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J. Hydrol. Hydromech., 69, 2021, 4, 436–446 ©2021. This is an open access article distributed DOI: 10.2478/johh-2021-0025 under the Creative Commons Attribution ISSN 1338-4333 NonCommercial-NoDerivatives 4.0 License Effect of mature spruce forest on canopy interception in subalpine conditions during three growing seasons 1 2, 3 4 1 1 5 Martin Jančo , Pavel Mezei , Andrej Kvas , Michal Danko , Patrik Sleziak , Jozef Minďáš , Jaroslav 4* Škvarenina Institute of Hydrology, Slovak Academy of Sciences, Dúbravská cesta 9, 841 04 Bratislava, Slovakia. Institute of Forest Ecology, Slovak Academy of Sciences, Štúrova 2, 960 53 Zvolen, Slovakia. Department of Forest Protection, Faculty of Forestry, Technical University in Zvolen, T.G. Masaryka 24, 960 01 Zvolen, Slovakia. Department of Natural Environment, Faculty of Forestry, Technical University in Zvolen, T.G. Masaryka 24, 960 01 Zvolen, Slovakia. Ecological & Forestry Research Agency EFRA, Medený hámor 11, 974 01 Banská Bystrica, Slovakia. Corresponding author. Tel.: +421 455 206 209. E-mail: email@example.com Abstract: The interception process in subalpine Norway spruce stands plays an important role in the distribution of throughfall. The natural mountain spruce forest where our measurements of throughfall and gross precipitation were carried out, is located on the tree line at an elevation of 1,420 m a.s.l. in the Western Tatra Mountains (Slovakia, Central Europe). This paper presents an evaluation of the interception process in a natural mature spruce stand during the growing season from May to October in 2018–2020. We also analyzed the daily precipitation events within each growing season and assigned to them individual synoptic types. The amount and distribution of precipitation during the growing season plays an important role in the precipitation-interception process, which confirming the evaluation of individual synoptic situations. During the monitored growing seasons, precipitation was normal (2018), sub-normal (2019) and above-normal (2020) in comparison with long-term precipitation (1988–2017). We recorded the highest precipitation in the normal and above-normal precipitation years during the north-eastern cyclonic synoptic situation (NEc). During these two periods, interception showed the lowest values in the dripping zone at the crown periphery, while in the precipitation sub-normal period (2019), the lowest interception was reached by the canopy gap. In the central crown zone near the stem, interception reached the highest value in each growing season. In the evaluated vegetation periods, interception reached values in the range of 19.6–24.1% of gross precipitation total in the canopy gap, 8.3–22.2% in the dripping zone at the crown periphery and 45.7–51.6% in the central crown zone near the stem. These regimes are expected to change in the Western Tatra Mts., as they have been affected by windstorms and insect outbreaks in recent decades. Under disturbance regimes, changes in interception as well as vegetation, at least for some period of time, are unavoidable. Keywords: Precipitation; Interception; Synoptic types; Norway spruce (Picea abies L. Karst.); Growing season. INTRODUCTION part of the rainwater is used or retained on the surface of trees or plants. This water neither infiltrates into the soil nor drains in In the conditions of the Western Carpathians, atmospheric the form of surface runoff. Therefore, the amount of intercepted precipitation is almost the only income component of the water precipitation that returns to the atmosphere upon evaporation is balance (Minďáš, 2003). Forest canopies standing up in the air often referred to as interception loss (Dohnal et al., 2014; impede precipitation from reaching the ground. A portion of Gregersen et al., 2007; Llorens and Gallart, 2000; Šraj et al., precipitation is inevitably intercepted by the canopy (canopy 2008; Ward and Trimble, 2003). interception), flows along the stem to the ground surface From the point of view of the water balance, the interception (stemflow), drips from the foliage and branches or passes of precipitation in spruce stands is quite significant. However, through canopy openings to the ground (throughfall), or is its magnitude varies in an orographically and vertically divided further intercepted by ground plants or the forest floor (litter area. Interception plays a significant negative role in spruce interception). These processes cause a reduction in precipitation forests at lower altitudes. By contrast, in mountain locations, quantity and a redistribution of precipitation towards the soil the interception process of liquid precipitation changes due to (Arnell, 2002; Chang, 2013; Klamerus-Iwan et al., 2020; occult precipitation from fog and interception may be perceived Sadeghi et al., 2020; Střelcová et al., 2006). The water regime very differently, from a significantly negative item of the water of forest stands is also determined by the precipitation condi- balance of stands up to a positive item, depending on the local tions of a given locality as well as by the properties of soils. conditions (Bartík et al., 2016; Chroust, 1997; Kantor, 1981; Out of the many properties of a stand, the amount and distribu- Krečmer, 1973; Krečmer et al., 1981; Valtýni, 1986). tion of the assimilation area is the most important factor for The topic of interception losses in forest hydrology has long affecting the water balance in an ecosystem. Indeed, it deter- received considerable attention. Nevertheless, we do not yet mines the amount of transpiration as well as the retention of have enough reliable quantitative data, particularly from specif- precipitation on the surface, i.e. interception (Bruijnzeel, 2004; ic mountain habitats. One such habitat consists of climax moun- Landsberg and Waring, 2014; Pypker et al., 2011; Shelton, tain spruce trees growing in extreme mountain climate condi- 2009; Zabret et al., 2018). Interception is the process in which tions below the tree line (Minďáš et al., 2018; Šípek et al., 436 Effect of mature spruce forest on canopy interception in subalpine conditions during three growing seasons 2020). Mountain spruce forests perform a number of important MATERIAL AND METHODS ecosystem services in the country (e.g. snow accumulation, Study site protection against avalanches and soil erosion, a headwater function) as stated by, for instance, Fleischer et al. (2017), The Červenec study site is situated in a mature (climax) Holko et al. (2021), Pichler et al. (2010) and Seidl et al. (2019). spruce stand in the Jalovecká valley in the Western Tatra Mts. The long-distance transport of air pollution and acid deposition (latitude 49.183617°N, longitude 19.641944°E, altitude 1,420 from the 1970s through the 1990s in many mountain massifs, m a.s.l.) (Fig. 1.). This valley is characterized with its quater- particularly in Western and Central Europe, caused a decline in nary glacial terrain modelling. The whole research plot is locat- natural mountain spruces (e.g Fazekašová et al., 2016; Minďáš ed within a geologic boundary between the Crystallinic and and Škvarenina, 1995; Oulehle et al., 2013; Rehfuess, 1985; Mesozoic zones in the Inner Western Carpathians. The predom- Vacek et al., 2015). The onset of climate change, accompanied inant crystalline rocks are granodiorites and rules covered with by natural hazards such as extreme temperatures, drought, cambisol podsoles and accompanied with lithosols and rankers. storms and the consequent calamities of bark beetles, has insti- From the Mesozoic rocks, the dominant types include calcites gated thelarge-scale decline of fragile mountain spruces and dolomites with developed cambisol rendzinas (Bartík et al., (Grodzki et al., 2006; Hroššo et al., 2020; Mezei et al., 2017; 2014, 2016; Holko et al., 2020). This part of the Western Tatras Seidl et al., 2011). Many recent works have also pointed to belongs to the cold climatic region, the cold mountain and very changes in the basic hydrological and ecological functions of wet district (Lapin et al., 2002). The annual average air temper- affected areas (Bartík et al., 2019; Bernsteinová et al., 2015; ature at Červenec is 3.0 °C and long-term annual precipitation Černohous et al., 2018; Gömöryová et al., 2017; Homolák et is 1,450 mm (Danáčová et al., 2019). al., 2020; Hotový and Jeníček, 2020; Iovino et al., 2018; The main vegetation cover of the study plots comprises for- Jeniček et al. 2017; Lichner et al. 2020; Švihla et al., 2016). est ecosystems, predominantly following forest types: Sorbeto- Due to the aforementioned reasons, it has become necessary to Piceetum (9410 Acidophilous spruce forests (Vaccinio- examine in detail the water balance of mountain spruces, in- Piceetea)); Cembreto-Piceetum (9420 Alpine Larix decidua cluding with regard to canopy interception. and Pinus cembra forests); above the timberline (4070 Bushes The present research was conducted in a natural mountain with Pinus mugo) (Hančinský, 1972; Stanová and Valachovič, Norway spruce (Picea abies L. Karst.) forest in the Western 2002). Tatra Mountains (Slovakia). It was designed to: (i) examine The predominant tree species is Norway spruce (Picea abies estimation of spruce canopy interception including the descrip- L. Karst.), accounting for 100% of the tree species coverage. tion of its small-scale spatial variability; (ii) determine the inter- Sites characterized by loosened canopy and the understorey ception losses of spruce stands based on data from three consec- include rowan (Sorbus aucuparia L.), raspberry brushes (Rubus utive growing seasons with different precipitation amounts ideaus L.), bilberry (Vaccinium myrtillus L.) and natural spruce (average, dry, wet) and determine the impact of atmospheric regeneration. The plot has a south-east exposition with a slope synoptic types on gross precipitation; and (iii) analyze the spatial of 20°–33° and an area of about 0.3 ha. In the over-130-year- and temporal variability of throughfall in the three growing old stand the average tree height is 26.8 m, the average stem seasons and to compare these values with those published for diameter at breast heigh is 40.5 cm and the stocking density, at spruce ecosystems with similar ecological conditions. about 0.6, is low (Oreňák et al., 2013). Fig. 1. Research plot Červenec. 437 Martin Jančo, Pavel Mezei, Andrej Kvas, Michal Danko, Patrik Sleziak, Jozef Minďáš, Jaroslav Škvarenina Precipitation measurements Data analysis The amount of precipitation was recorded in the growing In the period from 1 May to 31 October in years 2018, 2019 seasons of 2018–2020. The growing season in these areas be- and 2020, each day was assigned the appropriate type of synop- gins in early May and concludes around the end of October, tic situation (Slovak Hydrometeorological Institute, 2021) and, depending on the weather conditions. The data were sampled in in the case of precipitation on a given day,the appropriate pre- approximately two-week intervals, as the research plot is rather cipitation total as well.Atmospheric circulation was character- remote. Water precipitation was collected in ten standard ized by the synoptic types according to Ballon et al. (1964) and Czechoslovak rain gauges METRA (an orifice area of 500 cm Brádka et al. (1961), updated by Racko (1996), which are ex- (Fig. 2.). The primary categorization of the measurements of tensively used in synoptic and climatological practice in the precipitation was in an open area vs. in the forest stand. Daily Czech and Slovak republics. Czech and Slovak types are basi- precipitation totals were recorded by means of automatic cally a modification of the catalogue of Hess and Brezowsky (1977) to optimally suit the conditions in the former Czecho- weighing rain gauge TRwS 504 with an orifice area of 500 cm , we based our evaluation of synoptic situation on this metric. slovakia (Beranova and Huth, 2005). The Czech and Slovak One standard METRA rain gauge was located on an open area, catalogue consists of 28 types, leaving no days unclassified. For situated at a sufficient distance from the forest stand to limit or the list of types see Table 1. Similarly, the synoptic types were eliminate the influence of the surrounding standing trees on the applied to characterize pollutant concentrations in precipitation amount of precipitation as a result of the air flow. Due to the (Fišák and Tesař, 2015; Fišák et al., 2004). structure of the forest stand, the rain gauges were installed in The recorded totals of throughfall in individual measure- the canopy gap (GAP), in the dripping zone at the crown pe- ments were first expressed as the arithmetic mean for each riphery (CROWN) and in the central crown zone near the stem locality in the stand. Interception loss (IL)in mm was calculated (STEM) (Fig. 2.). In the forest, three METRA rain gauges were as the difference between gross precipitation (PG) and through- located in each of these three localities. We considered this fall (TF)using the following equation: research design sufficient for preliminary research on canopy interception in mountain forest, mainly due to rough terrain and IP=−T (1) LG F accessibility regarding periodical measurements. The canopy gap was characterized as an unconnected area The interception ratio (I) in % was then calculated as fol- by trees or their branches in a stand without trees with an area lows: of about 20–30 m . Rain gauges were placed in the middle of this space. The dripping zone at the crown periphery represent- I=×100 (2) ed precipitation, which was caught in the surface parts of the G crown and dripped into the sub-canopy space after canopy saturation. In the central crown zone near the stem, rain gauges All analyses and plot displays were performed using Stat- were located near the stem (Bartík et al., 2016; Dohnal et al., graphics Centurion 16, Statistica 12 and Microsoft Excel 2016 2014; Minďáš et al., 2018; Oreňák et al., 2013). Fig. 2. Throughfall measurements in the mature spruce forest in the research plot Červenec: in the canopy gap „GAP“ (A), in the dripping zone at the crown periphery „CROWN“ (B) and in the central crown zone near the stem „STEM“ (C). 438 Effect of mature spruce forest on canopy interception in subalpine conditions during three growing seasons software. When comparing the equality of the mean of the two We used correlation and regression analysis to determine the dependent samples, we first needed to ascertain whether the dependence of interception losses in the stand (mm) on gross data (interception in %) showed a normal distribution. To de- precipitation. The statistical significance of the linear relation- termine whether the data came from a normal distribution, we ship between the samples was tested with analysis of variance used the Shapiro–Wilk test. If the p-value ≥0.05, the data at a 95% confidence level. If p-value ≤0.05, the relationship showed a normal distribution, while if the p-value <0.05 the was not significant. data did not come from a normal distribution. If the compared samples showed a normal distribution, we used Student’s RESULTS AND DISCUSSION paired t-test. If the distribution of one of the compared samples Evaluation of synoptic situations and precipitation totals was not normal, we used the non-parametric Wilcoxon paired test. The level of significance (α) in the test was set at 95% in The occurrence of precipitation in individual synoptic types all cases, so if the p-value ≤0.05, we were able to state that the is presented in Table 1. For an illustration of the occurrence of difference between the individual samples was statistically individual synoptic types during the monitored periods in significant. 2018–2020, the absolute frequency of these types is also given in Table 1 (column 1 (days)). Table 1. Frequency of synoptic types (ST) in days, gross precipitation total (PG) and percentage contribution (PC) of each synoptic situation to the precipitation total of the months May–October in the years 2018, 2019 and 2020. 2018 2019 2020 Synoptic types ST PG PC ST PG PC ST PG PC (days) (mm) (%) (days) (mm) (%) (days) (mm) (%) B 21 83.2 10.7 22 17.1 28.5 17 90.5 8.8 Bp 20 119.7 15.5 24 86.7 14.1 5 72.0 7.0 C 4 28.2 3.6 5 112.2 18.3 6 105.1 10.3 Cv 11 26.9 3.5 2 7.8 1.3 19 155.6 15.2 NWc 13 131.5 17.0 1 5.8 0.9 3 72.7 7.1 NEc 17 288.4 37.3 7 10.0 1.6 12 247.3 24.2 Nc 2 23.7 3.1 10 26.5 4.3 3 33.3 3.3 Wc 3 6.2 1.0 7 48.5 4.7 Wcs 7 33.8 5.5 5 31.0 3.0 SWc1 3 5.2 0.8 8 41.9 4.1 SWc2 7 38.6 6.3 4 2.2 0.2 SWc3 2 24.4 2.4 SEc 10 32.2 4.2 3 11.9 1.9 5 15.7 1.5 Ec 3 0.2 0.0 3 4.7 0.5 Vfz 3 19.1 3.1 2 20.2 2.0 A 2 0.0 0.0 7 10.6 1.7 9 0.2 0.0 Ap1 8 31.6 5.1 7 9.2 0.9 Ap2 13 4.7 0.6 7 1.8 0.3 8 4.2 0.4 Ap3 5 0.5 0.1 NWa 8 0.9 0.1 13 8.9 1.4 11 5.2 0.5 NEa 13 8.7 1.1 1 0.1 0.0 9 6.3 0.6 Wa 2 1.4 0.2 7 3.0 0.5 8 0.7 0,1 Wal 20 6.3 0.8 0.0 0.0 14 18.6 1.8 Sa 11 0.2 0.0 16 0.5 0.1 3 0.1 0.0 SEa 1 2.4 0.3 7 16.6 2.7 3 11.4 1.1 SWa 7 0.3 0.0 10 0.8 0.1 6 2.6 0.3 Ea 9 15.2 2.0 3 0.5 0.1 5 0.0 0,0 Sume of type c 98 733.7 94.8 100 539.1 87.8 101 965.0 94.3 Sume of type a 86 40.1 5.2 84 74.9 12.2 83 58.6 5.7 Sume of c+a 184 773.8 100.0 184 614.0 100.0 184 1023.6 100.0 Synoptic situations: Wc, west cyclonic; Wcs, west cyclonic with southern pathway; Wa, west anticyclonic; Wal, west anticyclonic of summer type; NWc, north-west cyclonic; NWa, north-west anticyclonic; Nc, north cyclonic; NEc, north-east cyclonic; NEa, north-east anticyclonic; Ec, east cyclonic; Ea, east anticyclonic; SEc, south-east cyclonic; SEa, south-east anticyclonic; Sa, south anticyclonic; SWc1, south-west cyclonic of the 1st type; SWc2, south-west cyclonic of the 2nd type; SWc3, south-west cyclonic of the 3rd type; SWa, south-west anticyclonic; B, trough over Central Europe; Bp, travelling trough; Vfz, entry of the frontal zone; C, cyclone over Central Europe; Cv, upper cyclone; A, anticyclone over Central Europe; Ap1, travelling anticyclone of the 1st type; Ap2, travelling anticyclone of the 2nd type; Ap3, travelling anticyclone of the 3rd type 439 Martin Jančo, Pavel Mezei, Andrej Kvas, Michal Danko, Patrik Sleziak, Jozef Minďáš, Jaroslav Škvarenina Year 2018: a so-called normal/average year (102% of the obsevatory at Kasper Peak (elevation 1987 m a.s.l.). In addition long-term precipitation average for May–October). Almost to the synoptic situation of NEc in the summer rain totals, the 95% of the precipitation from May to October 2018 fell in situation of Nc predominates. Compared to other, southern cyclonic weather types. The highest total precipitation fell on parts, the south-western cyclonic situations (SWc1 to SWc3) days with the synoptic situation of NEc, namely 288 mm, rep- bringgreater precipitation to the marginal northern parts of our resenting 37% of the total in the observed period. In the NEc territory only sporadically (Polčák and Mészáros, 2018). situation, the highest daily total (129 mm) recorded in 2018 fell on 18 July. Subsequently, large amounts of precipitation fell in Comparison of interception in individual zones of stand NWc 132 mm (17%), Bp 120 mm (16%) and B 83 mm (11%). measurement during growing seasons (2018–2020) Types C, Cv SEc and Nc contributed only marginally (3–4%). The anticyclonic types, Ea, NWa and Wal, altogether contribut- The amount of precipitation had a significant effect on the ed about 4% to the total precipitation. values of interception during the analyzed growing seasons of Year 2019: a relatively dry year (85% of the long-term pre- 2018, 2019 and 2020. The distribution of sub-canopy precipita- cipitation average for May–October). Precipitation in 2019 fell tion within the natural spruce stand with reduced stocking den- in the following proportion: 88% for cyclonic types and 12% sity showed considerable heterogeneity. The recorded values of for anticyclone types of weather situations. During the period interception during vegetation periods fluctuated considerably. with synoptic situations B, almost 175 mm, representing 29% In the canopy gap, we recorded interception values of the gross of the total in the observed period. Then there were the follow- precipitation total in the range of 4.4–40.0% in the growing ing situations C 112 mm (18%) and Bp 87 mm (14%), together season of 2018, 7.0–39.3% in 2019 and 13.3–32.3% in 2020 SWc 44 mm (7%) and Wcs 34 mm (5.5%), and other cyclonic (Fig. 3.). Furthermore, in the canopy gap, there were two situa- types were below 5%. The highest daily total (64.2 mm) fell on tions in the growing season of 2019 and one situation in the 22 May in situation C. This situation C cyclone over Central growing season of 2020 when the measured precipitation total Europe lasted for five days from 19 to 23 May, during which a in the stand exceeded the gross precipitation. These situations total of 132 mm fell, representing about 21% of the precipita- could have been caused by the influence of the wind, which tion in the observed period. In 2019, in comparison with the transported precipitation captured in the canopy space into the area of the canopy gap. other years evaluated, there was more precipitation even in anticyclonic synoptic situations, mostly precipitation of a storm In the dripping zone at the crown periphery, we recorded the nature. The types Ap (together) accounted for about 34 mm highest variability of interception. One of the factors (5%), SEa for about 17 mm (3%) and A for 11 mm (2%). influencing values of interception during the vegetation period Year 2020: an above-normal year of precipitation (135% of is the occurrence of occult precipitation (Holko et al., 2009; the long-term precipitation average for the months of May– Krečmer, 1973; Minďáš et al., 2018; Vorčák et al., 2009). This October). In this year, cyclonic synoptic types predominated effect was most pronounced in the studied locality, when we (94% of the precipitation total), while anticyclonic types ac- recorded five cases in all evaluated periods with the throughfall counted for only 6%. As in 2018, the synoptic type NEc con- exceeding the gross precipitation. High levels of throughfall tributed the most to the total, with a total of 247 mm (24%). always occurred at the beginning of each growing season The highest daily total precipitation (77 mm) was reached again during a two-week period: for example, on 21 May 2020 we in the NEc situation on 30 September. It is worth mentioning recorded up to 42.9% higher throughfall than gross that the second-highest daily total (64 mm) was reached in the precipitation (Fig. 3.). We also registered significantly higher same synoptic situation NEc on 22 June. Synoptic types (Cv throughfall on 28 July 2018 at the highest recorded two-week 156 mm, 15%; C 105 mm (10%) also accounted for a more gross precipitation total (232.4 mm) of all three evaluated significant share of the total, so in summary, situations C and periods. In addition, occult precipitation by its interaction Cv represented up to 25% of the total. Regarding the othercy- reduces canopy storage capacity. The range of interception clonic types, B and Bp should be mentioned, as they collective- values in the dripping zone at the crown periphery ranged from ly contributed to a total of about 160 mm (15%). Out of the rest –17.9 to 53.7% in the growing season of 2018, from –17.3 to of the types, only the anticyclonic situations Wal and Ap con- 64.3% in 2019 and from –42.9 to 56.7% in 2020 (Fig. 3.). Out tributed above 1% of the total. of 12 measurements in the dripping zone at the crown The Western Tatras, as a massive mountain range, form the periphery, Bartík et al. (2016) reported up to 8 times higher north-western edge wall for precipitation-bearing western, throughfall than gross precipitation in a living spruce stand at northern and partly also north-eastern cyclonic situations. this locality during the growing season of 2014. In a spruce Compared to the other parts of Slovakia (Petrovič, 1972), the forest in the Orlické Mountains (960 m a.s.l.) in the growing character of precipitation hereis different. Indeed, in other seasons 1962–1966 during individual months, Krečmer (1968) regions of Slovakia, the most precipitation was brought by reported a significant variability of interception, ranging from synoptic situations with a western and north-western flow (Bp, an improvement of throughfall by 28.0% up to the canopy Wc, NWc and SWc). In the study area, the largest amount of interception of 25.0%. Fojt and Krečmer (1975) reported an precipitation wasobserved in the north-eastern cyclonic situa- enrichment of 15% by occult precipitation at the same locality tion (NEc) in 2018 and 2020. As mentioned by Krečmer during the growing season (6 months). Kantor (1981) reported a (1973), the mountain locality Šerlich (elevation 960 m a.s.l.) in negative interception of 2.0% in the growing season of 1978 the Orlické Mountains also classified the NEc type as the raini- during rainfall events with the occurrence of fog. In research est. The Orlické Mountains are located on the north-eastern conducted in North America, Lovett et al. (1982) reported border of the Czech Republic and Poland, where the geograph- enrichment with rainwater of 450 mm per year (20% of the ical effects of air flow and movement of active frontal and air annual gross precipitation) at an elevation above 1,200 m a.s.l. masses manifest similarly to those on the edge of the Western in a Douglas fir stand (Pseudotsuga menziesii), while Harr et al. Tatras. A similar opinion was expressed by Konček and Orlicz (1982) reported an improvement of 880 mm (30% of the annual (1974) for the Polish side of the Western Tatras, when they gross precipitation) in Oregon, also at an elevation above 1,200 analyzed the summer precipitation conditions of the mountain m a.s.l. in Douglas fir forests. 440 Effect of mature spruce forest on canopy interception in subalpine conditions during three growing seasons Fig. 3. Interception (%) in the canopy gap (GAP), in the dripping zone at the crown periphery (CROWN) and in the central crown zone near the stem (STEM) during the growing seasons of 2018–2020. In the central crown zone near the stem, interception reached crown zone near the stem. Also concerning this study site in the the highest values in most cases. In this locality, which is not living forest during the growing seasons of 2012–2015, Jančo et identical with the stemflow, the lowest amount of precipitation al. (2017) reported that average interception was 10.1% in the was able to penetrate due to the shape of the growing branches. canopy gap, 1.6% in the dripping zone at the crown periphery In the growing seasons, we recorded interception in the range and 70.6% in the central crown zone near the stem. Regrettably, of 36.2–87.8% in 2018, 37.1–81.7% in 2019 and 30.5–93.3% in both of the living stands used in the past with which we com- 2020 (Fig. 3.). pared our results are now dead. Expressing interception as the The calculated sums of throughfall (mm), interception losses average of these three localities (GAP, CROWN, STEM) dur- (mm), interception (%) and gross precipitation (mm) during the ing each evaluated growing season, interception reached 26.8% evaluated periods are given in Table 2. The canopy gap reached in 2018, 30.3% in 2019 and 28.3% in 2020. These interception a total interception loss of 163.7 mm (21.2% of the gross pre- values obtained in spruce forest support numerous previous cipitation total) in 2018, 120.5 mm (19.6%) in 2019 and 246.4 findings from Europe and North America that average conifer- mm (24.1%) in 2020. The dripping zone at the crown periphery ous forest interception ranges from 25.0 to 35.0% of the gross reached a total interception loss of 64.1 mm (8.3% of the gross precipitation total (Robinson and Ward, 2017) Furthermore, the precipitation total) in 2018, 136.4 mm (22.2%) in 2019 and values of average interception obtained here correspond to the 156.3 mm (15.3%) in 2020. The central crown zone near the results of other authors, who have reported values in the range stem reached a total interception loss of 395.2 mm (51.1% of of 23.0–38.0% for older spruce stands (e.g. Grelle et al., 1997; the gross precipitation total) in 2018, 300.9 mm (49.0%) in Grunicke et al., 2020; Halmová et al., 2006; Kofroňová et al., 2019 and 467.8 mm (45.7%) in 2020. When comparing indi- 2021; Tužinský, 2004; Viville et al., 1993). vidual localities, we recorded the lowest interception losses in We statistically compared the interception data (%) calculat- the growing seasons of 2018 and 2020 in the following order: ed from each measurement at individual localities in the stand the dripping zone at the crown periphery > canopy gap > the in each evaluated growing season (Fig. 4). A statistical evalua- central crown zone near the stem. An exception was the poorest tion of the results is given in Table 3. Based on the completed precipitation period of 2019, when we recorded the lowest Student’s paired t-test and the nonparametric Wilcoxon paired interception in the following order: the canopy gap > the drip- test, a statistically significant difference was not confirmed in ping zone at the crown periphery > the central crown zone near all growing seasons between the canopy gap and the dripping the stem. This could have been caused either by two recorded zone at the crown periphery. However, when comparing the situations, when the throughfall reached higher values than the central crown zone near the stem with these two localities, we gross precipitation, or by very warm weather, especially in the were able to see a significant difference (bold values in Table period June–October. The year 2019 was the warmest in Eu- 3) in all cases. rope since at least 1980, with the warmest period being June– August (European Centre for Medium-Range Weather Fore- Relationship between interception loss in individual zones casts and Copernicus Climate Change Service, 2020). The of stand measurement and gross precipitation warm growing season was also manifested by the highest val- ues of interception in the dripping zone at the crown periphery The expressed linear regression of the calculated values of in comparison with the growing seasons 2018 and 2020. Re- the interception loss (mm) on the amount of gross precipitation garding this study site in the living forest during the growing at the measured localities in the stand (GAP, CROWN, STEM) seasons of 2007–2011, Oreňák et al. (2013) reported that aver- are shown in Figs. 5, 6 and 7. Above the graphs are the linear age interception was 27.0% in the canopy gap, 20% in the regression equation, the coefficient of determination (R ), Pear- dripping zone at the crown periphery and 63% in the central son’s correlation coefficient (R) and p-value, informing us 441 Martin Jančo, Pavel Mezei, Andrej Kvas, Michal Danko, Patrik Sleziak, Jozef Minďáš, Jaroslav Škvarenina Table 2. Precipitation total and interception (mm, %) in the growing seasons of 2018–2020. Growing season Position of rain gauges 2018 2019 2020 Throughfall [mm] 610.1 493.5 777.2 Canopy gap Interception [mm, %] 163.7 120.5 246.4 21.2 19.6 24.1 Throughfall [mm] 709.7 477.6 867.3 Dripping zone at the crown periphery Interception [mm, %] 64.1 136.4 156.3 8.3 22.2 15.3 Throughfall [mm] 378.6 313.1 555.8 Central crown zone near the stem Interception [mm, %] 395.2 300.9 467.8 51.1 49.0 45.7 Gross precipitation [mm] Open area 773.8 614.0 1023.6 Table 3. Statistical characteristics of interception (%). Count Average Standard Coeff. of Minimum Maximum Range Shapiro–Wilk deviation variation p-value GAP 2018 12 19.4 10.21 52.61 4.4 40.0 35.6 0.8752 CROWN 2018 12 22.4 20.43 91.29 –17.9 53.7 71.6 0.7529 STEM 2018 12 58.6 15.60 26.64 36.1 87.8 51.7 0.8792 GAP 2019 11 18.8 15.22 80.97 –7.0 39.3 46.3 0.6239 CROWN 2019 11 30.8 22.17 71.89 –17.3 64.3 81.6 0.7255 STEM 2019 11 57.6 18.78 32.61 37.1 81.7 44.6 0.0352 GAP 2020 12 19.0 13.20 69.33 –13.3 32.3 45.6 0.0292 CROWN 2020 12 15.9 23.86 150.20 –42.9 56.7 99.6 0.1668 STEM 2020 12 50.7 16.54 32.63 30.5 93.3 62.8 0.0450 p* - result of Shapiro–Wilk test (bold value means, that the data come from normal distributions) Locality p-value Locality p-value Locality p-value GAP 18 vs. CROWN 18* 0.6978 GAP 19 vs. CROWN 19* 0.1562 GAP 20 vs. CROWN 20** 0.2721 GAP 18 vs. STEM 18* 0.0001 GAP 19 vs. STEM 19** 0.0033 GAP 20 vs. STEM 20** 0.0022 CROWN 18 vs. STEM 18* 0.0000 CROWN 19 vs. STEM19** 0.0044 CROWN 20 vs. STEM 20** 0.0022 *Student´s paired test, ** Wilcoxon paired test (bold values define statistically significant differences p ≤ 0.05) whether a statistically significant difference was confirmed and its interception losses are also significantly affected by the between the correlation of interception loss and gross precipita- gross precipitation, but to a lesser extent. Although this space tion. Bold values represent a statistically significant difference. has no active surface above it to retain precipitation, it is mainly The Pearson’s correlation coefficient was most significant in exposed to the wind. The higher the wind speed, the more the the central crown zone near the stem, indicating a relatively direction of rainfall deviates from the vertical direction, while strong relationship between the variables, followed by the can- the surrounding trees can act as a rain shadow. The vegetation opy gap, indicating a moderately strong relationship between may lead to ‘precipitation shading’ of the site in certain direc- the variables as well. The least significant of the three was the tion, but if the wind speed exceeds a certain limit, when it is dripping zone at the crown periphery, indicating a relatively able to carry the captured precipitation in the crowns, these may weak relationship between the variables. The R-squared statis- exceed the gross precipitation values (20 June, 4 July 2019 and tic (coefficient of determination) indicated that the fitted model 3 August 2020 (Fig. 3)). The gross precipitation total in the explained 88.8% of the variability in interception loss in the dripping zone at the crown periphery has the smallest effect on central crown zone near the stem, 87.6% of the variability in the interception loss, because in this area the variability of the interception loss in the canopy gap and 1.2% of the variability interception loss is the highest and it is influenced by the effect in interception loss in the dripping zone at the crown periphery of occult precipitation. In the dripping zone at the crown pe- out of the gross precipitation. A statistically significant differ- riphery, such a correlation was not statistically confirmed. ence in correlation was confirmed in the canopy gap and in the Similar results at the same studied site during the growing central crown zone near the stem. It follows that in the central seasons of 2007–2011 were reported by Oreňák et al. (2013), crown zone near the stem, interception losses were most affect- where the Pearson’s correlation coefficient of interception loss ed by the gross precipitation, because this space in the stand was most significant in the central crown zone near the stem, intercepts the largest amount of precipitation. The canopy gap followed by the canopy gap and least important in the dripping 442 Effect of mature spruce forest on canopy interception in subalpine conditions during three growing seasons Fig. 4. Box-whisker plots (maximum-minimum; lower and upper quartiles; median; the crosses show the arithmetic mean, the squares show the outliers) of interception (%) for the growing seasons of 2018–2020. Fig. 5. Linear regression between canopy gap (GAP) interception Fig. 7. Linear regression between central crown zone near the stem loss (mm) and gross precipitation (2018–2020). The solid line (STEM) interception loss (mm) and gross precipitation (2018– represents the regression line; the dashed lines are the upper and 2020). The solid line represents the regression line; the dashed lower 95% prediction intervals of the regression. lines are the upper and lower 95% prediction intervals of the re- gression. et al., 2019; Kaiser et al., 2013). Additionally, the topographic structure mediates the redistribution of water and the spatial patterns of forest vegetation, giving rise to temporal complexity in the ecological processes associated with vegetation. CONCLUSION Understanding how trees interact with interception processes is important for the development of effective strategies and tools for sustainable resource management in the future. Large parts of the Tatra Mts. have already been hit by significant ecosystem disturbances, including spruce bark beetle outbreaks. Our study aimed to evaluate the influence of mountain spruce forest on the distribution of throughfall in the growing seasons of 2018–2020 and provided a unique opportunity to analyze rainfall interception in an unaffected forest. And although the study design was constrained by rough terrain and challenges Fig. 6. Linear regression between the dripping zone at the crown regarding periodical monitoring, the analysis of synoptic types periphery (CROWN) interception loss (mm) and gross precipita- points to the differences in meteorological conditions of occur- tion (2018–2020). The solid line represents the regression line; the rence of precipitation in the observed study plot. We recorded dashed lines are the upper and lower 95% prediction intervals of amounts of precipitation in the growing seasons in descending the regression. order as follows: 2020 > 2018 > 2019. Most of the precipitation totals in each period were recorded in cyclonic situations. Fur- zone at the crown periphery. Droughts, insects and fungi al- thermore, based on the results of our measurements we can ready contribute to the decline of spruce forests (Sierota et al., state that the distribution of precipitation differs within the 2019). Given that interception is partially a function of forest stand structure in the sub-canopy space. structure and physiological characteristics of host trees (Bladon 443 Martin Jančo, Pavel Mezei, Andrej Kvas, Michal Danko, Patrik Sleziak, Jozef Minďáš, Jaroslav Škvarenina Our research can be used to develop a more mechanistic un- streamflow in catchments affected by a forest disease derstanding of the feedbacks between hydrology and ecological epidemic. Science of the Total Environment, 691, 112–123. processes. The lowest amount of throughfall in each evaluated Brádka, J., Dřevikovský, A., Gregor., Z., Kolesár, J., 1961. period was recorded in the central crown zone near the stem, Weather over the territory of Bohemia and Moravia in typi- indicating that interception here was highest. The lowest values cal weather situations. Hydrometeorologický ústav, Praha, of interception were seen in the dripping zone at crown periph- 31 p. (In Czech.) ery, with the exception of during the growing season of 2019, Bruijnzeel, L.A., 2004. Hydrological cycle. In: Burley, J., when we recorded the lowest interception in the canopy gap. Evans, J., Youngquist, J. (Eds.): Encyclopedia of Forest The mosaic of land-cover change that has affected the rest of Sciences. Elsevier Academic Press, Oxford, pp. 340–350. the Tatra Mts. can alter ecosystem response and hydrology will Černohous, V., Švihla, V., Šach, F., 2018. Manifestation of be among the first affected ecosystem services. Interception of drought in spruce pole-stage stand in summer 2015. Zprávy individual localities differed in each growing season in the Lesnického Výzkumu, 63, 10–19. (In Czech.) cases of the canopy gap and the central crown near the stem, Chang, M., 2013. Forest Hydrology: An Introduction to Water the dripping zone at the crown periphery and the central crown and Forests (third edition). CRC Press, Boca Raton, 595 p. zone near the stem. Canopy gap and the central crown zone Chroust, L., 1987. Ecology of forest education. Výzkumný near the stem affected also the interception loss between the ústav lesního hospodářství a myslivosti, Opočno. 277 p. (In gross precipitation. This phenomenon owed to the presence of Czech.) occult precipitation, which compensated for interception losses Danáčová, M., Danko, M., Lajda, D., 2019. The influence of and enriched the stand with rainwater. The total interception of the degree-day factor determination on the snow water the stand reached 26.8% (2018), 30.3% (2019) and 28.3% equivalent simulation. Meteorologický časopis, 22, 11–20. (2020) of the gross precipitation total. In the future, we expect (In Slovak.) significant changes in the hydrological cycle in the Tatra Mts., Dohnal, M., Černý, T., Votrubová, J., Tesař, M., 2014. Rainfall mainly due to repeated wind storms, bark beetle outbreaks and interception and spatial variability of throughfall in spruce subsequent sanitary measurements. Our study provides a basis stand. Journal of Hydrology and Hydromechanics, 62, for future comparison and changes in affected forests with 277–284. baseline conditions described in the above-presented study. European Centre for Medium-Range Weather Forecasts, Copernicus Climate Change Service, 2020. Copernicus: Acknowledgements. This work was supported by the VEGA 2019 was the second warmest year and the last five years project nos. 1/0500/19 and 2/0065/19 awarded by the Ministry were the warmest on record (https://climate.copernicus.eu/ of Education, Science, Research and Sport of the Slovak Re- index.php/copernicus-2019-was-second-warmest-year-and- public and the Slovak Academy of Sciences; and the projects of last-five-years-were-warmest-record). the Slovak Research and Development Agency nos. 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Journal of Hydrology and Hydromechanics – de Gruyter
Published: Dec 1, 2021
Keywords: Precipitation; Interception; Synoptic types; Norway spruce ( Picea abies L. Karst.); Growing season
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