Herbarium records provide reliable phenology estimates in the understudied tropics

Abstract

1. Plant phenology has been shifting dramatically in response to climate change, a shift that may have significant and widespread ecological consequences. Of

Geographic And Taxonomic Occurrence R‐based Scrubbing (gatoRs): An R package and workflow for processing biodiversity data

“…Herbarium data downloaded from these and other aggregators have been used to investigate a diverse array of biological questions (e.g., Wollan et al, 2008; Willis et al, 2017; Allen et al, 2019; reviewed in Heberling et al, 2019). Applications in research are broad and include species delimitation (e.g., Zapata and Jiménez, 2012; Su et al, 2020; de Mestier et al, 2023; Wu et al, 2023), understanding organismal response to seasonal events (e.g., Pearson et al, 2020; Guralnick et al, 2022; Belitz et al, 2023; Park et al, 2023), exploring global patterns of biodiversity (e.g., Gaynor et al, 2020; Melton et al, 2022; Folk et al, 2023), and investigating the potential impact of climate change on species distributions (e.g., Rawal et al, 2015; Gaynor et al, 2018; Hodel et al, 2022; Naranjo et al, 2022; Wang et al, 2022).…”

Leveraging natural history collections to understand the impacts of global change

“…And, just as most phenological studies have been done in the northern hemisphere, more have undoubtedly been conducted in temperate rather than tropical ecosystems. Park et al (2023) show that herbarium specimens from Brazil, because they typically represent a much broader sampling across geographic and climatic space than do field observational data, can be a better source of data to test phenological hypotheses. The data already reside in herbaria, and phenological estimates from herbarium specimens align well with those collected in the field.…”

Taking advantage of opportunistically collected historical occurrence data to detect responses to climate change: The case of temperature and Iberian dung beetles

“…Unsurprisingly, the biodiversity data compiled by different and uncoordinated initiatives (Feng et al., 2022) are almost always characterized by the pervasive existence of taxonomical and geographical biases and shortcomings (see, for example, Hortal et al., 2015; Hughes et al., 2021; Meyer et al., 2016; or Larsen & Shirey, 2021). These drawbacks, inherent to opportunistically collected historical occurrence data, may limit but not invalidate the use of such information for scientific or conservation purposes (Grand et al., 2007; Isaac et al., 2014; Park, Lyra, et al., 2023; Park, Xie, et al., 2023; van Strien et al., 2013). Different approaches to filtering and processing information from biodiversity databases have allowed taking advantage of this unprecedented source of information to propose explanatory hypotheses about the spatiotemporal distributions of organisms (Belitz et al., 2020; Di Cecco et al., 2023; García‐Roselló et al., 2015; Heberling et al., 2021; Isaac et al., 2014; Lajeunesse & Fourcade, 2023; Pagel et al., 2014).…”