The study area is a forest stand located in the Montsant mountain range (41° 19’ 47.3’’ N, 0° 50’ 2.6’’ E, 750 m a.s.l), in the northeast of the Iberian Peninsula. The climate in the region is Mediterranean temperate with continental tendency, with a mean annual precipitation of 517 mm and mean annual temperature of 12.3 °C. It is characterized by a dry and a relatively warm summer (mean summer precipitation of 89.5 mm, mean average temperature of 20.9 °C; averaged data of the two nearest meteorological stations with a long-term record (period 1970-2000), El Vilosell and Bisbal de Falset, each located at aprox. 11 km distance from the sampling site (AEMET-IM, 2011)). Year-to-year climate variability at this location is high with extreme drought events occurring every few years, a typical feature of the Mediterranean climate. The forest stand is a dense woodland community co-dominated by two typical Mediterranean trees, Holm oak and Aleppo pine. It is the result of natural regeneration of pine and oak in a former agricultural terrace which, according to the age of some individuals, was abandoned about 80 years ago. Understory vegetation is relatively scarce and current regeneration from both species is rare; thus, only adult pines and oaks with diameter at breast height (dbh) above 10 cm were included in the study. Stand density (dbh>10 cm) was 560 and 863 stems/ha for oak and pine respectively. We considered stem clumps of Q. ilex that seemingly derived from the same stool as single individuals. These sprout clumps were relatively common (about 1/3 of individuals), making stool density of Q. ilex considerably lower than stem density (370 stools/ha).

The rectangular plot area (24 x 37 m) had a strong slope (15-22%) facing west (X-axis), together with a gentle slope (3-7%) facing south (Y-axis). According to USDA soil taxonomy (Soil Survey Staff, 2010), soil is a loamy-skeletal, carbonatic, termic, active calcic pachic haploxeroll, with soil depths ranging from ca. 50 cm in the lower parts of the plot to ca. 20 cm in the upper part of the plot.

Field sampling took place on the 9^th September 2011, at the end of an exceptionally dry, but moderately warm, summer (summer precipitation of 23 mm, mean summer temperature of 21.5 °C, data from Ulldemollins, a recently established automatic meteorological station, only 3.5 km away from the site) (Figure 1). We sampled sun-exposed twigs from the 33 oaks and 78 pines with dbh>10 cm. After removing the bark and phloem, the xylem of the twigs was placed into cap vials, immediately frozen in dry ice and kept until water extraction using a cryogenic vacuum distillation line (Dawson et al., 1993). Six soil samples were also collected from the topsoil layer (2-10 cm, A horizon) and from 5 cm above the maximum soil depth (subsoil, up to 19-33 cm depending on the sample, B horizon), and similarly handled for water extraction. Water isotope ratios of hydrogen and oxygen of the xylem and soil water were determined using a Picarro Water Analizer L2130-i (Picarro Inc., Santa Clara, California). They were expressed in delta (δ) notation (‰) relative to V-SMOW (i.e. isotopic composition of oxygen, δ¹⁸O, and hydrogen, δ²H). Raw values were calibrated against three internal laboratory references (calibrated against IAEA standards VSMOW2, SLAP2 and GISP). Overall uncertainty (determined as the standard error of repeated analyses (N=20) of a reference sample not included in the calibration) was 0.05‰ and 0.17‰, for δ¹⁸O and δ²H, respectively. The potential presence of organic contaminants was checked using the post-processing software Picarro ChemCorrect 1.2.0, giving in all cases negative results.

Tree position for spatial analysis was determined using a high resolution GPS technology (GeoExplorer 6000 Series Handheld, Trimble Navigation Limited, California, USA) with spatial error inferior to 20 cm for latitude and longitude and to 40 cm for altitude. Tree coordinates were re-checked in the field with the aid of a measuring tape.

Isotope data (δ¹⁸O and δ²H) and one tree dendrometric characteristic (individual basal area, BA) were subjected to mixed model analysis of covariance (ANCOVA) considering a fixed effect for species (pine, oak) and the variation along the X and Y axes of the two-dimensional space (covariates), allowing for heterogeneity of regression slopes at the species level. This was done to check for (possible) differential systematic variation in the response variables following X and Y directions, i.e. anisotropic effects. We also allowed for heterogeneity of residual variances at the species level, which was checked by means of log likelihood ratio tests. For the difference between two nested models (homocedastic and heterocedastic), minus two times the log likelihood ratio follows, under the null hypothesis, asymptotically a χ² distribution with one degree of freedom (difference in the number of variance components; Verbeke & Molenberghs, 2000).

To analyse the spatial structure of Q. ilex and P. halepensis, we used spatial correlation functions derived from point process theory. A spatial point process is a stochastic mechanism that generates a countable set of events x _i in a bounded region A (see, for instance, Diggle, 2003). Any sequence of events, which can be seen as points on a given region, can be explained by point process theory, and one of the most common applications is the study of point occurrences in the Euclidean plane (e.g. individual trees in a forest stand) (Stoyan & Penttinen, 2000).

To study the spatial structure of trees (point locations) we used the pair correlation function (Illian et al., 2008), an estimator of which can be obtained as

The analysis of isotopic compositions of water extracted from soil samples showed a decreasing trend along the soil profile. In particular, the topsoil was significantly more enriched (δ¹⁸O = 0.2±1.2 ‰; δ²H = 34.6 ± 3.8 ‰) than the subsoil (δ¹⁸O = -3.0 ± 2.4 ‰; δ²H = –45.4 ± 8.5 ‰) (P = 0.019 and P = 0.035 for δ¹⁸O and δ²H, respectively; two-tailed, paired t-test). In addition, the variability found among soil samples taken in the subsoil (ranging from 19 to 33 cm depending on digging point) was mostly explained by soil depth (δ¹⁸O = 20.3–2.2 × depth(m), R ² = 0.85, P = 0.02; δ²H = 3.1 – 0.52 × depth(m), R ² = 0.67, P = 0.07). Conversely, we did not find any significant correlation between the isotopic composition of soil water and X or Y coordinates, neither for the topsoil nor for the subsoil. The range of values of xylem water for each species (δ¹⁸O = –7.4 to + 3.0‰ and δ²H = –61.5 to –7.0‰ in pines; δ¹⁸O = –8.1 to –2.6‰ and δ²H = –67.8 to –41.6‰ in oaks) was comparable, although in some cases exceeded the range observed in soil samples, particularly for δ²H (δ¹⁸O = –5.7 to + 1.7 ‰; δ²H = –55.7 to –28.5‰).

ANCOVAs revealed significant differences between pines and oaks (–1.2 ± 0.18‰ and -5.3 ± 0.15‰, respectively, for δ¹⁸O; –25.1 ± 0.78‰ and –54.3 ± 0.66‰, respectively, for δ²H), in addition to a progressive increase of both isotopes along the X axis that was significantly higher for Q. ilex (0.054‰ m^–1 and 0.155‰ m^–1, for pines and oaks, respectively, for δ¹⁸O; 0.248 ‰ m^–1 and 0.610 ‰ m^–1, for pines and oaks, respectively, for δ²H) (test of unequal slopes; Table 1). These results suggest the existence of spatial anisotropic effects for the xylem water isotopic compositions of oxygen and hydrogen.

Figure 2 shows the bivariate point pattern of Q. ilex and P. halepensis together with the resulting pair correlation functions (Eq. 1) and cross-pair correlation function (Eq. 2), and their respective fifth-largest and smallest envelope values based on 199 point configurations based on the null hypotheses, i.e. random labelling and Poisson point randomizations. Results suggest that both point configurations were at random, i.e. trees from the same species were independently located from each other, and that trees from distinct species were located at random from each other, thereby pointing to spatial independence between these two species in terms of individual tree location.

The spatial locations of Q. ilex and P. halepensis, along with individual tree BA in the area of study, are shown in Figure 3a. Visual inspection of bivariate marked point patterns did not provide much information about the spatial dependence of these two species. The resulting estimators of the mark correlation function (Eq. 3) for tree BA (Figure 3c and d) suggested that only the spatial structure of P. halepensis showed dependence, whereas no correlation was observed for Q. ilex. In particular, tree BA had negative correlation effects for P. halepensis as this empirical function lies down the lower envelope. There was evidence that trees at distances of less than two meters had smaller tree sizes than they should have under the hypothesis of random marking. Moreover, the resulting cross-mark correlation function (Eq. 4) for tree BA for both tree species (Figure 3b) suggested no inter-specific BA spatial correlation. Thus, tree size for a given species did not depend on the presence of the other species.

Visual inspection of the mark point pattern of Q. ilex and P. halepensis for the isotopic compositions of oxygen and hydrogen indicated increasingly higher values along the X-axis, suggesting the presence of anisotropic effects; this result was especially noticeable for Q. ilex (figure not included). This is in full agreement with the results obtained in the ANCOVAs. Because we observed directional components in the X-axis, i.e. anisotropic mark effects, and these effects affected the resulting estimated correlation functions, which are defined for isotropic (marked) point patterns, we considered a correction for such effects. Since the related point patterns were isotropic and only the mark component showed anisotropic effects, the use of inhomogeneous (anisotropic) versions of the point correlation functions based on a (non)parametric estimate of the point intensity (see, for instances, Law et al., 2009) were not of applicability. In the case of anisotropy in the marginal distribution of marks, these anisotropic effects should be incorporated in the mark correlation function by allowing this distribution to vary along this directional component. This could be done by assuming the mark expectation (say) to vary along this directional component. However, this approach is not trivial and few studies (if any) have corrected anisotropy for the mark component. Therefore, we adopted an easier procedure to correct mark anisotropic effects by considering the residuals of these variables (marks) after assuming a deterministic, species-dependent linear trend through this X-axis in accordance with the outcome of the ANOVAs. These residuals were also scaled to avoid negative values. The resulting marked point pattern of residuals is not affected by the linear trend and therefore ensures isotropy.

Figure 4 shows the resulting mark point pattern for δ¹⁸O residuals and the resulting mark correlation function, highlighting that water uptake strategies for P. halepensis were dependent on the spatial tree configuration. Particularly, pine trees had similar water uptake patterns at short inter-trees distances, and neighbouring trees at distances less than 4 meters tended to obtain more superficial (i.e. closer to topsoil values) water. Non-significant spatial dependencies were obtained for Q. ilex. In contrast, the cross-mark correlation function for this isotope showed spatial independence between both tree species (see Figure 4b). Thus, species-specific water extraction strategies did not depend on the presence of the other species.

As expected, comparable results to those of δ¹⁸O were obtained for the spatial structure of δ²H residuals (Figure 5) since both isotopes were highly correlated. For P. halepensis, δ²H residuals had spatial dependencies at short inter-tree distances (<4 meters), while for Q. ilex we assumed that the isotopic composition were spatially uncorrelated.

Marked point process statistics are valuable techniques to evaluate and describe forest systems (see, amongst others, Stoyan & Penttinen, 2000; Comas & Mateu, 2007). Here, we considered these spatial tools to disentangle competition effects for water at inter- and intra-specific levels in a water-limited environment. Our results highlight the existence of clear niche segregation between the Mediterranean trees P. halepensis and Q. ilex. Firstly, and using classical analysis of covariance procedures, we found that the stable isotope composition of xylem water (both δ¹⁸O and δ²H) was on average significantly higher in Aleppo pine than in Holm oak. Decreasing trends in soil water δ¹⁸O and δ²H were also observed with soil depth, confirming the existence of an evaporative gradient in the soil. An increasing trend in xylem water δ¹⁸O and δ²H was also observed along the X dimension of the experimental plot, which agrees with decreasing soil depth following this direction, hence favoring higher water evaporation. However, this trend was steeper for Q. ilex, suggesting that this species had comparatively better access to deep soil layers than P. halepensis with increasing soil depth. Comparing the δ¹⁸O and δ²H of xylem water with the soil profile, we may first conclude that Holm oak takes up more water from deeper soil layers than Aleppo pine after a long drought period, as would be expected according to the deeper root system of evergreen schlerophyllous, as compared to pines (Canadell et al., 1996). Besides overall inter-specific differences, the study of tree-tree interactions using mark correlation functions confirmed the existence of two separate niches for water uptake. Firstly, we observed a significant spatial dependencies of neighbouring pines (inter-tree distances of less than 4 m.) to obtain water from upper soil layers (i.e. higher δ¹⁸O and δ²H of xylem water), and an uncorrelated spatial configuration for oaks (see Figures 4-5). In contrast, when looking at the inter-specific relationships (i.e. the effect of neighbours from the opposite species), we did not find any clear pattern for either competition or facilitation. Thus, there are interdependencies among neighbour pines, but not among neighbours of different species. This is in agreement with the niche segregation hypothesis, further supporting the idea that oaks are able to get water from deeper soil layers that may be less accessible for pines. In this regard, the depleted isotopic values observed in the xylem of oaks are typical of deep soil water, showing no signs of evaporative enrichment. The postulated access to non-evaporated deep soil layers, with high water availability, would also explain the lack of spatial interaction among oak individuals: under such conditions, competition for water resources is scarce.

Similarly, the mark correlation function for BA of pines (Figure 3d) suggested the existence of competitive inhibition for growth at distances below 2 m. In direct contrast, tree BA was distributed at random for oaks and oaks-pines spatial structures, respectively. This points out that long-term growth in Aleppo pine is more strongly affected by competition than it is in the case of Holm oak, in agreement with its greater plasticity in radial growth (Ferrio et al., 2003; Zavala et al., 2000). Nevertheless, what remains intriguing is the fact that Aleppo pine, a more sensitive species to competition, does not show a clear response in terms of growth in the presence of Holm oak. In our case, observed BA responses may reflect the shade-intolerant character of Aleppo pine, but also they could be a result of increasing competition for water resources, or (most likely) a combination of both factors (Zavala et al., 2000).

In any case, it is likely that the competitive effect of Holm oak trees on individuals of Aleppo pine was much lower than if neighbor trees were from the same species. Particular reasons for this may be two-fold. On the one hand, and regarding competition for water resources, the observed evidences of distinct water uptake patterns for the two species may explain the lack of interaction, even when water resources are limiting (see e.g. Klein et al. 2013). On the other hand, the much faster height growth of pines may ensure them attaining a dominant position in terms of light interception, as compared to oaks (Zavala et al., 2000). Conversely, the shade-tolerant nature and conservative growth of the evergreen oak would cause a lack of negative response to this sort of dominance. Nevertheless, due to the existence of a relatively open canopy, it is more likely that growth patterns were dominated by water limitation, at least for the case of the most shade-intolerant species.

In this study we initially assumed that differences in xylem water would reflect distinct water uptake patterns originating from contrasting contributions of soil layers.

However, whereas interspecific differences can be easily explained by the uptake of water from different depths, the observed increase in δ¹⁸O and δ²H in neighbouring trees, particularly in pines, is less straightforward. The presence of close neighbours can be interpreted as a local increase in stand density, and indeed more positive values in δ¹⁸O of xylem water of Aleppo pine have been reported when comparing a densely afforested stand (770 trees ha^–1) with an open woodland (20 trees ha^–1) (Moreno-Gutiérrez et al., 2012a). The direct interpretation is that closer trees tend to use more water from upper soil layers, although there is no clear physiological reason for this behaviour. As pointed out by Moreno-Gutiérrez et al. (2012a), one possibility is that the presence of close neighbours increased shadowing, thus reducing soil evaporation and keeping more water available in upper soil layer, which is generally enriched as compared to deeper soil. Nevertheless, since the enrichment of upper soil water is caused by evaporation, the water available in the upper soil of dense stands is likely to be less enriched than that of a more exposed soil surface, thus having an opposite effect. In addition, a similar effect would have been expected in response to shadowing caused by oaks, and this is not supported by our data. An alternative explanation may come from evaporation processes occurring in the branch (Dawson & Ehleringer, 1993): when transpiration rates are drastically reduced, e.g. during drought periods or in a cold winter, water in the branches has a longer turnover time and may show progressive evaporation, or partially mix with enriched phloem water. In this regard, it is likely that neighbour trees competing for a limited water source would show higher restrictions in transpiration than those trees having fewer neighbours, thus becoming more prone to branch evaporation. Branch evaporation, in turn, would increase the proportion of heavy isotopes in xylem water, due to the faster evaporation of the light isotopes, and thus could explain the higher δ¹⁸O and δ²H observed in trees with close neighbours. This would also explain the stronger neighbour effect in pine as compared to oak, since the former is a water-saving species, with a more sensitive stomatal response (Ferrio et al., 2003; Zavala et al., 2000). However, again certain effect of the presence of oaks over pine isotope composition would have been expected, since the effective water uptake of oaks would also decrease water available for the pine, pushing the reduction of transpiration. Nevertheless, although we do not have direct measurements of tree transpiration in our site, previous studies on P. halepensis have shown that late-summer transpiration at the leaf level may still account for ca. 20% of maximum values (Klein et al. 2005; Baquedano & Castillo 2006; 2007), and a similar proportion has been observed in whole-tree transpiration (Raz Yaseef et al. 2010; Klein et al. 2013, 2014). Similarly, studies on Ponderosa pine have shown that even during summer drought the trees do not cease transpiration and can still use a significant proportion of water from upper soil layers (Fernández et al. 2008). Altogether, both current isotope evidence and previous works on P. halepensis suggest that the observed inter- and intra-specific differences could reflect the use of distinct water pools in the soil, although the underlying causes still require further clarification.