DOI: 10.5061/dryad.8gtht76kv
title: The contribution of environmental and dispersal filters on beta diversity patterns in Amazonian tree communities

description: Environmental filters (e.g. climate, geomorphology and soils) and
 dispersal filters are key determinants of species distributions of
 Amazonian tree communities. However, a comprehensive analysis of the role
 of environmental and dispersal filters is needed to understand the
 ecological and evolutionary processes that drive phylogenetic and
 taxonomic turnover of Amazonian tree communities. We compare measures of
 taxonomic and phylogenetic beta diversity in 40 one-hectare plots to test
 the relative importance of climate, soils, geology, geomorphology, pure
 spatial variables and the spatial variation of environmental drivers of
 phylogenetic and taxonomic turnover in Ecuadorian Amazon tree communities.
 We found low phylogenetic and high taxonomic turnover with respect to
 environmental and dispersal filters. In addition, our results suggest that
 climate is a significantly better predictor of phylogenetic turnover and
 species turnover than geomorphology and soils at all spatial scales. The
 influence of climate as a predictor of phylogenetic turnover was stronger
 at broader spatial scales (50 km2) whereas geomorphology and soils appear
 to be better predictors of taxonomic turnover at mid (5 km2) and fine
 spatial scales (0.5 km2) but a weak predictor of phylogenetic turnover at
 broad spatial scales. We also found that the combined effect of
 geomorphology and soils was significantly higher for species turnover at
 all spatial scales but not for phylogenetic turnover at large spatial
 scales. Geographic distances as proxy of dispersal limitation was a better
 predictor of phylogenetic turnover at distances of 50&lt;500 km. Our
 findings suggest that climatic variation at local and regional scales can
 better predict phylogenetic and taxonomic turnover than geomorphology and
 soils.
description: The 40 one hectare plot
 work used in this study are part of the Amazon Tree diversity Network and
 have been established by the lead author and co-authors in the past 20
 years representing an unprecedented data set. In the past four years, we
 established 15 one-hectare plots
 in both terra firme and white sand forests in the Ecuadorian Amazon.
 We established 8 plots on
 alluvial terraces of the Aguarico River towards the north of the
 Ecuadorian Amazon; the age of these units ranges from Pliocene to
 Pleistocene origin
 (http://www.geoinvestigacion.gob..ec, Laraque
 <i>et al.</i>2009) The landscape is mostly characterized by
 large areas that correspond to Pleistocene alluvial terraces that
 occasionally suffer flooding events. These geomorphological units are
 interrupted only by high terraces with flat surfaces that have not
 suffered erosion of their surfaces (Saunders 2008; Wesselingh <i>et
 al. </i>2006). Two additional plots were established in old alluvial
 terraces of Napo River, these units as well as the units located in the
 Aguarico River are high terraces that presumably constitute old flood
 plains of the previously mentioned rivers (Saunders<i>
 </i>2008). Ten plots were established in the Pastaza megafan which
 is a massive alluvial deposit located in the southwestern Ecuadorian
 Amazon, evidence suggests that the modern megafan complex dates from the
 Pliocene-Pleistocene and recent alluvial processes have occurred between
 the last 180 000-30 000 yrs. (Rasanen <i>et al. </i>1995;
 Bernal <i>et al. </i>2011). Five plots were established in
 areas belonging to plateaus originated during the Cretaceous period; these
 geomorphological units are located in the lowest part of Cordillera del
 Condor below 500 m. The remaining 25 one hectare plots
 were established in the Yasuní national Park and the Tigre-Corrientes
 watershed. The landscape in both areas is characterized by the
 predominance of geomorphological units such as highly dissected hills
 occasionally interrupted by valleys (Pitman 2000). The landscape is
 dominated by Curaray and Chambira formations from Miocene and Mio-Pliocene
 origin respectively and soils are characterized by higher nutrients
 content (Pitman <i>et al. </i>2008).
 <b>Geomorphological variables and proximity analysis</b> Four geographic variables (hierarchical slope position, slope, dem and landsat) were used in the analysis describing the geomorphology and land cover features in the vicinity of the forest plots. Digital terrain elevation data for the Ecuadorian Amazon was obtained from the Shuttle Radar Topography Mission (SRTM) distributed by the USGS through the Earth Explorer platform (https://earthexplorer.usgs.gov/). The SRTM dataset has worldwide coverage of void filled elevation data at a resolution of 1 arc-second (30 meters). Topographic slope in degrees was calculated from the elevation data using the Spatial Analyst extension in ArcGIS 10.3 software from ESRI (Environmental Systems Resource Institute). Hierarchical Slope Position identifies topographic exposure (ridge, slope, valley bottom, etc) by applying moving windows with increasing radii to a digital elevation model (DEM) (Murphy et al. 2010). The exposure is a ridge if the elevation of the center cell in the window is higher than the average of the cells in the window. The opposite case corresponds to a valley bottom or toe slope. Hierarchical integration is done by starting with exposure values for the largest (user defined) window and adding values from smaller windows if their absolute standardized values exceed the values of the larger scale map. The variable was calculated using the Geomorphometry and Gradient Metrics (version 2.0) for ArcGIS (Evans et al. 2014) using windows of radii between 2 and 10 pixels with increments of two pixels. Slope position was measured by subtracting the Slope Position<b> </b>average neighbor values from a focal value. Positive values indicate that the central point is located higher than its average surroundings, while negative indicates a position lower than the average. The range of the metric depends not only on differences but also on the defined neighborhood. This metric is also referred to as Topographic Position Index (TPI) (Guisan et al. 1999). Digital elevation models (DEM) measures the bare-earth surface based on raster grids of the elevation between two or more points. We obtained data for Ecuadorian Amazon from the SRTM 90-meter resolution Digital Elevation Model developed by the NASA. We concatenated the different mosaics of topography in ArcMap 10.5.1 using the Spatial Statistics tool. Land cover information was obtained from a mosaic of Landsat images for the period 2010-2014 that had been created for the Ministry of the Environment of Ecuador. The mosaic was was created using the approach described in Hansen et al. (2013) that includes (i) image resampling, (ii) conversion of raw digital values (DN) to top of atmosphere (TOA) reflectance, (iii) cloud/shadow/water screening and quality assessment (QA), and (iv) image normalization. A principal components analysis was performed using the three RGB bands of the mosaic and the first component, that explained 96.4% of the variance, was used for further analysis. For each plot, a set of circular buffers with areas of 0.5 km<sup>2</sup>, 5 km<sup>2</sup> and 50-100 km<sup>2</sup>. Descriptive statistics were calculated for each variable at each scale defined by the buffer areas using zonal statistics tools in ArcGIS. Climatic variables In order to assess the role of climatic variables in the patterns of taxonomic and phylogenetic turnover we used 19 climatic variables from Bioclim at 30 seconds of resolution as an initial set of variables.