DOI: 10.5061/dryad.xwdbrv1nm
title: Iowa herptile detection histories and landcover metrics

description: Predictions of species occurrence allow land managers to focus
 conservation efforts on locations where species are most likely to occur.
 Such analyses are rare for herpetofauna compared to other taxa, despite
 increasing evidence that herptile populations are declining because of
 land cover change and habitat fragmentation. Our objective was to create
 predictions of occupancy and colonization probabilities for 15 herptiles
 of greatest conservation need in Iowa. From 2006–2014, we surveyed 295
 properties throughout Iowa for herptile presence using timed
 visual-encounter surveys, coverboards, and aquatic traps. Data were
 analyzed using robust design occupancy modeling with landscape-level
 covariates. Occupancy ranged from 0.01 (95% CI = -0.01, 0.03) for prairie
 ringneck snake (Diadophis punctatus arnyi) to 0.90 (95% CI = 0.898, 0.904)
 for northern leopard frog (Lithobates pipiens). Occupancy for most species
 correlated to landscape features at the 1-km scale. General patterns of
 species’ occupancy included the negative effects of agricultural features
 and the positive effects of water features on turtles and frogs.
 Colonization probabilities ranged from 0.007 (95% CI = 0.006, 0.008) for
 spiny softshell turtle (Apalone spinifera) to 0.82 (95% CI = 0.62, 1.0)
 for western fox snake (Pantherophis ramspotti). Colonization probabilities
 for most species were best explained by the effects of water and grassland
 landscape features. Predictive models had strong support (AUC &gt;
 0.70) for six out of 15 species (40%), including all three turtles
 studied. Our results provide estimates of occupancy and colonization
 probabilities and spatial predictions of occurrence for herptiles of
 greatest conservation need across the state of Iowa.
description: We used three different methods for surveying herptiles
 throughout Iowa from 2006–2014. Occurrence data collected using all
 methods were compiled for all years to establish a single occurrence
 history for each species on each property. Properties were also clipped to
 the known ranges of each species, resulting in unequal sample sizes for
 each species. We conducted standardized visual
 encounter surveys for herptiles each year from April to October. This
 survey method involved a timed search on each property at the beginning of
 the survey year. We divided each year into three survey seasons to
 minimize seasonal variation in the detection probability of different
 species. Those seasons were spring (15 April–15 June), summer (16 June–15
 August), and fall (16 August–15 October). We surveyed each property for
 four person-hours twice during each of the three survey seasons for a
 maximum of six visits (24 person-hours) per year. We surveyed properties
 only during the year in which they were selected except for those
 properties that were selected for annual surveys. Surveys were conducted
 two weeks apart on average to increase independence among visits. During
 the spring and fall, we conducted surveys during warmer hours of the day,
 which typically fell between 10:00 hours and 18:00 hours, to maximize
 detection probabilities. Two species, Cope’s gray treefrog (<em>Hyla
 chrysoscelis</em>) and eastern gray treefrog (<em>Hyla
 versicolor</em>) can only be distinguished via auditory detections.
 Given that we could not confidently differentiate between the two species,
 we combined their detection histories and modeled both species in
 aggregate as the gray treefrog complex. We also placed
 coverboards at both systematic and random locations on the property to
 increase detection probabilities for herptiles. Six coverboards were
 placed systematically in a hexagonal arrangement 200 m apart in the core
 habitat type on the property and an additional nine coverboards were
 placed in locations that seemed most likely to capture individuals, for a
 total of 15 coverboards per property. Coverboards are frequently used by
 many species of herpetofauna as habitats for thermoregulation and cover,
 but may be a more efficient method for capturing reptiles than amphibians.
 Each coverboard was marked with a global positioning system (GPS) unit and
 checked during each visual encounter survey. All herptiles observed during
 the survey were identified to species. Surveys were not conducted on cool
 days (&lt; 10°C) or during periods of rain. Lastly,
 we used aquatic traps to target amphibians and turtles. We set a variety
 of aquatic traps, which typically consisted of three hoop nets, three box
 traps, three fish traps, and up to six minnow traps, for two trap nights
 once per each of three survey seasons described above for a total of six
 trap nights per property. We identified water bodies on each property,
 which included ponds, wetlands, lakes, rivers, and streams. Aquatic traps
 were placed within waterbodies at locations deemed most likely for
 captures. We baited larger traps with fish (e.g., sardines, dead grass
 carp [<em>Ctenopharyngodon idella</em>]) and checked traps
 once daily. We replaced bait as needed when traps were checked.
 We used ArcGIS (ver. 10.1) to measure landscape-level habitat
 variables within 200-m, 500-m, and 1000-m radii of each property. Buffers
 at each scale were placed around each survey mid-point for each property
 using the buffer tool in the ArcGIS toolbox (Analysis Tools, Proximity,
 Buffer). We then clipped a 2009 Iowa Landcover file, developed by the Iowa
 Department of Natural Resources, to all buffers at all properties. The
 2009 Iowa Landcover was developed using satellite imagery and includes six
 landcover types: water, agriculture, development, wetland, woodland, and
 grassland. These land cover types were selected due to their potential
 influence on our focal species and their interest in land managers. We
 opted to use landcover data for Iowa from 2009 because it is centered in
 our time series of surveys (2006-2014) and because the file is higher
 resolution (3m) than most other landcover products. We
 used FRAGSTATS (ver. 3.4) to summarize landcover metrics at each buffer.
 FRAGSTATS is a computer program that analyzes spatial patterns based on
 categorical maps and allows the user to pick from a variety of metrics to
 assess landscape configuration. We used the percentage of landscape
 (PLND), largest patch index (LPI), patch density (PD), and edge density
 (ED) for all analyses. The percentage of the landscape is the area of a
 land-use classification divided by the total area of the landscape. The
 largest patch index is the area of the largest patch of a land-use
 classification divided by the total area of the landscape. Patch density
 is the count of patches corresponding to a land-use classification divided
 by the landscape area. Edge density is the amount of linear edge on the
 landscape for a land-use classification divided by landscape area. We
 extracted each FRAGSTATS metric for each of the six landcover types within
 three different spatial scales (200, 500, and 1000 m radii) to be included
 as prediction covariates in our models. For a more
 detailed description of herptile survey methodology, see the Iowa
 Department of Natural Resources manual on their Multiple Species Inventory
 and Monitoring (MSIM) program: 
 https://www.iowadnr.gov/Conservation/Iowas-Wildlife/Wildlife-Diversity-Program/Diversity-Projects For more information on how landcover data were derived and collected see Harms et al. 2017: https://doi.org/10.1371/journal.pone.0173041
description: # Iowa herptile detection histories and landcover metrics
 [https://doi.org/10.5061/dryad.xwdbrv1nm](https://doi.org/10.5061/dryad.xwdbrv1nm) We surveyed 295 properties throughout Iowa for herptile presence using timed visual-encounter surveys, cover boards, and aquatic traps from 2006-2014. We aggregated data into presence/absence for 17 species of greatest conservation need for analyses using robust-design occupancy models. We used ArcGIS (ver. 10.1) to measure landscape-level habitat variables derived from a 2009 Iowa Landcover file developed by the Iowa Department of Natural Resources. At 200 m, 500 m, and 1000 m radii, we recorded six land cover types: water, agriculture, wetland, woodland, and grassland. We then used FRAGSTATS (ver. 3.4) to summarize landcover metrics, including the percentage of landscape (PLND), largest patch index (LPI), patch density (PD), and edge density (ED) for all analyses. ## Description of the data and file structure The Excel file consists of 17 tabs, representing each herptile species surveyed and labeled with species' common names. The data setup for each species is identical and is intended to be used for multi-season occupancy modeling in Program Mark or RMark, where rows correspond to properties and columns contain data on detection histories, landcover covariates, and detection covariates. **Columns 1 and 3**- Indicate to Program Mark or RMark that data between those columns (in this case, Property Name) are not relevant to analyses. **Column 2**- Property names where herptile surveys were conducted. **Column 4**- Detection histories for each species across visits and sites, with 0's representing surveys without detections, 1's representing surveys with detections, and periods representing a day without surveys. **Columns 5:80**- Data on land cover metrics for each property. The first letters of the column labels identify the landcover type as either water (Wtr), agriculture (Ag), wetland (Wtl), woodland (Wod), or grassland (Grs). The numbers in the middle of column labels show the scale at which the landcover data were collected (200 m, 500 m, and 1 km radii around each survey location). The final letters in the column labels identify the landcover metric used, being the percentage of landscape (PLND), largest patch index (LPI), patch density (PD), and edge density (ED). **Columns 81:652**- Air temperature in Fahrenheit at the time of the survey. The number of columns corresponds to the number of days during the entire survey period. A zero in these cells indicates that a survey was not done at that property on that day.  **Columns 653:1224**- The percentage of cloud cover at the time of survey. The number of columns corresponds to the number of days during the entire survey period. A zero in these cells indicates that a survey was not done at that property on that day.  **Columns 1225:1796**- Wind speed (mph) at the time of the survey. The number of columns corresponds to the number of days during the entire survey period. A zero in these cells indicates that a survey was not done at that property on that day.