Site-scale soil conditions influencing the decline of Aleppo pine stands in Mediterranean Spanish woodland

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Vegetative decline in individuals of plant populations is a phenomenon that involves multiple factors, both biotic and abiotic, that lead to highly irregular and complex spatial patterns of mortality at stand or forest scale. Although it might be assumed that site soil conditions are a predisposing factor to this phenomenon, very little research has specifically focused on this aspect, hence the lack of knowledge in this regard is evident. • Methods. Soil characterization was carried out at 20 sites (10 with evidence of decline and another 10 with no signs of decline) and the results were related to their role as modulation factor of the drought effects, which is the main cause of the observed decline in Aleppo pine stands in the Comunidad Valenciana (Spain). • Results. The soil properties which were found to be the most explanatory are those associated with soil quality in terms of available space for root exploration, which is vital for nutrition and, above all, water uptake. Episodes of decline are associated with stands where soils present a shallow effective depth due to a low degree of profile development or through marked textural anisotropy because of particularly clayey horizons that cause abrupt changes in permeability and aeration. • Conclusion. The inherent soil diversity acts as a predisposing driver to this physiological process that generates a heterogeneous spatial mosaic of patches with different degrees of decline. Edaphic heterogeneity forest dieback textural anisotropy Mediterranean climate soil evolution degree Figures Figure 1 Figure 2 1. Introduction The loss vigor in woody plants, with discoloration of the leaves, defoliation, progressive death of branches and, in advanced stages, dieback of the affected plant, is a phenomenon known as decline (Manion and Lachance 1992 ; Ciesla and Donaubauer 1994 ; Allen et al. 2010 ).This process, common in natural systems (Franklin et al. 1987 ), may be due to factors which are unexpected, unknown or difficult to determine, since it involves complex interactions between factors, both endogenous and exogenous (Manion 1991 ; Das et al. 2008 ; McEwan et al. 2011 ).The former (endogenous factors) refer to structural and genetic characteristics of population, which are closely related to human use (Heitzman et al. 2007 ; Urbieta et al. 2008 ; Greenwood and Weisberg 2008 ; Camarero et al. 2011 ; Camarero et al. 2016 ), while the exogenous factors include site conditions (climatic, topographic and soil characteristics) (Suarez et al. 2004 ; Hosseini et al. 2017 ; Nadal-Sala et al. 2017 ), as well as concurrence of disturbances such as droughts, heat waves, fires or action of biotic agents (insects and pathogenic fungi) (Allen et al. 2010 ; Haavik et al. 2015 ). All factors involved interact with each other, driving multiple mechanisms that operate at differing intensities across the territory. These mechanisms are not mutually exclusive and act in an interdependent (or compensatory) way, determining in parallel the resilience capacity of plant populations (McDowell et al. 2008 ) and favoring the appearance of complex spatio-temporal patterns of decline that show a marked stochastic character (Fensham and Holman 1999 ; Das et al. 2008 ). Forest decline (or forest dieback) can therefore occur over a wide range of spatial and temporal scales. This ranges from moderate episodes of gradual death of individual trees, which can be ephemeral (Camarero et al. 2016 ; De la Cruz et al. 2014 ), last for years (Ogaya and Peñuelas 2007 ; Heres et al. 2012 ) or become chronic in some areas (Carnicer et al. 2011 ; Camarero et al. 2015 ), to large-scale mortality of hundreds of trees throughout large areas (die-off), associated with severe disturbance events (Anderegg et al. 2012 ), which often include outbreaks of borer insects or pathogenic fungi (Ciesla and Donaubauer 1994 ; Worrall et al. 2008 ; Haavik et al. 2015 ; Garcia de la Serrana et al. 2015). According to the waterfall model of Manion ( 1991 ), the decline process begins with predisposing factors, which weaken individual resilience and increase susceptibility to the damaging defects of other factors that lead to tree morbidity (Manion and Lachance 1992 ; Ciesla and Donaubauer 1994 ). The latter include factors considered as either initiating or contributing factors. Drought stress (whether accompanied or not by high temperatures) is a key factor to understand the dynamics of many terrestrial ecosystems throughout the world (Dobbertin et al. 2005 ; Gitlin et al. 2006 ; Miao et al. 2009 ; Anderegg et al. 2012 ). An unusually severe decrease in rainfall can lead to high mortality in forest stands that are particularly vulnerable to the effects of drought. Even within the ecological optimum of their geographic distribution, a severe lack of rainfall can lead to trees being affected in areas with conditions that predispose them to possible decline. In the Mediterranean area, this is the most common initiating factor in the decline of forest stands (Peñuelas et al. 2001 ; Gea-Izquierdo et al. 2014 ; Sánchez-Salguero et al. 2012 ). At forest-stand scale, certain site characteristics interact with density-dependent processes, such as competition or facilitation, defining the degree of predisposition to processes that lead to decline (Suarez et al. 2004 ; Koepke et al. 2010 ; Hosseini et al. 2017 ; Brown et al. 2018 ). For example, high densities ​​frequently lead to mortality as a result of exacerbated competition for water and / or high activity of biotic agents (Lloret et al. 2004 ; Greenwood and Weisberg 2008 ). The combination of stand age, density and structure along with the specific site conditions (physical environment) produce complex spatial patterns of predisposition to decline due to drought, which are very difficult to predict (Fensham and Holman 1999 ; Das et al. 2008 ). The consequence is that forest decline episodes frequently manifest diffuse and irregular spatial boundaries (fronts) as well as highly variable degrees of mortality (Dobbertin et al. 2005 : Miao et al. 2009 ; Klos et al. 2009 ). Spatial patterns of drought-induced mortality are closely related to spatial and temporal variability in the conditions of the physical environment that determine water availability. Although climate determines water availability at larger scales, the physiographic characteristics (such as slope, exposure and position within the landscape) along with soil status (stoniness, texture and depth of the soil) act as local controllers of water availability for vegetation (Brown et al. 2018 ; Preisler et al. 2019 ). The role of these factors is especially relevant in the summer months in regions with Mediterranean climate, when water lost through evapotranspiration continuously exceeds precipitation (Prieto-Recio et al. 2015 ). Despite the important influence of non-climatic conditions on water availability and therefore on the spatial patterns of tree decline, few studies have specifically evaluated this influence (Galiano et al. 2010 ). In the scarce research addressing this issue, the focus tends not to be on physiographic factors but rather, these are dealt with as secondary or complementary aspects, with the exception being the effect of altitude, which has been analyzed in several studies (Guarín and Taylor 2005; Candel-Pérez et al. 2012 ). Much less attention has been directed towards evaluating the relationship between site soil conditions and decline. This aspect has frequently been ignored and therefore underestimated, despite evident indications that site-scale soil characteristics are an important factor in the predisposition to decline (Dobbertin et al. 2005 ; Peterman et al. 2012 ; Prieto-Recio et al. 2015 ). By modulating water availability in periods of maximum water deficit, soil is assumed to be an especially important component of predisposition to the effects of drought at local scale (Lloret et al. 2004 ; Galiano et al. 2012 ). Empirical support for this notion is particularly scarce, and studies documenting drought-induced decline rarely analyze the relative importance of potentially implicated soil features (Galiano et al. 2010 ). Improving our understanding of the role of soil attributes related to soil moisture conditions in forest decline is of particular interest in order to correctly interpret this complex ecophysiological process (Bruner et al. 2009). For this reason, specific sampling of soil conditions at locations with observed decline is essential to capture the small-scale variability (stand and tree level) and thus relate soil conditions with the individual health status of trees or stands as a whole (Brown et al. 2018 ). Accordingly, the main objective of this study is to evaluate the role of soil status in tree-decline processes, focusing in particular on determining the effect that spatial variability of soil properties throughout the profile (anisotropy) may have on predisposition of forest stands to decline. 2. Material and methods The study was undertaken in a set of Pinus halepensis Mill forest stands in the Comunidad Valenciana (Spain), a region which is particularly characteristic of the Mediterranean area of the Iberian Peninsula. These plant communities are a common element in the configuration of the current landscape, presenting a rich variety in terms of origin, maturity conditions and vegetative vigor (Del Rio et al. 2009). Given the highly frugal and drought-resistant nature of the species, it was routinely used in reforestations undertaken in the second half of the 20th century, often on marginal land as regards physical environmental requirements (García de la Serrana et al. 2015; Gómez-Sanz 2019 ). In recent years, episodes of notable vegetative decline have been observed in the tree formations of this circum-Mediterranean species, which have caused its complete disappearance in the most extreme cases (Allen et al. 2010 ). In this biogeographic context, a total number of 10 study locations were selected: two in Castellón province, six in Valencia and two in Alicante (Fig. 1 ). Their administrative situation, together with their UTM coordinates and general site characteristics are included in Table 1 . Altitude ranges from almost sea level (Almenara, Castellón) to more than 750 m in Jalance (Valencia), which obviously affects the variability of climatic conditions at each of the analyzed locations. Table 1 Main features of the study location and sites (the final letter of the site label indicates whether it shows decline, letter D, or not, letter N) Location Site Label UTM Coordinates (ETRS89 Huso 30) Elevation (m) Slope orientation Slope inclination (%) Bedrock X Y Almenara S01N 739659 4404126 35 NW 15 Sandstone S01D 739100 4403741 17 SW 35 Sandstone Soneja S02N 726199 4409447 266 NE 35 Dolomitic limestone S02D 729371 4409909 303 S 30 Sandstone Gilet-Sagunto S03N 726809 4393373 247 E 35 Dolomitic limestone S03D 730557 4391548 181 SE 45 Sandstone Sagunto S04N 726222 4393666 275 SW 20 Sandstone S04D 726257 4393705 283 SW 20 Sandstone Jalance S05N 660792 4343644 769 - 0 Limestone S05D 661107 4343625 759 SE 20 Limestone Guadassuar S06N 710163 4338690 67 - 0 Limestone S06D 709611 4338390 69 - 0 Limestone Lliria S07N 698656 4401217 455 S-SE 30 Limestone S07D 700365 4400789 429 SW 50 Limestone Vilamarxant S08N 703981 4379061 243 NW 20 Limestone S08D 703961 4379638 317 S-SW 35 Sandstone Orihuela S09N 678806 4220205 117 N-NW 30 Limestone (Colluvium) S09D 674683 4217131 76 S 30 Limestone (Colluvium) Jijona-Alicante S10N 717053 4262180 307 N 45 Limestone (Colluvium) S10D 717248 4261049 282 S-SE 35 Limestone In accordance with the hypothesis that soil characteristics can present notable differences during the decline process (Brown et al. 2018 ), a paired sampling was proposed in each location. The aim was to eliminate the effects of climatic variability and origin as well as management of stands, thus allowing the small-scale variability of site conditions to be determined. Consequently, two different situations were selected: (1) stand with good vegetative state and absence of recent mortality (site with a label ending in "N"); (2) stand geographically and physiographically close to the latter stand, with a similar origin, but in a situation of certain vegetative decline or recent manifestation of mortality (site with a label ending in "D"). In the field work undertaken at each of the sites, a representative point of dominant physiographic, botanical and canopy conditions was selected, followed by a detailed ecological inventory. For this task, a circular plot of 500 m 2 was established, in which dasometric, physiographic and botanical information was recorded. Furthermore, a soil profile study was carried out, opening the corresponding pit, identifying and describing different soil horizons, and taking a representative sample from each of them. The soil samples were processed in a specialized laboratory that meets the homologation and certification standards with regard to procedures and validation of results. Site soil conditions were described from a set of studied variables, highlighting those which have the greatest influence on water availability in the soil. The variables used were those related to the presence of non-sampleable stoniness (NSS)(FAO 2006 ) and those related to the USDA textural fractions content (coarse elements (CE), sands (SAN), silts (SIL) and clays (CLA)) and humified organic matter (OM). In addition, to assess the differences in the chemical status of the soil, pH in water(WPH) and total carbonates presence (TC) were considered. The information obtained from the analyzed samples was statistically treated as paired observations. In this way, Normality in distribution of differences between sites with and without decline was verified (Kolmogorov-Smirnov test) and a Student's t-test was performed for paired data. The significance level for hypothesis testing of means equality in paired differences was set at 0.05. In turn, genetic horizons were identified for each profile, thus allowing us to approximate the degree of evolution and assess changes in physical conditions (textural and structural) derived from the presence of markedly clayey and/or strongly cemented horizons or relatively continuous hard rock. The depth at which a notable change in permeability conditions, aeration and water retention capacity was observed (change in USDA textural type) was considered as a new study variable, termed ‘easily explored depth’ (EED). Finally, all analyzed profiles were classified, using the classification system proposed by FAO-UNESCO (IUSS Working Group 2014 ), for which different diagnostic elements were previously identified in accordance with criteria established by this taxonomic system. 3. Results The soil profile characterizations in inventoried plots are summarized in Table 2 . It can be observed that, from a physiographic perspective, all site profiles showing decline have a south-facing orientation (or at least close to this orientation), which is an obvious predisposing factor to decline. Conditions of hydric stress are increased, especially in summer, when demand for water is greater. The depths of the profiles differ, although 80% present more or less continuous hard rock at a depth of less than 1 m (leptic conditions according to WRB (IUSS Working Group 2014 )). There is also a notable presence of non-sampleable stoniness and coarse elements, with 80% of the profiles having less than 40% fine earth (skeletic or hyperskeletic features for WRB (IUSS Working Group 2014 )). As regards texture, equilibrated texture horizons dominate (loam and sandy clay loam), making up around 50% of the total. There are also horizons of coarse textures (sandy loam and loamy sand), approximately 30%, and of slightly imbalanced fine textures (clay loam and silt loam), and even fine textures (clay). The profiles are mostly homogeneous in terms of texture, although some present a marked heterogeneity, which leads to sudden changes in permeability and aeration conditions within the profile (abruptic qualifier of WRB (IUSS Working Group 2014 )). From a biochemical perspective, organic matter content is moderate-low, and dominant soil reaction is either strongly or extremely basic, especially in sites that do not show decline. Furthermore, the majority of sites where decline is observed present a scarcity or absence of inactive carbonates (non-calcareous material). Table 2 Soil variables at each study site (final letter of the site label indicates whether it shows decline, letter D, or if it does not, letter N) Location Site Genetic Horizon Depth (cm) NNS CE USDA Texture OM CT WPH SAN SIL CLA Texture classes Almenara S01N 1 20 10 68.6 40.7 27.0 32.3 Clay loam 3.06 24.7 8.2 2 30 5 29.4 33.4 30.6 36.0 Clay loam 1.20 32.2 8.3 S01D 1 20 40 39.2 68.7 24.0 7.3 Sandy loam 3.71 0.0 5.7 2 20 20 44.6 57.4 17.6 25.0 Sandy clay loam 1.03 0.0 6.8 Soneja S02N 1 25 30 46.9 40.7 38.0 21.3 Loam 4.68 41.4 8.3 2 25 15 6.7 53.4 35.6 11.0 Loam 1.19 54.4 8.6 S02D 1 15 15 36.4 66.7 24.0 9.3 Sandy loam 1.01 0.0 6.8 2 15 20 56.2 60.7 21.0 18.3 Sandy loam 0.96 0.0 7.2 Gilet-Sagunto S03N 1 15 40 24.3 56.7 20.0 23.3 Sandy clay loam 2.17 0.0 8.3 2 25 20 20.8 55.4 19.6 25.0 Sandy clay loam 0.89 0.0 8.1 S03D 1 20 40 26.5 62.7 24.0 13.3 Sandy loam 4.51 0.0 5.7 2 20 20 8.1 38.4 9.6 52.0 Clay 1.63 0.0 6.9 Sagunto S04N 1 30 5 54.0 62.7 22.0 15.3 Sandy loam 1.79 11.8 8.4 2 35 10 29.4 67.4 16.6 16.0 Sandy loam 0.77 9.2 8.4 S04D 1 25 10 31.5 64.7 22.0 13.3 Sandy loam 2.25 5.0 8.3 2 20 10 28.7 53.4 26.6 20.0 Loam 0.84 0.0 8.2 Jalance S05N 1 35 20 14.9 49.4 26.6 24.0 Sandy clay loam 2.95 9.4 8.2 S05D 1 10 90 40.8 61.4 14.6 24.0 Sandy clay loam 6.52 11.7 8.3 Guadassuar S06N 1 15 10 4.3 35.4 42.6 22.0 Loam 2.37 5.0 8.4 S06D 1 20 10 4.1 45.4 32.6 22.0 Loam 1.96 0.0 8.3 Lliria S07N 1 20 20 52.8 44.4 37.6 18.0 Loam 4.92 45.2 8.3 S07D 1 20 30 39.6 44.4 35.6 20.0 Loam 2.93 67.5 8.5 Vilamarxant S08N 1 30 15 44.0 51.4 24.6 24.0 Sandy clay loam 2.45 28.5 8.5 2 15 30 40.9 53.4 25.6 21.0 Sandy clay loam 0.68 25.5 8.2 S08D 1 30 50 39.7 77.4 15.6 7.0 Loamy sand 0.98 0.0 8.3 2 > 70 65 22.2 71.4 11.6 17.0 Sandy loam 0.61 0.0 8.7 Orihuela S09N 1 15 25 49.3 53.4 32.6 14.0 Loam 6.15 47.6 8.2 2 40 35 42.1 59.4 33.6 7.0 Sandy loam 1.54 77.2 8.5 3 > 60 50 33.3 57.4 35.6 7.0 Sandy loam 1.43 86.6 8.4 S09D 1 25 40 33.1 37.4 34.6 28.0 Clay loam 2.68 48.2 8.3 2 15 50 43.0 27.4 40.6 32.0 Clay loam 0.77 41.3 8.5 3 > 60 60 61.1 37.4 34.6 28.0 Clay loam 0.41 49.7 8.5 Jijona-Alicante S10N 1 40 35 59.7 53.4 30.6 16.0 Loam 1.68 71.5 8.6 2 > 60 45 76.7 54.4 32.6 13.0 Loam 1.57 73.1 8.4 S10D 1 15 40 58.1 29.4 66.6 4.0 Silt loam 2.14 84.9 8.5 NNS, non-sampleable stoniness (%); CE, coarse elements (%), SAN, sands (% in fine earth fraction); SIL, silts (% in fine earth fraction); CLA, clays (% in fine earth fraction); OM, organic matter (% in fine earth fraction); CT, total carbonates (% in fine earth fraction); WPH, pH in water. No significant differences were observed among the mean values of the studied variables according to the decline factor, with exception of the easily explored depth (EED). Hence, this variable is the only one that explains differences between sites with and without decline. The result of the statistical contrast for paired data, the differences in values of the studied variables between sites with decline and without decline, is shown in Table 3 . Table 3 Comparison of soil variables for sites with decline (labeled with the letter D in brackets) and non-decline (labeled with the letter N in brackets) based on t-test (significant t values with P < 0.05 are in bold) Variable n Descriptive Normality Related (paired) differences Mean Standard deviation Z of Kolmogorov-Smirnov P -value Mean Standard deviation t P -value CE(N) 10 51.03 18.96 0.48 0.974 9.42 20.89 1.43 0.188 CE(D) 10 41.61 23.26 0.48 0.977 SAN(N) 10 49.75 9.32 0.39 0.998 -2.93 17.31 -0.54 0.606 SAN(D) 10 52.68 13.76 0.62 0.841 SIL(N) 10 30.30 7.85 0.37 0.999 2.17 14.40 0.48 0.645 SIL(D) 10 28.13 15.87 0.69 0.724 CLA(N) 10 19.95 7.31 0.54 0.931 0.76 10.59 0.23 0.825 CLA(D) 10 19.19 8.14 0.49 0.972 OM(N) 10 2.51 1.06 0.49 0.972 0.06 1.82 0.10 0.919 OM(D) 10 2.45 1.65 0.60 0.860 WPH(N) 10 8.35 0.09 0.80 0.550 0.55 0.93 1.87 0.094 WPH(D) 10 7.80 0.98 1.17 0.129 CT(N) 10 31.76 26.64 0.58 0.886 10.26 21.19 1.53 0.160 CT(D) 10 21.50 32.58 1.01 0.263 TD(N) 10 52.00 29.17 0.72 0.680 10.00 34.64 0.91 0.385 TD(D) 10 42.00 32.68 0.83 0.491 EED(N) 10 52.00 29.17 0.72 0.680 22.50 25.74 2.76 0.022 EED(D) 10 29.50 26.61 1.07 0.199 CE, coarse elements (%), SAN, sands (% in fine earth fraction); SIL, silts (% in fine earth fraction); CLA, clays (% in fine earth fraction); OM, organic matter (% in fine earth fraction); WPH, pH in water; CT, total carbonates (% in fine earth fraction); TD, total depth (cm); EED, easily explored depth (cm). Regarding the degree of development, there is a wide variation among the profiles, from scarcely-developed young soils, without intermediate horizons and which usually lay directly over consolidated bedrock, to soils with highly evolved profiles, in which appears a genetic horizon of accumulation, with a notable presence of clay. Finally, Fig. 2 presents a classification of soils evaluated according to the FAO-UNESCO WRB (IUSS Working Group 2014 ). The soils in which it is possible to identify an argic diagnostic horizon are associated in all cases with sites where decline is observed. 4. Discussion The phenomenon of decline and death of forest tree species is particularly complex as it involves a varied set of commonly interdependent factors (Manion 1991 ; Ciesla and Donaubauer 1994 , La Manna and Rajchenberg, 2004 ). This notion is corroborated by the fact that the observed mortality was relatively heterogeneous at sites with decline and in their immediate surroundings. Some sites presented isolated dead trees in the same physiographic situation, while at others the dead trees appeared in relatively contiguous group sin similar physiographic situations. In the most severe cases, mortality affected all, or almost all, of the cover previously present at the site. In the Mediterranean area analyzed, an irregular rainfall regime and high thermal efficiency of the climate (globally mesothermic according to Thornthwaite ( 1948 )) result in a clearly defined drought period, which lasts more than three months, coinciding with the period of highest temperatures (summer months). These climatic conditions, typical of a genuine Mediterranean climate (Peñuelas et al. 2001 ) lead to a deficient water balance, which exposes vegetation to high levels of water stress. This entails a high level of vulnerability to episodes of low precipitation (drought), which can occur unexpectedly and become particularly intense. In the Comunidad Valenciana (Spain) this is a recurrent situation, having been verified in 2014 and in the immediately preceding years (García de la Serrana 2015). Forest dieback, a process determined by multiple factors, manifests the different behaviours of species, the structure of their populations and the interspecific interactions that develop within them (Lloret et al. 2015 ).Together with the restrictions imposed by site conditions, differences in life history characteristics and species resilience increase the heterogeneity within the forest as regards predisposition to drought damage, with different rates and spatial patterns of decline among coexisting tree species (Suarez et al. 2004 ; Gitlin et al. 2006 ; Fensham and Fairfax 2007 ; Newbery and Lingenfelder 2009 ). Consequently, the spatial pattern of decline at site-scale cannot always be attributed to the variability in physical environment conditions, and more specifically to the heterogeneity of soil conditions. At Guadassuar, Lliria and Orihuela, the soils in sites with decline are similar to those in sites where decline is not present; hence decline cannot be attributed to differences in soils at site level. The causes of the decline at these locations should, therefore, be sought in other predisposing factors such as: (a) consequences of different disturbances which generate physiological dysfunctions (for example, soil compaction due to recreational use in Guadassuar); (b) situation in locally drier landscape positions (Suarez et al. 2004 ) in the case of Lliria; (c) exacerbated marginal climatic conditions (Gómez-Sanz 2019 ), as in the case of Orihuela, where good soil conditions do little to alleviate the damaging effect of drought. Under the poor climatic environment at Orihuela, good soil conditions favored excessive extension of the root system in non-drought years, making it hydraulically unviable in the face of a relatively intensive drought episode (Martínez-Vilalta and Piñol 2002 ; Collins and Bra 2007). In contrast, the role of the soil was found to be highly relevant as a predisposing factor at the rest of the locations (Fig. 2 ). This confirms the statement by Gitlin et al. ( 2006 ), that the inherent spatial variability in site conditions can underlie the irregularity of small-scale mortality patterns. However, not all soil features are equally determinant. Differences in biological (organic matter content) and chemical (soil reaction and presence of carbonates) properties do not appear to be related to the observed response. Although acidic or neutral reaction soils are associated with decline episodes in all the cases analyzed, according to their autoecology (Gandullo and Sánchez 1994 ), Aleppo pine is tolerant to these acidity values (pH in water), so the effect on predisposition to decline is not sufficiently clear. However, the metabolic response to these chemical conditions could predispose the trees that live in these conditions to the synergistic effect of other factors that contribute to decline. This is not the case with physical properties, which have been shown to be much more explanatory in the observed decline. Of the set of soil characteristics, those that allow water availability to be decoupled from the purely climatic component associated with the rainfall pattern are key to vegetation survival (Nadal-Sala et al. 2017 ). This quality is determined by the ability of the soil to store water and make it available to vegetation efficiently. The availability of water to tree roots is highly dependent on available soil volume and its porosity. Both attributes are nuanced by their internal variability (within the soil profile), closely linked to the degree of soil evolution. This makes it necessary to assess the way in which the properties determining soil moisture vary with depth, especially with regard to the soil volume easily explored by roots (Suarez et al. 2004 ), from stoniness (which increases the infiltration capacity of soil but reduces its effective volume) (Hlaváčiková et al. 2016 ; Preisler et al. 2019 ), to textural class (percentages of sand, silt and clay that determine the state and behavior of water and air in the soil) (Colins and Bra 2007) and to organic matter content as structure-creating agent (Six et al. 2004 ). Development of root system consumes a large part of primary production (McDowell et al. 2011 ), and therefore requires a compromise between developing and maintaining a larger root system and the additional water it can provide (Jackson et al. 2000 ). Consequently, those sites with well developed, deep soils will host individuals with a more extensive, hydraulically balanced root system, which implies an advantage in water-limited environments over other individuals growing on shallow soil sand therefore shallower root systems (Nadal-Sala et al. 2017 ). Soil depth stands out as a property that clearly predisposes trees to decline problems. The volume explored by radical systems in shallow or poorly developed soils is very low (Leptosols in WRB (IUSS Working Group 2014 )), and this is frequently accompanied by low water retention capacity (these soils tend to be particularly stony, showing skeletic, or even hyperskeletic, conditions). On such soils, individuals do not usually develop an adequate root system, which makes them especially vulnerable to drought as a trigger of decline (Schenk and Jackson 2005 ; Preisler et al. 2019 ). This is the case at sites where mortality is present in Jalance and Jijona-Alicante. In more developed soils, the most determinant characteristic as regards predisposition to decline is textural variability according to profile depth, which is closely related to the degree of evolution of the soil. Hence, soils with obvious profile heterogeneity (presence of intermediate accumulation horizon, argic in WRB (IUSS Working Group 2014 )), are significantly associated with sites where decline is present. This situation is even more marked in soils with abrupt textural changes in their profiles (abruptic qualifier from the WRB (IUSS Working Group 2014 )). The presence of an argic horizon conditions root development, limiting it almost entirely to the surface horizon, thus considerably reducing the soil volume explored by roots in search of water and nutrients (low effective depth of soil). The enduring nature of trees and their ability to change resource allocation and hydraulic architecture throughout their lives largely explain this behavior. If, in addition, the surface horizon has a texture that does not promote water retention (sandy and/or low content in fine earth), as occurs in Vilamarxant, Almenara and Gilet-Sagunto, the predisposition to decline is considerably accentuated. The opposite occurs in the case of soils with homogeneous profiles (relatively isotropic), without a clear development of an intermediate accumulation horizon. Although effective depth may be limited by the presence of continuous hard rock at medium depths (WRB leptic qualifier (IUSS Working Group 2014 )), soil volume is sufficient, in the presence of an adequate textural class (not unbalanced coarse or coarse and not highly stony), to provide a water retention capacity capable of sufficiently mitigating certain levels of water stress, thus reducing or buffering the physiological dysfunctions that lead to decline. 5. Conclusions Within a synoptic region prone to drought, spatial patterns of decline are often quite heterogeneous and irregular at finer spatial scales. However, within this variability, specific episodes of decline are significantly associated with stands where soils present a shallow effective depth due to a low degree of profile development or to marked textural anisotropy associated with the presence of particularly clayey horizons that cause abrupt changes in permeability and aeration. The site soil conditions have thus been identified as a main predisposing factor, modulating the effects of drought as a triggering factor in the decline of Aleppo pine stands. In the analyzed area, episodes of notable reduction in precipitation water inflows (drought in 2014 and in the immediately preceding years) led to critical levels of water stress. Some trees were physiologically destabilized by the catalytic effect of local site conditions (physiographic and/or soil conditions), which was manifested in individual, group or superficial mortality. The notion that the climate in the Mediterranean basin will evolve towards warmer and more arid scenarios is constantly garnering greater acceptance. The consequences of this predicted climate change on arboreal stands in general, and Aleppo pine stands in particular, will be highly nuanced by specific site conditions, especially those relating to soil, giving rise to highly heterogeneous decline patterns on a local scale. Hence, the importance of taking into consideration the soil diversity inherent to the territory with a view to implementing more adaptive and flexible planning as well as management models that seek to anticipate emerging problems or challenges associated with the effects of global change dynamics, and especially, those linked to climate change. Declarations Funding. The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests. The authors have no relevant financial or non-financial interests to disclose. Author Contributions. The study conception and design were carried out by Valentín Gómez-Sanz and Rafael Serrada Hierro. All authors performed in data collection and analysis. The draft of the manuscript was written by Valentín Gómez-Sanz and all authors provided comments and suggestions on it and approved manuscript final version. Data Availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Acknowledgments We would like to thank Emilio González and Eduardo Péres Laorga, technical staff of the "Servicio de Ordenación y Gestión Forestal de la Consellería D'Infraestructures, Territori I Medi Ambient de la Generalitat Valenciana”, for making the study possible, along with the staff and service agents who carry out Forest Health related functions in VAERSA and in the Consellería for their help in facilitating the field work. References Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Kitzberger T, Rigling A, Breshears DD, Hogg EH, Gonzalez P, Fensham R, Zhang Z, Castro J, Demidova N, Lim J-H, Allard G, Running SW, Semerci A, Cobb N (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3813100","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264905325,"identity":"c3d546c5-cf55-4b91-aff5-5d6c76a427ac","order_by":0,"name":"VALENTIN GOMEZ SANZ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYFAC5gYgIQHj2RCjhRGoJQGuJY1oLXDeYcIaDI4fbHxc+MMij4F/8dENH/6cT9wudoDx4Q98Ws4kNhvPSJAoZpB4lnZzBs/txJ2zE5iNefBokWxIbJPmSZBIbJA4Y3abR+J24obbCWzS+Bwm2f+w/Tdcyx+DcyAt7D/xOYxfIrGNGayFv8fsNkPCAbAtDPgcxi/xsFmaJw2oUYIt7WbPgWTjnbMTgSJ4tLDxJx/8zGNTl9jPf/jYjR9/7GS3Sycf/IjPYQi9EgkQhgE4pogC/AdgWkbBKBgFo2AUoAIACFNPYNFZODQAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-4661-1654","institution":"Universidad Politécnica de Madrid - Escuela Técnica Superior de Ingeniería de Montes, Forestal y del Medio Natural","correspondingAuthor":true,"prefix":"","firstName":"VALENTIN","middleName":"GOMEZ","lastName":"SANZ","suffix":""},{"id":264905326,"identity":"ed5d17d8-309b-4247-8d9d-dccc30ee4f0f","order_by":1,"name":"Aitor Gastón González","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Aitor","middleName":"Gastón","lastName":"González","suffix":""},{"id":264905327,"identity":"44ef5a04-c618-430c-999d-436d28c91ef1","order_by":2,"name":"Juan Ignacio García Viñas","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"Ignacio García","lastName":"Viñas","suffix":""},{"id":264905328,"identity":"4674676b-999d-4b9f-a469-4e097a952816","order_by":3,"name":"Rafael Serrada Hierro","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"Serrada","lastName":"Hierro","suffix":""}],"badges":[],"createdAt":"2023-12-27 16:48:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3813100/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3813100/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11104-024-06638-2","type":"published","date":"2024-04-01T15:01:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49238811,"identity":"8db04d85-9100-473d-8119-06929dc9e5bc","added_by":"auto","created_at":"2024-01-05 18:13:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54433,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of study locations\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3813100/v1/212649093774e965189beaa5.png"},{"id":49238812,"identity":"64571391-eff9-4c18-b0a2-76b0df78b6d1","added_by":"auto","created_at":"2024-01-05 18:13:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":484419,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between general soil condition and observed decay (final letter of the site label indicates whether it shows decline, letter D, or not, letter N)\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3813100/v1/1627cb8969554802bc1e7bbb.png"},{"id":54304150,"identity":"b980bff1-0f13-4225-bd75-2e8fc7d7fca0","added_by":"auto","created_at":"2024-04-08 15:14:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":635538,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3813100/v1/b3eebb58-9439-4ad0-9e2c-b9512884ed14.pdf"}],"financialInterests":"","formattedTitle":"Site-scale soil conditions influencing the decline of Aleppo pine stands in Mediterranean Spanish woodland","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe loss vigor in woody plants, with discoloration of the leaves, defoliation, progressive death of branches and, in advanced stages, dieback of the affected plant, is a phenomenon known as decline (Manion and Lachance \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Ciesla and Donaubauer \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Allen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).This process, common in natural systems (Franklin et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1987\u003c/span\u003e), may be due to factors which are unexpected, unknown or difficult to determine, since it involves complex interactions between factors, both endogenous and exogenous (Manion \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Das et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; McEwan et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).The former (endogenous factors) refer to structural and genetic characteristics of population, which are closely related to human use (Heitzman et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Urbieta et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Greenwood and Weisberg \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Camarero et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Camarero et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), while the exogenous factors include site conditions (climatic, topographic and soil characteristics) (Suarez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hosseini et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nadal-Sala et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), as well as concurrence of disturbances such as droughts, heat waves, fires or action of biotic agents (insects and pathogenic fungi) (Allen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Haavik et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll factors involved interact with each other, driving multiple mechanisms that operate at differing intensities across the territory. These mechanisms are not mutually exclusive and act in an interdependent (or compensatory) way, determining in parallel the resilience capacity of plant populations (McDowell et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and favoring the appearance of complex spatio-temporal patterns of decline that show a marked stochastic character (Fensham and Holman \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Das et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eForest decline (or forest dieback) can therefore occur over a wide range of spatial and temporal scales. This ranges from moderate episodes of gradual death of individual trees, which can be ephemeral (Camarero et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; De la Cruz et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), last for years (Ogaya and Pe\u0026ntilde;uelas \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Heres et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) or become chronic in some areas (Carnicer et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Camarero et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), to large-scale mortality of hundreds of trees throughout large areas (die-off), associated with severe disturbance events (Anderegg et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), which often include outbreaks of borer insects or pathogenic fungi (Ciesla and Donaubauer \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Worrall et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Haavik et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Garcia de la Serrana et al. 2015).\u003c/p\u003e \u003cp\u003eAccording to the waterfall model of Manion (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), the decline process begins with predisposing factors, which weaken individual resilience and increase susceptibility to the damaging defects of other factors that lead to tree morbidity (Manion and Lachance \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Ciesla and Donaubauer \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The latter include factors considered as either initiating or contributing factors.\u003c/p\u003e \u003cp\u003eDrought stress (whether accompanied or not by high temperatures) is a key factor to understand the dynamics of many terrestrial ecosystems throughout the world (Dobbertin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Gitlin et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Miao et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Anderegg et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). An unusually severe decrease in rainfall can lead to high mortality in forest stands that are particularly vulnerable to the effects of drought. Even within the ecological optimum of their geographic distribution, a severe lack of rainfall can lead to trees being affected in areas with conditions that predispose them to possible decline. In the Mediterranean area, this is the most common initiating factor in the decline of forest stands (Pe\u0026ntilde;uelas et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Gea-Izquierdo et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; S\u0026aacute;nchez-Salguero et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt forest-stand scale, certain site characteristics interact with density-dependent processes, such as competition or facilitation, defining the degree of predisposition to processes that lead to decline (Suarez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Koepke et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hosseini et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Brown et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). For example, high densities ​​frequently lead to mortality as a result of exacerbated competition for water and / or high activity of biotic agents (Lloret et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Greenwood and Weisberg \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe combination of stand age, density and structure along with the specific site conditions (physical environment) produce complex spatial patterns of predisposition to decline due to drought, which are very difficult to predict (Fensham and Holman \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Das et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The consequence is that forest decline episodes frequently manifest diffuse and irregular spatial boundaries (fronts) as well as highly variable degrees of mortality (Dobbertin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e: Miao et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Klos et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSpatial patterns of drought-induced mortality are closely related to spatial and temporal variability in the conditions of the physical environment that determine water availability. Although climate determines water availability at larger scales, the physiographic characteristics (such as slope, exposure and position within the landscape) along with soil status (stoniness, texture and depth of the soil) act as local controllers of water availability for vegetation (Brown et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Preisler et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The role of these factors is especially relevant in the summer months in regions with Mediterranean climate, when water lost through evapotranspiration continuously exceeds precipitation (Prieto-Recio et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the important influence of non-climatic conditions on water availability and therefore on the spatial patterns of tree decline, few studies have specifically evaluated this influence (Galiano et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In the scarce research addressing this issue, the focus tends not to be on physiographic factors but rather, these are dealt with as secondary or complementary aspects, with the exception being the effect of altitude, which has been analyzed in several studies (Guar\u0026iacute;n and Taylor 2005; Candel-P\u0026eacute;rez et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMuch less attention has been directed towards evaluating the relationship between site soil conditions and decline. This aspect has frequently been ignored and therefore underestimated, despite evident indications that site-scale soil characteristics are an important factor in the predisposition to decline (Dobbertin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Peterman et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Prieto-Recio et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). By modulating water availability in periods of maximum water deficit, soil is assumed to be an especially important component of predisposition to the effects of drought at local scale (Lloret et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Galiano et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Empirical support for this notion is particularly scarce, and studies documenting drought-induced decline rarely analyze the relative importance of potentially implicated soil features (Galiano et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImproving our understanding of the role of soil attributes related to soil moisture conditions in forest decline is of particular interest in order to correctly interpret this complex ecophysiological process (Bruner et al. 2009). For this reason, specific sampling of soil conditions at locations with observed decline is essential to capture the small-scale variability (stand and tree level) and thus relate soil conditions with the individual health status of trees or stands as a whole (Brown et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Accordingly, the main objective of this study is to evaluate the role of soil status in tree-decline processes, focusing in particular on determining the effect that spatial variability of soil properties throughout the profile (anisotropy) may have on predisposition of forest stands to decline.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cp\u003eThe study was undertaken in a set of \u003cem\u003ePinus halepensis\u003c/em\u003e Mill forest stands in the Comunidad Valenciana (Spain), a region which is particularly characteristic of the Mediterranean area of the Iberian Peninsula. These plant communities are a common element in the configuration of the current landscape, presenting a rich variety in terms of origin, maturity conditions and vegetative vigor (Del Rio et al. 2009). Given the highly frugal and drought-resistant nature of the species, it was routinely used in reforestations undertaken in the second half of the 20th century, often on marginal land as regards physical environmental requirements (Garc\u0026iacute;a de la Serrana et al. 2015; G\u0026oacute;mez-Sanz \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In recent years, episodes of notable vegetative decline have been observed in the tree formations of this circum-Mediterranean species, which have caused its complete disappearance in the most extreme cases (Allen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this biogeographic context, a total number of 10 study locations were selected: two in Castell\u0026oacute;n province, six in Valencia and two in Alicante (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Their administrative situation, together with their UTM coordinates and general site characteristics are included in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Altitude ranges from almost sea level (Almenara, Castell\u0026oacute;n) to more than 750 m in Jalance (Valencia), which obviously affects the variability of climatic conditions at each of the analyzed locations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain features of the study location and sites (the final letter of the site label indicates whether it shows decline, letter D, or not, letter N)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLabel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUTM Coordinates\u003c/p\u003e \u003cp\u003e(ETRS89 Huso 30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eElevation (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSlope orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSlope inclination (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBedrock\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlmenara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS01N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e739659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4404126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS01D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e739100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4403741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSoneja\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS02N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4409447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDolomitic limestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS02D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e729371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4409909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGilet-Sagunto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS03N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4393373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDolomitic limestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS03D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e730557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4391548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSagunto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS04N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4393666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS04D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4393705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eJalance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS05N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e660792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4343644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS05D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e661107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4343625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGuadassuar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS06N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e710163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4338690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS06D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e709611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4338390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLliria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS07N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e698656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4401217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS-SE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS07D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e700365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4400789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVilamarxant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS08N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e703981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4379061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS08D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e703961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4379638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS-SW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSandstone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOrihuela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS09N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e678806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4220205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN-NW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone (Colluvium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS09D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e674683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4217131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone (Colluvium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eJijona-Alicante\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS10N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e717053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4262180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone (Colluvium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS10D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e717248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4261049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS-SE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn accordance with the hypothesis that soil characteristics can present notable differences during the decline process (Brown et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), a paired sampling was proposed in each location. The aim was to eliminate the effects of climatic variability and origin as well as management of stands, thus allowing the small-scale variability of site conditions to be determined. Consequently, two different situations were selected: (1) stand with good vegetative state and absence of recent mortality (site with a label ending in \"N\"); (2) stand geographically and physiographically close to the latter stand, with a similar origin, but in a situation of certain vegetative decline or recent manifestation of mortality (site with a label ending in \"D\").\u003c/p\u003e \u003cp\u003eIn the field work undertaken at each of the sites, a representative point of dominant physiographic, botanical and canopy conditions was selected, followed by a detailed ecological inventory. For this task, a circular plot of 500 m\u003csup\u003e2\u003c/sup\u003e was established, in which dasometric, physiographic and botanical information was recorded. Furthermore, a soil profile study was carried out, opening the corresponding pit, identifying and describing different soil horizons, and taking a representative sample from each of them. The soil samples were processed in a specialized laboratory that meets the homologation and certification standards with regard to procedures and validation of results.\u003c/p\u003e \u003cp\u003eSite soil conditions were described from a set of studied variables, highlighting those which have the greatest influence on water availability in the soil. The variables used were those related to the presence of non-sampleable stoniness (NSS)(FAO \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and those related to the USDA textural fractions content (coarse elements (CE), sands (SAN), silts (SIL) and clays (CLA)) and humified organic matter (OM). In addition, to assess the differences in the chemical status of the soil, pH in water(WPH) and total carbonates presence (TC) were considered.\u003c/p\u003e \u003cp\u003eThe information obtained from the analyzed samples was statistically treated as paired observations. In this way, Normality in distribution of differences between sites with and without decline was verified (Kolmogorov-Smirnov test) and a Student's t-test was performed for paired data. The significance level for hypothesis testing of means equality in paired differences was set at 0.05.\u003c/p\u003e \u003cp\u003eIn turn, genetic horizons were identified for each profile, thus allowing us to approximate the degree of evolution and assess changes in physical conditions (textural and structural) derived from the presence of markedly clayey and/or strongly cemented horizons or relatively continuous hard rock. The depth at which a notable change in permeability conditions, aeration and water retention capacity was observed (change in USDA textural type) was considered as a new study variable, termed \u0026lsquo;easily explored depth\u0026rsquo; (EED).\u003c/p\u003e \u003cp\u003eFinally, all analyzed profiles were classified, using the classification system proposed by FAO-UNESCO (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), for which different diagnostic elements were previously identified in accordance with criteria established by this taxonomic system.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe soil profile characterizations in inventoried plots are summarized in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. It can be observed that, from a physiographic perspective, all site profiles showing decline have a south-facing orientation (or at least close to this orientation), which is an obvious predisposing factor to decline. Conditions of hydric stress are increased, especially in summer, when demand for water is greater.\u003c/p\u003e \u003cp\u003eThe depths of the profiles differ, although 80% present more or less continuous hard rock at a depth of less than 1 m (leptic conditions according to WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)). There is also a notable presence of non-sampleable stoniness and coarse elements, with 80% of the profiles having less than 40% fine earth (skeletic or hyperskeletic features for WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eAs regards texture, equilibrated texture horizons dominate (loam and sandy clay loam), making up around 50% of the total. There are also horizons of coarse textures (sandy loam and loamy sand), approximately 30%, and of slightly imbalanced fine textures (clay loam and silt loam), and even fine textures (clay). The profiles are mostly homogeneous in terms of texture, although some present a marked heterogeneity, which leads to sudden changes in permeability and aeration conditions within the profile (abruptic qualifier of WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eFrom a biochemical perspective, organic matter content is moderate-low, and dominant soil reaction is either strongly or extremely basic, especially in sites that do not show decline. Furthermore, the majority of sites where decline is observed present a scarcity or absence of inactive carbonates (non-calcareous material).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSoil variables at each study site (final letter of the site label indicates whether it shows decline, letter D, or if it does not, letter N)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGenetic Horizon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDepth\u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNNS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eUSDA Texture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWPH\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSAN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSIL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCLA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTexture classes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAlmenara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS01N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eClay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eClay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS01D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy clay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSoneja\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS02N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLoam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLoam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e54.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS02D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGilet-Sagunto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS03N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy clay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy clay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS03D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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\u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS04D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e 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align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSandy clay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGuadassuar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS06N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLoam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" 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\u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eClay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eClay loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eJijona-Alicante\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS10N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLoam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e71.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLoam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e73.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS10D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSilt loam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e84.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eNNS, non-sampleable stoniness (%); CE, coarse elements (%), SAN, sands (% in fine earth fraction); SIL, silts (% in fine earth fraction); CLA, clays (% in fine earth fraction); OM, organic matter (% in fine earth fraction); CT, total carbonates (% in fine earth fraction); WPH, pH in water.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNo significant differences were observed among the mean values of the studied variables according to the decline factor, with exception of the easily explored depth (EED). Hence, this variable is the only one that explains differences between sites with and without decline. The result of the statistical contrast for paired data, the differences in values of the studied variables between sites with decline and without decline, is shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of soil variables for sites with decline (labeled with the letter D in brackets) and non-decline (labeled with the letter N in brackets) based on t-test (significant t values with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 are in bold)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eDescriptive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eNormality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eRelated (paired) differences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ of\u003c/p\u003e \u003cp\u003eKolmogorov-Smirnov\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e -value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e -value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCE(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCE(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAN(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e17.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAN(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIL(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e14.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIL(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLA(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLA(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOM(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOM(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWPH(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWPH(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e21.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTD(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e34.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTD(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEED(N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e22.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e25.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e2.76\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEED(D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eCE, coarse elements (%), SAN, sands (% in fine earth fraction); SIL, silts (% in fine earth fraction); CLA, clays (% in fine earth fraction); OM, organic matter (% in fine earth fraction); WPH, pH in water; CT, total carbonates (% in fine earth fraction); TD, total depth (cm); EED, easily explored depth (cm).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding the degree of development, there is a wide variation among the profiles, from scarcely-developed young soils, without intermediate horizons and which usually lay directly over consolidated bedrock, to soils with highly evolved profiles, in which appears a genetic horizon of accumulation, with a notable presence of clay.\u003c/p\u003e \u003cp\u003eFinally, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents a classification of soils evaluated according to the FAO-UNESCO WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The soils in which it is possible to identify an argic diagnostic horizon are associated in all cases with sites where decline is observed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe phenomenon of decline and death of forest tree species is particularly complex as it involves a varied set of commonly interdependent factors (Manion \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Ciesla and Donaubauer \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1994\u003c/span\u003e, La Manna and Rajchenberg, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This notion is corroborated by the fact that the observed mortality was relatively heterogeneous at sites with decline and in their immediate surroundings. Some sites presented isolated dead trees in the same physiographic situation, while at others the dead trees appeared in relatively contiguous group sin similar physiographic situations. In the most severe cases, mortality affected all, or almost all, of the cover previously present at the site.\u003c/p\u003e \u003cp\u003eIn the Mediterranean area analyzed, an irregular rainfall regime and high thermal efficiency of the climate (globally mesothermic according to Thornthwaite (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1948\u003c/span\u003e)) result in a clearly defined drought period, which lasts more than three months, coinciding with the period of highest temperatures (summer months).\u003c/p\u003e \u003cp\u003eThese climatic conditions, typical of a genuine Mediterranean climate (Pe\u0026ntilde;uelas et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) lead to a deficient water balance, which exposes vegetation to high levels of water stress. This entails a high level of vulnerability to episodes of low precipitation (drought), which can occur unexpectedly and become particularly intense. In the Comunidad Valenciana (Spain) this is a recurrent situation, having been verified in 2014 and in the immediately preceding years (Garc\u0026iacute;a de la Serrana 2015).\u003c/p\u003e \u003cp\u003eForest dieback, a process determined by multiple factors, manifests the different behaviours of species, the structure of their populations and the interspecific interactions that develop within them (Lloret et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).Together with the restrictions imposed by site conditions, differences in life history characteristics and species resilience increase the heterogeneity within the forest as regards predisposition to drought damage, with different rates and spatial patterns of decline among coexisting tree species (Suarez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Gitlin et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Fensham and Fairfax \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Newbery and Lingenfelder \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Consequently, the spatial pattern of decline at site-scale cannot always be attributed to the variability in physical environment conditions, and more specifically to the heterogeneity of soil conditions.\u003c/p\u003e \u003cp\u003eAt Guadassuar, Lliria and Orihuela, the soils in sites with decline are similar to those in sites where decline is not present; hence decline cannot be attributed to differences in soils at site level. The causes of the decline at these locations should, therefore, be sought in other predisposing factors such as: (a) consequences of different disturbances which generate physiological dysfunctions (for example, soil compaction due to recreational use in Guadassuar); (b) situation in locally drier landscape positions (Suarez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) in the case of Lliria; (c) exacerbated marginal climatic conditions (G\u0026oacute;mez-Sanz \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as in the case of Orihuela, where good soil conditions do little to alleviate the damaging effect of drought. Under the poor climatic environment at Orihuela, good soil conditions favored excessive extension of the root system in non-drought years, making it hydraulically unviable in the face of a relatively intensive drought episode (Mart\u0026iacute;nez-Vilalta and Pi\u0026ntilde;ol \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Collins and Bra 2007).\u003c/p\u003e \u003cp\u003eIn contrast, the role of the soil was found to be highly relevant as a predisposing factor at the rest of the locations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This confirms the statement by Gitlin et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), that the inherent spatial variability in site conditions can underlie the irregularity of small-scale mortality patterns.\u003c/p\u003e \u003cp\u003eHowever, not all soil features are equally determinant. Differences in biological (organic matter content) and chemical (soil reaction and presence of carbonates) properties do not appear to be related to the observed response. Although acidic or neutral reaction soils are associated with decline episodes in all the cases analyzed, according to their autoecology (Gandullo and S\u0026aacute;nchez \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), Aleppo pine is tolerant to these acidity values (pH in water), so the effect on predisposition to decline is not sufficiently clear. However, the metabolic response to these chemical conditions could predispose the trees that live in these conditions to the synergistic effect of other factors that contribute to decline.\u003c/p\u003e \u003cp\u003eThis is not the case with physical properties, which have been shown to be much more explanatory in the observed decline. Of the set of soil characteristics, those that allow water availability to be decoupled from the purely climatic component associated with the rainfall pattern are key to vegetation survival (Nadal-Sala et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This quality is determined by the ability of the soil to store water and make it available to vegetation efficiently.\u003c/p\u003e \u003cp\u003eThe availability of water to tree roots is highly dependent on available soil volume and its porosity. Both attributes are nuanced by their internal variability (within the soil profile), closely linked to the degree of soil evolution. This makes it necessary to assess the way in which the properties determining soil moisture vary with depth, especially with regard to the soil volume easily explored by roots (Suarez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), from stoniness (which increases the infiltration capacity of soil but reduces its effective volume) (Hlav\u0026aacute;čikov\u0026aacute; et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Preisler et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), to textural class (percentages of sand, silt and clay that determine the state and behavior of water and air in the soil) (Colins and Bra 2007) and to organic matter content as structure-creating agent (Six et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDevelopment of root system consumes a large part of primary production (McDowell et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and therefore requires a compromise between developing and maintaining a larger root system and the additional water it can provide (Jackson et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Consequently, those sites with well developed, deep soils will host individuals with a more extensive, hydraulically balanced root system, which implies an advantage in water-limited environments over other individuals growing on shallow soil sand therefore shallower root systems (Nadal-Sala et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSoil depth stands out as a property that clearly predisposes trees to decline problems. The volume explored by radical systems in shallow or poorly developed soils is very low (Leptosols in WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)), and this is frequently accompanied by low water retention capacity (these soils tend to be particularly stony, showing skeletic, or even hyperskeletic, conditions). On such soils, individuals do not usually develop an adequate root system, which makes them especially vulnerable to drought as a trigger of decline (Schenk and Jackson \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Preisler et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This is the case at sites where mortality is present in Jalance and Jijona-Alicante.\u003c/p\u003e \u003cp\u003eIn more developed soils, the most determinant characteristic as regards predisposition to decline is textural variability according to profile depth, which is closely related to the degree of evolution of the soil. Hence, soils with obvious profile heterogeneity (presence of intermediate accumulation horizon, argic in WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)), are significantly associated with sites where decline is present. This situation is even more marked in soils with abrupt textural changes in their profiles (abruptic qualifier from the WRB (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eThe presence of an argic horizon conditions root development, limiting it almost entirely to the surface horizon, thus considerably reducing the soil volume explored by roots in search of water and nutrients (low effective depth of soil). The enduring nature of trees and their ability to change resource allocation and hydraulic architecture throughout their lives largely explain this behavior. If, in addition, the surface horizon has a texture that does not promote water retention (sandy and/or low content in fine earth), as occurs in Vilamarxant, Almenara and Gilet-Sagunto, the predisposition to decline is considerably accentuated.\u003c/p\u003e \u003cp\u003eThe opposite occurs in the case of soils with homogeneous profiles (relatively isotropic), without a clear development of an intermediate accumulation horizon. Although effective depth may be limited by the presence of continuous hard rock at medium depths (WRB leptic qualifier (IUSS Working Group \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)), soil volume is sufficient, in the presence of an adequate textural class (not unbalanced coarse or coarse and not highly stony), to provide a water retention capacity capable of sufficiently mitigating certain levels of water stress, thus reducing or buffering the physiological dysfunctions that lead to decline.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eWithin a synoptic region prone to drought, spatial patterns of decline are often quite heterogeneous and irregular at finer spatial scales. However, within this variability, specific episodes of decline are significantly associated with stands where soils present a shallow effective depth due to a low degree of profile development or to marked textural anisotropy associated with the presence of particularly clayey horizons that cause abrupt changes in permeability and aeration.\u003c/p\u003e \u003cp\u003eThe site soil conditions have thus been identified as a main predisposing factor, modulating the effects of drought as a triggering factor in the decline of Aleppo pine stands. In the analyzed area, episodes of notable reduction in precipitation water inflows (drought in 2014 and in the immediately preceding years) led to critical levels of water stress. Some trees were physiologically destabilized by the catalytic effect of local site conditions (physiographic and/or soil conditions), which was manifested in individual, group or superficial mortality.\u003c/p\u003e \u003cp\u003eThe notion that the climate in the Mediterranean basin will evolve towards warmer and more arid scenarios is constantly garnering greater acceptance. The consequences of this predicted climate change on arboreal stands in general, and Aleppo pine stands in particular, will be highly nuanced by specific site conditions, especially those relating to soil, giving rise to highly heterogeneous decline patterns on a local scale. Hence, the importance of taking into consideration the soil diversity inherent to the territory with a view to implementing more adaptive and flexible planning as well as management models that seek to anticipate emerging problems or challenges associated with the effects of global change dynamics, and especially, those linked to climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding. \u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests. \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions. \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study conception and design were carried out by Valent\u0026iacute;n G\u0026oacute;mez-Sanz and Rafael Serrada Hierro. All authors performed in data collection and analysis. The draft of the manuscript was written by Valent\u0026iacute;n G\u0026oacute;mez-Sanz and all authors provided comments and suggestions on it and approved manuscript final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Emilio Gonz\u0026aacute;lez and Eduardo P\u0026eacute;res Laorga, technical staff of the \u0026quot;Servicio de Ordenaci\u0026oacute;n y Gesti\u0026oacute;n Forestal de la Conseller\u0026iacute;a D\u0026apos;Infraestructures, Territori I Medi Ambient de la Generalitat Valenciana\u0026rdquo;, for making the study possible, along with the staff and service agents who carry out Forest Health related functions in VAERSA and in the Conseller\u0026iacute;a for their help in facilitating the field work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAllen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Kitzberger T, Rigling A, Breshears DD, Hogg EH, Gonzalez P, Fensham R, Zhang Z, Castro J, Demidova N, Lim J-H, Allard G, Running SW, Semerci A, Cobb N (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. 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For Ecol Manage 255:686\u0026ndash;696. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foreco.2007.09.071\u003c/span\u003e\u003cspan address=\"10.1016/j.foreco.2007.09.071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStatements \u0026amp; Declarations\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Edaphic heterogeneity, forest dieback, textural anisotropy, Mediterranean climate, soil evolution degree","lastPublishedDoi":"10.21203/rs.3.rs-3813100/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3813100/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u0026bull; Background and Aims. Vegetative decline in individuals of plant populations is a phenomenon that involves multiple factors, both biotic and abiotic, that lead to highly irregular and complex spatial patterns of mortality at stand or forest scale. Although it might be assumed that site soil conditions are a predisposing factor to this phenomenon, very little research has specifically focused on this aspect, hence the lack of knowledge in this regard is evident.\u003c/p\u003e \u003cp\u003e\u0026bull; Methods. Soil characterization was carried out at 20 sites (10 with evidence of decline and another 10 with no signs of decline) and the results were related to their role as modulation factor of the drought effects, which is the main cause of the observed decline in Aleppo pine stands in the Comunidad Valenciana (Spain).\u003c/p\u003e \u003cp\u003e\u0026bull; Results. The soil properties which were found to be the most explanatory are those associated with soil quality in terms of available space for root exploration, which is vital for nutrition and, above all, water uptake. Episodes of decline are associated with stands where soils present a shallow effective depth due to a low degree of profile development or through marked textural anisotropy because of particularly clayey horizons that cause abrupt changes in permeability and aeration.\u003c/p\u003e \u003cp\u003e\u0026bull; Conclusion. The inherent soil diversity acts as a predisposing driver to this physiological process that generates a heterogeneous spatial mosaic of patches with different degrees of decline.\u003c/p\u003e","manuscriptTitle":"Site-scale soil conditions influencing the decline of Aleppo pine stands in Mediterranean Spanish woodland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-05 18:13:34","doi":"10.21203/rs.3.rs-3813100/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-01-23T11:26:05+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-01-05T14:56:06+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-02T19:33:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2023-12-29T10:03:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-28T09:09:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2023-12-27T06:59:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6d9e2230-d313-4686-975e-83701976d7f6","owner":[],"postedDate":"January 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-08T15:09:32+00:00","versionOfRecord":{"articleIdentity":"rs-3813100","link":"https://doi.org/10.1007/s11104-024-06638-2","journal":{"identity":"plant-and-soil","isVorOnly":false,"title":"Plant and Soil"},"publishedOn":"2024-04-01 15:01:29","publishedOnDateReadable":"April 1st, 2024"},"versionCreatedAt":"2024-01-05 18:13:34","video":"","vorDoi":"10.1007/s11104-024-06638-2","vorDoiUrl":"https://doi.org/10.1007/s11104-024-06638-2","workflowStages":[]},"version":"v1","identity":"rs-3813100","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3813100","identity":"rs-3813100","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}