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• Published: 30 May 2023

An updated floristic map of the world

• Yunpeng Liu   ORCID: orcid.org/0000-0001-6188-3511 1 , 2   na1 ,
• Xiaoting Xu   ORCID: orcid.org/0000-0001-8126-614X 1 , 3   na1 ,
• Dimitar Dimitrov   ORCID: orcid.org/0000-0001-5830-5702 4   na1 ,
• Loic Pellissier   ORCID: orcid.org/0000-0002-2289-8259 5 , 6 ,
• Michael K. Borregaard   ORCID: orcid.org/0000-0002-8146-8435 2 ,
• Nawal Shrestha 1 , 7 ,
• Xiangyan Su 1 , 8 ,
• Niklaus E. Zimmermann   ORCID: orcid.org/0000-0003-3099-9604 6 ,
• Carsten Rahbek   ORCID: orcid.org/0000-0003-4585-0300 1 , 2 , 9 , 10 &
• Zhiheng Wang   ORCID: orcid.org/0000-0003-0808-7780 1  

Nature Communications volume  14 , Article number:  2990 ( 2023 ) Cite this article

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• Biodiversity
• Biogeography
• Macroecology

Matters Arising to this article was published on 02 May 2024

Floristic regions reflect the geographic organization of floras and provide essential tools for biological studies. Previous global floristic regions are generally based on floristic endemism, lacking a phylogenetic consideration that captures floristic evolution. Moreover, the contribution of tectonic dynamics and historical and current climate to the division of floristic regions remains unknown. Here, by integrating global distributions and a phylogeny of 12,664 angiosperm genera, we update global floristic regions and explore their temporal changes. Eight floristic realms and 16 nested sub-realms are identified. The previously-defined Holarctic, Neotropical and Australian realms are recognized, but Paleotropical, Antarctic and Cape realms are not. Most realms have formed since Paleogene. Geographic isolation induced by plate tectonics dominates the formation of floristic realms, while current/historical climate has little contribution. Our study demonstrates the necessity of integrating distributions and phylogenies in regionalizing floristic realms and the interplay of macroevolutionary and paleogeographic processes in shaping regional floras.

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Introduction.

Biogeographic regionalizations divide the world into regions based on the similarity between faunas or floras and have been one of the central topics in biogeography since the time of Charles Darwin and Alfred Russel Wallace 1 , 2 , 3 , 4 . Darwin’s biogeographic observations on the similarities in faunas or floras across regions during the voyage of Beagle (1831–1836) led him to his theory on natural selection 3 , 5 . In 1876, Wallace published his global map of zoological realms based on compositional similarity and taxonomic relationships of animal families across regions. The early maps of biogeographic regions, including the Wallace zoological realms, have significantly improved our understanding of global biodiversity 6 , and provided a spatially explicit tool for conservation planning 7 , 8 .

To understand the evolution of plant diversity, several global floristic regionalization schemes were generated by early authors, including de Candolle (1820) 9 , 10 , Schouw (1823) 4 , Engler (1892) and others 1 , 4 , 10 , 11 , 12 . Later, Takhtajan (1969, 1970, 1974, 1978, and 1986) summarized the basic understanding on the distribution and origin of floras and developed the most widely used map of floristic biogeographic regionalization scheme up to now, which divided the world landmasses into six “kingdoms” and 35 “regions” 4 . These early floristic schemes identified biogeographic regions and their hierarchical relationships mainly based on endemism of floras at different taxonomic levels, combined with a generally descriptive understanding of paleoclimate and geological history 1 , 4 , 10 , 11 , 12 . The rapid accumulation of phylogenetic and species distribution data has significantly improved the development of quantitative and repeatable biogeographic regionalizations, providing valuable insight on the historical relationships among floras or faunas 2 , 13 , 14 , 15 , 16 , 17 , 18 , 19 . For example, an updated global zoogeographic regionalization 2 was generated recently using quantitative phylogenetic relatedness of birds, mammals and amphibians showing the geographic variations in tetrapod evolution at the global scale 20 , 21 . A few regional floristic regionalizations using similar methods have been conducted in China 17 , 22 , Japan 23 , South Africa 15 , and the tropics 14 . However, the progress in building a global floristic regionalization using quantitative approaches has lagged behind state-of-the-art zoogeographic regionalizations due to the lack of phylogenetic and distribution data of plants at a global scale. Recently, Carta et al. proposed a global floristic regionalization with three floristic kingdoms based on phylogenetic beta diversity of a fraction (ca. 20%) of vascular plant species 24 . The impacts of incomplete sampling in both distribution and phylogeny on the regionalization of Carta et al. 24 remain unknown. Meanwhile, this regionalization was based on species rather than genera, limiting its comparison with previous floristic regionalizations based on genus and family endemism 4 , 11 , 12 .

The drivers shaping boundaries between different biogeographic regions are critical for understanding the macroevolution of floras and faunas in different regions 20 , yet they remain rarely explored 20 , 25 . The dynamics in geology and macroclimate over time have left profound effects on the speciation, extinction, and dispersal of plants and thus are considered as drivers shaping floristic boundaries 20 , 21 , 26 , 27 . The dynamics in plate tectonics throughout the earth’s history, including plate collision, orogeny and the emergence and breakup of land bridges, have led to significant changes in geographic isolation and floristic exchanges among landmasses over time, subsequently influencing evolutionary processes such as speciation and extinction of floras in different regions 20 , 28 , 29 . Macroclimate, especially temperature and precipitation, represents a major dimension of the ecological niches of plants 30 , 31 . Geographic differences in paleoclimate during geological times led to significant changes in species compositions across space because of the effect of climatic filtering on species distributions 30 , 32 . A recent study indicated that current climate and tectonic movements contributed to the boundaries between zoological realms 20 . However, the spatiotemporal variation in the relative roles of these two drivers on the boundaries between global floristic realms remain unknown. Moreover, isolation-induced clade splitting, and the independent radiation of descendant lineages have led to abrupt floristic transitions across biogeographic boundaries 33 . In addition, different clades may contribute unequally to the division of different realms due to differences in clade evolutionary histories and geographic distributions 34 , which remains to be evaluated.

Here, we present a global map of floristic realms by integrating distribution data and a phylogeny of 12,664 angiosperm genera (ca. 85% of all known angiosperm genera). Floristic realms are identified using hierarchical clustering methods based on phylogenetic beta diversity between regions at genus level. We then demonstrate the temporal dynamics of the identified floristic realms during the Cretaceous and the Cenozoic, and further compare our work with Takhtajan’s floristic map 4 and Holt et al.’s zoological map 2 . To explore the mechanisms underlying the formation of the identified floristic realms, we evaluate the effects of contemporary climate, the dynamics of geographic isolation induced by long-term plate tectonics, and historical climate. We also evaluate the relative contributions of clade splitting events at different geological times to realm divisions.

Results and discussion

World’s floristic regionalization.

Hierarchical clustering analysis based on phylogenetic beta diversity (see Methods) indicates that the terrestrial world is divided into eight floristic realms, namely African, Australian, Novozealandic, Indo-Malesian, Neotropical, Chile-Patagonian, Holarctic and Saharo-Arabian realms (Fig. 1a ). The African realm is closely related to the Indo-Malesian realm, the Australian realm is closely related to the Novozealandic realm, and the Neotropical realm is closely related to the Chile-Patagonian realm (Fig.  1b ). The above realms are grouped into the Gondwanan super-realm. The Holarctic and Saharo-Arabian realms are grouped into the Laurasian super-realm. Within these eight realms, we further identified 16 floristic sub-realms (Fig.  1 ; also see Supplementary Table  1 for their names and Supplementary Fig.  1 for their relationships).

a Boundaries of the eight floristic realms and 16 sub-realms are shown in solid and dashed lines, respectively. b The unrooted dendrogram depicts the relationships among floristic realms evaluated using UPGMA clustering method based on phylogenetic beta diversity between realms. The scale bar in the dendrogram shows the dissimilarity between realms. c The scatter plot shows the dissimilarities in the phylogenetic compositions between different geographic standard units (GSU) generated using non-metric multidimensional scaling (NMDS) ordination. Each tip in the dendrogram and each point in the scatter plot represents a geographic standard unit and the colors indicate the floristic realms that they belong to. For comparison, the floristic realms and sub-realms based on trees with alternative dating constraints are shown in Supplementary Fig.  2 . Source data are provided as a Source Data file.

The boundaries between different realms generally have high confidence (i.e., “hardness”) in most cases as evaluated by silhouette analysis 35 (Supplementary Fig.  2 , see Methods) and are robust to different assumptions on the crown age of angiosperms (Supplementary Fig.  3 ) and to variations in phylogenetic topology (Supplementary Figs.  4 – 8 ). We also evaluated the effect of incomplete sampling on realm boundaries by repeating our regionalization process using only the genera included in ref. 24 (9905 angiosperm genera), and we found that the boundaries were also robust (Supplementary Fig.  9 , also see Supplementary Discussions for details). Interestingly, distribution ranges for ca. 53.6% genera do not extend beyond the identified boundaries (Supplementary Data  5 ), suggesting that the identified realm boundaries may reflect ecological or evolutionary barriers of plant distributions 31 . Although the boundaries identified by the UPGMA clustering are mostly consistent with those based on the fuzzy clustering method (i.e., fuzzy c-means), inconsistency exits in the identification of the Chile-Patagonian realm and the North American sub-realm, suggesting lower confidence in the identification of these realms/sub-realms than others (see Supplementary Fig.  17 , Methods, and Supplementary Discussions for details).

Floristic realms and their relatedness based on taxonomic beta diversity are relatively consistent with phylogenetic-based floristic realms with three exceptions (Supplementary Fig.  10 , also see Supplementary results and discussion for a detailed comparison). First, subtropical East Asia was grouped into the Indo-Malaysian realm when taxonomic beta diversity was used but was grouped into the Holarctic realm when phylogenetic beta diversity was used. Second, Mexico was grouped into the Chile-Patagonian realm when taxonomic beta diversity was used but was grouped into the Neotropical realm when phylogenetic beta diversity was used. Third, (Australian, Chile-Patagonian) realms are grouped with (African, Indo-Malesian) realms, but was groped with ((African, Indo-Malesian), (Neotropical, Chile-Patagonian)) realms when phylogenetic beta diversity was used. These differences between the taxonomic-based and phylogenetic-based results may suggest recent exchange through dispersal of lineages among these regions (see Supplementary Discussion for details).

The divergent times between the identified realms

By cutting the dated phylogeny at different depths (i.e., geological times), we found that the identified floristic realms have not become distinct before the Cretaceous (160 Ma; Fig.  2 & Fig.  3 ). During the Early Cretaceous, the divergences in present-day floras in the Gondwanan and Laurasian super-realms had formed (Fig.  2c ). The divergences between the floras of Neotropical and African realms were not clear until about 80 Ma ago. During the Cenozoic, the dissimilarity between the present-day floras of different realms significantly increased (Fig.  3 ).

The phylogenetic tree is cut at successive phylogenetic depths and all descendent leaves are collapsed into the branches encountered at that depth. Then the realms at each phylogenetic depth are identified using the same clustering method as in Fig.  1 . It is noteworthy that we do not intend to estimate the ancestral geographic ranges of phylogenetic branches. This chronological sequence of maps represents the divergence times of flora that survived to the present day, but it provides only limited information on the ancestral floristic relatedness, which should be evaluated by fossils. The floristic realms which can be matched to the present-day realms are shown in the same colors as shown in Fig.  1a . As the present-day floristic realms are not distinguishable in some historical periods, we used other colors to represent these ancestral floristic realms. Specifically, light green in maps of 10, 40, and 50 Ma represents the ancestral realm covering the geographic ranges of the present-day African and Indo-Malesian realms; pink appearing from 100 Ma to 140 Ma represents the ancestral realms covering the present-day Neotropical+African realms, the present-day Neotropical+African+Indo-Malesian realms, and the present-day Gondwanan super-realm, respectively. Notably, most present-day floristic realms are undistinguishable in 160 Ma.

The Euclidean distance between dots is positively associated with the dissimilarity in phylogenetic composition of the flora between them: the larger the distance, the higher is the dissimilarity. Each line represents the distance of present phylogenetic composition of a realm to other realms at different phylogenetic depths. The colors of the lines are consistent with the colors of the realms shown in Fig.  1a , and the color gradient of each thick line represents evolutionary time. Source data are provided as a Source Data file.

The divergences among the present-day floras of most realms have formed since the early Cenozoic, and the boundaries between them remain largely unchanged towards the present with two exceptions (Fig.  2 ). First, the boundaries between the African and the Indo-Malesian realms disappeared when evaluated at the phylogenetic depth from the Eocene to the Pliocene, although their divergence was clear during the Paleogene (60 Ma; Fig.  2 ). The dissimilarity between the present-day floras of these two realms was much lower at the phylogenetic depth from the Eocene to the Pliocene than at the present (0 Ma), resulting in the disappearance of boundaries of these two realms at these times (Fig.  3 ). Fossil evidence on historical changes in woody assemblages during the Cenozoic 36 further supports this finding, which is possibly because the northward drifted of the Indian subcontinent during the Cenozoic accumulated floristic exchanges between Eurasia and Africa 37 , 38 .

Second, the northern boundary of the Neotropics realm ends at the Greater Antilles and the Yucatan Peninsula in Mesoamerica during 60–40 Ma and further extends to Mexico afterwards (Fig.  2 ). These results are consistent with recent findings about the history of biotic interchange between South America and Mesoamerica 39 , 40 , 41 , 42 . Recent studies 39 , 40 found that dispersal of plant lineages from Amazonia to Mesoamerica and the Caribbean islands occurred continuously since the early Cenozoic and was much more frequent than dispersal from Amazonia to any adjacent regions in the south. Fossil and plate tectonic evidence suggest that the expansion of megathermal vegetation 43 and an emergent Aves Ridge during the Paleocene 42 , 44 may have facilitated the biotic interchange from South America to Mesoamerica and the Caribbean islands, which may have led to high phylogenetic similarities of flora in these regions.

It is noteworthy that the inference of the divergence times between the identified realms was based on the phylogeny of present-day taxa. Although these results are relatively consistent with fossil evidence, how to reconstruct historical divergences between floristic realms by integrating distributions of current clades and fossils remains to be explored in future studies. Such studies may need a comprehensive framework that integrates analytical tools in paleoecology, systematics, paleoclimatology, and macroecology, in order to better explore the historical changes of floristic realms and the underlying drivers.

Comparison with Takhtajan’s floristic regionalization and the updated Wallace realms

Several notable differences are recognized between the Takhtajan (1986) and our floristic maps (Supplementary Fig.  11 ). First, the “Paleotropical kingdom” in Takhtajan’s map is divided into the Indo-Malesian realm and the African realm. These two realms have been separated by the Indian Ocean since the late Jurassic 31 , 37 , which may have led to the division between them. The temporal changes in the floristic similarity between these two realms are also supported by woody angiosperm fossils in these regions 36 .

Second, the “Antarctic kingdom” in Takhtajan’s map is divided into the Chile-Patagonian and Novozealandic realms here, which is consistent with the view of Cox 1 . Our results indicate that the floras in these two regions are phylogenetically more similar to their adjacent realms than to each other throughout the geological history (Fig. 1b ), which is also supported by the similarity in woody fossils during the Cenozoic 36 .

Third, we define the new Saharo-Arabian realm, which was treated as a subset of the “Holarctic kingdom” in Takhtajan’s map 4 . Our updated Holarctic realm mainly covers the ancient Laurasia landmasses 19 , 31 . The newly defined Saharo-Arabian realm covers northern Africa and the Arabian Peninsula, and has been connected with Africa and separated from the ancient Laurasia landmasses by the Tethys Sea since the Cretaceous 37 , 45 . Our analysis on realm dynamics shows that the flora in the Saharo-Arabian realm already differed from that in the Holarctic realm during the late Cretaceous (Fig.  2 ). Since the Early Miocene (23–16 Ma), the Saharo-Arabian realm experienced several waves of aridification, which may have further led to the evolutionary divergence of its flora from that of the Holarctic realm 46 , 47 . Notably, the separation of the Saharo-Arabian realm from the Holarctic realm is robust to different assumptions on the crown age of angiosperms (Supplementary Fig.  3 ), variations in phylogenetic topology (Supplementary Figs.  4 – 8 ), sampling biases (Supplementary Fig.  9 ), taxonomic beta diversity (Supplementary Fig.  10 ) and the chosen of different clustering methods (Supplementary Fig.  17 ). Even though, the boundary between the Saharo-Arabian and the Holarctic realms remains uncertain, as the fuzzy c-means clustering suggests that the boundary might encroach into Europe (Supplementary Fig.  17 ). The boundary uncertainty may be induced by the overlap between the Saharo-Arabian and Holarctic floras (Supplementary Data  5 , also see Supplementary Fig.  19 ), and therefore, future investigations at regional scales are needed to further clarify the northern boundary of the Saharo-Arabian realm.

Fourth, the Cape region is ranked as one of six “kingdoms” in Takhtajan’s map 4 , but as a sub-realm of the African realm here. Our result is consistent with Cox 1 . The Cape region has not been geographically separated from Africa and shares similar tectonic history with the African continent 31 . The endemism in the Cape flora is primarily observed at species level, while the number of endemic taxa at higher levels, e.g., genus and family, is much lower than in other realms 1 , 48 . Many genera with high proportions of endemic species in the Cape region are also widely distributed in Africa, such as Erica, Protea, Helichrysum 49 . However, most endemic genera in the Cape region contain only very few species 1 . These findings suggest that the Cape flora may not have higher evolutionary distinctiveness at higher taxonomic (e.g., the genus or family) levels compared with floras in other African regions 1 .

A comparison between our floristic map and the recently updated zoogeographic map (9) indicates several consistencies, suggesting that there are common drivers of terrestrial plant and animal biogeographic patterns. Specifically, the Saharo-Arabian and Indo-Malesian realms are identified in both maps and the boundaries of these realms are largely consistent (Supplementary Fig.  11 ). Moreover, the Cape region is not recognized as a realm in both maps. Notably, there are also interesting differences between our floristic and the zoogeographic maps. Our floristic map supports: (1) a Holarctic realm rather than the separated Palearctic, Nearctic and Sino-Japanese realms in the zoogeographic map; (2) an African realm rather than separated Afrotropical and Madagascan realms; (3) an Indo-Malesian realm rather than separated Oriental and Oceanian realms. These differences may to some extent reflect the effects of different dispersal abilities of plants and vertebrates on biotic interchanges between regions 1 . Fossil and molecular evidence suggests that dispersal across land bridges separated by water is relatively common and has occurred in many plant clades 39 , 40 . In contrast, long-distance dispersal across sea water in vertebrates has been found to be biased to clades with specific locomotion, e.g., flight in birds 50 .

The drivers on the division between floristic realms

Contemporary climate explains considerable variations in phylogenetic beta diversity within the Neotropical ( R 2  = 17.8%), Chile-Patagonian ( R 2  = 32.9%), Indo-Malesian ( R 2  = 23.8%), African ( R 2  = 14.7%) and Australian realms ( R 2  = 17.6%), but not within the Holarctic ( R 2  = 6.6%) and Saharo-Arabian realms ( R 2  = 1.3%). In contrast, contemporary climate has consistently extremely low explanatory power on the phylogenetic beta diversity between realms ( R 2  < 8% for all realm pairs). These results suggest that, although contemporary climate influences floristic variations within some realms, it is not a dominant driver for realm division (Fig.  4 ).

The bars show the explained variance in the phylogenetic beta diversity within (red and blue) and between (gray) different realms (or clusters of realms) as shown by the inset maps. a Gondwanan super-realm vs. Laurasian super-realm; b Holarctic realm vs. Saharo-Arabian realm; c (Australian, Novozealandic) realms vs. ((African, Indo-Malesian), (Neotropical, Chile-Patagonian)) realms; d Neotropical realm vs. Chile-Patagonian realm; e (African, Indo-Malesian) realms vs. (Neotropical, Chile-Patagonian) realms; f Australian realm vs. Novozealandic realm and g African realm vs. Indo-Malesian realm. Source data are provided as a Source Data file.

We then evaluated the relative effects of the other two factors on the division of realms, i.e., the historical climatic differences across space during geological times (historical climate hereafter) and historical geographic isolation induced by plate tectonics (geographic isolation hereafter). It is noteworthy that geographic isolation and historical climate may, to some extent, interlink with each other as plate tectonics may lead to shifts in landmasses and their climates. Our results indicate that the correlations between temporal dynamics in historical climate and geographic isolation are generally low in most cases (Supplementary Fig.  12 , Pearson r  < 0.3) except in the comparison between the Australian and Neovozealandic realms (Supplementary Fig.  12f , Pearson r  = 0.56 ± 0.01). To better compare the effects of historical climate and geographic isolation on realm division, we conducted hierarchical partitioning analysis to estimate their independent effects (Fig.  5 ). We find that historical climate has weak effects on the division between most realms. For the division of the temperate realms (i.e., Saharo-Arabian, Chile-Patagonia, and Novozealandic realms, Fig.  5b, d, f ), the effect of historical climate increased from the Oligocene to the present. This may be because the global climate started to become cooler and dryer since the late Eocene and this trend intensified after the mid-Miocene 31 . Compared with historical climate, geographic isolation has stronger effects on the division between the Gondwanan and Laurasian super-realms (Fig.  5a ), between the Saharo-Arabian and Holarctic realms (Fig.  5b ), between the (Neotropical, Chile-Patagonian) and the (African, Indo-Malesian) realms (Fig.  5e ), and between the (Australian, Novozealandic) realms and other realms of the Gondwanan super-realm (Fig.  5c ). These results suggest that geographic isolation induced by plate tectonics has played a dominant role in the division of these super-realms and realms.

At each time interval of 1 Ma during the last 80 Ma, the partial R 2 of geographic isolation and historical climate are evaluated using hierarchical partitioning model as ln (phylogenetic beta diversity) ~ ln (Climate isolation) + ln (Geographic isolation). Colors of lines represent the independent R 2 of geographic isolation (green) and historical climate (blue) on phylogenetic beta diversity, respectively. The lines and the shaded areas represent the mean ± SE of the R 2 summarized every 5 Ma. a Gondwanan super-realm vs. Laurasian super-realm; b Holarctic realm vs. Saharo-Arabian realm; c (Australian, Novozealandic) realms vs. ((African, Indo-Malesian), (Neotropical, Chile-Patagonian)) realms; d Neotropical realm vs. Chile-Patagonian realm; e (African, Indo-Malesian) realms vs. (Neotropical, Chile-Patagonian) realms; f Australian realm vs. Novozealandic realm and g African realm vs. Indo-Malesian realm. Source data are provided as a Source Data file.

Geological evidence indicates that the ancient Tethys Seaway separated the Gondwana and Laurasia landmasses before the Cenozoic 31 , 37 , which may have led to the dominant effects of geographic isolation on the division between the Laurasian and Gondwanan super-realms (Fig.  5a ) and on the division between the Holarctic and Saharo-Arabian realms (Fig.  5b ). The breakup of Gondwana and the opening of the Atlantic Ocean may have enhanced the effects of geographic isolation on the division between the realms within the Gondwanan super-realm. (Fig.  5c, e, f ). The present-day floras in South America and Africa cannot be distinguished from each other in the Middle Cretaceous (100 Ma, Fig.  2 ), but increasingly diverged from each other since 80 Ma (Fig.  3 ), which is possibly due to the reduced flora exchange caused by the expansion of the Atlantic Ocean as shown by the fossil evidence 29 , 31 . Hence the effect of geographic isolation induced by the expansion of the Atlantic Ocean on the division of the Neotropical and the Chile-Patagonian realms from African and Indo-Malesian realms within the Gondwanan super-realm also increased over time (Fig.  5e ). The northward drift of the Australian plate and the southward drift of the Antarctic plate starting from the late Cretaceous combined with the onset of the Antarctic glaciation in the Oligocene (30–28 Ma) cut off the floristic exchange between Australia and other Gondwana landmasses (i.e., South America and Africa) 31 . This may have led to an increased effect of geographic isolation from the Oligocene to the mid-Miocene on the separation of the Australian and Novozealandic from the African and Indo-Malesian realms (Fig.  5c ). New Zealand drifted away from the ancient Gondwana in the Late Cretaceous (80 Ma) 29 , likely leading to a higher contribution of geographic isolation on the evolution of its flora than historical climate before the Eocene (Fig.  5f ).

Geographic isolation has weaker effects on the division between the Neotropical and the Chile-Patagonian realms than historical climate through geological times (Fig.  5d ). These two realms have been geographically connected during most of the Cenozoic period, which may have led to the weak effects of geographic isolation. Interestingly, neither geographic isolation nor historical climate well explain the division between the African and Indo-Malesian realms (Fig.  5g ). This may be due to biotic interchange between the floras of African and the Indo-Malesian realms. The northward drift of the Indian subcontinent since the early Cenozoic and its final collision with Eurasia brought a large number of floristic elements that are closely related to the African flora to the Indo-Malesian realm 37 , 38 , which may have led to the low explanatory power of both geographic isolation and historical climate on the division between these two realms.

The effects of clade evolution on the division of floristic realms

The clades with high contribution to realm divisions vary among realms. Specifically, we find that younger clades generally have higher contribution than older ones to the division of the (Australian, Novozealandic) realms from the other realms of the Gondwana super-realm (Supplementary Fig.  13c ), the division between the (Neotropical, Chile-Patagonian) and the (African, Indo-Malesian) realms (Supplementary Fig.  13e ), and the division between the African and Indo-Malesian realms (Supplementary Fig.  13g ). This result corroborates the enhanced effect of geographic isolation caused by the breakup of Gondwana on realm divisions (Fig.  5 ). Among major angiosperm clades, malvids, campanulids and lamiids have high contributions to the divisions between African and Indo-Malesian realms ( R 2  > 89.8%), between Neotropical and Chile-Patagonian realms ( R 2  > 38.0%) and between Holarctic and Saharo-Arabian realms ( R 2  > 54.7%), respectively (see Supplementary Data  3 for details). Notably, our study only indicates the contribution of present-day clades to global realm divisions. Further investigations could compare the relative contribution of extinct and present-day clades by integrating contemporary and fossil evidence.

We present the global map of floristic regionalization quantitatively delineated using the distributions and phylogeny of global angiosperm genera. Global lands are divided into two super-realms and eight realms. The boundaries and the hierarchical divisions between the identified realms mostly reflect the effect of geographic isolation induced by plate tectonics over geological times rather than the effect of contemporary and historical climate. These findings together with the high consistency between the boundaries in floristic and zoogeographic realms suggest that geographic isolation during the geological history is likely a common driver for the formation of both floristic and zoological realms. Our global map of floristic realms provides a geographic framework for a wide variety of comparative studies in historical and ecological biogeography, macroecology, and systematics.

A full description of the methods, such as phylogenetic reconstruction, compilation of distribution data, identification of floristic realms and sub-realms, and evaluation on the sensitivity of realm boundaries, is included in the Supporting Methods.

The phylogeny of global angiosperm genera

A genus-level phylogeny for seed plants was constructed using molecular data for 8 gene markers obtained from GenBank (May 19, 2018), including 18S rDNA, ITS (i.e., ITS1, 5.8S ribosomal DNA and ITS2), and 26S rDNA from the nuclear genome; atpB, matK, ndhF and rbcL from the chloroplast genome; and matR from the mitochondrial genome. Sequences from hybrids and taxa with dubious identification were excluded. To construct the genus-level dataset, we first assessed the monophyly of each genus following 51 . For monophyletic genera, one representative sequence per marker per genus (generally the longest one) was selected. For a non-monophyletic genus (totally 593 genera, 4.7%), we only selected species from its core or the largest monophyletic clade. This procedure ensured that we only combined sequences from species belonging to the same monophyletic lineage. Accession number of the sequences that were used in our molecular analyses are available in Supplementary Data  6 .

The genus-level sequences were aligned within each order separately and then merged using MAFFT v7.4 with the most accurate L-INS-i strategy 52 . Phylogenetic analysis were partitioned by RAxML v8.0.26 53 with GTRGAMMA model. We constrained the phylogenetic analyses in RAxML v8.0.26 using the APG IV relationships among angiosperm orders and among eudicots, monocots and magnoliids. The tree was dated with treePL v1.0 54 using fossil calibrations from ref. 55 . As the crown age of angiosperms is still debated 56 , we conducted three dating analyses with different constraints on the age of angiosperm crown: (1) between 149 Ma and 256 Ma following 57 ; (2) between 140 Ma and 210 Ma following 58 ; and (3) between 140 and 150 Ma following 59 . Seed plant genera without sequence data were added to the dated phylogenies as polytomies based on current taxonomy, and then were resolved using the polytomy resolver following 60 . The final molecular and full phylogenies contain 12,539 and 14,244 seed plant genera, respectively. As all results are consistent across the phylogenies, we reported results based on the phylogeny with a constraint of 140–210 Ma for angiosperm crown age, and others in the supplementary materials.

To further explore the potential influence of the fast-evolving genes (particularly ITS1 and ITS2) on phylogenetic topology, we reconstructed the molecular phylogeny using sequence data without ITS and dated it in the same way as previously described. Then we compared it with the phylogeny based on the full sequence dataset and found both the topologies and phylogenetic distances among genera to be highly consistent between the two phylogenies (see supplementary method for details).

Global distributions of angiosperm genera

Geographic distributions of angiosperm species were compiled from >1100 sources, including published regional and local floras, floristic investigations, specimen records and online databases (see Supplementary Data  1 for the full list of data sources). The geographic standard units (hereafter GSUs) used for the compilation of species distributions were generated following 61 , and the average size of GSUs was ca. 4 o longitude × 4 o latitude. After removing small islands (<25,000 km 2 ) and Antarctica, the earth’s landmass was divided into 420 GSUs (see Supplementary Data  2 ). We classified the raw distributional data into four types: coordinates, range maps, gridded distributions, and recorded localities. Depending on the types of the raw data, we applied different methods to reduce spatial conflicts between the original records and the boundaries of the GSUs used in our study and to improve the accuracy of species distributions in the final dataset (see Supplementary Methods for details of these methods). To improve the quality of species distribution data, we set a threshold for the number of data sources to keep an occurrence record of a species in a given GSU. For geographical units in Europe, Australia, China, South Africa, Madagascar and North America, an occurrence record of species in a geographical unit corroborated by at least 3 data sources was retained, leading to high confidence of the data quality in these regions. For the geographical units in Central America, Greenland, Amazon and Turkey, an occurrence record of species in a geographical unit corroborated by at least 2 data sources was retained, leading to medium confidence of the data quality in these regions. The entire data was retained for India, North and Central Africa, and Patagonia because of data deficiency in these regions, leading to relatively low confidence of the data quality in these regions.

The taxonomic status and the accepted names of species from all data sources were standardized following the World Flora Online (WFO, http://www.worldfloraonline.org/ , accessed: December, 2022), Catalog of Life (COL, https://www.catalogueoflife.org/ , accessed: May, 2018), ThePlantList (TPL, http://www.theplantlist.org/ , accessed: Jan 3, 2015) and POWO (accessed: December, 2022). Synonyms are replaced with the accepted names. We kept accepted names with the highest confidence level. Taxonomic names that were identified as ‘unresolved’ in both COL and POWO were removed. The misspelt taxonomic names were corrected using the Taxonomic Name Resolution Service 4.0 (TNRS, https://tnrs.biendata.org/ ), which has been widely used in plant studies.

During data compilation, we also collected the status of species (i.e., being native, cultivated, introduced, invasive and hybrid) from regional data sources as much as we could, and non-native and hybrid species in different regions with clear records were not included in the database. After the compilation of distribution data at species level, we further checked the distribution maps and removed cultivated records from the database following the Plants of the World Online (POWO, https://powo.science.kew.org/ , accessed: May, 2019) and efloras ( http://www.efloras.org/ , accessed: May, 2019).

Finally, we compiled the distributional data for each genus by aggregating distribution data of all its species. The distribution maps of all genera were carefully verified manually to improve data quality. We then integrated the phylogeny and distribution data, and the final distributional database contains 384,771 records for 12,664 angiosperm genera (see Supplementary Data  2 ), representing 90.63% of the total 13,974 accepted genera in POWO 62 .

Taxonomic and phylogenetic beta diversity

Simpson beta diversity 63 was used to evaluate the dissimilarity between species assemblages of GSUs:

where a represents species shared between two GSUs, b and c represent species unique to each GSU. We used this metric because it is not affected by the number of species and provides unbiased estimate of compositional turnover across space 2 , 13 . Using Equ. (1), pairwise matrices of taxonomic beta diversity (calculated using the number of shared ( a ) and unique ( b , c ) species between two GSUs) and phylogenetic beta diversity (calculated based on the length of shared ( a ) and unique ( b , c ) branches of angiosperm phylogenies between two GSUs) were generated separately.

Identification of floristic realms and sensitivity analysis of realm boundaries

Hierarchical clustering analyses were conducted using the “hclust” function in stats (version 3.6.2) package in R 3.6.1 64 to group GSUs into floristic super-realms, realms, and sub-realms. With this method, GSUs with highest similarity (i.e., lowest distance) were first grouped together and then the most similar groups were grouped into clusters. This process was repeated until all GSUs were all grouped into a single cluster. The hierarchical clustering analyses were conducted for taxonomic and phylogenetic beta diversity between the GSUs, separately.

Following Holt et al., 2 we compared the performance and accuracy of different clustering methods. Performance evaluation aims to choose the clustering algorithm that can best represent the floristic divergences with the lowest number of clusters. For each clustering method, we calculated the proportion of beta diversity explained by identified clusters at a certain dendrogram height ( P beta ) as the sum of between-cluster beta diversity divided by the sum of beta diversity between all GSUs 2 . The best performing method was identified as the one returning the minimum number of clusters when P beta reached 99%. Accuracy evaluation aims to choose the clustering algorithm that can represent the floristic divergences with the lowest biases. To do this, the co-phenetic correlation coefficients were calculated for each clustering algorithm using the “cophenetic” function 65 in stats (version 3.6.2) package in R 3.6.1 64 , and the clustering method with the highest accuracy has the highest co-phenetic coefficients.

We found that the “average” method, also known as the Unweighted Pair Group Means Algorithm (UPGMA) performed the best (Supplementary Fig.  14 ). Using the UPGMA, an unrooted dendrogram was generated. Floristic realms and sub-realms were identified by cutting the dendrogram at different heights, which were determined following the approach of 2 . Floristic realms and sub-realms were identified as the clusters required to reach P beta  = 80% and P beta  = 95%, respectively 2 . Then we used the Nonmetric Multidimensional Scaling (NMDS hereafter) to illustrate the relationships between floristic realms in a two-dimension non-hierarchical space.

The GSUs on realm boundaries may contain mixed floristic components, which may lead to soft boundaries 19 , 31 . For comparison with the hierarchical clustering analysis, we redefined the floristic realms using the fuzzy c-means clustering method. Unlike the hierarchical method, which assigns GSUs exclusively to one cluster, the fuzzy c-means clustering method estimates the likelihood of each GSU belonging to a certain cluster, under a given degree of fuzziness 66 . We then conducted silhouette analysis for both results of UPGMA and fuzzy c-means clustering to evaluate the uncertainties in assigning GSUs to a single floristic realm 67 . The identification of floristic realms may also be influenced by uncertainties in phylogenetic topology and incomplete sampling across lineages 24 . Therefore, we repeated the hierarchical clustering analysis using: (1) the single maximum credibility tree; (2) the trees containing only genera with molecular data, (3) randomly sampled post burn-in posterior trees from the polytomy resolver, and (4) trees containing only the genera used in a recent study 24 .

Changes in floristic realms through time

To explore the phylogenetic depth at which the spatial divergence of realms appears, we cut the phylogenetic trees at different geological times and generated the maps of floristic realms at each time following the approach used in refs. 34 , 68 , 69 , 70 , 71 . This approach collapsed all the descendent leaves of each branch encountered at a given time and then identified the floristic realms using the UPGMA clustering method as described above. We then illustrated the changes in the dissimilarity between the floras of different realms by overlaying the NMDS ordinations conducted at different geological times. Note that this analysis did not intend to estimate the ancestral geographic ranges of phylogenetic branches or the ancestral floristic assemblages.

Effects of contemporary climate, historical climate, and geographic isolation on realms divisions

If the contemporary climate dominates the division between floristic realms, contemporary climate should have higher explanatory power on the beta diversity between than within realms. The climate difference of a given pair of GSUs was defined as the Euclidean distance between them in a two-dimensional (i.e., annual mean temperature and precipitation) climatic space. Then we evaluated the effect of contemporary climate on beta diversity between and within realms using Ordinary Least Square (OLS) regressions with phylogenetic beta diversity as the response variable and contemporary climate differences as the predictor.

Following the method in ref. 72 and the reconstructed map in ref. 73 , we produced paleogeographic maps with a spatial resolution of 1 × 1 degree from 80 Ma up to the present in a 1 Ma step. Then, at every geological time, we calculated the geographic isolation between each two grid cells as the minimum total route cost between them, which was a function of geographic distance, separation by ocean, and elevation of the grid cells on the route. The geographic isolation was estimated using the ‘gdistance’ R package (version 1.6) 74 . Paleo-temperature and paleo-precipitation at 1 Ma step from 80 Ma to the present were reconstructed by ref. 72 . We calculated the Pearson correlation of geographic isolation and historical climate differences for each pair of floristic realms from 80 Ma to the present, and then hierarchical partitioning analysis was used to compare the relative effects of geographic isolation and historical climate at each geological time on the division of floristic realms. Specifically, phylogenetic beta diversity between GSUs of two realms was used as the response variable, and geographic isolation and historical climate distances between GSUs were used as the predictors.

Contribution of different clades to floristic realms division

We first detected angiosperm clades whose descendant lineages have little overlap in their geographic distributions, and then measured their contribution to the division of floristic realms as the degree of consistency between the realm boundaries and the geographic divergences of their descendant lineages. Specifically, the geographic divergences of descendant lineages of a clade was evaluated using node-based analysis conducted in the “nodiv” R package (version 1.4.0) 34 . Specifically, this method calculates the degree of mismatch in the geographic distribution of two sister lineages diverging at a given node, i.e., the ‘geographic node divergence’ (GND) score, and the specific overrepresentation scores (SOS) for each geographic unit occupied by the two sister lineages. GND values over 0.65 indicate significant distributional divergence between the two sister lineages. Positive (or negative) SOS values indicate predominance of one of the two descendant lineages in a geographic unit (see Supplementary Fig.  15 ). Using node-based analysis, we detected the clades with GND scores over 0.65 and extracted the SOS scores of all GSUs occupied by these clades. The contribution of each of these clades on the division of two floristic realms was measured by the R 2 of the one-way analysis of variance (ANOVA) with SOS scores as the response variable, and the two realms as the predictor.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. The distribution data can be found in Supplementary Data  2 . The phylogeny and the shapefiles of the floristic realms identified in this paper are available at https://en.geodata.pku.edu.cn/index.php?c=content&a=list&catid=199 (User: flowertree; Password: flowertree). DNA sequence data were downloaded using from GenBank (as of May 19, 2018) and the Accession numbers for DNA sequences can be found in Supplementary Data  6 . Global Administrative Areas boundaries were downloaded from http://www.gadm.org (accessed: May 2016). Distribution data was obtained from both on-line databases and directly from the literature and the complete list of distributional data sources is provided as supplementary data. Species distribution data recorded as locality names were searched in the global geographical names service http://www.geonames.org . The taxonomic status and the accepted names of species from all data sources were standardized following the World Flora Online (WFO, http://www.worldfloraonline.org/ , accessed: December, 2022), Catalog of Life (COL, https://www.catalogueoflife.org/ , accessed: May, 2018), ThePlantList (TPL) available at http://www.theplantlist.org/ (accessed: Jan 3, 2015) and POWO (accessed: December, 2022). Climate data was downloaded from the WorldClim database v2.0 ( https://www.worldclim.org/ , accessed: December, 2022). Paleo-digital elevation models are obtained from Scotese’s paleoatlas 73 . Paleoclimate data are obtained from 72 .  Source data are provided with this paper.

Code availability

All code needed to evaluate the conclusions in the paper can be found in https://github.com/yunpengliu1994/regionalization ( https://doi.org/10.5281/zenodo.7758185 ) 75 .

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Acknowledgements

This work was supported by the National Key Research Development Program of China (#2022YFF0802300), National Natural Science Foundation of China (#31988102, #32125026, #31770566), and the Strategic Priority Research Program of Chinese Academy of Sciences (#XDB31000000). D.D received additional support by the Norwegian Metacenter for Computational Science (NOTUR; project NN9601K). MKB, CR and YL acknowledge the Danish National Research Foundation (DNRF96) and VILLUM FONDEN (25925) for support of the Center for Macroecology, Evolution and Climate.

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These authors contributed equally: Yunpeng Liu, Xiaoting Xu, Dimitar Dimitrov.

Authors and Affiliations

Institute of Ecology, College of Urban and Environmental Sciences, and Key Laboratory of Earth Surface Processes of Ministry of Education, Peking University, 100871, Beijing, China

Yunpeng Liu, Xiaoting Xu, Nawal Shrestha, Xiangyan Su, Ao Luo, Carsten Rahbek & Zhiheng Wang

Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Universitetsparken 15, 2100, Copenhagen Ø, Denmark

Yunpeng Liu, Michael K. Borregaard & Carsten Rahbek

Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, 610065, Chengdu, Sichuan, China

• Xiaoting Xu

Department of Natural History, University Museum of Bergen, University of Bergen, Postbox 7800, 5020, Bergen, Norway

• Dimitar Dimitrov

Landscape Ecology, Institute of Terrestrial Ecosystems, ETH Zurich, 8092, Zurich, Switzerland

Loic Pellissier

Swiss Federal Research Institute WSL, 8903, Birmensdorf, Switzerland

Loic Pellissier & Niklaus E. Zimmermann

State Key Laboratory of Grassland Agro-ecosystems, Institute of Innovation Ecology, Lanzhou University, 730000, Lanzhou, China

Nawal Shrestha

Land Consolidations and Rehabilitation Center, Ministry of Natural Resources, 100035, Beijing, China

Xiangyan Su

Center for Global Mountain Biodiversity, GLOBE Institute, University of Copenhagen, Universitetsparken 15, 2100, Copenhagen, Denmark

Carsten Rahbek

Danish Institute for Advanced Study, University of Southern Denmark, 5230, Odense M, Denmark

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Contributions

Z.W., C.R., and Y.L. conceived the idea; Z.W. Y.L., X.X., X.S., and A.L. constructed the distribution dataset; Z.W., X.X., and D.D. conducted the phylogeny; L.P. and N.Z. conducted the palaeogeographical and paleoclimate data; Y.L. and M.B. conducted the node-based analysis; Y.L. and N.S. generated the figures in the manuscript; Y.L. led the analysis and writing, and all authors contributed to the writing.

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Correspondence to Carsten Rahbek or Zhiheng Wang .

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Liu, Y., Xu, X., Dimitrov, D. et al. An updated floristic map of the world. Nat Commun 14 , 2990 (2023). https://doi.org/10.1038/s41467-023-38375-y

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• 4 Department of Botany, University of Okara, Okara, Pakistan
• 5 Department of Botany, Institute of Life Sciences, State Museum of Natural History, Karlsruhe, Germany
• 6 Department of Food Industries, Faculty of Agriculture, Damietta University, Damietta, Egypt
• 7 Department of Plant Production, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia

Introduction: Scientific documentation of the qualitative forest vegetation parameters of a biogeographical area provides baseline information to guide conservation strategies and design policies for biodiversity management regulations.

Methods: We present one of the most comprehensive qualitative vegetation analyses to evaluate the entire structure and function of an ecosystem in the remote northern part of the Kashmir Himalaya, India. Several multivariate ecological community analyses were conducted after determining the presence of plant species in the various habitats using a random sampling technique.

Results: In total, 155 plant species belonging to 120 genera and 49 families occurred in the area. Asteraceae was the largest family (12% of plant species) followed by Rosaceae (11%). The patterns of species distribution across families were uneven, with 50% of the species belonging to only 7 families, and 23 families being monotypic. In terms of functional groups, the herbaceous growth form dominated. Therophytes were the dominant life form, indicating that the vegetation was disturbed. According to the phytogeographical research, 65% of the species documented in the study area were native, 15% were invasive, 14% naturalized, and 5% being casual. The majority (30%) of exotic species were reported along roadsides. Of all the species found, 39% grew in their natural habitats, such as forests, and 11% were scattered along roadsides. Plant species were grouped in five different clusters based on their floristic similarity. According to the estimated diversity indices, natural forest has the greatest values for Shannon’s and Simpson’s index. We found that the study area serves as the natural habitat for several significant, endangered medicinal plants, including Arnebia benthamii, Bergenia ciliata, Delphinium roylei, Gentiana kurroo, Phytolacca acinosa, Saussurea costus , and Trillium govanianum . Therefore, we recommend that human intervention in natural regeneration efforts be prioritized in these habitats to increase the population of these species.

Conclusion: Examining species features from the perspective of functional groups contributes to our understanding of the ecological aspects of the flora. It may also be useful in developing management plans to ensure long-term management of forest landscapes in this remote Himalayan region.

Introduction

Floristic diversity is an important element of ecosystems ( Hua et al., 2022 ). This diversity includes the plant species diversity of a particular area representing the local flora of a given area ( Qian et al., 2021 ). Taxonomy is concerned with their identification and classification of species ( Barkley et al., 2004 ). Floristic and taxonomic studies provide efficient information about different aspects of an ecosystem, including nomenclature, distribution, ecology and utility of plant species of an area ( Grime et al., 2014 ; Haq et al., 2022d ). While information on plants of many regions has long been available online via checklists ( Safidkon et al., 2003 ), comprehensive floristic studies are still necessary to document the whole plant diversity of any geographic region ( Noss, 1983 ). Lack of such studies strongly limits the scientific inquiry into plants ( Kier et al., 2005 ), and is needed to ultimately understand how plant communities are structured and distributed.

Among the various ecological attributes of plant communities, floristic composition and ecological diversity are the most important ones that are influenced by a variety of biotic and abiotic factors ( Khan et al., 2018 ; Solefack et al., 2018 ). The understanding of linkages among plants diversity and its ecological functions is critical for understanding the adjustment of plant communities, and how they adopt toward specific habitats ( Rahman et al., 2019a ; Altaf et al., 2022 ). Lifeform and habit are the two important physiognomic features that are being widely used while investigating vegetation ( Haq et al., 2019 ). Studying functional plant traits of a given region is an important tool that helps in understanding the relationship between environmental variables and plant community structure and distribution, ultimately revealing the biological functions of individual species in a community ( Vakhlamova et al., 2016 ).

The Himalayan Mountain Range is a prominent biogeographic ecoregion that shows great variation in topography and climate, and thus harbors significant plant diversity ( Olson et al., 2001 ). This mountain ecosystem has been recognized as a global biodiversity hotspot due to its significant biodiversity and huge endemism ( Myers et al., 2000 ). The Kashmir Himalaya, part of Indian Himalayan Region, has been considered as a promising floristic region with high endemism ( Mahar et al., 2009 ). Nonetheless, many remote areas of this biodiversity-rich region have not received much attention as far as floristic and ecological investigations are concerned, which is especially the case of remote mountains region in Kashmir Himalayas. The capability and productivity of the Himalayan forest ecosystem have decreased as a result of numerous stressors, including anthropogenic factors (such as over-exploitation of forest resources and the spread of invasive species), environmental (climate, slope, soil), fire incidences, and declining biological diversity ( Haq et al., 2020 ). Floristic and ecological studies are crucial to advancing our understanding of the distribution and composition of plant communities in biodiversity hotspots. It is crucial and most effective to record qualitative forest vegetation parameters in order to preserve floristic diversity in the future and utilize biological resources sustainably. Keeping this in view, we focused on the following objectives: (i) to record the floristic composition of the vegetation in the region. (ii) What are the patterns of the emergent ecological traits groups in the flora in this region (iii) to find out the contribution of native and alien elements in the region vegetation and (iv) to find out the forest species pool shows habitat filtering in the region.

Given the ecological and economic significance of the forest vegetation under consideration, the findings of this study can guide sustainable biodiversity management and habitat restoration, particularly in invaded habitats in this Himalayan region, with global implications.

Materials and methods

Research area.

The study area one of the remotest Tehsil of District Bandipore, Jammu and Kashmir, India. The Gurez valley is situated in the high-altitude Kashmir Himalaya, about 86 kms from Bandipore and 146 kms from the regions summer capital (Srinagar) ( Figure 1 ). The Gurez valley is at an altitude of ranges from 2,400 to 3,500 masl and is mostly inhabited by Pahari and Gujjar tribes. The study area includes fifteen Panchayats (village administrative units) with about 30,000 inhabitants. Dawar is known as the main town in the area. Due to heavy snowfall (approx. 1.5–1.8 m), the area remains disconnected from the rest of the region for about 6 months a year, as Razdan Pass is completely closed in the winter. It has a dry and mild climate. The valley is vital for wildlife tourism because it is surrounded by high mountains and steep gorges that are drained by the Kishanganga River. It also supports a variety of vegetation, dense forests, and a wealth of species.

Figure 1. Map of study area (A) India (B) Jammu and Kashmir (C) Bandipora district and point showing the Gurez Valley in the Kashmir Himalaya, India (generated using ArcGIS version,10.5).

Field survey

Frequent surveys were conducted to obtain a better understanding of the research area and field data were collected during in various expeditions 2019–2021. Sites for the floristic studies were chosen using a random sampling technique to guarantee that plant species from various habitats had an equal chance of being sampled. The quadrat method was used to record floristic composition and functional characteristics to improve vegetation documentation ( Haq et al., 2020 ). We set up 36 0.1 ha plots for field sampling across different habitats in the study area. Within each 0.1 ha plot, two 5 m 2 plots were placed in opposite corners estimate shrub diversity. For the herbaceous layer, 5 plots of size 1 m 2 were laid (4 in each corner 0.1 ha plot and one in the center). In total, 32 plots for trees, 64 (2 plots × 32 = 64) plots for shrubs and 160 (5 plots × 32 = 160) plots for herbs were sampled in the present study. Field data about each specimen of plant material was meticulously recorded during field studies. In order to serve as herbarium voucher specimens, plant specimens were collected from the field, identified using taxonomic literature, and then authenticated by comparing the plant specimens with material in the KASH herbarium. Ecological traits (like Raunkiaer’s life-form, plant habit, phyto-geographical, life span) of each species were recorded during sampling, following Raunkiaer (1934) , and Pérez-Harguindeguy et al. (2016) . Furthermore, habitat characteristics of each plant species were categorized as Dry slope (DS), Moist places (MP), Natural forest (FR), Shady places (SP), Riparian vegetation (RV), Rock crevice (RC), Roadside (RS), Crop fields (CF), Vegetable garden (VG) ( Plate 1 ). The range of native phyto-geographically reported plant specimens was acquired by using secondary sources like manuals, Flora and specified internet web pages (GRIN: Germplasm Resource Information Network). 1 Based on the available data, all plant specimens were categorized into native and exotic species.

Plate 1. Representation of different habitats in the study area.

Data analysis

To investigate the relationships between ecological variables and plant compositions, heat map and clustering analysis were employed ( Rahman et al., 2019a ; Haq et al., 2021d ). The heat map displayed the distribution of species using presence/absence data, and the clustering algorithm grouped species with similar habitat categories. The Sørensen (1948) similarity coefficient based on presence/absence data was used to identify significant differences among different habitat types and microclimatic similarities ( Dalirsefat et al., 2009 ). In order to identify hypothetical variables (components) that explain the majority of the variance in our multidimensional data, Non-Metric Multidimensional Scaling (NMDS) was utilized. The contribution of various Raunkiaer’s life forms was visualized using chord diagrams generated with the circlize package ( Gu et al., 2014 ). Subsequently, we computed three diversity indices, namely, species richness, Shannon and Simpson, based on presence/absence of species for all habitats, and all plots and analyses were performed using R software version 4.0.0 ( R Core Team, 2020 ).

Floristic composition and distribution

Based on the present investigation, 155 plant species from 120 genera and 49 families were reported in the current study area ( Table 1 ). The distribution of the species among the 49 families was unequal; just 7 families held half of the species, while 42 families held the other half. 23 families were monotypic ( Figure 2 ). The top five plant families were Asteraceae (19 species, or 12% of all species), Rosaceae (17 species, or 11% of all species), Lamiaceae (15 species, or 10%), Ranunculaceae (10 species, or 6%), and Apiaceae (8 species, or 5%) ( Table 1 ).

Table 1. Floristic composition and life span traits of the forest vegetation in Gurez Valley of Kashmir Himalaya, India.

Figure 2. Species- family relationship of documented species in the study area.

Species distribution among growth form types

In the current study, the highest number of plant species (111) were herbaceous plants (72% of all species), followed by 21 tree species (13%), 15 shrubs (10%), four climbers (3%), and four sub-shrubs (2%) ( Table 1 ). Most of the tree species growing in the valley were deciduous (e.g., Aesculus indica, Acer caesium, Betula utilis, Celtis australis, Prunus armeniaca , Prunus cornuta, Populus nigra, and Ulmus villosa ). A few coniferous tree species (e.g., Abies pindrow, Cedrus deodara, Picea smithiana, Pinus wallichiana , and Taxus wallichiana ) were also reported. Shrubs included Rosa webbiana, Berberis lyceum, Rubus ulmifolius, Parrotiopsis jacquemontiana, and Indigofera heterantha. Important medicinal herbs reported from the valley were Ajuga parviflora, Bergenia ciliate, Delphinium roylei, Gentiana kurroo, Heracleum candicans, Phytolacca acinosa, Saussurea costus , Taraxacum officinale , and Trillium govanianum ( Table 1 ). The representative plants species documented in the different habitats of the study area are shown in Plate 2 .

Plate 2. Representative plant species growing in different habitats of the study area.

Species distribution among life-form traits

About 35% of the species (54 species) were therophytes which constituted the dominant life form, followed by 29 species of hemicryptophytes (19%), chamaephytes and geophytes with 15 species each (10%), megaphanerophytes with 13 species (8%), nanophanerophytes with 12 species (8%), cryptophytes and mesophanerophytes with 7 species each (4%), microphanerophytes with 2 species (1%), and parasitic forms with a single species (1%) ( Figure 3 ). Majority of the plant species (129) in the studied valley were represented by perennials (83%) followed by annuals with 23 species (15%), and biennials with three species (2%). According to the phyto-geographical research, 65% of the species documented in the study area were native, with the remaining 15% being invasive, 14% being naturalized, and 5% being casual ( Figure 4 and Table 1 ). The majority (30%) of exotic species were reported on the roadside, followed by natural forests (23%), crop fields (17%), dry slopes (16%), shady areas (5%), moist places, and riparian zones (4% each).

Figure 3. Plant species distribution according to Raunkiaer’s life form of the vegetation in Gurez valley, Kashmir Himalaya, India.

Figure 4. Plant species distribution according to nativity range of the vegetation in Gurez valley, Kashmir Himalaya, India.

Habitat-wise distribution

Of all species encountered 39% grew in the natural forests, 17% on dry slopes, 11% in shady places, 10% in moist places, 2% in riparian zones, 3% in rock crevices, and the remaining species were dispersed in highly distributed habitats, e.g., 11% along roadsides, 6% in crop fields, and 1% in vegetables gardens ( Table 1 and Plate 2 ). Based on their floristic similarity, cluster analysis identified five clusters of various habitat types ( Figure 5 ). Natural forests made up the first cluster, dry slopes and roadside vegetation made up the second, wet and shady areas made up the third, crop fields and vegetable gardens made up the fourth, and riparian vegetation and rock crevices made up the fifth ( Figure 5 ).

Figure 5. Heat map based on Sørensen’s (1948) similarity index of plant species in Gurez valley, Kashmir Himalaya, India.

Similar to this, the NMDS revealed significant variation in habitat types, with some species groups having a stronger association with particular habitat types than others ( Figure 6 ). In the biplot, five clusters of habitats based on species presence/absence can be identified: dry slope; natural forest; roadside; moist places and rocky crevice; and crop fields, riparian vegetation, shady places, and vegetable gardens. The major plant species richness was detected in rich and optimally moisturized natural forest habitats and middle richness in moist places as well as less distributed habitations.

Figure 6. Non-Metric Multidimensional Scaling (NMDS) (plot of different habitat types in Gurez valley, Kashmir Himalaya, India. Full name of habitat is depicted in Table 1 .

According to the estimated diversity indices, Natural forest had the greatest values for all three indices ( Table 2 ). Shannon’s index for this habitat was 4.73, and Simpson’s was 0.99. There were 113 species present. After that, Dry slope and Shady areas held 46 and 31 specie (3.83 and 3.43 for Shannon index, and 0.98 and 0.97 for Simpson index, respectively) ( Table 2 ) lowest values were recorded for Rock crevice and Vegetable garden ( Table 2 ).

Table 2. Variation of diversity indices between habitat types in Gurez valley, Kashmir Himalaya, India.

In this study, we provide an in-depth evaluation of the qualitative vegetation of remote region of Kashmir Himalaya. The study revealed (i) 155 plant species belonging to 120 genera and 49 families, with (ii) an uneven distribution within families, with 50% of the species belonging to just 7 families and 23 families being monotypic. (iii) Therophytes were the most prevalent form of life, showing that the vegetation was disturbed (iv) Exotic species made up the remaining 35% and most exotic plants were found along roadsides. Finally, (v) natural forests scored the highest values for all three estimated diversity indices, compared to other human-modified habitats. Vegetation analysis helps to develop a comprehensive image of the plant communities of a particular region ( Chhetri and Shrestha, 2019 ). Assessing the floristic diversity of hotspots of biodiversity is essential to understand the conservation status of these areas, which have a significant role in making the conservation strategies as well as policies. The vegetation of region was found to be very diverse due to ecological zonation, different microhabitats, and topographic features. 49 families and 155 species were found in the current investigation. In comparison to past studies conducted in other Himalayan locations ( Qureshi and Bhatti, 2010 ; Semwal et al., 2010 ; Shaheen and Qureshi, 2011 ; Dangwal et al., 2012 ; Singh and Rawat, 2012 ) the number of plant species recorded in the current research area was higher. Numerous interrelated factors, including elevation, regional climate, topography, competition, regional species pool, regional species dynamics, and human activity have an impact on the regional patterns of species richness ( Rahman et al., 2020 ; Mitchell et al., 2023 ). However, Khan et al. (2012) reported a higher number of plant species (198) from the Naran valley forest of Pakistan Himalaya but distributed in a lower number of families (68) when compared to our study. Similarly, Verma and Kapoor (2011) reported 160 vascular plant species belongs to 51 families from Ropa-Giavung valley in the cold deserts of District Kinnaur, Himachal Pradesh, India (also see Manzoor et al., 2016 ; Haq et al., 2022d ; Ullah et al., 2022 ). However, at the region level the species richness of our study was comparatively higher than report in previous studies from Kashmir Himalayas ( Bhat et al., 2014 ). Thus, the slight but predictable fluctuation in species number might be attributed to both abiotic environmental and biotic causes. Apart from elevation, microhabitats that reflect or predict vegetation patterns across landscapes. Together with the previously described findings, our findings demonstrate that while various studies have analyzed the floristic composition of the Himalayan region, each micro-region has unique functional groups that can significantly affect the structuring of the local plant community. Our study showed a smaller number of species than several other studies, but had a larger number of families, which may also represent an important result for the analysis of biodiversity in these regions. Asteraceae, Rosaceae, Lamiaceae, Ranunculaceae, and Apiaceae were reported as the families with the largest number of plant species. Due to wide range of ecological amplitudes, the plant species of Asteraceae are varied in habitats ( Rahman et al., 2019a ; Rashid et al., 2021 ; Waheed et al., 2022 ). Similar findings were observed by Haq et al. (2021d) in Kashmir Himalaya, India and Rahman et al. (2018) in Manoor valley, Pakistan. Many researchers have reported Asteraceae as the dominant family from different regions ( Verma and Kapoor, 2011 ; Hussain et al., 2015 ; Ali et al., 2016 ; Amjad et al., 2017 ; Khan et al., 2018 ; Rahman et al., 2019a ). This demonstrates the family’s strong capacity for adaptation to a variety of environments and temperatures. Additionally, in agreement with our findings, two other studies— Suyal et al. (2010) in the Garhwal Himalaya, India, and Khan et al. (2015) in Kabal (Swat), Pakistan—reported Lamiaceae as the dominant family.

The current study emphasizes the uneven distribution of plant species throughout families, with 23 families being identified as monotypic. The large variety of families, which revealed a varied distribution of flora in the area, is explained by variances in microhabitat, morphological features, life duration, and dynamic ecological niche ( Haq et al., 2022a ; Khoja et al., 2022 ). The diversity and structure of these plant communities can be influenced by various abiotic and biotic factors, which has also been shown by earlier research in the Western Himalayan region, and some species and/or families may not be as able to inhabit particular habitats as others ( Rahman et al., 2018 ). The growth form of trees had higher proportion (13%) than shrubs (10%), an expression of a functioning forest ecosystem ( Khan et al., 2015 ). The present results agreed with Khan et al. (2015) , who found that a large diversity of microhabitats was favorable to tree species in the region. The findings of Sharma and Raina (2018) from other Himalayan forests further support these findings. Herbaceous species (111) were the dominant habit similar to other areas of the Northwestern Himalaya ( Dar and Sundarapandian, 2016 ; Rahman et al., 2019b ; Haq et al., 2021a ; Nafeesa et al., 2021 ). Previous research in the Western Himalayan region has shown that certain species and/or families rarely have the same ability to occupy specific habitats as others, where varied abiotic and biotic effects can alter the diversity and organization of these plant communities ( Haq et al., 2021b ; Nafeesa et al., 2021 ).

It has been observed that the most promising approaches for predicting the species composition of any forest communities revolves around their functional traits. Therefore, studying functional groups usually provides clear information on the direct physiological adaptations of plant communities to particular environments conditions ( Haq et al., 2019 ). The most common life form class were therophytes, followed by hemicryptophytes, magaphanerophytes, chamaephytes, and geophytes. Such biological variety represents the adaptation of plant species to the climatic factors ( Khan et al., 2018 ). Hemi-cryptophytes predominate in the study area due to the cold and mountainous climate. In general, they withstand water scarcity by remaining dry or developing physiological, morphological, and anatomical traits that allow them to tolerate water loss. The fact that therophytes were found as the dominant life form in the studied area, which indicates high biotic disturbance levels on the habitat via grazing, human settlements, agricultural practices, and road constructions, since this life form is commonly associated with the unfavorable dry environmental condition, resulting in adopted strategies for their survival ( Vakhlamova et al., 2016 ). The current findings agreed with Asim et al. (2016) , Rahman et al. (2018 , 2019b ), Wali et al. (2022) who also documented the dominance of therophytes in the respective research areas. The high biotic disturbance significantly alters composition of the herbaceous layer and favored the abundant growth of alien annual weedy species such as such as Anthemis cotula, Amaranthus caudatus, Centaurea iberica, Datura stramonium , and Galinsoga parviflora , all of which are therophytes ( Haq et al., 2021d ). The second most prevalent type of life was hemicryptophytes. The association of hemicryptophytes with a cold, mountainous climate is a likely explanation for their predominance ( Shimwell, 1971 ). Because of the soil and climate in the subalpine zones, chamaephytes are more common ( Khan et al., 2018 ). Some habitats are more suited to plant development than others based on the diversity of species found in the forest environments of different geographic regions ( Medvecká et al., 2018 ). Comparing natural forest habitats to other types of habitat, the current study found that natural forest environments harbored the highest diversity of species. However, anthropogenic disturbances are fragmenting, destroying, and degrading natural forest habitats, which is affecting the composition and layout of forest communities including in this area of the Himalayan region ( Chakraborty et al., 2017 ; Rahman et al., 2022 ). Qureshi and Bhatti (2010) , who recorded the highest number of plant species in natural forest habitats from Pakistan, provide additional support for our findings. Moreover, the resemblance in the plant species pool in human modified habitats provides an evidence toward the indication of ecological filtration that occurs in the region ( Gardner et al., 2009 ). Anthropogenic disturbances common in this Himalayan region include overgrazing, deforestation, over-exploitation and fragmentation of natural intact forests due to linear development such as road networks and transmission lines ( Haq et al., 2022b ). Out of the total reported plant species, 35% were exotic, mostly in human modified habitats. Such numbers are comparable with those documented by Kohli et al. (2004) from the forests of Himachal Pradesh of Indian Himalayas. The most common invasive species growing in forest ecosystems of Jammu and Kashmir included trees like Aesculus indica, Ailanthus altissima, Juglans regia, Populus ciliate , subshrub Sambucus wightiana , and herbs such as Anthemis cotula, Amaranthus caudatus, Centaurea iberica and Datura stramonium ( Haq et al., 2019 , 2023b ). The invasion of plant species is typically facilitated by disturbance because it overwhelms environmental and physical barriers. The parameters that cause the disturbances have been seen to be able to filter the makeup of a community and affect species concurrence by altering resource and safe spot availability ( Davis et al., 2000 ; Haq et al., 2022c , 2023a ). Generally, those species having wide niches and can pass via these filters and likely to overrun newly ecosystems after these are disturbed ( Dukes and Mooney, 1999 ). Furthermore, invasions of exotics into forests might be facilitated by the incursion of other plant species generating conditions that encourage other invasive plant species over native species ( Niu et al., 2007 ). When alien species invade a newly range, innate plant species, adaptation to the new environment, is sometimes evacuated ( van Boheemen et al., 2019 ). The vegetation composition variations rise via a variety of procedure sensuing the disappearance of the diversity of plant species such as communities change from native desired plant species to monospecific positions of the invasive plant species ( Pérez-Ramos et al., 2019 ; Haq et al., 2021c ). Invasive species have broad consequences in affecting potential management to decrease the effects of climate changes ( Kraft et al., 2015 ).

Implications for forest management and policy

According to our findings, 35% of plant species were deemed to be alien, indicating that a large number of non-native species have spread to the inaccessible and isolated Himalaya region. We discovered a high percentage of exotic species (such as Aesculus indica, Ailanthus altissima, Sambucus wightiana, Anthemis cotula, Amaranthus caudatus, Centaurea iberica , and Datura stramonium ) in disturbed forest habitats such as roadsides, and we propose that tunnels, rather than roads, are the best opinions of connectivity in fragile mountain ecosystems. The elements that threaten biodiversity must be minimized in order to keep ecosystems operating and their members intact. Regulations that limit alien species like Anthemis cotula, Artemisia absinthium, Bupleurum falcatum, Cuscuta reflexa, Galinsoga parviflora, and Senecio chrysanthemoides , introductions, and boost recovery, such as modifying structure through enhanced species regeneration and planting native species ( Abies pindrow , Cedrus deodara , Pinus roxburghii, P. wallichiana, Taxus wallichiana, Betula utilis, Ulmus villosa, Trillium govanianum, Ajuga parviflora ). We found that the study area serves as the natural habitat for several significant, endangered medicinal plants, including Arnebia benthamii, Bergenia ciliata, Delphinium roylei, Gentiana kurroo, Phytolacca acinosa, Saussurea costus , and Trillium govanianum . Therefore, we recommend that human intervention in natural regeneration efforts be prioritized in these habitats to increase the population of these species. Finally, existing knowledge of threats to the forest flora can be used to guide management in the face of future climate change. The forest management strategy could be organized so that potential hazards (like forest fragmentation, invasion of exotic species) are addressed before they become a problem. Furthermore, the majority of species recovery initiatives should focus on managing forest restoration in human modified habitats through by planting and reseeding native species like, Ulmus villosa, Betula utilis, Aconitum heterophyllum, Trillium govanianum, Fritillaria roylei, Arnebia benthamii , to lessen susceptibility to future threats in the landscape.

The identification of areas with a high value for biodiversity and the prioritization of these areas for conservation are crucial for preserving biodiversity. The present investigation described qualitative vegetation characteristics in a remote region of the Kashmir Himalaya. The dominance of few families, especially the Asteraceae, is a result of actual and potential dominating invaders in zones with significant disturbance. Therophytes emerged to be the primary form of life in the research area. The presence of a large fraction of therophytes indicates major anthropogenic disruptions. The study examined how environmental factors affect plant communities and placed special emphasis on the idea of habitat filtration as it relates to plant species’ abiotic tolerance. Furthermore, by examining species features from a functional groups standpoint, it may be possible to predict an ecosystem functionality more accurately. The study’s findings suggest that decision-makers and planners should place a greater emphasis on ecologically sustainable development in forest landscapes, considering species composition and the preservation of ecosystem function. Similar approaches should undoubtedly ensure that development activities do not contribute to biodiversity loss in fragile ecosystems.

Data availability statement

The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author contributions

SH, FL, and AK collected the data. SH and MW analyzed and interpreted the data and results. SH wrote initial draft of the manuscript. SH, RB, EM, HE, and FL revised the manuscript. All authors read and approved the final manuscript.

This study was Researchers Supporting Project (RSP2023R118), King Saud University.

Acknowledgments

We would like to thank Researchers Supporting Project number (RSP2023R118), King Saud University, Riyadh, Saudi Arabia.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : plant invasion, habitat diversity, hotspots of biodiversity, ecological traits, Kashmir Himalaya

Citation: Haq SM, Khoja AA, Lone FA, Waheed M, Bussmann RW, Mahmoud EA and Elansary HO (2023) Floristic composition, life history traits and phytogeographic distribution of forest vegetation in the Western Himalaya. Front. For. Glob. Change 6:1169085. doi: 10.3389/ffgc.2023.1169085

Received: 18 February 2023; Accepted: 15 May 2023; Published: 02 June 2023.

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Copyright © 2023 Haq, Khoja, Lone, Waheed, Bussmann, Mahmoud and Elansary. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Shiekh Marifatul Haq, [email protected] ; Hosam O. Elansary, [email protected]

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Forest Ecosystems in Mountain Regions: Conditions, Risks and Impacts

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Biodiv Sci ›› 2017 , Vol. 25 ›› Issue (2) : 111-122.  DOI: 10.17520/biods.2016253

• Review • Previous Articles     Next Articles

Current research and development trends in floristic geography

• 1 Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201 2 University of Chinese Academy of Sciences, Beijing 100049
• Received: 2016-09-20 Accepted: 2016-11-07 Online: 2017-02-20 Published: 2017-03-06
• Contact: Sun Hang

• 1. 探讨2016版国际胰瘘研究小组定义和分级系统对胰腺术后患者胰瘘分级的影响.PDF (500KB)

This paper summarizes the research status, existing issues, and trends in floristic geography. There is now a wealth of research accumulation on floristic investigations, distribution types of genera, floristic regions, and regional floristic analysis. It is also noted that most of these studies utilize simple statistical analyses, comparative studies, traditional methods, and single subjects, to provide a basic understanding and description of the floristic phenomenon, which is lacking spatial pattern formation processes and detailed exploration of formation mechanisms. Additionally, there are still some weak and non-existent areas of botanical investigation. Many existing specimens lack detailed or accurate information and the precise identification of plant species also needs to be much improved. At the same time, when analyzing the development trends of floristic geography, with the rapid development of related disciplines, including the development of biogeography and analysis methods and improvements, floristic geography research is an area of multidisciplinary integration, comprehensive research, and analysis. On the one hand, using database information, and combining ecology, paleobotany, and geology can allow us to probe into spatial pattern formation. On the other hand, combining phylogenetics, the tree of life, and molecular biogeography allow us to reveal floristic origins and evolution. The rapid development of various disciplines has given rise to a large amount of data, meanwhile, the emergence and application of new analytical methods and theories incorporate big data into floristic geography research, which will enhance qualitative understanding and description, and allow us to further explore the mechanisms of formation quantitatively.

Key words: floristic geography, floristic investigation, comprehensive research, ecology, molecular phylogenetics, biogeography, big data

Cite this article

Hang Sun, Tao Deng, Yongsheng Chen, Zhuo Zhou. Current research and development trends in floristic geography[J]. Biodiv Sci, 2017, 25(2): 111-122.

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Floristic Diversity of India: An Overview

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The present chapter gives a synthesis of the floristic diversity of India, dwelling briefly on its ecosystem diversity, vegetation pattern, species richness in various taxonomic groups traditionally dealt with as plants (angiosperms, gymnosperms, pteridophytes, bryophytes, algae, fungi and lichens), endemism and primitive angiosperms and phytogeographical analysis of the flora. It is estimated that out of 49,003 species of plants forming the evident vegetal cover, angiosperms comprise ca. 18,532 species, representing ca. 10% of all known flowering plants of the world. The largest angiosperm family in the number of species is Leguminosae (with 1421 spp.), followed by Poaceae (1291spp.), Orchidaceae (1251 spp.), Asteraceae (1120 spp.) and Rubiaceae (679 spp.). The largest genus is Impatiens (with 279 spp.), followed by Carex (160 spp.), Pedicularis (145 spp.), Bulbophyllum and Primula (135 spp. each). Existing estimate pertaining to the political boundaries of present-day India is that about 4300 (23.20%) of 18,532 flowering plant species are endemic to this country.

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Acknowledgements

A review paper encompassing such an extensive canvas of literature could not have been possible without help from within Botanical Survey of India and various universities and institutes. I thank the staff of Botanical Survey of India, particularly different subject experts, for helping in collating the information on different groups of plants.

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Anzar A. Khuroo

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Singh, P. (2020). Floristic Diversity of India: An Overview. In: Dar, G., Khuroo, A. (eds) Biodiversity of the Himalaya: Jammu and Kashmir State . Topics in Biodiversity and Conservation, vol 18. Springer, Singapore. https://doi.org/10.1007/978-981-32-9174-4_3

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