DOI: 10.6084/m9.figshare.19319894.v2
title: Cudney-Valenzuela et al. 2022. Tropical forest loss impoverishes arboreal mammal assemblages through its negative effect on tree canopy connectivity. Figshare dataset.

description: The Lacandona rainforest is situated in the eastern portion of the State of Chiapas (91˚6’42.8”–90˚41’8.7’’W; 16˚19’17.1”–16˚2’49.3N). Our study was carried out in the Marqués de Comillas region within the Lacandona rainforest, which comprises 203,999 ha of fragmented forest. We selected 20 old-growth forest patches (area ranging from 5 to 2170 ha), separated from each other by at least 2.5 km (distances measured from their geographical centers; Fig. 1).<i>Vegetation structure</i> In the center of each forest patch, we established five 10 × 50 m plots separated by at least 30 m, avoiding forest edges and vegetation gaps. In these plots, we measured the diameter at breast height (DBH) of all trees with DBH ≥ 10 cm, and calculated the sum of tree basal area in each plot. We also estimated the percentage of canopy connectivity inside each plot by taking three hemispherical photographs (25 m apart) with a wide-eye lens (Apexel 198˚ Fisheye Lens). The photos were analyzed using the program Gap Light Analyzer (Frazer et al. 1999) and used the inverse of canopy openness to calculate canopy connectivity. Both tree basal area and canopy connectivity are considered proxies for tree biomass and resource availability. We also considered tree basal area to be a proxy of stand maturity, and canopy connectivity a proxy of canopy movements for arboreal mammals in the focal forest patches.<i>Sampling of arboreal mammals</i> Mammal surveys are detailed elsewhere (Cudney-Valenzuela et al. 2021), but a brief overview is given here. Within the same vegetation plots, we selected five focal trees with suitable climbing conditions (branches ≥ 20 cm wide, preferably hardwood species) and whose architecture allowed installing a camera trap facing other main branches. In each tree, we established a single-rope climbing system. Focal trees in the same patch were separated from each other by a distance ≥ 30 m. Of the five focal trees per patch, four reached the canopy (mean height ± SD = 21.8 ± 6.2 m, range = 10.2 to 36.6 m) and one the midstory (9.1 ± 4.7 m, 3.4 to 19.6 m). <br>Within each patch, we used one camera trap (Bushnell Trophy Cam HD Aggressor Low Glow ©) at a time, which was rotated among the five focal trees once a month, except from October to December when they remained on the same focal tree. Cameras were placed at varying heights depending on the characteristics of the focal tree (camera height of canopy and midstory trees was 15 ± 4.3 m and 2 ± 0.6 m, respectively). Cameras were continuously active from May 2018 to May 2019, and they were serviced once a month (change of batteries, downloading of pictures, replacement of malfunctioning cameras).Total sampling effort was 7,387 camera trap nights (average per patch = 369 ± 11.6 nights), with 6,233 active camera trap nights (average per patch = 311.7 ± 19.9 nights).We calculated each species’ relative abundance index (O’Brien 2011) by dividing the number of events for a given species by the number of days the camera was active in the forest patch, and then multiplying it by 100 . Then we summed the relative abundance index of the species recorded in each patch as an estimate of total abundance of arboreal mammals per forest patch. We used the ‘entropart’ package (Marcon and Hérault 2015) to estimate species diversity using Hill numbers of order 0 (species richness, <i><sup>0</sup>D</i>) and 1 (exponential of Shannon entropy, <i><sup>1</sup>D</i>) (Jost 2006). Species richness (<i><sup>0</sup></i><i>D</i>) gives disproportionate weight to rare species by considering all species equally abundant while the exponential of Shannon entropy weighs species’ abundances without disproportionately favoring either rare or dominant species, and is therefore interpreted as the number of common (or typical) species in the assemblage (Jost 2006).<i>Forest cover</i>We adopted a site‐landscape approach (sensu Brennan et al. 2002), in which response variables were measured in same-sized sample sites (i.e., 5 focal trees at the center of each forest patch, total tree basal area and canopy connectivity), and forest cover (i.e., area covered by old-growth forest divided by landscape size × 100) were measured within 13 circular concentric radii (100- to 1300-m radius, at 100 m intervals) from the geographical center of each forest patch (Fig. 1). We used recent and high-resolution Sentinel S2 satellite images (obtained in 2016) to produce land-cover maps of each landscape using ENVI 5.0 software, and extracted forest cover metrics using ArcGIS software with the ‘Patch Analyst’ extension.