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iForest - Biogeosciences and Forestry
vol. 9, pp. 946-953
Copyright © 2016 by the Italian Society of Silviculture and Forest Ecology
doi: 10.3832/ifor1848-009

Collection: IUFRO RG7.01.00 - Nice (France 2015)
“Global Challenges of Air Pollution and Climate Change to Forests”
Guest Editors: Elena Paoletti, Pierre Sicard

Research Articles

Evergreen species response to Mediterranean climate stress factors

Loretta GrataniCorresponding author, Rosangela Catoni, Laura Varone


The projected global climate warming could affect a wide range of species and ecosystems ([25]). Considering that the implications of global climate change are characterized by strong latitudinal variations ([27]), regional studies are recommended to provide an essential tool for scientists and decision-makers ([18]). The Mediterranean basin is especially vulnerable to climate change ([19]). Due to its unique geographic location, this region is a transitional zone between the very hot and dry African climate in the South and the mild and humid European climate in the North ([19]). Recent climatic projections for the Mediterranean basin predict an air temperature increase and a decline in rainfall mainly during summer ([27]). Moreover, the Mediterranean basin undergoes more prolonged dry periods than in the past. This produces a negative soil water balance as the amount of water that evaporates overcomes the amount of water intercepted by soil through rainfall and summer humidity ([8], [33]). The Mediterranean basin is characterized by a high plant diversity of growth forms, habits and phenology ([17]). In particular, physiological adaptations involve regulation of the water status by stomatal control ([23]). Morphological and anatomical adaptations involve leaf protective structures (i.e., hairs, thick cuticle, sclerenchymatic cells), steep leaf inclination, low leaf surface area ([9], [29], [21]) and a high stomatal density of small size ([39], [23]). Such traits improve drought resistance by decreasing photochemical damage of the photosynthetic apparatus and limiting leaf transpiration ([9]). Among the Mediterranean species, the sclerophyllous have a high construction cost of their leaf protective structures (i.e., high leaf consistency) and a long leaf longevity ([20]), while the semi-deciduous species have a lower leaf consistency and a shorter leaf longevity. Moreover, they have leaf morphological and anatomical differences between summer and winter leaves ([10]). Leaf longevity may be a source of variation in the relationship among the different leaf traits ([37]). Nevertheless, if the dry season lasts too long, water deficit may negatively affect Mediterranean evergreen species carbon assimilation, as a result of the lowest photosynthetic rates and leaf surface areas produced ([35]). Thus, plant survival in Mediterranean environments depends largely upon their capacity to photosynthesize and keep water loses lower than the supply. It is important to take into account the key role of leaf respiration when plants experience intense drought periods, since it has a critical function in modulating carbon balance ([45]). The effects of leaf respiration on gross photosynthesis, particularly under drought conditions ([16]) may allow more reliable climate change scenarios of ecosystem functioning.

In this context, the main goal of our research was to analyze the response of the evergreen species co-occurring in the Mediterranean maquis to seasonal variations in water availability and air temperature during the year. In particular, the effects of leaf respiration on gross photosynthesis were considered. The Mediterranean maquis is largely distributed in areas around the Mediterranean Basin and its structure and composition is strongly influenced by air temperature and water availability ([24]).

Material and methods 

Study area and plant materials

The study was carried out in the period January - December 2014 in the Mediterranean maquis inside the Presidential Estate of Castelporziano (SSW of Rome, Italy; 4° 45′ N, 12° 26′ E - ⇒ http:/­/­palazzo.­quirinale.­it/­residenze/­c_porziano_en.­html).

The Presidential Estate of Castelporziano is included in the “Natura 2000’’ network and is classified as a ZPS (Special Protection Area, “Tenuta Presidenziale”, IT603 0084) and a SIC (Sites of Community Importance) with two areas: “Querceti igrofili” (IT6030028) and “Fascia costiera” (IT6030027). The maquis under study was characterized by the presence of the following species: Arbutus unedo L., Phillyrea latifolia L., Pistacia lentiscus L., Quercus ilex L. (typical sclerophyllous species), Cistus incanus L. (drought semi-deciduous species), Erica arborea L., Erica multiflora L., Rosmarinus officinalis L. (narrow-leaves species), and Smilax aspera L. (liana - [20]).

The climate of the area is Mediterranean, with the mean minimum air temperature (Tmin) of the coldest months (February) of 3.7 ± 1.8 °C (mean ± SD), the mean maximum air temperature (Tmax) of the hottest months (August) 30.3 ± 1.4°C, and the mean yearly air temperature (Tm) 15.6 ± 5.9 °C. Total annual rainfall is 738 mm, mainly occurring in autumn and winter. Drought period is from the end of May to the beginning of September (60 mm in the period). During the study period, Tmin of the coldest month (March) was 5.0 ± 2.1°C, Tmax of the hottest month (August) 28.0 ± 2.4°C and the total rainfall during the drought period (from the end of July to the end of August) was 15 mm (Fig. 1). Weather and climate data (1985-2014) were obtained from the Meteorological Station located inside the Estate.

Fig. 1 - Monthly trend of air temperatures and total monthly rainfall during the study period (January - December 2014); (R): total monthly rainfall (Tmin): minimum air temperature; (Tmax): maximum air temperature; (Tm): mean air temperature.

Structural, morphological, anatomical and physiological leaf traits were measured on twelve representative shrubs per each of the considered species, randomly distributed in three representative areas (100 m2 each). Mature leaves were detached from the southern, upper portion of each shrub at the end of May 2014 for measurements.

Structural shrubs traits

Measurements of shrub structure included total height (HS, defined as the maximum vertical distance from the ground to the highest point of the shrub), height of the shrub crown (Ch, defined as the vertical distance from the lowest leaf insertion to the highest point of the shrub), depth of the shrub crown (CD, excluding the central non-foliated branch portion, according to [41]), major axis (A) and minor axis (a, orthogonal to A) of the shrub crown. Shrub volume (VS) was derived from the measured traits, by assigning simple geometric solids to shrub form, such as cone, semisphere and ellipsoid which appeared to give the best fit of the natural shape of the crown, according to Sternberg & Shoshany ([43]); the volume of the shrub crown (Vcrown) was calculated excluding the central non-foliated branch portion of shrub. For S. aspera was measured the length (ls).

Anatomical leaf traits

The following parameters were considered for leaf anatomical measurements (n = 3 leaves per shrub per species): total leaf lamina thickness (LT); palisade and spongy thickness; thickness of the upper and lower cuticle and epidermis (CET, µm). Measurements were restricted to vein-free areas. The fraction of mesophyll volume occupied by the intercellular air spaces (fias, %) was calculated according to Syvertsen et al. ([42]) as follows (eqn. 1):

\begin{equation} f_{ias} = 1-A_{m}/lW \end{equation}

where Am is the cross-sectional area of the mesophyll cell, W the width of the measured section and l is the mesophyll thickness.

The following parameters were measured for stomata: guard cell length and width (LA and WB, respectively), according to Stojnić et al. ([44]), and the stomatal pore surface of stomata guard cell (SPSLAWB, µm2), according to Balasooriya et al. ([7]) as (eqn. 2):

\begin{equation} SPS_{LAWB} = (L_{A} \cdot W_{B} \cdot \pi) / 4 \end{equation}

The potential conductance index (PCI) was calculated according to Holland & Richardson ([26]), as follows (eqn. 3):

\begin{equation} PCI = L_{A}^{2} \cdot SD \cdot 10^{-4} \end{equation}

where SD is the stomatal density (stomata mm-2), measured from nail varnish impressions of the inferior lamina, according to Sack et al. ([40]), each of them 0.5 × 1.0 cm, obtained by a Zeiss Axiocam MRc 5® digital camera (Carl Zeiss, Jena, Germany), equipped with the software Axiovision AC® (release 4.5).

Morphological leaf traits

The following parameters were measured for leaf morphological measurements (n = 5 leaves per shrub per species): projected fresh leaf surface area excluding petioles (LA, cm2), obtained by the Image Analysis System® (Delta-T Devices, Burwell, UK) and leaf dry mass (DM, mg), drying leaves at 80 °C to constant mass.

Leaf mass per unit leaf area (LMA, mg cm-2) was calculated by the ratio of DM and LA and leaf tissue density (LTD, mg cm-3) by the ratio of LMA and total lamina thickness.

Gas exchange

Gas exchange measurements were carried out using an infrared gas analyzer (LCPro+®, ADC Bioscientific Ltd., Hoddesdon, UK) equipped with a conifer leaf chamber (PLC, Parkinson Leaf Chamber) for E. arborea, E. multiflora and R. officinalis, and with a broad leaf chamber (PLC) for Q. ilex, A.unedo, C. incanus, P. latifolia, P. lentiscus and S. aspera. Measurements were taken on fully expanded sun leaves (n = 6 per each sampling occasion for A. unedo, C. incanus, P. latifolia, P. lentiscus, Q. ilex, and S. aspera) and on sun apical shoots (n= 6 per each sampling occasion for E. arborea, E. multiflora and R. officinalis). Net photosynthetic rate (PN, µmol CO2 m-2 s-1), stomatal conductance (gs, mol H2O m-2 s-1), leaf transpiration (E, mmol H2O m-2 s-1), sub-stomatal CO2 concentration (Ci, μmol CO2 mol-1 air), leaf temperature (Tl, °C) and photosynthetic photon flux density (PPFD, µmol photons m-2 s-1) were measured from 9.00 to 11.00 a.m., under natural conditions, on cloud-free days (PPFD > 1000 µmol m-2 s-1, saturating level) to ensure that the near maximum daily photosynthetic rates were measured ([38]). The apparent carboxylation efficiency of Rubisco (PN/Ci, mol CO2 m-2 s-1) was determined according to Arena et al. ([2]).

Leaf dark respiration rate (RL, µmol CO2 m-2 s-1) measurements were carried out contemporary to photosynthesis measurements, by darkening the leaf chamber with a black paper for 30 min prior to each measurement to avoid transient post-illumination bursts of CO2 releasing. Measurements were carried out in four sampling days with the same weather conditions for each month.

Gross photosynthetic rates (PG, µmol CO2 m-2 s-1) were calculated as the sum of the average values for PN, photorespiration and RL, based on the assumption that RL (excluding photorespiration) were similar in the light and in the dark ([46]). Photorespiration rates (Pr, µmol CO2 m-2 s-1) were evaluated considering that under natural conditions C3 plants lose about 20% of the photosynthetically acquired CO2 in the form of photorespiratory CO2 ([30]). Total yearly PN and RL (PNy and RLy, respectively) were calculated on the basis of the daily photosynthetic and respiratory activity, according to Van Iersel ([46]), extending data over the whole year. The ratio RL/PG was calculated according to Chastain et al. ([14]). Total yearly PG (PGy) and the fraction of total yearly RLy on PGy (RLy/PGy) were also calculated.

Leaf water status

Leaf water potential at pre-dawn (Ψpd) was measured on leaves of A. unedo, C. incanus, P. latifolia, P. lentiscus, Q. ilex, and S. aspera and on shoots of E. arborea, E. multiflora, R. officinalis (five leaves and five apical shoots per species, respectively, per each sampling occasion). Ψ measurements were carried out using a portable pressure chamber (SKPM 1400®, Skye Instruments, Llandrindod Wells, Powys, UK). Relative water content at pre-dawn (RWCpd) was calculated at the same time and on the same leaves used for Ψ measurements as (eqn. 4):

\begin{equation} RWC = {\frac{ FM - DM} { TM - DM}} \cdot 100 \end{equation}

where FM is the leaf fresh mass, DM the leaf mass after drying at 90 °C until constant mass was reached, and TM the leaf mass after rehydration until saturation for 48 h at 5 °C in the darkness ([6]). Ψpd and RWCpd measurements were carried out in April and May (during the favorable period) and in August (during drought), simultaneously with gas exchange measurements.

Statistical analysis

All statistical tests were performed using the software package Statistica® v. 10.0 (Statsoft Inc., Tulsa, OK, USA).

The differences in physiological leaf traits were determined by the analysis of variance (ANOVA) and the post-hoc Tukey’s test for multiple comparisons (α ≤ 0.05). Data were tested for normality and homogeneity of variances before carrying out the statistical analysis, with α ≤ 0.05.

A Partial Least Squares Regression analysis (PLS) was carried out to explore the pattern of co-variation between morphological and physiological leaf traits and to establish the order of the variable importance (i.e. VIP). PLS was carried out using the structural leaf traits (LMA, LTD, LT, CET, PCI and fias) as predictor variables and physiological traits (PN, RL, RL/PG, Ψ and RWC) as the response variables.


Structural shrub traits

Structural shrub traits of the considered species are shown in Tab. 1. In particular, among the species analyzed, E. arborea showed the highest HS (1.72 ± 0.24 m) and C. incanus the lowest (0.76 ± 0.11 m). Q. ilex was the species with the highest VS and Vcrown values (7.16 ± 5.20 m3 and 2.72 ± 1.24 m3, respectively), while C. incanus the lowest ones (0.32 ± 0.24 m3 and 0.20 ± 0.12 m3, respectively).

Tab. 1 - Mean values and standard deviation of shrub height (Hs, m), shrub volume (VS, m3) and volume of shrub crown (Vcrown, m3) in the considered species (n =12).

Anatomical and morphological leaf traits

E. arborea showed the lowest LT (200 ± 19 µm), followed by C. incanus (217 ± 9 µm), P. lentiscus (254 ± 18 µm), A. unedo (300 ± 20 µm), Q. ilex, P. latifolia and S. aspera (316 ± 5 µm, mean value) and by R. officinalis and E. multiflora (335 ± 7 µm).

CET was the highest in P. latifolia (43 ± 3 µm), followed by E. multiflora (41 ± 2 µm), A. unedo (35 ± 4 µm), E. arborea and R. officinalis (26 ± 3 µm, mean value), S. aspera (25 ± 2 µm), Q. ilex (22 ± 1 µm), P. lentiscus (16 ± 2 µm) and C. incanus (14 ± 2 µm).

A. unedo and C. incanus showed the highest fias (37 ± 1 %, mean value), followed by P.lentiscus, Q. ilex and P. latifolia (31 ± 3 %, mean value), R. officinalis, E. multiflora and E. arborea (26 ± 1 %, mean value) and S. aspera (15 ± 3%).

SPSLAWB and PCI varied significantly among the considered species (Tab. 2), P. latifolia having the highest SPSLAWB (574 ± 96 µm2) and E. arborea the lowest one (155 ± 21 µm2). Q. ilex had the highest PCI (31.2 ± 3.0) while R. officinalis, E. multiflora and E. arborea the lowest (6.0 ± 0.5, mean value).

Tab. 2 - Mean values and standard deviation of stomatal pore surface of stomata guard cell (SPSLAWB, μm2) and potential conductance index (PCI) in the considered species (n = 36). Mean values with the same letters are not significantly different after Tukey’s test (P ≥ 0.05).

Morphological leaf traits varied significantly among the considered species (Tab. 3). In particular, LMA value ranged from 26.3 ± 1.7 mg cm-2 (E. multiflora) to 12.0 ± 1.1 mg cm-2 (E. arborea) and LTD from 760 ± 23 mg cm-3 (E. multiflora) to 355 ± 32 mg cm-3 (S. aspera).

Tab. 3 - Mean values and standard deviations of leaf mass per area (LMA, mg cm-2) and leaf tissue density (LTD, mg cm-3) in the considered species (n = 60). Mean values with the same letters are not significantly different after Tukey’s test (P ≥ 0.05).

Gas exchange

The considered species had the same RL trend during the year. The lowest rates were measured in winter (January-February: 0.95 ± 0.44 μmol m-2 s-1, mean value) and the highest in August (3.05 ± 0.96 μmol m-2 s-1, mean value). In particular, R. officinalis had the highest RL in August (4.5 ± 1.6 μmol m-2 s-1) and P. latifolia the lowest (1.58 ± 0.05 μmol m-2 s-1).

The species analyzed shared the same PG trend during the year (Fig. 2), though some differences were observed. A relatively low PG value (12.4 ± 4.3 μmol m-2 s-1, mean value) was monitored in winter (January-February), R. officinalis having the lowest rate (7.9 ± 1.2 μmol m-2 s-1) and C. incanus the highest (19.0 ± 3.7 μmol m-2 s-1). The highest PG (22.0 ± 7.1 μmol m-2 s-1, mean value) was measured in April-May, C. incanus having the highest PG (39.5 ± 1.3 µmol m-2 s-1), followed by A. unedo, Q. ilex, P. latifolia and P. lentiscus (22.6 ± 7.7 µmol m-2 s-1, mean value), S. aspera, R. officinalis, E. multiflora and E. arborea (17.3 ± 2.0 µmol m-2 s-1, mean value). A 61% PG decrease (mean value) than the spring maximum was monitored in August (i.e., during drought), with C. incanus and S. aspera having the highest PG decrease (79%, mean value) and P. latifolia the lowest (46%). After the first rainfall, at the beginning of September, PG increased, on average, by 92%, S. aspera having the highest increase (> 100%).

Fig. 2 - Trend of leaf gross photosynthesis (PG, µmol CO2 m-2 s-1) during the study period for the considered species. Each point is the mean value of four sampling days per months (n = 24). Mean values (points) and standard deviation (error bars) are shown.

PGy for the considered species are shown in Fig. 3. In particular, C. incanus showed the highest PGy (412 ± 20 mol m-2), followed by Q. ilex, A. unedo, P. latifolia and P. lentiscus (314 ± 37 mol m-2, mean value), S. aspera, E. arborea, E. multiflora and R. officinalis (208 ± 13 mol m-2, mean value). The ratio RLy/PGy was the highest in R. officinalis (28%), followed by E. multiflora and E.arborea (16%), C. incanus (13%), S .aspera (12%), Q. ilex, P. latifolia and P. lentiscus (11%, mean value) and A. unedo (5%).

Fig. 3 - Mean values and standard deviation (error bars) of yearly gross photosynthesis (PGy, mol CO2 m-2) in the considered species (n= 12). Mean values with the same letters are not significantly different after Tukey’s test (P ≥ 0.05).

Among all the species, the lowest RL/PG ratio (0.07 ± 0.03, mean value) was monitored in winter and the highest in August (0.40 ± 0.15, mean value). R. officinalis had the highest ratio (0.65 ± 0.06) and A. unedo the lowest (0.22 ± 0.03 - Fig. 4).

Fig. 4 - Trend of the ratio of leaf respiration to gross photosynthesis (RL/PG) during the study period. Each point is the mean value of four sampling days per months (n = 24). Error bars represent the standard deviation.

Trend of apparent carboxylation efficiency is reported in Fig. 5. During the study period, the highest CE was monitored, in all the considered species, in April-May (0.080 ± 0.025 mol m-2 s-1, mean value) and the lowest in August (0.016 ± 0.007 mol m-2 s-1, mean value). The mean yearly CE value was the highest in C. incanus (0.063 ± 0.034 mol m-2 s-1) and the lowest in E. multiflora (0.026 ± 0.014 mol m-2 s-1).

Fig. 5 - Trend of the apparent carboxylation efficiency (CE, mol CO2 mol-1 CO2) during the study period. Each point is the mean value of four sampling days per months (n = 24). Error bars represent the standard deviation.

Trends of stomatal conductance and transpiration rates are displayed in Fig. 6 (A, B). In particular, gs showed the same PN trend with the highest rates in April-May (0.140 ± 0.06 mmol m-2 s-1, mean value) and the lowest in August (0.028 ± 0.011 mmol m-2 s-1, mean value). The lowest E value were monitored in winter (January-February) in all the considered species (0.639 ± 0.143 mol m-2 s-1, mean value).

Fig. 6 - Trend of (A) stomatal conductance (gs, mol H2O m-2 s-1) and (B) transpiration rates (E, mmol H2O m-2 s-1) during the study. Each point is the mean value of four sampling days per months (n = 24). Error bars represent the standard deviation.

Leaf water status

The highest Ψpd were measured in April-May (-0.11 ± 0.03 MPa, mean value), A. unedo and E. multiflora having the highest Ψpd (-0.07 ± 0.02 MPa, mean value) and R. officinalis the lowest (-0.15 ± 0.01 MPa). Ψpd decreased in August (-0.89 ± 0.31, mean value) P. lentiscus having the highest value (-0.40 ± 0.09 MPa) and R. officinalis the lowest (-1.50 ± 0.05 MPa).

RWCpd followed the same trend showed by Ψpd during the study period, with the highest values in April-May (93.2 ± 1.1 % mean values) and a significant decrease in August. Q. ilex, P. latifolia, P. lentiscus and A. unedo had the highest values (92.0 ± 1.1 %) and R. officinalis the lowest (78 ± 4 %).

Partial least squares regression

PLSR extracted two significant components which explained 24.1 % (component 1) and 20.5 % (component 2) of the original variance in the physiological variables, respectively (Tab. 4). In particular, component 1 was mainly associated to fias and PCI, while component 2 was mainly associated to LTD and CET. fias and PCI had the highest VIP (0.548 and 0.520, respectively), followed by LTD (0.370), LT (0.364), CET (0.326) and LMA (0.260).

Tab. 4 - Weights of each structural trait in the component 1 and 2 extracted by the Partial Least Squares Regression (PLSR), and variable influence on projection (VIP) values for traits in the component 1. PLSR was carried out with structural traits as predictor variables and physiological traits as response variables. (LMA): leaf mass per unit leaf area; (LTD): leaf tissue density; (PCI): potential conductance index; (fias): fraction of mesophyll volume occupied by the intercellular air spaces; (LT): total leaf lamina thickness; (CET): thickness of both upper and lower cuticle and epidermis.

Moreover, since a high VIP was found for PCI, a simple linear regression analysis was carried out to analyze the relationship between PCI and its components (i.e., LA and SD). The results showed that PCI was significantly correlated with SD (PCI = 0.0688 SD - 2.3879; R2 = 0.68; P ≤ 0.05) while any significant relationship was found between PCI and LA (PCI = 0.9423 LA - 8.5206; R2 = 0.33; P > 0.05)


Drought resistance in Mediterranean plant species is realized by different traits or combination of traits ([23]). Our results highlight that leaf structural traits can be considered driving factors for physiological traits. This is confirmed by PLS which showed that structural and physiological traits co-vary. Structural trait variations explained 44.61 % of the total variance in PN, RL, RL/PG, Ψ and RWC. The most important structural variables in the physiological trait projection are fias and PCI, from which the internal CO2 diffusion pattern mainly depends ([36]). Photosynthesis and respiration are the most fundamental physiological processes which affect the carbon cycle on a scale ranging from the leaf to the globe ([13]). Moreover, it is recognized that leaf respiration changes are related to physiological factors ([4]) as well as environmental factors, in particular temperature and water availability ([15]). To date, the RL behavior during drought is still unclear, since RL has been found to either increase or decrease depending on the severity of drought stress and the species ([32]).

Overall, our results show a similar RL response across the considered species, with the lowest rates in winter (0.95 ± 0.44 µmol m-2 s-1, mean value) and the highest in the dry period (3.05 ± 0.96 µmol m-2 s-1, mean value). This finding supports the hypothesis that RL increases under drought, which may reflect an enhanced leaf senescence, solute accumulation and energy dissipation by the mitochondria to prevent oxidative damage by excess reductants from light reactions ([3]). The metabolic damages under drought requires a surplus of respiratory products (i.e., ATP and reducing equivalents - [47]). Thus, RL increases to meet the demand for higher ATP levels ([3]). Nevertheless, a different RL impact on gross photosynthesis (i.e., RL/PG) under drought was observed among the considered species. In particular, C. incanus, E. multiflora, R. officinalis and S. aspera show the highest RL/PG (0.54 ± 0.08, mean value) due to a higher RL (3.31 ± 1.02 µmol m-2 s-1, mean value) associated to the highest PN decrease under drought (by 84%, mean value). Differences among the species in RL/PG are also related to a different PN sensitivity to drought, which has a higher inhibitory effect on photosynthesis than on respiration ([16]). The higher PN sensitivity to drought is also confirmed by the thermal windows analysis which highlights that PN drops below half of its maximum when leaf temperature is above 33.4 °C (mean value of the species - [23], [11]). Moreover, Ψpd which can be considered a powerful indicator of drought stress ([28]) varies from -1.30 ± 0.27 MPa in August to -0.11± 0.04 MPa in May (mean of the considered species) associated to a 10% RWCpd decrease in August. R. officinalis, C. incanus, and E. multiflora show a lower capacity to adjust photosynthesis in drought also due to their shallow root system ([1]), which entails only the access to the superficial soil profile subjected to large changes in water content ([5]). The response of R. officinalis to drought may also be explained by 87% gs decrease and the lowest PCI (5.5 ± 1.4) which depends on both stomatal density (SD = 168 ± 23 stomata mm-2) and size (SPSLAWB= 219 ± 47µm2). This indicates a low capacity of R. officinalis to regulate stomatal conductance ([26]). Moreover, the higher CE decrease (by 87%), indicating a lower Rubisco activity, suggests that in addition to a stomatal limitation, there are a non-stomatal limitation of photosynthesis according to Llorens et al. ([31]). On the contrary, Q. ilex, P. latifolia, P. lentiscus, A. unedo and E. arborea are characterized by a lower RL/PG (0.22 ± 0.05, mean value) under drought, resulting from a lower RL (2.55 ± 0.52 µmol m-2 s-1, mean value) and a lower PN decrease (62% of the maximum, mean value). The sclerophyllous species and E. arborea have a sufficiently higher Ψpd (-0.64 ± 0.21 MPa, mean value) and RWCpd (92 ± 2%, mean value), reflecting their deep root system which accesses water from those parts of the soil profile subjected to narrow changes in water content ([23]). Moreover, the higher LMA and LTD of these species (17.4 ± 3.5 mg cm-2 and 523 ± 73 mg cm-3, mean value, respectively) result in a higher leaf compactness which improves drought resistance. This behavior was also attested by the thermal windows analysis showing that PN drops below half of its maximum when leaf temperature is above 37.0 °C (mean value of the species - [23]). A. unedo displays several mechanisms of drought stress resistance ([34]). It is functionally adapted to cope with the summer drought by its stomatal regulation to which contributes a higher PCI (18.2 ± 2.8) and the steeper leaf inclination angle ([22]), a mechanism which prevents the potential photo-inhibition of water-stressed leaves during drought ([49]).

With regards to PGy (i.e., the daily photosynthetic and respiratory activity over the year), C. incanus had the highest PGy and R. officinalis and E. multiflora the lowest. In particular, C. incanus maintains a relatively high RL in spring necessary to produce summer leaves ([10], [12]). The higher PN in C. incanus is reflected by a higher fias (38%) and a lower LMA (15.1 ± 0.7 mg cm-2), which result from a shorter diffusion path from stomata to chloroplasts ([23]). Moreover, this is consistent with the high CE (0.063 ± 0.034 mol m-2 s-1, mean value of the study period) compared to the others species, according to the results of Arena et al. ([2]), considering that the apparent carboxylation efficiency is usually correlates with Rubisco activity ([48]). On the contrary, the lowest PGy in R. officialis and in E. multiflora mainly reflects the low PN during the year, as a consequence of the low CE value (0.031 ± 0.007 mol m-2 s-1, mean value) and the lower fias (26 ± 1%, mean value), associated to a higher LMA and LTD (23.6 ±3.9 mg cm-2 and 670 ±127 mg cm-3 mean value, respectively).


The results of this study revealed similar RL trends across the considered species over the year. Nevertheless, large RL/PG variations among the species depend on the different sensitivity of both RL and PN to drought. Considering the increase of drought stress which is expected to occur in the Mediterranean basin and that the photosynthesis of Mediterranean evergreen species is frequently limited by sub-optimal conditions (i.e., water deficit, high light intensity and high temperature), improving the knowledge of leaf respiration variations and its effect on gross photosynthesis over time will result in a more accurate estimation of carbon balance.


Amato M, Sarnataro M (2001). Root analysis of maquis at Castel Volturno, Italy. In: “ModMED: Modelling Mediterranean Ecosystem Dynamics” (Mazzoleni S, Colin CJ eds). Final Report ModMED III Project, EU-DGXII Environment (IV) Framework, ENV4-ct97-0680, Bussels, Belgium, pp. 110-120.
::Google Scholar::
Arena C, De Micco V, De Maio A, Mistretta C, Aronne G, Vitale L (2013). Winter and summer leaves of Cistus incanus: differences in leaf morphofunctional traits, photosynthetic energy partitioning, and poly(ADP-ribose) polymerase (PARP) activity. Botany 91: 1-9.
::CrossRef::Google Scholar::
Atkin OK, Macherel D (2009). The crucial role of plant mitochondria in orchestrating drought tolerance. Annals of Botany 103: 581-597.
::CrossRef::Google Scholar::
Atkin OK, Westbeek MHM, Cambridge ML, Lambers H, Pons TL (1997). Leaf respiration in light and darkness (a comparison of slow-and fast-growing Poa species). Plant Physiology 113: 961-965.
::Online::Google Scholar::
Aubert G (1978). Relations entre le sol et cinq espécies d’ericacées dans le Sud-est de la France [Relationship between soil and five Ericaceae species in the South-Est of France]. Oecologia Plantarum 13: 253-269. [in French]
::Google Scholar::
Bacelar EA, Santos DL, Moutinho-Pereira JM, Lopes JI, Gonçalves BC, Ferreira TC, Correia CM (2007). Physiological behaviour, oxidative damage and antioxidative protection of olive trees grown under different irrigation regimes. Plant and Soil 292: 1-12.
::CrossRef::Google Scholar::
Balasooriya BLWK, Samson R, Mbikwa F, Vitharana UWA, Boeckx P, Van Meirvenne M (2009). Biomonitoring of urban habitat quality by anatomical and chemical leaf characteristics. Environmental and Experimental Botany 65: 386-394.
::CrossRef::Google Scholar::
Brunetti M, Maugeri M, Nanni T, Navarra A (2002). Droughts and extreme events in regional daily Italian precipitation series. International Journal of Climatology 22: 543-558.
::CrossRef::Google Scholar::
Castro-Díez P, Villar-Salvador P, Pérez-Rontomé C, Maestro-Martínez M, Montserrat-Martí G (1998). Leaf morphology, leaf chemical composition and stem xylem characteristics in two Pistacia (Anarcardiaceae) species along climatic gradient. Flora 193: 195-202.
::Google Scholar::
Catoni R, Gratani L, Varone L (2012). Physiological, morphological and anatomical trait variations between winter and summer leaf of Cistus species. Flora 207: 442-449.
::CrossRef::Google Scholar::
Catoni R (2013). Carbon balance of mediterranean evergreen species. Ph.D. thesis, Ecological Science, “Sapienza” University of Rome, Rome, Italy, pp. 51.
::Google Scholar::
Catoni R, Gratani L (2014). Variations in leaf respiration and photosynthesis ratio in response to air temperature and water availability among Mediterranean evergreen species. Journal of Arid Environment 102: 82-88.
::CrossRef::Google Scholar::
Cavaleri MA, Oberbauer SF, Ryan MG (2008). Foliar and ecosystem respiration in an old-growth tropical rain forest. Plant Cell and Environment 31: 473-483.
::CrossRef::Google Scholar::
Chastain DR, Snider JL, Collins GD, Perry CD, Whitaker J, Byrd SA (2014). Water deficit in field-grown Gossypium hirsutum primarily limits net photosynthesis by decreasing stomatal conductance, increasing photorespiration, and increasing the ratio of dark respiration to gross photosynthesis. Journal of Plant Physiology 171: 1576-1585.
::CrossRef::Google Scholar::
Crous KY, Zaragoza-Castells J, Löw M, Ellsworth DS, Tissue DT, Tjoelker MG, Barton CVM, Gimeno TE, Atkin OK (2011). Seasonal acclimation of leaf respiration in Eucalyptus saligna trees: impacts of elevated atmospheric CO2 and summer drought. Global Change Biology 17: 1560-1576.
::CrossRef::Google Scholar::
Flexas J, Galmés J, Ribas-Carbo M, Medrano H (2005). The effects of water stress on plant respiration. In: “Plant respiration: from cell to ecosystem” (Lambers H, Ribas-Carbo M eds). Kluwer Academic Publishers, Springer, Dordrecht, Netherlands, vol. 18, pp. 85-94.
::CrossRef::Google Scholar::
Galmés J, Ribas-Carbó M, Medrano H, Flexas J (2007). Response of leaf respiration to water stress in Mediterranean species with different growth forms. Journal of Arid Environment 68: 206-222.
::CrossRef::Google Scholar::
Giannakopoulos C, Le Sager P, Bindi M, Moriondo M, Kostopoulou E, Goodess CM (2009). Climatic changes and associated impacts in the Mediterranean resulting from a 2 °C global warming. Global and Planetary Change 68: 209-224.
::CrossRef::Google Scholar::
Goubanova K, Li L (2007). Extremes in temperature and precipitation around the Mediterranean basin in an ensemble of future climate scenario simulations. Global and Planetary Change 57: 27-42.
::CrossRef::Google Scholar::
Gratani L, Crescente MF (1997). Phenology and leaf adaptive strategies of Mediterranean maquis plants. Ecologia Mediterranea 23 (3/4): 11-19.
::Google Scholar::
Gratani L, Bombelli A (2000). Correlation between leaf age and others leaf traits in three Mediterranean maquis shrub species: Quercus ilex, Phillyrea latifolia and Cistus incanus. Environmental and Experimental Botany 43: 141-153.
::CrossRef::Google Scholar::
Gratani L, Ghia E (2002). Adaptive strategy at the leaf level of Arbutus unedo L. to cope with Mediterranean climate. Flora 197: 275-284.
::CrossRef::Google Scholar::
Gratani L, Varone L (2004). Adaptive photosynthetic strategies of the Mediterranean maquis species according to their origin. Photosynthetica 42: 551-558.
::CrossRef::Google Scholar::
Gratani L, Varone L, Ricotta C, Catoni R (2013). Mediterranean shrublands carbon sequestration: environmental and economic benefits. Mitigation Adaptations Strategies of Global Change 18: 1167-1182.
::CrossRef::Google Scholar::
Hamann A, Wang T (2006). Potential effects of climate change on ecosystem and tree species distribution in British Columbia. Ecology 87: 2773-2786.
::CrossRef::Google Scholar::
Holland N, Richardson AD (2009). Stomatal length correlates with elevation of growth in four temperate species. Journal of Sustainable Forestry 28: 63-73.
::CrossRef::Google Scholar::
IPCC (2014). Summary for policymakers. In: “Climate Change 2014: Impacts, Adaptation, and Vulnerabil-ity. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change” (Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL eds). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32.
::Google Scholar::
Jones HG (2007). Monitoring plant and soil water status: established and novel methods revisited and their relevance to studies of drought tolerance. Journal of Experimental Botany 58: 119-130.
::CrossRef::Google Scholar::
Karabourniotis G (1998). Light-guiding function of foliar sclereids in the evergreen sclerophyll Phillyrea latifolia: a quantitative approach. Journal of Experimental Botany 49: 739-746.
::CrossRef::Google Scholar::
Larcher W (2003). Physiological plant ecology. Springer-Verlag, Berlin, Heidelberg, Germany, pp. 514.
::Online::Google Scholar::
Llorens L, Peñuelas J, Estiarte M (2003). Ecophysiological responses of two Mediterranean shrubs, Erica multiflora and Globularia alypum, to experimentally drier and warmer conditions. Physiologia Plantarum 119: 231-243.
::CrossRef::Google Scholar::
Loka D, Oosterhuis D, Ritchie G (2011). Water-deficit stress in cotton. In: “Stress physiology in cotton” (Oosterhuis DM eds). The Cotton Foundation, Cordova, TN, USA, pp. 37-72.
::Google Scholar::
Moretti V, Di Bartolomei R, Sorgi T, Aromolo R, Salvati L (2015). Soil water deficit and climate conditions during the dry season along the coastal-inland gradient in Castelporziano forest, central Italy. Rendiconti Lincei Scienze Fisiche e Naturali 26: 283-288.
::CrossRef::Google Scholar::
Munné-Bosch S, Peñuelas J (2004). Drought-induced oxidative stress in strawberry tree (Arbutus unedo L.) growing in Mediterranean field conditions. Plant Science 166: 1105-1110.
::CrossRef::Google Scholar::
Pereira JS, Mateus JA, Aires LM, Pita G, Pio C, David JS, Andrade V, Banza J, David TS, Paço TA, Rodrigues A (2007). Net ecosystem carbon exchange in three contrasting Mediterranean ecosystem’the effect of drought. Biogeosciences 4: 791-802.
::CrossRef::Google Scholar::
Puglielli G, Crescente MF, Frattaroli AR, Gratani L (2015). Leaf Mass Per Area (LMA) as a possible predictor of adaptive strategies in two species of Sesleria (Poaceae): analysis of morphological, anatomical and physiological leaf traits. Annales Botanici Fennici 52 (1-2): 135-143.
::CrossRef::Google Scholar::
Reich PB, Uhl C, Walters MB, Ellsworth DS (1991). Leaf lifespan as a determinant of leaf structure and function among 23 tree species in Amazonian forest communities. Oecologia 86: 16-24.
::CrossRef::Google Scholar::
Reich PB, Ellsworth DS, Walters MB, Vose JM, Gresham C, Volin JC, Bowman WD (1999). Generality of leaf trait relationships: A test across six biomes. Ecology 80: 1955-1969.
::CrossRef::Google Scholar::
Rotondi A, Rossi F, Asunis C, Cesaraccio C (2003). Leaf xeromorphic adaptations of some plants of a coastal Mediterranean macchia ecosystem. Journal of Mediterranean Ecology 4 (3/4): 25-35.
::Online::Google Scholar::
Sack L, Grubb PJ, Marañón T (2003). The functional morphology of juvenile plants tolerant of strong summer drought in shaded forest under stories in southern Spain. Plant Ecology 168: 139-163.
::CrossRef::Google Scholar::
Schulze ED, Fuchs MI, Fuchs M (1977). Spacial distribution of photosynthetic capacity and performance in a mountain spruce forest on northern Germany. I. Biomass distribution and daily CO2 uptake in different crown layers. Oecologia 29: 43-61.
::CrossRef::Google Scholar::
Syvertsen JP, Lloyd J, McConchie C, Kriedemann PE, Farqhar GD (1995). On the relationship between leaf anatomy and CO2 diffusion through the mesophyll of hypostomatous leaves. Plant Cell and Environment 18: 149-157.
::CrossRef::Google Scholar::
Sternberg M, Shoshany M (2001). Influence of slope aspect on Mediterranean woody formations: comparison of a semiarid and an arid site in Israel. Ecological Research 16: 335-345.
::CrossRef::Google Scholar::
Stojnić S, Orlović S, Trudić B, Zivković U, Von Wuehlisch G, Miljković D (2015). Phenotypic plasticity of European beech (Fagus sylvatica L.) stomatal features under water deficit assessed in provenance trial. Dendrobiology 73: 163-173.
::CrossRef::Google Scholar::
Sun J, Wu J, Guan D, Yao F, Yuan F, Wang A, Jin C (2014). Estimating daytime ecosystem respiration to improve estimates of gross primary production of a temperate forest. PLoS ONE 9 (11): e113512.
::CrossRef::Google Scholar::
Van Iersel MW (2003). Carbon use efficiency depends on growth respiration, maintenance respiration, and relative growth rate. A case study with lettuce. Plant Cell and Environment 26: 1441-1449.
::CrossRef::Google Scholar::
Varone L, Gratani L (2015). Leaf respiration responsiveness to induced water stress in Mediterranean species. Environmental and Experimental Botany 109: 141-150.
::CrossRef::Google Scholar::
Von Caemmerer S (2000). Biochemical models of leaf photosynthesis. CSIRO Publishing, Collingwood, Victoria, Australia, pp. 165.
::Online::Google Scholar::
Werner C, Correia O, Beyschlag W (1999). Two different strategies of Mediterranean macchia plants to avoid photoinhibitory damage by excessive radiation levels during summer drought. Acta Oecologica 20: 15-23.
::CrossRef::Google Scholar::


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Gratani L, Catoni R, Varone L (2016).
Evergreen species response to Mediterranean climate stress factors
iForest - Biogeosciences and Forestry 9: 946-953. - doi: 10.3832/ifor1848-009
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Paper ID# ifor1848-009
Title Evergreen species response to Mediterranean climate stress factors
Authors Gratani L, Catoni R, Varone L
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