A Model of Southern Sikhote-Alin Liverwort Flora and a New Approach to Analyze the Altitudinal Distribution Patterns in the Zov Tigra National Park (South of the Russian Far East, Temperate Pacific Asia)

Abstract

The liverwort flora in Zov Tigra National Park in southern Sikhote-Alin (Primorye Territory, south of the Russian Far East), which has one of the richest regional floras, was studied to assess its taxonomic diversity, and analyzed using a new approach to determine altitudinal distribution patterns. This new approach is based on probabilistic models of the altitudinal distribution of individual taxa proposed for identifying altitudinal groups of species. This method can be used to analyze patterns of the distribution of species of various taxonomic groups in cases where a sufficiently representative dataset is available and may be especially relevant in regions where altitudinal zonation is not obvious or changes in the altitudinal fractions of the dominant vegetation are too continuous. The proposed method revealed three altitudinal groups that were more clearly differentiated than groups of taxa based on altitudinal vegetation belts. Based on the obtained results, the most important bioclimatic indices correlated with the altitudinal distribution of liverworts were identified: annual mean temperature (BIO1), annual precipitation (BIO12), isothermality (BIO3), and factors associated with the temperature and amount of precipitation during the warmest period of the year, including the maximum temperature of the warmest month (BIO5), the mean temperature of the wettest quarter (BIO8), the mean temperature of the warmest quarter (BIO10), precipitation during the wettest month (BIO13), precipitation during the wettest quarter (BIO16), and precipitation during the warmest quarter (BIO18). This study reports 130 species, 1 variety, and 1 subspecies. Pseudolophozia debiliformis and Scapania praetervisa are newly recorded for Sikhote-Alin and the Primorye Territory. Diplophyllum albicans and Cephaloziella rubella are newly reported for the Primorye Territory. The national park liverwort flora can be classified as boreal–temperate circumpolar–East Asian. Given the high taxonomic diversity and coverage of all altitudinal zones represented in the region, the liverwort flora in Zov Tigra National Park can serve as a model for all liverwort floras in southern Sikhote-Alin.

1. Introduction

The Primorye Territory, located at the southern tip of the Russian Far East, occupies a special position in the phytogeographical system of Pacific Asia due to its proximity to the border between the East Asian and Circumboreal floristic regions of the Holarctic [1]. Here, there is an interpenetration of the ancient East Asian complex of plant species and the circumboreal complex (at the generic level, almost identical to even the floras as far apart as Northern Europe or Canada). This mixing of flora leads to an increase in regional diversity and the formation of specific transitional complexes co-existing for a long time [2]. The mixing of floral elements is more pronounced due to the well-developed altitudinal zonation in the southern part of the Sikhote-Alin.

The liverwort flora of the southern part of the Primorye Territory may be conditionally treated as rather well studied among regions of the Russian Federation. S.K. Gambaryan, the first professional hepaticologist who worked in the Russian Far East, wrote a PhD thesis on liverworts in this area (1989) that later became the basis of the monograph “Hornworts and Liverworts of the Southern Primorye” [3]. The book includes data on the distribution of 132 liverwort species within Primorye south at 45° N.

However, the last 15 years were marked by numerous studies of Far Eastern liverworts, particularly in the southern part of the Primorye Territory. These studies showed that the previous estimations of the taxonomic diversity in the land should be corrected. The extensive use of molecular phylogenetic methods in taxonomic studies has resulted in the description of new taxa [4,5]. The study of the Far Eastern liverwort flora has also been influenced by the great development of the digital photography of oil bodies’ structure [6] and taxonomic changes in some genera [7,8,9,10,11].

One of the particularly important nature areas that need to be considered to better understand the natural characteristics of the liverwort floras in the East Asian–circumboreal transition zone is Zov Tigra National Park (Figure 1), characterized by the high landscape diversity. This protected area was the focus of our research, and the main goal was to provide a comprehensive description of the liverwort floristic phenomenon of one of the most taxonomically rich areas of the southern tip in the Russian Far East. Taking into account the potentially high diversity of species and communities, the liverwort flora of Zov Tigra National Park can be considered a model object for the liverwort flora of southern Sikhote-Alin as a whole.

This liverwort flora study was conducted in the following ways: (1) understanding the total taxonomic diversity in the area studied; (2) revealing the distribution patterns of taxa along the altitudinal gradient in the park; and (3) evaluating the bioclimatic parameters that correlate with the selected altitudinal groups (if any).

The tasks are actualized in the following ways. Although a sufficient amount of data on the distribution of liverworts in Primorye and Sikhote-Alin as a whole (mostly published, incomplete lists of flora in nature reserves, some phytogeographically interesting areas, and new findings) have been accumulated [12,13], no attempts to analyze the regularities of the altitudinal distribution of liverworts in Sikhote-Alin, aside from the somewhat speculative account of [14], have been made.

The nature conservation history of the area, which now belongs to the Zov Tigra National Park, is long and controversial. Since the establishing, the protected area considerably changed the size and even was not existed in some decades. The present-day protected area is drastically different to the initially protected area almost 90 years ago. This historical background is described in Supplementary Material S1 [15,16,17,18].

The first botanical studies performed in the territory of the park were initiated approximately 90 years ago and primarily concerned the flora of vascular plants and vegetation [19,20,21,22,23], cited after [24]; [25,26,27,28,29]. Presumably, the geobotanist P.P. Zhudova gathered the first scattered collection of liverworts in the second half of the 1940s from the present-day park area and nearby areas. Eighteen liverwort taxa were recorded in her work, and all were identified by A.L. Abramova [28]. Only one of them, Barbilophozia barbata (Lophozia barbata (Schmidel ex Schreb.) Dumort. in [28]), with some confidence can be referred to the current park territory. It was collected from the slopes on the alpine belt, whereas the author shows the existence of an alpine belt only for the Oblachnaya, Snezhnaya, and Sestra Mountains [28] (p. 17); all of these areas are within the present-day park territory. The report of Bazzania trilobata for Snezhnaya Mt. [30] by Zerov does not consider the location of the park. Zerov identified the species from the collection of liverworts made by B.P. Kolesnikov in 1935 during an expedition to the middle part of the Sikhote-Alin Mts. [31]. Furthermore, L.V. Bardunov, V.Ya. Cherdantseva, A.G. Minakov, and N.M. Denisov collected bryophytes from Snezhnaya Mt. in 1977. In late July 1980, S.K. Gambaryan collected liverworts from the Milagradovskie Waterfalls, followed by Oblachnaya Mt in September in the same year. The results of her own collection from Oblachnaya Mt. and the collection that was performed by the abovementioned colleagues in 1977 were published in 1984 [32]. Later, all available information on the liverwort collections from the park territory became a chapter in the monograph on hornworts and liverworts of southern Primorye [3]. Therefore, before our research, only 49 species of liverworts were recorded in Zov Tigra National Park [3,28,32].

2. Materials and Methods

2.1. Study Area

Zov Tigra National Park is located in the southern part of the Sikhote-Alin Mts. The park includes a dividing ridge with spurs and the highest mountain peaks of South Primorye, including Oblachnaya Mt. (1854 m a.s.l.) (Figure 2A–E), Snezhnaya Mt. (1684 m a.s.l.) (Figure 2F), and Sestra Mt. (1671 m a.s.l.) (Figure 2G,H), as well as the upper course of the Ussuri River, the upper part of the Milogradovka River basin, and the northern part of the Kievka River basin [24,33]. The park’s territory belongs to the Chuguevsky, Olginsky, and Lazovsky administrative and municipal districts of the Primorye Territory and stretches from north to south for 33 km and from east to west for 38 km. Its total area is 835 km² [33].

Zov Tigra National Park has a low- and mid-mountain relief with altitudinal ranges from 155 to 1854 m a.s.l. and is composed of Cretaceous-aged (~130–80 Ma ago) rocks, which are found in the vast lands of the park [34]. Below, we provide a brief geological description of the collection sites. The mountain tops of Oblachnaya and Snezhnaya consist of Upper Cretaceous porphyrites and tuffs. The tops are mainly covered with rock fields and screes, with a small amount of rocky outcrops and no prominent rocks. The southern and southeastern slopes of Oblachnaya (below 1200 m a.s.l.) and the southwestern slope of Snezhnaya (below 1400 m a.s.l.) are mostly composed of Early Triassic rocks (sandstones, siltstones, and conglomerates) pierced by Upper Cretaceous porphyrite–granite and granite intrusions. The Sikhote-Alin main ridge line between the Kamen’-Brat and Sestra Mountains, as well as the Vtoroi Svetlyi stream valley formed by Upper Cretaceous granitic intrusions, has created many rocky outliers in the watershed area of the range and rocky outcrops and rocks in the stream valley. The top of Mt. Sestra is covered by rock fields without distinct cliffs and walls. The west and southwest slopes of its top are composed of Lower Cretaceous siltstones, sandstones, gravelites, and conglomerates. Most of the Ussuri River valley is covered by modern Quaternary deposits [35].

According to G.P. Skrylnik, this park has a continental climate with monsoon features [36]. To characterize the climate features of the study area, we used climatic parameters for the Yasnoe Settlement [37] and Listvennaya Village [38]. Yasnoe is approximately 13 km northwest of the western border of the national park, at 453 m a.s.l. The mean annual temperature is 4.5 °C. The warmest month is August, with an average temperature of 20.5 °C, and the coldest month is January, with an average temperature of −14.4 °C. The mean annual amount of precipitation is 709 mm per year, with an uneven distribution across the year. Specifically, more precipitation occurs in the warm season (maximum in July and August) when the rainfall exceeds 133 mm per month, and less precipitation occurs in the cold season, with distinct minima occurring in January (13 mm) and February (17 mm). Listvennaya is approximately 15 km to the east from the southeastern border of the National Park, at 75 m a.s.l., and has nearly the same mean annual temperature (4.6 °C) as Yasnoe. The warmest month is August, with an average temperature of 19.6 °C. The coldest month (January) is slightly warmer than that in Yasnoe and has an average temperature of −11.9 °C. The mean annual amount of precipitation is 832 mm per year, with similarly greater amounts in the warm season and distinct maxima in July (139 mm) and August (147 mm), and the same distinct minimum in the cold season, with the driest months being January (17 mm) and February (20 mm).

The presented data show the climate of the lowlands. However, this information does not allow us to determine the climate in the mountains, where the mean temperatures should be lower than those in the valleys. To trace the climate change along the altitudinal gradient, we obtained data for 19 bioclimates (Worldclim, 2020–2022) [39,40] at 1 km intervals along an imaginary straight line between the summits of Oblachnaya Mt. and Sestra Mt., thus crossing the lower altitudinal points of the park in the Ussuri River valley (Figure 3, Supplementary Material S2) and the two highest local altitudinal points in the national park.

The annual mean temperature (BIO1) decreases noticeably to the upper altitudinal levels near the mountain tops (Figure 4) and becomes negative above 1000 m a.s.l. In addition, the annual precipitation (BIO12) increased in the same direction, approaching a value of 1000 mm per year near the mountain tops. Considering the direct impact of the decreasing temperature on the potential water evaporation ability of the substrate, this feature causes the substrates to moisten in addition to increasing the total precipitation in absolute values from 817 mm in the valley to 999 mm at the top. In addition, the table in Supplementary Material S2 shows that the warmest quarter (BIO18) is also the wettest quarter (BIO16), which is a common feature for all Sikhote-Alin mountain peaks.

The variations in the elevation and orographic characteristics determine the evident altitudinal zonality in the area [24,41]. Forests occupy the main area of the national park (96%). A large part of the forestless area consists of rock fields and screes. Non-forest vegetation, such as shrubs, dwarf shrub grass, and grass communities, is dominant in subalpine and alpine belts (1600–1800 m a.s.l.) [41]. The altitudinal boundaries of vegetation belts vary widely depending on the relief, substrate, and slope exposure. The main vegetation belts listed from lower to upper elevations are as follows: (1) broadleaved deciduous and Pinus koraiensis broadleaved deciduous forest belts (up to 500–900 m a.s.l.) formed by Pinus koraiensis Siebold et Zucc., Quercus mongolica Fisch. Ex Ledeb., Tilia amurensis Rupr., Acer mono Maxim., Betula costata Trautv., B. davurica Pall., and B. platyphylla Sukacz., with an admixture of Juglans mandshurica Maxim., Ulmus japonica (Rehder) Sarg., U. laciniata (Trautv.) Mayr, Phellodendron amurense Rupr., and Kalopanax septemlobus (Thunb.) Koidz. These are East Asian temperate taxa and represent the most common components of the so-called “Ussuri taiga”, reflecting the geographical position of the park in southern Sikhote-Alin. (2) The Abies-Picea forest belt (in the ranges of 600–900 and 1600–1650 m a.s.l.) is dominated by Picea ajanensis (Lindl. et Gord.) Fisch. ex Carr. and Abies nephrolepis (Trautv.) Maxim. (3) Stone birch forests (1000–1600 m a.s.l.) are composed of Betula lanata (Regel) V. Vassil., with Rosa acicularis Lindl., Weigela middendorffiana (Carrière) K. Koch, and Sorbus sambucifolia Cham. et Schlecht. dominating in the understory. (4) The Pinus pumila (Pall.) Regel crooked forest belt and alpine belt (higher than the range of 1600–1700 m a.s.l.). The alpine belt is dominated by arctic–alpine dwarf shrubs, including Vaccinium uliginosum subsp. alpinum (Bigel.) Hult., Arctous alpina (L.) Niedenzu, Ledum decumbens (Ait.) Lodd. ex Steud., Cassiope ericoides (Pall.) D. Don, and Diapensia obovata (Fr. Schmidt) Nakai. [24,41]. An alpine belt with tundra vegetation exists only on the highest peaks of the mountains (Oblachnaya Mt., Snezhnaya Mt., and Sestra Mt.) [26,28] and consists of lichen and dwarf shrub tundra and their variations [28]. Additionally, dwarf shrub–forb communities are quite abundant in this area (Figure 2A) [26]. The vegetation communities of adjacent vegetation belts deeply interpenetrate one another and form transitional types in contact zones, including Picea-Betula lanata forests and other vegetation variants. Of note, so-called alpine glades are present in the areas near the top of Mt. Oblachnaya. Such glades are usually inhabited by Bupleurum euphorbioides Nakai, Anemonastrum brevipedunculatum (Juz.) Holub, Hedysarum branthii Trautv. et C. A. Mey., Carex tenuiformis Lévl. et Vaniot, and Carex rigidioides (Gorodk.) V. Krecz. Rock fields and screes differ in species composition depending on the vegetation belt. In any case, the most common vegetation species are Artemisia lagocephala (Bess.) DC., Bergenia pacifica Kom., and Rhododendron sichotense Pojark. [24]. In addition, there are communities dominated by Larix olgensis A. Henry that do not form distinct vegetation belts, and we did not visit them for this study. Flood-plain areas in stream and river valleys are occupied mostly by forests composed of Chosenia arbutifolia (Pall.) A. Skvorts., Populus suaveolens Fisch., and several species of Salix [24,28].

2.2. Specimens

The present work is based on the material collected by the first author in July 2017 (14 days); V.A. Bakalin in 2007 (4 days), 2012 (2 days), and 2014 (1 day); and a few specimens collected by the authors during a 1-day botanical trip to Snezhnaya Mt. in late September 2017. The total number of collected specimens was 691. Specimens were collected along routes covering various parts of the park (Figure 1). For all collection localities, the geographic coordinates, elevation above sea level, vegetation type, light, substrate, and moisture of the liverwort mats were recorded.

All collected materials were stored in the herbarium at the Botanical Garden Institute FEB RAS (VBGI). The list of collection localities united by clusters as indicated by the collector’s name and year of collection is presented below. The collection locations are shown in Figure 1.

List of Collection Localities

A. Lukyanov Log stream valley. 1. Near interfluve of Pasechnaya River, rocks along stream in mixed forest, 43°28′35.3″ N 134°02′37″ E, 513 m a.s.l. 2. Left side of the valley in the stream’s middle course, mixed forest on the ridge, 43°29′40.3″ N 134°04′18.8″ E, 747 m a.s.l. (Coll. Klimova, 2017).

B. Interfluvial watershed between tributaries of Lukyanov Log stream. 3. Betula forest with Pinus pumila clumps, 43°30′16.3″ N 134°05′03.8″ E, 1153 m a.s.l. 4. Picea–Betula forest with rocky blocks, 43°30′31.2″ N 134°05′16.4″ E, 1248 m a.s.l. 5. Rocky outliers surrounded by Betula crooked forest, 43°30′39.7″ N 134°05′15.4″ E, 1311 m a.s.l. 6. Betula crooked forest, 43°30′42.6″ N 134°05′22.4″), 1364 m a.s.l. (Coll. Klimova, 2017).

C. Kamen′ Brat Mt. area. 7. Picea–Abies–Betula forest on a ridge, 43°30′46.8″ N 134°05′29.6″ E, 1412 m a.s.l. 8. Rocks in crooked Betula–Picea forest on a ridge, 43°30′56.8″ N 134°05′22.5″ E, 1407 m a.s.l. 9. Betula–Picea forest on a ridge, 43°31′06.5″ N 134°05′06.5″ E, 1350 m a.s.l. (Coll. Klimova, 2017).

D. Ridge between Kamen′ Brat Mt. and Sestra Mt. 10. Scattered Betula forest with rocks and rocky outcrops and tundra-like vegetation spots (Cassiope) on a ridge, 43°31′08.9″ N 134°04′19.1″ E, 1406 m a.s.l. (Coll. Klimova, 2017).

E. Sestra Mt. area. 11. Saddle at the bottom of SE-facing slope of the mountain, coniferous forest at the top of NE-facing slope, 43°31′28.7″ N 134°03′46.4″ E, 1460 m a.s.l. 12. Saddle at the bottom of SE-facing slope of the mountain, little rock field on a ridge with Pinus pumila thickets, 43°31′24.9″ N 134°03′47.3″ E, 1483 m a.s.l. 13. The top of the mountain, rock fields and spots of dwarf shrub–herb tundra-like communities with Pinus pumila dwarf clumps, 43°31′51.4″ N 134°03′35.1″ E, 1657 m a.s.l. (Coll. Klimova, 2017).

F. Vtoroy Svetlyi stream valley. 14. NE-facing slope to stream head, coniferous forest on big blocks with an admixture of deciduous trees, 43°31′29.6″ N 134°03′51.3″ E, 1404 m a.s.l. 15. NE-facing slope, the head of the stream, coniferous forest on big blocks with an admixture of deciduous trees, 43°31′37.1″ N 134°04′13.1″ E, 1199 m a.s.l. 16. Mixed forest in the upper course of the stream, 43°31′41.8″ N 134°04′37″ E, 1076 m a.s.l. 17. The upper course, rocks along the stream in a mixed forest, 43°31′43.7″ N 134°04′48.1″ E, 1023 m a.s.l. 18. The upper course, rocks along the stream in a mixed forest, 43°31′48.2″ N 134°05′03.7″ E, 980 m a.s.l. 19. The upper course, rocks along the stream in a mixed forest, 43°31′50.8″ N 134°05′08.3″ E, 975 m a.s.l. 20. The middle course, rocks along the stream in a mixed forest, 43°32′44″ N 134°06′51.7″ E, 713 m a.s.l. 21. The middle course, rocks along the stream in a mixed forest, 43°32′30.7″ N 134°06′45.1″ E, 738 m a.s.l. 22. The middle course, area near a small waterfall in a mixed forest, 43°32′29.7″ N 134°06′44.2″ E, 741 m a.s.l. 23. The middle course, area near small a waterfall in a mixed forest, 43°32′27.5″ N 134°06′43.7″ E, 752 m a.s.l. 24. The lower course, sluggishly flowing water in a ditch in a mixed forest with no vegetation cover, 43°33′44.5″ N 134°07′23.9″ E, 604 m a.s.l. (Coll. Klimova, 2017).

G. Ussuri River valley. 25. Ussuri River flood-plain, flood-plain forest, 43°35′30.5″ N 134°07′34.3″ E, 536 m a.s.l. 26. Pobedinskaya Polyana, Ussuri Station, 43°36′43.3″ N 134°07′01.7″ E, 539 m a.s.l. (Coll. Klimova, 2017). 27. Ussuri River valley, mixed (Picea, Abies, broadleaved deciduous trees) forest on rocky slope to the valley, 43°36′12.60″ 134°12′10.40″, 600 m a.s.l. 28. Upper course of Ussuri River, Picea–Abies forest with moss cover on steep slope, 43°38′05.4″ N 134°20′53.8″ E, 721 m a.s.l. (Coll. Bakalin, 2007). 29. Upper course of Ussuri River, N-facing rocks in a mixed forest, 43°37′42.2″ N 134°20′12.5″ E, 694 m a.s.l. (Coll. Klimova and Bakalin, 2017).

H. Oblachnaya Mt. area. 30. Southern spur of the mountain, coniferous forest with an admixture of Betula and Acer on an SW-facing slope, 43°43′00.4″ N 134°11′51.8″ E, 1274 m a.s.l. 31. Southern spur, saddle in front of the main top area, tundra-like herb communities with Pinus pumila thickets and small rock fields at the bottom of a hill, 43°41′04.1″ N 134°12′01.5″ E, 1706 m a.s.l. 32. Southern spur, saddle in front of the main top area, N-facing slope of a small hill mostly covered with rock fields intermingled with spots of dwarf-shrub–lichen tundra and dwarf Pinus pumila clumps, 43°41′04.1″ N 134°12′01.5″ E, 1728 m a.s.l. 33. Southern spur, saddle in front of the main top area, Pinus pumila thickets with big rocky blocks, 43°41′24.2″ N 134°11′53.3″ E, 1707 m a.s.l. 34. Area near the top of the mountain, N-facing rocks, Pinus pumila thickets with big rocky blocks, rocks in Alnus fruticosa, young trees of Betula lanata and Pinus pumila thickets, 43°41′43.7″ N 134°12′02.9″ E, 1839 m a.s.l. 35. Area near the top, rocks and rock fields with dwarf-shrub–lichen tundra spots, thickets of Pinus pumila, Alnus fruticosa, young trees of Betula lanata on an N-facing slope, 43°41′44.5″ N 134°12′08.8″ E, 1798 m a.s.l. 36. Northern spur of the mountain, rock fields with dwarf-shrub–lichen tundra spots and Pinus pumila thickets on an N-facing slope, swampy Pinus pumila thickets along rocks, 43°42′02.8″ N 134°11′49.9″ E, 1765 m a.s.l. 37. NE-facing slope, water-flow depression in thickets of Alnus fruticosa with young trees of Betula lanata with dripping water, 43°41′50.2″ N 134°11′57.6″ E, 1768–1724 m a.s.l. 38. NE-facing slope, Betula lanata forest, 43°41′55.1″ N 134°12′02″ E, 1649 m a.s.l. 39. NE-facing slope, Picea–Betula forest, 43°41′57″ N 134°12′06.7″ E, 1570 m a.s.l. 40. NE-facing slope, coniferous forest, 43°41′58.6″ N 134°12′07.3″ E, 1543 m a.s.l. 41. NE-facing slope, coniferous forest with an admixture of Betula and Acer, 43°42′05.9″ N 134°12′12.4″ E, 1430 m a.s.l. 42. Southern spur, coniferous forest with moss cover (mostly Hylocomium splendens) on an S-facing slope, 43°42′05.9″ N 134°12′12.4″ E, 1500 m a.s.l. 43. Gniloy stream valley, coniferous forest with an admixture of Betula and Acer on an NE-facing slope, 43°38′38.2″ N 134°11′58.7″ E, 950 m a.s.l. (Coll. Klimova, 2017).

I. Snezhnaya Mt. area. 44. Ussuri River upper course of 6 km to the top of the mountain, dominantly Picea–Abies forest along the river, 43°40′58.2″ N 134°23′43.6″ E, 861 m a.s.l. 45. Southern spur of the mountain, gravelly barrens, 43°43′58.0″ N 134°25′55.5″ E, 1500 m a.s.l. 46. Northern spur, lichen–dwarf shrub tundra with gravelly barrens fields, 43°44′19.7″ N 134°25′32.9″ E, 1500 m a.s.l. 47. Northern spur, valley with a temporary stream in a Betula–Alnus mountain forest, 43°44′33.65″ N 134°25′27.69″ E, 1200 m a.s.l. 48. Northern spur, wet Betula–Picea forest with Pinus pumila underbrush and moss cover near the stream, 43°44′49.74″ N 134°25′15.38″ E, 1000 m a.s.l. 49. Southeastern spur, Betula forest with an admixture of Acer, Picea, underbrush of Rhododendron mucronulatum and forb cover on an E-facing slope, 43°42′32.2″ N 134°26′50.3″ E, 1100 m a.s.l. 50. Southeastern spur at the head of the Ostantsovyi stream, broadleaved deciduous Picea forest with forb cover, 43°43′33.4″ N 134°27′23.3″ E, 780 m a.s.l. 51. Southern spur, slope toward the Istokovyi stream, Picea forest with an admixture of Betula and isolated broadleaved deciduous trees with no vegetation cover, 43°42′32.2″ N 134°26′50.3″ E, 1000 m a.s.l. (Coll. Bakalin, 2007). 52. Area near the top of the mountain, gravelly barren field, 43°45′58″ N 134°25′56″ E, 1600 m a.s.l. leg. 53. Ussuri River upper course, multidominant (mostly coniferous) forest with moss cover, 43°39′45″ N 134°24′32″ E, 820 m a.s.l. (Coll. Bakalin, 2014). 54. One of the heads of the Ussuri River, scattered vegetation on an S-facing slope, 43°43′59.4″ N 134°25′52.8″ E, 1438 m a.s.l. 55. Southeast spur of the mountain, rock fields with rocky outcrops and spots of Pinus pumila and tundra vegetation, 43°43′59.4″ N 134°25′52.8″ E, 1438 m a.s.l. 56. S-facing slope, Picea–Betula forest, 43°40′14.2″ N 134°25′22.0″ E, 1031 m a.s.l. 57. Bottom of the mountain, Ussuri River basin, coniferous forest with broadleaved deciduous trees, 43°39′44.8″ N 134°24′33.1″ E, 809 m a.s.l. (Coll. Klimova and Bakalin, 2017).

J. Pad′ Solnechnaya valley. 58. Chyornaya River valley, broadleaved deciduous forest with shrub–grass cover, 43°23′45″ N 134°11′59″ E, 356 m a.s.l. 59. The head of Chyornaya River, broadleaved deciduous Picea–Abies forest on a small ridge, 43°26′32″ N 134°13′20″ E, 632 m a.s.l. 60. Mountain range near the pass Solnechnaya Pad′ valley—Milogradovka River, broadleaved deciduous Picea–Abies forest, 43°26′32″ N 134°13′20″ E, 800 m a.s.l. (Coll. Bakalin, 2012).

2.3. Data Analysis

A comparison of the National Park liverwort flora with other protected areas in southern Sikhote-Alin was made using the following published data [42,43,44,45,46,47].

To reveal the phytogeographic relationships, we performed a geographical analysis using a classification scheme of floristic elements and area types provided by Bakalin [48] with some additions and updates. The ratios of floristic elements and area types were analyzed for both the entire set of revealed taxa and the altitudinal groups. Two approaches were used for the division into groups.

(1) Division by sets of taxa for three altitudinal vegetation belts, where the largest number of specimens was collected. These include (a) a lower altitudinal belt (up to 500–900 m a.s.l.), where broadleaved deciduous and Pinus koraiensis–broadleaved deciduous (mixed in a broad sense) forests dominate, (b) a middle altitudinal belt (in the ranges of 500–900 and 1600–1650 m a.s.l.) dominated by conifers (Picea ajanensis and Abies nephrolepis), and (c) the uppermost elevations dominated by Pinus pumila thickets, tundra, and tundroid communities with rock fields (above 1600–1650 m a.s.l.). A species belonging to a certain type of vegetation was the main criterion for inclusion in a particular group. However, given that taxa are often not confined to only one vegetation type, each species could be included in altitudinal groups 1–3 times.

(2) Using a mathematical analysis, the entire set of taxa was divided into groups based on the altitudinal distribution patterns of each species, which was expressed as the elevation above sea level. In addition, we took into account the amount of data and methods for obtaining them.

Furthermore, in the Study Area subsection, we presented sufficiently detailed climatic characteristics of the study area based on modern climate models (Supplementary Material S2, Figure 4) (Worldclim, 2020–2022) [39,40]. However, even the most detailed description of the climate allows us only in general terms to judge which climatic factors are important for the distribution of species. To address this issue, we attempted to mathematically process the available data. The proposed analysis is unusual, and we describe it below in detail.

The mathematical analysis consisted of two main steps. The purpose of the first step was to divide the existing set of taxa into altitudinal groups based on probabilistic models of altitudinal distribution. In the second step, the bioclimatic indices were obtained for each collection locality, and their change trends were analyzed to determine which climatic factors correlated with the altitudinal distribution of the species.

2.3.1. Source Data for Altitudinal Belt Analysis

To analyze the altitudinal distribution of taxa, a table (Supplementary Material S3) was compiled in which the location of each taxon is indicated for all 60 collection localities based on the terms “found/not found” (corresponding to the list of collection localities presented above). All the localities are ranked in descending order of elevation from 1839 to 356 m a.s.l. To describe the statistical model, all the collection localities are designated as H. Given that the elevations of all the collection localities are unique, we simply denote them by elevation in meters above sea level as follows:

H = (356,513,536, …, 1839),

(1)

From the entire list of taxa (132), 124 taxa had an exact reference to 60 collection localities, whereas the remaining 8 taxa were not included in the calculation. Let us designate them as the set T. Then, the source data can be represented as a function, f, defined for these sets:

$$\begin{gathered} f\left(t,h\right)=\{\begin{array}{l}1 \left(true\right), if species t is found at height h \\ 0 \left(false\right), if species t is notfound at height h,\end{array} \\ t\in T, h\in H \end{gathered}$$

(2)

The values of the function, $f\left(T,H\right)$, are shown in the table in Supplementary Material S3.

Then, the localities where each particular species were found can be visualized using the graph, $f\left(t,H\right)$, where t is a particular species. For example, Figure 5 shows the graph, $f\left(t,H\right)$, for $t=“Anastrophyllum michauxii \left(F.Weber\right) H.Buch”$. Thus, for the entire set of collection localities, H, the localities where the species was found and not found are shown.

2.3.2. Creation of a Statistical Model and the Maximum Likelihood Estimation Method

To determine a statistical model for these data, we assumed that the taxa distribution depending on the elevation of the landscape elements exhibited a normal distribution. This assumption is based on the fact that a number of independent factors, such as climate, soil conditions, competition with other species, and resource availability, can influence the spatial distribution of taxa. Many of these changes seem to be gradual. According to the central limit theorem (CLT), the distribution of the results of such factors tends to be normal. This assumption is commonly used for the analysis of similar ecological processes [49,50,51].

Based on this assumption, the parameters of the statistical model are the mean (μ) and standard deviation (σ) of the normal distribution. These parameters are used for further analyses as key characteristics of the altitudinal confinement of taxa and the extent of their altitudinal diapason.

We use the maximum likelihood estimation (MLE) method to estimate the parameters μ and σ by maximizing the likelihood function. The likelihood function L(μ, σ) is defined as the product of the probability densities of the observations as follows:

$$L\left(\mu ,\sigma \right)=\prod \left[PDF{\left(H;\mu ,\sigma \right)}^{f\left(T,h\right)}\ast {\left(1-PDF\left(H;\mu ,\sigma \right)\right)}^{1-f\left(T,h\right)}\right]$$

(3)

Here, the probability density function (PDF) describes the probability distribution of observed taxa at various altitudes within set H, thereby quantifying the likelihood of taxon occurrence across different altitudinal levels.

Regarding the limits for parameter variation, we define the following values:

μ—from 0 to 3000,
σ—from 150 to 1500

(4)

The actual elevations in the studied area, as noted above, range from 356 to 1839 m a.s.l. However, the potential altitudinal ranges for most conditionally “southern” and ”northern” elements in the flora are not realized. The choice of the potential range for analysis is based on the assumption of the potential distribution capabilities in the studied region of “northern” taxa, namely, what it could be if the extreme elevations in the studied area reached 3000 m. This estimation is partially based on the distribution of taxa on Changbai Mt. (located slightly more than 500 km southwest of the studied area and reaching an elevation of 2744 m a.s.l.) [52,53].

The lower limit is due to the minimum scatter of elevation values for taxa occurrence groups, whereas the upper limit is taken as the size of the entire analyzed area. It should be noted that increasing these limits does not affect the nature of the results, and the results are defined in these specific values mainly to increase the accuracy of the MLE algorithm.

To estimate the parameters, we use the maximum likelihood method. For this purpose, a program was written in Python 3.10 using the scipy.optimize.minimize function from the SciPy library version 1.10.1 (L-BFGS-B optimization method).

This approach is often used in similar cases, and it effectively describes the distribution of most taxa [54,55,56].

Using the program, estimates of the parameters μ and σ were obtained for the likelihood function, L. Graphs of the normal distribution density can be plotted based on these estimates. For example, a graph for Anastrophyllum michauxii is shown in Figure 6.

When analyzing the graphs for all the taxa (Supplementary Material S4), it can be seen that, for most taxa, the results correspond to the data. Nevertheless, in some cases, the method does not yield correct estimates. Three cases of species distribution are considered when the elevations of the locations are near the extreme limits of the studied altitudinal range (Figure 7, Figure 8 and Figure 9).

In all the listed cases (Figure 7, Figure 8 and Figure 9), it is evident that the species is found at the edge of the analyzed range. In this case, the identified distribution center always lies within this range, which seems implausible. If the species is found at most localities at the edge of the range and it occurs more often at the border, it can be assumed that the distribution center of the species is probably outside the range.

At the edge of the range, the relative density of elevations of collection localities is lower, so finding a species here is more significant than finding a species in the middle of the range, where the relative density of collection localities is high and the probability that some species will be found in one of them is statistically greater. Thus, taking into account these features, the statistical model should be modified.

2.3.3. Statistical Model Taking into Account Collection Localities at the Edge of the Range

For convenience, we named the first method used for the analysis of the conventional maximum likelihood estimation or the “classical MLE”. Based on this, we developed a method (“range–density MLE”) that takes into account the differences in the density of collection localities within the analyzed range. For this purpose, we first defined the taxon occurrence density function; for convenience, we called this the range–density function.

We assume that the distribution of taxa at an elevation within a sufficiently narrow elevation range, d, may be estimated as uniform. This follows from the assumption that the distribution of a species at an elevation is normal. In addition, with the selection of a sufficiently small d, we can consider the distribution density to be constant.

We need to define for the set of all collection localities, H, the subset $H_x^{\prime }$ of localities that are within a radius, d, from the elevation, x:

$$H_x^{\prime }=\left\{h\in H: \left|h-x\right| \le d\right\}$$

(5)

Within the set, $H_x^{\prime }$, the ratio of the number of localities where the taxon was found to the total number of localities can be calculated. The function is defined as follows:

$$g\left(x\right)={\displaystyle \frac{\sum H_x^{\prime }}{\left|H_x^{\prime }\right|}}$$

(6)

$$x\in \left[\min H,\max H\right]$$

(7)

This operation is essentially the application of a rectangular window function, which allows the determination of localities that have an elevation different from x by no more than d for any x.

For subsequent calculations, it is necessary to select a value for the radius, d, which determines the width of the window function. If this value is too small, i.e., less than the elevation differences between species collection points, the function g(x) fragments into several distinct peaks, and approximating a normal distribution curve may yield irrelevant results. Conversely, if the value of d is too large, the function g(x) becomes overly smoothed, potentially obscuring significant details in the distribution analysis.

To establish acceptable limits, we calculated the elevation interval between the findings for each species. The distribution of these intervals is illustrated in a histogram (Figure 10).

Therefore, more than 33% of the species (42 out of 124) has an average elevation interval between findings of less than 50 m; 19% of species has an average elevation interval between findings from 50 to 100 m, etc. A significant decline occurs at approximately 250 m. Beyond this point, the number of species per 50 m interval did not exceed 3%. In total, all other intervals accounted for less than 9% of the species. Thus, more than 90% of the species had average elevation intervals of no more than 250 m.

A radius of approximately 250 m equates to a window width of approximately 500 m, which is approximately 1/3 of the total analyzed elevation range (356–1839 m a.s.l.). This is a convenient estimate for further calculations; therefore, we accept this value as the actual estimate for the radius, d:

$$d={\displaystyle \frac{\max H-\min H}{6}}=247$$

(8)

Although the approach to determining the elevation interval for research purposes described above is very different from the approaches used in other works [57,58,59,60], the final results are generally very similar. Thus, in our case, the average elevation interval width is 247 m; however, in the cited publications, it is usually 200 m. In addition, it is obvious that the “even” number in meters was used largely for reasons of convenience and is not justified in the methodological part of the cited papers.

Based on these assumptions, we can plot the graph of the function, g(x). For clarity, in the graphs of g(x) here and below, the function is averaged with a step equal to the scale division value of the abscissa. For example, consider Aneura pinguis (L.) Dumort. (Figure 11).

On the graph (Figure 11), there is a noticeable point (emphasized by a black circle) that demonstrates the differences between these approaches. Although only one nearby mark of locality elevation was found for the species at an elevation of approximately 530 m, other findings were more pronounced. This locality has more weight because there were very few localities from where specimens were collected (compared to other parts of the analyzed range) in the vicinity of this elevation (530 m a.s.l.). Thus, finding the species at this locality is more significant and has greater weight compared to other locations.

The classical MLE and range–density function are compared using the example of Gymnomitrion parvitextum (previously shown in Figure 9) (Figure 12).

It can be seen that the function, g(x), better describes the observations. Specifically, given that this species was found in most of the boundary localities, it is likely that its maximum density lies outside of the analyzed range, as demonstrated by the shape of g(x). The orange graph (classical MLE) exhibits a maximum at approximately 1730 m a.s.l. and a very narrow altitudinal confinement, which is unlikely. The wide distribution of Gymnomitrion parvitextum at considerable elevations northward of the studied flora [61] indirectly confirms the accuracy of the range–density function approach.

In addition, for the vast majority of distribution examples, where the maximum density of occurrences is inside the analyzed elevation range, the function, g(x), describes the data in a manner that is visually similar to the classical MLE result. An example of such a distribution is provided in Figure 13.

Thus, the results demonstrate the range–density function can be used to statistically model the data in this study. Now, it is necessary to apply the maximum likelihood estimation method to this function to determine the statistical distribution parameters.

2.3.4. Range–Density MLE

By definition, g(x) describes the ratio of the number of localities where the species was found to the total number of collection localities for a given elevation range. In this study, g(x) is the relative frequency, which is an approximate estimate of the probability of finding a given taxon within a radius, d, from elevation x.

This allows us to define the likelihood function as follows:

$$L\left(\mu , \sigma \right)=\sum \left[ {\left(g\left(x\right)-PDF\left(x; \mu , \sigma \right)\right)}^2\right]$$

(9)

L(μ, σ) needs to be minimized to estimate μ and σ

The numerical solution was also implemented using the Python 3.10 program with the same scipy.optimize.minimize function (L-BFGS-B optimization method).

Below, we present a graph to compare the analysis results (Figure 14).

Figure 13 shows that the new range–density MLE method for estimating the parameters with a normal distribution (shown by the green line) correctly takes into account boundary taxa and approximates the measurement data. The method also takes into account the different densities of localities in the middle portions and edges of the analyzed range.

All the graphs and comparisons of the classical MLE and range–density MLE for all 124 analyzed taxa are provided in Supplementary Material S5.

The values of μ and σ for all taxa, indicating the taxon name, its number, and the number of localities in which the taxon was found, are presented in Supplementary Material S6.

2.3.5. Analysis of Bioclimatic Indices for Altitudinal Taxa Groups

To trace the bioclimatic factors that influence the altitudinal distribution of the species, 19 bioclimatic indices were obtained for all the collection localities (Supplementary Material S7).

$$BI{O}_{H, i=1..19}-\mathrm{bioclimatic}\mathrm{index}$$

(10)

H—the set of all collection localities

Using the results presented in Supplementary Materials S5 and S6, all the taxa, H, can be divided into groups according to their altitudinal confinement based on the distribution of the parameters μ and σ. This division makes it possible to analyze subsets of taxa belonging to the same altitudinal belt, based on their common characteristics.

Thus, dividing the taxa into altitudinal groups allows us to make estimates and assumptions based on the common properties of the taxa in each group. In particular, we analyzed the bioclimatic indices determined for each collection locality.

Let us consider that some sets of taxa, $T^{\prime }$, belong to a certain altitudinal group. $T^{\prime }$ is a subset of the sets of all taxa, T. Now, we define a function describing the taxa that were found at location h and at the same time belong to the presented altitudinal group $T^{\prime }$:

$$\begin{gathered} q\left(h,t\right)=\{\begin{array}{l}1 \left(true\right), if species t is found at height h, and t\in T^{\prime } \\ 0 \left(false\right), else \end{array} \\ t\in T, h\in H \end{gathered}$$

(11)

After the latter step, we can determine the average bioclimatic value, I, for all localities where taxa belonging to a certain altitudinal group occur. For this purpose, we find the sum of bioclimatic values, i, for all localities where any taxa from this altitudinal group were found and divide this value by the number of these values:

$$I_{ i=1..19}={\displaystyle \frac{{{\displaystyle \sum }}_H\left(BI{O}_{h, i}·{{\displaystyle \sum }}_{T}q\left(h, t\right)\right)}{{{\displaystyle \sum }}_H{{\displaystyle \sum }}_{T}q\left(h, t\right)}}$$

(12)

Of note, if several taxa belonging to the selected altitudinal group were found at the same locality, then the corresponding bioclimatic values were taken several times to determine the average. This reflects the logic of using the average bioclimatic value, given that localities where many taxa belonging to a given altitudinal group were found make a greater contribution to determining the average value than localities where fewer of these taxa were found.

To find all the values of bioclimatic indices for locations where the taxa of the altitudinal group $T^{\prime }$ were found, we defined multiple sets (ordinary sets should not contain duplicate values) as follows:

$$X_{i=1..19}^{T^{\prime }}=\left[\left[BI{O}_{i=1..19}\left(h\right)|\forall h,\forall t:q\left(h,t\right)=1\right]\right]$$

(13)

For the obtained multisets, we constructed confidence intervals for different confidence levels to show how bioclimatic indices changed among the altitudinal groups. To calculate the confidence intervals, the Python 3.10 program was developed using the scipy.stats module from the SciPy package version 1.10.1.

3. Results

3.1. Taxonomic Diversity

The total number of revealed taxa is 132, belonging to 58 genera, 31 families, 130 species, one variety, and one subspecies. Three of the identified species are referred to as doubtful records (Calypogeia neesiana, Chiloscyphus pallescens, and Gymnocolea inflata), and they were not included in the geographical analysis. In addition, eight taxa (Calypogeia neesiana, Chiloscyphus pallescens, Gymnocolea inflata, Pellia endiviifolia, Plagiochila satoi, Plectocolea ovalifolia, Porella platyphylla, and Radula constricta) do not have exact geographical references and cannot be adequately processed for statistical analysis. Thus, only 124 taxa that we collected with clear geographical identification were processed using mathematical methods. As noted above, prior to our research, 49 species of liverworts were recorded in the preset-day area of Zov Tigra National Park [3,32]. Four of the 49 species were excluded from the flora for various reasons (excluded taxa are listed after the checklist in Appendix A). Therefore, excluding nomenclatural changes and situations where name changes were made (changes caused by heterotypic and homotypic synonymy), 87 liverwort taxa are newly reported for the flora of the park.

The list of taxa is available in Appendix A. Taxa treatment and nomenclature followed those of Söderström et al. [62], with some recent updates. Details of the taxon annotations are presented in the preface to the checklist (Appendix A).

3.2. Data Analysis

3.2.1. Altitudinal Grouping

Figure 15 shows the dependence of μ on σ for all the analyzed taxa.

The abscissa on the diagram (Figure 15) indicates the mean (μ) value, which is the estimated center of the taxon distribution with respect to elevation. The ordinate characterizes the standard deviation (σ), which determines the smoothness of the distribution curve. Small σ values in the lower part of the graph indicate a rather narrow altitudinal range for the taxa. For the majority of the analyzed taxa, the estimated characteristic radius of distribution did not exceed several-hundred meters in elevation. The color of the markers in Figure 15 shows the number of collection locations in which the taxa were found. It varies gradually from red dots (single findings) to green dots (with a maximum of 22 findings for Bazzania denudata and Diplophyllum taxifolium, separately).

In the upper part of the diagram, taxa (for example, 2, 7, 94, and 110) with a very flat distribution curve shape are shown. These results indicate that taxa are more evenly distributed over the entire analyzed elevation range.

The small number of species findings indicates a reduced reliability of the estimation of the species distribution parameters. However, given that the absence of a species at many collection locations is also statistically significant, we decided to exclude the taxa with a small number of findings. Therefore, information about the number of species found was not used for further analyses, and these data were used only for illustrative purposes.

The results of the taxon distribution beyond the extreme limits of the studied altitudinal range are of a probabilistic nature. These results are not used to determine the exact values of taxon distribution, but only for a general assessment of its altitudinal confinement. By definition, the range–density function can be heavily influenced by extreme collection localities, enhancing the effect of taxon altitudinal spacing, as shown in Figure 15. The result at this stage is not the specific position of individual points in this diagram, but rather the identification of general trends and the division of the entire set of taxa into altitudinal groups. In subsequent calculations of bioclimatic indices based on altitudinal groups, the distribution parameters of individual taxa were not used.

Based on the diagram in Figure 15, all involved taxa can be divided into altitudinal groups. We present a histogram for the entire analyzed range based on intervals of 200 m in elevation.

Based on the histogram (Figure 16), it is possible to define three altitudinal groups:

Group A—This group is defined as the lower belt that includes taxa with a calculated distribution center below 300 m a.s.l. Eighteen taxa belong to this group (Figure 16).

A = {1, 4, 23, 26, 28, 35, 37, 40, 55, 82, 88, 89, 90, 93, 99, 100, 121, 122}

Group B—This group is defined as the middle belt and includes taxa with a calculated distribution center between 300 and 1600 m a.s.l. Sixty-four taxa belong to this group (Figure 16).

B = {3, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 24, 25, 27, 33, 34, 36, 38, 39, 41, 42, 43, 44, 46, 47, 49, 52, 53, 54, 56, 57, 58, 60, 63, 67, 69, 71, 72, 75, 76, 79, 80, 81, 84, 85, 86, 87, 95, 96, 97, 98, 102, 103, 104, 105, 110, 113, 114, 115, 118, 124}

Group C—This group is defined as the upper belt and includes taxa with a calculated distribution center above 1600 m a.s.l. Forty-three taxa belong to this group (Figure 16).

C = {2, 5, 6, 19, 20, 21, 22, 29, 30, 31, 32, 45, 48, 50, 51, 59, 61, 62, 64, 65, 66, 68, 70, 73, 74, 77, 83, 91, 92, 94, 101, 106, 107, 108, 109, 111, 112, 116, 117, 119, 120, 123}

The table with the determined altitudinal Groups A, B, C is shown in Supplementary Material S8.

3.2.2. Bioclimatic Characteristic of Altitudinal Groups

To determine how defined the altitudinal groups are in relation to the selected bioclimates, the following operations were performed. All species divided into altitudinal Groups A, B, and C are related to specific localities (one or several among 60) for which the bioclimatic indices were obtained (Supplementary Material S7). To summarize the values of bioclimatic indices for each locality where species of the particular altitudinal group were found, we calculated the arithmetic mean for every bioclimatic index for each altitudinal group. However, the mean value alone is not very informative, as it does not show the span of data. To illustrate the variability diapason, confidence intervals can be calculated. Figure 17 and Figure 18 show how confidence intervals change for values of bioclimatic indices for different altitudinal groups with a confidence interval range of 0.7–0.99.

The confidence intervals of different altitudinal groups intersect in some graphs, and the confidence level sufficient for the intervals not to intersect can be determined. An example is provided in Figure 18.

To visualize the mutual arrangement and intersection of confidence intervals for different confidence levels (0.7–0.99), graphs similar to those in Figure 17 and Figure 18 were created for each bioclimatic index (Supplementary Material S9). In these graphs, the confidence intervals are not normalized, which allows us to assess their real values.

After analyzing the graphs, we selected a confidence level of 95%. The results of constructing 95% confidence intervals are presented in Supplementary Material S10.

The 95% confidence intervals for all bioclimatic indices are presented in Figure 19. The data for each bioclimatic index were normalized.

The minimum (min) lower limit value and the maximum (max) upper limit value of the confidence intervals for Groups A, B, and C were selected for each bioclimate.

The length of the rectangles in the diagram (Figure 19) indicates the breadth of the bioclimatic data of the collection localities corresponding to each altitudinal group of species. The longer the rectangle, the greater the extent to which the data are spread, and vice versa. The distance between the colored rectangles shows how much the bioclimatic indicators differ between the altitudinal groups. Thus, the farther the rectangles are from each other, the more the particular bioclimatic indicators differ by altitudinal group, and the greater the correlation between this bioclimatic index and the distribution of taxa along the altitudinal gradient.

According to Figure 19, the key bioclimatic indicators that are most important for the distribution of liverwort species by altitude group are the annual mean temperature (BIO1), isothermality (BIO3), maximum temperature of the warmest month (BIO5), mean temperature of the wettest quarter (BIO8), mean temperature of the warmest quarter (BIO10), annual precipitation (BIO12), precipitation during the wettest month (BIO13), precipitation during the wettest quarter (BIO16), and precipitation during the warmest quarter (BIO18).

3.2.3. Geographical Analysis

The distribution of flora as a whole and its altitudinal fractions by latitudinal floristic elements and longitudinal area types are provided in the following tables, which are then evaluated in the Section 4.

The latitudinal distribution of floristic elements in the liverwort flora in the park is shown in

Table 1. The latitude fractional composition of liverwort flora in Zov Tigra National Park. The leading elements are presented in bold.

Floristic Elements (Latitudinal Types)	Number of Taxa	Percentage (%)
Arctic-montane	10	7.7
Arctic-boreal	42	32.6
Boreal	20	15.5
Boreal–temperate	20	15.5
Temperate	20	15.5
Temperate–subtropical	12	9.3
Subtropical	1	0.8
Tropical–subtropical	1	0.8
Multizone	3	2.3

.

The longitudinal areas of the park’s liverwort flora are shown in

Table 2. The longitudinal distribution patterns of liverworts in Zov Tigra National Park. The leading area types are presented in bold.

Area Type (Longitudinal Types)	Number of Taxa	Percentage (%)
Circumpolar	62	48.1
Asian	8	6.2
Asian–American	4	3.1
East Asian	34	26.4
East Asian–American	1	0.8
Amphi-Oceanic	10	7.8
Amphi-Pacific	4	3.1
Eurasian	2	1.6
Multi-area	4	3.1

.

The latitudinal distribution of floristic elements and the longitudinal distribution patterns of liverworts by vegetation communities along the altitudinal gradient (distribution by altitudinal vegetation belts) are shown in

Table 3. The latitude fractional composition of vegetation altitudinal belts for liverwort flora in Zov Tigra National Park. The leading elements are presented in bold.

Floristic Elements (Latitudinal Types)	Lower Altitudinal Belt		Middle Altitudinal Belt		Upper Altitudinal Belt
Arctic-montane	1	1.4%	4	4.9%	8	13.1%
Arctic-boreal	16	22.9%	30	36.6%	33	54.1%
Boreal	9	12.9%	18	21.9%	8	13.1%
Boreal–temperate	15	21.4%	9	11.0%	8	13.1%
Temperate	15	21.4%	14	17.1%	2	3.3%
Temperate–subtropical	9	12.9	6	7.3%	2	3.3%
Subtropical	1	1.4%	0	0	0	0
Tropical–subtropical	1	1.4%	0	0	0	0
Multizone	3	4.3%	1	1.2%	0	0
Total	70	100.0%	82	100.0%	61	100.0%

and

Table 4. The longitude fractional composition of vegetation altitudinal belts for liverwort flora in Zov Tigra National Park. The leading elements are presented in bold.

Area Type (Longitudinal Types)	Lower Altitudinal Belt		Middle Altitudinal Belt		Upper Altitudinal Belt
Circumpolar	28	40.0%	43	52.4%	39	63.9%
Asian	3	4.3%	5	6.1%	3	4.9%
Asian–American	3	4.3%	1	1.2%	2	3.3%
East Asian	25	35.7%	23	28.0%	7	11.5%
East Asian–American	1	1.4%	1	1.2%	1	1.6%
Amphi-Oceanic	5	7.1%	5	6.1%	4	6.6%
Amphi-Pacific	2	2.9%	2	2.4%	2	3.3%
Eurasian	0	0	0	0	2	3.3
Multi-area	3	4.3	2	2.4%	1	1.6%
Total	70	100.0%	82	100.0%	61	100.0%

, correspondingly.

In order to assess the internal relationships of the flora (namely, whether there is a taxonomic relationship between liverwort fractions in different altitudinal vegetation belts), we counted the liverwort species found only in one vegetation belt, in two belts simultaneously, and in all three zones. These results are presented in

Table 5. Belt specificity of liverwort species in the flora of Zov Tigra National Park. The total numbers of species for one, two and three belts are presented in bold.

Species Participation in Altitudinal Belts	Number of Taxa	Percentage (%)
Lower belt (500–900 m a.s.l.)	70	54.3
Middle belt (600–1000 to 1600–1650 m a.s.l.	84	66.7
Upper belt (above 1600 m a.s.l.)	59	45.7
Only in one belt	65	50.4
Lower belt (500–900 m a.s.l.)	25	19.4
Middle belt (600–1000 to 1600–1650 m a.s.l.	22	17.1
Upper belt (upper 1600 m a.s.l.)	18	14.0
Total in two belts	44	34.1
Only Lower belt and middle belt	23	17.8
Only Lower belt and upper belt	2	1.6
Only Middle belt and ipper belt	19	14.7
Total in all three belts	20	15.5

.

The ratios of floristic elements and area types were calculated for the three altitudinal groups, A, B, and C (based on the definitions provided in the Section 3.2.1) (

Table 6. The latitude fractional composition of altitudinal groups of liverwort flora in Zov Tigra National Park. The leading elements are presented in bold.

Floristic Elements (Latitudinal Types)	A		B		C
Arctic-montane	0	0	2	3.2%	8	18.6%
Arctic-boreal	1	5.6%	16	25.4%	24	55.8%
Boreal	0	0	13	20.6%	6	14.0%
Boreal–temperate	4	22.2%	10	15.9%	3	7.0%
Temperate	5	27.8%	14	22.2%	1	2.3%
Temperate–subtropical	4	22.2%	7	11.1%	1	2.3%
Subtropical	1	5.6%	0	0	0	0
Tropical–subtropical	1	5.6%	0	0	0	0
Multizone	2	11.1%	1	1.6%	0	0
Total	18	100.0%	63	100.0%	43	100.0%

and

Table 7. The longitude fractional composition of altitudinal groups of liverwort flora in Zov Tigra National Park. The leading elements are presented in bold.

Area Type (Longitudinal Types)	A		B		C
Circumpolar	3	22.2%	26	41.3%	29	67.4%
Asian	4	16.8%	3	4.8%	2	4.7%
Asian–American	1	5.6%	2	3.2%	1	2.3%
East Asian	8	44.4%	23	36.5%	1	2.3%
East Asian–American	0	0	0	0	1	2.3%
Amphi-Oceanic	0	0	7	11.1%	4	9.3%
Amphi-Pacific	0	0	1	1.6%	2	4.7%
Eurasian	0	0	0	0	2	4.7%
Multi-area	2	11.1%	1	1.6%	1	2.3%
Total	18	100.0%	63	100.0%	43	100.0%

).

4. Discussion

Due to the data at hand, the liverwort flora considered in this study is the most taxonomically rich among the flora in the protected areas of the Primorye Territory that have been published to date.

Table 8. The published data on liverworts in the protected areas of the Primorye Territory.

Name	Area, km2	Number of Taxa	References
Kedrovaya Pad′ Nature Reserve	180	74	[45]
Ussuriysky Nature Reserve	404.32	66	[43]
Lazovsky Nature Reserve	1209.98	73	[42,46,47]
Sikhote-Alin Nature Reserve	4016	89	[44]
Zov Tigra National Park	835	132	Present account, [3,32]

shows the data for the total areas and numbers of liverwort taxa in the compared protected areas.

Among the five compared territories, Zov Tigra National Park had the third largest area, as noted above, and the largest number of known taxa. The most obvious explanation for the relatively low number of liverwort taxa reported for other protected areas is the relatively low-quality earlier studies. For example, even a superficial view of the liverwort checklist for the Lazovsky Nature Reserve [42] shows that the largest number of taxa was found in the lower altitudinal belts. However, the number of records belonging to the upper reaches of streams and rivers is relatively low, and most of these records were produced by non-hepaticologists. Therefore, the numbers of known taxa in Table 8 are only considered indicative and not final.

However, there are other objective explanations for Zov Tigra National Park liverwort flora richness. For example, given the significant altitudinal variations (155–1854 m a.s.l.), a possible explanation could be that the park exhibits almost the full range of vegetation communities known in the southern part of Sikhote-Alin [24]. Three of the highest peaks of the Primorye Territory are located in the park, with maximum elevations varying from 1671 to 1854 m a.s.l., allowing for the possibility for alpine community development and, consequently, the presence of “northern” taxa.

For comparison, the highest point of the Kedrovaya Pad Nature Reserve is approximately 700 m a.s.l., and the highest points of the the Ussuriysky Nature Reserve are approximately in the range of 650–700 m a.s.l. Due to the lower altitudes, the broadleaved deciduous and coniferous–broadleaved deciduous forests in the former and coniferous-broadleaved deciduous and fir–spruce forests in the latter are almost exhaust-dominant vegetation types [45,63,64]. There is no possibility for the development of crooked forests and mountain tundra in those reserves. This limits the possibility of certain liverwort taxa associated with these communities. In other words, there are conditionally “southern” taxa in the lower altitudinal belts, and there are no conditionally “northern” taxa related to the upper altitudinal belts in other parts of the southern Sikhote-Alin. Moreover, in the case of the Kedrovaya Pad Nature Reserve, as mentioned by Bakalin et al. [45] (p. 24), “due to loose compressing of the rocks…the drainage abilities of the landscapes are relatively high”. This means that some of the “dryness” in this area may reduce the potential taxonomical richness of the liverworts. In addition, it should be noted that the Kedrovaya Pad Nature Reserve is situated in the northeasternmost fringe of the East-Manchurian Mts. but not within Sikhote-Alin in a geographical sense. Several species, such as Calypogeia tosana, Cephalozia cf. lacinulata, Cylindrocolea kiaeri, and Scapania ciliata, are present only in the former reserve, but are not known to be present at all in Sikhote-Alin. This fact, as mentioned by Bakalin et al. [45], may indicate that the Razdolnaya River valley and the Khanka Lowland, which are between two mountain systems, form a minimally passable phytogeographical barrier.

The Lazovsky and Sikhote-Alin Nature Reserves (the latter is located in the middle part of Sikhote-Alin) exhibit a more complete range of vegetation types along the altitudinal profile. The highest altitudinal points reach a range of 1200–1400 m a.s.l. in the former [17], whereas several mountain peaks exceed a range of 1400–1500 m a.s.l. in the latter [65]. Consequently, there are no obvious reasons other than an insufficient study of the liverwort flora in these areas.

Conditionally “northern” taxa (including arctic-montane and arctic-boreal) are noticeably rare liverwort flora in the park and Sikhote-Alin flora in general, especially in the southern part. However, these taxa are often common in more northern flora in the Russian Far East. The “northern” taxa group in the park includes the arctic-montane Diplophyllum albicans and Pseudolophozia debiliformis, which were collected only above 1700 m a.s.l.; the arctic-boreal Isopaches bicrenatus, which was found at the highest mountain elevations, but are occasionally found along roadsides at elevations no lower than 1000 m a.s.l.; Lophoziopsis excisa and Lophoziopsis longidens, which are collected at elevations no lower than 1600 m a.s.l.; and Scapania parvifolia and boreal Cephaloziella rubella, which are collected at elevations no lower than 1650 m a.s.l. The arctic-montane Scapania praetervisa, which is collected from areas higher than 1700 m a.s.l., is the highlight of this species list. Until recently, the species was only reported in Chukotka and Kamchatka in the Russian Far East [66]. An interesting finding is the identification of arctic-boreal montane East Asian Scapania diplophylloides collected from Oblachnaya Mt. In Russia, the species has mostly been recorded only in the insular part of the Russian Far East (Kurils and Sakhalin Isl.). Subsequently, it was found on Tardoki-Yani Mt., the highest peak of Sikhote-Alin [67]. Cephaloziella rubella, Diplophyllum albicans, and Scapania diplophylloides are newly reported in the Primorye Territory. At the highest elevations (more than 1700 m a.s.l.), boreal-temperate amphi-Oceanic Metzgeria temperata was collected for the first time in Primorye. In Sikhote-Alin, it is also known to have been collected from Tardoki-Yani Mt. [67]. For the first time, Pseudolophozia debiliformis and Scapania praetervisa are reported in the Primorye Territory and Sikhote-Alin Mts., correspondingly. The first species has not been reported in the southern part of the Sikhote-Alin; for the second species, the only location in Sikhote-Alin. However, none of the collected taxa could be attributed to arctic-montane taxa. “True” arctic-montane taxa occur on the highest points of the mountains, starting in the middle part of Sikhote-Alin (approximately 46° N), reaching their highest diversity and abundance in the northern part of these mountains ([67]; Klimova, unpublished). This rarity of arctic-montane taxa is most likely caused by the very limited distribution of mountain tundra in the southern Sikhote-Alin region, even during the Pleistocene, which did not allow representatives of the northern liverwort flora, especially arctic-montane liverworts, to spread widely “step by step” and assume a stable position in vegetation communities. Moreover, this is connected to the general position of the Sikhote-Alin within hemiboreal and cool–temperate vegetation zones and the topography of these mountains, which are characterized as having a low average elevation of ridges (800–1000 m a.s.l.). As a result, a small area of the highlands has an “insular character” and does not form an uninterrupted mountain range [29] (p. 67).

The examples showing the southern relationships of the liverwort flora in the park include tropical–subtropical Acrolejeunea sandvicensis, subtropical Asterella leptophylla, temperate–subtropical Fuscocephaloziopsis catenulata ssp. nipponica, Frullania taradakensis, Mesoptychia ussuriensis, Metzgeria lindbergii, Plectocolea infusca var. infusca, Porella grandiloba, temperate Calypogeia orientalis, Cephaloziella spinicaulis, Frullania appendiculata, Harpanthus scutatus, Lophocolea cuspidata, Metacalypogeia cordifolia, Mylia verrucosa, and Schistochilopsis cornuta. Acrolejeunea sandvicensis, Cephaloziella spinicaulis, Harpanthus scutatus, Mesoptychia ussuriensis, and Plectocolea infusca var. infusca are among the rarest species. The vast majority of the listed species is East Asian. In addition, the East Asian relationships of the liverwort flora found in the park are emphasized by the following taxa: Bazzania manczurica, Bazzania parabidentula, Clevea nana, Cololejeunea ornata, Gymnomitrion parvitextum, Lejeunea japonica, Pedinophyllum truncatum, Porella vernicosa, Radula constricta, Scapania parvitexta, and Solenostoma pseudopyriflorum.

4.1. Geographical Analysis

The arctic-boreal species composed 32.6% (42 taxa) of the liverwort flora, followed by boreal species at 15.5% (20 taxa), temperate species at 15.5% (20 taxa), and boreal-temperate species at 15.5% (20 taxa) (Table 1). These four latitudinal groups constitute most of the liverwort flora. The specificity to the flora is presented, on the one hand, by the presence of arctic-montane taxa (7.7%) caused by the occurrence of tundra and tundra-like communities in the apical parts of the mountains and, on the other hand, by the presence of temperate–subtropical, subtropical, and tropical–subtropical taxa (13.2% of all the flora). The latter emphasizes the “southern” relationships of the liverwort flora in the southern part of Sikhote-Alin and particularly of the liverwort flora in Zov Tigra National Park.

Regarding the distribution of longitudinal types (Table 2), two main groups dominate. Approximately half of the total number of taxa was circumpolar species (48.1%, 62 taxa), and approximately one-quarter (26.4%, 34) had a predominantly East Asian distribution. The presence of amphi-Oceanic (7.8%, 10) and amphi-Pacific (3.1%, 4) taxa was caused by the close proximity of the mountain system to the ocean and provided peculiar features to the liverwort flora.

4.1.1. Geographical Analysis of Liverworts by Vegetation Communities Along the Altitudinal Gradient (Distribution by Altitudinal Vegetation Belts)

The total number of species found in the lower vegetation belt is 70, and the species distribution by floristic elements based on the latitude shows the following regularities. Specifically, arctic-boreal (22.9%, 16 taxa), temperate (21.4%, 15 taxa), and boreal-temperate (21.4%, 15 taxa) liverworts play the leading role, followed by boreal (12.9%, 9 taxa) and temperate–subtropical (12.9%, 9 taxa) liverworts (Table 3). In the middle altitudinal belt, 82 taxa were recorded. This belt is characterized by the dominance of arctic-boreal (36.6%, 30 taxa), boreal (21.9%, 18 taxa), and temperate (17.1%, 14 taxa) liverworts, accounting for 75% of all liverworts. The number of taxa in the arctic-boreal group increased in comparison with that in the lower-belt group. In the upper vegetation belt, 61 taxa were collected. In this belt, there was the largest shift toward the presence of arctic-boreal taxa (more than 50%). The share of arctic-montane taxa (13.1%, 8 taxa) substantially increased compared to that in the other altitudinal belts. Boreal and boreal-temperate groups of taxa exhibit approximately similar numbers.

An analysis of the area types in the three altitudinal belts based on the longitude (Table 4) revealed two clear trends in the changes in species floristic composition. The share of circumpolar taxa increased with elevation, whereas the share of East Asian taxa decreased in the same direction (Table 4). The latter closely corresponds to Rappoport’s rule when applied to altitude [68].

These two groups of species predominate in all three belts. However, in the lower altitudinal belt, circumpolar and East Asian taxa are quite similar in numbers (40.0% and 35.7%, respectively); however, their numbers in the middle belt (52.4% and 28.0%, respectively) and in the upper belt (63.9% and 11.5%, respectively) differed.

Dark coniferous forests in the southern part of the Russian Far East (in both the continental and insular parts), as mentioned by Bakalin [14], are concentrated among East Asian taxa. The present data partly confirm the latter idea. Specifically, the highest number of East Asian taxa was found in coniferous–broadleaved deciduous (mixed in a broad sense) forests, but not in pure coniferous stands. In turn, the conclusion regarding dark coniferous forests should be the same for circumpolar taxa. These taxa comprise more than 50% (Table 4) of the total number of species occurring here. Certainly, the greatest concentration of circumpolar taxa was observed at the highest mountain elevations (above the range of 1600–1650 m a.s.l.). In addition, the absolute maxima number of species in the two belts coincided. Given that altitudes greater than a range of 1600–1650 m a.s.l. are rare in the Primorye Territory, the importance of forests dominated by dark conifers for the housing of circumpolar taxa can hardly be overestimated.

4.1.2. Internal Flora Similarity

Internal flora similarity is difficult to measure across altitudinal groups (discussed below) because they do not intersect (thus, each species belongs to one group only), but can be traced across altitudinal groups based on vegetation type, where each species may be recorded in 1–3 belts. To determine the latter, all taxa were divided into three groups: (a) specific to one belt, (b) found in two belts, and (c) found in three belts. The results for such group are shown in Table 5.

As shown in Table 5, half of all the taxa (50.4%) occurred in one belt, and slightly more than one-third occurred in two belts (34.1%), with the overwhelming majority of the latter occurring in adjacent belt pairs (lower and middle belts or middle and upper belts). Only the lower and upper belts (without the middle belt) shared two taxa (1.6%). In total, 20 taxa (15.5%) were found in all three belts. Thus, the similarity between altitudinal belts does not appear to be very strong because not less than half of the taxa occur in only one belt. In most cases, taxa occurring in two belts are found only in adjacent belts. The vast majority of such taxa common to the two belts could be explained by the sharing of the same types of habitats (e.g., decaying wood, stones near watercourses, etc.). However, this phenomenon of shared potential habitats cannot surpass the climatic differences that obviously change from lower to upper elevations (Supplementary Material S2, Figure 4). Unfortunately, we cannot definitively determine the degree of internal similarity (or, conversely, altitudinal differentiation) of the liverwort flora in Zov Tigra National Park due to a lack of comparable data for the hemiboreal zone in Pacific Asia. Presumably, a similar analysis of other local flora of the same size and taxonomical diversity in the hemiboreal Pacific Asia will enable us to compare and critically evaluate internal similarity or differences in liverwort flora found in the park. The nearest local liverwort flora for which such calculations were performed is found in the southern part of the Korean Peninsula [69]. According to Choi et al. [69], 50.4% of all taxa occurs in one belt, 25.2% is found in two belts, and 24.4% is found in three belts. Therefore, the proportion of taxa common in all three belts was greater than that in Zov Tigra National Park. We explain this fact by the suggestion that, in Mt. Deogyu National Park, climate alterations due to variations in altitude do not lead to dramatic changes in the vegetation. The lowlands up to the environs of watersheds in the park are occupied by broadleaved deciduous forests, and these areas turn into broadleaved forests with some twisted conifers with an admixture near the ridgelines.

4.1.3. Geographical Analysis of Liverworts by Altitudinal Groups

The temperate (27.8%), temperate–subtropical (22.2%), and boreal-temperate (22.2%) taxa play a leading role in altitudinal Group A (Table 6). This ratio clearly reflects the temperate nature of the vegetation that predominates in the altitudinal range of this group, namely, at elevations up to 300 m a.s.l. The “southern” examples of liverworts include Acrolejeunea sandvicensis, Asterella leptophylla, Frullania taradakensis, Porella grandiloba, etc. The role of temperate (22.2%) taxa remains significant in altitudinal Group B. However, these taxa rank in second place, giving way to arctic-boreal (25.4%) taxa. Boreal (20.6%) floristic elements are in third place. The elevation range of this group is the largest and lies between 300 and 1600 m a.s.l. (note that all altitudes here, as defined in the Section 2, have conditional values). Thus, all types of forest vegetation found in the park fall into it, namely, cool–temperate broadleaved deciduous, hemiboreal Pinus koraiensis broadleaved deciduous, oroboreal Abies–Picea forests, and even hemiarctic mountain Betula lanata crooked forest, which form the general “superforest” belt. Slightly more than half of all liverwort species found in the park is confined to this group, and the ratio of floristic elements reflects the character of the entire liverwort flora of the park. In other words, Group B forms the core of the liverwort flora, whereas the species of altitudinal Groups A and C show the specificity of the flora. In altitudinal Group C, “northern” floristic elements comprise more than 90% of the total. The top-three most-common taxa are arctic-montane (18.6%), arctic-boreal (55.8%), and boreal (14.0%) taxa. The altitudinal range of this group extends above 1600 m a.s.l. and determines the absence of tall forests and the predominance of crooked forests, tundra, rock fields, and screes. Notable examples of this altitude group include Diplophyllum albicans, Isopaches bicrenatus, Pseudolophozia debiliformis, and Scapania praetervisa. It is necessary to note some aberrations in the obtained results. For example, it is logical to expect Cololejeunea ornata to be part of Group A, but this species is found in altitudinal Group B because the calculation used the elevation of the single collection locality two-times greater than the elevation limit of Group A. In the case of the typical boreal forest species Anastrophyllum michauxii, which is found in Sikhote-Alin on decaying wood in coniferous forests, its identification in an atypical habitat (a crevice between rocky blocks in lichen–dwarf shrub tundra at 1768 m a.s.l.) played a role in the mathematical analysis. Given that the species was collected from only one locality in this part of the analyzed elevation range, the identified distribution center of the species appeared to be greater than expected (this case is explained in the Section 2, Figure 10). Notably, for the southern Appalachians in North America, Schuster (1969) wrote that Anastrophyllum michauxii “is more often somewhat of an xerophyte” [70] (p. 729) and grows on open-to-shady cliffs with accompanying taxa (also present in Sikhote-Alin), such as Diplophyllum taxifolium, Sphenolobus minutus, and S. saxicola. In the same place, “both northward and in the Southern Appalachians”, the species ecology often includes decaying wood with a set of epixylous species [70] (p. 729). Despite such a variety of substrates, according to Schuster (l.c.), the species “appears to be an excellent indicator species of the Spruce-Fir Forest Region” and “rare in alpine situations, above tree line, where it occurs very sporadically” [70] (p. 729), and this notion is also confirmed by our materials. Such deviations, as described above, did not have a significant impact on the overall trends in the altitudinal distributions of the species.

The change in the longitudinal fractional composition of the altitudinal groups (Table 7) exhibited the same trend as that in a similar analysis of the altitudinal vegetation belts (Table 4). Specifically, the number of circumpolar taxa increased with the altitude, whereas the number of East Asian taxa decreased in the same direction. Interesting differences were only noted between altitudinal Group C (Table 7) and the upper altitudinal belt (Table 4). In the former, the species with an amphi-Oceanic (9.3%) distribution ranked second after the circumpolar species. However, in the latter, these species ranked in third place (after East Asian species).

The observed differences in the distribution patterns of floristic elements and area types based on the altitudinal group determined using the two approaches (Table 3, Table 4, Table 6, and Table 7) are quite explainable. When divided into altitudinal groups based on altitudinal vegetation belts (lower, middle, and upper), one particular taxon may be related to two or even three belts simultaneously, as it was collected from different vegetation communities. The grouping is based on probabilistic models of altitudinal distribution (A, B, and C), and each species can be classified into only one group. Thus, in the latter case, the species was unique to the group. As a result, on the one hand, the number of species in each group decreased; on the other hand, the characteristics of each altitudinal group became more evident.

The liverworts found in the communities of the lower vegetation belt are a group composed of the truly “southern” elements of the flora, and taxa that occur here due to the spread of common substrates in the lower- and middle-altitudinal vegetation belts. These include decaying and rotten wood and stones along watercourses. However, the frequency of their occurrence is generally lower than that in communities in the middle vegetation belt. The same patterns were observed for taxa in the middle and upper vegetation belts. In addition, mathematical analyses performed on the basis of the patterns of the altitudinal distribution of species, where each species could fall into only one of the selected groups, clearly revealed the fraction of the most “southern” and most “northern” elements of the studied flora. The results of the division into altitudinal groups (A, B, and C) using mathematical methods showed that plant communities (altitudinal vegetation belts) are not decisive for ensuring optimal growing conditions for species. The criterion of elevation above sea level, which reflects all the related climatic factors as well as the availability of a suitable substrate for growing, is of much greater importance.

4.2. Climatic Factors Correlating with the Altitudinal Distribution of Liverworts in Zov Tigra National Park

Figure 19 shows that the lower- and middle-altitudinal groups presented the smallest differences in all climatic parameters. In other words, the dependence of bioclimatic indices on elevation in these cases is unambiguous. The minimum variation in climate can be explained by the fact that both altitudinal groups belong to the forest belt in a general sense (albeit different types of forest communities are identified by different dominant species). The difference within the forest belt is much smaller than that between the forest belt and the open areas (tundra, alpine glades, and rock fields), even if they are located in close proximity. The upper altitudinal group is characterized by a generally greater variation in bioclimatic indicators within the group and an approximately 1.5–2.0-times greater variation in some bioclimatic indices (BIO6, 9, and 10, and, to a lesser extent, BIO14, 17, and 19) than other bioclimates in the group. The high dispersion of the listed bioclimatic indicators may be explained by the fact that this altitudinal group belongs to vegetation belts located above the timberline. There are mainly tundra and tundra-like communities in forestless landscapes, and tall trees (forests) cannot “smooth out” the influence of climatic factors [71], whereas mesorelief, slope exposure, and other factors can have a strong influence on the outcome climatic indicators of each specific site. The abovementioned factors do not negate the importance of microniches (with microclimates) for liverwort distribution in general. However, the results indicate the prevailing importance of the mesoclimate (measured using the methods adopted in the present research) for determining the species composition in the elevation belt. Otherwise, bioclimatic indicators highly intersect and are superimposed on each other; however, this is not the case in the present study (Figure 19). In addition, it is worth paying attention to the relatively narrow ranges of bioclimatic variability, which are measured with a reliability of 95%; thus, in most cases, they do not overlap. Such a strictly positioned spread, of course, does not mean that the bioclimates of each group are not meeting each other in reality; however, it does indicate that the groups are defined correctly, given that the “blurring” of the parameters does not occur.

Figure 19 shows a group of key bioclimatic indicators that are the most important for the distribution of liverwort species by altitude group. These variables include annual mean temperature (BIO1), isothermality (BIO3), maximum temperature of the warmest month (BIO5), mean temperature of the wettest quarter (BIO8), mean temperature of the warmest quarter (BIO10), annual precipitation (BIO12), precipitation during the wettest month (BIO13), precipitation during the wettest quarter (BIO16), and precipitation during the warmest quarter (BIO18). All of these variable are characterized by fairly uniform changes in parameters with elevation. The dependence of precipitation (BIO12, 13, 16, and 18) on elevation is direct, whereas the dependence of temperature characteristics (BIO1, 5, 8, and 10) is inverse. We can only trace the main trends and therefore cannot rank these bioclimatic indices in order of importance. The general conclusion is that the distribution of species correlates not only with average annual precipitation and temperature, but also with the temperature and amount of precipitation during the warmest period of the year. As we indicated earlier in the “Study Area” subsection, the warmest quarter is the wettest in the study area.

The leading role of isothermality (BIO3) is noteworthy. This is the only derived climate index that shows a clear dependence on elevation by altitudinal group. It quantifies the large variations in day and night temperatures relative to summer and winter (annual) variations. The absolute values of this parameter are generally quite low in the study area, which indicates a low level of temperature variability in the average month compared to the year. With an increasing elevation, the isothermality (BIO3) decreases in the study area.

The bioclimatic indices, including precipitation during the driest month (BIO14), precipitation during the driest quarter (BIO17), and precipitation during the coldest quarter (BIO19), do not exhibit large variations between altitudinal Groups A and C; however, there are clear differences between Groups A and C and Group B. A similar situation exists for the minimum temperature in the coldest month (BIO6), mean temperature in the driest quarter (BIO9), and mean temperature in the coldest quarter (BIO11), which do not have such fundamental differences in indicators between Groups A and B, in contrast to those noted for Group C. Derived bioclimatic indicators, such as annual temperature range (BIO7) and seasonal precipitation (coefficient of variation) (BIO15), are not significantly correlated with the altitudinal distribution of species. For the bioclimatic index mean diurnal range (BIO2), the dependence of bioclimatic indices on elevation was clear only at lower elevations (altitudinal Group A), and temperature seasonality (BIO4) was only relevant at middle elevations (altitudinal Group B).

5. Conclusions

The liverwort flora of Zov Tigra National Park can generally be described as boreal-temperate circumpolar–East Asian. A clearer definition is impossible due to the strong altitude variation in the studied area that led to the mixture of the various floristic elements. This assumption highly correlates with the general phytogeographic position of the studied area near the northern edge of the East Asian floristic region, where flora should inevitably possess transitive characteristics. The latter also promoted by the old history of continuous florogenesis in the treated area that was never suddenly and dramatically interrupted by Pleistocene glaciations, in contrast to that noted in boreal and hemiboreal Europe. Two groups of taxa provide special peculiarities to the studied flora. On the one hand, the presence of temperate–subtropical, subtropical, and tropical–subtropical taxa emphasizes “southern” relations. On the other hand, arctic-montane taxa, which currently occur in the southern part of the Sikhote-Alin Mts., are relics and are reminiscent of connections with northwardly situated floras in the past.

The conducted research showed a distinctly greater level of taxonomic diversity of “local” flora in the southern part of Sikhote-Alin and particularly in the southern Primorye than could be expected based on previously published data. The number of taxa known in the park was nearly double the number of taxa known in the other protected areas of southern Primorye. The main explanations for this finding include (1) better exploration and (2) high landscape diversity in the studied area. It is worth mentioning that the number of taxa known in the national park is nearly the same as that reported for southern Primorye in total in the past thirty years. The latter also reflects progress in the knowledge of liverwort diversity in the southern part of the Russian Far East. The present account does not pretend to provide complete knowledge of liverwort taxonomical diversity in the National Park, since we could not visit some of the noteworthy areas. At the same time, based on our previous research in the southern part of the mainland Russian Far East, we suggest the liverwort flora was revealed for not less than 80%. Thus, not less than 20 species can be added to the Park’s flora in the future.

The analysis of the altitudinal organization of the flora revealed the following: (1) moderate internal flora similarity along the altitudinal vegetation belts, given that only one-third of the total number of taxa occurred simultaneously in the two belts, and (2) a trend toward an increase in the number of circumpolar species and a decrease in the share of East Asian species with elevation.

Two approaches to altitudinal analysis, namely, “traditional” (grouping of taxa based on altitudinal vegetation belts) and “mathematical” (grouping based on probabilistic models of taxon altitudinal distribution), are not mutually exclusive, but rather show features of the flora from different points of view. The most important difference in altitudinal distribution patterns identified by mathematical approaches lies in the fact that the characteristics of each altitudinal group became more evident. Presumably, the developed new approach can be used in regions where altitudinal zonation is not entirely evident (for example, in mountain floras in the tropics) and to reconstruct florogenesis in future comparisons. In addition, the presented method allows the use of all data collected by the route method commonly used in the floristic practice of regional bryologists.

The most important climatic factors (bioclimatic indices) correlated with the altitudinal distribution of liverworts include the annual mean temperature (BIO1), annual precipitation (BIO12), isothermality (BIO3), and factors associated with the temperature and amount of precipitation during the warmest period of the year, including maximum temperature of warmest month (BIO5), mean temperature during the wettest quarter (BIO8), mean temperature during the warmest quarter (BIO10), precipitation during the wettest month (BIO13), precipitation during the wettest quarter (BIO16), and precipitation during the warmest quarter (BIO18).