10.5061/DRYAD.RT679NG
Szewczyk, Tim M.
University of New Hampshire
McCain, Christy M.
University of Colorado Boulder
Data from: Disentangling elevational richness: a multi-scale hierarchical
Bayesian occupancy model of Colorado ant communities
Dryad
dataset
2018
Predictive model
National Science Foundation
https://ror.org/021nxhr62
DEB-0949601
2018-11-27T18:28:59Z
2018-11-27T18:28:59Z
en
https://doi.org/10.1111/ecog.04115
26304 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Understanding the forces that shape the distribution of biodiversity
across spatial scales is central in ecology and critical to effective
conservation. To assess effects of possible richness drivers, we sampled
ant communities on four elevational transects across two mountain ranges
in Colorado, USA, with seven or eight sites on each transect and twenty
repeatedly sampled pitfall trap pairs at each site each for a total of 90
days. With a multi-scale hierarchical Bayesian community occupancy model,
we simultaneously evaluated the effects of temperature, productivity,
area, habitat diversity, vegetation structure, and temperature variability
on ant richness at two spatial scales, quantifying detection error and
genus-level phylogenetic effects. We fit the model with data from one
mountain range and tested predictive ability with data from the other
mountain range. In total, we detected 105 ant species, and richness peaked
at intermediate elevations on each transect. Species-specific thermal
preferences drove richness at each elevation with marginal effects of
site-scale productivity. Trap-scale richness was primarily influenced by
elevation-scale variables along with a negative impact of canopy cover.
Soil diversity had a marginal negative effect while daily temperature
variation had a marginal positive effect. We detected no impact of area,
land cover diversity, trap-scale productivity, or tree density. While
phylogenetic relationships among genera had little influence, congeners
tended to respond similarly. The hierarchical model, trained on data from
the first mountain range, predicted the trends on the second mountain
range better than multiple regression, reducing root mean squared error up
to 65%. Compared to a more standard approach, this modeling framework
better predicts patterns on a novel mountain range and provides a nuanced,
detailed evaluation of ant communities at two spatial scales.
Data list for JAGS model: SJ transectsList (R data structure) of data
required to parameterize the Bayesian model detailed in Appendix A2 with
the San Juans elevational transects. Includes species occurrences,
trap-level covariates, site-level covariates, and other objects in
Appendix A2. Loading the file in R with `SJ.ls <-
readRDS("SJ_data_for_JAGS.rds")` will load a named list with all
necessary objects. See Appendix A2 for the model code and descriptions of
objects contained in the list.SJ_data_for_JAGS.rdsData list for JAGS
model: Front Range transects, shared speciesList (R data structure) of
data required to predict occurrences and richness along the two Front
Range transects with only species detected in both the Front Range and the
San Juan range, using a model parameterized with the San Juan range.
Loading the file in R with `FR.shared.ls <-
readRDS("FR-shared_data_for_JAGS.rds")` will load a named list
with all necessary objects. See Appendix A2 for the model code and
descriptions of objects contained in the
list.FR-shared_data_for_JAGS.rdsData list for JAGS model: Front Range
transects, all speciesList (R data structure) of data required to predict
occurrences and richness along the two Front Range transects with all
species detected in the Front Range, using a model parameterized with the
San Juan range. This requires generating species-specific responses from
the parameterized genus-level or family-level distributions. Loading the
file in R with `FR.all.ls <-
readRDS("FR-all_data_for_JAGS.rds")` will load a named list with
all necessary objects. See Appendix A2 for the model code and descriptions
of objects contained in the list.FR-all_data_for_JAGS.rds
USA
Colorado