10.5061/DRYAD.C59ZW3R52
Aguiar, Ludmilla
0000-0002-9180-5052
Universidade de Brasília
Ramos Pereira, Maria João
Federal University of Rio Grande do Sul
Zortea, Marlon
0000-0002-0827-7704
Universidade Federal de Goiás
Machado, Ricardo
0000-0002-6508-9005
Universidade de Brasília
Aguiar, Ludmilla M. S.
0000-0002-9180-5052
University of Brasília
Pereira, Maria João R.
0000-0002-9365-5166
Federal University of Rio Grande do Sul
Zortéa, Marlon
0000-0002-0827-7704
Universidade Federal de Goiás
Machado, Ricardo B.
0000-0002-6508-9005
University of Brasília
Where are the bats? An environmental complementarity analysis in a
megadiverse country
Dryad
dataset
2020
National Council for Scientific and Technological Development
https://ror.org/03swz6y49
2020-09-08T00:00:00Z
2020-09-08T00:00:00Z
en
https://doi.org/10.1111/ddi.13137
475876 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Aim: Field surveys are necessary to overcome Wallacean shortfalls. The
task is even more important when human pressure on tropical – megadiverse
– ecosystems is considered. However, due to financial constraints, spatial
and temporal prioritization is required. Here we used the concept of
environmental complementarity to identify non-surveyed regions for bats
that are environmentally different from other already surveyed regions. We
highlighted regions in Brazil where field inventories could be conducted
to locate new occurrences or even new bat species. Location: Brazil.
Methods: We based our analysis on environmental characterization aiming to
identify dissimilar regions to those already sampled for bats in Brazil.
We used 21 environmental variables to characterize 1,531 unique localities
where bats occur. Then, we applied the parameters of a generalised linear
model (GLM) to extrapolate the expected values of the environmental
variables for the entire country. We compared the predicted values of
localities with newly described bat species occurrence against the values
for other bat species. Results: We found that sites from which recently
discovered species were described are environmentally distinct from the
sites where previously described species occur. Therefore, new occurrences
and even new species could be found in regions that are environmentally
dissimilar from those already surveyed. By crossing the model with a human
footprint map, we defined temporal priorities for field inventories.
Regions such as the Northern Cerrado and Western Caatinga should be
surveyed first. Similar approaches could be undertaken for other
biological groups or regions, allowing the identification of spatial
congruence and the development of a comprehensive national programme for
biological field inventories. Main conclusion: Newly described species
occurred in environments dissimilar to those previously identified,
showing that environmental complementarity analysis is a valid approach to
define priority regions for new bat inventories.
We compiled a dataset on Brazilian bat species occurrences based on an
extensive literature revision, scientific collections belonging to our
institutions and from the Global Biodiversity Facility - GBIF. The list
has a total of 181 Brazilian bat species, including the species cited by
Nogueira et al. (2018), plus four additional species recently described:
Eumops chimaera Gregorin, Moras, Acosta, Vasconcellos, Poma, Santos
& Paca 2016, Histiotus diaphanopterus Feijó, Rocha &
Althoff 2015, Lonchophylla inexpectata Moratelli & Dias 2015, and
Pteronotus alitonus Pavan, Bobrowieck & Percequillo 2018. The
database was primarily organized by LMSA and complemented with records
provided by MRJP, MZ and from online databases (Global Information
Facility – GBIF). We used the package rangeBuilder in R to apply a spatial
filter to eliminate all duplicated coordinates and keeping just one-point
location.
The dataset is available in a csv format composed by four columns: species
(scientific name), source, long, and lat. The source field can have the
values “lmsa” (literature and field data compiled by Ludmilla M.S.
Aguiar), “mjrp” (field data compiled by Maria João Ramos Pereira), “mz”
(literature and field data compiled by Marlon Zortéa), and “gbif” (data
obtained from the Global Biodiversity Information Facility – GBIF)
(https://doi.org/10.15468/dl.9rg5ue). Geographical coordinates are
represented in decimal degrees, WGS84 datum.