DOI: 10.5061/dryad.gtht76hsv
title: Dietary items recorded in Chocoan bats

description: Human disturbances have reduced the three basic niche dimensions for the
 survival of some mammalian species (space, time and resources). Many
 studies consider that anthropic activities cause the extinction of
 ecological functionalities faster than the species extinctions. The
 effects of human disturbances on the niche structure and ecological
 relationships of bat communities are fairly unknown.  Based on
 management use, we identified 4 types of habitats in the Ecuadorian Andean
 Chocó: primary forest (PF), secondary forest in natural regeneration
 (SF1), secondary forest in assisted regeneration (SF2) and pastures for
 cattle (P). We used these habitats to determine the responses in the
 trophic niche and the ecological relationships of understory fruit bats.
 Our results show that niche overlap is higher in disturbed habitats (SF1,
 SF2, and P), while ecological relationships are weaker. These results mean
 that bat communities and the ecosystem services that these animals provide
 are highly endangered due to anthropogenic disturbances.
description: Sampling was organized according to the lunar calendar periods,
 avoiding full moon periods because many species reduce their activity
 patterns to lower predation risk. There were 12 sampling nights in
 February, 11 in March, and 12 in May. During these months, we captured
 bats in the primary forest of Mashpi Lodge (PF), the secondary forest in
 natural regeneration (SF1) in Pambiliño and Chontaloma, and the secondary
 forest in assisted regeneration (SF2) in Chontaloma. Additionally, between
 July and August 2021, a 9-night sampling trip was carried out between the
 Mashpi Shungo and Chontaloma reserves. In Mashpi Shungo, we sampled in
 primary forest and SF1, whereas in Chontaloma, we sampled in pastures for
 cattle (P). For the capture sessions, we used 4-7 mist
 nets of variable sizes (6, 9 and 10 meters), opened between 19:00 pm to
 00:30 am (Arias and Pacheco, 2019; Novoa et al. 2011). We placed capture
 stations on closed trails, mountain ridges, near water sources, and
 potential flight sites where bats could be intercepted (Kelm et al. 2008).
 Nets were checked in 15 to 20 minute intervals. Bat species were
 identified with the help of field guides (López-Baucells et al. 2016;
 Tirira, 2017). To obtain seeds, the animals were kept for an hour in cloth
 bags. Fecal samples obtained were preserved in 2 ml eppendorf tubes with
 70% alcohol (Arias and Pacheco, 2019). We collected voucher specimens
 according to the guidelines of the American Society of Mammalogist (Sikes
 and Gannon, 2016). The specimens were deposited with their respective
 reference data in the Instituto Nacional de Biodiversidad (INABIO) under
 the research license with code MAE-ARSFC-2020-0.512 granted by the
 Ministerio del Ambiente Agua y Transición Ecológica del Ecuador (MAATE)
 (Appendix 1). <strong><em>Counting
 seeds</em></strong> The seeds collected
 were separated from the fecal remains in the laboratory with entomological
 tweezers. Once separated, they were dried on paper envelopes and then
 photographed with a stereomicroscope (Arias and Pacheco, 2019). To count
 very numerous seeds, such as those of the genus
 <em>Piper</em>, we used the app CounTThings from Photos
 (Dinamic Ventures INC, 2017), and for cases in which this application
 could not differentiate seeds from other fecal residues, we used ImageJ
 (Wayne Rasband (NIH), 2019), which allows counting the seeds based on the
 size of their pixels. Seed identification was performed to the lowest
 taxonomic level possible using field guides (Kirkbride et al. 2006; Lobova
 and Mori, 2007). Counts were made for each bat, then grouped by genus or
 morphospecies and type of habitat (PF, SF1, SF2, P). The seed collection
 was deposited in the MECN to act as a reference guide for other
 studies. <strong><em>Counting
 pollen</em></strong> Samples obtained from
 nectarivorous bats were spread on microscope slides, stained with
 methylene blue, and finally photographed (Arias and Pacheco, 2019). We
 used the same applications described before to count each grain of pollen.
 In a similar way, counts were made by individual, then grouped by pollen
 (in general) and type of habitat.
 <strong><em>Counting
 insects</em></strong> We counted how many
 insects existed in each fecal sample. We identified each insect order by
 comparing the morphology and anatomy of their wings, mouthparts, heads,
 eyes, antennae, and other structures with field guides (Borror and White,
 1970; Pokhrel and Budha, 2015). Insect remains that could not be
 identified (undetermined insects) were counted as a single food item based
 on their presence, adding 1 to the count if this type of remains were
 present. However, all the counts were summarized as insects and for each
 type of habitat. <strong><em>Counting
 vertebrates</em></strong> Some omnivorous
 bats usually feed on small vertebrates (birds, frogs, rodents and other
 bats), fecal remains of these bats usually present fur, bones, or feathers
 (Gardner, 1977). We compared these remains with biological material
 available at INABIO. We counted the different types of preys identified in
 fecal samples for each individual<strong><em>,
 </em></strong>then counts were summarized by vertebrates and
 type of habitat.
description: # Dietary items recorded in Chocoan Bats
 [https://doi.org/10.5061/dryad.gtht76hsv](https://doi.org/10.5061/dryad.gtht76hsv) This file contains original datasets collected for performing analyses of niche breadth, niche overlap, and ecological relationships. ## Description of the data and file structure Data are organized by 4 types of habitats, primary forest (PF1), secondary forest in natural regeneration (SF1), secondary forest in assisted regeneration (SF2), pastures for cattle (P), and a summarized data set among all the habitats. Bats are in rows, and each dietary item is recorded in columns. Users can use these data for any type of ecological analysis or simulation in R or another console. ## Code/Software Each one of these matrix must be charged in R Studio and R 4.1.0. For replicating null models and other analyses, its necessary to use the next R packages: bipartite, bipartite d3, spaa, vegan, cluster, ecosimr. A detailed tutorial for some of these packages is found here: [https://cran.r-project.org/web/packages/bipartite/vignettes/Intro2bipartite.pdf](https://cran.r-project.org/web/packages/bipartite/vignettes/Intro2bipartite.pdf) [https://www.uvm.edu/\\~ngotelli/EcoSim/EcoSim.html](https://www.uvm.edu/\\~ngotelli/EcoSim/EcoSim.html) [https://cran.r-project.org/web/packages/bipartiteD3/vignettes/bipartiteD3\\_Intro.html](https://cran.r-project.org/web/packages/bipartiteD3/vignettes/bipartiteD3\\_Intro.html) For bipartite d3, we recomend using R Posit cloud and R pubs, for publishing widgets. [https://posit.cloud/](https://posit.cloud/) [https://rpubs.com/](https://rpubs.com/)