The flickering connectivity system of the north Andean páramos

Aim To quantify the effect of Pleistocene climate fluctuations on habitat connectivity across páramos in the Neotropics. Location The Northern Andes Methods The unique páramos habitat underwent dynamic shifts in elevation in response 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 responsive to temperature. Here we reconstruct the extent and connectivity of páramos over the last 1 million years (Myr) by reconstructing the UFL 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 páramos and estimates their connectivity to provide insights into the role of topography in biogeographic 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 stadials and mild interstadials dominated the climate system. These variable degrees of connectivity through time result in what we term the ‘flickering connectivity system’. 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 elevational and spatial shifts in páramos causing dynamic changes in habitat connectivity 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 topographic configuration. The flickering connectivity system of the páramos uncovers the dynamic settings in which evolutionary radiations shaped the most diverse alpine biome on Earth.


Calculations of connectivity per páramo "island" 149
To calculate the degree of connectivity between páramos, we used a graph-based habitat availability index 150 called probability of connectivity (PC) metric. This metric takes into account the area of the páramo 151 "island" itself and the distances to other islands where a user-defined distance threshold defines the 152 'reachability' of other islands (Saura & Pascual-Hortal, 2007; Saura, Estreguil, Mouton, & Rodríguez-153 Freire, 2011), even if they are not physically connected (i.e. 'structural connectivity', Tischendorf & 154 Fahrig, 2000). The metric assigns a value to each páramo island representing its contribution in 155 maintaining the overall connectivity of the páramo biome (Saura & Pascual-Hortal, 2007;Saura et al., 156 2011). The total PC is built up in three 'fractions', namely the 'intrapatch', the 'flux', and the 'connector' 157 fractions (Saura & Rubio, 2010). The first fraction focusses on the available surface area and habitat 158 quality (if applicable) within the individual island. The second fraction assesses how well the individual 159 island is connected to other islands given additional importance to the other islands' attributes (surface and 160 quality) and its strategic position to other páramo islands. The third fraction quantifies the contribution of 161 the island to maintain connectivity between the rest of the islands, in other words its role as an 162 intermediate stepping stone between non-adjacent islands. Additionally, we calculated the equivalent 163 connected area (ECA), which is derived directly from the PC, as a measure of the overall connectivity of a 164 region (Saura et al., 2011). Conefor Sensinode 2.2 software and ESRI ArcGIS 10.3 were used to calculate 165 the straight-line distances between islands, the PC and ECA (Saura & Pascual-Hortal, 2007;Saura & 166 Torné, 2009). We calculated connectivity for the entire Northern Andes and for each mountain range 167 separately. 168 169

Calculations of corridors between páramo islands 170
We identified corridors between páramo islands within and between cordilleras under different climatic 171 conditions. We used the Gnarly Landscape Utilities (V0.1.3; McRae, Shirk, & Platt, 2013) with ESRI 172 ArcGIS 10.3 to create a raster grid of 'landscape resistance' based on ruggedness (Fig. 2b) and habitat 173 suitability. We assumed an increased landscape resistance with increased ruggedness, assigning values 174 between 0 (no resistance) to 100 (maximum resistance) using an equal interval classification. For the 175 habitat suitability map, we started by assigning a "perfectly suitable" score of 100 to each páramo island, 176 while outside the island the score of 0 reflects maximum unsuitability. To soften this boundary, an 177 exponential decay function was then used by increasing resistance in 5 elevational steps of 100 m where 178 we assigned a suitability score of 40 to the boundary of the páramo. As a result of the decay function the 179 highest suitability of páramo -its core area -was restrained 200 m above the UFL and 200 m below the 7 snowline. 181 We used Linkage mapper to calculate the least-cost pathways, or corridors, based on the produced raster 182 grid of landscape resistance (McRae & Kavanagh, 2011). These corridors are expressed as 'conductance 183 maps' that represent gradients of cumulative corridors. Where the densities of corridors is highest, it is 184 assumed that there is a high probability of dispersal and migration possible between islands (McRae,  185 Dickson, Keitt, & Shah, 2008). The full landscape of the Northern Andes is considered an area where 186 corridors could exist, with exception of the region between SNSM and the Sierra de Perijá (Fig. S2.1). 187 We resampled the 30 m Digital Elevation Model (DEM, Fig. 2) to a 1 km resolution to reduce computing 188 time for each Linkage mapper down to on average 2 hours. We allowed Linkage mapper to create 189 corridors through (instead of only between) core areas to represent the full arsenal of connectivity through 190 the landscape. Only corridors between páramo islands larger than 1 km 2 were considered at any given 191

Calculations of páramo connectivity 210
Our estimations on the spatial and elevational extent of ancient páramos and their connectedness at 211 different times in the past reveals that páramos underwent frequent spatial alterations between fragmented 212 and connected spatial configurations, but the exact patterns were highly dependent on mountain chain 213 topography (Fig. 4a,b. See Appendices 4 and 5). The páramos in the Ecuadorian Cordillera generally 214 maintained a high degree of connectivity over the last 1 Myr, rarely enduring severe fragmentation. 215 Fragmentation did however occur when the snowline plunged significantly during colder and wetter 216 glacial periods, causing a break up of páramo areas on lateral flanks of the mountains. Likewise, the level 217 of connectivity between páramos on the Central Cordillera fragmented substantially through a descending 218 snowline, breaking the upper elevation limit of páramo connectivity. In contrast, the Eastern Cordillera 219 shifted substantially between periods of connectivity and fragmentation, always, however, maintaining 220 two large páramo islands surrounded by smaller 'satellite islands'. Páramos in the Cordillera de Mérida 221 seem to have been restricted during interglacials to one core area only, while during colder periods a 222 relatively high fragmentation is observed possibly due to glaciers pushing páramos to lateral distributions. 223 Here connectivity increased mainly towards the southwest and during colder periods (UFL ≤ 2300 m asl). 224 The páramos of the SNSM and the Western Cordillera endured the highest degree of rates of change in 225 fragmentation of all ranges. In the latter, páramo habitats are estimated to have often completely 226 disappeared. In contrast, páramos of the Central Cordillera maintained a long latitudinal distribution, 227 forming a chain of isolated populations in small patches that on the whole remained connected. Even in 228 very cold conditions, no continuous connectivity of core areas seems to have been possible between the 229 Eastern Cordillera and Cordillera de Mérida, or the region of Sierra de Perijá. Towards the south of the 230 Eastern Cordillera a low-elevation barrier was possibly crossed at 1900 m asl forming a brief bridge 231 suitable for páramo habitat into the Macizo Colombiano of the Central Cordillera. 232 The reconstruction of putative corridors shows a complex spatial pattern through the mountainous 233 landscapes of the Northern Andes (Fig. 4c,d). The long ridge of the Central Cordillera forms the starting 234 point of numerous corridors to the páramos in the Western Cordillera. The Eastern Cordillera shows a 235 complex internal pattern of corridors, where there are neither strong corridors towards Sierra de Perijá in 236 the North, nor towards the Cordillera de Mérida, while a high concentration of corridors is found between 237 the large páramos complexes in the Eastern Cordillera (Páramos of Boyacá and Cundinamarca, Fig. 1). In 238 the Ecuadorian Cordillera a more lateral pattern of high/low potential corridors is observed following the 239 intra-Andean valleys and peaks within this mountain range. Corridors to the southernmost páramos of 240 Ecuador as also the northernmost páramos of the Western Cordillera are weak and occurred infrequent 241 during the last million years, shown by the thin lines. 242 9

Flickering connectivity systems 243
Páramo connectivity through time shows a highly variable pattern ( Fig. 5

.a) introduced by Flantua & 244
Hooghiemstra (2018) as a flickering connectivity system (see visualization in Appendix S6). We find 245 support for the hypothesis that this system with fluctuating, highly variable connectivity in spatial and 246 temporal dimension is unique for each mountain range of the Northern Andes (Fig. 1). For example, 247 changes in connectivity within the Ecuador Cordillera are substantial but the system 'flickers' around a 248 high average when compared to other mountain ranges. The flickering connectivity systems within the 249 Eastern and Central Cordillera are surprisingly similar, though the peaks of connectivity during glacial 250 periods and the dips of connectivity during interglacials are more extreme in the former (Fig. 5a). The 251 Western Cordillera is a larger mountain range than the Cordillera of Mérida and the SNSM (Table S.1), 252 and its variation of connectivity has been correspondingly larger ( Fig. 5b) but with the lowest occurrence 253 of connectivity compared to the other mountain ranges (Fig. 5a). Considering only the frequency in the 254 distribution of data (Fig. 5b), the Ecuadorian Cordillera and the SNSM stand out for their relatively small 255 within-mountain range variation in connectivity, compared to the Eastern and Central Cordillera (similar 256 patterns) and the Western Cordillera. 257 When frequencies of connectivity are weighted by the amount of time that connectivity lasted two main 258 patterns emerge (Fig. 5c) Although currently isolated, evolutionary radiations and the assembly of the páramo ecosystem formed 269 during times when the páramos were flickering in and out of connectivity (Fig. 5b.) The concept of 270 'mountain fingerprints' (Flantua & Hooghiemstra 2018) proposes that the region's complex topography 271 would have meant that páramos in different mountain regions would have fragmented and connected at 272 different periods of time and with different rates and frequencies (as summarized in Fig. 1). This means 273 that in some mountain ranges the páramos are a mix of somewhat even occurrence of connectivity and 274 fragmentation events through time (Fig.1b, here representative of the Eastern Cordillera), or could have 275 been dominantly fragmented (Fig.1a, e.g. Western Cordillera), or more connected (Fig. 1c, e.g.  276 Ecuadorian Cordilleras). These regional differences in the temporal and spatial variation in past páramo 277 connectivity (Figs 4 and 6) are likely to have resulted not only in regional differences in biogeographical 278 patterns through time, but also varying ecological and evolutionary processes. We therefore propose that 279 the data we present can be used to test hypotheses of the drivers of species richness, endemism and