Abstract
The ecological impacts of forest plantations are a focus of intense debate, from studies 2 that consider plantations as "biological deserts" to studies showing positive effects on plant 3 diversity and dynamics. This lack of consensus might be influenced by the scarcity of studies 4 that examine how the ecological characteristics of plantations vary along abiotic and biotic 5 gradients. Here we conducted a large-scale assessment of plant regeneration and diversity in 6 plantations of southern Spain. Tree seedling and sapling density, plant species richness, and 7 Shannon's (H') diversity index were analysed in 442 pine plantation plots covering a wide 8 gradient of climatic conditions, stand density, and distance to natural forests that act as seed 9
Pronounced variation in regeneration and diversity was found in plantation understoreys 11 along the gradients explored. Low-mid altitude plantations showed a diverse and abundant 12 seedling bank dominated by Quercus ilex, whereas high-altitude plantations showed a virtually 13 monospecific seeding bank of Pinus sylvestris. Regeneration was null in plantations with stand 14 densities exceeding 1500 pines/ha. Moderate plantation densities (500-1000 pines/ha) promoted 15 recruitment in comparison to low or null canopy cover, suggesting the existence of facilitative 16 interactions. Quercus ilex recruitment diminished exponentially with distance to the nearest Q. 17 ilex forest. Richness and H' index values showed a hump-shaped distribution along the 18 altitudinal and radiation gradients, and decreased monotonically along the stand density gradient. 19 From a management perspective, different strategies will be necessary depending on 20 where a plantation lies along the gradients explored. Active management will be required in 21 high-density plantations with arrested succession and low diversity. Thinning could redirect 22 plantations towards more natural densities where facilitation predominates. Passive management 23 might be recommended for low-moderate density plantations with active successional dynamics 1 (e.g., towards oak or pine-oak forests at low-mid altitudes). Enrichment planting will be required 2 to overcome seed limitation, especially in plantations far from natural forests. We conclude that 3 plantations should be perceived as dynamic systems where successional trajectories and diversity 4 levels are determined by abiotic constraints, complex balances of competitive and facilitative 5 interactions, the spatial configuration of native seed sources, and species life-history traits. 6 7
INTRODUCTION 12
Humans play a key role in shaping the structure and abundance of most ecosystems 13 around the world (Sanderson et al. 2002 , Haberl et al. 2007 ). The significance of the human 14 footprint has been formally recognized in the term "emerging ecosystems", defined as 15 ecosystems where species occur in combinations and relative abundances that have not occurred 16 previously within a given biome and that are the result of deliberate or inadvertent human action 17 (sensu Hobbs et al. 2006 ). An example of this type of novel or emerging ecosystems are forest 18 plantations (Chazdon 2008) , usually characterized by higher stand density, lower tree diversity, 19 and different specific composition than in natural forests (Hartley 2002 , FAO 2005 . The area 20 covered by forest plantations has increased dramatically in recent decades, currently representing 21 approximately 140 million ha worldwide (FAO 2005) . Although only a 22% of this area has a 22 primarily protective function (i.e., conservation of soil, water and biodiversity), the importance 23
In fact, most pine saplings appeared in plantations with extremely high (> 2000 pines/ha) canopy 1 densities. 2
Our analyses of tree seedling and sapling density in plantations estimated three terms: 1) 3 average potential regeneration (PotReg, in number of individuals per 5-m radius plot), and three 4 sets of scalar modifiers ranging from 0 to 1 that quantify the effects on average potential 5 regeneration of 2) local climatic conditions (expressed in terms of altitude and annual radiation), 6
3) stand density (number of pines per ha), and 4) distance (in m) to the nearest seed source. This 7 last scalar was considered only for analyses of Q. ilex seedlings and saplings, since seedlings of 8 pine species never appeared in plots without conspecifics in the canopy (i.e., distance to seed 9 sources equalled zero in all cases). Our full model has the following form: 10 Regeneration = PotReg x Climatic effect x Density effect x Distance effect (1) 11
Potential regeneration (PotReg) that control the breadth of the function (i.e., the variance of the normal distribution). Equation 2 18 produces the classic Gaussian distribution of species performance along an environmental axis 19 usually assumed to describe vegetation-environment relationships (e.g., Curtis 1959 , Whittaker 20 1975, Gauch 1982) , but can also produce sigmoidal, monotonic curves within restricted ranges of 21 where X3 0 represents the pine density (pines/ha) at which maximum seedling/sapling density 5 occurs, and X3 b controls the breadth of the function. The density effect was also tested using pine 6 basal area instead of density as predictor, but in no case were the models a better fit (data not 7 shown). 8 We also tested a variant of the Eq. 3 in which the density effect was allowed to vary as a 9 function of the climatic conditions of the plot. This effect is independent of the underlying direct 10 effect of climate on potential regeneration (i.e., the climatic effect). For this, the mode term (X3 0 ) 11 in Eq. 3 was allowed to vary as a function of climatic variables (either altitude or annual 12 radiation): 13 seedling/sapling density is reached at lower pine densities with increasing altitude or radiation. 17 We tested two alternative forms to model the distance effect: a Weibull dispersal function 18 (the most used in previous studies; see Ribbens et al. 1994 , Clark et al. 1998 , LePage et al. 2000 ) 19 and a lognormal dispersal function (suggested by Greene et al. 2004 to fit empirical data as well 20 as or better than Weibull functions). However, because the lognormal function was in no case abetter fit to the data than the Weibull function (results not shown for simplicity), we selected the 1
Weibull dispersal kernel to model the distance effect. The Weibull function has the form: 2 Distance effect = exp (-α * Distance
where α controls the rate of decrease of seedling/sapling density with distance, and β controls the 4 shape of the function. 5
Diversity models.-We conducted separate analyses for two different diversity indexes: 6 species richness (or species number) and the Shannon's (H') diversity index (a more complex 7 index that combines species richness and relative abundance), both calculated at the 10-m radius 8 plot scale. Models were run for the two indexes because some authors have argued that species 9 richness and evenness may be independent, and thus should be treated separately (Weiher and together and for species sub-groups, in order to explore differences among life-forms and 12 dispersal syndromes. Plant species were classified into three different functional groups: fleshy-13 fruited woody species (with endozoochorous dispersal), dry-fruited woody species (with 14 dispersal syndromes other than endozoochory, mainly abiotic dispersal), and herbaceous species 15 (Appendix A). Herbaceous species were not divided into subgroups according to dispersal 16 syndrome because most of them (>95%) were dry-fruited and abiotically dispersed. Following 17 the same reasoning as for regeneration, our analyses of richness and H' index estimated three 18 terms: 1) average potential richness (PotRich) or H' index (PotH'), and two sets of scalar 19 modifiers ranging from 0 to 1 that quantify the effects on PotRich/PotH' of 2) local climatic 20 conditions (altitude and annual radiation), and 2) plantation density (pines/ha). The climatic and 21 density effects on diversity were modelled using the same forms as in Eqs. 2, 3 and 4. 22
Parameter estimation, model comparison, and model evaluation 1
We first compared evidence for each of the three independent factors (climate, stand 2 density, distance to seed sources) separately by comparing the Akaike Information Criterion 3 (AIC) of their regression models to the AIC of the value of a null model (i.e., mean or intercept-4 only model). Null models were also run for total regeneration (i.e., number of seedlings/saplings 5 of all tree species together) in both plantation and natural forest plots, as well as for richness and 6 H' index in natural forest plots, in order to compare mean values of natural regeneration and 7 diversity in pine plantations vs. natural broadleaf forests. We then tested increasingly complex 8 models by combining sets of independent factors for which there was evidence (as measured by 9 AIC) of univariate effects. The absolute magnitude of the differences in AIC between alternate 10 models (ΔAIC) provides an objective measure of the strength of empirical support for the 11 competing models. ΔAIC values were also used to derive the Akaike weights (w i ) for the set of 12 candidate models (Burnham and Anderson 2002). The Akaike weight of model i can be 13 interpreted as the expected probability of that model being selected as best when repeated 14 independent samples are taken from the same population. The best model is considered to be 15 clearly superior to the other candidate models when its w i ≥ 0.9. 16
The number of recruits (i.e., seedlings or saplings) in a 5-m radius plot was assumed to 17 follow a zero-inflated Poisson (ZIP) distribution. By using this distribution, we modelled 18 regeneration as the result of two distinct processes: first, the occurrence of recruitment, and 19 second, the number of recruits conditional on the occurrence of recruitment. The ZIP function 20 has the form: 21
where y i represents the number of recruits in plot i, pz represents a constant probability across the 1 dataset of getting zero recruits (structural or supplementary zeros), and λ is the mean of the 2
Poisson distribution (modelled here as a function of climatic, density, and distance effects). Zero-3 inflated distributions have been recommended for the modelling of processes that, like tree 4 recruitment, are often characterized by an excess number of zero counts that cannot be 5 accommodated by traditional discrete probability distributions (i.e., Poisson distribution; 6
Lambert 1992, Rathbun and Fei 2006, Fortin and DeBlois 2007) . For species richness, we 7 assumed a Poisson error structure (since the low number of zeros did not require the use of zero-8 inflated models). H' index values were modelled using a normal error distribution. 9
We used simulated annealing, a global optimisation procedure, to determine the most 10 likely parameters (i.e., the parameters that maximize the log-likelihood) given our observed data 11 (Goffe et al. 1994 ). The R 2 of the regression (1 -SSE/SST) of observed vs. predicted values was 12 used as a measure of goodness of fit (SSE, sum of squares error; SST, sum of squares total). We 13 used asymptotic two-unit support intervals to assess the strength of evidence for individual 14 maximum likelihood parameter estimates (Edwards 1992) . A support interval is defined as the 15 range of the parameter value that results in less than a two-unit difference in AIC. It is roughly 16 equivalent to a 95% support limit defined using a likelihood ratio test (Hilborn and Mangel 17 1997 ). All analyses were performed using R v 2. However, seedling density values varied strongly among plantation plots along axes of altitude, 9 radiation, stand density and, in the case of Q. ilex, also distance to seed sources, as indicated by 10 the best models of each of the 5 species tested (w i > 0.9 for the full models; Table 1 ). 11
All species showed the expected Gaussian curve in response to altitude (Fig. 2a) . The 12 lack of overlap among species in the value of the mode of the curve (parameter XA 0 in Appendix 13 C) indicates a clear segregation along this gradient (from lower to higher altitude): P. halepensis 14 < P. pinaster < Q. ilex seedlings < Q. ilex saplings < P. nigra < P. sylvestris. Most species also 15 showed a Gaussian response along the radiation gradient (Fig. 2b) . Only for Q. ilex did our data 16 fail to support a radiation effect on seedling abundance. Along this abiotic gradient, however, the 17 mode of the curve often overlapped among species, maximum densities occurring in most cases 18 Seedling species also segregated along a gradient of stand density: P. halepensis reached 20 maximum seedling densities at low values of pine density (0-100 pines/ha), tending to null 21 regeneration within 1000-1500 pines/ha ( Fig. 2c ; Appendix C). The three remaining pine species 22 and Q. ilex saplings had recruitment peaks (XD 0 parameter) at densities between 400-900 23 pines/ha, tending to null regeneration within 1500-2000 pines/ha. Finally, Q. ilex seedling 1 abundance peaked at 1100-1300 pines/ha, some seedlings recruiting at even 3000 pines/ha. 2
Moreover, for three of the five tree species, our data supported a model in which the mode of the 3 density effect was allowed to vary as a function of the climatic conditions of the plot (Table 1) . 4
Thus, for Q. ilex seedlings and saplings, the maximum seedling abundance occurred at lower 5 pine densities with decreasing altitude (i.e., decreasing precipitation and increasing temperature, 6
positive values of the γ parameter; Fig. 3a ,b and Appendix C). For P. nigra and P. sylvestris, the 7 maximum seedling abundance occurred at lower pine densities with increasing annual radiation 8
(negative values of the γ parameter; Fig. 3c,d) . 9
In the case of Q. ilex, seedling and sapling abundance also depended heavily on the 10 distance to the nearest seed source (i.e., natural Q. ilex forest), as indicated by the large decrease 11 in AIC when distance effects were added to a model of climatic and density effects (Table 1) . 12
Quercus ilex recruitment in plantation plots decreased exponentially with distance to the nearest 13 Q. ilex forest (Fig. 2d) . The rate of decrease was much slower for Q. ilex seedlings than for Q. 14 ilex saplings. Thus, whereas the predicted probability of finding a Q. ilex seedlings tended to 15 zero within 4 km from the nearest seed source, for Q. ilex saplings it tended to zero within half 16 the distance (2 km). 17
Altogether, the effects of climate, stand density, and dispersal distance determined that 18 plantations at low (~ 1300 m a.s.l.) and middle altitudes (~ 1700 m a.s.l.) and with moderate 19 stand densities (500-1000 pines/ha) had the highest seedling and sapling abundance, mainly of Q. 20
ilex, but also of the four pine species (Fig. 4a,b ). At these altitudinal levels, even the densest 21 plantations had some regeneration thanks to the capacity of Q. ilex to recruit at even 3000 22 pines/ha. On the contrary, high-altitude plantations (~ 2100 m a.s.l.) had much lower recruitment, 23 the seedling bank being largely dominated by P. sylvestris (Fig. 4c) . At this altitude, plantations 1 with > 2000 pines/ha were totally devoid of regeneration. 2 3 Diversity 4
The comparison of the mean models (i.e., null models) for plantations and natural stands 5 indicated that plantations had on average lower species richness (PotRich = 13.09 in the mean 6 model; Appendix B) than native Q. ilex (PotRich = 14.92) and deciduous forests (PotRich = 7 17.55). However, this lower richness was due mainly to a lower number or herbaceous species, 8 whereas the number of woody species (both fleshy-fruited and dry-fruited) was sometimes even 9 higher in plantations than in natural forests (Appendix B). Plantations had also a lower H' index 10 (PotH' = 1.47) than Q. ilex (PotH' = 1.77) and deciduous forests (PotH' = 1.81). However, this 11 lower value was again due primarily to a lower H' index of herbaceous species, whereas the H' 12 index for woody species (both fleshy-fruited and dry-fruited) was similar in the three forest 13 formations (support intervals overlapped among forest formations for PotH' WFleshy and PotH' WDry ; 14
Appendix B). 15
Our data clearly supported a strong climatic and stand density effect on species richness 16 (w i > 0.9 for the full models; Table 2 ). Total species richness peaked at middle altitudes (Fig. 5a ). 17
The altitudinal effect was stronger for the subgroup of fleshy-fruited woody species, as indicated 18 by a smaller breadth (XA b parameter) of the Gaussian curve (Appendix D). Fleshy-fruited woody 19 species was also the only subgroup that responded to radiation, their richness decreasing roughly 20 linearly with increasing radiation (Fig. 5b) . Stand density had a strong negative effect on species 21 richness of all groups. However, whereas the response curves of dry-fruited woody and 22
herbaceous species peaked at zero density values, maximum richness of fleshy-fruited woody 23 species occurred at a greater density (XD 0 =455.78 pines/ha; Appendix D) and decreased at a 1 slower rate (larger XD b parameter) with increasing density (Fig. 5c ). 2
We found strong empirical support for an effect of both climate (only altitude) and stand 3 density on the H' index of all species together and of dry-fruited woody species (Table 2) . On the 4 contrary, the most parsimonious models for fleshy-fruited woody and herbaceous species 5 included only a climatic effect of both altitude and annual radiation ( Table 2 ). The response of 6 the H' indices to altitude was similar to that of richness estimators, with a peak at intermediate 7 altitude and a stronger effect on the fleshy-fruited woody species subgroup (Fig. 5d) . The effect 8 of radiation on the H' index differed for fleshy-fruited and herbaceous species: whereas fleshy-9 fruited woody species decreased monotonically with increasing radiation (as occurred for 10 richness), the H' index of herbaceous species peaked at intermediate radiation (Fig. 5e ). Stand 11 density had, as for richness, a strong negative effect on the H' index for all species grouped (Fig.  12 5f). However, this effect was owed mainly to the effect on dry-fruited woody species, the only 13 subgroup for which data supported a stand density effect. Our data did not support models in 14 which the peak of maximum richness or H' index varied depending on the climatic conditions of 15 the site (i.e., AIC did not improve with the addition of the γ term to the model; Table 2) . 16 Altogether, the effects of climate and stand density determined that plantations at middle 17 altitudinal levels and low tree densities (<500 pines/ha) had the highest values of richness and H' 18 index (Fig. 6) . 19 
DISCUSSION 21
Our results indicate that pine plantations in Mediterranean mountain landscapes had, on 22 average, less active regeneration and lower plant species diversity than natural broadleaf forests. 23
However, this general negative effect of plantations needs to be qualified, since it varied strongly 1 depending on local climatic conditions, stand density, and distance to seed sources, as well as 2 among plant species with different life-history traits. 3 4
Effects of pine plantations on tree regeneration 5
We developed models that relate the seedling and sapling density of the most common 6 tree species in plantation understoreys with the abiotic (climate, distance to seed sources) and 7 biotic (stand density) characteristics of the plantation plots. For the five species tested, we found 8 strong empirical support (w i > 0.9) for the full model that included all these factors as predictors 9 of regeneration. Tree seedling density varied along the 3 gradients from virtually zero to values 10 close to those found in natural forests of Sierra Nevada (~1 seedling/m 2 ; Fig. 3 ). Therefore, 11 regeneration dynamics in a particular plantation were highly dependent on the specific 12 characteristics of the plot. 13
Plantations at low-mid altitudes had a more diverse and abundant seedling and sapling 14 bank than high-altitude plantations (Fig. 4) . The former showed a seedling bank dominated by Q. 15 ilex and accompanied by several pine species (P. halapensis, P. pinaster, P. nigra), whereas the 16 latter showed a virtually monospecific seedling bank of P. sylvestris. The fact that P. sylvestris 17 had maximum seedling density at higher altitude than the other tree species is consistent with its 18 domination of the treeline in Sierra Nevada, where extremely low temperatures and high 19 radiation can limit the establishment of other pine and Quercus species. Based on the species 20 composition of the seedling bank, high-mountain plantations could be expected to exhibit 21 autosuccessional dynamics and perpetuate as monospecific P. sylvestris plantations. On the 22 contrary, low-medium altitude plantations could be expected to follow a successional trajectory 23 towards the replacement of pine forests by oak or mixed pine-oak forests, as suggested by the 1 much larger seedling numbers of Q. ilex than of any pine species. This pine-oak replacement is 2 in agreement with previous studies conducted in Mediterranean areas (Retana et al. 1999, 3 Lookingbill and Zavala 2000) and other parts of the world where pines and oaks are also major 4 structural components of forest ecosystems (Zavala et al. 2007). 5
Stand density had a striking effect on regeneration throughout the whole altitudinal 6 gradient. Seedling and sapling density of all 5 species peaked in the first half of the density 7 gradient (<1500 pines/ha), tending quickly to zero above this level ( Fig. 2c and 4) . Only Q. ilex 8 was able to recruit some seedlings in high-density plantations, probably as a result of its much 9 higher shade-tolerance than pine species (Retana et analyses reveal regeneration patterns that are consistent with a shift from facilitation to 4 competition in the overstorey-understorey interaction along the stand density gradient. Therefore, 5 the rationale behind the establishment of pine plantations in degraded Mediterranean systems -its 6 nurse role of native vegetation-applies only over a relatively small fraction (<1000 pines/ha) of 7 the entire density gradient found at the landscape scale. 8
It bears noting that we found support for the shift between facilitation and competition 9 occurring at different stand density thresholds depending on local climate (Fig. 3) . Thus, 10 maximum recruitment of Q. ilex and mountain pines (P. nigra and P. sylvestris) occurred at 11 lower stand densities with decreasing altitude (i.e., decreasing precipitation and increasing 12 temperature) or increasing radiation. This result suggests that, under stressful conditions of low 13 water availability (i.e., low altitude and high radiation) the potential benefits of the pine 14 overstorey (e.g., amelioration of extreme climatic conditions) are quickly outweighed by the 15 negative effects of competition for water. In fact, pine plantations have been shown to have a 16 strong desiccating effect on soils due to high rainfall interception and water uptake (Maestre et al. high altitude and low radiation) competition for water relaxes, the shift from facilitation to 19 competition occurs at higher stand densities, and net facilitation is found over a larger fraction of 20 the density gradient. This line of reasoning is also supported by the fact that P. halepensis and P. 21 pinaster (the two most drought-tolerant pines) were the only seedling species for which optimal 22 stand density did not vary with climate, probably due to their higher ability to tolerate the 23 negative effects of competition for water with canopy trees. The verification of this mechanistic 1 explanation requires, however, an experimental study that analyse how soil characteristics, 2 microclimate, and seedling performance vary along gradients of pine densities. 3
Our study clearly indicates a prominent importance of distance to seed sources for the 4 colonization of plantations by Q. ilex. Thus, seedling abundance diminished in 50% within the 5 first 250 m from the nearest Q. ilex forest, and by 80% within 1 km (Fig. 2d) . However, some 6 seedlings were found at distances as far as 4 km from the nearest seed source, likely as a result of 7 long-distance dispersal events. In fact, 4 km coincides with the maximum flight distance reported 8 for jays, one of the main dispersers of Quercus sp. in Europe (European jay, Garrulus glandarius) 9
and North America (blue jay, Cyanocitta cristata L.)(Bossema 1979, Johnson and Adkisson 10 1985 ). Yet, the rate of long-distance dispersal events does not seem to be sufficient to maintain a 11 sapling bank of Q. ilex in such remote patches, since the probability of sapling recruitment 12 tended to zero within shorter distance (2 km). In heterogeneous Mediterranean landscapes, jays 13 move acorns nonrandomly, avoiding some patches (e.g., shrublands and grasslands) and moving 14 most acorns to pine stands, which in turn are high-quality habitats for emergence and survival of 15 Q. ilex seedlings (Gómez 2003 (Gómez , 2004 ). This effective directed dispersal, together with the 16 abundance of Q. ilex forests at the landscape scale (>70% of the 442 plantation plots were at ≤2 17 km from the nearest Q. ilex fragment), may be crucial for the successional dynamics towards oak 18 forests that many pine plantations appear to undergo in Sierra Nevada. 19 
20

Effects of plantations on the diversity of vascular plants 21
Pine plantations had on average lower total plant richness and H' index values than native 22 stands, especially when compared with deciduous broadleaf forests. However, in a detailed 23 analysis, this negative effect appeared only for herbaceous species, and not for woody species. 1
The negative effect on herbaceous species is probably a result of the much higher tree density of 2 plantations in comparison to native fragments, which in turn implies lower understorey light 3 levels usually responsible of low herbaceous richness and cover (Harrington and Edwards 1999, 4 Thomas et al. 1999). In any case, pine plantations were not "biological deserts", and several 5 woody and herbaceous species were able to survive within these forest stands. However, plant 6 diversity was very heterogeneous among plantation plots, depending on their local climatic and 7 density characteristics. 8
Both species richness and H' index values showed a hump-shaped pattern distribution 9 along the altitudinal gradient (Fig. 5a,d ). This pattern seems to be the most common when entire 10 altitudinal gradients are sampled (as in this study) due to both higher productivity and lower 11 human impact at mid-altitudinal habitats (Rahbek 2005 
, Nogués-Bravo et al. 2008). Radiation 12
had a more modest effect than altitude on both richness and H' index values, its effect being 13 restricted primarily to fleshy-fruited woody species. In fact, this group, much less abundant than 14 dry-fruited and herbaceous species in all cases, was also the most affected by climatic gradients, 15 being restricted largely to areas at intermediate altitudes and with low radiation (i.e., north-facing 16 slopes, valley floors). Therefore, mid-altitude plantations had not only higher species richness 17 and evenness, but also higher relative abundance of fleshy-fruited woody species, than did 18 plantations at the two extremes of the altitude gradient. 19 Stand density had a strong effect on total species richness and evenness, which decreased 20 monotonically along the density gradient (Fig. 6) . The impoverished plant diversity of high-21 density plantations was presumably due to higher seed and establishment limitation than in low-22 density plantations. On the one hand, bird abundance and richness is in native species are not adapted to establish in such competitive environments, since natural forests 7 of the area rarely exceed 1000 trees/ha. 8
When species subgroups were considered, richness of dry-fruited and herbaceous species 9 followed a variation pattern along the density gradient similar to that of total species richness -10 that is, a monotonically decrease with increasing stand density. On the contrary, richness of 11 fleshy-fruited bird-dispersed species peaked at a moderate tree density (about 500 pines/ha) and 12 was less negatively affected by stand density than in the other subgroups (i.e., richness at 13 maximum stand density reduced only to about 40% of potential, instead of to 20% as in the other 14 subgroups; Fig. 5b ). These among-group differences might be influenced by the relationship 15 between dispersal mode and successional status (Huston and Smith 1987) . A large number of 16
Mediterranean fleshy-fruited woody species are late-successional shade-tolerant species, whereas 17 pioneer woody species (e.g., Cistaceae, Labiatae, Leguminosae) usually have dry fruits (Herrera 18 1995). Therefore, fleshy-fruited species will have a comparatively higher probability of 19 persisting in the dark understorey of dense plantations than light-demanding dry-fruited woody 20 and herbaceous species. Because shade-tolerance is negatively correlated with drought-tolerance 21 (Niinemets and Valladares 2007) , fleshy-fruited species will also benefit more than any other 22 group from the mild microclimate generated by a moderate canopy density. 23
In areas such as the Mediterranean Basin, where millions of hectares are covered with 3 plantations, there is an increasing concern to reconvert them into more natural forests with active 4 regeneration, high biodiversity levels, and high resilience to disturbances such as pests and fires 5 because regeneration dynamics and plant diversity of pine plantations in heterogeneous 7
Mediterranean mountains varies broadly along abiotic and biotic gradients, plantations at 8 different points along these gradients will require different management strategies. 9
Active management will be urgently required in high-density plantations (>1500 pines/ha) 10 with arrested succession, where excessive pine density causes a net overstorey-understorey 11 competitive interaction and limits seed inputs from both local (due to a poor understorey) and 12 external sources. Thinning should be prescribed to allow the entrance of light, seeds, and 13 dispersers, redirecting plantations towards more natural densities where facilitative interactions 14 predominate. Densities of 500-1000 pines/ha seem to offer the best compromise between high 15 seedling and sapling densities of most tree species, and high diversity levels of both woody and 16 herbaceous species. However, thinning levels should be adjusted to the climatic conditions of the 17 site. More intense thinning will be necessary under more stressful climatic conditions, but 18 consistently leaving a residual density (at least 500 pines/ha) that minimizes the costs of negative 19 interactions while maximizing the benefits of habitat amelioration by canopy trees. 20
On the other hand, passive management might be recommended for plantations with low 21 and moderate stand density, since they can be considered transient systems with active 22 successional dynamics. When at low and mid altitudes, these plantations would be expected to 23 change towards oak or pine-oak forests, with the coexistence of these two genera being 1 determined by the stress level (oak dominance being promoted at mesic sites due to greater 2 shade-tolerance) and the frequency of disturbance (disturbance promoting pine persistence; 3 Zavala et al. 2000, Zavala and Zea 2004). When at high altitudes, these plantations would be 4 expected to persist as pine forests dominated by P. sylvestris, the natural forest formations in the 5 Sierra Nevada treeline. 6
Management strategies should also take into account that spontaneous colonization of a 7 plantation depends heavily on its distance to natural forest fragments that act as seed sources, as 8 well as on the dispersal ability of the species inhabiting such forests. Thus, among the pool of 9 native tree species available at the landscape scale in Sierra Nevada, Q. ilex was the only 10 broadleaf species abundantly found in plantation understoreys. Other species such as Q. 11 pyrenaica, A. opalus subsp. granatense, or S. aria were basically absent, probably due to seed 12 limitation derived from their low regional abundance (most plantations being too far from seed 13 sources of these species) and/or less effective dispersal systems (i.e., wind dispersal in Acer). In 14 fact, previous studies indicate that, when seeds are available, all these tree species have high 15 probability of seedling and sapling establishment under moderate shade (as that found in many index, H') in plantation understoreys (n = 442 plots). Models were run for all species together and separated into three subgroups (fleshy-fruited woody species, dry-fruited woody species, and herbaceous species). The best model (lowest AIC, ΔAIC=0) is indicated in boldface type.
Notes: NP is the total number of parameters in the best model; ω i is the Akaike weight for each competing model; and R 2 = 1 -SSE/SST for the relationship between predicted and observed growth. The Climatic axes column indicates whether the best model incorporates terms for effects of altitude (A), annual radiation (R), or both. The γ column indicates whether (Y, yes; N, no) the best model also includes a term that allows sensitivity to pine density to vary with climatic conditions (either altitude [A] 

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