DOI: 10.5061/dryad.6q573n68m
title: Using Anuran community diversity and Pseudacris crucifer to predict landscape quality across a land use gradient

description: As human-modified landscapes and climate changes proliferate, maintaining
 biodiversity and understanding the function and quality of available
 habitat is imperative. As anurans (frogs/toads) such as Pseudacris
 crucifer, can be an indicator species of habitat quality and ecosystem
 productivity, studying the anuran community in a mixed-land use region
 provides an opportunity to better understand the relationship between
 species and landscape modification. We explored the relationship between
 anurans and ecosystem productivity by assessing the effects of spatial and
 temporal heterogeneity on the presence of anurans across a land use
 gradient. Within the Toledo Metropolitan Area, including the biodiversity
 hotspot Oak Openings Region, we surveyed 67 different wetlands (N=1800)
 over three years. There was a difference in community assemblage between
 rural and suburban/urban habitats driven by human modification (impervious
 surface), composition (landcover type), and productivity (NDVI). The
 variation in spatial structure but lack of variation in temporal variables
 suggests that spatial factors explain differences in the anuran community
 among sites. Areas with more impervious surfaces, lower amounts of swamp
 forest, and lower NDVI generally had significantly fewer anuran species (p
 &lt; 0.001, p = 0.001, p = 0.013), significantly lower average species
 per survey (p &lt; 0.001, p = 0.011, p = 0.005), and lower relative
 abundance of anurans. Utilizing Generalized Linear Mixed Modeling, we
 found that P. crucifer relative abundance (p = 0.006) and greater species
 richness (p = 0.021) were the best predictors of ecosystem productivity.
 Our research demonstrates the value of non-invasive anuran call surveys to
 assess ecosystem productivity and species richness on a large scale, while
 also offering a method to evaluate conservation efforts internationally.
 This scalable approach can be applied anywhere with available
 environmental data, and we recommend utilizing anurans as indicator taxa
 for understanding ecosystem function, especially in human-modified
 landscapes.
description: # Using Anuran community diversity and *Pseudacris crucifer* to predict
 landscape quality across a land use gradient Dataset DOI:
 [10.5061/dryad.6q573n68m](10.5061/dryad.6q573n68m) ## Description of the
 data and file structure This data was collected over three field seasons
 (1 March through 1 August) from 2021-2023, assessing the relationship
 between anthropogenic land use change and anuran species
 diversity/density.  **Within sheet 1 (Master Collapsed Data 21-23 for R
 analysis):** Cells in columns A through E display data about the sites
 surveyed, the year of the survey, and the number of surveys conducted.
 Within the "Class" column (D), Class #1 = rural sites, #2 =
 suburban, #3 = urban. Columns H through BE display data regarding anuran
 species surveyed, with WCHF = Western chorus frog, NSPP = Northern spring
 peeper, NOLF = Northern leopard frog, WOOF = wood frog, EAMT = Eastern
 American toad, GRTF = gray tree frog complex, FOWT = Fowler's toad,
 BCRF = Blanchard's cricket frog, GREF = green frog, and BULF =
 bullfrog. In species "intensity" columns, 0 values were replaced
 by 1e-14.  Columns BF through FX display habitat and environmental data
 for each site across the three years of surveying. Columns BG through BL,
 BN, BO, BS, and BT are averages taken from several measurements at the
 beginning and end of each field season. BY through EW are values drawn
 from spatial analysis based on a 250-meter or 1km buffer surrounding the
 survey point. EX through FX display either averages or single values
 regarding many weather variables taken from the nearest weather station to
 the survey point across the time period indicated (February = 2, March =
 3, August = 8, September = 9). ### Files and variables #### File:
 Master\_Collapsed\_Data\_21-23\_for\_R\_analysis.xls **Description:** NA
 cell values coded as "-" Class #1 = rural sites, #2 = suburban,
 #3 = urban WCHF = Western chorus frog, NSPP = Northern spring peeper, NOLF
 = Northern leopard frog, WOOF = wood frog, EAMT = Eastern American toad,
 GRTF = gray tree frog complex, FOWT = Fowler's toad, BCRF =
 Blanchard's cricket frog, GREF = green frog, and BULF = bullfrog.
 February = 2, March = 3, August = 8, September = 9 ##### Variables Site =
 Name of site Year = year of survey SiteNum = number assigned to each site 
 Class = urbanization class (1 = rural, 2 = suburban, 3 = urban) NumSurv =
 number of surveys at the site during the survey year TotalRichness =
 number of species recorded at that site during the survey year
 AvgSppsurvey = average species per survey WCHF (or other species
 abbreviation) = species presence WCHFIntensity (or other species
 abbreviation) = species calling intensity, on a scale of 1 to 3 WCHFavg =
 percentage of surveys a species was detected WCHFIntAvg = average
 intensity of a species over all surveys  WCHFRelative = relative abundance
 of a species detected, based on the species' calling intensity and
 percentage of surveys encountered Elev = elevation (in meters) ChngLitDep
 = change in litter depth from March to July (centimeters) ChngGrsHi =
 change in grass height from March to July (cm) ChngLitCov = change in
 litter cover from March to July (cm) ChngGrsCov = change in grass cover
 from March to July (cm) ChngBgCov = change in bare ground cover from March
 to July (cm) ChngOthCov = change in other cover from March to July (cm)
 NumCoarseWoody = number of coarse woody debris encountered ChngEmVeg =
 change in emergent vegetation from March to July (percentage, estimated by
 surveyor) ChngFloVeg = change in floating vegetation from March to July
 (percentage, estimated by the surveyor) NumSnags = number of snags
 encountered NumShrbs = number of shrubs encountered NumTrees =  number of
 trees encountered ChngCanCov = change in canopy cover from March to
 July (percentage) ShrubCover = shrub cover (percentage, calculated based
 on the diameter of the shrub) FineWoody  = number of fine woody debris
 encountered  TrafficCount = raw number of cars passing in the test time
 period (from Ohio Department of Transportation (ODOT) data during the most
 recent traffic survey period) AADT = Annual Average Daily Traffic (from
 ODOT data) 6to6Traffic Count = traffic count between 6 pm and 6 am (from
 ODOT data) PercentImp = percent impervious surface within a 250m (meter)
 circle of the survey point, from the US Geological Survey (USGS)
 impervious surface raster AvgNDVI250m = average NDVI (normalized
 difference vegetation index) within a 250m circle of the survey point from
 March through July, from the USGS' EarthExplorer tool EarlyNDVI250m =
 NDVI within a 250m circle of the survey point in March, from the
 USGS' EarthExplorer tool LateNDVI250m = NDVI within a 250m circle of
 the survey point in July, from the USGS' EarthExplorer tool
 PercentTurf = percentage of turf within a 250m circle of the survey point,
 based on landcover data from Martin and Root (2020)  Percent2Wp
 = percentage of wet prairie within a 250m circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc3RMX = percentage
 of residential/mixed use within a 250m circle of the survey point, based
 on landcover data from Martin and Root (2020)  Percent4PerPns = percentage
 of perennial ponds within a 250m circle of the survey point, based on
 landcover data from Martin and Root (2020)  Perc5UpSav = percentage of
 upland savanna within a 250m circle of the survey point, based on
 landcover data from Martin and Root (2020)  Perc6Wtshr = percentage of wet
 shrubland within a 250m circle of the survey point, based on landcover
 data from Martin and Root (2020)  Perc7SwmpFor = percentage of swamp
 forest within a 250m circle of the survey point, based on landcover data
 from Martin and Root (2020)  Perc8UpCon = percentage of upland coniferous
 within a 250m circle of the survey point, based on landcover data from
 Martin and Root (2020)  Perc9UpDec = percentage of upland deciduous within
 a 250m circle of the survey point, based on landcover data from Martin and
 Root (2020)  Perc10FldFrst = percentage of floodplain forest within a 250m
 circle of the survey point, based on landcover data from Martin and Root
 (2020)  Perc11SandBarrens = percentage of sand barrens within a 250m
 circle of the survey point, based on landcover data from Martin and Root
 (2020)  Perc12EurM = percentage of Eurasian meadow within a 250m circle of
 the survey point, based on landcover data from Martin and Root (2020) 
 Perc13Upprair = percentage of upland prairie within a 250m circle of the
 survey point, based on landcover data from Martin and Root (2020) 
 Perc14Urb = percentage of urban within a 250m circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc60Cropland
 = percentage of cropland within a 250m circle of the survey point, based
 on landcover data from Martin and Root (2020)  PercOtB, PercTdA, PercOaC,
 PercGr, PercCoB, PercSh, PercW, PercGF, PercRnA, PercSo, PercOaB, PercMf,
 PercUo, PercByA, PercSdB, PercOuB, PercCe, PercSuE3, PercEe, PercDdA,
 PercBxA, PercCo, PercUn, PercBxB, PercDsA, PercSmC, PercPq, PercSmB,
 PercWt, PercDcA, PercSmD, PercLf, PercDgB, PercHoA, PercDgA, PercSnB,
 PercCp, PercDtA, PercDoA - percentage of soil values within a 250m circle
 from survey point (not used in this analysis) PercImp1km =  percentage of
 impervious surface within a 1km circle of the survey point, based on
 landcover data from Martin and Root (2020)  AvgNDVI1km = average NDVI
 (normalized difference vegetation index) within a 1km circle of the survey
 point from March through July, from the USGS' EarthExplorer tool
 EarlyNDVI1km = early NDVI within a 1km circle of the survey point in
 March, from the USGS' EarthExplorer tool LateNDVI1km = late NDVI
 within a 1km circle of the survey point in July, from the USGS'
 EarthExplorer tool PercTurf1km = percentage of turf within a 1km circle of
 the survey point, based on landcover data from Martin and Root (2020) 
 Perc2WP1km = percentage of wet prairie within a 1km circle of the survey
 point, based on landcover data from Martin and Root (2020)  Perc3RMX1km =
 percentage of residential/mixed-use land within a 1km circle of the survey
 point, based on landcover data from Martin and Root (2020)  Perc4PerP1km =
 percentage of perennial ponds within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc5UpSav1km =
 percentage of upland savanna within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc6Wtshr1km =
 percentage of wet shrubland within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc7SwmpFor1km =
 percentage of swamp forest within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc8UpCon1km = percentage
 of upland coniferous forest within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc9UpDec1km = percentage
 of upland deciduous forest within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc10FldFrst1km =
 percentage of floodplain forest within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc11SandBarrens1km
 = percentage of sand barrens within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)   Perc12EurM1km =
 percentage of Eurasian meadow within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc13Upprair1km  =
 percentage of upland prairie within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc14Urbkm =
 percentage of urban area within a 1km circle of the survey point, based on
 landcover data from Martin and Root (2020)  Perc60Cropland1km = percentage
 of cropland within a 1km circle of the survey point, based on landcover
 data from Martin and Root (2020)  PrevYr3to8avgprecip = average
 precipitation from March through August in centimeters during the year
 before the survey PrevYr3to8numdayswithprecip = number of days with
 precipitation from March through August during the year before the survey
 PrevYr3to8totalprecip = total precipitation from March through August in
 centimeters during the year before the survey PrevYr3to8avgtemp = average
 temperature from March through August in Celsius during the year before
 the survey PrevYr3to8avgMintemp = average minimum temperature from March
 through August in Celsius during the year before the survey
 Prevyr3to8avgMaxtemp = average maximum temperature from March through
 August in Celsius during the year before the survey PrevYr3to8avgwindspd =
 average wind speed from March through August in miles per hour during the
 year before the survey PrevWinter9to2avgprecip = average precipitation
 from September through February in centimeters during the winter before
 the survey PrevWint9to2Numdayswprecip = number of days precipitation from
 September through February in centimeters during the winter before the
 survey PrevWint9to2totalprecip = total precipitation from September
 through February in centimeters during the winter before the survey
 PrevWint9to2avgtemp = average temperature from September through February
 in Celsius during the winter before the survey PrevWint9to2Avgmintemp =
 average minimum temperature from September through February in Celsius
 during the winter before the survey PrevWint9to2Avgmaxtemp = average
 maximum temperature from September through February in Celsius during the
 winter before the survey PrevWint9to2avgwindspeed = average wind speed
 from September through February in miles per hour during the winter before
 the survey Inyear3to8avgprecip = average precipitation from March through
 August in centimeters during the year of the survey
 Inyear3to8numprecipdays = number of days with precipitation from March
 through August in centimeters during the year of the survey
 Inyear3to8totalprecip = total precipitation from March through August in
 centimeters during the year of the survey Inyear3to8Avgtemp = average
 temperature from March through August in Celsius during the year of the
 survey Inyear3to8avglowtemp = average temperature from March through
 August in Celsius during the year of the survey Inyear3to8averagehitemp =
 average high temperature from March through August in Celsius during the
 year of the survey Inyear3to8avgwindspeed = average wind speed from March
 through August in miles per hour during the year of the survey
 NumD1Weekinyear3to8 = number of weeks under D1 drought conditions
 (moderate drought) from March through August during the year of the survey
 NumD1WeeksPrevWinter9to2 = number of weeks under D1 drought conditions
 (moderate drought) from September through February during the previous
 winter of the survey NumD1weeksPrevBreedingseason3to8 = number of weeks
 under D1 drought conditions (moderate drought) from March through August
 during the year before the survey NumD0Weeksinyear3to8 = number of weeks
 under D0 drought conditions (abnormally dry) from March through August
 during the year of the survey NumD0weeksPrevWinter9to2 = number of weeks
 under D0 drought conditions (abnormally dry) from September through
 February during the previous winter NumD0weeksPrevBreedingSeason3to8 =
 number of weeks under D0 drought conditions (abnormally dry) from March
 through August during the year before the survey #### File:
 Mini\_Collapsed\_Data\_21-23\_for\_R\_for\_avg\_spp\_survey\_only.xls
 **Description:** **Within sheet 2 (Mini collapsed data 21-23 for R for avg
 spp survey only):** These data were used only for the analysis of factors
 that may have influenced the average species heard per survey.  Cells in
 columns A through E display data about the sites surveyed, the year of
 survey, and the number of surveys conducted. Within the "Class"
 column (D), Class #1 = rural sites, #2 = suburban, #3 = urban. Columns F
 and G display data regarding anuran species detected during the surveys
 across each year. Columns H through BL include many of the same habitat
 data measurements as in sheet 1. Columns I-N, P, Q, U, V are averages of
 several measures taken at both the beginning and end of the field season.
 Columns H, O, R-T, and W-Y display single values or averages. AA through
 BL are values drawn from spatial analysis based on a 250-meter buffer
 surrounding the survey point.  NA cell values coded as "-" Class
 #1 = rural sites, #2 = suburban, #3 = urban February = 2, March = 3,
 August = 8, September = 9 ##### Variables Site = Name of site Year = year
 of survey SiteNum = number assigned to each site  Class = urbanization
 class (1 = rural, 2 = suburban, 3 = urban) NumSurv = number of surveys at
 the site during the survey year TotalRichness = number of species recorded
 at that site during the survey year AvgSppsurvey = average species per
 survey Elev = elevation (in meters) ChngLitDep = change in litter depth
 from March to July (centimeters) ChngGrsHi = change in grass height from
 March to July (cm) ChngLitCov = change in litter cover from March to July
 (cm) ChngGrsCov = change in grass cover from March to July (cm) ChngBgCov
 = change in bare ground cover from March to July (cm) ChngOthCov = change
 in other cover from March to July (cm) NumCoarseWoody = number of coarse
 woody debris encountered ChngEmVeg = change in emergent vegetation from
 March to July (percentage, estimated by surveyor) ChngFloVeg = change in
 floating vegetation from March to July (percentage, estimated by the
 surveyor) NumSnags = number of snags encountered NumShrbs = number of
 shrubs encountered NumTrees =  number of trees encountered ChngCanCov =
 change in canopy cover from March to July (percentage) ShrubCover = shrub
 cover (percentage, calculated based on the diameter of the shrub)
 FineWoody  = number of fine woody debris encountered  TrafficCount = raw
 number of cars passing in the test time period (from Ohio Department of
 Transportation data during the most recent traffic survey period) AADT =
 Annual Average Daily Traffic (from ODOT data) 6to6Traffic Count =  traffic
 count between 6 pm and 6 am (from ODOT data) PercentImp = percent
 impervious surface within a 250m (meter) circle of the survey point, from
 the US Geological Survey impervious surface raster AvgNDVI250m = average
 NDVI (normalized difference vegetation index) within a 250m circle of the
 survey point from March through July, from the USGS' EarthExplorer
 tool EarlyNDVI250m = NDVI within a 250m circle of the survey point in
 March, from the USGS' EarthExplorer tool LateNDVI250m = NDVI within a
 250m circle of the survey point in July, from the USGS' EarthExplorer
 tool PercentTurf = percentage of turf within a 250m circle of the survey
 point, based on landcover data from Martin and Root (2020)  Percent2Wp
 = percentage of wet prairie within a 250m circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc3RMX = percentage
 of residential/mixed use within a 250m circle of the survey point, based
 on landcover data from Martin and Root (2020)  Percent4PerPns = percentage
 of perennial ponds within a 250m circle of the survey point, based on
 landcover data from Martin and Root (2020)  Perc5UpSav = percentage of
 upland savanna within a 250m circle of the survey point, based on
 landcover data from Martin and Root (2020)  Perc6Wtshr = percentage of wet
 shrubland within a 250m circle of the survey point, based on landcover
 data from Martin and Root (2020)  Perc7SwmpFor = percentage of swamp
 forest within a 250m circle of the survey point, based on landcover data
 from Martin and Root (2020)  Perc8UpCon = percentage of upland coniferous
 within a 250m circle of the survey point, based on landcover data from
 Martin and Root (2020)  Perc9UpDec = percentage of upland deciduous within
 a 250m circle of the survey point, based on landcover data from Martin and
 Root (2020)  Perc10FldFrst = percentage of floodplain forest within a 250m
 circle of the survey point, based on landcover data from Martin and Root
 (2020)  Perc11SandBarrens = percentage of sand barrens within a 250m
 circle of the survey point, based on landcover data from Martin and Root
 (2020)  Perc12EurM = percentage of Eurasian meadow within a 250m circle of
 the survey point, based on landcover data from Martin and Root (2020) 
 Perc13Upprair = percentage of upland prairie within a 250m circle of the
 survey point, based on landcover data from Martin and Root (2020) 
 Perc14Urb = percentage of urban within a 250m circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc60Cropland
 = percentage of cropland within a 250m circle of the survey point, based
 on landcover data from Martin and Root (2020)  PercImp1km =  percentage of
 impervious surface within a 1km circle of the survey point, based on
 landcover data from Martin and Root (2020)  AvgNDVI1km = average NDVI
 (normalized difference vegetation index) within a 1km circle of the survey
 point from March through July, from the USGS' EarthExplorer tool
 EarlyNDVI1km = early NDVI within a 1km circle of the survey point in
 March, from the USGS' EarthExplorer tool LateNDVI1km = late NDVI
 within a 1km circle of the survey point in July, from the USGS'
 EarthExplorer tool PercTurf1km = percentage of turf within a 1km circle of
 the survey point, based on landcover data from Martin and Root (2020) 
 Perc2WP1km = percentage of wet prairie within a 1km circle of the survey
 point, based on landcover data from Martin and Root (2020)  Perc3RMX1km =
 percentage of residential/mixed-use land within a 1km circle of the survey
 point, based on landcover data from Martin and Root (2020)  Perc4PerP1km =
 percentage of perennial ponds within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc5UpSav1km =
 percentage of upland savanna within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc6Wtshr1km =
 percentage of wet shrubland within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc7SwmpFor1km =
 percentage of swamp forest within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc8UpCon1km = percentage
 of upland coniferous forest within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc9UpDec1km = percentage
 of upland deciduous forest within a 1km circle of the survey point, based
 on landcover data from Martin and Root (2020)  Perc10FldFrst1km =
 percentage of floodplain forest within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc11SandBarrens1km
 = percentage of sand barrens within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)   Perc12EurM1km =
 percentage of Eurasian meadow within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc13Upprair1km  =
 percentage of upland prairie within a 1km circle of the survey point,
 based on landcover data from Martin and Root (2020)  Perc14Urbkm =
 percentage of urban area within a 1km circle of the survey point, based on
 landcover data from Martin and Root (2020)  Perc60Cropland1km = percentage
 of cropland within a 1km circle of the survey point, based on landcover
 data from Martin and Root (2020)  ## Code/software R v. 4.3.2, with the
 packages lme4, conflicted, dplyr, emmeans, coda, reshape2, lattice, car,
 ggpubr, unmarked, lme4, Matrix, nlme, glmm, reshape, MASS, DHARMa,
 performance, glmmTMB, bbmle, readxl