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Quercus suber forest and Pinus plantations show different post-fire resilience in Mediterranean north-western Africa

  • Brahim CherguiEmail author
  • Soumia Fahd
  • Xavier Santos
Research Paper
Part of the following topical collections:
  1. Mediterranean Pines

Abstract

Key message

In the African rim of the Western Mediterranean Basin, cork oak forests and pine plantations coexist. Under similar fire regimes, cork oak forest is more resilient in terms of habitat structure (canopy, understory, and complexity of vegetation strata) than pine plantation. By contrast, both woodland types show similar resilience in plant species composition. Resilience in habitat structure varies between the two woodland types because of the resprouting and seeding strategies of cork oak and pine species, respectively. These differences can be relevant for the conservation of biodiversity of forested ecosystems in a future scenario of increased fire frequency and scale in the Mediterranean basin.

Context

Wildfires have major impacts on ecosystems globally. In fire-prone regions, plant species have developed adaptive traits (resprouting and seeding) to survive and persist due to long evolutionary coexistence with fire. In the African rim of the Western Mediterranean Basin, cork oak forest and pine plantation are the most frequently burnt woodlands. Both species have different strategies to respond fire: cork oak is a resprouter while pines are mostly seeders.

Aims

We have examined the hypothesis that pine plantations are less resilient in habitat structure (canopy, understory, diversity of vegetation strata) and plant composition than cork oak woodlands.

Methods

The habitat structure and plant species composition were measured in 30 burnt and 30 unburnt 700-m transects at 12 burnt sites from north-western Africa, where the two forest types can coexist. Habitat structure and plant species composition were compared between burnt and unburnt transects from cork oak and pine plantation woodlands with generalized linear mixed models and general linear models.

Results

The results showed significant interaction effect of fire and forest type, since cork oak forest was more resilient to fire than was pine plantation in habitat structure. By contrast, both forest types were resilient to fire in the composition of the plant communities, i.e., plant composition prior to fire did not change afterwards.

Conclusion

The higher structural resilience of cork oak forest compared to pine plantation is related to the resprouting and seeding strategies, respectively, of the dominant tree species. Differences in the responses to fire need to be considered in conservation planning for the maintenance of the Mediterranean biodiversity in a future scenario of changes in fire regime.

Keywords

Cork oak forest Pine plantation Fire Habitat structure Resilience Rif Mediterranean basin 

1 Introduction

Fire is a natural process in many ecosystems and a key element to understand their functioning and plant community composition (Moritz et al. 2012; Bond et al. 2005). In fire-prone regions, the effects of fire on vegetation are usually the most obvious impacts of burning (DeBano et al. 1998), and this variation may influence biodiversity at local and landscape scales (De Grandpré et al. 2000; Burrows 2008). Moreover, the long history of fire has strongly selected against fire-sensitive plant species and has promoted a wide range of fire-resistant strategies (Pausas et al. 2008). Thus, forest ecosystems can recover their original structure and composition following a fire due to the resilience of plant community (Trabaud and Lepart 1980; Keeley 1986; Retana et al. 2002). Post-fire resilience is based on the ability of plant species to generate new shoots from dormant buds located on fire-resistant structures after stems have been fully scorched (hereafter resprouters) and/or to generate a fire-resistant seed bank stored in the soil or in the canopy with seeds that germinate profusely after blazes (hereafter seeders; Keeley 1986; Hodgkinson 1998; Pausas et al. 1999; Pausas 2001).

A forest ecosystem can be considered resilient if it is able to recover its composition, structure, and main functions following a disturbance (Folke 2006). Forest resilience can be partitioned in two components: (i) structural resilience when the habitat after fire recovers soon in terms of canopy, understory, and complexity of vegetation strata and (ii) compositional resilience when the plant communities after fire resemble those of pre-fire conditions in terms of species composition and relative abundance (Drever et al. 2006; Lipoma et al. 2016). In fire-prone regions, forest resilience can be disrupted by changes in fire regimes (greater fire frequency and extent) because of socioeconomic changes (e.g., land abandonment and fuel increase; Moreira et al. 2001; Moreira and Russo 2007; Pausas and Fernández-Muñoz 2012; Pausas et al. 2012). Likewise, the introduction of very flammable species in monocultures such as coniferous trees also can disrupt forest resilience (Shakesby et al. 1996; Pausas et al. 2004; Vallejo et al. 2006). This process is occurring in Western Mediterranean landscapes as coniferous species (seeders) are replacing oak species (resprouters) (Aronson et al. 2009; Costa et al. 2011). Seeder species recover after fire from seeds stored in the soil or in the canopy (Pausas and Keeley 2014). By contrast, resprouters often have lower seed recruitment than seeder species (Keeley 1986; Burgman and Lamont 1992; Pausas 2001), although they resprout after fire from basal lignotuber or epicormic stem buds (Clarke et al. 2013). The establishment of seedlings requires more time and thus their regeneration is slower than resprouting. These opposing responses of fire make resprouter species faster fire resilient than seeders (Lloret 1998; Pausas 1999; Rodrigo et al. 2004; Valdecantos et al. 2009).

The forest cover in the African rim of the Western Mediterranean Basin accounts for 35% of the total area. The commonest native tree species is the cork oak Quercus suber. In recent decades, however, cleared or degraded Q. suber forest and shrublands have been replaced by coniferous plantations composed mostly of maritime pine Pinus pinaster (Pastor-López et al. 1997). Wood and resin from pine plantations are important socioeconomic resources which are reflected in the intensity of reforestation. These reforestations have been undertaken often in the bioclimatic subhumid and humid zones of the Rif and eastern Middle Atlas (Emberger 1955), representing about 90% of all reforestation in the region (Belghazi and Romane 1994).

The cork oak resprouts after fire from basal lignotuber but to a greater extent from epicormic stem buds (Molinas and Verdaguer 1993). This species is adapted to the impact of fire due the capacity of the bark to protect against high temperatures (Barberis et al. 2003; Úbeda et al. 2006). By contrast, maritime pine and other Pinus species are susceptible to crown fires, particularly at the juvenile stage (Cruz and Fernandes 2008; Molina et al. 2011; Mharzi Alaoui et al. 2017). Pines regenerate from seed (Díaz-Delgado et al. 2002) especially in serotinous populations (Hernández-Serrano et al. 2013). Although P. pinaster and other pines can survive low-intensity surface fires (Catry et al. 2010; Vega et al. 2010; Keeley 2012), it is considered low-resilience species (Proença et al. 2010). This pine species is an obligate seeder with low but variable degree of serotiny depending on populations (Tapias et al. 2004; Hernández-Serrano et al. 2013). Moreover, P. pinaster seedlings are shade intolerant and recruitment can be highly heterogeneous and influenced by a combination of climatic, edaphic, and structural factors (Rodríguez-García et al. 2011). Therefore, post-fire regeneration of P. pinaster forest can be slow, and also pines can be replaced by more competitive species such as Quercus trees in early post-fire stages (Torres et al. 2016).

In this study, we compare the structural and compositional resilience of cork oak forests and coniferous plantation in an area located on the African rim of the Western Mediterranean Basin. This area is affected by Mediterranean fire regime (crown and summer fires; Chergui et al. 2017), and Q. suber forest and P. pinaster plantations are the commonest burnt woodlands. Due to the opposing responses to fire on the part of Q. suber and P. pinaster (resprouter and seeder, respectively), we expect marked differences in post-fire structural resilience between these two forest types, as well as differences in compositional resilience. Quercus suber recovers very quickly because it resprouts directly from the trunk and branches and this can allow its re-establishment in a short time period (Pausas 1997; Carrión et al. 2000; Alanís-Rodríguez et al. 2011). For this reason, we hypothesize that Q. suber forests will present higher structural and compositional resilience following fire than P. pinaster plantations.

2 Material and methods

2.1 Study area and fire regime

The study area is located in north-western Africa between 35° 00′ and 35° 55′ N and between 5° 00′ and 6° 15′ W, covering nearly 12,650 km2 (Fig. 1). The maximum elevation is 2159 m a.s.l. at Jbel Lakraa. The climate is mainly of the Mediterranean type with an altitudinal gradient in temperature and precipitation from valleys and coast to uplands. Mean annual temperatures vary from 15 to 19 °C (Ajbilou 2001; Ghallab and Taiqui 2015), whereas the annual rainfall in some areas of the Rif reaches 2000 mm.
Fig. 1

Location map at the African rim of the Western Mediterranean Basin, fire sites (red polygons), and example of the spatial scheme of three burnt and three unburnt transects from site Oued Lil

Vegetated areas cover 396,165 ha, which represents 35% of the total area of the region including natural woodlands and scrublands (84.5%) as well as plantations (15.5%; Benabid 2007). The forest coverage is dominated by cork oak Quercus suber and scrubland formations, followed distantly by Holm oak Quercus rotundifolia and maritime pine Pinus pinaster. In the study area, natural P. pinaster and Pinus halepensis populations are distributed discontinuously, covering small, patchy areas (Quezel et al.1992; Belghazi et al. 2000; Benabid 2007). Plantations include 49,124 ha of coniferous (mainly P. pinaster) and 14,462 ha of deciduous species (mainly Eucalyptus) (Mharzi Alaoui et al. 2015). The study area undergoes a typical Mediterranean fire regime with blazes occurring in the hot, dry summer season (Chergui et al. 2017). Two major forests are affected by fire, i.e., native cork oak forests and pine plantations, in which fires are likely medium- or small-size fires (< 1000 ha) due to the intense fuel (wood) use linked to the particular socioeconomic conditions of northern Morocco (Chergui et al. 2017).

2.2 Site selection and vegetation sampling

The vegetation was sampled at 12 field sites (Fig. 1; Table S1) in the spring of 2016. These sites were selected according to the fire extent and year of fire occurrence between 2008 and 2015 (8 years to1 year = time since fire; TSF thereafter). The fire history at each site was taken from the Haut Commissariat aux Eaux et Forêts et à la Lutte Contre la Désertification (hereafter the HCEFLCD) and from Mharzi Alaoui et al. (2015). Most of the fires in both forest types occurred in summer (Table S1) as is characteristic of the Mediterranean region in general (Chergui et al. 2017). The forest at the study sites is mostly composed by Q. suber and Pinus pinaster plantations. Some burnt plantations were composed by other Pinus species such as P. halepensis, Pinus brutia, and Pinus pinea (Table S2; Mharzi Alaoui et al. 2017). These coniferous species have different degree of serotiny, but all of them are obligate seeders (Thanos and Doussi 2000; Pausas et al. 2004; 2008); therefore, all burnt pine transects were pooled as pine plantation sites for further analyses.

The 12 sites covered an altitudinal gradient from 97 to 1281 m a.s.l. Average rainfall and annual temperature at each site (range 16.20–19.43 °C and 631–965 mm respectively; Table S1) were obtained from Climatology Resource for Agroclimatology (https://power.larc.nasa.gov/cgi-bin/agro.cgi?na). Average rainfall and annual temperature were positively correlated with elevation (r = 0.547, P = 0.002 and r = 0.469, P = 0.005, respectively). We found no differences in the distribution of the two forest types (Quercus and Pinus) with respect to elevation (Mann-Whitney U test, Z = − 1.90, P = 0.06). Thus, we discarded biases in the resilience of cork oak and pine plantation burnt sites due to climate (e.g., rainfall) effects (Walker et al. 2016).

At each site, burnt polygons were laid out from Landsat imagery provided by the USGS Earth Explorer server (http://earthexplorer.usgs.gov/), and 60 transects (2–3 burnt and 1–3 unburnt at each site) were randomly assigned for vegetation sampling. Unburnt (control) transects were selected around each burnt area and usually near each unburnt pair (the maximum distance between the burnt-unburnt pair was 2 km). We assumed that vegetation in control areas was left unchanged and reflected initial vegetation composition before the fire occurred. Transects followed small unpaved trails were located at least 50 m from the burnt edge left by the fire and averaged 698 m ± 0.93 length. The elevation and geographic location of each transect were recorded with a Global Positioning System (GPS).

2.3 Variable selection and data analysis

At each transect, habitat structure and species composition were measured on 50 quadrats (25 quadrats on each side of the transect). Quadrats were 10 m × 10 m and located 15 m apart. In each quadrat, nine habitat structure and four species composition variables were recorded (Table 1). Structural variables were arranged roughly into three vegetation layers: the overstory, defined as trees, which were dominant in the uppermost canopy; the midstory, composed mainly by shrubs; and the understory, composed of grasses and other ground covers. Thus, structural variables were defined as the extent (percentage of cover) of three vegetation types, i.e., tree, shrub, and grass, as well as three ground cover types, i.e., bare ground, litter, and rocks. Percentage of cover for structural variables was visually estimated at each quadrat. Additionally, we estimated the maximum tree height at each quadrat and calculated the canopy using a convex spherical densiometer. At each quadrat center, the densiometer was mounted on a tripod oriented in direction of the four cardinal points and four canopy measurements were taken. The canopy closure was the average of the four cardinal point measurements (Lemmon 1957). For the structural variables (tree, shrub, grass, bare ground, litter, rock cover, maximum tree height, and canopy), we calculated average values at each transect using individual values of each quadrat. Additionally, we estimated the structural complexity of each transect by calculating the Simpson diversity index from the percentage of all vegetation and ground cover types in each quadrat. This index equals the diversity of vegetation and ground layers; therefore, higher Simpson diversity scores indicate more complex (heterogeneous) transects.
Table 1

List and description of the structural and compositional vegetation variables (nine and four, respectively) examined in burnt and unburnt transects at 12 sites located in north-western Africa

Variable

Description

Canopy

Measured using a convex spherical densitometer in each quadrat

Tree height

Average height (m) of the tallest tree estimated from 100 10 × 10 m quadrats per transect

Treea, shrubs, grass, bare ground, litter, and rock cover

Average percentage cover estimated from 100 10 × 10 m quadrats per transect

Simpson diversity (STR)

Calculated from the percentage of all vegetation and ground cover types

Number of plantsa

Recorded at each transect

PC1 and PC2

Axes of the principal component analysis based on the cover of each plant species estimated at each transect

Simpson index (SP)

Calculated from the cover of each plant species estimated at each transect

aThe excluded variables to perform statistical models due to the high correlation (r > 0.7)

Compositional variables were based on the cover of all perennial and the commonest herbaceous plant species (n = 43) identified at each quadrat. Plant species cover is a methodological surrogate of vegetation composition and abundance (Daubenmire 1959). The cover of each species followed Daubenmire’s (1959) procedure: at each 10 × 10 m quadrat, each species cover was visually estimated using a cover classification as follows 1, 0.5%; 2, 3.5%; 3, 15.5%; 4, 38.0%; 5, 63.0%; and 6: 88.0%. For each plant species identified along the transect, we calculated average values using cover scores of all quadrats. Average values of each plant species found at each transect were used to calculate the Simpson diversity index and to run a principal components analysis (PCA) to reduce all the variability of transects in terms of plant composition to a low number of variables. Thus, the total number of plant species found in each transect (all perennial and the commonest herbaceous plant species), the Simpson diversity index, and the first two axes of the PCA (PCA1 and PCA2) were used as compositional variables in further analyses (Table 1).

From the 13 variables initially considered, we removed tree cover and the total number of plants (perennial and the commonest herbaceous) as they were highly correlated (r > 0.7) with canopy and PCA1-PCA2 respectively. The 11 variables retained were used as dependent variables in further multivariate models. We used linear models to examine the effect of elevation, fire (burnt vs. unburnt), forest type (Q. suber forest and P. pinaster plantation) on eight structural and three compositional variables. Generalized linear mixed models (GLMMs) with site as a random effect were conducted for seven dependent variables (canopy, tree height, shrub cover, grass cover, bare ground cover, litter cover, and rock cover) with a Poisson distribution as the data are non-negative values and counts, e.g., cover classes and tree height estimation (Table 2). General linear models (GLMs) were conducted for four dependent variables (Simpson index [STR], Simpson index (SP), PC1 and PC2) with Gaussian distribution (Table 2). GLMs and GLMMs were performed using the lme4 package (Bates et al. 2015) and loess smooth curves using the ggplot2 package (Wickham 2009). All the statistical analyses were made with R (R Development Core Team 2015).
Table 2

Summary results of the generalized linear mixed models (GLMMs) and general linear model (GLMs) analyzing the influence of fire on structure (STR) and composition (SP) of the vegetation in burnt sites from north-western Africa

Response variable

Model type

Fire

Forest types

Fire*forest

Elevation

Estimate

t/z value

p

Estimate

t/z value

p

Estimate

t/z value

P

Estimate

t/z value

P

Canopy

GLMMs

1.225

11.403

< 0.0001

0.702

3.591

0.0003

− 0.962

− 7.093

< 0.0001

− 0.0001

− 0.597

ns

Tree height

GLMMs

0.838

4.128

< 0.0001

0.452

1.295

ns

− 0.643

− 2.436

0.014

− 0.0004

− 0.969

ns

Shrub cover

GLMMs

0.158

2.817

0.0048

0.115

1.197

ns

− 0.192

− 2.422

0.015

− 0.00010

− 0.518

ns

Grass cover

GLMMs

− 0.023

− 0.342

ns

− 0.004

− 0.035

ns

0.129

1.322

ns

0.00011

0.486

ns

Bare ground cover

GLMMs

− 0.183

− 2.786

0.0053

− 0.112

− 1.058

ns

0.336

3.389

0.0007

0.00010

0.440

ns

Litter cover

GLMMs

− 0.258

− 2.488

0.0129

− 0.212

− 0.903

ns

0.170

0.898

ns

0.0000

0.151

ns

Rock cover

GLMMs

0.356

2.118

0.0342

0.503

2.518

0.0118

− 0.149

− 0.691

ns

0.0012

3.224

0.0012

Simpson index (STR)

GLMs

0.0000

2.126

0.0378

0.0000

2.474

0.0165

0.0000

− 1.275

ns

0.0000

1.274

ns

PC1

GLMs

− 0.195

− 0.275

ns

2.064

2.854

0.0060

0.889

0.869

ns

0.0031

5.498

< 0.0001

PC2

GLMs

0.028

0.044

ns

3.550

5.107

< 0.0001

− 0.202

− 0.214

ns

− 0.003

− 4.262

< 0.0001

Simpson index (SP)

GLMs

0.0000

0.127

ns

0.0000

0.225

ns

0.0000

− 0.086

ns

0.0000

− 0.054

ns

z values are provided for data modeled with Poisson distribution and t values for those modeled with Gaussian distribution. Significant P values are in italic. PC1 and PC2 are scores of the first two axes of a principal components analysis based on the matrix of all plant species cover at each transect

ns not significant tests

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

3 Results

3.1 Structural resilience

We detected significant variation in almost all structural variables (canopy, tree height, shrub cover, bare ground cover, litter cover, rock cover, and Simpson index) between burnt and unburnt transects (Table 2; supplementary material data set). Significant differences also appeared between the two forest types (cork oak and pine plantation) for canopy, rock cover, and Simpson index (Table 2). Notably, we found significant differences in the interaction fire × forest type for canopy, tree height, shrub cover, and bare ground cover (Table 2). Shrub cover and the Simpson index remained similar between burnt and unburnt cork oak transects, whereas strong variation arose in pine plantations. In burnt pine plantations, fire significantly decreased canopy, tree height, and shrub cover, whereas bare ground cover increased (Fig. 2). A forest type effect on the habitat-complexity resilience was observed: the Simpson index of the cork oak forest did not change significantly with fire, whereas it diminished in burnt pine plantations (Fig. 2g). We found no significant differences of structural variables with the elevation of the transects except rock cover (greater at higher elevations).
Fig. 2

Generalized linear mixed models and general linear models results of the interaction between forest types and fire in context of a canopy, b shrub cover, c tree height, d bare ground cover, e litter cover, f rock cover, and g Simpson index (structure). Circles mean pine plantation; triangles mean cork oak forest. Symbols refer to mean values and whiskers are ± one standard error

3.2 Compositional resilience

A total of 45 and 45 plant species were recorded in burnt and unburnt transects, respectively, belonging to 23 taxonomic families (Table S3). We found no differences in the diversity of plant communities between the two forest types (Table 2). However, plant species composition differed between cork oak and pine plantation transects according to the values of the first and second PCA axes (PC1: eigenvalue 5.46, 12.7% of explained variance; PC2: eigenvalue 5.10, 11.9% of total variance explained; Table 2, Fig. 3). Among the commonest plant species, those that best explained the shift in plant composition between cork oak forest and pine plantation were Cistus monspeliensis and Pistacia lentiscus, which were more abundant in pine plantations, whereas Arbutus unedo, Cistus salvifolius, and Cistus crispus were more abundant in cork oak forest (Table S4). Plant species composition (PC1 and PC2 scores) also varied with elevation.
Fig. 3

General linear models results of the interaction between forest types and fire in context of the first two axes PC1 (a) and PC2 (b) of a principal components analysis of the relative abundance of each plant species found in transects. Circles mean pine plantation; triangles mean cork oak forest. Symbols refer to mean values and whiskers are ± one standard error

4 Discussion

4.1 Vegetation structure

The most evident result of our study was that fire simplifies the complexity of the forest regardless of the type of forest studied; this trend was especially visible in canopy and tree height (overstory), which decreased after burning. Notably, several structural variables showed significant differences in the interaction between fire and forest type variables. These results did support the hypothesis that cork oak forest had greater structural resilience following fire disturbance than did coniferous plantations. These differences between forest types suggest that less diversified systems such as pine plantations are less resilient to natural disturbance than are more complex ecosystems such as native Q. suber forest (Drever et al. 2006). Besides differences between native forest and pine plantations, variation in local environmental and weather conditions can also play a role in local resilience to fire (Proença et al. 2010; Walker et al. 2016). However, we detected no effect of elevation (a surrogate of temperature and rainfall) on structural resilience, suggesting that variation of local environmental gradients was less important than forest characteristics to explain resilience to fire.

Although large (= old) cork oak trees can be eliminated by fire due to their reduced ability to resprout, canopy and tree height (overstory variables) did not significantly vary after fire in the cork oak forest from the study area. By contrast, we observed a great decline in canopy and tree height from pine plantations. These divergent results confirm the high post-fire survival ability of Q. suber in Western Mediterranean regions such as Spain (Pausas 1997; Gonzalez et al. 2007), Portugal (Moreira et al. 2007; Catry et al. 2009), and Algeria (Bekdouche et al. 2008). It is known that Q. suber has thick bark and resprouts vigorously, while fire-created seedbeds are suitable for acorn germination (Pausas 1997). Usually Q. suber recovers very quickly because it resprouts directly from the trunk and branches, this allowing the re-establishment of the canopy in a short period of time (Pausas 1997). Fire vulnerability (and lower resprouting) increases for young or recently debarked Q. suber individuals, as well as depending on the location of the forest and timing of the fire (Catry et al. 2012). Despite these differences among populations, there is a high survival rate of this species in fire-prone environments, probably the highest among Western Mediterranean tree species (González et al. 2007). Short intervals between successive fires can lead to substantial changes in vegetation (Lippitt et al. 2012; Tessler et al. 2015), including Q. suber forests (Santos and Cheylan 2013). However, repeated fire regimes do not appear to be typical of our study area since most of the study sites have burnt only once over the last 50 years (Chergui et al. 2017).

Our results would support the slow post-fire recovery of pine plantations especially in dry regions during the first years after fire (Trabaud 1982; Domínguez et al. 2002; Perula et al. 2003); this is because most P. pinaster individuals die, as do most other coniferous species (Catry et al. 2006; Proença et al. 2010). Pine plantations are highly flammable as they consist of dense stands of pine trees with branches all along the main stem (Pausas et al. 2008) and due to the quality, quantity, and structural arrangement of its fuel (Nimour Nour 1997; Fernandes and Rigolot 2007). Thus, fire progression in the pine plantation canopy is further encouraged by the high tree density (Perula et al. 2003) and the ladder fuel (e.g., lower dead branches, fallen needles) that promote the vertical progression of fire (Fernandes and Rigolot 2007; Fernandes 2009; Ormeño et al. 2009).

The low shrub cover resilience observed in pine plantations can be caused by the slow recovery rate of the dominant tree species and the high intensity of fire, which may destroy regenerative tissues and reduce seed viability (Proença et al. 2010). By contrast, there was similar shrub cover between burnt and unburnt cork oak forest plots, probably due to the post-fire preservation of the extensive root system of shrubs. When the root system is preserved, resprouting can occur immediately after disturbance, taking advantage of the nutrients and water accumulated in the roots (Fernández and Paruelo 1988; Verdú 2000). Contrary to the scrubland, grass cover did not vary after fire in pine plantations and tended to decline in the cork oak forest. The slight effect of fire on grassy species was probably because most post-fire annual species are transitory in these ecosystems (Trabaud and Lepart 1980; Bonnet et al. 2002; Buhk et al. 2006). In addition, the high intensity that characterizes fire events of pine plantations could act as short-term inhibitor of other plant species in these communities.

4.2 Vegetation composition

Our study demonstrated that the composition of plant communities between Q. suber and P. pinaster woodlands differed. However, the resilience of both forest types to fire was similar under similar fire regime as in the Rif (Chergui et al. 2017). In this scenario, the most evident cause of shift in plant composition is expected to be not fire but the use of conifer plantation. The compositional resilience of plant communities both in native Q. suber forests and in P. pinaster plantations highlights the evolutionary strategies of Mediterranean plant species to respond to burning, i.e. resprouting and seeding (Hodgkinson 1998; Pausas and Vallejo 1999; Coca and Pausas 2012; Ne’eman et al. 2012). For example, many shrub species observed in the studied sites were supported mainly by resprouting shoots (James 1984; Canadell and Zedler 1995; Lloret et al. 2003), with fast regeneration processes immediately after fire. This is the case of Arbutus unedo (Cabezudo et al. 1995). In addition, post-fire seedlings recruited from dormant soil-stored seed banks (Keeley et al. 2012) are also confirmed in the commonest species recorded in this study such as Cistus salviifolius (Trabaud and Oustric 1989; Roy and Sonié 1992). The presence of these species guarantees the resilience in the composition of plant communities from the north-western Africa, at least under a fire regime characterized by few big blazes (> 500 ha) and few areas with recurrent burning (Chergui et al. 2017).

4.3 Conclusions and conservation remarks

In conclusion, Q. suber and P. pinaster plantations support different plant communities in the African rim of the Western Mediterranean Basin. However, these communities show similar resilience to fire. In contrast, the structure of Q. suber stands recover more rapidly after burning than do Pinus plantations under a similar fire regime (Calvo et al. 2003). This was caused primarily by the functional strategies of Q. suber and P. pinaster responding to fire, which may affect other structural layers. Differences in structural resilience between forest types can disturb the resilience of other ecosystem components such as fauna and soil (Seybold et al. 1999; Jacquet and Prodon 2007; Mateos et al. 2011; Chambers et al. 2014). The low post-fire regeneration shown by pine plantations can have direct consequences in the loss of diversity under changes in the current fire regime (Pausas and Fernández-Muñoz 2012; Chergui et al. 2017). The resilience of other components of the ecosystem merits future research to guarantee the conservation of biodiversity in this area characterized by high rate of endemism (Pleguezuelos et al. 2010).

Notes

Acknowledgments

We wish to thank Professor Mohamed Kadiri, Director of the Applied Botanical Laboratory (Biology Department, Abdelmalek Essaâdi University), for helping on the identification of plant species. Also, we would like to thanks Juli Pausas and Xavier Santos for their revisions of an early version of the manuscript. In addition, we are grateful to Saúl Yubero for their kindness and help in the field work.

Funding

This study was partially financed by the Instituto de Estudio Ceuties (research grant 2015-1).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

13595_2018_742_MOESM1_ESM.xlsx (22 kb)
ESM 1 (XLSX 22 kb)
13595_2018_742_MOESM2_ESM.docx (41 kb)
ESM 2 (DOCX 32 kb)

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© INRA and Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Equipe de Recherche Ecologie, Systématique, Conservation de la Biodiversité, Faculté des Sciences de TétouanUniversité Abdelmalek EssaâdiTétouanMorocco
  2. 2.CIBIO/InBIOCentro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do PortoVairãoPortugal

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