DOI: 10.5061/dryad.02v6wwqhg
title: Data from: Combining thermal and hydric constraints for spatially predicting the activity suitability of Neotropical Leptodactylid frogs

description: The data integrate empirical physiological, behavioral, and environmental
 parameters to mechanistically assess how temperature and hydration jointly
 constrain amphibian activity across space and time. We combined
 experimentally obtained laboratory data — including thermal performance
 curves for locomotor function, critical thermal limits (CTmin and CTmax),
 evaporative water loss rates, and dehydration tolerance — with
 microclimatic datasets. Using these empirical inputs and ready-to-use
 microclimatic dataset, we parameterized a biophysical modeling workflow
 that links organismal heat and mass transfer processes with ground-level
 microclimate conditions. The R scripts provide mechanistic simulations
 used to estimate hourly body temperatures, evaporative water loss, and
 cumulative constraints on surface activity time for three Neotropical frog
 species (Leptodactylus fuscus, L. mystacinus, and L. macrosternum). Model
 outputs include spatially explicit maps of thermal, hydric, and combined
 suitability throughout each species’ current distribution and across
 seasonal phases. This dataset and accompanying R code support these
 results and provide a detailed framework for integrating physiological and
 environmental data to model activity suitability under interacting thermal
 and hydric constraints, offering a reproducible basis for future
 mechanistic distribution modeling.
description: # Data from: Combining thermal and hydric constraints for spatially
 predicting the activity suitability of Neotropical Leptodactylid frogs
 Dataset DOI:
 [10.5061/dryad.02v6wwqhg](https://doi.org/10.5061/dryad.02v6wwqhg) ##
 Description of the data and file structure Overview Amphibians balance
 their thermal and hydric budgets in response to environmental conditions,
 with both temperature and hydration jointly constraining activity. Yet,
 most mechanistic approaches generally emphasize thermal over water
 limitations. We used a mechanistic modeling framework to assess how
 interacting thermal and hydric constraints shape the potential activity of
 three ground-dwelling Neotropical frogs (*Leptodactylus fuscus*, *L.
 mystacinus*, and *L. macrosternum*) across their geographic
 ranges. Laboratory-derived physiological data—including thermal
 performance curves, critical thermal limits (CTmin and CTmax), evaporative
 water loss rates, skin resistance, and dehydration tolerance—were
 integrated with microclimatic simulations to parameterize a spatially
 explicit biophysical model. The model computes organismal heat and water
 exchanges to estimate hourly body temperatures, evaporative water loss,
 and nighttime activity time under varying environmental conditions. Model
 outputs were used to generate thermal, hydric, and joint activity
 suitability maps across species distributions and seasonal phases. Results
 revealed that low rather than high temperatures were the main thermal
 constraint on nocturnal activity, whereas hydric limitations were body
 size-dependent, being most restrictive for smaller species. This
 integrative workflow highlights how mechanistic modeling grounded in
 empirical physiology can reveal species-specific sensitivities to
 interacting thermal and hydric stressors across space and time. ### Files
 and variables All data files and variables are annotated within each R
 script across folders, including variable names and units of measurement.
 Each step of the processing and analysis pipeline contains comments
 specifying the origin, structure, and function of variables and dataset
 used. Where applicable, consistent variable definitions are applied across
 scripts (provided in-line within each code chunk). #### File:
 Senzano_et_al_mechanistic_sdm.zip **Description:**  This repository
 contains the datasets and R scripts used to generate all mechanistic
 simulations and analyses reported in the associated publication. The
 workflow integrates empirical, physiological, and performance data with
 microclimatic and spatial datasets to predict the joint effects of
 temperature and hydric constraints on the nighttime activity suitability
 of three Neotropical Leptodactylus frogs (*L*. *fuscus*, *L*.
 *mystacinus*, and *L*. *macrosternum*). Repository structure ├── 01_sdm/ 
                              # ensemble species distribution modeling
 (SDMs) │ ├── data/                                 # resources for running
 ensemble species distribution models (SDMs) │ │ ├── 00_bio.currSouthAm/ #
 ready-to-use microclimatic variables (GeoTIFF files) │ │ ├── extra/       
                      # complementary R functions (contained within R and
 RDS files) │ │ └── occ/                                # cleaned
 georeferenced occurrence points for each species (csv files) │ └──
 01_ensemble.R                # Runs the ensemble SDM for species
 distributional ranges (R file) │ ├── 02_mechanistic_act/          #
 mechanistic modeling │ ├── 00_microclim/                  # ready-to-use
 microclimatic data from the ‘microclim’ dataset │ │ ├── 0pctShade/       
            # Tsub, Tair and RH in 0% shade conditions │ │ ├── 90pctShade/ 
                # Tsub, Tair and RH in 90% shade conditions (netCDF files)
 │ │ ├── SOLR/                             # solar radiation (netCDF file)
 │ │ └── V1cm/                             # wind speed (netCDF file) │ ├──
 01_heat_model_valid/     # biophysical model evaluation (field Tb vs.
 computed hourly Tb) │ │ └── data/                               #
 complementary resources for running model evaluation │ │ ├── agar_models/ 
           # empirical field Tb data collected from agar replicas (text
 file) │ │ └── extra/                          # auxiliary R functions (R
 file) │ ├── 02_database/                   # base data for simulations │ │
 ├── ewl_empirical/              # species-specific empirical evaporative
 water loss (EWL) (text files) │ │ ├── extra/                             
 # complementary R functions (R file) and South America shape file (RDS
 file) │ │ └── micro/                             # microclimatic data
 corrected for canopy classes │ │ ├── early/                             #
 early season │ │ │ ├── RH(relat_hum)/       # 1cm above-ground RH (netCDF
 file) │ │ │ ├── Soil(subst_temp)/    # substrate (Tsub) and below
 substrate (Tsub5) temperatures (netCDF files) │ │ │ ├── SOLR/             
           # solar radiation (netCDF file) │ │ │ ├── TA(air_Temp)/         
  # 1cm Tair (netCDF file) │ │ │ └── V1cm/                        # 1cm
 wind speed (netCDF file) │ │ ├── mid/                                # mid
 season │ │ │ ├── RH(relat_hum)/        # 1cm RH (netCDF file) │ │ │ ├──
 Soil(subst_temp)/     # Tsub and Tsub5 temperatures (netCDF files) │ │ │
 ├── SOLR/                         # solar radiation (netCDF file) │ │ │
 ├── TA(air_Temp)/           # 1cm Tair (netCDF file) │ │ │ ├── V1cm/     
                   # 1cm wind speed (netCDF file) │ │ └── late/           
                     # late season │ │ ├── RH(relat_hum)/        # 1cm RH
 (netCDF file) │ │ ├── Soil(subst_temp)/     # Tsub and Tsub5 temperatures
 (netCDF files) │ │ ├── SOLR/                         # solar radiation
 (netCDF file) │ │ ├── TA(air_Temp)/            # 1cm Tair (netCDF file) │
 │ └── V1cm/                         # 1cm wind speed (netCDF file) │ │ │
 ├── 03_Lfuscus/ │ │ └── mechanistic_mod_lf.R   # generates mechanistic
 thermal, hydric, and joint suitability maps # for L. fuscus (R file) │ ├──
 04_Lmystacinus/ │ │ └── mechanistic_mod_lm.R  # generates mechanistic
 thermal, hydric, and joint suitability maps # for L. mystacinus (R file) │
 └── 05_Lmacrosternum/ │ └── mechanistic_mod_lma.R  # generates mechanistic
 thermal, hydric, and joint suitability maps # for L. macrosternum (R file)
 └── README.txt ## Description of folder structure The repository is
 composed of two major components. '01_sdm/' contains the
 ensemble species distribution modeling (SDMs) workflow, while
 '02_mechanistic_act/' contains the mechanistic modeling workflow
 that integrates empirical physiological data and microclimatic inputs to
 simulate thermal and hydric constraints on frog activity. The .nc (NetCDF)
 files contained within the '02_mechanistic_act/00_microclim/'
 and '02_mechanistic_act/02_database/micro/' directories store
 spatially explicit hourly microclimatic variables used to parameterize the
 biophysical models. Each NetCDF file represents hourly climatic data at
 ~15 km spatial resolution across species-specific distributional ranges.
 The variables include air temperature (Tair, 1 cm above ground), substrate
 temperature (Tsub, surface), subsurface temperature (Tsub5, 5 cm depth),
 relative humidity (RH, 1 cm above ground), solar radiation (SOLR), and
 wind speed (V1cm, 1 cm above ground). The microclimatic variables come
 from the ready-to-use 'microclim' dataset (see Kearney et al.,
 2014;
 [http://dx.doi.org/10.6084/m9.figshare.878253](http://dx.doi.org/10.6084/m9.figshare.878253)). The '00_microclim/' folder contains the existing 'microclim' dataset of Kearney et al. (2014), specifically, for 0% and 90% canopy shading conditions, used to evaluate the biophysical model under field conditions representing sunny and shady scenarios. In turn, the nested directory '02_database/micro/' contains canopy-corrected 'microclim' datasets organized by seasonal phases, 'early/', 'mid/', and 'late/', corresponding respectively to the early (time of season when frogs emerge with the first seasonal rains), mid (frogs' peak activity during the most humid month), and end (when their activity gradually reduces as the rainy season ends) seasonal activity of frogs. Each seasonal folder is further subdivided by climatic variable ('RH/', 'Soil/', 'SOLR/', 'TA/', and 'V1cm/'), each holding NetCDF files with the corresponding hourly microclimatic data. All simulations were performed in the R language (version 4.1.1) under the Windows 11 operating system. The simulations can be reproduced by running the scripts sequentially, following the folder numbering that indicates their execution order. The workflow integrates various data components, including physiological traits, microclimate data, and species distributional ranges and procedures for model evaluation. Physiological traits comprise mean species-specific values obtained under laboratory conditions. Distributional ranges are derived from α-hull delimitation and species distribution model (SDM) procedures constructed from species' occurrence records. Validation datasets include field-based thermal data from agar replicas and laboratory evaporative water loss (EWL) measurements used to evaluate the predictive accuracy of the biophysical model. ## File types and extensions * NetCDF files (.nc): store gridded hourly microclimatic data. * GeoTIFF files (.tif): raster outputs from ensemble species distribution models and mechanistic simulations. * Comma-separated values (.csv): species occurrence records and tabular outputs from SDM models. * R scripts (.R): code executing analyses, complementary functions, and model simulations. * R data files (.RDS): serialized R objects (e.g., ready-to-use shapefiles). * Text files (.txt): field and empirical measurement data. ## Code/software The repository is fully self-contained and structured to run all simulations directly in R without requiring any additional software. All necessary data (raster datasets and physiological information), dependencies, and scripts (including used R-packages and specific functions, along with custom-made functions) are included and organized for complete reproducibility. For detailed information on experimental data collection, physiological trait quantification, the pretreatment of bioclimatic variables and microclimatic datasets, and modeling procedures and assumptions, please refer to the associated publication (Senzano et al., 2025, Ecography), which provides complete methodological and data acquisition details.