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Proceeding Paper

Russian Red Data Book Orchids: Taxonomic Diversity and Anthropogenic Drivers of Their Extinction in Regions †

by
Anatoliy A. Khapugin
1,2
1
Institute of Environmental and Agricultural Biology (X-BIO), Tyumen State University, Volodarskogo Street, 6, 625003 Tyumen, Russia
2
Joint Directorate of the Mordovia State Nature Reserve and National Park ‘Smolny’, Krasnaya Street, 30, 430005 Saransk, Russia
Presented at the 1st International Electronic Conference on Biological Diversity, Ecology and Evolution, 15–31 March 2021; Available online: https://bdee2021.sciforum.net/.
Biol. Life Sci. Forum 2021, 2(1), 21; https://doi.org/10.3390/BDEE2021-09493
Published: 16 March 2021

Abstract

:
The research of drivers leading to plant extinction is a primary task in global biodiversity conservation. Despite Russia covering a large area, there is a lack of data on factors leading to plant extinction there, including orchids. We aimed to evaluate the anthropogenic drivers that threaten orchids included in the Russian Red Data Books. For this purpose, we generalized and systematized data on orchids included in all relevant (i.e., published during the last 10–11 years) regional Red Data Books available online on 31 December 2020. For each Red Data Book orchid, we identified threats, i.e., drivers leading to species extinction, according to the sections “Limiting factors” or “Limiting factors and threats” of the regional Red Data Books. We found the total taxonomic list of Red Data Book orchids in the analyzed regions of Russia. The similarity of the lists of orchid taxa in analyzed regions was established based on the Jaccard index. In regard to extinction drivers, we found which of them are the most serious threats to orchids in the regions of the Russian Federation. We believe that conducting a similar study for the whole array of threatened plants of Russia will provide highly valuable results demanded all over the world.

1. Introduction

The extinction of species is the leading problem in biodiversity conservation at national and global levels. While the extinction of animals can be more easily realized (e.g., [1]), we need more time to prove a plant extinction event [2]. Humphreys et al. (2019) [3] stated that plant extinction studies should undoubtedly come with caveats, indicating an underestimation of plant extinction rates, which could be explained by many unreported extinctions of poorly known taxa. Moreover, regional extinction events could be fixed more slowly at global assessments (e.g., global IUCN Red List). Therefore, they play an important role in the estimation of plant extinctions able to be achieved at a global scale through the regional one.
Although Russia covers about 11.0% of the total terrestrial area, there is a remarkable lack of biodiversity data from this country. This is well recordable in global reviews of biodiversity, including GBIF data [4], naturalized plants [5], ex situ plant conservation centers [6], and peatland vegetation conservation [7]. We believe that this derives from the low availability of biodiversity data written in Russian, which is not prepared according to international publication standards. In particular, this concerns data on the conservation and distribution of orchids. For instance, Khapugin (2020) [8] demonstrated that despite numerous studies of orchids in protected areas, there is a remarkable gap of data in Russia, even when taking into account the high number of protected areas in the country.
Notably, threats registered for each threatened plant could be recognized as extinction drivers. At the same time, various factors differently influence a certain plant species’ extinction. In this study, we aimed (i) to present the taxonomic composition of orchid species included in the recently published Red Data Books of Russia and (ii) to analyze the main threats leading to the extinction of orchids in Russia. We assumed that the extinction of orchids, as more attractive, vulnerable, and wider known plants, is more influenced by such factors as the direct elimination of the aboveground parts of the plants (bouquet gathering) and the disturbance of their habitats.

2. Materials and Methods

For the study, we analyzed the Red Data Books published and/or available online in 2010–2020. This period was selected to use the most modern and relevant data. As a result, we analyzed data on Red Data Book orchid taxa from 51 regions (Figure 1).
To estimate drivers leading to the orchid taxa in Russia, we analyzed the sections “Limiting factors” or “Limiting factors and threats” in each Red Data Book. We did not assess and judge the completeness and reliability of the original data for each orchid included in each Red Data Book. In addition, we did not estimate the validity or reasons for the inclusion of each orchid in the Red Data Books of Russian regions. To establish a scheme of extinction drivers, we mainly applied IUCN—CMP Unified Classification of Direct Threats [10], with modifications based on some relevant publications [9,11,12]. As a result, we used 12 extinction drivers, applied previously in [9], namely, agriculture, fire, forestry, grazing, habitat degradation, habitat destruction, hydrological disturbance, invasion, mining, unknown, urbanization, and utilization.
To standardize the scheme of scientific names, we used the database Plants of the World Online (http://www.plantsoftheworldonline.org/, accessed on 1 November 2021). For this purpose, we applied a three-stage algorithm. In the first stage, we ordered all taxa alphabetically. In the second stage, the scientific names of the orchids were standardized according to the POWO database. In the third stage, we deleted duplicate taxa from species lists for further analysis.
Regarding the determination of the similarity of lists taxa from the regional Red Data Books using the Jaccard similarity index, Jaccard’s similarity index J S = 100 × C / ( A + B C ) was calculated, where A = number of species in floristic list A; B = number of species in floristic list B; and C = number of species shared between two (A and B) floristic lists. For this purpose, we used the function “vegdist” in package “vegan” [13] in software R ver. 3.4.0 [14].

3. Results and Discussion

3.1. Taxonomic Diversity of Red Data Book Orchids

Originally, the accumulated sum of orchid taxa in 51 Red Data Books was 1070. After taxonomic standardization according to taxonomic systems, the total taxonomic list of Red Data Book plants in 51 Russian regions finally contained 120 taxa (Appendix A). The Red Data Book orchid species richness varied across the regions, ranging from 0 in the Astrakhan region to 44 in Krasnodarsky Krai. This is partially in accordance with Efimov (2020) [15], who demonstrated Krasnodarsky Krai as the region with the highest number of orchid taxa in Russia. The average number of Red Data Book species per region in Russia was 18 ± 8 (mean ± SD; median = 18). We also found no correlation between the region’s area and the number of Red Data Book orchids per region (r = 0.08, p < 0.95). The most widespread species were Cypripedium calceolus L. (48 regions) and Orchis militaris L. (46 regions), followed by Epipactis palustris (L.) Crantz (42 regions), Ponerorchis cucullata (L.) X.H.Jin, Schuit. & W.T.Jin (40 regions), Epipogium aphyllum Sw. (39 regions), Hammarbya paludosa (L.) Kuntze (38 regions), Liparis loeselii (L.) Rich. (35 regions), and Corallorhiza trifida Châtel. (33 regions) (Appendix A). Notably, orchids were demonstrated to be the most widespread among all Red Data Book plant species in Russia (see [9]). This is in accordance with data from other studies that demonstrated the high vulnerability of orchids in various regions around the world (e.g., [8,16,17]).
The 120 species belong to 39 genera. The highest number of taxa was found in Dactylorhiza (17 species), Orchis (11 species), Platanthera (11 species), and Neottia (10 species). Thirty-two genera were represented by one (e.g., Calypso, Chamorchis, Gastrodia, and Pogonia) to seven (Epipactis) species (Appendix A).
We conducted a cluster analysis (Ward method; Figure 2) of the similarity of taxonomic lists of orchids in Russian regions based on the Jaccard index similarity. The results reflected the biogeographical position of the regions, with some deviations caused by the number of Red Data Book orchids per region. In the obtained dendrogram, four groups (A, B, C, and D) are distinguishable. Thus, the large and complicated cluster A is represented by regions of the center of European Russia and regions of Urals (e.g., Sverdlovsk region and Chelyabinsk region) and West Siberia (e.g., Tyumen region and Omsk region). Cluster B includes regions of East Siberia (e.g., Krasnoyarsk region and Irkutsk region) and the northwest of European Russia (Novgorod region and Pskov region). Cluster C is certainly complicated, being represented by regions of the north of European Russia (Republic of Komi and Murmansk region) and West Siberia (Khanty-Mansi Autonomous Okrug), as well as the Russian Far East (e.g., Sakhalin region) and East Siberia (e.g., Republic of Yakutia). Finally, cluster D predominantly includes regions of the south of European Russia (e.g., Krasnodarsky Krai and Voronezh region). In this cluster, there is a highly different sub-cluster represented by the Republic of Kalmykia, Yamalo-Nenetskiy Autonomous Okrug, and Kaliningrad region based on the very low number of orchid species per region (i.e., one, four, and six taxa, respectively). These results are similar to the data demonstrated in [9], highlighting that the similarity of the lists of Red Data Book plants reflects the geographical position of regions.

3.2. Extinction Drivers Leading to the Extinction of Red Data Book Orchid Species

To date, many studies have demonstrated that habitat destruction and ecosystem overexploitation are major extinction drivers of plants and animals [18]. Based on our results, it was found that the main drivers leading to the extinction of orchids are generally the same as those that were found for all plants in various regions of the world [9,12,19]. Undoubtedly, various factors cause a different influence on the possibility of orchid extinction. If we have these data, we may judge on measures counteracting the disappearance of plants in certain regions. In our study, we revealed that among the considered extinction drivers, habitat degradation (19.8%), hydrological disturbance (15.6%), urbanization (15.0%), and utilization (14.8%) play key roles in the extinction of Red Data Book orchid species in Russia resulting from multiple drivers (Figure 3).
Notably, by having data on plant extinction in Russia [9] and worldwide [12], we may compare them with data on drivers causing orchid extinction in Russia. Thus, driver “unknown” is somewhat lower than for all Red Data Book plants in Russia (8.1%, see [9]) and even much lower than on a global scale (48.3%, see [12]). This could be explained by the high attractiveness and vulnerability of orchids around the world, which reflects the increased attention to these plants. In turn, the high attractiveness is a reason for drivers “urbanization” and especially “utilization” (including gathering for bouquets and/or attempts to introduce orchids into backyards) (e.g., [20,21]).
The high proportion of the driver “hydrological disturbance” is in accordance with data on the sensitivity of orchids to this factor around the world. Thus, it was found that the fruit set is influenced by precipitation amount [22,23]. The groundwater level (e.g., [24]), as well as drought conditions (e.g., [25]), is also crucial for several orchid species.
The most impactful driver was “habitat degradation”, which also coincides with data on orchids in various regions of the world (e.g., [21,26,27,28,29]). Despite the abovementioned drivers, other drivers could considerably influence various parameters of orchid populations, including “grazing” (e.g., [28,30]) and “fire” (e.g., [21,31]).

4. Conclusions

Our study of drivers leading to the extinction of orchids considerably contributes to the biodiversity conservation in Russia. Despite the high number of Russian-language publications on orchid distribution and conservation, there is a lack of data on factors causing orchid extinction in the whole of Russia. Our study could be considered as an attempt to estimate the drivers using internationally applied schemes (e.g., [9,12]) for orchids in Russia. Our results are considered as a basis for the creation of national classification of threats to plants.
The data on threats to Red Data Book orchids in Russian regions could fill the gaps in the global knowledge on drivers leading to the national extinction of orchid species. This is in accordance with data on extinction drivers on both Russian and global scales, where we found habitat degradation, hydrological disturbance, urbanization, and utilization to be leading factors threatening orchids in Russian regions. In comparison to data on plant extinction on a global and Russian scale, we found that orchids are more susceptible to the direct elimination of the aboveground parts of the orchids (utilization and grazing), disturbance of habitats (urbanization and habitat degradation), and changes in water regime (hydrological disturbance). As expected, the geographical position of regions is associated with the species composition of orchid floras in these regions. Based on our results, we suggest conducting more detailed studies of factors affecting or leading to species extinction of plants and particular plant groups (e.g., families and genera) in Russia or a wider area.

Funding

This study was performed within the framework of the state assignment FEWZ-2020-0009 from the Ministry of Education and Science of the Russian Federation.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

We are grateful to the anonymous reviewer for the helpful comments and suggestions that contributed to the improvement of the manuscript.

Conflicts of Interest

The author declares no conflict of interest.

Appendix A

Table A1. Taxonomic composition of Red Data Book orchids in the 51 studied regions of Russia.
Table A1. Taxonomic composition of Red Data Book orchids in the 51 studied regions of Russia.
Orchid SpeciesNumber of Regions
Cypripedium calceolus L.48
Orchis militaris L.46
Epipactis palustris (L.) Crantz42
Ponerorchis cucullata (L.) X.H.Jin, Schuit. & W.T.Jin40
Epipogium aphyllum Sw.39
Hammarbya paludosa (L.) Kuntze38
Liparis loeselii (L.) Rich.35
Corallorhiza trifida Châtel.33
Cypripedium guttatum Sw.30
Gymnadenia conopsea (L.) R.Br.30
Neottia ovata (L.) Bluff & Fingerh.30
Malaxis monophyllos (L.) Sw.27
Cypripedium macranthon Sw.26
Epipactis atrorubens (Hoffm.) Besser26
Neottia cordata (L.) Rich.26
Dactylorhiza majalis subsp. baltica (Klinge) H.Sund.26
Dactylorhiza viridis (L.) R.M.Bateman, Pridgeon & M.W.Chase25
Herminium monorchis (L.) R.Br.25
Cephalanthera rubra (L.) Rich.23
Calypso bulbosa (L.) Oakes22
Neotinea ustulata (L.) R.M.Bateman, Pridgeon & M.W.Chase22
Neottia nidus-avis (L.) Rich.22
Platanthera bifolia (L.) Rich.22
Dactylorhiza incarnata (L.) Soó20
Platanthera chlorantha (Custer) Rchb.20
Dactylorhiza maculata (L.) Soó19
Dactylorhiza traunsteineri (Saut. ex Rchb.) Soó18
Epipactis helleborine (L.) Crantz18
Goodyera repens (L.) R.Br.18
Dactylorhiza fuchsii (Druce) Soó17
Dactylorhiza incarnata subsp. cruenta (O.F.Müll.) P.D.Sell17
Cypripedium × ventricosum Sw.12
Dactylorhiza russowii (Klinge) Holub12
Cephalanthera longifolia (L.) Fritsch11
Orchis mascula (L.) L.10
Spiranthes sinensis (Pers.) Ames10
Anacamptis coriophora (L.) R.M.Bateman, Pridgeon & M.W.Chase9
Anacamptis palustris (Jacq.) R.M.Bateman, Pridgeon & M.W.Chase7
Ophrys insectifera L.7
Platanthera fuscescens (L.) Kraenzl.6
Platanthera obtusata subsp. oligantha (Turcz.) Hultén5
Cephalanthera damasonium (Mill.) Druce4
Dactylorhiza fuchsii subsp. hebridensis (Wilmott) Soó4
Neottia camtschatea (L.) Rchb.f.4
Anacamptis pyramidalis (L.) Rich.3
Dactylorhiza urvilleana (Steud.) H.Baumann & Künkele3
Gymnadenia odoratissima (L.) Rich.3
Limodorum abortivum (L.) Sw.3
Neolindleya camtschatica (Cham.) Nevski3
Neotinea tridentata (Scop.) R.M. Bateman, Pridgeon & M.W. Chase3
Orchis picta Raf.3
Pseudorchis albida (L.) Á.Löve & D.Löve3
Traunsteinera sphaerica (M.Bieb.) Schltr.3
Anacamptis morio (L.) R.M.Bateman, Pridgeon & M.W.Chase2
Cypripedium shanxiense S.C.Chen2
Cypripedium yatabeanum Makino2
Dactylorhiza incarnata subsp. ochroleuca (Wüstnei ex Boll) P.F.Hunt & Summerh.2
Dactylorhiza majalis (Rchb.) P.F.Hunt & Summerh.2
Dactylorhiza romana subsp. georgica (Klinge) Soó ex Renz & Taubenheim2
Dactylorhiza salina (Turcz. ex Lindl.) Soó2
Dactylorhiza traunsteineri subsp. curvifolia (F.Nyl.) Soó2
Eleorchis japonica (A.Gray) Maek.2
Ephippianthus sachalinensis Rchb.f.2
Gastrodia elata Blume2
Gymnadenia × densiflora (Wahlenb.) A.Dietr.2
Habenaria linearifolia Maxim.2
Orchis pallens L.2
Orchis purpurea Huds.2
Orchis simia Lam.2
Orchis spitzelii Saut. ex W.D.J.Koch2
Oreorchis patens (Lindl.) Lindl.2
Platanthera chorisiana (Cham.) Rchb.f.2
Platanthera densa Freyn2
Platanthera ophrydioides F.Schmidt2
Platanthera tipuloides (L.f.) Lindl.2
Pogonia japonica Rchb.f.2
Ponerorchis chusua (D.Don) Soó2
Steveniella satyrioides (Spreng.) Schltr.2
Amitostigma kinoshitae (Makino) Schltr.1
Cephalanthera cucullata Boiss. & Heldr.1
Cephalanthera erecta (Thunb.) Blume1
Cephalanthera longibracteata Blume1
Chamorchis alpina (L.) Rich.1
Cremastra appendiculata var. variabilis (Blume) I.D.Lund1
Dactylorhiza fuchsii subsp. psychrophila (Schltr.) Holub1
Dactylorhiza sambucina (L.) Soó1
Dactylostalix ringens Rchb.f.1
Epipactis condensata Boiss. ex D.P.Young1
Epipactis microphylla (Ehrh.) Sw.1
Epipactis papillosa Franch. & Sav.1
Epipactis pontica Taubenheim1
Galearis cyclochila (Franch. & Sav.) Soó1
Goodyera henryi Rolfe1
Goodyera schlechtendaliana Rchb.f.1
Habenaria yezoensis H.Hara1
Himantoglossum caprinum (M.Bieb.) Spreng.1
Himantoglossum comperianum (Steven) P.Delforge1
Liparis kumokiri F.Maek.1
Liparis loeselii subsp. sachalinensis (Nakai) Efimov1
Liparis makinoana Schltr.1
Myrmechis japonica (Rchb.f.) Rolfe1
Neottia acuminata Schltr.1
Neottia convallarioides (Sw.) Rich.1
Neottia krasnojarica Antipova1
Neottia papilligera Schltr.1
Neottia pinetorum (Lindl.) Szlach.1
Neottia puberula (Maxim.) Szlach.1
Ophrys apifera Huds.1
Ophrys caucasica Woronow ex Grossh.1
Ophrys sphegodes subsp. mammosa (Desf.) Soó ex E.Nelson1
Orchis × colemanii Cortesi1
Orchis × wulffiana Soó1
Orchis provincialis Balb. ex Lam. & DC.1
Orchis punctulata Steven ex Lindl.1
Platanthera bifolia subsp. extremiorientalis (Nevski) Soó1
Platanthera maximowicziana Schltr.1
Platanthera sachalinensis F.Schmidt1
Serapias vomeracea (Burm.f.) Briq.1
Spiranthes spiralis (L.) Chevall.1
Traunsteinera globosa (L.) Rchb.1
Table A2. The number of taxa per genus of Red Data Book orchids in the 51 studied regions of Russia.
Table A2. The number of taxa per genus of Red Data Book orchids in the 51 studied regions of Russia.
Orchid GenusNumber of Species per Genus
Dactylorhiza17
Orchis11
Platanthera11
Neottia10
Epipactis7
Cephalanthera6
Cypripedium6
Anacamptis4
Liparis4
Ophrys4
Goodyera3
Gymnadenia3
Habenaria2
Himantoglossum2
Neotinea2
Ponerorchis2
Spiranthes2
Traunsteinera2
Amitostigma1
Calypso1
Chamorchis1
Corallorhiza1
Cremastra1
Dactylostalix1
Eleorchis1
Ephippianthus1
Epipogium1
Galearis1
Gastrodia1
Hammarbya1
Herminium1
Limodorum1
Malaxis1
Myrmechis1
Neolindleya1
Oreorchis1
Pogonia1
Pseudorchis1
Serapias1
Steveniella1

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Figure 1. Map of the Russian Federation, where the sampled regions are indicated. Empty regions refer to the absence of data on Red Data Book orchids (according to [9] with modifications).
Figure 1. Map of the Russian Federation, where the sampled regions are indicated. Empty regions refer to the absence of data on Red Data Book orchids (according to [9] with modifications).
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Figure 2. Cluster tree (Ward method, Euclidian distance) showing the similarity of regions based on the Jaccard index similarity of the lists of Red Data Book orchid species in Russian regions. Designations: Ady—Republic of Adygea, AlK—Altaisky Krai, AlR—Republic of Altai, Bsh—Republic of Bashkiria, Bel—Belgorod region, Bry—Bryansk region, Bur—Republic of Buryatia, Chlb—Chelyabinsk region, Chrk—Republic of Karachay-Cherkessia, Chu—Republic of Chuvashia, Irk—Irkutsk region, Iva—Ivanovo region, Kln—Kaliningrad region, Klm—Republic of Kalmykia, Klg—Kaluga region, Kam—Kamchatsky Krai, Kem—Kemerovo region, Khb—Khabarovsk Krai, Khk—Republic of Khakassia, KhMa—Khanty-Mansi Autonomous Okrug, Kir—Kirov region, Kom—Republic of Komi, Krd—Krasnodarsky Krai, Krya—Krasnoyarsk Krai, Krg—Kurgan region, Krsk—Kursk region, Lip—Lipetsk region, Mag—Magadan region, MEl—Republic of Mari El, Mrd—Republic of Mordovia, Msc—Moscow region, Mur—Murmansk region, NNo—Nizhniy Novgorod region, Nvg—Novgorod region, Nsk—Novosibirsk region, Omsk—Omsk region, Ore—Orenburg region, Pnz—Penza region, Psk—Pskov region, Rst—Rostov region, Rya—Ryazan region, Skh—Sakhalin region, Sam—Samara region, Sve—Sverdlovsk region, Tat—Republic of Tatarstan, TrB—Zabaikalsky Krai, Tul—Tula region, Tve—Tver region, Tmn—Tyumen region, Tyv—Republic of Tyva, Udm—Republic of Udmurtia, Uly—Ulyanovsk region, Vla—Vladimir region, Vlg—Volgograd region, Vor—Voronezh region, Yak—Republic of Yakutia, YaN—Yamalo-Nenetskiy Autonomous Okrug, Yar—Yaroslavl region.
Figure 2. Cluster tree (Ward method, Euclidian distance) showing the similarity of regions based on the Jaccard index similarity of the lists of Red Data Book orchid species in Russian regions. Designations: Ady—Republic of Adygea, AlK—Altaisky Krai, AlR—Republic of Altai, Bsh—Republic of Bashkiria, Bel—Belgorod region, Bry—Bryansk region, Bur—Republic of Buryatia, Chlb—Chelyabinsk region, Chrk—Republic of Karachay-Cherkessia, Chu—Republic of Chuvashia, Irk—Irkutsk region, Iva—Ivanovo region, Kln—Kaliningrad region, Klm—Republic of Kalmykia, Klg—Kaluga region, Kam—Kamchatsky Krai, Kem—Kemerovo region, Khb—Khabarovsk Krai, Khk—Republic of Khakassia, KhMa—Khanty-Mansi Autonomous Okrug, Kir—Kirov region, Kom—Republic of Komi, Krd—Krasnodarsky Krai, Krya—Krasnoyarsk Krai, Krg—Kurgan region, Krsk—Kursk region, Lip—Lipetsk region, Mag—Magadan region, MEl—Republic of Mari El, Mrd—Republic of Mordovia, Msc—Moscow region, Mur—Murmansk region, NNo—Nizhniy Novgorod region, Nvg—Novgorod region, Nsk—Novosibirsk region, Omsk—Omsk region, Ore—Orenburg region, Pnz—Penza region, Psk—Pskov region, Rst—Rostov region, Rya—Ryazan region, Skh—Sakhalin region, Sam—Samara region, Sve—Sverdlovsk region, Tat—Republic of Tatarstan, TrB—Zabaikalsky Krai, Tul—Tula region, Tve—Tver region, Tmn—Tyumen region, Tyv—Republic of Tyva, Udm—Republic of Udmurtia, Uly—Ulyanovsk region, Vla—Vladimir region, Vlg—Volgograd region, Vor—Voronezh region, Yak—Republic of Yakutia, YaN—Yamalo-Nenetskiy Autonomous Okrug, Yar—Yaroslavl region.
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Figure 3. Primary drivers leading to orchid extinctions in Russia according to lists of Red Data Books of Russian regions.
Figure 3. Primary drivers leading to orchid extinctions in Russia according to lists of Red Data Books of Russian regions.
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Khapugin, A.A. Russian Red Data Book Orchids: Taxonomic Diversity and Anthropogenic Drivers of Their Extinction in Regions. Biol. Life Sci. Forum 2021, 2, 21. https://doi.org/10.3390/BDEE2021-09493

AMA Style

Khapugin AA. Russian Red Data Book Orchids: Taxonomic Diversity and Anthropogenic Drivers of Their Extinction in Regions. Biology and Life Sciences Forum. 2021; 2(1):21. https://doi.org/10.3390/BDEE2021-09493

Chicago/Turabian Style

Khapugin, Anatoliy A. 2021. "Russian Red Data Book Orchids: Taxonomic Diversity and Anthropogenic Drivers of Their Extinction in Regions" Biology and Life Sciences Forum 2, no. 1: 21. https://doi.org/10.3390/BDEE2021-09493

APA Style

Khapugin, A. A. (2021). Russian Red Data Book Orchids: Taxonomic Diversity and Anthropogenic Drivers of Their Extinction in Regions. Biology and Life Sciences Forum, 2(1), 21. https://doi.org/10.3390/BDEE2021-09493

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