Torres | Forest shifts induced by fire and management legacies in a Pinus pinaster woodland[END_REF]others 2016, Baudena andothers 2020).

Plant succession is expected to be modulated by factors such as fire severity (Díaz-Delgado and others 2003; López-Poma and others 2014), seed source, disperser preference, and the occurrence of safe germination microsites (Pons andPausas 2006, 2007). The persistence of a litter layer after a fire, which largely depends on fire severity (Lamont and others 1993;Maia and others 2012), modifies the colonization probability of plants from different functional groups.

Thick litter layers may selectively inhibit the germination and establishment of species with small seeds (Farrell and others 2012;Loydi and others 2013) as opposed to big seeds [START_REF] Thompson | The functional ecology of soil seed banks in Michael Fenner ed Seeds: the ecology of regeneration in plant communities CAB international[END_REF]. This contrast in seed size broadly coincides with that in early vs. late successional Mediterranean species and, simultaneously, with that between obligate seeder shrubs vs. resprouter species (Cerabolini and others 2003). Also, by buffering temperature and moisture fluctuations, pine litter favours the establishment of late successional species over that of early successional species (Facelli and Picket 1991;Gaudio and others 2011). However, despite the important role of litter as modulator of the composition and structure of plant communities (Facelli and Facelli 1993;Xiong and Nilson 1999), its effects have not been included so far in the analysis of the successional dynamics of pine forests under different fire regimes.

According to Baudena and others (2020), pine forests will be replaced by oak forests in the long run. However, the post-fire resprouting ability of oak trees can be hampered because of unfavourable environmental conditions, e.g., due to the predicted climatic changes; this can, in turn, lead to the dominance of fire-prone shrublands instead of late successional oak forests. Furthermore, we expect that, under high fire recurrence, oak tree dominance will be delayed by reduced seed colonization (low seed entry). We hypothesise that facultative resprouter shrubs will likely delay oak tree dominance further than obligate seeder shrubs because facultative species exhibit both a positive fire feedback due to their high flammability and a high persistence after fire due to their resprouting capacity. In short, whereas frequent fires in a short interval can deplete seed banks of obligate seeder shrubs, facultative shrub species can persist by their resprouting capacity, thus delaying their replacement by late successional species. According to this hypothesis, the main objective of this study was to improve our understanding of the role of facultative resprouter shrubs in delaying succession, represented by the dominance of oak tree species, following wildfire.

To test the role of shrubs in post-fire succession, we developed a dynamic successional model that simulates the population dynamics of three plant functional types simultaneously: pine, oak tree and either an obligate seeder or a facultative shrub species. The simulated temporal scale allowed species replacement and succession. Using this model, we studied the long-term vegetation dynamics of a mimicked Mediterranean pine forest under different understory functional composition (obligate seeder versus facultative species) and fire frequency conditions, and we analysed the dynamics of the transient period (until approximately 1000 years), by studying the time at which the late successional species (oak tree) attained relative dominance. Additionally, we studied how the oak tree colonization capacity (represented by the entry of acorns) and post-fire microsite conditions (represented by fire severity and litter depth) influence the progress of succession.

Material and Methods

We implemented a stochastic cellular automata model (also called interacting particle systems; Durrett and Levin 1994), which allowed representing spatial processes at the landscape scale. Cellular automata consist of one lattice, in which each cell acquires a discrete and finite value, and of transition rules that control the temporal and spatial changes in the values of the state of the cells [START_REF]Cellular automata as models of complexity[END_REF]. In our model, the state variable was the plant functional type.

The lattice had 100*100 cells (each cell being denoted by x in what follows), and each cell contained only one plant type, which could be interpreted as one adult tree but also of few small shrub plants. For simplification purposes, if the cell was considered as occupied by more plants, they were of the same type and age. The

Soil seedbank

We kept track of the soil seedbank SBi at the plot scale (i.e., the whole lattice), for each plant functional type i, by computing both the production and the seed input from neighbouring areas. We assumed that the seeds were dispersed homogeneously across the plot, thus we multiplied each cell seed production rate, SPi(x), by the number of cells that were occupied by mature individuals in the whole lattice. For pines and shrubs, the average numbers of seeds per cell, Nseeds1,2(x), were then calculated as the number of seeds in the soil seedbank, SB1,2, divided by the total number of cells. In the case of oak tree, given the small number of seeds compared to the other species, the seeds locally produced and those arrived from elsewhere were randomly distributed across the cells in the lattice to calculate Nseeds3. In the following, we detail how we implemented seed production and storage in the seed bank.

Seed production

The annual pine seed production per cell SP1(x) was estimated at 100 seeds, which was calculated by considering that 10% of the average produced seeds would be available for germination after predation and seed loss (Vega and others 2008). Pine age of maturity (AM, the age at which a tree starts, on average, producing seeds) was defined as 10 years, as an approximation of the values reported for Pinus pinaster (Tapias andothers 2001, Thanos and[START_REF] Thanos | Ecology biogeography and management of Pinus halepensis and P brutia forest ecosystems in the Mediterranean Basin p 79-90[END_REF].

The shrub species (either obligate seeder or facultative species) produced 1000 available seeds per occupied cell. It was considered that both the obligate seeder and the facultative shrub species started producing seeds after 2 years.

Finally, we defined that each mature oak tree produced 10 acorns per year that were available for germination (considering predation as well as seed and seedling loss, Gomez and others 2003). The oak trees reached maturity at 20 years (average value between field observation by Pausas 1999a and the authors, unpublished).

Seed Bank

Depending on their specific strategy, each plant functional type was linked to different rules for the yearly seed bank update. Pines had a seed bank (serotinous cones) accumulating in the canopy over time (Vega and others 2008). We considered a degree of serotiny of 50%, which means that half of the seeds that were contained in serotinous cones before the fire were released after the fire (Table 1). Thus, every year, half of the seeds that were produced in each cell, SP1(x), were accumulated in the pine canopy bank (CB1) and the other half was released to the soil:𝑆𝑃 ! (𝑥) = DS * 𝐶𝐵 ! (𝑥). The pine seeds remained viable in the soil for two years at most (de las Heras and others 2012): we simulated that 50% of the seeds died after the first year and the other 50% after the second year. In the case of the seeds of shrub species, the annual decay rate was set at 10%.

Finally, the oak tree seed bank was re-set to zero yearly, due to the typical loss of viability during the first year of the seed (Hendry and others 1992).

Litter accumulation

The accumulation of litter was a spatially explicit process that took place in the cells occupied by a mature pine tree as well as in their surrounding eight cells (Moore neighbourhood). The litter content increased with an annual litter accumulation rate (Table 1), which was reduced to 20% of its value if the pines

were not yet mature. The value obtained was the litter accumulation rate in the cell that was occupied by a pine tree, while the eight neighbours of this cell received 50% of this value. In the model, each year, part of the litter was degraded (40%), so that for a monospecific plantation of pine, a maximum litter depth (6 cm) was reached 20-30 years after pine plantation. All the litter values were based on field observations by experts.

Transition rules: plant colonization and mortality

The colonization of an empty cell was defined as a stochastic process that depended on the probability of establishment, ProbC, defined as: 𝑃𝑟𝑜𝑏𝐶 " = 𝑃𝑟𝑜𝑏𝑆 " * 𝑃𝑟𝑜𝑏𝐿 " for each species i (i=1-3). ProbSi depended on the number of available seeds and establishment capacity of species i and ProbLi depended on the microsite conditions, as represented by litter depth.

Given the fact that the habitat conditions were equally suitable for all three species, the probability of establishment ProbSi(x) of species i in a cell x was defined as a function of the seed number in the cell, Nseedsi(x), following Cannas and others (2003): )) . Ei represented the number of seeds that under optimal conditions would guarantee the dominance of the species i in a cell. The values of Ei for the different species represented a competition factor for the seedlings, which considering the differences in seed size between species, was approximated to differ by a factor of 10 between the different species. This number was set to 2 for the oak trees, 10 for the pines, 100 for the shrubs (i=2, 10, 100). For the oak tree, this value was established at 2 rather than 1, because the latter would lead to an establishment probability of almost 100%. The relations between the number of available seeds in a cell and the ProbSi for each species are shown in Fig. 2.

𝑃𝑟𝑜𝑏𝑆(𝑥) = 1 -41 - ! # ! 5 $%&&'% ! (
Given the starting point of the system represented a pine plantation, the probability of establishment ProbLi in an empty cell was expressed as a function of litter depth, as we assumed that the increasing litter thickness over time would favour the relative dominance of the late successional species and, at the same time, inhibit the colonization of the early successional species (Fig. 3; please see the equations in the appendix). More specifically, the effect of litter thickness was defined as depending on seed size and thus on species regeneration strategy and successional stage. These assumptions were based on the following arguments: i) bigger seeds typically do not present dormancy, whereas smaller seeds do and the breaking of this dormancy require fluctuations in temperature that do not occur when the litter layer is thicker than 1 cm; ii) bigger seeds have To decide which species will colonize a certain empty cell, we followed a standard approach to assign species to cells in proportion to the respective establishment probability. The species colonization probabilities in each cell were compared to a random number (r) drawn from a uniform distribution between 0 and 3. If the random number was smaller than the probability of colonization of species 1 (r<ProbC1), the cell was colonized by species 1. Otherwise, if the number was smaller than the sum of the probabilities of species 1 and 2 (ProbC1≤r<ProbC1+ProbC2), species 2 colonized the cell. Species 3 colonized if ProbC1+ProbC2≤r<ProbC1+ProbC2+ProbC3, and otherwise the cell remained empty (Danet 2014).

The annual mortality rate (AMOrate, of each species was defined as one over its life span (Baudena and others 2020).

Fire

Fire disturbance regime was defined stochastically, with the occurrence of fires expressed by an exponential distribution of return times [START_REF] Kampen | Stochastic processes in Physics and Chemistry Stochastic Processes in Physics and Chemistry Revised and enlarged edition[END_REF]Baudena and others 2010). In order to study the response of the system to different fire frequency conditions, we selected three different average fire return times: seven, fifteen and thirty years, plus a scenario without fire. When a fire occurred, the species with resprouting ability (oak tree or facultative shrub species) continued to occupy the same cell, whereas pines and obligate seeder shrubs die. The fire that was simulated was of high severity for which all the needles (crown) and litter (floor) were consumed.

Model simulation settings

The initial conditions of the model were those of a pine plantation that developed for 100 years without fires, until it reached a mature stage. It was assumed that the system was not managed after the initial pine plantation. This simulated extensive pine plantations on old fields and degraded land with low presence of oak trees. In all cases the model was run for 3000 years, with fires occurring after the initial 100 yr. For each fire recurrence regime, ten different fire series were used in the model experiments and each set of conditions was repeated 20 times to account for the stochasticity of the model.

The model was initialized with a range of different initial conditions (e.g., variable initial pine density, number of shrub seeds and variable annual acorn input; not shown). After learning that the model was mostly sensitive to the variation in yearly acorn input, the initial conditions for the model runs were then selected as follows: initial pine plantation interval: 4 cells between pines; 100 shrub seeds per cell (produced on site during the early development of the pine plantation), number of oak seeds (acorns) across the plot given by the annual input, which, to obtain a broad spectrum, was simulated at 1, 5, 50 and 200 seeds.

The differences in the time at which oak trees reached relative dominance (more than 50% of cover of the cells in the lattice) in the communities with either obligate seeder or facultative shrub species were recorded. This was done separately for each combination of fire frequency, fire severity and values of yearly acorn input.

Results

In the absence of fire, the system attained a stochastically stable coexistence of the three plant types at steady state. This equilibrium was reached after about 500-1000 years from the initial pine plantation state and included predominantly oak trees (~75%) with co-existing pines (~20%) and both shrub types (<5%) (Fig. 4A-B).

The shifts in the relative dominance of each plant functional type over time relate to the respective lifespan: during the first decades the short lived, early successional shrub species dominated (about ~100 years at most after plantation), then the intermediate lived species (pine) dominated, and finally the long lived, late-successional species (oak tree) dominated (at ~250 years). The increase of the oak tree population was slow, but steady. In the absence of fire, neither the time when the equilibrium occurs nor the species that is dominant at the equilibrium (oak tree) were sensitive to changes in the values of the initial conditions.

The relative dominance of oak trees at steady state (i.e., cover values higher than 50%) was maintained under all recurrence intervals of high-severity fires (Fig. 4C-F). The coexistence of all three functional types, however, was not observed when fires were simulated, since pines went extinct in all fire regimes, because of a combination of seed bank depletion and a reduction in empty sites available for pine establishment. Under high fire frequency conditions, obligate seeder species were also eradicated from the system (average fire return time of 7 years; Fig. 4H). Nevertheless, when the facultative shrub species was included in the simulations, a long-term co-existence of shrub and oak trees was reached under all fire disturbance regimes (Fig. 4C,E,G). The time at which pine trees were eradicated from the system depended exclusively on the fire return time (Fig.

4C,E,G). Pine cover was eradicated (0% of cover) fastest at the highest fire frequency, namely we observe eradication times of about 40, 130 and 265 years, for fire frequency of 7, 15 and 30 years, respectively. These values did not change for different values of oak trees seed input or regeneration strategy of the shrub.

However, the time at which oak trees reached dominance was not only dependent on fire frequency, but also on the resprouting capacity of the shrub (Fig 4C -H). In particular, high fire frequency accelerated oak tree dominance when the shrub was an obligate seeder but delayed it when the shrub had resprouting ability (facultative shrub species; Fig. 4C-H). This result was observed for all the input rates of oak tree seeds. However, oak tree dominance was delayed substantially (up to 550 years) when acorn input rates were very low

(1 seed.year -1 , Fig. 5).

Thus, the time at which oak trees reached dominance was shorter in communities with the obligate shrub species than in those with the facultative shrub species for all the three fire frequency regimes, whereas no difference was observed in the absence of fire (as expected).

Discussion

We evaluated the role of plant characteristics, namely post-fire regeneration strategies of fire prone shrubs in influencing successional processes. Our model results indicated that the period of dominance of shrubs after fire is mostly dependent on their post-fire resprouting capacity, with a delay in succession caused by the resprouting capacity of the shrubs. This was due to spatial competition between species since a cell that is occupied by a resprouter shrub remained occupied after a fire, while a cell that was occupied by an obligate seeder was empty after a fire. Field studies also suggested that the post-fire recovery of oak forests could be slow, with shrubland communities dominating in the first decades (Baeza and others 2007;Alvarez and others 2009). In short, we found that the facultative strategy (which regenerates both by seeds and resprouting) could delay succession for a considerable amount of time, in the order of centuries. This would likely lead to notable degradation, with increased erosion risk, reduced biodiversity, soil fertility, and potential for C sequestration (Mayor and others 2016; Van del Elsen and others 2020) and could be enhanced by climate change and aridity (Batllori andothers 2017, 2019). In this context, the increase in the time of dominance of facultative shrub species that was observed in our model, highlights the importance of assessing the resprouter capacity of Mediterranean shrubs in response to recurrent fires.

In the absence of fire, our results showed a stable coexistence between shrubs, pines and oak trees. The time of species relative dominance related to their life span, in the sense that short lived species dominated earlier in the succession, whereas long lived species dominate later on, in agreement with the theory of initial floristic model of succession [START_REF] Egler | Vegetation science concepts I Initial floristic composition a factor in old-field vegetation development with 2 figs[END_REF]. The relative dominance of late successional oak tree, such as Quercus robur, in the Iberian Peninsula during the last ten thousand years was confirmed by paleobotanical records (Alcalde and others 2006). These records also suggested a long presence of Pinus pinaster in the Iberian Peninsula, prior to their widespread plantation by humans.

Furthermore, sporadic fires might be favourable to pine communities, by creating open areas for pine colonization (López-Sáez and others 2010). Thus, the prevailing vegetation before intensive human impacts in the landscape probably consisted of a mixed pine-oak woodland and not of the typical climax vegetation suggested by the phytosociological model of Rivas and Martinez (1987), in which the tree layer was exclusively composed of oak species (Alcalde and others 2006; López-Sáez and others 2010). As expected, in the absence of fire, no differences between different shrub strategies were found since for modelling purposes only differences in post-fire regeneration strategy were considered. Previous model studies confirmed that in the absence of fire, the vegetation was dominated by early successional species, mainly Pinus spp. and with the passage of time this vegetation became dominated by later successional tree species (Quercus spp.).

However, when early successional communities were affected by recurrent fires, plant succession can be arrested or delayed through a positive flammability-fire feedback loop, hence hampering fire resilience (Baudena and others 2020). A single fire is sometimes enough to change Pinus spp. forests into alternative stable states dominated by shrub communities. This trajectory deviation is more likely under high fire frequency regimes where the vegetation changes to dwarf shrubs and herbs (Santana andothers, 2010, 2014). In this line, post-fire recovery is expected to be faster in communities that are already dominated by oak trees before the fire than in communities that are dominated by pine or shrubs (Calvo and others 2003).

In our model, we observed the eradication of pines as a result of high frequency of severe fire. In fact, pine was eradicated at relatively low fire frequencies (30 years average fire return) as a result of some fire events occurring within 10 years after each other, because of the stochastic fire return time. This was caused by a combination of the depletion in the pine seed bank and by a reduction of empty sites available for post-fire pine establishment (competition). We expected that the eradication of pines would only occur at fire recurrence intervals shorter than the age of maturity of the pines, i.e., 10 years (Eugenio and others 2006), however, the stochastic variations in fire return time that were simulated in the model (with a possibility for events of short fire recurrence intervals than the average frequency that is observed) can also be observed in nature.

According to our model results, oak trees also reached dominance under high fire frequency. In particular, oak trees were dominant at equilibrium in all the scenarios of fire disturbance, and this final outcome was not sensitive to changes in other model parameters, such as low acorn availability. These results agree with previous works (Baudena and others, 2020) that found oak tree dominance in the long-term independently of the regime of fire occurrence. This pattern can be explained by the very high resprouting ability and long-life span of oak trees.

Conversely, the other species tend to lose dominance over time, either because of having a short life span (shrubs) or a regeneration strategy that depends on local seed banks (pine and obligate seeder shrubs). Our results also agree well with the initial floristic model of succession [START_REF] Egler | Vegetation science concepts I Initial floristic composition a factor in old-field vegetation development with 2 figs[END_REF], according to which postfire conditions tend to attain a similar state of equilibrium than the one that would be achieved in the absence of fire [START_REF] Trabaud | Natural and prescribed fire: survival strategies of plants and equilibrium in Mediterranean ecosystems in Plant response to stress[END_REF]. Furthermore, previous field studies suggested that oak tree species generally resprout rapidly and vigorously after fire under a wide set of conditions (Espelta andothers 2003, Pausas 1997).

Similar results were found under a frequent fire regime (Lloret and others 2003;Konstantinidis and others 2005), even after a period as short as three years after the last fire (Delitti and others 2005). These studies concerned forests that were already dominated by oak tree species, so that colonisation by oak tree species was not a limiting factor. In many instances, however, oak tree seed sources are distant, and there are few oak stands in the region, leading to very low acorn inputs from the surrounding areas, hence absolutely delaying the post-fire succession of pine forests (Acacio and others 2010; Urbieta and others 2010).

Unfavourable environmental conditions for the regeneration of oak tree species, such as steep slopes and cold or dry sites have been previously linked to the persistence of pine populations, however such conditions were not simulated in our model (López-Sáez and others 2010). We have found that oak tree dominance under optimal conditions for oak establishment was accelerated by a higher yearly input of acorns, as expected. Previous research, however, has shown that the relative abundance of oak tree species depends strongly on their colonization potential and on the establishment success of oak seedlings [START_REF] Sheffer | A review of the development of Mediterranean pine-oak ecosystems after land abandonment and afforestation: are they novel ecosystems?[END_REF]. Our model showed that a very small initial oak tree population and a small but steady yearly supply of 1 or 2 acorns per hectare could lead to oak tree dominance within 200 years, at least in the absence of fire. This outcome was altered by frequent fire regimes, which led to a delay in oak tree dominance of a few centuries in cases of very low acorn supply (1 acorn per hectare per year). At yearly acorn supply values of 50 per hectare, frequent fire regimes no longer delayed oak tree dominance. In the field, acorn inputs strongly depend on the distance from seed sources, e.g., on the presence and distribution of mature oak trees in the landscape. Since a low seed input has shown to influence the speed of oak tree dominance, we can expect that, understanding and manipulating the potential and effective dispersal of oak trees to the area can increase the presence of oak trees in the landscape. To do this, the promotion of acorn dispersers, such as the jay (Garrulus glandarius L.) could be considered (Ouden and others 2005). In this context, it is important to note that the type of plant community species dominance can interact with the colonization capacity of oak trees, as pine stands foster seed arrival, whereas shrublands are usually avoided by the jay because open areas usually lead to a higher exposure to predators [START_REF] Pons | Oak regeneration in heterogeneous landscapes: the case of fragmented Quercus suber forests in the eastern Iberian Peninsula[END_REF]. These mechanisms could inhibit oak tree colonization in highly dense shrublands, which could, in turn, lock the system in an early successional phase, especially when pines are eradicated from the system. This would agree well with the findings of Acacio and others (2007) who found seed arrival to be one of the limitations of oak tree establishment in shrublands.

Another factor that can lead to a decrease in oak tree numbers after a fire is The model presented here assumed resprouting behaviour of the main shrub species and the oak trees as a binomial feature, i.e., a species either does or does not resprout after fire. However, it is presently known that post fire resprouting capacity is actually a continuum, in terms of both the individual and the community response to a disturbance (e.g. fire or herbivory) (Moreira andothers, 2012, Nicholson andothers 2017). In spite of the high relative abundance of resprouting species in several ecosystems around the globe and on their tendency to become numerous in less productive sites, a focus on the role of resprouters in community dynamics has been underrepresented in previous modelling and successional studies [START_REF] Midgley | Why the world's vegetation is not totally dominated by resprouting plants; because resprouters are shorter than reseeders[END_REF][START_REF] Bond | Ecology of sprouting in woody plants: the persistence niche[END_REF].

The plantation of extensive areas with pines in the Iberian Peninsula did not only target wood production interests, but also aimed to foster ecological succession, with pines as a pioneer species promoting the subsequent colonization by more resource-demanding late successional species (Zavala and others 2000).

However, several studies have shown that, pine stands have largely failed to harbour late successional species, possibly because of their high planting densities [START_REF] Maestre | Are Pinus halepensis plantations useful as a restoration tool in semiarid Mediterranean areas?[END_REF]Gavinet and others 2015). In this context, the use of mixed pine plantations including late successional species has been proposed to increase the resilience of pine forests to frequent wildfires as well as to foster and accelerate succession (Pausas and others 2004;Vallejo and others 2009;Santana and others 2018). Our model results suggest that the composition of the understory of pine stands should be considered, in particular regarding the resprouting capacity of fire-prone shrubs, as it can play an important role in constraining successional processes after pine has been eradicated from the system. Further research on the post-fire competitive effect of other facultative species with invasive behaviour in Portugal, such as acacia (Acacia spp.) and Hakea sericea Schrader is needed since, according to our results, their potential to delay the establishment of oak tree populations could be enhanced by their regeneration strategy.

Conclusion

Our model indicated that the final succession state of pine-oak tree-shrub ecosystems is not influenced by fire frequency. The steady state dominated by oak trees is nearly insensitive to differences in initial model conditions. However, the time until oak tree dominance was reached was strongly delayed by the postfire resprouting ability of understorey shrub species. Our results showed the importance of considering the resprouting ability of understorey shrubs in the assessment and management of pine forests that are subject to frequent fires, as a high post-fire resprouting capacity could inhibit plant succession for several centuries, especially under low levels of acorn yearly input, which could, in turn, lead to extensive post-fire erosion and degradation.

o

  Oaks were dominant both in the absence of fire and under high fire recurrence o Post-fire regeneration was key, with facultative shrub species delaying succession o Understorey species regeneration type should be considered in post-fire restoration (CASCADE project). Thanks are due to FCT/MCTES for the financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020), through national funds and the post-doctoral research contract of Jacob Keizer (FCT-IF/01465/2015) the Spanish Ministry of Science and Innovation for financial support (CGL2017-89804-R) of the work of Susana Bautista. Post-fire regeneration traits of understorey shrub species modulate successional responses to high severity fire in Mediterranean pine forests Abstract Recurrent fires can impede the spontaneous recruitment capacity of pine forests.

  model considered three plant types (i=1-3), each representing a different functional group with contrasting seed size, seed production and life span. Namely, we modelled pines (i=1), either facultative or obligate seeder shrubs (i=2) and oak tree (i=3). The model species were inspired in Genista spp. (including formerly classified Pterospartum tridentatum (L.) Willk.) and Ulex europaeus L. for the facultative species, in Erica umbellata L., Ulex parviflorus Pourr. and Salvia rosmarinus Schleid. (formerly Rosmarinus officinalis L.) for the obligate seeder species, in Pinus pinaster Ait. for the pine and in Quercus robur L. for the oak tree ( Tavsanoglu and Pausas 2018; Paula and others 2009). The model included additional information concerning the age of the plant cell when occupied and the number of seeds produced per cell, which corresponded to realistic values from literature (Fig. 1). The time steps used were of one year (i.e. dt=1 yr). The simulations were performed by implementing a Matlab R2015b code.

  Fig.3for the relations between litter depth and ProbLi(x) for each functional type.

  resprouting failure, due to factors such as environmental stress, drought or age(Pausas and others 1999b; Baudena and others 2020).Pratt and others (2014) found a high mortality of facultative shrub species as a result of the combined action of frequent fires and post-fire drought. Furthermore, it is expected that resprouter species will have lower resprouting capacity and high mortality in dry areas(Ojeda and others 2005: Pausas and others 2015), which could undermine their dominance. If other factors such as drought were to be analysed, oak tree species might experience a greater reduction in abundance under likely climate change scenarios than pine or shrub species (Torres and others 2016; Batllori and others 2015, 2019; Baudena and others 2020), promoting shifts in species dominance as a result of high fire frequency. To further understand the effects of climate change scenarios on vegetation dynamics, research on the impacts of likely future climate conditions in oak tree establishment success as well as in resprouting capacity of the shrubs is needed (Enright and others 2015).

Acknowledgments

We would like to thank Oscar Gonzalez-Pelayo and Angeles García-Mayor for their comments and suggestions. The authors are grateful to two anonymous reviewers and editors for their comments, which greatly contributed to improve the manuscript.

Funding

This research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under the grant agreement n° 283068


Patrick Martin

Maroua Nouiri

Ali Siadat

Moving Towards a Sustainable Model: Societal, Economic and Environmental

Industry of the future and sustainable development

The industrial transition mentioned in Chapter 1 is accompanied by the consideration of sustainable development constraints (Nouiri et al. 2019a). Indeed, environmental issues, such as the reduction of pollution, carbon dioxide (CO 2 ) emissions, the reduction of raw material resources, biodiversity as well as the control of climate change, are becoming increasingly important. Some authors have even started to build a new paradigm (Industry 5.0), greatly emphasizing ecology and humans [START_REF] Nahavandi | Industry 5.0 -A human-centric solution[END_REF]Région Grand-Est 2020;EU Horizon 2020). Whatever the name, achieving a balance between production of goods, ecological aspects and human factors is a major challenge in the transition to the industry of the future.

Sustainable development is a concept of development that meets the needs of the present without compromising the ability to meet the needs of future generations [START_REF] Wced | World commission on environment and development[END_REF]. A sustainable model must therefore ensure a balance between economic, environmental and social impacts. Figure 2.1 illustrates the three working dimensions, leading to a model consistent with sustainable development. The objective of this chapter is to show how industrial cyber-physical systems (ICPS) have characteristics that contribute to solving the sustainable development challenges presented above. Our approach is thus positioned within the framework of sustainable engineering, defined in recent works as the combination of three interacting environmental, societal and economic dimensions (see Figure 2.1). Therefore, these three aspects applied to ICPS will be addressed consecutively, starting with the societal aspect, and more particularly, focusing on the role and integration of humans in ICPS. [START_REF] Mann | Visualising sustainability[END_REF]

Contribution of ICPS to the social dimension

Background

Humans have always been present in the industrial environment, but their scalability and versatility have not improved productivity and profitability in the face of an exponential increase in demands. Cost reduction and system efficiency optimization are among the main objectives of most industrialists, often to the detriment of a relevant integration of the human in these systems. Numerous studies [START_REF] Futurprod | Les systèmes de production du futur, atelier de réflexion prospective de l'ANR[END_REF][START_REF] Veltz | L'industrie, notre avenir[END_REF][START_REF] Effra | European factory of the future association, Effra vision for a manufacturing partnership in Horizon Europe[END_REF][START_REF] Neumann | Industry 4.0 and the human factor -A systems framework and analysis methodology for successful development[END_REF] thus underline the importance of taking into account the humans in the new challenges related to the industry of the future. New and crucial objectives are emerging, for which human expertise is relevant (Nouiri et al. 2019a): improving system resilience, adapting to disturbances (physical, economic, societal, etc.), taking into account environmental and social constraints, etc. Figure 2.2 repositions the different dimensions of sustainable development presented previously on the impacting elements of an ICPS, as defined in Chapter 2. At the level of social objectives, the presence of humans is plural: observer, supervisor, operator and decision-maker, at the level of the workstation, as well as at the level of design or industrialization managers, in the physical as well as the cyber layer. The constraints specific to humans concern safety (accidents), physical health (musculoskeletal disorders, fatigue, vibrations, dangerous environments, etc.), psychological health (psycho-social risks, stress, cognitive fatigue) and, more generally, well-being at work. In the context of ICPS, technological developments, identified as levers for the deployment of the industry of the future with regard to work flexibility, show an evolution of equipment, manufacturing processes and procedures, and functional and even organizational constraints. Tasks can indeed be performed alternatively by a human, automated equipment, several operators or human-robot cooperation [START_REF] Krüger | Cooperation of human and machines in assembly lines[END_REF][START_REF] Murashov | Working safely with robot workers: Recommendations for the new workplace[END_REF][START_REF] Kousi | Enabling human robot interaction in flexible robotic assembly lines: An augmented reality based software suite[END_REF], depending on the use. Automated industrial systems have made it possible, since the third industrial revolution, to ensure the repetitiveness of tasks, the rate and the constant quality of the manufactured product. Thus, humans can be relieved of tedious, repetitive tasks (physical or decisional), and with their global and contextual vision, adaptability, experience and non-formalized skills, can adapt to various tasks, make decisions adapted to complex situations and face the unknown. Nevertheless, some tasks are difficult to automate: flexible products of small dimensions, fragile, difficult to access. Thus, the interaction, cooperation, and permanent and dynamic coordination between the human and the automated system constitute the paths to be developed within the ICPS (see Figure 2.3) at the level of equipment (mechanics, sensors, communication networks, fixed or mobile robots, exoskeletons), interfaces, decision-making and organization (implementation, planning). Five levels of integration have been identified, from local solutions to the optimization of sustainable production involving humans (see Figure 2.4, EU Horizon (2020)): paper documents, software and siloed data, connectivity, offline optimization, real-time optimization. Within this process of evolution of tools and technologies, ICPS is part of the connectivity between equipment, planning and logistics. The advantages of ICPS in favor of humans will thus be found in the different categories of aspects: the cognitive aspects, where ICPS collaborate with humans for better decision-making or to relieve humans who may be victims of mental overload, and the OHS aspects (occupational health and safety), where the adaptation capacity of ICPS will make it possible to physically relieve humans, while providing them with more advanced interaction conditions and guaranteeing their safety. The rest of this section is dedicated to the description of these two families of aspects.

Cognitive aspects

One of the major interests of ICPS is their ability to adapt to the context and diversity, both in terms of external elements (constraints, objectives, disturbances) and within themselves. Thus, it is expected that the ICPS can adapt to the presence of the human during various decision-making processes. The collaboration between the operator and the ICPS is positioned at the level of decision-making within the physical system (assistance for the accomplishment of a task, individualized training, etc.), at the level of the organization and planning of tasks within this same physical part with the objective of optimizing and eliminating unproductive time, or at the level of monitoring within the cyber part. Flow tension, reconfiguration and sharing the task with artificial intelligence are all parameters that should not be neglected in the evaluation of psycho-social risks engendered in operators, particularly via the stress generated by change. This cooperation leads to the need to identify characteristic parameters and develop new models combining structural, organizational and human points of view.

Chapter 10 of this book discusses the opportunities offered by ICPS to establish a fruitful relationship with the human in these different decision-making processes, in more detail. In this context, the human is then alternatively considered as an "Operator 4.0", or as a constituent part of a cyber-physical human system.

Health and safety aspects at work

The adaptation of ICPS to humans is also at the purely physical level: gender, origin, age, disability and culture are all factors that characterize the operator, which must be taken into account to optimize this relationship and offer assistance adapted to each user, in order to reduce health and safety risks (adaptation in space and in the planning of tasks, identification of weak warning signals).

Several projects have been carried out on work organization, monitoring of muscle fatigue and ergonomics (posture, vibrations, environment: temperature, humidity, noise, etc.), which are aimed at improving working conditions and reducing the workload. Mobile industrial robots are used to reduce the difficulty of tasks and the physical effort required by operators when transferring heavy products, etc. Collaborative robots, "cobots", are increasingly integrated in the industrial environment [START_REF] Julien | L'usine du futur -Stratégies et déploiement : Industrie 4.0, de l'IoT aux jumeaux numériques[END_REF]. Several modes of cooperation thus exist, depending on the types of interactions possible:

-common working area when the robot is stopped (control, finishing operation, etc.); -physical assistance (exoskeleton, third hand); -physical and cognitive cooperation (effort, trajectory, etc.) to meet product quality and precision in the repetitiveness of the task; -presence of the operator in the working area of the robot with stop associated with proximity or contact sensors.

These different types of robots make it possible for the humans to be relieved of heavy loads or very precise tasks, but their use is associated with the acceptability of the operator (permanent presence, physical or psychological constraint). The interfacing between the human and the robot is declined according to two major aspects:

-Sensors: in the industry, presence sensors (light barriers, pressure detection mats, cameras, distance or contact sensors, etc.), effort sensors, fatigue or vigilance sensors are increasingly being developed. In addition, measurements of environmental parameters (brightness, noise, temperature, radiation, dust, etc.) are necessary to prevent harmful effects on health.

-Interaction: this is based on interfaces that enable operators to interact with their environment (touch screens, keyboards, tablets, joysticks, etc.), to have assistance interfaces for a better knowledge of their environment (virtual and augmented reality, haptic interfaces, visualization of the state of the product, the process, the production to which they cannot have access, simulation of an operation to help its realization, etc.) and to receive real-time feedback on processing and decision-making (connected watch, tablets, etc.). However, this can only be achieved if the integration of the human in the ICPS is made in such a way that the problems related to the exchange of information between the digital and human worlds are handled in an intelligent way, taking into account the specificities and constraints of both worlds. The "shell administration" concept of the BASE architecture clearly illustrates this aspect [START_REF] Sparrow | An architecture to facilitate the integration of human workers in Industry 4.0 environments[END_REF]). Finally, it should be noted that interaction is the basis for the cooperation mechanisms in ICPS, which are specifically studied in Chapter 10 of this book.

If many hopes are placed in the technological offer to improve working conditions, it is essential for designers to make a precise assessment of the risks they present, by endeavoring to identify those that are new, accentuated or more difficult to control. Particular attention must be paid to technologies that aim to "increase" the physical or cognitive capacities of operators (exoskeletons, physical assistance robots, augmented reality, artificial intelligence). The boundary is indeed imprecise and subject to discussion between a use that makes it possible to preserve health and safety at work and one that would, on the contrary, have negative effects because it would be primarily aimed at working faster, carrying more loads, standardizing work, etc. The opening of industrial equipment control systems to the Internet can also, in the presence of viruses, affect the operation of installations and consequently be more or less directly a cause of accidents for employees (see Chapter 6).

Safety at work

The accident is directly associated with the simultaneous presence of the operator and a potentially dangerous object at the workstation. The identification of dangerous situations, and thus prevention, therefore requires investigation of:

-scheduling of tasks, including those of the operator; -identification of characteristic design parameters related to risk qualification; -quantification of risks and their exploitation in order to help the designer in their activities of safe design of work situations.

In this sense, the concept of Design for Safety recommends the improvement of knowledge sharing between the different trades, with a strong involvement of the health and safety expert as early as possible in the design process. This has been the subject of numerous works [START_REF] Fadier | Safety design: Towards a new philosophy[END_REF][START_REF] Shahrokhi | A framework to develop an analysis agent for evaluating human performance in manufacturing systems[END_REF][START_REF] Houssin | An approach to solve contradiction problems for the safety integration in innovative design process[END_REF]. The analysis of all of these methods, techniques and design tools made it possible to produce the findings synthesized by [START_REF] De Galvez | EZID: A new approach to hazard identification during the design process by analysing energy transfers[END_REF] and [START_REF] Jafari-Sadeghi | Level of education and knowledge, foresight competency and international entrepreneurship: A study of human capital determinants in the European countries[END_REF]. In order to identify hazardous phenomena as early as possible during the design process, it is first necessary to identify the different functional elements constituting a production system. The significant parameters (energy and volume of influence) related to potential risks can be associated with each element. In these definitions, the operator is at the same level as functional modules and can perform most of these operations. The association of functional elements able to perform a task constitutes a workstation. A production cell is a set of workstations. Figure 2.5 illustrates the typology of the different elements making up a production cell in the manufacturing field.

Each module has mechanical, physical, electronic or software elements that ensure physical, quality and functionality control, and decision actions. The operator also has the same functionalities. The interaction, at a given moment between the modules and the operator(s), generates actions that can lead to dangerous phenomena. The granulometry is chosen by the designer, taking into account their objective (organization link, space management, use, etc.), knowledge of the system state and accuracy of analysis sought. It thus plays a decisive role in monitoring hazardous phenomena and their level of severity according to the modifications made to the production system.

The strong assumption for the analysis of the production system to identify and quantify the hazardous elements for health and safety is that the hazardous phenomena are related to the presence of energy. These energy flow parameters can be divided into two families: the main energy parameters that characterize a generalized energy flow (technological description of the way in which this flow circulates: mechanical, electrical, thermal, chemical/biological, radiation) and the complementary parameters (shape, material, surface condition, trajectory). The accident is linked to the presence of the operator in the space occupied at a given moment by the dangerous object. This dangerous object can potentially appear at the level of the task carried out (cutting tool, etc.) or in the machine, released at the time of the task in a voluntary way or not (potential mechanical energy, fluid under pressure, pollutant, etc.). The hazardous area (geometry) is defined by the spaces occupied at each stage studied (sequence of static images) by the zones of influence of the equipment and the operator (simplified modeling) (see Figure 2.6).

The quantification of the severity is carried out by analyzing the standards associated (INRS 2006;[START_REF] Iso | Robots and robotic devices -Collaborative robots[END_REF]INRS 2017;[START_REF] Inrs | Valeurs limites d'exposition au bruit et port de protecteurs individuels[END_REF] with each type of energy identified. From this information, the maximum energy value to which the worker is exposed is usually classified on a severity level scale [START_REF] Gomez Echeverri | Prise en compte dans la conception et l'exploitation des postes de travail de l'usine du futur des aspects sante -securité. 16ème colloque national S-mart[END_REF]. This information allows the designer to choose a technical or organizational solution so as to eliminate severe and very severe cases.

In the framework of ICPS, advanced strategies of collaboration within the physical parts, in particular through a relevant use of multi-agent or holonic systems (see Chapters 7 and 8), can propose, for example, a set of cooperative solutions, making it possible to complete the design solutions by a dynamic management of the working areas between the various controlled elements and the humans.

Health at work

Occupational health is an important aspect of a company's sustainable development. There are many standards, structures and committees that ensure this aspect. Beyond these regulatory aspects, there are possible actions to be carried out within the ICPS itself that contribute to guaranteeing it: scheduling of tasks under ergonomic constraints, taking fatigue into account in activities, optimizing preventive maintenance operations, etc. The study of the margins of maneuver illustrates the first action. For several years now, the ergonomics community has considered the margins of maneuver as a means of preventing musculoskeletal disorders (MSDs) and psychosocial risks, as well as a condition for keeping senior or disabled operators at work. Designing a system with room for maneuver therefore means giving it a certain "plasticity", to enable operators to manage variability without jeopardizing their health, by developing new practices and reinventing their uses, and to enable a dynamic work activity. Thus, Lean Manufacturing (operational excellence), whose objective is to eliminate non-value-added activities in order to improve the company's performance, is becoming the subject of questioning, particularly in terms of employees' working conditions. It is necessary to develop tools for the "monitoring" or "surveillance" of operator solicitations during the production phase, in order to predict "drifts" that lead to work situations or states that will cause disorders or fatigue. The margins of maneuver (see Figure 2.7) is defined as the possibility or freedom available to a worker to develop different ways of working, in order to meet production requirements, without adverse effects on their health. [START_REF] Lanfranchi | Explicative models of musculoskeletal disorders (MSD): From biomechanical and psychosocial factors to clinical analysis of ergonomics[END_REF] We consider that it is possible to reduce the organizational and spatial margins of maneuver to temporal margins. Thus, thanks to simulation, the effects of variability disrupting production, as well as the effects of these temporal margins left to the operator, could then be studied from the dual point of view of occupational health and safety and system performance: beyond a certain threshold of "flow tension" or "organizational rigidity", it is likely that the system is no longer capable of absorbing variability, and that the operators are no longer able to operate the regulations necessary to maintain performance under good conditions. As an illustration, this point has been studied for an ICPS purpose by El Mouayni et al.

(2017) and focused on the simulation of "operator" variability implemented in a multi-agent model (see Figure 2.8) by studying the following points:

-parameterization of the fatigue model; -parameterization of the learning model; -error model parameterization: HEART (human error assessment and reduction technique) method.

Contribution of ICPS to the environmental dimension

Objectives and expectations

The consideration of the environmental impact must be ensured from the design phase and throughout the lifecycle of systems. A typical approach is to carry out a lifecycle assessment (LCA) of the production systems and products made within the ICPS [START_REF] Ballarino | The CPS and LCA modelling: An integrated approach in the environmental sustainability perspective[END_REF]) and verify the sustainability of the ICPS themselves, due to the intensive use of digital technologies in particular. This type of study typically leads to the use of bio-sourced materials as raw materials or recycled materials with less environmental impact [START_REF] Kovarik | Carbon neutral buildings and recycled materials: How cities want to solve the challenge. Royal commission for Riyadh city in the Kingdom of Saudi Arabia[END_REF][START_REF] Carrodeguas | High elasticity, chemically recyclable, thermoplastics from bio-based monomers: Carbon dioxide, limonene oxide and ε-decalactone[END_REF]. Reverse logistics is also developing. It is based on the use of reusable materials and packaging to reduce the environmental footprint [START_REF] Ruel | Pratiques de logistique inverse au sein d'une coopérative : une motivation environnementale ?[END_REF]. Sustainable production strategies are also being developed, such as mass customization. This type of strategy aims to produce goods and services to meet the needs of each customer while ensuring effective and efficient productivity. Thus, the customer is involved in the design phase of the product. Product customization implies a specified production that best satisfies the customer's needs, thus guaranteeing an increase in the product's lifespan.

State organizations can also participate in the sustainable transition by imposing certain binding regional policies (variation of the cost of carbon, taxes, penalties for exceeding an energy or pollution threshold).

Thanks to the use of information and communication technologies (ICTs), everything within the ICPS becomes communicative: consumers, logistics operators, goods producers, energy producers, etc. This communication encourages interaction and negotiation for the local benefit of each ICPS and thus optimizes the global gain.

The concept of ICPS is relevant to reduce environmental impacts within the industrial environment (subject to its LCA, as mentioned previously). Indeed, the cyber layer makes it possible to retrieve data in real time and extract useful information in the environmental component. For example, a major advantage of ICPS is that they can be designed to use real-time information to reduce local energy consumption, manage waste or collaborate with other ICPS to optimize global energy and raw material consumption. The intelligence built into ICPS also allows them to react dynamically to internal energy constraints (exceeding an expected energy threshold) or external constraints (variation in the availability of renewable energy). The ICPS management system can thus integrate new performance indicators relating to environmental effectiveness and efficiency. These indicators will be used to quantify an estimate of the impact on the environment (energy, waste, pollutants, greenhouse gases, etc.) during the predictive phase and monitor their evolution in real time. [START_REF] Mazumder | A review of current research trends in power-electronic innovations in cyber-physical systems[END_REF] presented research books related to power electronic innovations in cyber-physical systems (CPS), more precisely new energy distribution architectures, protection techniques taking into account a wide integration of renewable energies in smart grids, simultaneous transmission of energy and information, etc. [START_REF] Nouiri | Towards energy efficient scheduling of manufacturing systems through collaboration between cyber physical production and energy systems[END_REF] proposed a multi-agent architecture named EasySched, based on the collaboration between goods producers (energy consumers) and renewable energy producers. Two types of ICPS are considered in this example: cyber-physical production systems (CPPS) and cyber-physical energy supply systems (CPES). As illustrated in Figure 2.9, the Industrial Internet of Things (IIoT) enables communication between CPPS and CPES. External communication enables the coordination and control of the energy consumption of the connected plants and the availability of renewable energy.

Example of application

Renewable energy production is difficult to predict, as it is highly dependent on uncontrollable conditions (e.g. weather conditions). A disturbance related to the decrease in renewable energy availability is communicated and broadcasted to the connected plants, which then cooperate with the CPPS in order to respect this constraint. Rescheduling techniques are then executed to react quickly to this disturbance. The originality of this architecture lies in the fact that the scheduling is performed taking into account the production needs and the dynamic level of available renewable energy.

Contribution of ICPS to the economic dimension

Because of their ability to adapt quickly (to markets, hazards, urgent requests, etc.), optimize (scheduling, planning) and integrate the various information systems, ICPS clearly contribute to the economic dimension of companies. Because of their ability to process large masses of data at the cyber level, they also allow for the implementation of mechanisms to optimize the various "assets" of companies, in particular by optimizing maintenance processes (predictive, opportunistic, etc.), and to monitor the life of the various fleets of equipment, machines, tools, etc. via IIoT technologies, for example.

However, the transition to a sustainable model also implies optimizing the overall economic gain, in the longer term, beyond compliance with classic short-term financial constraints (turnover, market share, profit, margin, etc.). Typically, taking into account environmental constraints, a priori restrictive, can then be a source of long-term gain. For example, the use of recycled materials aims to reduce production costs, the impact on the use of non-renewable resources and the generation of non-valuable waste. In this context, the ICPS, capable of fine and global control of a production, can help to monitor the impact of the integration of these elements in the products and processes.

Reverse logistics or the implementation of dismantling channels is also an illustrative example of this global vision and is a major issue for the future [START_REF] Tolio | Design, management and control of demanufacturing and remanufacturing systems[END_REF]. In particular, dismantling aims to break down a product into homogeneous components, parts and materials, thus making it possible to meet the requirements of reuse or treatment at the end of life. It includes different phases: disassembly and size reduction, sorting and separation, recycling, inspection, cleaning, repackaging and logistics (see Figure 2.10). Within these phases, digital technologies associated with the Industry of the Future are present, particularly in terms of online and offline data collection, knowledge capitalization and feedback to the operator (AR headset, haptic interface). With the cyber dimension, ICPS can thus facilitate the interconnection between the various logistics chains and the information systems of the players to contribute to this global financial optimization. [START_REF] Hu | Analyse des aspects santé-sécurité lors du démantèlement/de-manufacturing[END_REF] In another area, the reduction of internal transport costs thanks to ICPS would be possible by setting up horizontal collaboration between ICPS, for example, thanks to fleets of mobile transport robots. Just-in-time or just-in-sequence delivery of components would reduce the cost of storage in warehouses, both intra-and inter-site, which is often variable. Smart management of logistics within ICPS makes it possible to not only react to disruptions (increased demands, closure of a distribution platform, etc.) but also reduce expenses related to internal and external transport and storage costs. Optimizing the filling of trucks and efficient communication within the fleet would help to minimize the overall transport costs (see Chapter 12).

The benefits in terms of health and safety and well-being at work also have a significant economic impact, only if the production resource capacity is available, through their day-to-day efficiency or the reduction of costs incurred by accidents or illnesses at work. Here again, the ICPS can contribute through their ability to capitalize on the events that have occurred and link them together to analyze the root events that cause incidents, accidents, work stoppages, etc.

Conclusion

In this chapter, the main challenges of the industrial transition towards a sustainable model were presented. The three pillars of sustainable development (environmental, social, economic) were put into perspective with the evolutions brought by ICPS, which make it possible to respond to these new challenges efficiently. A particular focus was given to the importance of the cyber layer to collect and process data from the physical layer, in order to make decisions that are increasingly in line with sustainable development. This decision-making is generally performed in the framework of a collaboration between the ICPS and the human decision-maker.

However, the digitalization of the industry is still handicapped by factors related to the adaptability of the human to accept these changes, train technologically (increase in skills, use of digital technologies) without forgetting the risk of quality degradation due to the diversification of human tasks, and the challenges of cybersecurity.

Figure 2 . 1 .

 21 Figure 2.1. The three dimensions of sustainable development[START_REF] Mann | Visualising sustainability[END_REF]

Figure 2 . 2 .

 22 Figure 2.2. Positioning of humans within the ICPS

Figure 2 . 3 .

 23 Figure 2.3. Respective human-robot advantages (Thomas Project 2014)

Figure 2 . 5 .

 25 Figure 2.5. Typology of elements constituting production cell (Gomez Echeverri et al. 2019)

Figure 2 . 6 .

 26 Figure 2.6. CAD modeling of influence volumes (Gomez Echeverri et al. 2019)

Figure 2 . 7 .

 27 Figure 2.7. Margins of maneuver[START_REF] Lanfranchi | Explicative models of musculoskeletal disorders (MSD): From biomechanical and psychosocial factors to clinical analysis of ergonomics[END_REF]

Figure 2 . 8 .

 28 Figure 2.8. Simulation of the times of maneuvering margins (El Mouayni et al. 2017)

Figure 2 . 9 .

 29 Figure 2.9. EasySched: a multi-agent architecture for predictive and reactive scheduling of goods production systems based on available renewable energy in an Industry 4.0 context (Nouiri et al. 2019b)

Figure 2 . 10 .

 210 Figure 2.10. Modeling the dismantling process[START_REF] Hu | Analyse des aspects santé-sécurité lors du démantèlement/de-manufacturing[END_REF]