Body mass data set for 1,317 bird and 270 mammal species from Colombia

Abstract

Body mass is one of the most important phenotypic attributes in animal ecology and life history. This trait is widely used in the fields of ecology and macroevolution, since it influences physiology, morphological functions, and a myriad of ecological and social interactions. In this data set, our aim was to gather a comprehensive bird and mammal body mass data set from northern South America. We report body mass, discriminated by sex, for 42,022 individual birds and 7,441 mammals representing 1,317 bird species (69% of Colombia’s avifauna) and 270 mammal species (51% of Colombian mammals) from the Neotropics. The data were sourced from vouchers collected between 1942 and 2020 and from individuals captured and released at banding stations over the last two decades for birds (2000–2020) and the last decade for mammals (2010–2020), by 10 research groups and institutions in Colombia. This data set fills gaps identified in other similar databases, as it focuses on northern South America, a highly diverse Neotropical region often underrepresented in morphological data sets. We provide wide taxonomic coverage for studies interested in information both at regional and local scales. There are no copyright restrictions; the present data paper should be appropriately cited when data are used for publication. The authors would appreciate learning about research projects, teaching exercises, and other uses given to this data set and are open to contribute in further collaborations using these data.

New estimates indicate that males are not larger than females in most mammals

“…Many others do not report body mass data in a sex-segregated format (e.g., the Malagasy Animal trait Data Archive, EltonTraits1.0) ( 52, 53 ). However, we found several published datasets that included data that met our criteria ( 16, 29, 38, 54–58 ). We then searched Google Scholar for primary sources to top up sample sizes for underrepresented orders and families in our dataset, using Burgin et al’s ( 25 ) estimations of species richness in each mammalian order.…”

Contrasting effects of frugivore assemblages and phylogeny on global variation in fruit length and width

“…Due to the strong positive relationship between gape size and body mass (Malmborg & Willson, 1988; Lord, 2004; also see Appendix S2‐Figure S1), we used body mass for frugivorous species as a proxy of gape size in our study because data on gape size were only available for 216 frugivorous species. Unless the width and length of fruits and the body mass of frugivores were reported in the original studies (Bello et al., 2017; Buitrón‐Jurado & Sanz, 2021; Burns, 2013; Flörchinger et al., 2010; Pizo et al., 2021; Quintero et al., 2021; Quitián et al., 2019; Ramos‐Robles et al., 2018; Sankamethawee et al., 2011; Schlautmann et al., 2021), they were extracted from available database, other published literature or websites (Jordano, 1995; Dunning Jr, 2007; Gosper & Vivian‐Smith, 2010; Galetti et al., 2011; Valido et al., 2011; Gallagher & Leishman, 2012; Masaki et al., 2012; Wilman et al., 2014; Albrecht et al., 2018; Sinnott‐Armstrong et al., 2018; Tavşanoğlu & Pausas, 2018; Koike & Masaki, 2019; Machado‐de‐Souza et al., 2019; Rodrigues et al., 2019; Delmas et al., 2020; Urban et al., 2020; Buitrón‐Jurado & Sanz, 2021; Ocampo et al., 2021; Báez et al., 2022; http://www.iflora.cn/). If different fruit lengths and widths were reported for a species by different studies, we used the maximum, although there was usually consistency among the literature.…”

Neotropical birds and mammals show divergent behaviour responses to human pressure

“…a measurement of circular mean and dispersion, respectively) were calculated and reported (SI Table 2). The species diet, body size, activity pattern (diurnal, nocturnal or cathemeral) and if it was a game species or not was determined based on both local expert knowledge and literature (Emmons and Feer, 1997; Hilty and Brown, 2001; IUCN, 2022; Myers et al, 2022; Ocampo et al, 2021). All analysis were performed in R version 4.2.1 (R Core Team, 2022), using the packages “lme4” (Bates et al, 2015), “circular” (Agostinelli and Lund, 2022), and ggplot2 (Wickham, 2016).…”