Journal of Biogeography. 2019;00:1–18.  |  1wileyonlinelibrary.com/journal/jbi Received: 30 November 2018  |  Revised: 8 March 2019  |  Accepted: 8 April 2019 DOI: 10.1111/jbi.13607 R E S E A R C H A R T I C L E The flickering connectivity system of the north Andean páramos Suzette G.A. Flantua1,2  | Aaron O'Dea3  | Renske E. Onstein4  | Catalina Giraldo1,5,6 | Henry Hooghiemstra1 This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Journal of Biogeography Published by John Wiley & Sons Ltd. Editor: Alexandre Antonelli 1Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, The Netherlands 2Department of Biological Sciences, University of Bergen, Bergen, Norway 3Smithsonian Tropical Research Institute, Balboa, Republic of Panama 4German Centre for Integrative Biodiversity Research (iDiv), Halle‐Jena‐Leipzich, Leipzig, Germany 5Piet Zwart Institute, Willem de Kooning Academy, Hogeschool Rotterdam, Rotterdam, The Netherlands 6Fundación Biodiversa Colombia, Bogotá, D.C., Colombia Correspondence Suzette G.A. Flantua, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, The Netherlands Email: s.g.a.flantua@gmail.com Funding information Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Number: 2012/13248/ALW; Hugo de Vries foundation ‐ Amsterdam; Sistema Nacional de Investigadores (SNI) de SENACYT; Deutsche Forschungsgemeinschaft (DFG), Grant/Award Number: FZT 118; NUFFIC Abstract Aim: To quantify the effect of Pleistocene climate fluctuations on habitat connectiv‐ ity across páramos in the Northern Andes. Location: Northern Andes. Methods: The unique páramos habitat underwent dynamic shifts in elevation in re‐ sponse to changing climate conditions during the Pleistocene. The lower boundary of the páramos is defined by the upper forest line, which is known to be highly respon‐ sive to temperature. Here, we reconstruct the extent and connectivity of páramos over the last 1 million years (Myr) by reconstructing the upper forest line from the long fossil pollen record of Funza09, Colombia, and applying it to spatial mapping on modern topographies across the Northern Andes for 752 time slices. Data provide an estimate of how often and for how long different elevations were occupied by pára‐ mos and estimate their connectivity to provide insights into the role of topography in biogeographical patterns of páramos. Results: Our findings show that connectivity amongst páramos of the Northern Andes was highly dynamic, both within and across mountain ranges. Connectivity amongst páramos peaked during extreme glacial periods but intermediate cool stadi‐ als and mild interstadials dominated the climate system. These variable degrees of connectivity through time result in what we term the ‘flickering connectivity sys‐ tem’. We provide a visualization (video) to showcase this phenomenon. Patterns of connectivity in the Northern Andes contradict patterns observed in other mountain ranges of differing topographies. Main conclusions: Pleistocene climate change was the driver of significant eleva‐ tional and spatial shifts in páramos causing dynamic changes in habitat connectiv‐ ity across and within all mountain ranges. Some generalities emerge, including the fact that connectivity was greatest during the most ephemeral of times. However, the timing, duration and degree of connectivity varied substantially among mountain ranges depending on their topographical configuration. The flickering connectivity 2  |     FLANTUA eT AL. 1  | INTRODUC TION Mountains are regarded as powerhouses of biodiversity in the world (Antonelli et al., 2018; Barthlott, Rafiqpoor, Kier, & Kreft, 2005; Kreft & Jetz, 2007) and harbour numerous examples of very rapid and re‐ cent species diversifications (‘radiations’; Hughes & Atchison, 2015). It is thought that a large part of this diversity arose geologically re‐ cently, during the Plio‐Pleistocene (last 5.3 million years [Myr]), but there is no consensus on the drivers of these radiations. One favoured hypothesis is that the combination of high topographical relief and Plio‐Pleistocene climatic oscillations led to rapidly changing distribu‐ tions of montane species, which generated new lineages (e.g. Graham et al., 2014; Mutke, Jacobs, Meyers, Henning, & Weigend, 2014; Qian & Ricklefs, 2000). However, the relative contributions of isolation (e.g. Schönswetter, Stehlik, Holderegger, & Tribsch, 2005; Wallis, Waters, Upton, & Craw, 2016; Weir, Haddrath, Robertson, Colbourne, & Baker, 2016) versus gene flow and dispersal (e.g. Cadena, Pedraza, & Brumfield, 2016; Knowles & Massatti, 2017; Kolář, Dušková, & Sklenář, 2016; Smith et al., 2014) in driving fast diversification rates (i.e. the ‘species‐pump’ effect, Rull, 2005; Rull & Nogué, 2007; Winkworth, Wagstaff, Glenny, & Lockhart, 2005; Ramírez‐Barahona & Eguiarte, 2013; Steinbauer et al., 2016; Flantua & Hooghiemstra, 2018) are still debated. It is likely that these radiations have been the results of the interchange between phases of isolation, causing allo‐ patric, in situ speciation, and connectivity, triggering diversification through dispersal and settlement in new areas and hybridization of differentiated taxa from previously isolated populations (Flantua & Hooghiemstra, 2018). The fastest and most spectacular radiations may therefore occur in mountain regions with variable degrees of past connectivity and isolation during climate fluctuations, which, complex in space and time, are inherently related to the mountain topography (Flantua & Hooghiemstra, 2018). It is therefore critical to quantify connectivity of montane habitats using our understanding of topography and past climate fluctuations (Figure 1). The Northern Andes is an ideal model system to quantify con‐ nectivity, due to the large variation in topography and the advanced palaeoecological knowledge on Plio‐Pleistocene climate fluctuations derived during the last five decades (Hooghiemstra & Flantua, 2019). The Northern Andes is topographically rich with high elevations, steep ridges and valleys (see illustrations by Von Humboldt during his trips in Latin America, 1773–1858), composed of several mountain ranges, some of which are parallel running from North to South. The area hosts the treeless tundra‐like alpine biome, the páramos, regarded as the richest alpine flora in the world in terms of endemism and species richness (Sklenář, Hedberg, & Cleef, 2014) and is known for its bursts of Plio‐Pleistocene species diversification amongst plants (Hughes & Atchison, 2015; Madriñán, Cortés, & Richardson, 2013). In terms of quantifying Plio‐Pleistocene temperature fluctuations, the palaeoeco‐ logical history of the páramos has been studied extensively (e.g. Cleef, 1979; Hooghiemstra, 1984; Hooghiemstra & Van der Hammen, 2004; Van der Hammen, 1974; Van der Hammen & Cleef, 1986) because of the unique high elevation fossil pollen records that cover most of the Pleistocene (Bogotá‐A, Hooghiemstra, & Berrio, 2016; Bogotá‐Angel et al., 2011; Groot, Hooghiemstra, Berrio, & Giraldo, 2013; Groot et al., 2011; Torres, Hooghiemstra, Lourens, & Tzedakis, 2013). Under cur‐ rent conditions, the páramos form isolated archipelagos of ‘alpine (sky) islands’ (McCormack, Huang, & Knowles, 2009; Sklenář et al., 2014) but the rich collection of fossil pollen sequences throughout this region (Flantua et al., 2015) show that the páramos underwent substantial el‐ evational shifts during the Pleistocene, resulting in extensive changes in surface area and connectivity (Flantua et al., 2014; Hooghiemstra & Van der Hammen, 2004; Sklenář et al., 2014; Van der Hammen, 1974). Thus, the topographical diversity and the robust catalogue of palaeo‐ ecological reconstructions make the Northern Andes a highly suitable model region to explore patterns of connectivity in mountain biomes in response to Pleistocene climate fluctuations. In this study, we aim to quantify the biogeographic changes of the páramos in terms of spatial scale and connectivity based on modern to‐ pography and pollen‐based records of past climate change. Specifically, we developed a novel tool to explore the complex temporal and spa‐ tial patterns of páramo connectivity. We constrain our model by using the last 1 Myr of the high‐resolution fossil pollen record of Funza09, a composite 586 m deep core taken from the Bogotá basin of Colombia (Torres et al., 2013). Available surface area (Elsen & Tingley, 2015) and connectivity (Bertuzzo et al., 2016; Flantua & Hooghiemstra, 2017; Flantua et al., 2014) is variable along elevational gradients of mountains. We therefore hypothesize that the different mountain ranges that com‐ pose the Northern Andes display variable patterns of past páramo con‐ nectivity dependent upon their topography (Figure 1). We discuss the implications of our outcomes for evolutionary processes and how defin‐ ing and quantifying past connectivity in mountain systems is essential to help reveal mechanisms of ecological, biogeographical and evolu‐ tionary change. Ultimately, our quantification of páramo connectivity through space and time provides a unique opportunity to disentangle some of the mechanistic drivers (‘modulators’) of radiations in this biome (Bouchenak‐Khelladi, Onstein, Xing, Schwery, & Linder, 2015). system of the páramos uncovers the dynamic settings in which evolutionary radia‐ tions shaped the most diverse alpine biome on Earth. K E Y W O R D S alpine biome, evolutionary arenas, evolutionary radiations, flickering connectivity system, fossil pollen, mountain fingerprint, neotropical biodiversity, Páramos, past habitat connectivity, species pump      |  3FLANTUA eT AL. 2  | MATERIAL AND METHODS 2.1 | Geographical features The Northern Andes (ca. 448,000 km2) covers parts of Venezuela, Colombia and Ecuador (Figure 2a), and can be partitioned into six principal mountain ranges or ‘cordilleras’ (Figure 2c), namely the Sierra Nevada de Santa Marta (SNSM), Cordillera de Mérida, Eastern, Central and Western Cordillera and the Ecuadorian Cordilleras. Most of the Northern Andes is considered a highly to extremely high rugged landscape (Figure 2b; See mountain illustrations by Von F I G U R E 1  Connectivity and fragmentation in a mountain landscape. Connectivity (blue) and fragmentation (orange) events occurred in a spatially and temporally variable manner. This complex pattern in space (latitude, longitude, elevation) and time resemble a multi‐dimensional ‘mountain fingerprint’ which is unique for each mountain range (Flantua & Hooghiemstra, 2018). Three hypothetical mountain profiles are shown where elevational shifts in vegetation distribution driven by climate change (pollen‐based record at the left indicating temperature) cause events of increased fragmentation (F) and connectivity (C) of mountain ecosystems. We recognize mountains where (a) only few events of connectivity occurred during the Pleistocene compared to fragmentation events (‘fragmentation‐prone mountain fingerprint’), (b) connectivity events interchanged with isolation events in an evenly manner (‘mixed connectivity‐ fragmentation mountain fingerprint’), (c) connectivity is facilitated and occurred more often than fragmentation events (‘connectivity‐prone mountain fingerprint’). The right panel is only based on frequency, not the duration of each event 4  |     FLANTUA eT AL. Humboldt, 1845) where the high peaks and deep inter‐Andean val‐ leys cause strong contrasts in climate throughout the region (Flantua et al., 2016). Surface area in mountains does not decrease mono‐ tonically with elevation as has been shown previously in southern Colombia by Flantua et al. (2014) and on a global scale by Elsen and Tingley (2015). The Northern Andes shows a decrease of surface area going upslope where there is a slight peak around 900–1,200 m above sea level (a.s.l.) but then continues to decrease up to 6,260 m a.s.l. (Figure 2d), following a typical ‘pyramid shape’. However, the different cordilleras show different patterns of elevational surface area (Figure 2d) where the Eastern Cordillera shows a sharp peak around 2,600 m a.s.l. and the Ecuadorian Cordillera shows high val‐ ues of surface area at much higher elevations than the other cor‐ dilleras (for more details see Table S1.1, Appendix S1 in Supporting Information). The páramos today are spread out over the Northern Andes as a ‘mountain archipelago’ of small and highly fragmented páramo complexes (See Figs S2.1, S2.2 for more details and photos of different páramo complexes) but their full range also cover iso‐ lated páramo islands in Costa Rica and northern Peru (Luteyn, 1999). Of all tropical alpine floras, such as in East Africa and New Guinea, the páramos are home to the highest species richness and endemism (Luteyn, 1999; Sklenář et al., 2014), with low between‐mountain sim‐ ilarity in species (Sklenář et al., 2014). They also provide numerous ecosystem services on a local and regional scale (Herzog, Martínez, Jørgensen, Tiesse, 2011) and references therein), and especially in terms of hydrological services, they are vital for the provision of fresh water to several large cities in South America, such as Bogotá, Medellín, Quito, Cuenca, Piura and Cajamarca. 2.2 | Quantifying temperature and upper forest line based on fossil pollen data To quantify temperature fluctuations during the Pleistocene (and consequently estimate páramo connectivity), we used fossil pol‐ len data from the Northern Andes. The composite pollen record Funza09 (4.83°N, 75.2°W; 2,550 m a.s.l., Fig. S2.1. Red star) re‐ veals vegetation and climate dynamics over the past 2.25 Myr (Torres et al., 2013). We reconstructed the páramos’ elevational fluctuations, and consequently páramo connectivity, by estimat‐ ing the upper forest line (UFL; the transition from the upper mon‐ tane forest to the páramos) from the Funza09 record. Though this record covers the last 2.25 Myr, we only used the last 1 Myr as this interval reflects continuous lake conditions in comparison with variable hydrological conditions between 2.2 and 1 million years ago (Ma) which makes a quantification of changes to the UFL less precise. We follow the methodology described and implemented by Hooghiemstra (1984), Groot et al. (2011) and Hooghiemstra et al. (2012) to derive the Andean UFL and palaeotemperature curve (for detailed methodology on the UFL reconstruction see Appendix S3). F I G U R E 2  Hypsographical curves of the Northern Andes. (a) Elevation (m a.s.l.). (b) Terrain ruggedness index calculates the sum change in elevation between a grid cell and its eight neighbour grid cells (Riley, DeGloria, & Elliot, 1999) using a ca. 30 m DEM (NASA STRM Global 1arc second V003). (c) Delimitation of mountain ranges. (d) Elevational availability of surface area for the Northern Andes and each mountain range separately shown for 100 m bins. Hypsographical curves based on the Shuttle Radar Topography Mission 1‐arc second Digital Terrain Elevation Data (~30 m resolution; USGS), taking an elevational threshold of 500 m a.s.l. as the horizontal reference plane. Maximum elevation per cordillera is indicated. VEN: Venezuela; COL: Colombia; ECU: Ecuador VEN COL ECU Elevation (m asl) 13 6261 4040 Terrain Ruggedness Index(m) 0 2010 15 00 50 0 25 00 35 00 45 00 55 00 3 2Area (10 km ) Eastern Cordillera max elevation Central Cordillera Cord. Merida Western Cordillera E le va tio n (m as l) EcuadorSN SM (a) (b) (d) Northern Andes Mountain ranges (c) Eastern Cordillera Central Cordillera Ecuadorian cordilleras Western Cordillera Cordillera de Mérida Sierra Nevada de Santa Marta (SNSM) 41 1 2 4 6 2 6 2 2 40 0º 10ºN 70ºW80ºW      |  5FLANTUA eT AL. 2.3 | Calculations of connectivity per páramo ‘island’ To calculate the degree of connectivity between páramos, we used a graph‐based habitat availability index called probability of con‐ nectivity (PC) metric. This metric takes into account the area of the páramo ‘island’ itself and the distances to other islands where a user‐defined distance threshold defines the ‘reachability’ of other islands (Saura, Estreguil, Mouton, & Rodríguez‐Freire, 2011; Saura & Pascual‐Hortal, 2007), even if they are not physically connected (i.e. ‘structural connectivity’, Tischendorf & Fahrig, 2000). The metric as‐ signs a value to each páramo island representing its contribution in maintaining the overall connectivity of the páramo biome (Saura & Pascual‐Hortal, 2007; Saura et al., 2011). The total PC is built up in three ‘fractions’, namely the ‘intrapatch’, the ‘flux’ and the ‘connec‐ tor’ fractions (Saura & Rubio, 2010). The first fraction focuses on the available surface area and habitat quality (if applicable) within the in‐ dividual island. The second fraction assesses how well the individual island is connected to other islands given additional importance to the other islands’ attributes (surface and quality) and its strategic position to other páramo islands. The third fraction quantifies the contribution of the island to maintain connectivity between the rest of the islands, in other words its role as an intermediate stepping stone between non‐adjacent islands. Additionally, we calculated the equivalent connected area (ECA), which is derived directly from the PC, as a measure of the overall connectivity of a region (Saura et al., 2011). Here, Conefor SenSinode (V2.2; Saura & Pascual‐Hortal, 2007; Saura & Torné, 2009) and ESRI ArCGIS 10.3 (ESRI, 2014) were used to calculate the straight‐line distances between islands, the PC and ECA. We calculated connectivity for the entire Northern Andes and for each mountain range separately. 2.4 | Calculations of corridors between páramo islands We identified corridors between páramo islands within and between cordilleras under different climatic conditions. We used the GnArly lAndSCApe UtilitieS (V0.1.3; McRae, Shirk, & Platt, 2013) with ESRI ArCGIS 10.3 to create a raster grid of ‘landscape resistance’ based on ruggedness (Figure 2b) and habitat suitability. We assumed an increased landscape resistance with increased ruggedness, assign‐ ing values between 0 (no resistance) to 100 (maximum resistance) using an equal interval classification. For the habitat suitability map, we started by assigning a ‘perfectly suitable’ score of 100 to each páramo island, while outside the island the score of 0 reflects maxi‐ mum unsuitability. To soften this boundary, an exponential decay function was then used by increasing resistance in five elevational steps of 100 m where we assigned a suitability score of 40 to the boundary of the páramo. As a result of the decay function the high‐ est suitability of páramo – its core area – was restrained 200 m above the UFL and 200 m below the snowline. We used linkAGe mApper to calculate the least‐cost pathways, or corridors, based on the produced raster grid of landscape resistance (McRae & Kavanagh, 2011). These corridors are expressed as ‘con‐ ductance maps’ that represent gradients of cumulative corridors. Where the densities of corridors is highest, it is assumed that there is a high probability of dispersal and migration possible between is‐ lands (McRae, Dickson, Keitt, & Shah, 2008). The full landscape of the Northern Andes is considered an area where corridors could exist, with exception of the region between SNSM and the Sierra de Perijá (Fig. S2.1). We resampled the 30 m Digital Elevation Model (DEM, Figure 2) to a 1 km resolution to reduce computing time for each linkAGe mAp- per down to on average 2 hr. We allowed linkAGe mApper to create cor‐ ridors through (instead of only between) core areas to represent the full arsenal of connectivity through the landscape. Only corridors between páramo islands larger than 1 km2 were considered at any given moment in time. From the final output maps, only values lower than 200k conductance (default threshold) are selected to highlight the strongest corridors. The outputs were weighted according to the percentage of time they occurred during the last 1 Myr. 3  | RESULTS 3.1 | A million years of temperature fluctuations Temperatures at Funza (2,550 m a.s.l.) are estimated to have fluc‐ tuated between ca. 15 and 6°C causing an estimated maximum 1,600 m elevational shift of the UFL between ca. 3,500 and ca. 1,900 m a.s.l. (Figure 3). The Pleistocene glacial‐interglacial dy‐ namics were not replicated cycles of temperature change showing repeated patterns of high and lows, but display a high temporal vari‐ ability between each glacial‐interglacial cycle. Conditions similar to the current warm, interglacial conditions occurred several times dur‐ ing the last 1 Myr and accounted for around a quarter of the time. Extreme cool glacial conditions, ~6–8°C cooler than today, were relatively rare, occurring less than 10 percent of the time. On the whole, intermediate cool stadials and mild interstadials dominated the last 1 Myr, occurring over two‐thirds of the time. 3.2 | Calculations of páramo connectivity Our estimations on the spatial and elevational extent of ancient páramos and their connectedness at different times in the past reveals that páramos underwent frequent spatial alterations be‐ tween fragmented and connected spatial configurations, but the exact patterns were highly dependent on mountain chain topogra‐ phy (Figure 4a,b. See Appendices S4 and S5). The páramos in the Ecuadorian Cordillera generally maintained a high degree of con‐ nectivity over the last 1 Myr, rarely enduring severe fragmentation. Fragmentation did however occur when the snowline plunged signif‐ icantly during colder and wetter glacial periods, causing a break up of páramo areas on lateral flanks of the mountains. Likewise, the level of connectivity between páramos on the Central Cordillera frag‐ mented substantially through a descending snowline, breaking the upper elevation limit of páramo connectivity. In contrast, the Eastern 6  |     FLANTUA eT AL. Cordillera shifted substantially between periods of connectivity and fragmentation, always, however, maintaining two large páramo islands surrounded by smaller ‘satellite islands’. Páramos in the Cordillera de Mérida seem to have been restricted during interglaci‐ als to one core area only, while during colder periods a relatively high fragmentation is observed possibly due to glaciers pushing páramos to lateral distributions. Here, connectivity increased mainly towards the southwest and during colder periods (UFL ≤ 2,300 m a.s.l.). The páramos of the SNSM and the Western Cordillera endured the high‐ est degree of rates of change in fragmentation of all ranges. In the latter, páramo habitats are estimated to have often completely dis‐ appeared. In contrast, páramos of the Central Cordillera maintained a long latitudinal distribution, forming a chain of isolated populations in small patches that on the whole remained connected. Even in very cold conditions, no continuous connectivity of core areas seems to have been possible between the Eastern Cordillera and Cordillera de Mérida, or the region of Sierra de Perijá. Towards the south of the Eastern Cordillera a low‐elevation barrier was possibly crossed at 1,900 m a.s.l. forming a brief bridge suitable for páramo habitat into the Macizo Colombiano of the Central Cordillera. The reconstruction of putative corridors shows a complex spa‐ tial pattern through the mountainous landscapes of the Northern Andes (Figure 5a,b). The long ridge of the Central Cordillera forms the starting point of numerous corridors to the páramos in the Western Cordillera. The Eastern Cordillera shows a complex inter‐ nal pattern of corridors, where there are neither strong corridors towards Sierra de Perijá in the North, nor towards the Cordillera de Mérida, while a high concentration of corridors is found between the large páramos complexes in the Eastern Cordillera (Páramos of Boyacá and Cundinamarca, Fig. S2.1). In the Ecuadorian Cordillera a more lateral pattern of high/low potential corridors is observed following the intra‐Andean valleys and peaks within this mountain range. Corridors to the southernmost páramos of Ecuador as also the northernmost páramos of the Western Cordillera are weak and occurred infrequent during the last million years, shown by the thin lines. 3.3 | Flickering connectivity systems Páramo connectivity through time shows a highly variable pattern (Figure 6a) introduced by Flantua and Hooghiemstra (2018) as a flickering connectivity system (see visualization video in Appendix S6). We find support for the hypothesis that this system with fluctu‐ ating, highly variable connectivity in spatial and temporal dimension is unique for each mountain range of the Northern Andes (Figure 1). For example, changes in connectivity within the Ecuadorian Cordillera are substantial but the system ‘flickers’ around a high average when compared to other mountain ranges. The flickering connectivity sys‐ tems within the Eastern and Central Cordillera are surprisingly similar, though the peaks of connectivity during glacial periods and the dips of connectivity during interglacials are more extreme in the former (Figure 6a). The Western Cordillera is a larger mountain range than the Cordillera of Mérida and the SNSM (Table S1.1), and its variation of connectivity has been correspondingly larger (Figure 6b) but with the lowest occurrence of connectivity compared to the other mountain ranges (Figure 6a). Considering only the frequency in the distribution of data (Figure 6b), the Ecuadorian Cordillera and the SNSM stand out for their relatively small within‐mountain range variation in connectiv‐ ity, compared to the Eastern and Central Cordillera (similar patterns) and the Western Cordillera. When frequencies of connectivity are weighted by the amount of time that connectivity lasted two main patterns emerge (Figure 6c). The first is shared by the Western, Central and Eastern Cordilleras, which all display an elongated pattern where the highest values are around a centroid, resembling a ‘humming top’ or, as Elsen and Tingley (2015) recognized in mountain hypsographies, a ‘diamond’ shape. Ecuadorian Cordilleras, Cordillera de Mérida and SNSM instead reveal a different pattern with a narrower centroid that widens towards the upper and lower section, resembling an ‘hourglass’ shape. Here, the Ecuadorian Cordillera and SNSM show a surprising similarity though at different connectivity ranges. The Central and Eastern Cordilleras are strikingly similar overall. 4  | DISCUSSION 4.1 | Variable degrees of past connectivity of different mountain ranges Although currently isolated, evolutionary radiations and the as‐ sembly of the páramo ecosystem formed during times when the páramos were flickering in and out of different degrees of connec‐ tivity (Figure 6). The concept of ‘mountain fingerprints’ (Flantua & F I G U R E 3  Upper forest line (UFL) curve of Funza09 (Torres et al., 2013) and reconstructed temperature record covering the last 1 Myr (last ca. 30 kyr BP not included) 6.2 Funza09 (Torres et al. 2013) 2800 3200 3500 2400 2000 11.3 15.2 100 kyr cycle (eccentricity) 41 kyr cycle (obliquity) Millions of years ago Te m pe ra tu re ( C ) a t Fu nz a (2 55 0 m a .s .l. ) ° UFL (m asl) Oak forest abundantly presentAndean forest with Alder, without Oak 1 0.5 0.05 8.6 13.7 Warm interglacials (24 %) Cool stadials and interstadials (68%) maximum glacials (8 %) duration (% of last 1 Myr) 0 4 8 102 6 12 14 %      |  7FLANTUA eT AL. F I G U R E 4  Páramo connectivity at different upper forest line (UFL) elevations. (a) Probability of connectivity metric (PC; distance = 10 km, p = 0.5; Saura & Rubio, 2010) calculated for all páramos larger than 1 km2. Maps are plotted with natural‐breaks classification. Temperature at 2,550 m elevation are relative to the present. (b) Frequency bar indicates when the corresponding UFL elevation occurred during the last 1 Myr. See Appendices S4 and S5 for all maps and frequencies 70º80ºW ΔT : + 1.8 °CΔT : + 0.6 °C ΔT : - 0.6 °CΔT : - 1.8 °CΔT : - 4.2 °C ΔT : - 3.0 °C UFL 2500 m UFL 2700 m UFL 3500 m ΔT : - 7.8 °C UFL 1900 m UFL 2100 m UFL 2900 m UFL 3100 m UFL 3300 m Connectivity (PC) 0.03 1 Ma Frequency bar 0.02 - 0.22 No páramo 0.23 - 0.74 0.75 - 3.97 3.98 - 9.35 9.36 - 98.84 (a) (b) UFL 2300 m ΔT : - 5.4 °CΔT : - 6.6 °C 0º 10ºN 8  |     FLANTUA eT AL. F I G U R E 5  Dispersal pathways among páramos during the last 1 Myr weighted by frequency and duration. (a) Least cost pathways calculated by the cost weighted distance to path length – ratio. Circuit model (McRae et al., 2008) expressed in cumulative current flow density using the full range of values (b) and only the strongest corridors (threshold of 200k used) before calculating the weighted sum (c). Areas with low least cost pathways (a) and high current flows (b and c) indicate frequent and highly possible corridors during the last 1 Myr 0 - 2449 2450 - 6663 6664 - 12.069 12.070 - 18.143 18.144 - 34.457 70ºW80ºW 0º 10ºN (a) High Low High Low Cumulative current flow density Cost weighted distance to path length - ratio (b) Cumulative current flow density (top range) (c) Absent F I G U R E 6  The ‘Flickering Connectivity System’ of the Northern Andes. (a) Páramo connectivity (here expressed as equivalent connected area, ECA) through time (1,000–30 kyr BP) for each cordillera. ECA has area units (m2) representing the amount of ‘reachable or available habitat area’ (Saura et al., 2011). (b) ‘Beanplots’ (Kampstra, 2008) or ‘violin plot’ showing kernel densities summarizing the data distribution of past connectivity of each cordillera, only considering how often certain degree of connectivity occurred, not how long it lasted. (c) Beanplot showing kernel densities summarizing the data distribution of past connectivity of each cordillera multiplied by how long connectivity persisted to represent both how often an event occurred and how long it lasted C on ne ct iv ity (E C A ) Time (kyr BP) C on ne ct iv ity (E C A ) (a) (b) 810 910 1010 810 910 1110 1010 1000 750 500 250 0 Eastern Cordillera Ecuador Mérida SNSM Central Cordillera Western Cordillera (c) 103x10 102x10 1010 0 Density plot (frequency) Density plot (frequency*duration) Páramo connectivity through time E as te rn C or di lle ra E cu ad or M ér id a S N S M C en tra l C or di lle ra W es te rn C or di lle ra E as te rn C or di lle ra E cu ad or M ér id a S N S M C en tra l C or di lle ra W es te rn C or di lle ra      |  9FLANTUA eT AL. T A B L E 1   O ve rv ie w o f s tu di es w it h ph yl og eo gr ap hi c/ ph yl og en et ic /b io ge og ra ph ic al s up po rt f or t he f lic ke ri ng c on ne ct iv it y sy st em in t he N or th er n A nd es . N ot e th at t hi s is n ot a co m pr eh en si ve li st a nd is o nl y ai m ed a t pr ov id in g an o ve rv ie w o f a va ila bl e st ud ie s Le ve l o f a na ly si s/ M ou nt ai n ra ng e G ro up Ta xo n Fa m ily D at as et /m ar ke rs A pp ro ac h Re su lt/ fin di ng Re fe re nc e Ec ua do ria n C or di lle ra B ir ds Sp in us Fr in gi lli da e cy t b, N D 2, N D 3, M U SK , M YO 2 P hy lo ge ne ti c R ec en t ra di at io n B ec km an a nd W it t (2 01 5) A nd es P la nt s Va le ria na V al er ia na ce ae ps bA ‐t rn H in tr on , t rn K ‐ m at K in tr on , t rn L‐ F, IT S P hy lo ge ne ti c R ec en t ra di at io n B el l a nd D on og hu e (2 0 05 ) Ea st er n an d C en tr al C or di lle ra B ir ds Bu ar re m on Em be ri zi da e N D 2, c yt b , A TP as e 6, A TP as e 8, A C O 1, M U SK P hy lo ge og ra ph ic H ig h ge ne ti c di ve rg en ce C ad en a, K lic ka , a nd R ic kl ef s (2 0 07 ) W es te rn a nd C en tr al C or di lle ra B ir ds Bu ar re m on Em be ri zi da e N D 2, c yt b , A TP as e 6, A TP as e 8, A C O 1, M U SK P hy lo ge og ra ph ic H ig h ge ne ti c re se m bl an ce a nd li ke ly h ig h m ig ra ti on C ad en a et a l. (2 0 07 ) A nd es P la nt s O re ob ol us C yp er ac ea IT S, t rn L in ro n an d tr nL ‐F in te rg en ic s pa ce r P hy lo ge ne ti c R ec en t ra di at io n; S ou th t o no rt h m ig ra ti on C ha có n, M ad ri ñá n, C ha se , an d B ru hl (2 0 06 ) A nd es B ir ds M us ci sa xi co la Ty ra nn id ae C O II an d N D 3 P hy lo ge ne ti c R ec en t ra di at io n C he ss er (2 0 0 0) C en tr al a nd Ea st er n C or di lle ra , Ec ua do ria l C or di lle ra P la nt s Lu pi nu s Le gu m in os ae G en om e‐ sc al e ne xt R A D se q P hy lo ge og ra ph ic / P hy lo ge no m ic H ig h ge ne ti c di ve rg en ce C on tr er as ‐O rt iz , A tc hi so n, H ug he s, a nd M ad ri ňá n (2 01 8) C en tr al a nd E as te rn C or di lle ra P la nt s Es pe le tia A st er ac ea e G en ot yp in g by s eq ue nc in g P hy lo ge og ra ph ic R ap id m or ph ol og ic al r ad ia ti on s C or té s, G ar zó n, V al en ci a, an d M ad ri ñá n (2 01 8) N or th er n A nd es P la nt s Ca lc eo la ria C al ce ol ar ia ce ae IT S, m at K a nd m or ph ol og y P hy lo ge ne ti c R ec en t ra di at io n C os ac ov e t al . ( 20 09 ) N or th er n A nd es P la nt s Es pe le ti in ae A st er ac ea e n. a. B io ge og ra ph ic St ep ‐w is e bu t ir re gu la r m ig ra ti on o f s pe ci es C ua tr ec as as (1 97 9, 2 01 3) Ea st er n C or di lle ra P la nt s Es pe le ti in ae A st er ac ea e IT S, E TS , r pl 16 , A FL P da ta P hy lo ge ne ti c H ig h ge ne ti c di ve rs it y in t he la rg er p ár am o co m pl ex es w it h m ul ti pl e di st in ct c la de s so m ew ha t re la te d to e ac h ot he r D ia zg ra na do s an d B ar be r (2 01 7) Ea st er n C or di lle ra P la nt s Es pe le ti in ae A st er ac ea e IT S, E TS , r pl 16 , A FL P da ta P hy lo ge ne ti c H yb ri di za ti on D ia zg ra na do s an d B ar be r (2 01 7) Ec ua do ria n C or di lle ra P la nt s Se ne ci o A st er ac ea e IT S, A FL P da ta P hy lo ge ne ti c/ P hy lo ge og ra ph ic G en et ic d if fe re nc es b et w ee n no rt he rn a nd so ut he rn p op ul at io ns w it hi n Ec ua do r D uš ko vá e t al . ( 20 17 ) N or th er n A nd es P la nt s O xa lis O xa lia ce ae IT S an d nc pG S P hy lo ge ne ti c R ec en t ra di at io n Em sh w ill er (2 0 02 ) N or th er n A nd es P la nt s O re ob ol us C yp er ac ea IT S, t rn L‐ F, t rn H ‐p sb A a nd rp l3 2‐ tr nL P hy lo ge og ra ph ic In co m pl et e lin ea ge s or ti ng , c ry pt ic sp ec ia ti on , g en et ic d iv er ge nc e, s ug ge st s ev id en ce o f r ep ea te d vi ca ri an ce a nd s ec ‐ on da ry c on ta ct G óm ez ‐G ut ié rr ez e t al . (2 01 7) A nd es B ir ds M an y n. a. n. a. P hy lo ge ne ti c B io re gi on f or m at io ns c or re la te s w it h A nd ea n up lif t an d m ou nt ai n di sp er sa l fa ci lit at ed b y te m pe ra tu re o sc ill at io ns o f th e P le is to ce ne H az zi e t al . ( 20 18 ) (C on ti nu es ) 10  |     FLANTUA eT AL. Le ve l o f a na ly si s/ M ou nt ai n ra ng e G ro up Ta xo n Fa m ily D at as et /m ar ke rs A pp ro ac h Re su lt/ fin di ng Re fe re nc e C en tr al a nd E as te rn C or di lle ra P la nt s Lu pi nu s Le gu m in os ae IT S/ LE G C YC IA g en es P hy lo ge ne ti c R ec en t ra di at io n, h ig he r di ve rs if ic at io n at hi gh er e le va ti on s H ug he s an d Ea st w oo d (2 0 06 ); D ru m m on d, Ea st w oo d, M io tt o, a nd H ug he s (2 01 2) ; H ug he s an d A tc hi so n (2 01 5) Ea st er n an d C en tr al C or di lle ra P la nt s Pu ya B ro m el ia ce ae A FL P da ta P hy lo ge ne ti c G en et ic d iv er ge nc e, s ug ge st m ul ti pl e m ig ra ‐ ti on e ve nt s fr om t he E as te rn C or di lle ra t o th e W es te rn C or di lle ra Ja ba ily a nd S yt sm a (2 01 3) N or th er n A nd es P la nt s Pu ya B ro m el ia ce ae A FL P da ta P hy lo ge ne ti c St ep ‐w is e bu t ir re gu la r m ig ra ti on o f p ár am o pl an t sp ec ie s, r ec en t ra pi d ra da ti on Ja ba ily a nd S yt sm a (2 01 3) W es te rn a nd C en tr al C or di lle ra P la nt s Pu ya B ro m el ia ce ae A FL P da ta P hy lo ge ne ti c Fr eq ue nt g en e fl ow e ve nt s Ja ba ily a nd S yt sm a (2 01 3) Ec ua do ria n C or di lle ra P la nt s Lo ric ar ia A st er ac ea e A FL P an d pl as ti d D N A P hy lo ge og ra ph ic St ep ‐w is e bu t ir re gu la r m ig ra ti on o f p ár am o pl an t sp ec ie s K ol ář e t al . ( 20 16 ) Ec ua do ria n C or di lle ra P la nt s Lo ric ar ia A st er ac ea e A FL P an d pl as ti d D N A P hy lo ge og ra ph ic La ck o f g en et ic d iv er ge nc e. S ug ge st s ex te n‐ si ve g en e fl ow . K ol ář e t al . ( 20 16 ) A nd es P la nt s M an y n. a. n. a. P hy lo ge ne ti c En vi ro nm en ta l c ha ng e, a da pt at io n an d bi ot ic in te ra ct io ns a s dr iv er s of A nd ea n ra di at io ns Lu eb er t an d W ei ge nd (2 01 4) A nd es P la nt s Po ly st ic hu m D ry op te ri da ce ae C yt os ol ic p ho sp ho gl uc os e is om er as e ge ne P hy lo ge ne ti c G en e ev ol ut io n du ri ng r ad ia ti on Ly on s, M cH en ry , a nd B ar ri ng to n (2 01 7) N or th er n A nd es P la nt s M an y A st er ac ea e n. a. P hy lo ge ne ti c R ec en t ra di at io n M ad ri ñá n et a l. (2 01 3) A nd es P la nt s Po ly st ic hu m D ry op te ri da ce ae tr nS ‐r ps 4, r bc L P hy lo ge ne ti c R ec en t ra di at io n, m ul ti pl e se co nd ar y di sp er ‐ sa l e ve nt s fr om c en tr al A nd es t o N or th er n A nd es M cH en ry a nd B ar ri ng to n (2 01 4) N or th er n A nd es P la nt s La ch em ill a R os ac ea e IT S, t rn L‐ F P hy lo ge ne ti c R ec en t ra di at io n M or al es ‐B ri on es , R om ol er ou x, K ol ář , a nd Ta nk (2 01 8) C en tr al a nd E as te rn C or di lle ra P la nt s Lu pi nu s Le gu m in os ae G en om ic a nd t ra ns cr ip ‐ to m ic d at a P hy lo ge no m ic / P hy lo ge og ra ph ic H ig h ge ne ti c di ve rg en ce b ut e ve nt s of g en e fl ow d et ec te d N ev ad o et a l. (2 01 8) Ea st er n C or di lle ra P la nt s Lu pi nu s Le gu m in os ae G en om ic a nd t ra ns cr ip ‐ to m ic d at a P hy lo ge no m ic / P hy lo ge og ra ph ic H ig h ge ne ti c di ve rs it y in t he la rg er p ár am o co m pl ex es w it h m ul ti pl e di st in ct c la de s so m ew ha t re la te d to e ac h ot he r N ev ad o et a l. (2 01 8) Ea st er n C or di lle ra P la nt s Lu pi nu s Le gu m in os ae G en om ic a nd t ra ns cr ip ‐ to m ic d at a P hy lo ge no m ic / P hy lo ge og ra ph ic H yb ri di za ti on N ev ad o et a l. (2 01 8) T A B L E 1   (C on ti nu ed ) (C on ti nu es )      |  11FLANTUA eT AL. Le ve l o f a na ly si s/ M ou nt ai n ra ng e G ro up Ta xo n Fa m ily D at as et /m ar ke rs A pp ro ac h Re su lt/ fin di ng Re fe re nc e A nd es P la nt s H yp er ic um H yp er ic ac ea e n. a. n. a. Su gg es ts n ic he e xp an si on /e vo lu ti on a nd sh if ts in t em pe ra tu re o pt im a th at m ay h av e fa ci lit at ed p ár am o ra di at io ns N ür k, M ic hl in g, a nd Li nd er (2 01 7) A nd es P la nt s H yp er ic um H yp er ic ac ea e IT S P hy lo ge ne ti c R ec en t ra di at io n N ür k, S ch er ia u, a nd M ad ri ñá n (2 01 3) Ea st er n C or di lle ra an d M er id a C or di lle ra P la nt s Es pe le tia A st er ac ea e M et ab ol om ic s n. a. M et ab ol ic f in ge rp ri nt s lin ke d to h ig h ge ne ti c di ve rg en ce b ut w it h ev en ts o f g en e fl ow P ad ill a‐ G on zá le z, D ia zg ra na do s, a nd D a C os ta (2 01 7) W es te rn a nd C en tr al C or di lle ra P la nt s Es pe le tia A st er ac ea e M et ab ol om ic s n. a. A pp ar en t cl us te ri ng P ad ill a‐ G on zá le z et a l. (2 01 7) M er id a C or di lle ra , no rt he rn t ip o f Ea st er n C or di lle ra P la nt s Es pe le ti in ae A st er ac ea e W ho le p la st om es , d e no vo as se m bl y P hy lo ge no m ic H yb ri di za ti on , s ug ge st s tw o in de pe nd en t ce nt er s of r ad ia ti on s an d no d is pe rs al be tw ee n co rd ill er as . I nc re as e of d iv er si fi ‐ ca ti on d ur in g la st 1 M yr Po uc ho n et a l. (2 01 8) A nd es B ir ds M an y n. a. n. a. P hy lo ge ne ti c H ig he r di ve rs if ic at io n ra te s at h ig he r el ev at io ns Q ui nt er o an d Je tz (2 01 8) N or th er n A nd es P la nt s Es pe le ti a co m pl ex A st er ac ea e IT S P hy lo ge ne ti c R ec en t ra di at io n R au sc he r (2 0 02 ) A nd es B ir ds Pi on us P si tt ac id ae cy t a an d N D 2 P hy lo ge ne ti c R ec en t ra di at io n R ib as , M oy le , M iy ak i, an d C ra cr af t (2 0 07 ) N or th er n A nd es P la nt s Ja m es on ia ‐ Er io so ru s C om pl ex P te ri da ce ae E TS , 1 8S –2 6S r D N A , rp s4 , i nt er ge ni c sp ac er rp s4 ‐t rn S P hy lo ge ne ti c Fa st s pe ci at io n of p ár am o sp ec ie s, p os si bl y lin ke d to m or ph ol og ic al a da pt at io n Sá nc he z‐ B ar ac al do a nd T ho m as (2 01 4) N or th er n A nd es P la nt s Ja m es on ia , Er io so ru s P te ri da ce ae E TS , 1 8S –2 6S r D N A , rp s4 , i nt er ge ni c sp ac er rp s4 ‐t rn S P hy lo ge ne ti c R ec en t ra di at io n Sá nc he z‐ B ar ac al do (2 0 0 4) A nd es P la nt s As tr ag al us Le gu m in os ae IT S an d ch lo ro pl as t sp ac er s tr nD ‐t rn T an d tr nf M ‐t rn S1 P hy lo ge ne ti c R ec en t ra di at io n Sc he rs on , V id al , a nd Sa nd er so n (2 0 0 8) A nd es P la nt s Ba rt sia O ro ba nc ha ce ae tr nT –t rn F re gi on a nd t he rp s1 6 in tr on P hy lo ge ne ti c R ec en t ra di at io n, s ug ge st s to b e re la te d to di sp er si fi ca ti on U ri be ‐C on ve rs a nd T an k (2 01 5) A nd es P la nt s D ip lo st ep hi um A st er ac ea e IT S, r po B , r po C 1, a nd ps bA ‐t rn H P hy lo ge ne ti c R ad ia ti on o ri gi na te d in p ár am o, w it h di ve rs if ic at io n sl ow do w ns a ss oc ia te d w it h co lo ni za ti on o f A nd ea n fo re st s. P hy lo ge ny sh ow s la rg e un ce rt ai nt y. V ar ga s an d M ad ri ñá n (2 01 2) T A B L E 1   (C on ti nu ed ) (C on ti nu es ) 12  |     FLANTUA eT AL. Hooghiemstra, 2018) proposes that the region's complex topogra‐ phy would have meant that páramos in different mountain regions would have fragmented and connected at different periods of time, at different elevations, and with different rates and frequencies (as summarized in Figure 1). This means that in some mountain ranges the páramos are a mix of somewhat even occurrence of connectivity and fragmentation events through time (Figure 1b, exemplified by the Eastern Cordillera), or could have been dominantly fragmented (Figure 1a, e.g. Western Cordillera), or more connected (Figure 1c, e.g. Ecuadorian Cordilleras). These regional differences in the tem‐ poral and spatial variation in past páramo connectivity (Figures 4‒6) are likely to have resulted not only in regional differences in bio‐ geographical patterns through time, but also varying ecological and evolutionary processes. We therefore propose that our data and models can be used to test hypotheses of the drivers of species rich‐ ness, endemism and degrees of Pleistocene diversification in the Northern Andes, and the approach applicable to other mountain regions around the world. 4.2 | Evolutionary implications of the flickering connectivity system Several insightful schematic representations of Pleistocene diver‐ sification models in the Neotropics have been developed in recent years (Flantua & Hooghiemstra, 2018; Hazzi, Moreno, Ortiz‐Movliav, & Palacio, 2018; Ramírez‐Barahona & Eguiarte, 2013; Rull, 2005). Phylogeographical and phylogenetic synthesis work within and among páramo taxa is currently still largely lacking (see for instance Yu et al., 2019 for the Qinghai‐Tibet Plateau), inhibiting the direct testing of these models. However, here we highlight several recent studies that are considered valuable in the light of the flickering connectivity system reconstruction (see Table 1), emphasizing the expectation that the rapidly growing body of phylogeographical/ phylogenetic literature in the region will support future comparative analyses. The dynamic history of the páramos elucidated by the flicker‐ ing connectivity system can provide three important insights in terms of evolutionary processes. First of all, the regional differences in past páramo connectivity – the mountain fingerprint – support temporally and spatially discordant phylogeographical patterns (Massatti & Knowles, 2014; Papadopoulou & Knowles, 2015, 2016; Pennington et al., 2010). This means that the timing of diversification in the different mountain regions would not be expected to have occurred synchronously, even if all phylogenetic studies on páramo species could overcome current issues in model inference, taxon‐ omy and distribution, spatial resolution and time‐calibration points (Rull, 2011). Secondly, diversification rates might differ along the elevational gradient and this might be the rule rather than the ex‐ ception. Elevational differences in surface availability and connec‐ tivity (Bertuzzo et al., 2016; Flantua & Hooghiemstra, 2017; Flantua et al., 2014) are likely to influence at what elevation the strongest geographical processes will occur, and these processes are thus ex‐ pected to differ between mountain systems resulting in elevational L ev el o f a na ly si s/ M ou nt ai n ra ng e G ro up Ta xo n Fa m ily D at as et /m ar ke rs A pp ro ac h Re su lt/ fin di ng Re fe re nc e N or th er n A nd es P la nt s D ip lo st ep hi um A st er ac ea e C om pl et e nu cl ea r ri bo so ‐ m al c is tr on , t he c om pl et e ch lo ro pl as t ge no m e, a pa rt ia l m it oc ho nd ri al g e‐ no m e an d nu cl ea r‐ dd R A D P hy lo ge no m ic H yb ri di za ti on , r ec en t ra di at io n V ar ga s, O rt iz , a nd Si m ps on (2 01 7) Ea st er n C or di lle ra , C or di lle ra s of C ol om bi a P la nt s Lu pi nu s al op ec ur oi de s Le gu m in os ae 11 m ic ro sa te lli te m ar ke rs P hy lo ge og ra ph ic H ig h ge ne ti c di ve rs it y in t he la rg er p ár am o co m pl ex es w it h m ul ti pl e di st in ct c la de s so m ew ha t re la te d to e ac h ot he r V ás qu ez , B al sl ev , H an se n, Sk le ná ř, an d R om ol er ou x (2 01 6) A nd es P la nt s G en tia ne lla , H al en ia G en ti an ac ea e IT S, m at K , r pl 16 in tr on P hy lo ge ne ti c R ec en t ra di at io n vo n H ag en a nd K ad er ei t (2 0 01 , 2 0 03 ) A nd es B ir ds M an y n. a. n. a. P hy lo ge ne ti c R ec en t ra di at io n, in cr ea se in d iv er si fi ca ti on in la st 1 M yr W ei r (2 0 06 ) N or th er n A nd es P la nt s Es ca llo ni a Es ca llo ni ac ea e tr nH ‐p sb A , M YC , N IA P hy lo ge ne ti c R ec en t ra di at io n Z ap at a (2 01 3) T A B L E 1   (C on ti nu ed )      |  13FLANTUA eT AL. differences of diversification (see e.g. Hughes & Eastwood, 2006; Kropf, Kadereit, & Comes, 2003; Lagomarsino, Condamine, Antonelli, Mulch, & Davis, 2016; Quintero & Jetz, 2018). Furthermore, the cli‐ mate fluctuations of the Pleistocene caused connectivity to occur at different moments through time (Figure 1), a process facilitating the step‐wise but irregular migration of páramo plant species through‐ out the landscape, such as Puya, Loricaria and Espeletiinae (Table 1). Thirdly, the flickering connectivity system, which is expected to cause phases of increased isolation followed by increased connec‐ tivity of populations, is expected to result in pulses of diversification (Knowles, 2000), possibly resulting in series of sub‐radiations in the páramos. Where isolation resulted in allopatric, in situ speciation, connectivity triggered diversification through dispersal and settle‐ ment in new areas (‘dispersification’, Moore & Donoghue, 2007), and hybridization of previously isolated populations (Grant, 2014; Petit et al., 2003). Much evidence suggests that hybridization is not the processes of species becoming ‘reabsorbed’ into their parental forms but contributes by bringing evolutionary novelty and gene flow operating at different introgression rates (Dušková et al., 2017; Nevado, Contreras‐Ortiz, Hughes, & Filatov, 2018; Pouchon et al., 2018), and thus a likely trigger of speciation and morphological diver‐ sity. Interestingly, population‐level processes such as gene flow, dis‐ persification and hybridization, alongside periods of isolation, have been increasingly recognized to play out at the phylogenetic scale, leading to (rapid) lineage diversification, for example in mountains (e.g. Hazzi et al., 2018; Knowles & Massatti, 2017), tropical rain for‐ ests (e.g. Onstein et al., 2017) and islands (e.g. Ali & Aitchison, 2014). Interestingly, the Funza09 pollen record shows a clear increase in the amplitude of climate change around the mid‐Pleistocene tran‐ sition (ca. 0.9 Ma) coinciding with accelerated diversification of high elevation birds (Weir, 2006) and the Espeletiinae in the Cordillera de Mérida (Pouchon et al., 2018; Table 1). Indeed, these studies signal a potential link between the intensity of the flickering connectivity system and biological radiations (Flantua & Hooghiemstra, 2018). Thus, the flickering connectivity system is expected to have left an imprint on geographical patterning of genetic divergence (between populations) and within‐populations genetic diversity with obvious inter‐cordillera differences. Furthermore, extinction events may further complicate the observed patterns of divergence between cordilleras. 4.3 | Future research Our spatio‐temporal estimates of past connectivity lay a founda‐ tion for further research on elucidating the causal mechanisms of mountain diversifications (see also Appendix S7). Models of past connectivity (Figures 4‒6), when combined with phylogeographic data, could help reveal the role of interspecific gene flow and allopatric speciation in driving radiations in the high Andes and contribute to a better understanding of the relative importance of geography versus adaptive radiation that underpin Andean di‐ versifications. In such a complex system it may also be useful to pay attention to commonalities. For example, when considering both frequency and duration, our data show that two connectivity patterns emerge (i.e. hourglass versus non‐hourglass; Figure 6c). Research could explore if cordilleras with shared connectivity patterns also share phylogenetic histories and contemporary (en‐ demic) species’ biogeographies to test for universal mechanisms that have shaped present day alpine biomes. This would be espe‐ cially useful if used in conjunction with information on the repro‐ ductive life histories, growth and dispersal capacities of specific taxa. Finally, past patterns of connectivity are critical to interpret bio‐ geographical patterns of currently isolated or fragmented systems in a wide variety of terrestrial ecosystems including mountains (Flantua & Hooghiemstra, 2018), islands (e.g. Simpson, 1974; Weigelt, Steinbauer, Cabral, & Kreft, 2016; Norder et al., 2018), fresh water systems (e.g. Dias et al., 2014), rain forests (e.g. Graham, Moritz, & Williams, 2006), grasslands (e.g. Lindborg & Eriksson, 2004; Münzbergová et al., 2013) and marine coastal ecosystems (Hoeksema, 2007) that similarly expe‐ rienced major spatial changes during rapid sea‐level fluctuations over the Pleistocene. The approach developed here, to quantify historical connectivity, can therefore provide a platform for interpreting con‐ temporary biogeographies and past drivers of diversification in a wide array of both marine and terrestrial ecosystems where available space has been altered by climatic fluctuations. We postulate that quantify‐ ing flickering connectivity systems will facilitate a much more detailed and much needed quantitative basis to compare phylogeographic/ phylogenetic patterns, e.g. the Tibeto‐Himalayan region (Muellner‐ Riehl, 2019), and species (endemic) richness (e.g., Sklenář et al., 2014), from different mountain regions of the world. 5  | CONCLUSIONS We present a pollen record‐based biogeographical model for the páramo biome spanning the northern Andes (Venezuela, Colombia and Ecuador) over the last 1 Myr. Our models suggest substantial temperature oscillations where extreme temperature lows were ca. 8°C cooler than today, causing a total amplitude of the UFL of up to 1,600 vertical meters. These extreme cold events were, how‐ ever, rare (See frequency bars in Figure 4) and during glacial peri‐ ods most of the time cool stadial and interstadial climate conditions prevailed (Figure 3). Our analysis shows that páramos on all moun‐ tain ranges underwent frequent alterations between fragmented and connected configurations (Figures 4 and 5), but the estimated degrees and amount of connectivity varied among mountain ranges (Figure 6). Most páramos expanded during glacial periods even though extensive glaciers were present. To a large extent the cur‐ rent páramo distribution (located near their highest Pleistocene elevational position) was replaced by the lowermost ice extensions during the cool stadials, and during the coldest events replaced by the thick ice masses of mountain glaciers, implicating a substantial range size change of populations and a highly dynamic system dur‐ ing Pleistocene times. Depending on the location of initial dispersal – originating from ancestral areas – species would have experienced 14  |     FLANTUA eT AL. the flickering connectivity system differently and thus a mosaic of contrasting patterns of genetic divergence and diversity is expected among cordilleras mirroring the mountain fingerprint signatures. In light of Von Humboldt's work of relevance of different topog‐ raphies for mountain biota, we show that topography and climate change together dictated páramo connectivity through time with high spatial variability. The interplay of the topographical and pa‐ laeoclimatic conditions created a unique pattern of connecting and fragmenting páramo patches through time, here described as the flickering connectivity system. Our spatially explicit model quantifies the complexity of mountain biome dynamics during climate oscilla‐ tions, in terms of the degree, frequency and duration of past con‐ nectivity of high mountain biome (Figures 4‒6) and can be applied to other mountain regions. Our connectivity estimates can contribute to answering long‐standing questions on the drivers of evolutionary diversification in phylogenetic and phylogeographical studies, and enrich our understanding of the biogeographical history of mountain ecosystems more generally. There the different climates are ranged the one above the other, stage by stage, like the vegetable zones, whose succession they limit; and there the observer may readily trace the laws that regulate the diminu‐ tion of heat, as they stand indelibly inscribed on the rocky walls and abrupt declivities of the Cordilleras. (Von Humboldt, 1877 (1845), I, p 46) ACKNOWLEDG EMENTS This work was part of SGAF's doctoral thesis funded by Netherlands Organization for Scientific Research (NWO, grant 2012/13248/ALW to HH.). The Hugo de Vries foundation (Amsterdam) is acknowledged for financially supporting multiple grant proposals during the project includ‐ ing the development of the visualization accompanying this paper. The Sistema Nacional de Investigadores (SNI) de SENACYT supported AO. REO acknowledges the support of the German Centre for Integrative Biodiversity Research (iDiv) Halle‐ Jena‐Leipzig funded by the Deutsche Forschungsgemeinschaft (DFG)—FZT 118. CG thanks NUFFIC (the Hague) for financial support to obtain her master degree and Piet Zwart Institute (Rotterdam) advisors for designing and technical support. UvA‐ IBED colleagues Carina Hoorn and Daniel Kissling are thanked for the educational environment shaped by the parallel paper on mountain di‐ versity (Antonelli et al., 2018). 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Onstein is an evolutionary ecologist who enjoys col‐ lecting (and eating) tropical megafaunal fruits, e.g. on Borneo and Madagascar, while studying how fruit functional traits interact with frugivores to affect diversification dynamics. She is gener‐ ally interested in the broad‐scale distribution and diversification of functional and taxonomic diversity of flowering plants. Catalina Giraldo is an environmental artist (www.catal hinag iraldo.com/) who combines her scientific background with vis‐ ual media to raise awareness of environmental issues. She co‐ founded Fundación Biodiversa Colombia (www.funda cionb iodiv ersa.org), a biodiversity foundation that carries out research and educational projects in Colombia to protect the environment and help local communities develop a sustainable way of living. Author contributions: S.G.A.F. and H.H. conceived the ideas. H.H. provided the AP% of the Funza09 dataset. S.G.A.F. per‐ formed the spatial analyses. 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Aaron O'Dea is a marine palaeobiologist who uses the marine fossil record of Tropical America to explore drivers of macroev‐ olution in the seas, and takes cores on coral reefs from French Polynesia to the Dominican Republic to reconstruct how reefs changed over millennia with the aim of improving their future resilience.