DOI: 10.5061/dryad.9s4mw6mmg
title: Cloud forests of the Orinoco River Basin (Colombia): Variation in vegetation and soil macrofauna composition along the hydrometeorological gradient

description: We present vegetation, soil macrofauna, soil, hydrometeorological and
 topographical data collected from Tropical Montane Cloud Forests in the
 Orinoco River basin. Specifically, from the municipality of Chámeza,
 department of Casanare, Colombia. These data sets were used to evaluate
 how vegetation and soil macrofauna diversity vary along the 1700–2200 m
 a.s.l. elevation range. Within this elevation range, we have previously
 described a hydrometeorological gradient largely driven by a fog incidence
 increase with elevation. Vegetation data were collected for all
 individuals with a diameter at breast height (DBH) &gt; 5 cm in four
 vegetation plots (5 x 50 m; total: 0.1 ha) every 100 m in altitude between
 1700–2200 m a.s.l. From each plot, we obtained three soil monoliths from
 the organic layer and three from the mineral horizon, and manually
 extracted their soil macrofauna, and soil samples for determining pH,
 organic matter content, and soil texture, among others in a soil
 laboratory. Topographical data was inferred from Digital Elevation Models.
 Hydrometeorological data was collected in a previous study, but it was
 interpolated to the sampling plots. Here we present the interpolated
 hydrometeorological data.
description: Vegetation data On each transect, we
 delimited four plots of 5 x 50 m (250 m2) with a minimum distance between
 plots of 200 m. The four plots per elevation covered 0.1 ha. In each plot,
 we marked all trees with a diameter at breast height (DBH &gt; 5 cm
 regardless of their height, with traffic reflective yellow paint and an
 aluminum numbered tag. At the beginning of the wet season (March 2021) we
 collected botanical specimens with a telescopic tree pruner. Samples were
 pressed inside newspaper sheets and piled up. Then, the piles were tied
 up, bagged, and wet with 70% alcohol. In the Forest Herbarium of the
 Universidad Distrital Francisco José de Caldas (UDBC) these samples were
 oven-dried, quarantined, and identified to the most detailed taxonomic
 level possible. The data set has species abundance data
 per plot. Soil macrofauna data
 Soil macrofauna was collected in April 2021, one month after the
 beginning of the wet season, following the Tropical Soil Biology and
 Fertility method (TSBF) (Anderson & Ingram, 1993). This method
 consists of collecting a rectangular volume of soil (monolith) with the
 help of a metal frame of 25 x 25 x 10 cm. Along each vegetation plot, we
 aimed to collect three monoliths from the organic layer and three
 monoliths from the underlying top mineral horizon. The first monolith was
 extracted from the plot’s center and the other two were collected at a
 mean distance of 10 m to both sides of the central monolith. This would
 yield a total of 144 monoliths, however, in the field we extracted 134
 monoliths of which 70 were from organic layers and 64 from the top mineral
 horizon. In two sampled monoliths, we did not find an organic layer,
 likely due to the steep terrain and water flows that prevented the
 accumulation of plant debris. In the case of the top mineral horizon,
 there were eight monoliths in which the organic layer was directly on top
 of a rock substrate. Each extracted monolith was placed
 in a sealed plastic bag properly marked and transported back to a working
 area where soil macrofauna was manually extracted the same day to prevent
 desiccation and placed in 80% ethanol on 100 ml plastic vials. Specimens
 were identified to the order level (following Velásquez & Lavelle,
 2019) at the Forest Health Laboratory in the Universidad Distrital
 Francisco José de Caldas and then deposited at the Entomological Forest
 Collection (CEFUD- RNC 045).  Data of soil macrofauna
 orders was standardized to density per square meter, considering that the
 monoliths had 25*25 cm of area, and depending on the number of monoliths
 per plot. Soil analyses, hydrometeorological and
 topographical variables We collected soil samples
 (~500 g) from the organic layer and the top mineral horizon on the side of
 each extracted monolith. For each sample, we estimated the volume of the
 mineral/organic layer that was retrieved. This is an indirect measurement
 of the mineral/organic layer depth, as in most cases the depth of the
 layer was not enough to extract a full monolith. In this case, we can
 account for the studied horizons with less depth than 10 cm, but not for
 deeper soils. These samples were oven-dried at 70°C for 24 hours, then
 sieved with a 2-mm metal sieve. We weighed the &gt; 2 mm fraction and
 the &lt; 2 mm fraction. From the &lt; 2 mm fraction, we extracted
 10 g for pH measurements with an APERA SX-823-B pH-meter by dilution in
 distilled water. Also, to identify soil texture we employed the Bouyoucos
 method (Bouyoucos, 1962) and organic matter content by combustion in the
 Soil laboratory in the Universidad Distrital Francisco José de Caldas. The
 data were averaged to the plot level, to be included in the ordination
 analyses. Hydrometeorological data were collected from
 12 June 2014, to 13 July 2016, on 10-minute time resolution (see Ramírez
 et al., 2017a for a detailed description of the setup). Soil volumetric
 water content data were collected with GS-3 frequency domain soil moisture
 sensors (Decagon Devices Inc.) at 10-cm depth in the mineral horizon
 collected from 12 June 2014, to 13 July 2016, in three forested locations
 within our study area at 1720, 1973, and 2068 m a.s.l. Rainfall data were
 collected with four Decagon ECRN-100 rainfall gauges at 2 m above the
 ground. They were located at 2148, 1819, 1729, and 1554 m a.s.l. Fog hours
 were collected with three cylindrical Juvik type fog collectors (Juvik
 & Nullet, 1995) each connected to a Decagon ECRN-100 rainfall
 gauge. They were located at 1819, 1729, and 1554 m a.s.l. Disconnection of
 the hoses, failures of the tipping buckets during the wet season and poor
 silicone sealing before the dry season did not allow us to specifically
 quantify water inputs by fog. However, we used the data to discriminate
 between hours with and without fog, following Tanaka et al. (2011). With
 this approach, we established elevation trends in fog frequency, including
 estimating expected fog incidence at the 2148 m a.s.l. elevation. We
 estimated potential evapotranspiration with the Penman–Monteith model
 (Monteith, 1965) assuming a single-layered canopy with zero stomatal
 resistance, by employing shortwave incoming radiation, relative humidity,
 air temperature, wind speed, and barometric pressure data collected with
 two Davis Vantage Pro2-plus automated weather stations (AWS) located at
 1819 and 2148 m a.s.l. More detailed information about the
 hydrometeorological setup can be found in Ramírez et al.,
 (2017a). The collected and estimated data were
 interpolated to the focal vegetation and soil macrofauna plots by
 employing the inverse distance and elevation weighting interpolation
 method (IDEW) following Masih et al. (2011). We assigned a 50-50 % weight
 to distance and elevation. From these interpolations mean annual values
 were estimated for each variable: soil moisture, rainfall, fog hours, and
 potential evapotranspiration. Ramírez et al., (2017a, 2017b, 2018) showed
 that the study area and neighboring micro catchments present a
 hydrometeorological gradient with higher humidity and lower
 evapotranspiration at the higher elevations compared to the lower
 elevations. Topographical data including slope, aspect
 (nine-parameter second-order polynomial, sensu Zevenbergen &
 Thorne, 1987), and topographic position index (Guisan et al., 1999;
 Gallant & Wilson, 2000) were obtained from the Radiometric Terrain
 Corrected High-Resolution Digital elevation model ALOS PALSAR (ASF DAAC,
 2015). Aspect refers to the compass direction that a slope faces, and it
 can be related to wind and sunlight exposition. We transformed the aspect
 from degrees to a continuous variable by applying the cosine for the north
 aspect and the sine for the east aspect. 
description: All files are in .csv format so they do not need any particular
 software to be read.