The relation between phytogeographic affinity, location and space of vascular plant genera in the Andes Student Name: Aileen Hiralal Student Number: 10184821 Supervisor: Joost Duivenvoorden Examinor: Peter Roessingh Word Count: 3400 Date: 15-08-17
Abstract
A key concept in functional ecology is identifying relationships between plant traits and environmental variables. In this study RLQ and fourth-corner analyses, two three-table statistical techniques, are used to analyse the relation between phytogeographic affinities and environmental gradients with data derived from previous studies. The RLQ output revealed that axis 1 explains 83.9% of the total covariance between phytogeographic affinities and environmental variables and was most strongly correlated with maximum altitude (m) and genera belonging to the Neo-Tropical Montane and Wide Temperate element. These correlations were, however, not found significant by Fourth-Corner analysis. The results suggest that the genera in this dataset have been present in the northern Andes long enough to migrate to all suitable sites and to adapt to the various environmental gradients.
Introduction
A key question in functional plant ecology is how plants traits help plants and plant taxa to determine their presence and abundance (Legendre et al., 1997; Lacourse, 2009). Understanding the relation between environment and traits can enhance our knowledge of biological processes, explain current spatial distributions, predict future spatial distributions, and allow predictions on how these distributions may be affected by environmental change. The relation between traits and environmental variables and their effect on the occurrence of plants is particularly interesting when applied to a heterogeneous habitat as it can reveal patterns of distribution of different traits along an environmental gradient (Young et al., 2002). In this study, páramo vegetation from the Andes is used to examine the relation between environmental conditions and genera traits and how this relation helped form the current composition of the genera.
The Cordilleras de los Andes is a heterogeneous habitat covering about 9,000 km of South America (Young et al., 2002). The Andes has mountain peaks ranging from 2,000 m up to 6,000 m and is a young, geologically active mountain chain (Stern, 2004; Sklenar et al., 2010). Its formation is mostly due to tectonic plates shifting beneath western South America. The northern and youngest part of the Andes formed approximately 55 million years ago and it was not until the Pliocene (5,333 – 2,588 million years ago) and Pleistocene (2,588 million years ago – 11,56 thousand years ago) that it reached its current altitude (Wodzicki, 2000; Sklenar et al., 2010). Due to its vastness, geological activity, and great altitudinal differences, the Andes provides diversified habitats that expand beyond the climatic zone of the Neo-Tropics (Prance, 1982). The varying altitudes result in drastic changes in temperature and precipitation.
These characteristics thus result in many pronounced environmental gradients (Sklenar et al., 2006).
Páramo is a shrub and grass ecosystem that is located above the upper forest line and below the permanent slow line (Luteyn, 1992). Páramo evolved as a consequence of three biological processes: firstly by migrations of plants from temperate regions, secondly by adaptation of lower elevation plants to high altitude environments, and thirdly by speciation through isolation (Cuello et al., 2010). Páramo generally occurs at elevations between 3,200 – 5,000 m above sea level. The climate is wet and cool with frequent night frosts that result in an ecosystem mainly dominated by grasses and shrubs (van der Hammen & Cleef, 1986). However, the climatic changes along with the separation of continents and the continuous tectonic activity resulted in a complex biogeographic distribution of the flora and a continuous pattern of evolution within the páramo vegetation of the Andes (Kricher, 2011; Sklenar et al., 2006). Due to the altitudinal gradient and latitudinal distribution the páramo vegetation in the northern Andes is a good model to analyse genera distribution patterns (Peyre, 2015).
Páramo flora has been studied by categorizing the genera according to their
phytogeographic affinities. These affinities were described as tropical, temperate, and cosmopolitan flora components that were each subdivided into several elements (Table 1)(Sklenar et al., 2010). Understanding the processes that result in patterns of genera distribution are fundamental in providing conservation for the páramo
ecosystems (Anderson et al., 2011). The aim of this study is therefore to analyse and examine the relations between phytogeographic affinitiy of the vascular plant genera in the Andes and the environment in which these genera occur. In order to predict
future spatial distributions of Andean flora as consequences to i.e. climate change, it is crucial to understand the distribution and pattern formation of the flora present-day (Madrinan et al., 2013).
Glacial periods resulted in the connection and extension of páramo areas. It allowed Temperate, Holarctic and Astraul-Antarctic taxa to move longitudinally along the Andes (Sklenář 2000; Jørgensen & Ulloa-Ulloa 1994; Peyre, 2015). Due to the orogeny of the northern Andes the vascular plant genera present in páramo vegetation has multiple origins and the expectation is that the abundance and distribution of temperate and tropical taxa will vary along altitudinal and spatial gradients (van der Hammen & Cleef 1986; Smith & Cleef 1988). The expectation based on research by Sklenar et al. (2000) and Jorgensen et al. (1994) is that moving up the altitudinal gradient, the ratio of temperate vs. tropical taxa will increase as a consequence of tropical taxa that have migrated upwards from the Amazon basin and western lowlands (Simpson 1975; Hooghmiestra et al. 2006; Peyre, 2015). Also, Holarctic taxa that originated from the north can be expected to be more abundant in the
northern páramos. Likewise, Austral-Antarctic elements are expected to occur mostly in the southern páramos. (Peyre, 2015) The overall expectation in this study is
therefore that the phytogeographic affinity and altitude and space are related to each other. This expectation is made under the assumption that the young and active dynamics of the Andes will result in distribution patterns. A pattern will be present, where the distribution of genera will be correlated to their phytogeographic affinities (Table 1). The null hypothesis is that phytogeographic affinities show no relation to the environment and space. This can be interpreted as if the genera will have had ample time to migrate to all suitable areas and to adapt to the prevaling environmental
conditions. The alternative hypothesis is that phytogeographic affinities do show a relation to the environment and space. This can be interpreted as if the genera will not have had sufficient time to migrate to all suitable areas or adapt to the prevailing environmental conditions.
The relation between páramo vascular plant genera traits and environmental variables regarding genera abundance was analysed using RLQ analysis (Doledect et al., 1996) and Fourth-Corner analysis (Legendre et al., 1997; Dray & Legendre, 2008). RLQ and Fourth-Corner analysis are statistical techniques specifically designed to analyse trait-environment relationships based on the occurrence of plant taxa at different sites, using a three-table matrix. RLQ analysis (Doledec et al., 1996) uses multivariate ordination to identify the main relationships that the environmental table (R) and genera trait table (Q) have on the structure of the genera abundance table (L)
(Lacourse, 2009; Dray et al., 2014). The output of RLQ analysis contains a summary of the multivariate correlations but does not evaluate significance (Doledec et al. 1997). Fourth-Corner analysis performs an analysis on the correlation between each environmental variable (R) and genera trait (Q) regarding the genera composition (L) by performing bivariate test correlations. The fourth-corner method quantifies these correlations and evaluates a significance of each bivariate association (Legendre et al., 1997; Dray & Legendre, 2008).
Material and methods
Genera trait and environmental data
Both the vascular plant genera trait data and the páramo environmental data used in this study was retrieved from several previous studies (Table 1) that were combined into a database by Cuello et al. (2010). The latitude and longitude were retrieved from
Google Earth. Genera were categorized into phytogeographic affinities that consist of eight elements that belong to four components (Sklenar et al., 2010)(Table 2). .
Composing datasets
Three datasets were constructed. The first dataset, table L, consists of the absence or presence of 411 genera at the eight different locations (Fig. 1). The absence or presence is represented using 0 for absent and a number that sums up the number of each genera. This table thus contains the occurrences of p genera at n sites (L=n*p). The second dataset, table R, is composed of the environmental variables regarding the eight different locations. In this dataset 3 environmental variables were used:
1.Latitude, 2.Longitude and 3.Maximum elevation (m). This table describes m environmental variables for n sites (R=n*m). The third dataset, table Q, is the genera trait dataset where the 411 genera are categorized according to their phytogeographic affinity. Their phytogeographic affinities consist of three different components that are composed of in total seven different elements: Temperate component composed of elements: a) Austral Antarctic taxa, b) Widely distributed temperate taxa and c) Holarctic groups, 2.Tropical component composed of elements: d) Neo-tropical montane elements, e) Paramo endemics, f) Wide tropical taxa, and g) Andean Alpine taxa and 3.Cosmopolitan component composed of element: h) Cosmopolitan taxa (Table 1). The genera will be categorized using the binary system, 1 for belonging to an element, 0 for not. This table thus describes s traits for p genera (Q=s*p).
(Legendre et al., 1997; Dray & Legendre, 2008) The rows of table L correspond to the rows of table R and the columns of table L correspond to the columns of table Q (Doledec et al. 1996; Legendre et al., 1997).
RLQ analysis
Before the RLQ analysis, each table was analyzed separately. The results of this separate analysis were afterwards used for the ordination in the three-table RLQ analysis (Doledec et al, 1996). Table L was analyzed using correspondence analysis (dudi.coa) in order to evaluate the composition of the genera over the various sites. The output of this correspondence analysis reveals the optimal simultaneous ordination of genera and site scores. Principal component analysis (dudi.pca for quantitative analysis) was applied to table R with regard to row weights and column weights of table L, respectively, to evaluate the main environmental gradient. The Hill-Smith method for mixed type of data (dudi.hillsmith) was applied to table Q with row weights and column weights of L, respectively, to identify trait patterns (Doledec et al, 1996; Dray et al., 2014; Lacourse, 2009). After these separate analyses, the RLQ analysis was performed on the cross-matrix of tables R, L, and Q. RLQ analysis combines the three separate analyses of the tables and identifies the main relations between the environmental variables (R) and phytogeographic affinities (Q) with regard to genera abundances (L). RLQ analysis selects axes that maximize the
covariance between the site scores with regard to the environmental variables (R) and the genera scores with regard to the phytogeographic affinities (Q) computing an s x
m (traits x environmental variables) matrix containing the intensity of the correlations
(Doledec et al., 1996). The complete mathematical model for RLQ analysis is explained in Doledec et al. (1996). RLQ analysis was performed using the ade4 package (Chessel et al., 2004) in R studio (R Studio team, 2015).
Fourn-Corner analysis was applied on the three data tables to test the significance of the correlations between environmental variables (R) and phytogeographic affinities (Q). The fourth-corner statistic evaluates the relationship between genera abundance, environmental variables and phytogeographic affinities. The significance of these relationships was tested using model 6 proposed by Dray & Legendre (2008) with 4999 permutations and the false discovery rate method (FDR) (Benjamini & Hochberg, 1995). Model 6 is a combination of model 2 and model 4 proposed by Legendre et al (1997). It allows for the testing of both hypotheses (model 2 and 4) independently and corrects the type 1 error (Dray & Legendre, 2008; Ter Braak et al., 2012). Model 2 tests the null hypothesis that the distribution of genera with fixed phytogeographic affinities is not influenced by environmental variables by permuting the n sites, which correspond to the rows of table R and L. The alternative hypothesis for model 2 suggests that the genera distribution (L) with fixed phytogeographic affinities is significantly influenced by environmental variables (R) (Dray & Legendre, 2008). Model 4 tests the null hypothesis that the genera composition at sites (L) with fixed environmental variables is not effected by phytogeographic affinities (Q) by permuting the p genera that corresponds to the rows of Q or columns of L. The alternative hypothesis of model 4 suggests that the composition of genera (L) is influenced by phytogeographic affinities (Q) (Dray & Legendre, 2008). The tests were performed using a significance level α = 0.05. If both of the P values in the output of model 6 are lower than 0.05 the relations between phytogeographic
affinities and environmental variables regarding the composition of genera is found to be significant (Dray et al., 2014). The complete mathematical model of Fourth-Corner analysis is described in Legendre et al. (1997) and Legendre & Dray (2008).
Fourth-Corner analysis was performed using the ade4 package (Chessel et al., 2004) in R studio (R Studio team, 2015).
Results
Raw data
The vascular paramo flora is mostly composed of the Neo-Tropical and Temperate elements (Table 3), which is consistent with results from Sklenar et al. (2006).
RLQ analysis
The first two axes of the RLQ analysis extracted 83.9% and 11.7%, respectively, of the total variance of the cross matrix of the environmental variables (R) and
phytogeographic affinities (Q) (Fig. 2). The RLQ output demonstrated that genera of the Austral Antarctic and Neo-Tropical Montane element show strong negative
correlations with maximum altitude whereas genera of the Wide-Temperate, Holarctic and Andean-Alpine elements show a positive correlation with maximum altitude.
Fourth-Corner analysis
The fourth-corner analysis without correction for multiple testing revealed that among the 24 possible associations, 5 were found significant (Fig. 3). Austral Antarctic element was negatively correlated with longitude (r= -0.05, P=0.04) and maximum altitude (r= -0.06, P=0.03). Neo Tropical Montane element was also negatively correlated with maximum altitude (r= -0.09, P=0.02). Holarctic and Andean Alpine elements had a positive significant relation with maximum altitude (r= 0.06, P=0.04, r= 0.082, P=0.01 respectively). However, as the false discovery rate (fdr) was applied
using Holm’s correction method for multiple comparisons, the adjusted p values resulted in no significance.
Discussion
Distribution of phytogeographic flora elements along altitudinal gradients and space
The Fourth-Corner analysis of the data in this study demonstrated that there are no significant patterns of the phytogeographical affinity of the vascular plant genera along altitudinal gradients or location. Genera of the Páramo Endemic element showed a low correlation with all three environmental variables. The genera of this element are distributed throughout but within the páramo ecosystem and are therefore adapted to the various environmental gradients. Their abundance may therefore not be affected by the environmental gradients tested in this analysis. The low correlation of genera of the Wide Tropical element with environmental variables could be explained by their repeated colonization into páramo ecosystems. (van der Hammen & Cleef, 1986) Their widespread occurrence in tropical, subtropical and paleotropic habitats even ranging into the temperate zones (Sklenar, 2011) may provide them with adaptive advantages to the environmental variables used in this study. Genera of the Widely-Distributed Temperate element occur in both northern and southern temperate zones. The origin of genera from this element has not been fully determined although it seems there is a vast amount of genera that have migrated from the north as well as from the south (Sklenar, 2011) The inconsistency in migration could explain the lack of significance. The Cosmopolitan element also did not show a significant correlation with any environmental variables. Genera of this element have a worldwide
genera with adaptive advantages such that their distribution is not affected by the environmental variables used in this study.
Data set and analysis
It is important to note that the RLQ and fourth-corner techniques represent correlational approaches and that correlation alone does not prove a direct causal relationship between environment and phytogeographic affinities. It is also possible that some of the trait-environment correlations are driven by traits, such as life history or growth form, that are not included in the analysis. (Lacourse, 2009) This may explain in part that there appears to be a response to altitude and space by the RLQ output although it is not supported by the significance tests. Another important notion is that phytogeographical elements are strong generalizations of true distribution areas of genera (Sklenar et al., 2006). The concept of phytogeographic affinities thus has limitations and a deeper understanding of the origin of the flora is therefore necessary. (Sklenar et al., 2006) Besides the limitation of phytogeographic affinity, the
categorization of genera into phytogeographic elements may not have been accurate either. Sklenar et al. (2011) demonstrated that molecular phylogenetic data suggested that the Wide Temperate as well as the Cosmopolitan element might be redundant. They also demonstrated that a considerable variation among elements is revealed when the Wide Temperate element is split into northern and southern elements. Analysis of molecular phylogeny is thus necessary to establish the correct source area of the genera.
The potential effect of the climatic change in the páramo vegetation of the northern Andes is unclear. (Anderson et al., 2011; Peyre, 2015) As a result of global warming, an increase in temperature is expected, which will most likely result in different precipitation patterns compared to this day. (Urrutia, 2009) Páramo plant genera can respond to climatic change in various ways. They can change their abundances and distribution, adapt and evolve or become extinct. (Jørgensen et al., 2011; Peyre, 2015) It is essential that more research be done on the relation between genera occurrence, their traits and the environmental conditions so that accurate expectations can be made concerning potential climatic fluctuations. (Madrinan et al., 2013)
Conclusion
The RLQ output revealed correlations between phytogeographic affinity and
environmental variables. The fourth-corner analysis, however, revealed that none of these were significant. The results suggest that the genera in this dataset have been present in the northern Andes long enough to migrate to all suitable sites and adapt to the various environmental gradients.
Acknowledgements
I want to sincerely thank Joost Duivenvoorden for providing me with direction, information and his constant guidance over the last few months. I also want to give a special thanks to Peter Roessingh, without whom, this project would not have been possible.
References
Anderson EP, Marengo J, Villalba R, Halloz S, Young B, Cordero D, Gast F, Jaimes E, Ruiz D (2011) Consequences of climate change for ecosystems and ecosystem services in
the tropical Andes. Climate change and Biodiversity in the Tropical Andes. In: Herzog SK, Martínez R, Jørgensen PM, Tiessen M (eds) Climate change and Biodiversity in the Tropical Andes. Inter‒American Institute for Global Change Research (IAI) and Scientific Committee on Problems of the Environment (SCOPE), pp 1‒5.
Barrington, D.S. 2005. Helechos de los páramos de Costa Rica. In: Kappelle, M. & Horn, S.P. (eds.), Páramos de Costa Rica: 375-
395. INBio, Santo Domingo de Heredia.
Bussmann, R.W. 2002. Estudios florísticos de la vegetación en la Reserva Biológica de San Francisco (ECSF) Zamora - Chinchipe. Herbario LOJA (Ecuador) 8: 1-106.
Cleef, A.M. 1979. The phytogeographical position of the neotropical vascular páramo flora with special reference to the Colombian Cordillera Oriental. In: Larsen, K. & al. (eds.), Tropical Botany:175-184. Academic Press, London.
Cleef, A.M. 2005. Phytogeography of the generic vascular páramo flora of Tatamá (Western Cordillera), Colombia. In: Van der Hammen, T. & al. (eds.), La Cordillera Occidental colombiana - Transecto de Tatamá. Studies on Tropical Andean Ecosystems 6: 661-668. Cramer/Borntraeger, Berlin-Stuttgart
Cleef, A.M., Rangel-Ch, J.O., Salamanca, S., Ariza-N, C. & Van Reenen, G.B.A. 2005. La vegetación del páramo del Macizo de Tatamá, Cordillera Occidental, Colombia. In: Van der Hammen, T. & al. (eds.), La Cordillera Occidental colombiana – Transecto de Tatamá. Estudios de Ecosistemas Tropandinos 6: 377-468. Cramer/Borntraeger, Berlin-Stuttgart. Cuello, N., Cleef, A. and Aymard, G. (2010). Phytogeography of the vascular páramo flora of Ramal de Guaramacal (Andes, Venezuela) and its ties to other páramo floras. Anales del Jardín Botánico de Madrid, 67(2), pp.177-193.
Dolédec, S., Chessel, D., ter Braak, C., & Champely, S. (1996). Matching species traits to environmental variables: a new three-table ordination method. Environmental And Ecological
Statistics, 3(2), 143-166
Dray, S. (2013). A tutorial to perform fourth-corner and RLQ analysis in R.
Dray, S. and Legendre, P. (2008). Testing the Species Trait-Environment Relationships: The Fourth-Corner Problem Revisited. Ecology, 89(12), pp.3400-3412.
Duivenvoorden, J. and Cuello A, N. (2012). Functional trait state diversity of Andean forests in Venezuela changes with altitude. Journal of Vegetation Science, 23(6), pp.1105-1113.
Franco-R., P. & Betancur, J. 1999. La flora del Alto Sumapaz (Cordillera oriental, Colombia). Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales 23 (Suplemento especial): 53-78.
Hooghiemstra H, Wijninga VM, Cleef AM (2006) The paleobotanical record of Colombia: implications for biogeography and biodiversity. Annals of the Missouri Botanical
Garden 93(2): 297‒325.
Hutchinson, G. (1957). Concluding remarks. Cold Spring Harbor Symposium of Quantitative
Biology (1st ed., pp. 415–427). New York: Biological Laboratory.
Jørgensen PM., Ulloa-Ulloa C (1994) Seed plants of the high Andes of Ecuador: a checklist. AAU Reports (No. 34), Aarhus.
Jørgensen PM, Ulloa-Ulloa C, León B, León-Yánez S, Beck SG, Nee M, Zarucchi JL, Celis M, Bernal R, Gradstein R (2011) Regional Patterns of Vascular Plant Diversity and
Endemism. In: Herzog SK, Martínez R, Jørgensen PM, Tiessen M (eds) Climate change and Biodiversity in the Tropical Andes. Inter‒American Institute for Global Change Research (IAI) and Scientific Committee on Problems of the Environment (SCOPE), pp 192‒203.
Keating, P. L. 1999. Changes in páramo vegetation along an elevation gradient in southern Ecuador. Journal of the Torrey Botanical Society 126(2): 159-175.
Kricher, J. (2011). Tropical Ecology. Princeton, N.J.: Princeton University Press. Lacourse, T. (2009). Environmental change controls postglacial forest dynamics through interspecific differences in life-history traits. Ecology, 90(8), 2149-2160.
Legendre, P., Galzin, R. and Harmelin-Vivien, M. (1997). Relating Behavior to Habitat: Solutions to the Fourth-corner Problem. Ecology, 78(2), p.547.
Lozano, P., Cleef, A. and Bussmann, R. (2009). Phytogeography of the vascular páramo flora of Podocarpus National Park, south Ecuador. Arnaldoa, 16(2), pp.69-85.
Madriñán, S., Cortés, A. and Richardson, J. (2013). Páramo is the world's fastest evolving and coolest biodiversity hotspot. Frontiers in Genetics, 4.
Pedraza-Peñaloza, P., Betancur, J. & Franco-Rosselli, P. 2004. Chisacá, un recorrido por los páramos andinos. Instituto de Ciencias Naturales e Instituto de Investigación de Recursos Biológicos Alexander von Humboildt, Bogotá.
Peyre, G. (2015). Plant diversity and vegetation of the Andean Paramo (Doctoral dissertation). University of Barcelona, Barcelona
Prance, G. (1982). A Review of the Phytogeographic Evidences for Pleistocene Climate Changes in the Neotropics. Annals Of The Missouri Botanical Garden, 69(3), 594. http://dx.doi.org/10.2307/2399085 Ramsay, P. (1992). The Paramo Vegetation of Ecuador: the Community Ecology, Dynamics
and Productivity of Tropical Grasslands in the Andes. Ph.D. School of Biological Sciences,
University of Wales, Bangor.
Ricardi, M, Gaviria, J. & Estrada, J. 1997. La Flora del Superpáramo venezolano y sus relaciones fitogeográficas a lo largo de Los Andes. Plantula 1(3): 171-187.
Rivera-Díaz, O. 2007. Caracterización florística de la alta montaña de Perijá. In: Rangel-Ch., J.O. (ed.), Colombia Diversidad biótica V: La alta montaña de la Serranía de Perijá: 71-132. Arfo Editores e Impresores Ltda. Bogotá.
Simpson BB (1975) Pleistocene changes in the flora of the high tropical Andes. Paleobiology 273‒294.
Sklenář, P., & Balslev, H. (2006). Geographic flora elements in the Ecuadorian superpáramo. Flora - Morphology, Distribution, Functional Ecology Of Plants, 202(1), 50-61.
http://dx.doi.org/10.1016/j.flora.2006.03.002
Sklenář, P., Dušková, E. and Balslev, H. (2011). Tropical and Temperate: Evolutionary History of Páramo Flora. The Botanical Review, 77(2), pp.71-108.
Sklenář, P., Kovář, P., Palice, Z., Stančík, D., & Soldán, Z. (2010). Primary succession of high-altitude Andean vegetation on lahars of Volcán Cotopaxi, Ecuador. Phytocoenologia, 40(1), 15-28.
http://dx.doi.org/10.1127/0340-269x/2010/0040-0442
ter Braak, C. (1985). Correspondence Analysis of Incidence and Abundance Data: Properties in Terms of a Unimodal Response Model. Biometrics, 41(4), 859–873.
http://dx.doi.org/10.2307/2530959
Urrutia R, Vuille M (2009) Climate change projections for the tropical Andes using a regional climate model: temperature and precipitation simulations for the end of the 21st
century. Journal of Geophysical Research: Atmospheres (1984–2012) 114(D2).
van der Hammen T, Cleef AM (1986) Development of the high Andean páramo flora and vegetation. In: Vuilleumier F, Monasterio M (eds) High altitude tropical
biogeography, Oxford University Press, New York, New York, pp 153‒201.
Vargas, G. & Sánchez, J.J. 2005. Plantas con flores de los páramos de Costa Rica y Panamá: El páramo ístmico. In: Kappelle, M. &
Horn, S.P. (eds.), Páramos de Costa Rica: 397-435. Editorial INBio, Santo Domingo de Heredia.
Gregory-Wodzicki, K. (2000). Uplift history of the Central and Northern Andes: A review. Geological Society Of America Bulletin, 112(7), 1091-1105.
http://dx.doi.org/10.1130/0016-7606(2000)112<1091:uhotca>2.3.co;2
Young, K., Ulloa, C., Luteyn, J. and Knapp, S. (2002). Plant Evolution and Endemism in Andean South America: An Introduction. The Botanical Review, 68(1), pp.4-21.
Tables Component Flora Element
Distribution Migration Expectation Tropical Wide Tropical Widely distributed in
the tropics including African-American and Asian-American
Inconsistent Relatively low
Andean alpine Mainly in Azonal
paramo
High elevation Northern
Paramo Endemics
Confined to paramo and also down slope Andean forests
Not applicable All over
Neotropical Montane Element
Range from montane forest into the supraforest zone
South to north Southern
Temperate Widely Distributed Temperate
Temperate and cool regions in both hemispheres
Inconsistent Relatively low
Holarctic Northern temperate
including Mediterranean distribution
North to south Northern
Austral Antarctic
Southern temperate distribution
South to north Southern
Cosmopolitan Cosmopolitan Worldwide distribution
Inconsistent All over
Table 1. Definitions of phytogeographic affinities. (Sklenář et al., 2010), (Cuello et al., 2010)
Paramo Max. Elevation (m)
Latitude Longitude Source of floristic data Sierra Nevada del
Cocuy, Colombia
5330 6,51319 -72, 197138 Cleef, Unpubl. data
Sierra Nevada de Merida, Venezuela
4980 8,556944 -70,9925 Ricardi & al., 1997;
Berg & Suchi, 2001
Sumapaz,
Cordillera Oriental, Colombia
4250 3,749869 -74,41667 Cleef, 1979;
Franco & Betancur, 1999; Pedraza-Penaloza & al, 2004; Rangel-ch, 200b
Tatama massif, Cordilelra Occidental, Colombia
4100 5,112951 -76,096387 Cleef & al., 2005; Cleef,
2005 Serrania de Perija, Colombia 4100 10 -73 Rivera-Diaz, 2007 Talamancas, Costa Rica/Panama 3850 9,5 -83,666667 Barrington, 2005;
Vargas & Sanchez, 2005
South Ecuador: Podocarpus National Park (PNP)
3695 -4,08499 -79,205503 Lozano & al., 2009;
Bussman, 2002;Keating, 1999 Guaramacal, Venezuela 3130 9,180487 -70,217021 Cuello et al., 2010
Table 3. Percentages of phytogeographic affinities at locations. (Sklenář et al., 2010), (Cuello et al., 2010)
Paramo Wide Tropical Andean Alpine Paramo Endemic Neo-Tropical Montane Widely Distributed Temperate Holarctic Austral Antarctic Cosmpolitan
Sierra Nevada del Cocuy, Colombia 7,9 8,4 6,5 27,6 18,2 12,1 10,7 8,4 Sierra Nevada de Merida, Venezuela 8,1 8,1 5,4 22,3 23 14,2 10,8 8,1 Sumapaz, Cordillera Oriental, Colombia 8,6 7,1 4,8 25,7 18,6 11,9 12,4 11 Tatama massif, Cordilelra Occidental, Colombia 9,7 8 1,8 25,7 22,1 8,8 14,2 9,7 Serrania de Perija, Colombia 12,4 3,6 5,8 27 20,4 13,9 10,2 6,6 Talamancas, Costa Rica/Panama 8,5 3,4 1,7 27,7 19,2 16,4 12,4 10,7 South Ecuador: Podocarpus National Park (PNP) 12 5,5 4 32,5 13,5 10,5 13 9 Guaramacal, Venezuela 11,1 0,9 1,9 38,9 18,5 3,7 11,1 13,9
Figures 3 4 5 7 6 8 2 1
Figure 1. The eight locations of the paramo study sites. 1 = Serrania de Perija, 2 = Guaramacal, 3 = Sierra Nevada de Merida, 4 = Sierra Nevada del Cocuy, 5 = Talamancas, 6 = Tatana Massif, 7 = Sumapaz, 8 = Podocarpus National Park (PNP) d = 0.5 d = 0.5 Austral.Antarctic Wide.Temperate Holarctic Neo.Tropical.Montane Paramo Wide.Tropical Andean.Alpine Cosmopolitan Latitude Longitude Max altitude (m)
Figure 2. Biplot representing RLQ ordination of environmental variables (R) and phytogeographic affinities (Q) (axis 1 = x, axis 2 = y, d represents grid size.
Figure 3. Results of the fourth-corner analysis. Significant positive associations are represented by red cells, significant negative associations are represented by blue cells and variables with no significant correlations are shown in grey. (significant when P < 0.05)
Austral−Antarctic Wide−Temperate Holarctic Neo−Tropical−Montane Paramo Wide−Tropical Andean−Alpine Cosmopolitan
