Horizontal Distribution Pattern: A Phorophyte Dependant Spatial Trend of Epiphytic Fern in a Greenbelt Corridor Using Geospatial Techniques

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Edwin-Wosu, N.L. , Ahanonu, C.M.

Department of Plant Science and Biotechnology, Faculty of Science, University of Port Harcourt, Choba, PMB 5323, Rivers State, Nigeria

Corresponding Author Email: nsirim.edwin-wosu@uniport.edu.ng

DOI : https://doi.org/10.51470/JPB.2026.5.2.01

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1.0       INTRODUCTION

The inquiry in the study of arboreal epiphytic fern has proven to be the basis and foundation for comprehending the nature and biology of vascular plants, in light of their ecological importance in both tropical and temperate regions. And their ability to control the potential regeneration of forest ecosystems [1, 2, 3]. They are regarded as “Islands” that grow on tree canopies and are highly sensitive to forest disturbance and obstructions [4, 5]. They are mostly herbaceous in nature and with a substantial water storage capacity; thus tend to influence the hydrology and energy flow in phorophyte canopies [6,7]. The presence, growth, and development of these epiphytic ferns influence the uptake of carbon and biomass production while serving as a microhabitat, source of food and medicine, and tree canopy nutrient cycling [8, 9, 10]. Arboreal epiphytic ferns have a great influence on biodiversity because of their great significance in contributing to plant diversity, with about 25% of their vascular nature observed in tropical forests [11].

The horizontal distribution of arboreal epiphytic ferns entails the horizontal spread of epiphytic species across a given area; such distribution is irregular as a result of ecological and abiotic environmental (sunlight, precipitation, etc) gradients [12]. Though the complexity in epiphytic fern distribution lies in their degree of arboreal lifestyle dependence, their specialized tissues and organs, which make it possible for their adaptation [13]; their distribution pattern is influenced by the forest structure, which involves the phorophyte height and type, species distribution, epiphytic density, and disturbances such as tree felling [14, 11, 15, 16, 17]. It has been highlighted that the ecology of epiphytic ferns is poorly harnessed despite their importance in biodiversity protection [18]. Arboreal epiphytic ferns are known to be seen on different substrates, showing distinct and different responses to environmental and ecological factors [19]. Arboreal epiphytic ferns like the Platycerium species have shown one of the greatest microclimate functions in retaining and maintaining the amount of moisture in tree canopies [20] while serving as a cool buffering microhabitat to relatively hot and dry greenbelt canopies [21].

Greenbelt canopy, an aggregate of tree crowns of vegetation stand, is known for it habitation system, supporting diverse organisms ranging from insects to plant species, including arboreal epiphytic ferns [22]. The use of randomness and deterministic approaches is highly crucial in the study of the canopies in rainforest communities [23]. The differences in the distribution of arboreal epiphytic ferns on a greenbelt canopy lie in the chance and limitations of their dispersal in different areas under different environmental gradients and canopy assemblages [19]. The phyto-social attributes of these epiphytic ferns have defined the greenbelt canopy as a hub to global biomass with the absolute ability to support numerous conditions that favour biodiversity [24].

It has been revealed that the complexity of elevation patterns, biotic and abiotic factors, is adversely affecting the various epiphytic fern phorophytes, and consequently generally posing difficulty in assessing their individual pattern of distribution, which informed the need for the adoption of geospatial tools [25]. Geospatial tools or Geographical Information Systems can be described as a hub for different geographical locations and maps of various abiotic and biotic indices, analyzing their combined attributes in order to produce a single result revealing their relationship [26]. The use and application of geospatial tools to understand the trends involved in the spatial distribution of epiphytic ferns within an ecological study area has also become one of the most recent approaches needed in the study of epiphytic fern biodiversity [27, 28]. This involves such tools as: the remote sensing, web-mapping, and GPS with its significant role to botanists, ecologists, and environmental managers as aid to the necessary information needed on the biodiversity of epiphytic fern [26].

Several studies have reported on epiphytic fern distribution with paucity of information as well as gaps in parts of Rivers State [28, 29, 30,31, 32, 33] and just about 4% of annual ecological publication on epiphytic fern distribution pattern [18]. Therefore, this study is aimed at assessing the horizontal distribution of arboreal epiphytic ferns with the objectives of identifying the presence of epiphytic ferns and their distribution trend using the Average Nearest Neighbor (ANN) analysis to predict the distribution pattern on both the western and eastern wing of the greenbelt canopy. Significantly, this study will reveal the rate at which ferns are distributed with the use of modern geospatial tools.

2.0       MATERIALS AND METHODS

2.1.      Study Area and Field Sampling Delineation

The geographical location of the study area (Fig.2.1), with its neighborhood location and site has been documented [32]. The environmental characteristics involving the climatic conditions, vegetation system and the edaphic conditions have been described [34, 35, 36]. The survey and inventory were carried out on the gradient horizontal distribution of arboreal-fern bearing Phorophyte greenbelt canopy of the study site. A total stand of 214 trees (mainly Azadirachta indica) were observed from the inlet direction of Delta -Abuja campus gate of the study location sampled site. The sample site was delineated into eastern and western wing using a total distance of 1560m for the eastern wing, consisting of 145 canopy formations of which 69 trees are epiphytic-fern bearing Phorophytes while the western wing covers a distance of 1600m with 109 canopy formations in which 72 of them are epiphytic-fern bearing Phorophytes.

2.2 Sampling Methods, Procedure and Analysis

Using the line transect sampling design on the delineated eastern and western wing of the study sampled site, the Braun-Blanquet releve [37] and Rapid Representative of Epiphyte Diversity (RRED) [38] analytical methods were adapted. A total of 11 sampling plots were delineated on both the eastern and western wing. A handheld GPS (BHnav 300 model) was used to ascertain the geo-reference point of each tree Phorophyte along the horizontal row of the canopy gradients. The respective coordinates of all the Phorophytes and Non-Phorophytes tree stands and the obtained data were carefully inserted into the GIS ESRI’s ARCMAP to generate the satellite imagery and maps of study location and sample site revealing the Phorophyte and Non-Phorophyte canopies with the qualitative trend condition of the epiphytic ferns (Fig.2.2).

2.3.      Average Nearest Neighbor (ANN) Spatial and Phytosociological Analysis

The geo-referenced data obtained were imputed into the ArcGIS software, version 10.8 2021 for Nearest Neighborhood ratio between the western and eastern belt of the epiphytic canopies to ascertain the individual spatial distribution pattern between individual species of ferns on both belts. A negative z-score indicates clustering, while a positive z-score means disperse or evenness. The z-score usually return a range value between -2.58 to 2.58. Therefore, a negative z-score less than -2.58 indicate a significant clustering at 0.01 probability level while a positive z-score greater than 2.58 indicates a significant regularity or dispersal at 0.01 probability level [39]. In addition, if the ratio is less than 1, it is said that the data exhibits a clustered pattern whereas a value greater than 1 indicates a dispersed pattern in the data [40].

            The phytosociological analysis for frequency distribution of species and density of individual of a species as well as their relativity was based on Supriya and Yadava [41, 42] and Misra [43] methods.

3.0       RESULT

3.1.      Epiphytic Habit and Niche habitation

 The result of the Nearest Neighbor Analysis of the western and eastern belt has recorded six common obligatory arboreal epiphytic ferns under two families (Table 3.1), though with variation in their spatial horizontal distribution pattern (Table 3.2) in tandem with the variation of their various georeferenced situates (Tables 3.3a & b).

• Cryptogamic Phytosociology

Frequency and Density

The phytosociological frequency of occurrence and density of observed cryptogams across the eastern and western green belt based on summary of phorophyte georeferenced points (Tables 3.4a&b), has recorded Oleandra distenta with the highest percentage frequency of 67.16% (Rf = 44.49%) followed by Platycerium bifurcatum with frequency of 50.75% (Rf = 33.62%) while Drynaria laurentii recorded 0% frequency at the eastern belt.  Platycerium bifurcatum had the highest frequency of 70.59% (Rf = 33.82%) followed by O. distenta with 61.67% (Rf = 29.55%) while Drynaria laurentii recorded the least frequency of 1.47% (Rf = 0.70%)

The population of individual of each species (estimated density) (Table 3.4b), on the eastern belt recorded Oleandra distenta with the highest population density of 40.69 (Rd = 77.56%) and Drynaria laurentii with the least population density of 0.00 (Rd = 0.00%).  The western belt recorded same species with the highest density of 34.22 (Rd = 44.56%), while Pyrossia mechowii recordedthe least density of 0.31 (Rd = 0.40%).

Distribution pattern

The phytosociological result based on the Average Nearest Neighbor (ANN) geospatial Analysis, revealed distribution pattern of the species based on distances between species within the respective corridor formation of the eastern and western greenbelt represented in Table 3.2.

Nephrolepis pumicicola

The ANN analysis of the eastern corridor green belt N. pumcicola with a coverage distance of 181.81m revealed a Nearest Neighbor Ratio index of 3.14 greater than 1 (the hypothetical random distribution index) (Fig 3.1) while the western belt N. pumicicola with distance of 62.25m had a Nearest Neighbor ratio index of 1.58 (Fig 3.2) greater than 1. This implies a dispersed trend of distribution and given a critical value (Z-score) of 10.03 (eastern belt) and 3.86 (western belt), there is a less than 1% likelihood that the dispersed pattern could be the result of random chance.

Oleandra distenta

The Oleandra distenta of the eastern corridor of green belt with a distance coverage of 15.35m had a Nearest Neighbor Ratio of 0.41 with a critical Z-score value of -7.65 less than 1 (< 1); while in the western corridor Oleandra distenta with 21.73 distance coverage, recorded a Nearest Neighbor Ratio of 0.62 with a critical value (-4.75) less than 1. This implies the trend of clustering distribution between species of respective corridor and with the given critical values, there is a less than 1% likelihood that the clustered pattern could be the result of random chance.

Phymatode  sclopendria

The pattern of distribution of Phymatode sclopendria at the eastern corridor of green belt as revealed by the Nearest Neighbor Ratio (1.22) with distance coverage (162.12m), exhibited random distribution pattern. Given a critical value of 1.54, the pattern does not appear to be significantly different than random distribution while the western corridor of green belt distribution with distance coverage of 19.27 meters, had a Nearest Neighbor Ratio of 0.48 and a Z-score with critical value (-5.90), This implies a clustered pattern of distribution, with a less than 1%; s likelihood that could be the result of random chance (Figs. 3.5 & 3.6)

Platycerium bifurcatum

The Platycerium bifurcatum on the eastern corridor of green belt with an average distance coverage of 29.50m had a Nearest Neighbor Ratio of 0.62 which is less than 1, signifying a clustered distribution pattern. Given a critical Z-score value (- 4.29), there is a less than 1% likelihood that the clustered pattern could be the result of random chance. The same species on the western corridor of green belt with a distance coverage of 4620.89 meters and a Nearest Neighbor Ratio of 0.62 greater than 1 recorded a dispersed distribution pattern (Figs 3.7 and 3.8)

Pyrossia mechowii

Pyrossia mechowii recorded a dispersed pattern at both the eastern and western corridors of green belt with a Nearest Neighbor Ratio of 2.87 and 2.00 respectively greater than 1, though at the distances of 552.51 and 139.29 meters. Given the critical Z-score values of 14.33 (eastern) and 4.66 (western), there is a less than 1% likelihood that the dispersed pattern could be the result of random choice (Figs 3.9 and 3.10).

4. DISCUSSION

The integrated use of conventional phytosociological tools, geospatial tools, and modern software technologies like the ArcGIS and the Average Nearest Neighborhood (ANN) Analysis to predict the phytosociology of species frequency and density, as well as the distribution pattern of epiphytic ferns in a green belt corridor in part of Rivers State, Nigeria, has revealed six different epiphytic ferns in the canopy formation.

The frequent occurrence and density of epiphytic ferns recorded on both greenbelt canopies (Tables 3.4a & b) have shown that Oleandra distenta (Eastern and western belt) has the highest frequency of occurrence (67.16%), followed by Platycerium bifurcatum (50.75%). On the western belt, Platycerium bifurcatum had the highest frequency of occurrence (70.59%), and then Oleandra distenta (61.67%). The species have exhibited variance in the transect subunit, revealing their dominance across horizontal gradients of individual phorophyte. This corroborates studies on the richness and abundance of epiphytic fern species on phorophytes along horizontal distribution [44, 45]. Similar reports have also revealed phorophytes with mid-level elevational gradients influencing the initiation, bearing, and colonization of more epiphytic fern species [46, 47, 48, 49].

Besides the elevational gradients of phorophytes, dominant species have been shown to have a sound resilience characteristic to adapt to the ever-changing climatic conditions of their environment [50]. This could be exemplified in this present study, where the level of humidity and rainfall experienced within the study area has greatly proven the influence of precipitation in the distribution pattern of these six epiphytic fern species along a horizontal gradient [51, 52, 53, 54].

By the phorophyte assessment of individual species on the western and eastern green belt, Drynaria laurentii remains the only epiphytic fern that appeared in one greenbelt location. This implies a very low level of adaptability compared to other epiphytic fern species recorded within the study site. This supports the assertion that the species requires very favorable abiotic and biotic conditions that will permit its growth and development because of their sensitive nature [20]. However, the influence of anthropogenic activity within the study site has revealed variation in the frequency of occurrence (presence and absence) of individual fern species across the green belt as represented in Table 3.3. It is shown that some epiphytic fern species, like Phymatodes sclopendria, have shown their absence in subunit 7 of the western belt and subunits 1, 6, and 10 of the eastern belt. Nephrolepsis pumicicola on the eastern belt was seen in all the subunits except in subunits 1,4,6,8 and 10, as well as in subunits 1, 6, and 11 of the western belt. Pyrossia mechowii was present in all subunits of the western belt except in 4, 5, 6, 7, and 11, and also of the eastern belt, present only in subunits 1,3,4,5,6,7,9 and 10.

The rate at which these epiphytic ferns are distributed along a horizontal gradient based on the nearest neighbour ratio has shown that a random and clustered pattern of distribution could possibly be as the result of litter accumulation and composition of the fronds at the greenbelt canopy and the activities of the micro and macro organisms of the individual phorophytes on which the fern species grow [55]. The clustered pattern of distribution by Oleandra distenta on both eastern and western wings has invariably indicated that the greenbelt canopy of the phorophytes did not affect the distribution. This reaffirms the assertion by Nervo et al. [19] that the distribution of arboreal epiphytic fern on a greenbelt canopy lies on the chance and limitations of their dispersal in different areas under different environmental gradients and canopy assemblages. This could also imply that the distribution of pteridophytes may be promoted by their higher dispersal abilities but restricted by habitat availability [56].

Though it has been reported that cryptogamic ferns are not randomly distributed but rather clustered or dispersed with their presence or absence relating to microhabitat characteristics and abiotic variables [57, 58]. In the present study Platycerium bifurcatum and Phymatodes sclopendria were found to be clustered on the eastern and western corridor green belt, respectively while attaining a dispersed and random pattern of distribution on the reverse side of the corridor belt, respectively. This has greatly shown that distribution pattern can be changed, altered or influenced by some abiotic and biotic determinants such as phorophyte bark texture and pH as well as anthropogenic activities like logging and canopy branching with attendant impact on individual distribution of the canopy belts [59]. With all the ferns having a common host, Nephrolepis pumicicola and Pyrossia mechowii with a dispersed distribution pattern on both green belt corridor indicates their weak ability to adapt to this kind of environment, unlike Oleandra distenta, Platycerium bifurcatum and Phymatodes sclopendria, this variationin distribution is likely to be caused by the phorophyte host bark structure and texture and pH [59]. However, the inability to have Drynaria laurentii on both sides of the study site might be a result of poor accumulation of litter based on the branching of the phorophytes which has limited its growth and distribution.

Anthropogenic activities such as clearing of story, logging, pruning of tree branches, or felling of whole trees often take place at the study site. All these activities as noted by Hietz et al. [60] and Kromer et al. [61] have an alteration impact on the natural environment and habitat and consequent changes in the diversity and distribution of ferns thus influencing their abundance as been revealed in the results. Such activities might also lead to species isolation, reduced cover, increased exposure to solar radiation and an increase in evapotranspiration rate, thereby modifying the microhabitat [62].

Conclusion

The use of geospatial technologies like the handheld GPS and ArcGIS has revealed the phytosociological attributes of six different arboreal epiphytic ferns. Oleandra distenta, Platycerium bifurcatum and Phymatodes sclopendria have shown have high adaptability ratios to withstand the climate of this region due to their high frequency of occurrence, which has invariably made them to have a clustered kind of distribution across the green belt canopies. Unlike Pyrossia mechowii,  Nephrolepis pumicicola and Drynaria laurentii and coupled with their various adaptive features and shorter life span if compared to their hosts, this study has helped to understand their distribution as a window for conservation priority.

Acknowledgements

This paper is an excerpt of the result of an approved research project at the University of Port Harcourt, Nigeria. The authors thank colleagues and laboratory staffs that helped in field work and Cartographer of the GIS Unit, Geography and Environmental Department, University of Port Harcourt in course of the study.

Conflict of Interest

The authors declare no conflict of interest in any aspect of the study.

References

[1] Ellwood, M. D. F., and Foster, W. A. (2004). Doubling the estimate of invertebrate biomass in a rainforest canopy. Nature 429: 549–551.

[2] Coomes, D. A., Allen, R. B., Bentley, W. A., Burrows, L. E., Canham, C. D., Fagan, L., Forsyth, D. M., Gaxiola-alcantar, A., Parfitt, R. L., Ruscoe, W. A., Wardle, D. A., Wilson, D. J.  and Wright, E. F., (2005). The hare, the tortoise and the crocodile: the ecology of angiosperm dominance, conifer persistence and fern filtering. Journal of Ecology 93: 918–93

[3] James, S.A., Bell, D.T. and Pate, J.S. (2007). Nitrogen relations to epiphytic ferns in a temperate Autralian forest. Journal of ecology, 95: 127 – 136. Doi: 10.1111/j.1365-2745.2006.-01195.x

[4] Wenzhang, M., Wenyao, L., Lipan, Y. and Guoping, Y. (2008). Edge effects on epiphytes in montane moist evergreen broadleaved forest. Biodiversity Science, 16: 245–254.

[5] Mehltreter, K., Walker, L.R. and Sharpe, J.M. (2010). Fern Ecology. Cambridge University Press

[6] Neider, J., Porsperi, J., and Michaloud, G. (2001). Epiphytes and their contribution to canopy diversity. Pl. Ecol. 153:51-63

[7] Hietz, P., Buchberger, G. and Winkler, M. (2009). Epiphytes and canopy water storage in tropical forests. Journal of hydrology. 376: 34 – 42

[8] Benzing, D.H, (2001). Vascular epiphytes. In:Levin, S.A. (ed). Encyclopedia of Biodiversity. 5:57 – 72. Academic press

[9] Ellwood, M.D., Jones, D.T. and Foster, W.A. (2002). Canopy ferns in lowland Dipterocarp forest support. A Prolific abundance of Ants, Termites and other invertebrates. Biotropica 34: 575- 583

[10] Bartels, S.F. and Chen, H.Y. (2012). Mechanisms regulating epiphytes abundance and distribution in forest ecosystems. Journal of Ecology. 100:1009 – 1021. Doi: 10.1111/l.1365-2745-2012.01997.x

[11] Zotz, G., and Hietz, P. (2001). The physiological ecology of vascular epiphytes: current knowledge, pen questions. Journal of experimental botany, 50(364): 2067-2078.

[12] Gradstein, S.R., Nadkarni, N.M., Kromer, T., Holz, I. and Noske, N. (2003). A protocol for rapid and representative sampling of vascular and non vascular epiphytic diversity of tropical rainforests. Selbyana. 24:105 – 111

[13] Bennett, B.C. (1991). Comparative biology of Neotropical epiphytic and saxicolous Tillandsia species: Population structure. Journal of tropical ecology 7:361 – 371

[14] Barthlott, W., Schmit-Neuerburg, V., Nieder, J. and Angwald, S. (2001). Diversity and abundance of vascular epiphytes: A comparison of secondary vegetation and primary montane forest in the Venezuelan Andes. Plant Ecol. 152: 145-156

[15] Vandunne, H.T.F. (2002). Effects of the spatial distribution of trees, nonspecific epiphytes and geomorphology on the distribution of epiphytic bromeliads in secondary montane forest (Cordillera Central, Colombia) Trop. Ecol. 18:193 – 213

[16] Flores-Palacios A. and García-Franco J.G. (2006). The relationship between tree size and epiphyte species richness: testing four different hypotheses. Journal of Biogeography 33(2): 323–330. https://doi.org/10.1111/j.1365-2699.2005.01382.x

[17] Tewari, L.M., Tewari, G., Nailwal, T.K. and Pangtey, Y.P.S. (2009). Bark factors affecting the distribution of epiphytic ferns communities. Nature and science. 7(5): 76 – 81

[18] Mehltreter, K. and Hooper, EA. (2013). Annual Review of Pteridological Research 26: 1-102

[19] Nervo, M.H., Andrade, B.O., Tomquist, C.G., Mazurana, M., Winddisch, P.G. and Overbeck, E.O., (2018). District responses of terrestrial and epiphytic ferns and lycophytes along an elevational gradient in southern Brazil. Journal of vegetation science. pp. 55 – 64 Doi: 10.1111/jvs.12709

[20] Cummings, J., Martin, M. and Rogers, A. (2006). Quantifying the abundance of four large epiphytic fern species in remnant complex notophyll vine forest on the Atherton Tableland, north Queensland, Australia. Cunninghamia 9: 521–527.

[21] Scheffers, B.R., Phillips, B.L and Shoof, LP. (2014). Asplenium bird’s nest ferns in rainforest canopies are climate-contingent refuges for frogs. Global Ecology of Conservation 2:37-46. DOI: 10.1016/j.gecco.2014.06.004

[22] Parker, G.G. (1995). Structure and Microclimate of Forest Canopies. In: Forest Canopies (M.D)

[23] Hubbell, S. P. (2001). The unified theory of biodiversity and biogeography. Monographs in population biology Vol. 32.     Princeton,         NJ,       USA:    Princeton University Press.

[24] Lowman, M. D., and Nadkarni, N. M. (1995). Forest canopies. Academic Press, San Diego, California, USA.

[25] Merem, E. and Twumasi, Y. (2008). Using spatial information technologies as monitoring devices in international watershed conservation along the Senegal River Basin of West Africa. Int. J. Environ. Res. Public Health. 5: 464 – 476. 

[26] Gillespie, T.W., Foody, G.M., Rocchini, D., Giorgi, A.P., and Saatichi, S. (2008). Measuring and modeling biodiversity from space. Prog. Phys. Geogr.: Earth Environ., 32: 203 – 221

[27] Foody, G.M. (2008). GIS: Biodiversity applications. Prog. Phys. Geogr. 32: 223 – 235

[28] Edwin-Wosu, N.L., Anekwe, C.C.1 and Okeke, N.P. (2022). Geospatial ecological distribution of cryptogamic flora in swamp forest riparian vegetation in parts of Rivers state, Nigeria. Ethiopian Journal of Environmental Studies & Management 15(1): 111 – 124. Doi: https://ejesm.org/doi/v15i1.10

[29] Zhang, L., Nurvianto, S. and Harrison, R. (2010). Factors affecting the distribution and abundance of Asplenium nidus L. in a tropical lowland rainforest in Peninsular Malaysia. Biotropica. 42(4): 464 – 469. Doi: 10.1111/j.1744.7429.2009.00607.x

[30] Palaniswami, C., Gopalasundaram, P. and Bhaskaram, A. (2011). Application of GPS and in sugar cane Agriculture. Sugar Tech 13(4): 360-365. 

[31] Plumptre, A.J. and  Masozera, M. (2002). Biodiversity surveys of the Hyungwe forest reserve in S.W Rwanda. WCS. Working paper No. 19.

[32] Edwin-Wosu and Michael, C. Ahanonu . (2020). Geospatial Delineation of Arboreal Epiphytes in a Greenbelt Canopy Formation in parts of Rivers State, Nigeria., Asian Journal of Science and Technology, 11, (08):11090-11103

[33] Edwin-Wosu, N.L, Omara-Achong, T.E., Edward, P.O., and Okeke, N.P. (2024). Geospatial Trend of Phytodistribution Pattern of Cryptogamic Ferns in a Rainforest Vegetation. Trends Appl. Sci. Res., 19 (1): 1-19

[34] Kuruk, P. (2004). Customary water loss and practices: Nigeria.

[35] Alagoa, E.J. (1999). The land and people of Rivers State, Central Niger Delta. Onyema research publication. Port harcourt, Rivers State, Nigeria.

[36] Egwuogu, C.C., Okeke, H.U., Emenike, H.I. and Abayomi T.A (2016). Rainwater Quality Assessment in Obio/Akpor L.G.A of Rivers State Nigeria. International Journal of Science and Technology. 5 (8)

[37] Braun-Blanquet J. (1964). Pflanzensoziologie, Grundzüge der Vegetation skunde. (3. Auflage). Springer Verlag, Wien, 865 pages.

[38] Shaw, J.D. and Begstrom, D.M.  (1997). A rapid assessment technique of vascular epiphyte diversity at forest and regional levels. Selbyana 18:195-199

[39] Getis, A. and Ord, J.K. (1996). Local spatial statistics: An Overview. In O. Longley & M. Batty (Eds.), Spatial analysis: Modelling in a GIS Environment. 261 – 277

[40] Pimpler, E. (2017). Spatial Analytics with ArcGIS: Build powerful insights with spatial analytics. Packet publishing, 290 pages. ISBN:9781787122581

[41] Supriya, LD, and Yadava, P.S. (2006). Floristic diversity assessment and vegetation analysis of tropical semievergreen forest of Manipur, North East India. Tropical Ecology, 47(1):89-98

[42] Chikkahuchaiah, S., Rayasamudra, K.S. and Badenahally, C.N. (2016). Diversity and composition of riparian vegetation across forest and agrosystem landscapes of River Cauvery, Southern India. Tropical Ecology, 57(2):343-354.45.

[43] Misra R, (1968). Ecology Workbook. Oxford & IBH Publishing Co. Pvt Ltd., New Delhi; 244.46.

[44] Rahbek, C. (1995). The elevational gradient of species richness: A uniform pattern? Ecography. 18: 200 – 205.

[45] Rahbek, C. (2005). The role of spatial scale and the perception of large scale species richness pattern. Ecology letters. 8: 224 – 239

[46] Colwell, R. K., and Lees, D. C. (2000). The mid-domain effect: geometric constraints on the geography of species richness. Trends in Ecology & Evolution 15: 70–76.

[47] Grytnes, J. A., and Vetaas, O. R. (2002). Species richness and altitude: a comparison between null models and interpolated plant species richness along the Himalayan altitudinal gradient, Nepal. American Naturalist 159: 294–304.

[48] Grytnes, J. A. (2003). Ecological interpretations of the mid-domain effect. Ecology Letters 6: 883–888.

[49] Colwell, R. K., Rahbek, C. and Gotelli, N. J.  (2004b). The mid-domain effect and species richness patterns: what have we learned so far? American Naturalist 163: E1–E23.

[50] Etterson JR (2004) Evolutionary potential of Chamaecrista fasciculata in relation to climate change. I. Clinal patterns of selection along an environmental gradient in the Great Plains. Evolution 58(7):1446–1456

[51] Aldaroso, J.J.,        Cabezas, F., and Aedo, C. (2004). Diversity and distribution of ferns in sub-Saharan Africa,          Madagascar and some    islands  of the South Atlantic.     Journal of Biogeography, 31, 1579–1604. https://doi. org/10.1111/j.1365-2699.2004.01106.x

[52] Greer, G. K., Lloyd, R. M., and McCarthy, B. C. (1997). Factors influencing the distribution of pteridophytes in a southeastern Ohio hardwood forest. Journal of the Torrey Botanical Society, 124, 11–21. https://doi. org/10.2307/2996594

[53] Kessler, M. (2001b). Patterns of diversity and range size of selected plant groups       along    an elevational transect in the Bolivian Andes. Biodiversity & Conservation, 10, 1897–1921. https://doi.org/10.1023/a:10131309 0299310.1023/a:1013130902993

[54] Kessler, M., Kluge, J., Hemp, A. and Ohlemüller, R. (2011). A global comparative analysis of elevational species richness patterns of ferns. Global Ecology and Biogeography, 20, 868–880. https://doi. org/10.1111/j.1466-8238.2011.00653.x

[55] Watkins, J. E., Mack, M.K. and Mulkey, M.K. (2007).Gametophyte ecology and demography of epiphytic and terrestrial tropical ferns. American Journal of Botany, 94(4): 701–708.

[56] Richard, A.F., Dewar, R.E., Schwartz, M. and Ratsirarson, J. (2000). Mass change, environmental variability and female fertility in wild Propithecus verreauxi. Journal of Human Evolution, 39(4): 381-391.

[57] Nóbrega, G.A., P.V. Eisenlohr, M.L.B. Paciência, J. Prado and Aidar, M.P.M. (2011). Ferns composition and diversity differ between Restinga and Lowland Rainforest areas in the Serra do Mar?. Biota Neotrop., 11: 153-164.

[58] Patil, S., Lavate, R., Rawat, V. and Dongare, M. (2016). Diversity and distribution of pteridophytes from Satara District, Maharashtra (India). Plant Science Today, 3: 149-156.

[59] Nalini, M., Nadkarni, M., Merwin, C. and Jurgen, N. (2001). Forest canopies, Plant diversity. Encyclopedia of Biodiversity 3.

[60] Hietz, P., Buchberger, G. and Winkler, M. (2006). Effect of forest disturbance on abundance and distribution of epiphytic bromeliads and orchids. Ecotropica, 12: 103-112.

[61] Kromer, T., Kessler, M., Gradstein, S.R.  and Acebey, A. (2005). Diversity patterns of vascular epiphytes along an elevational gradient in the Andes. J. Biogeogr., 32: 1799-1809

[62] Adubasim, C.V., H.A. Akinnibosun, S.N. Dzekewong and Obalum, S.E. (2018). Diversity and spatial distribution of epiphytic flora associated with four tree species of partially disturbed ecosystem in tropical rainforest zone. Agro-Science, 17: 46-53.