National Park Service U.S. Department of the Interior

Natural Resource Stewardship and Science Gulf Coast Network Texas Tortoise Monitoring in Palo Alto Battlefield National Historical Park Protocol Narrative—Version 3.0

Natural Resource Report NPS/GULN/NRR—2018/1816

ON THE COVER Texas tortoise, Gopherus berlandieri, at Palo Alto Battlefield National Historical Park. NPS photo/William Finney

Gulf Coast Network Texas Tortoise Monitoring in Palo Alto Battlefield National Historical Park Protocol Narrative—Version 3.0

Natural Resource Report NPS/GULN/NRR—2018/1816

Jane Carlson1, Robert L. Woodman1, Whitney Granger1, Jeff Bracewell1, Kurt Buhlmann2, James W. Garrett3, and Martha Segura1

1National Park Service Gulf Coast Inventory and Monitoring Network 646 Cajundome Blvd. Lafayette, LA 70506

2Savannah River Ecological Laboratory University of Georgia Aiken, SC 29801

3Auburn University School of Fisheries and Allied Aquaculture Swingle Hall, Auburn, AL 36849

The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, Colorado, publishes a range of reports that address natural resource topics. These reports are of interest and applicability to a broad audience in the National Park Service and others in natural resource management, including scientists, conservation and environmental constituencies, and the public. The Natural Resource Report Series is used to disseminate comprehensive information and analysis about natural resources and related topics concerning lands managed by the National Park Service. The series supports the advancement of science, informed decision-making, and the achievement of the National Park Service mission. The series also provides a forum for presenting more lengthy results that may not be accepted by publications with page limitations.

All manuscripts in the series receive the appropriate level of peer review to ensure that the information is scientifically credible, technically accurate, appropriately written for the intended audience, and designed and published in a professional manner.

This report received formal peer review by subject-matter experts who were not directly involved in the development or pilot implementation of the project. Peer review was conducted by highly qualified individuals with subject area technical expertise and was overseen by a peer review manager.

Views, statements, findings, conclusions, recommendations, and data in this report do not necessarily reflect views and policies of the National Park Service, U.S. Department of the Interior. Mention of trade names or commercial products does not constitute endorsement or recommendation for use by the U.S. Government.

This report is available in digital format from the Gulf Coast Network website and the Natural Resource Publications Management website. If you have difficulty accessing information in this publication, particularly if using assistive technology, please email [email protected].

Please cite this publication as:

Carlson, J. E., R. L. Woodman, W. Granger, J. Bracewell, K. Buhlmann, J. Garrett and M. Segura. 2018. Gulf Coast Network Texas tortoise monitoring in Palo Alto Battlefield National Historical Park: Protocol narrative—Version 3.0. Natural Resource Report NPS/GULN/NRR—2018/1816. National Park Service, Fort Collins, Colorado.

November 2018

U.S. Department of the Interior National Park Service Natural Resource Stewardship and Science FortNPS Collins,469/149469 Colorado, November 2018 ii

Change History

Version numbers will be incremented by a whole number (e.g., version 1.3 to version 2.0) when a change is made that significantly alters project requirements, procedures, continuity of the data, or interpretation of the data. Version numbers will be incremented by decimals (e.g., version 1.6 to version 1.7) when there are minor modifications that do not affect project requirements, procedures, data continuity or data interpretation.

Attribution notes: The network’s first ecologist, Robert Woodman, led the development of protocol versions 1 and 2, with major assistance from all co-authors. The network’s second ecologist, Jane Carlson, is responsible for updating, rewriting, and finalizing content for version 3, again with substantial co-author guidance.

Date Revised by Changes New Version #

10/2014 Robert Version 1 (completed in fall 2013) was updated to version 2 a 2.0 Woodman, Jim year later to refine and fully standardize field sampling time and Garrett effort and to establish a panel design, where seven 3-4 ha patches of tortoise habitat were identified at the park. Each of these patches was split into two 1.5 or 2 ha polygons: an A and a B polygon. Tortoise monitoring data were collected in A polygons one year and then B polygons the next. Additional major changes between versions 1 and 2 were updates to reflect new standards for formatting and content in protocol narratives.

8/2018 Jane Carlson, Version 2 underwent major revisions to improve the monitoring 3.0 Whitney objectives, sampling design and statistical analyses. For the Granger, Brian monitoring objectives, the scope of each objective was refined so Mitchell that each measurement had a clear purpose, and each analysis was feasible and appropriate for the design. For the sampling design, the A and B panels were combined and are now sampled every time, on a fall trip only. During that trip, each unit is surveyed twice, on different days and by different crews. One new unit was added to a previously unsampled loma and one unit was removed from a loma that previously had two. Finally, the single unit that was 3 hectares in size was increased to 4, so all units covered the same area. For the analyses, the mark- recapture data can now be analyzed using Pollock’s robust design models, closed population models (Lincoln-Petersen), or open population models (C-J-S).

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Contents

Page

Change History ...... iii

Figures...... ix

Tables ...... ix

List of Standard Operating Procedures (each published as a separate document) ...... xi

Executive Summary ...... xiii

Acknowledgments ...... xv

Background ...... 1

Program History ...... 1

Rationale for Monitoring Texas Tortoises in Palo Alto Battlefield NHP ...... 2

The Habitat ...... 2

The Tortoise...... 5

Potential Threats and Hazards to the Park’s Texas Tortoise Population ...... 8

Population Isolation ...... 8

Disease ...... 8

Human-Induced Losses ...... 8

Predation ...... 9

Habitat Alteration ...... 10

Project Development and Preliminary Findings ...... 10

Phase I: Need is Recognized, Project is Initiated and Pilot Work Begins ...... 10

Phase II: Effort is Standardized and Sampling Frame is Identified ...... 11

Phase III: Effort is Redistributed to Maximize Recaptures ...... 11

Summary and Preliminary Findings ...... 12

Monitoring Objectives ...... 15

Sampling Design ...... 17

Sampling Frame...... 17

Justification for Sampling Frame ...... 17 v

Contents (continued)

Identification of Major Lomas and Sampling Units ...... 18

Frequency, Timing and Schedule of Sampling ...... 20

Justification for Frequency, Timing and Schedule ...... 21

Frequency and Timing Across Trips ...... 21

Timing of Events within Trips ...... 22

Schedule of Events within Trips ...... 23

Sample Metrics and Their Measurement ...... 23

Detectable Levels of Change ...... 23

Field Methods ...... 27

Pre-season Field Preparation ...... 27

Permitting and Compliance ...... 28

Safety ...... 28

Supplies and Equipment ...... 28

Activities during and after Sampling ...... 29

Crew Roles and Activities during Visual Ground Search ...... 29

Disturbance to Tortoise ...... 30

Digital Photography...... 30

Post-Sampling Activities ...... 30

Data Management, Analysis, and Reporting ...... 33

Data Collection and Post-field Validation of Datasheets ...... 33

Overview of Database Approach ...... 34

Data Entry ...... 34

Database QA/QC ...... 34

Data Processing and Data Quality Levels ...... 35

Data Documentation, Product Posting, Distribution, and Archiving ...... 39

Protected Data ...... 39

Data Analyses and Reporting ...... 39 vi

Contents (continued)

Format and Contents of the Trip Report ...... 40

Format and Contents of the Status and Trends Report ...... 42

Analyses and Metrics of the Status and Trends Report ...... 42

Recommended Reporting Schedule and Delivery ...... 44

Procedure for Revising the Protocol ...... 45

Personnel Requirements and Training ...... 47

Staff Roles, Responsibilities, and Qualifications ...... 47

Network Program Manager ...... 47

Project Leader ...... 47

Field Crew Leaders...... 48

Field Crew Members ...... 49

Data Manager ...... 50

GIS Specialist ...... 50

Training Procedures...... 51

Operational Requirements ...... 53

Annual Workload and Field Schedule ...... 53

Facility and Equipment Needs ...... 53

Budget ...... 53

Personnel Costs ...... 54

Travel Costs ...... 54

Equipment and Supply Costs ...... 54

Project Funding ...... 54

Literature Cited ...... 57

Appendix A: Event-Level Datasheet ...... 63

Appendix B: Observer Datasheet, Half-sheet Size ...... 65

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Figures

Page

Figure 1. Texas tortoise with an important food source, prickly pear cactus (Opuntia engelmannii), in its natural habitat at Palo Alto Battlefield National Historical Park...... 2 Figure 2. Map of southern-most Texas, showing the location of Palo Alto Battlefield National Historical Park ...... 3 Figure 3. Dense Tamaulipan thornscrub (center) with insets showing a few of the diverse shrub species that occur there ...... 5

Figure 4. The geographic range of the Texas tortoise in the USA and Mexico ...... 7

Figure 5. The remains of a road-killed Texas tortoise that was found in August 2016 on the four-lane highway FM 1847, which spans the western border of Palo Alto Battlefield NHP...... 9

Figure 6. Timeline of major events for Texas tortoise monitoring at Palo Alto Battlefield NHP, including relevant dates for the park and tortoise research in the region ...... 13

Figure 7. (A) Tilted map image of LiDAR -derived bare earth elevations at Palo Alto Battlefield NHP ...... 17

Figure 8. Sampling units for Texas tortoise monitoring at Palo Alto Battlefield NHP ...... 19

Figure A-1. Example of Event-Level Datasheet...... 63

Figure B-1. Example of Observer Datasheet Half-sheet size, front...... 65

Figure B-2. Example of Observer Datasheet Half-sheet size, back...... 65

Tables

Page

Table 1. Recommended sampling order for two independent crews (called A and B) as they sample seven units (#1– #7) two times each over a three-day park trip ...... 21

Table 2. Data processing steps and products for the Texas tortoise monitoring protocol...... 36

Table 3. Example of the data summary table in a Texas Tortoise Monitoring Trip Report ...... 41 Table 4. Estimated annual budget for monitoring Texas tortoise at Palo Alto Battlefield NHP [na = not available or not applicable]...... 55

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List of Standard Operating Procedures (each published as a separate document)

TORT01: Sampling Crew Training and Safety

TORT02: Preparation for Sampling

TORT03: Performing Visual Ground Search

TORT04: Tortoise Handling, Photography, Measurement, and Marking

TORT05: Post-sampling Activities

TORT06: Entering Data into the Database

TORT07: Data Management

TORT08: Data Analysis and Reporting

TORT09: Protocol Revisions

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Executive Summary

The mission of the National Park Service (NPS) is to conserve unimpaired the natural and cultural resources of the national park system for the enjoyment of this and future generations (NPS 1999). To uphold this goal, the NPS has implemented a science-based program to document and monitor important natural resources in more than 270 parks, which are organized into 32 Inventory and Monitoring (I&M) networks. During program development each I&M network worked with its parks to identify a set of high-priority “Vital Signs” that are monitored as indicators of park ecosystem health. At Palo Alto Battlefield National Historical Park, the Gulf Coast Network (GULN) selected the Texas tortoise (Gopherus berlandieri) as one of their vital sign for long-term monitoring. This species is designated as threatened by the state of Texas due to population declines and range loss caused by habitat conversion. At the park, it is a valued faunal component of the park’s shrublands, which mainly occur on low-rising ridges called lomas.

The Texas tortoise population at Palo Alto Battlefield NHP is subject to several specific threats. First, park tortoises may be geographically isolated from outside populations by ditches, roads and developed lands. Second, park tortoises may be lost to illegal collection, road mortality, or predation. Third, park tortoises may be impacted by the conversion of some of the park’s shrublands into grasslands, in an effort to return park landscapes to the conditions present during the Mexican- American War in 1846. Long-term monitoring data will inform the park on how to best manage for and protect Texas tortoises and their habitats. These data will also contribute to the broader regional assessment of Texas tortoise populations across their limited geographic range. To monitor the park’s Texas tortoises, the Gulf Coast Network conducts a long-term mark-recapture study using time-and- area defined survey events that occur in the fall of each year. On seven permanent sampling units representing each of the park’s major lomas, tortoises are encountered, marked and measured, and their GPS locations are recorded.

Monitoring objectives addressed by this protocol include: 1. To provide a detailed depiction of the status of Texas tortoises across the park’s major lomas, including catch per unit effort, within-park tortoise movements, tortoise body condition, and the distribution of sizes and sexes captured. Catch per unit effort and tortoise body condition are also analyzed for change over time. 2. To assess tortoise population parameters across the park’s major lomas and track how these parameters change over time, including estimated abundance and survivorship from mark- recapture data.

The protocol consists of a narrative and nine standard operating procedures (SOPs). Together, these documents detail how the Gulf Coast Network collects, manages, disseminates, and reports on monitoring data for Texas tortoises over the long term, using statistically-defensible and repeatable methods. To the extent possible, trends detected in these data will be considered in light of park management actions, habitat alterations, and other stressors.

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Acknowledgments

This project was developed for vital sign monitoring by the Gulf Coast Network Inventory and Monitoring Program of the National Park Service. The authors thank Rolando Garza, Chief of Natural Resource Management at Palo Alto Battlefield National Historical Park (PAAL), for his invaluable contributions throughout the development and continued performance of this project. Additionally, we thank Tracey Tuberville of University of Georgia—Savannah Ecological Laboratory, for her professional insights into how to monitor this small and cryptic tortoise species. We also thank Greg Mitchell of San Antonio Missions National Historical Park for his energetic participation in field events and testing, as well as numerous volunteers that have helped with preliminary data collection at the park. Finally, we acknowledge the NPS Institutional Animal Care and Use Committee for their review and guidance on tortoise handling.

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Background

Program History The National Park Service (NPS) is tasked with managing park resources “unimpaired for the enjoyment of future generations” (NPS 1999), which requires both knowledge of current resource conditions and whether they are changing over time. To meet this information need, the NPS initiated a long-term ecological monitoring program known as Vital Signs Monitoring (Fancy et al. 2009). In this context, vital signs are a subset of park organisms and ecosystem processes selected to reflect the overall condition and health of park resources, reflect the effects of stressors, or have particular value to park visitors. The NPS Inventory and Monitoring (I&M) program monitors vital signs in over 270 national park units, with the goal of providing broad-based, scientifically-sound information to park management, park stakeholders, other scientists and the public.

Vital signs monitoring is implemented by the NPS I&M Division through 32 networks, which are regional groupings of parks (Fancy et al. 2009). All I&M network offices follow the same planning and design strategy for monitoring in their parks, which includes a network-wide monitoring plan and a series of peer-reviewed protocols that describe how data are collected, managed, analyzed, and reported for each vital sign (Oakley et al. 2003). Although each network creates their own monitoring protocols, they do so based on a shared suite of program-wide goals for integrated natural resource monitoring. As stated by Fancy et al. (2009), these goals are to: 1. “Determine the status and trends of selected indicators of park ecosystem conditions” for improved decision-making and collaboration; 2. “Provide early warning of abnormal conditions” to allow for timely mitigation and reduced management costs; 3. “Provide data to better understand” dynamic park ecosystems and to serve as reference points; 4. “Provide data to meet certain legal and Congressional mandates,” and 5. “Provide a means of measuring progress toward performance goals.”

The Gulf Coast Network conducts vital signs monitoring in eight National Park units in its network region, which includes all of Louisiana and Mississippi and parts of Texas, Florida, Alabama, and Tennessee. From 2002–2006, the network underwent an extensive scoping process that involved network staff, park staff, and academic researchers, with the goal of identifying key natural resources and stressors to park ecosystems. The scoping process, relevant resources, and probable stressors are described in the Gulf Coast Network Vital Signs Monitoring Plan (Segura et al. 2007). As part of this process, the Texas tortoise Gopherus berlandieri (Figure 1) was selected as a top priority for long- term monitoring in Palo Alto Battlefield National Historical Park. This protocol narrative details the Texas tortoise sampling strategy, field methods and analysis approaches, which enable network personnel to achieve monitoring objectives identified in this document and in the Network monitoring plan (Segura et al. 2007).

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Figure 1. Texas tortoise with an important food source, prickly pear cactus (Opuntia engelmannii), in its natural habitat at Palo Alto Battlefield National Historical Park.

Rationale for Monitoring Texas Tortoises in Palo Alto Battlefield NHP The Habitat Palo Alto Battlefield NHP is located in Brownsville, Texas, which is in Cameron County, the southern-most county in the state (Figure 2). The park was founded to preserve and interpret the site of the first battle of the Mexican-American War (1846–1848). The primary park unit, called the battlefield unit, comprises approximately 520 hectares (ha, or 1,285 acres [ac]) of grasslands, thorny shrubs and cacti, with a small area developed as park infrastructure. The park and surrounding areas are primarily post-agricultural and ranch lands, but there is little connectivity on and off the park due to roads, fences and drainage canals. Two sides of the battlefield unit (south and west) are bounded by busy highways and fences (Figure 2), and a third side (north) is bounded by a substantial drainage canal. Only the fourth (east) side currently lacks a restrictive border with the surrounding grasslands and shrublands, although this could change as urban Brownsville continues to grow and drive landscape conversion to more residential and industrial uses.

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Figure 2. Map of southern-most Texas, showing the location of Palo Alto Battlefield National Historical Park. The green shading represents the main unit of the park, referred to as the battlefield unit throughout this document.

The park battlefield unit is located on the Rio Grande delta plain, within 30 kilometers (km, or 18.6 miles) of the Gulf of Mexico. The climate is subtropical and semi-arid, and much of the park is only a few meters above sea level (elevation range of 3.0–6.4 meters [m] or 9.7–20.9 feet [ft]). What elevational changes exist, however, are associated with marked changes in vegetation (Farmer 1992; Richard and Richardson 1993). The lowest elevations have poorly drained saline soils that primarily support cordgrass sacahuiste (Spartina spartinae) with some expanses of sea oxeye daisy (Borrichia

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frutescens). At slightly higher elevations, there is a transitional zone with short-statured, salt tolerant forbs and grasses (e.g., Borrichia frutescens, Batis maritima, Suaeda sp., Atriplex sp., Rayjacksonia phyllocephala, Prosopis reptans, Maytenus phyllanthoides, Monanthochloë littoralis, Pappophorum vaginatum) and abundant Engelmann’s prickly pear (Opuntia engelmannii). Collectively, these two ‘salt prairie’ vegetation types make up at least half of the park’s area (Richard and Richardson 1993), and they are presumed to have been even more common at the time of the commemorated battle in 1846. Following hydrologic disruption and agricultural land-use, some mid- to lower-elevation areas have been colonized by honey mesquite (Prosopis glandulosa) and other shrubs. Returning these post-agricultural shrublands to the native salt prairie is among the vegetation management objectives for Palo Alto Battlefield NHP.

The higher elevation areas within the park are called lomas, and they support a variety of thorny shrub, cactus and small tree species. The lomas were originally formed through natural sediment deposition as levees around historic river meanders, and their soils are better drained and less saline than the surrounding flats. Some of the park’s lomas were once cleared for cattle, allowed to regrow, and are now dominated by mesquitals, which are woodlands or shrublands of honey mesquite (Prosopis glandulosa) with a grassy understory (Richard and Richardson 1993) that now includes the invasive Guineagrass (Urochloa maxima). Otherwise, the primary vegetation type on lomas is a dense and diverse assemblage of thorny shrubs called Tamaulipan thornscrub (Figure 3). Notable species in the thornscrub include honey mesquite, spiny hackberry (Celtis pallida),Texas ebony (Ebenopsis ebano), lotebush (Ziziphus obtusifolia), snake-eyes (Phaulothamnus spinescens), cat-claw acacia (Senegalia greggii), colima (Zanthoxylum fagara), huisache (Vachellia farnesiana), allthorn goatbush (Castela erecta), fiddlewood (Citharexylum berlandieri), brasil (Condalia hookerii), elbowbush (Foresteria angustifolia), Spanish dagger (Yucca treculeana), pencil cactus (Oputnia leptocaulis) and Engelmann’s prickly pear (Opuntia engelmannii; Farmer 1992; Richard and Richardson 1993; Rose and Judd 2014; J. Carlson, personal observation). Whether a loma is covered in Tamaulipan thornscrub, a lower-diversity mesquital, or a mix, these habitats are collectively called loma shrublands, to distinguish them from post-agricultural shrublands elsewhere on the park. Vegetation elements from the salt prairie may be present in the shrubland understory, in addition to many other cactus, forb and grass species. For a complete listing of plant species at Palo Alto Battlefield NHP, see the most recent checklist published in 2004 (Leonard et al. 2004).

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Figure 3. Dense Tamaulipan thornscrub (center) with insets showing a few of the diverse shrub species that occur there. (A) snake-eyes (Phaulothamnus spinescens), (B) cat-claw acacia (Senegalia greggii), (C) lotebush (Ziziphus obtusifolia), (D) colima (Zanthoxylum fagara), (E) spiny hackberry (Celtis pallida), (F) guayacan (Guaiacum angustifolium), (G) coma (Sideroxylon celastrinum), and (H) allthorn goatbush (Castela erecta).

The Tortoise Like other tortoise species, the Texas tortoise is moderately long-lived, slow-growing and has low fecundity. Texas tortoises become mature at four to five years old, and they are known to reach over fifty years old in captivity (Rose and Judd 2014). They remain small into adulthood, with those at Palo Alto Battlefield NHP reaching no more 230 millimeters (mm; 9 inches [in]) in carapace length, with females averaging 160 millimeters (6.3 in) and males slightly larger at 179 millimeters (7.1 in; GULN unpublished data). Adult tortoises engage in courtship and reproduction once or twice per year, with one study estimating that 1.3 clutches are laid per year with two eggs per clutch (clutch size range 1–4; Hellgren et al. 2000). The same study predicted that hatching success should be at least 53% and survivorship from hatching to four years at least 25% for population stability or 5

growth over time (Hellgren et al. 2000, for additional studies of demographic parameters, see Auffenberg and Weaver 1969; Judd and Rose 1982; Rose and Judd 1989).

Unlike other Gopherus tortoises, Texas tortoises do not have burrows around which they center their activities. Instead, they temporarily use shallow depressions (called pallets), low-lying vegetation, mammal burrows, or wood rat middens to hide or take shelter as needed. Despite the lack of burrows, this species is characterized by small home ranges and limited dispersal in adults. In a well-studied coastal population near the park, home ranges were estimated at 0.47 hectares (1.2 ac) for males and 0.34 hectares (.84 ac) for females (Rose and Judd 2014; see Kazamier et al. 2002 for non-coastal estimates). Based on their small ranges and demographic characteristics, Texas tortoise populations in semi-isolated habitats like those in the park may be particularly vulnerable to seemingly modest changes in predation, disease, or habitat alteration. This is because low population growth rates and very limited immigration equate to slow recovery from mortality events.

Throughout their small geographic range (Figure 4), Texas tortoises typically inhabit shrublands, woodlands, and transitional ecotones to grassland, which are characterized by sparse to mostly closed canopies and some Opuntia englemanni, a preferred food source (Auffenberg and Weaver 1969; Kazmaier et al. 2001a; Rose and Judd 2014). The Texas tortoise has a noted affinity for Tamaulipan thornscrub, which shares the tortoise’s geographic extent in the United States and Mexico. In coastal areas, Texas tortoises are most often associated with shrublands on lomas, although these low-relief ridges are absent in other parts of their range. The dependence of Texas tortoises on woody habitats suggests that many of the area’s current land use and land conversion practices, e.g., clearing for infrastructure or crops, will cause tortoises to be excluded, although some grazing and pasture maintenance practices may not (Kazmaier et al. 2001c).

The increasing rate of habitat loss, habitat fragmentation and documented declines in tortoise range and density indicate that protection may be needed for the species’ long-term persistence. Texas Parks and Wildlife initially listed the tortoise as a state species-of-concern and then in 1982 raised that listing to threatened species (Rose and Judd 1982; Judd and Rose 2000; Rose and Judd 2014). The current range of the Texas tortoise is limited to south Texas and portions of three northern states in Mexico (Figure 4). There is also evidence for separate lineages within this range, based on significant but weak genetic differentiation in microsatellite loci between eight populations in and north of Duval County, Texas, and four populations south of it, all in the United States (Fujii and Forstner 2010). Portions of this diversity are threatened, however, by landscape change and development throughout the entire region. Indeed, there is some evidence that populations are in decline (Judd and Rose 2000; Rose and Judd 2014). For example, the well-studied tortoise population in Chaparral Wildlife Management area (see e.g., Kazmaier et al. 2001a, 2001b; Kazmaier et al. 2002; Hellgren et al. 2000) was significantly reduced if not largely extirpated due to a fire in 2008 (Rose and Judd 2014). Although little is known about the range and health of tortoise populations in Mexico, Judd and Rose (2000) stated that basic life history information on populations in Mexico is greatly needed because of rapid conversion of rangeland to agricultural production. Jahrsdoerfer and Leslie (1988) noted that the total area of Tamaulipas, Mexico devoted to agriculture increased from 243,800 hectares (602,442 ac) in 1953 to over 1.3 million hectares (3.2 million ac) in

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1980. These factors have led park managers and network staff to rate the Texas tortoise at the top of the park’s list of vertebrate species for vital signs monitoring.

Figure 4. The geographic range of the Texas tortoise in the USA and Mexico. The tortoise is restricted to Texas in the U.S. and to three states in Mexico: Coahuila, Nuevo León and Tamaulipas. Range limits follow Rose and Judd (2014).

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Potential Threats and Hazards to the Park’s Texas Tortoise Population Population Isolation The park’s battlefield unit is a small piece of federally protected land that is surrounded by pastures and undeveloped shrublands that are rapidly being converted for industrial and residential uses (Figure 2). The park is further isolated by its bordering highways, fences, and drainage-ditches. These obstacles prevent some of the potential tortoise movement in and out of the park, increasing the likelihood that Palo Alto Battlefield NHP tortoises are ecologically and genetically isolated from nearby tortoise populations. The degree of this isolation and its potential long-term effect on the park population remain to be assessed in targeted research. Park managers would like to know if the park’s population is large enough to be reproductively viable or if this population consists of a cohort of aging and senescing tortoises fated to eventually die off.

Disease There are several diseases that impact Texas tortoise populations, although none are currently known to cause high rates of mortality in the wild. The most significant potential threat is upper respiratory tract disease, which is suspected to have caused population declines in Gopherus agassizii and Gopherus polyphemus (Weitzman et al. 2017). This disease is transmissible through contact or airborne particles, and infected individuals may exhibit lethargy, distressed breathing, swollen eyelids, watery exudate and bubbles from the nares, and even death (Rose and Judd 2014; Judd and Rose 2000). Two of the pathogens associated with the disease, Mycoplasma agassizii and Mycoplasma testudineum, have been documented recently in a Texas tortoise population roughly 20 kilometers (12.4 mi) east of Palo Alto Battlefield NHP, as well as in several other wild and captive Texas tortoise populations (Judd and Rose 2000; Tristan 2009; Rose and Judd 2014;Weitzman et al. 2017). There is currently no evidence for this or other significant pathogen hazards in the population at Palo Alto Battlefield NHP, but direct testing has not occurred. In Gopherus agassizii, upper respiratory tract disease is associated with a range of pathogenic agents, such as the bacteria Pasteurella testudinis, the Testudinid herpesvirus 2 and an iridovirus (Rose and Judd 2014; Weitzman et al. 2017; U.S. Fish and Wildlife Service 2015). As such, the network remains vigilant to clinical signs of disease and aims to mitigate potential risks of spreading bacterial, viral, or fungal infective agents while sampling.

One disease that has been observed at Palo Alto Battlefield NHP is necrotizing scute disease, caused by a fungus species that breaks down keratin (Rose et al. 2001). This disease is observed as white spotting, chalkiness and flakiness of scutes on the carapace and plastron, and although damage can be extensive on some individuals, it is not known to be lethal (Rose and Judd 2014). Finally, Bowen (1977) reported that Texas tortoise tested positive for equine encephalitis virus, although the current extent or impacts are unknown.

Human-Induced Losses Texas tortoise in Palo Alto Battlefield NHP may be subject to two direct threats from humans, as described by Rose and Judd (2000 and 2014). Tortoises that leave the dense shrublands of the park risk being killed by vehicles or collected/poached by people. Collection, either for personal reasons or for the pet trade, is a potential concern in and around the park, although there are currently no

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documented cases from Palo Alto Battlefield NHP. Road traffic is likely an even greater risk to tortoises, given that roads are known to be major sources of mortality in other tortoises, such as the desert tortoise Gopherus agassizii (Nicholson 1978). Road-killed Texas tortoises have been reported on both of the major highways along Palo Alto Battlefield NHP (Figure 5), with a total of seven such events recorded by the network since 2008. Because of concerns of Texas tortoise roadkills on the southern border, a tortoise-proof fence was installed in July 2015.

Figure 5. The remains of a road-killed Texas tortoise that was found in August 2016 on the four-lane highway FM 1847, which spans the western border of Palo Alto Battlefield NHP. Using this and other photos, the network crew identified the dead animal as tortoise 219, which was marked 16 months earlier in a sampling unit 2 km away from the kill site. The ID was confirmed by deciphering portions of the ID code on remaining marginal scutes and then using the network’s tortoise photo database to find a visual match. Photos courtesy of Rolando Garza.

Predation Texas tortoise is vulnerable to predation by a variety of mammal species, including the invasive feral hog (Sus scrofa; Buhlmann et al. 2008; Jolley et al. 2010; Rose and Judd 2014). Feral hogs are present in moister areas of the park, and findings during the November 2012 sampling visit suggest hog predation may be an occasional threat to the tortoise population on the park. The potential for hogs to seriously impact the park’s population is unknown, but is a matter for concern to both the network and park staff. The population’s isolation may cause it to be more vulnerable to localized hog predation than a larger, more-interconnected population. After the network reported to the park 9

that several tortoises were apparently killed by hogs in 2012, the park began to develop an aggressive hog management plan for the battlefield.

Predation from other animals, although not yet assessed, could include skunks, coyotes, and foxes. Egg predation is a concern from snakes, birds, raccoons, opossums, badgers, feral cats, and feral dogs (Judd and Rose 2000; Rose and Judd 2014). Auffenberg and Weaver (1969) noted that southern plains woodrat Neotoma micropus is potentially the most active egg predator. Judd and Rose (2000) described how urbanization not only impacts habitat but also brings with it an increase of these potential predators. As the growth of Brownsville continues to engulf Palo Alto Battlefield NHP, the potential for increased predator abundance places the park’s tortoises at even greater risk.

Habitat Alteration Vegetation in Palo Alto Battlefield NHP has changed significantly over the past 150 years. Even up until the late 1990’s, some sections of the park were tilled for row crops or cleared for grazing cattle. On the park today, there exist approximately 150 hectares (371 ac) of shrublands, with about a sixth of these shrublands on the tops of major lomas. Loma shrublands and the adjacent sloping ecotones are believed to be the habitats preferred by Texas tortoises in coastal regions of Texas. It is unknown whether or not this relatively small area within the park, roughly 22% of the total battlefield unit area, can sustain a viable population without becoming a genetic bottleneck. An additional concern is that the park’s own vegetation management plan could diminish available tortoise habitat. A primary management objective for the park is to restore the salt prairie grassland conditions that existed at the time of the battle. In some areas, this includes removing post-agricultural shrublands (mesquite and other shrubs) that have encroached into the salt prairie. If Texas tortoises on the lomas also rely on the lower elevation habitats nearby, their numbers could be impacted by the resulting vegetation changes. Knowledge of Texas tortoise abundances in loma shrublands and the adjacent transitional ecotones will assist park managers in maintaining a sound vegetation plan that will not only suit park cultural interests but also address impacts to the tortoise population.

Project Development and Preliminary Findings Phase I: Need is Recognized, Project is Initiated and Pilot Work Begins Texas tortoises were first officially documented in the park during initial biological inventories in 1992 and 1993, although they were only briefly mentioned in these reports (Farmer 1992; Richards and Richardson 1993). Over time, interest in the park’s Texas tortoises increased due to their state- level protected status, their visibility as a vertebrate species in the park, and the potential for vegetation management actions to impact them. In 2007, the park’s resource management and Gulf Coast Network staff had discussions about potential assessment of this species in the battlefield unit. The initial focus was to determine baseline information about the population and its characteristics to aid the park in the formal development of its vegetation management plan. The network solicited input from its consulting herpetologist, Kurt Buhlmann (UGA and the Savannah River Ecological Laboratory), to develop a species-specific assessment and monitoring project for Texas tortoises in Palo Alto Battlefield NHP. Pilot assessment of methods and potential sampling units began in early 2008. From 2008 to 2011, the network developed and field-tested its sampling routines and techniques.

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When pilot work began in 2008, initial surveys focused on the two loma shrublands closest to the park entrance. This sampling decision was based on past sightings by park staff, previous herpetological inventories (Abell et al. 2000; Duran 2004), and habitat preferences from earlier research on Texas tortoises (e.g., Auffenberg and Weaver 1969; Judd and Rose 1983; Bury and Smith 1986). As described previously, lomas are discrete ‘knolls’ or ‘humps’ (from Spanish) that are higher in elevation than their immediate surroundings and are typically covered in relatively tall woody vegetation, including honey mesquite, diverse thorny shrubs, cacti and yuccas. During these initial surveys, an average of one to two tortoises were found per search event (range zero to four). Sampling efforts gradually expanded to other lomas, with crews surveying over loosely-defined areas, and sampling effort recorded but allowed to vary across survey events. Several surveys also took place in the salt prairies, but after more than 40 hours searching, no tortoises were found there. These early efforts culminated with a trial implementation in 2012, which was described in version 1 of the protocol narrative and SOPs (unpublished, writing completed in 2013).

Phase II: Effort is Standardized and Sampling Frame is Identified In 2014, a second version of the protocol was developed to reflect a new approach to the sampling design and statistical analyses. Most notably, version 2 introduced a time-and-area constrained search, which involved selecting permanent units for repeat visits over time. Based on past successes on lomas, the network opted to focus on and around these tortoise-preferred habitats, with the goal of sampling across most of the park’s major lomas. Loma shrublands were identified using both elevation and vegetation height from LiDAR data collected in 2005–2006. On each major loma, a three or four hectare polygon was drawn to encompass the highest elevation on each loma as well as portions of the gentle downward gradient into the salt prairie. Methods used in loma classification and unit selection are described in the ‘Identification of Major Lomas and Sampling Units’ section.

Concurrent with the identification of sampling units, the network implemented a panel design, under the assumption that all seven units could not be searched thoroughly within a single, three-day park visit. As such, each unit was split into two equal areas, called panels A and B. A panels were surveyed one year, and B panels were surveyed the next year. Five sampling trips were conducted under this second protocol version (also unpublished, writing completed in 2014).

Phase III: Effort is Redistributed to Maximize Recaptures Finally, beginning in fall 2016 the network instated four more changes that would ultimately produce the third and current version of the protocol. The first of these was to eliminate the panel design in fall 2016. The A and B panels were reunified into a single unit that was searched every time. This change was in response to statistical concerns and the conclusion that search effort was sufficient to cover the full unit during a single event, although 100% coverage in dense thorny shrubland is not considered realistic under any design. The second change was to redistribute annual effort from biannual trips to the park to double effort (two surveys per unit) on a fall trip only. This change was motivated by a need to improve estimates of detection probability, and hence population parameters, and to reduce total annual field time for the network. The third change was to add a new unit on a previously unsampled loma and drop one unit from a loma that previously had two. The result was that the original unit #5 was moved from west of unit #6 to SE of unit #6. This was done so that all

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major park lomas would be represented by one sampling unit each. The fourth change was to increase the area of the single 3-hectare unit to 4 hectares (unit #1), so that all units would be the same size and thereby would be sampled for the same time and effort. Implementation of changes two through four began in fall 2018.

Summary and Preliminary Findings The past 10 years of project development are summarized in Figure 6. This figure lists the key events in the design, testing and implementation of the network’s monitoring protocol, and it highlights other important dates for the park and tortoise research in the area. It also includes a plot of the cumulative number of tortoises marked in each unit. In brief, roughly 250 individuals have been marked, measured and had their location recorded, often more than once, during biannual surveys in targeted sampling units. Crew members have also observed courting and mating activity during survey events. Eggshells are frequently sighted, and hatchlings and juveniles less than 50 grams (1.7 ounces [oz]) have been captured on multiple events. These observations indicate that Texas tortoises are fairly abundant and viable within the park, and that the areas selected for monitoring are important for resident tortoises.

To make preliminary estimates of capture rates, recapture probabilities, and population abundance, we summarized and performed basic analyses on the most recent four sampling events, which provide data that are broadly consistent with the final design. Across the Fall 2016 to Spring 2018 trips, the average capture rate per person-hour of effort was 0.69 tortoises. In other words, there were 37 tortoises captured per trip, on average, over 54 person-hours of effort (range=26–44). The average number of captures per sampling unit was 5 tortoises (range=0–11). An estimate of recapture probability from this same period indicates that roughly 22% of all marked tortoises are likely to be found in a given survey; similarly, the average percent recaptures from one event to the next is 23%. These values are similar to the capture probabilities reported by Kazmaier et al. (2001a), which ranged from 0.12–0.38 on an annual basis. Finally, preliminary estimates of population abundance suggest there are 147 tortoises (95% CI=54–251) on 27 hectares of loma shrublands, or between 5 and 6 tortoises per hectare (using the Horvitz-Thomson estimator from R package mra [McDonald 2012]; see SOP TORT08—Data Analysis and Reporting [Carlson et al. 2018a] for more on this approach). This population density is within the bounds of other estimates made for Texas tortoise populations (Rose and Judd 2014; Kazmaier et al. 2001; Hellgren et al. 2000; Judd and Rose 1983), although slightly low for coastal Texas. Published estimates range from 6–122 per hectare (per 2.5 ac) in loma shrubland and adjacent ecotones in coastal Texas (Auffenberg and Weaver 1969; Judd and Rose 1983) to as few as 0.23–0.26 per hectare in more continuous, savannah-like shrublands in the inland portions of their range (Auffenberg and Weaver 1969; Kazmier et al. 2001).

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Figure 6. Timeline of major events for Texas tortoise monitoring at Palo Alto Battlefield NHP, including relevant dates for the park and tortoise research in the region. The graphical part of the figure shows the cumulative number of tortoises marked on each sampling visit, separately for each sampling unit. Each sampling unit name is preceded by a number representing the sampling order during a 3-day park visit, as initiated in 2014. In fall 2018, the original unit #5 (Crescent W) was dropped, and #5 was reassigned to a new unit called Pipeline.

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Monitoring Objectives

This project’s intent is to estimate the current status and population trends of Texas tortoises (Gopherus berlandieri) on loma shrublands and surrounding habitats in Palo Alto Battlefield National Historical Park, using time-and-area constrained surveys in seven permanent sampling units. During each sampling event, tortoises are marked and measured for a long-term mark-recapture study, and their GPS locations are recorded. The goals are to inform park managers as they make decisions affecting Texas tortoises and the park resources they rely upon, as well as enhance understanding of this understudied and cryptic species.

The protocol will address the following specific objectives:

Monitoring Objective 1: To provide a detailed depiction of the status of Texas tortoises across the park’s major lomas, including catch per unit effort, within-park movements, body condition and the distribution of sizes and sexes captured. Catch per unit effort and tortoise body condition are also analyzed for change over time.

Monitoring Objective 2: To assess tortoise population parameters across the park’s major lomas and track how these parameters change over time, including estimated abundance and survivorship from mark-recapture data.

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Sampling Design

Sampling Frame The sampling frame at Palo Alto Battlefield NHP consists of the park’s seven major lomas, including portions of the adjacent sloping ecotones (Figure 7A, B). All major lomas on the park were identified from field assessments, GIS layers and LiDAR data, as described below. These efforts revealed seven major lomas, and on each loma, a permanent, 4 hectare (9.9 ac) unit was established to cover 50–100% of the ‘high’ elevation area on that loma, i.e., area above 1.22 meters (4 ft) in relative elevation. It is within these units that all sampling events take place.

Figure 7. (A) Tilted map image of LiDAR -derived bare earth elevations at Palo Alto Battlefield NHP. Vertical relief is exaggerated 20 times to highlight (in white) the lomas. Altitude range is 3.0 to 6.4 meters on the park. (B) Sampling unit polygons on the park’s seven major lomas: 1=Southside; 2=Visitors center; 3=Maintenance; 4=Nilgai; 5=Pipeline; 6=Crescent; 7=NE boundary.

Justification for Sampling Frame During the project’s development, the network and park management explored the option of collecting data on Texas tortoises throughout the entire park, to support park-wide inference. Systematic transect- or grid-based approaches have been used in some studies of Texas tortoises (e.g., Judd and Rose 1983), but other studies have found, like ours, that monitoring Texas tortoises in this way is impractical (e.g., Kazmaier et al. 2001c). In our case, the decision to restrict the sampling frame was based on several factors, including the cryptic nature of these tortoises and the likelihood that their densities vary greatly among habitats.

Texas tortoises, like many other vertebrates, are difficult to sample and encounter across a range habitat types because of their mobility, habitat preferences, and habitat aversions (Zylstra et al.

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2010). An additional challenge of monitoring Texas tortoises is they have surprisingly low detection probabilities, presumably because they are small, cryptic in dense shrublands, and tend to hide themselves or stay hidden when approached (Auffenberg and Weaver 1969; Rose and Judd 2014; J. Carlson, personal observation). Furthermore, Texas tortoise densities can vary greatly among sites, and they appear to be particularly rare in salt prairies or other areas where shrubs are sparse (Auffenberg and Weaver 1969; Bury and Smith 1986; Kazmaier et al. 2001a). Given all of these factors, the network expects that time-constrained searches in the salt prairies would produce so few captures as to preclude population parameter estimates. This conclusion is supported by results from eight paired survey events during the project’s pilot phase, where 40 person-hours of searching produced 23 tortoises in loma shrublands and ecotones, and the same effort in prairies produced zero.

Because tortoise densities (and/or detection rates) are so low in the salt prairies, the network restricts its sampling frame to the tortoise’s preferred habitats and ecotones. This should maximize capture rates and thereby strengthen population abundance estimates. In doing so, however, the network recognizes they are limiting the project’s scope in at least two significant ways. First, by sampling only on the major lomas and their adjacent ecotones, the network is unable to make inferences throughout the entire park area. Second, by focusing on tortoise-preferred habitats, the network will remain unaware of population status in marginal areas such as salt prairies, and in particular, they will be unable to detect change in areas where population dynamics may be more volatile and sensitive to external stressors. Tortoises almost certainly use the salt prairies occasionally, based on documented movements between lomas for seven individuals from 2008–2018, as well as casual observations by park staff. To better understand how often lower elevations are used, the network will use alternative methods as opportunities arise, including radio tracking and GPS tagging studies.

Identification of Major Lomas and Sampling Units To identify all major lomas in the park, the network GIS specialist used both bare-earth and first- surface LiDAR, collected between December 2005 and February 2006 (Figure 7A, B). First, bare- earth data were used to detect lomas by absolute and relative elevation, with the latter included to adjust for an overall downward trend from northwest to southeast on the park. Second, first-surface data (i.e., vegetation height), were used to ensure that the lomas were covered in tall, woody vegetation. LiDAR data had an advantage over field assessment in several cases, because some lomas were not immediately recognizable in the field, due to their low relief and a land-use history that has altered many vegetation communities on the park.

The LiDAR data revealed seven discrete raised areas within the park boundary, now known as the park’s major lomas (Figure 7A). A few other raised areas were detected as well, but they were generally lower-elevation extensions of a major loma, or with woody vegetation absent or too patchy to be considered shrubland. Unifying features of the major lomas include all of the following: (1) a raised areas with at least half a continuous hectare of ‘high’ elevation, defined as greater than 1.22 meters in relative elevation; (2) a peak height on raised area above 6.1 meters (20 ft); and (3) dominated by taller, generally woody vegetation, defined as vegetation height (first-surface from LiDAR data) greater than 1.22 meters (Figure 8). Only one previously-studied loma failed to meet

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the two elevation-related criteria (#1 in Figures 7B and 8), but it was retained in the study because it was historically connected to a higher elevation area, now on the other side of a highway.

Figure 8. Sampling units for Texas tortoise monitoring at Palo Alto Battlefield NHP. The map highlights vegetation and elevational features that were used to identify and delimit lomas and sampling units for this protocol. Prior to fall 2018, unit #5 was located west of #6, and #1 was 3 hectares, rather than 4. 19

Once all seven major lomas were identified, it was determined that a four hectare unit size would be appropriate for surveys. This would cover 50–100% of the total ‘high’ elevation area of each loma, and for several lomas, it would also include a significant portion of the ecotone that slopes into the salt prairie. With the polygon sizes set, polygons were created in ArcGIS (10.5) as rounded shapes that included the highest point on the loma and spanned as much of the ‘high’ elevation area as possible. One exception was that for unit #2, the thornscrub at the center of the loma was known to be extremely dense and virtually impenetrable, so the polygon was shaped to avoid that area. An additional exception was that one loma (#1) was much smaller than the others and did not meet either elevational criteria. As such, the GIS specialist initially created a smaller polygon to encompass the area above 0.46 meter (15 ft) that was covered in taller vegetation. The sampling area for unit #1 was initially 3 hectares (7.4 ac), and from spring 2014 to spring 2018, this 3 hectare area was sampled at a proportionally-reduced effort to maintain two person-hours of effort per hectare of sampling unit. In fall 2018, the size of unit #1 was increased to 4 hectares (9.9 ac) to make effort and area fully consistent across loma units. This was accomplished by moving the curved park-facing boundary on unit #1 roughly 25 meters outward.

Across the seven sampling units, the sum total area is 28 hectares (66.7 ac). This area includes most shrubland area on the park’s major lomas; only lomas #5 and #6 have significant shrubland area left unsampled (roughly 5.7 ha), and a few other high elevation areas were also not included (Figure 8). These 28 hectares also encompass roughly 8 hectares of transitional ecotone habitats (defined by relative elevations between 0.46 and 1.22 meters), most of which are in the southern units on the park. These ecotones have varying densities of shrubs and cacti, but appear to have comparable rates of tortoise encounters, relative to the highest elevation areas.

To be relevant during sampling, permanent unit boundaries must either be physically present and visible to the crew, or the crew must have some other means of detecting them. For this protocol, sampling units exist only as polygon shapefiles (maintained in the project data files as permanent project records) overlaid with aerial imagery and carried on a hand held GPS. While searching for tortoises, crew members use the GPS to track their position in real-time relative to polygon edges. The procedures for GPS use during tortoise surveys within the seven permanent units are outlined in SOP TORT03 Performing Visual Ground Search—Version 3.0 (Carlson et al. 2018b).

Frequency, Timing and Schedule of Sampling Sampling trips to Palo Alto Battlefield NHP occur once per year in the fall, in late October or early November. Each trip lasts three or more consecutive days, during which all seven sampling units are searched on two separate events. The two events in each unit are completed between 24 and 72 hours apart, at the same time of day, and with different field crews whenever possible. All sampling takes place during daylight hours and under most weather conditions, except for lightning, heavy rain, or strong winds.

Each sampling day is divided into three time-blocks, during which a single crew can sample one unit, generally with up to one hour to spare. The first time-block starts at one half hour post-sunrise, the second starts at 3–3.5 hours post-sunrise and the third starts at 8 hours post-sunrise. The three time blocks are set according to hours since sunrise, because trips can take place either before or after 20

daylight savings time (DST) ends in late October. On a trip taking place after DST ends, approximate time-blocks would start at 7:00 a.m., 9:30 or 10:00 a.m.and 3:30 p.m. No sampling takes place between 1:00 p.m. and 3:30 p.m. to avoid the daylight hours that tortoises are least active, namely during peak mid-day temperatures (Auffenberg and Weaver 1969; Rose and Judd 2014).

Sampling units are surveyed in a set order within each trip, with the expectation that two crews are working independently for the entire trip (see Table 1 for schedule). The first day typically begins on the afternoon time-block, because this is also a travel day for some crew members. For the second and third days, sampling occurs during all three time-blocks. If the network cannot populate two crews of four or more members for all three days, additional days are added to the trip, ensuring that each unit is sampled within its assigned time-block.

Table 1. Recommended sampling order for two independent crews (called A and B) as they sample seven units (#1– #7) two times each over a three-day park trip. Additional days are added if two crews cannot be populated for the entire sampling trip. Times are for a trip occurring after the end of daylight savings time.

Start of each time block Day 1 Day 1 Day 2 Day 2 Day 3 Day 3 (assuming post-DST) Team A Team B Team A Team B Team A Team B a.m. 1: 7:00 a.m. – – #1 #5 #5 #1 a.m. 2: 9:30 or 10:00 a.m. – – #3 #6 #6 #3 p.m. 1: 3:30 p.m. #2 #4 #4 #7 #7 #2

Each sampling unit is surveyed at an intensity of eight person-hours, during a discrete sampling event by a team of four to eight members (see ‘Field Methods’ section for a description of search methods). The search period typically amounts to 1.5–2.5 hours spent searching per sampling unit. The total duration of the sampling event depends on the team size and number of tortoises captured. The initial amount of time spent searching a 4-hectare (9.8 ac) unit is one hour for eight people or two hours for four people. Additional time must be added to the clock for each tortoise processed. Once encountered, the tortoise is weighed, measured, photographed, and its location is recorded (see Sample Metrics and Their Measurement). Further, each tortoise is assigned and marked with a unique ID number at its first encounter. All processing steps take approximately twelve minutes per tortoise for one person, which divided among four to eight searchers, amounts to two to three minutes added to the clock. Prior to and during a sampling event, the data recorder can refer to a table that lists the number of minutes required to search a unit with a crew of four, five, six, seven or eight people. This table is in SOP TORT03, and it also lists how many minutes are added to the clock for each tortoise processed for these differently sized teams.

Justification for Frequency, Timing and Schedule Frequency and Timing Across Trips During the project’s pilot phase, the Gulf Coast network made two trips per year to Palo Alto Battlefield NHP, once in the spring and once in the fall. These times were chosen to coincide with

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the two seasonal peaks in tortoise activity, avoiding the coldest winter months, when tortoises are often inactive and buried in a deep pallet (Auffenberg and Weaver 1969), and the hottest times of the summer, when activity is also presumed to be lower. Sampling occurred biannually in the spring and fall until fall 2018, at which point the spring visit was dropped in favor of having both within-year events in the fall. By performing repeat-surveys of a unit closer in time and during an assumed period of population closure, recapture rates and population parameter estimates should improve through the use of closed population models. Further, sampling tortoises at one rather than two points in their annual cycle should eliminate some variability in tortoise metrics. Although estimating seasonal effects on tortoise captures, condition and behavior would potentially provide valuable insights, pilot data suggest that sample sizes and repeat captures are generally too low to estimate seasonal parameters. Pilot data also indicated there was no clear advantage to a fall versus spring sampling trip, in terms of capture and recapture rates, and so the network chose the fall for its higher quality body condition data. Specifically, since females are less likely gravid in the fall (Auffenberg and Weaver 1969; Rose and Judd 1982; Judd and Rose 1989; Hellgren et al. 2000), we presume their body condition index to be more indicative of their overall fat stores, rather than the presence or absence of eggs.

Over the 10 years of sampling on a spring and fall schedule, there were no detectable differences in capture rates, recapture rates or body condition between the two seasons. Even so, the network has documented several seasonal differences in behavior and sampled tortoise characteristics. Courting activity was higher in the fall than the spring, on the order of fifteen pairs versus two pairs observed. Possibly for this reason, the female:male sex ratio was more evenly balanced in the fall than in the spring, at 1.2 across all fall events and 1.75 across all spring events. Finally, spring events produced more juvenile tortoises (carapace length less than 120 millimeters [4.7 in]) than did fall events, on the order of 16 to 1 since spring 2014. Although the network regrets that juvenile captures will likely fall with the elimination of spring sampling, these young individuals were rarely captured and even more rarely recaptured, likely because their dispersal rates are relatively high and their survivorship low (Hellgren et al. 2000; Kazmaier et al. 2002). Additionally, these individuals were sometimes too small to permanently mark and include in the mark-recapture study.

Timing of Events within Trips For the timing of events within days, the network opted to sample for as many daylight hours as possible while avoiding the mid-day period of low tortoise activity. Although the reduction of mid- day activity should be less pronounced in the cooler fall months (Auffenberg and Weaver 1969; Rose and Judd 2014), the air temperature and relative humidity can still be quite high. For example, averaged over the last four fall trips, the air temperature and relative humidity (RH) during sampling was 30° C (86° F) and 60% RH, but for some events, they were as high as 38 °C (100 °F) and 92% RH. On these hotter days, avoiding peak mid-day heat reduces the risks of heat exhaustion for the crew and likely facilitates tortoise detections, although in practice, inactive tortoises are found as or more often than active tortoises across times of day. Field observations further suggest that tortoise activity is even more responsive to changing air temperature or recent rainfall events than time of day per se. As such, the crew records temperature, relative humidity and weather conditions at the start and end of each sampling event, so these data can be included as explanatory covariates in analyses.

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Schedule of Events within Trips The network decided to survey units in a standard order on every trip to reduce complexity during fieldwork and so that capture rates in each unit were more comparable over time. Given the emphasis on detecting trends over time, this seemed a high priority for the network, and the same schedule has been followed since 2014. The trade-off, however, is that for each trip individually, time-block effects on capture rates cannot easily be separated from unit differences in capture rates. Although this conflation should be recognized, the network considers it a relatively minor concern for long- term analyses, when data are compared across a large number of trips with event-level covariates included. Furthermore, preliminary analyses suggest that time-of-day effects explain less variation in captures than do the effects of year, relative humidity during sampling, and the amount of rainfall in the month prior to sampling (GULN, unpublished analyses).

Sample Metrics and Their Measurement To provide the park a detailed depiction of its Texas tortoise population over the long term, data collection must include a suite of sample metrics that are informative and intuitive to interpret. Key reported variables include abundance, apparent survivorship, and detection probabilities from mark- recapture data as well as catch per unit effort, body condition, sex ratio, mean size, and size distribution. Mark-recapture analyses are performed at least once every three years, using the data for all units combined and on adult tortoises only. Catch per unit effort is summarized after each sampling event as the number of tortoises captured per sampling unit and for the trip as a whole, under the standardized effort of eight person-hours per 4-hectare unit. Similarly, body condition is summarized on an annual basis, and it is calculated for each individual as an index of body mass to volume (carapace length × width × height) × 1,000. Catch per unit effort and body condition are reported separately for males, females and juveniles, and size distributions as well as means are also compared. See the section titled ‘Data Analysis and Reporting’ for fuller descriptions of how these data are summarized and how they are analyzed for trends over time.

The calculation, analysis and reporting of these focal metrics is described in SOP TORT08 Data Analysis and Reporting—Version 3.0 (Carlson et al. 2018a). To collect the required data, the field crew records the date, time and sampling unit at each capture, GPS location, carapace length, width and height (mm), weight (g), and sex if the carapace length is greater than 120 millimeters (4.7 inches; see Hellgren et al. 2000; Kazmaier et al. 2001). When a tortoise is initially captured, it is permanently marked by drilling small holes in marginal scutes. Recaptured tortoises are identified by a scute code following Buhlmann et al. (2008). A suite of nine standardized photographs are also taken at each tortoise encounter, to aid in tortoise ID verification. Detailed instructions on how to measure, weigh, sex, photograph and otherwise assess tortoise condition are included in SOP TORT04 Tortoise Handling, Photography, Measurement, and Marking—Version 3.0 (Carlson et al. 2018c) This SOP also includes instructions on how to read and apply the unique ID number to tortoises on their front and rear marginal scutes.

Detectable Levels of Change This protocol’s sampling approach was selected to provide a relevant and robust data set that describes the Texas tortoise population on and around the park’s major lomas, including any changes

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that may occur in the population over the long-term. Documenting meaningful trends over time can be particularly challenging with cryptic organisms like the Texas tortoise, and as such, the network must consider whether reasonable statistical targets can be met under the current design. To assess this, the network has performed power analyses for real change detection in one variable in a pilot dataset: catch per unit effort. For the remaining focal variables, datasets are insufficient for an appropriate analysis at this time, but such analyses will be performed in 2021, once we have three years of data using the current sampling design.

The power analysis data set is from four consecutive sampling trips: fall 2016, spring 2017, fall 2017 and spring 2018. Because the final design has only 4 hectare units, the power analysis dataset excluded the single 3-hectare unit (#1) that was increased to 4 hectares in fall 2018. Data were collected as described in this protocol, with the exception that the two surveys per unit were once in the fall and once in the spring, rather than twice in the fall. By changing the design to fall trips only, the total annual effort in each unit is unchanged, but seasonal variation is eliminated and time for mortality or dispersal reduced, thereby presumably reducing unexplained variability in capture rates, increasing recaptures, and improving detection probability estimates. In using a pilot dataset that does not fully reflect this recent design change, the network considers its results preliminary and likely conservative.

Two different simulation-based power analyses were performed on the fall 2016 to spring 2018 data. The first analysis used data from the fall trips alone (i.e., seven survey events per year), but had the simulated sample size per year set at the actual effort for the final design, i.e., fourteen survey events. The second analysis used both the spring and fall data in the simulations, but the two consecutive fall-spring trips were paired as year 1 and year 2, to approximate the actual effort of the final design for two fall trips. To conduct the two analyses, simulated datasets incorporating a range of effect sizes were generated (via bootstrapping) from the two data sets, and linear mixed models were used to test for change between years. For the model on fall data only, year was a fixed effect and sampling unit was a random effect. For the model on data from both seasons, both year and season were fixed effects and sampling unit was a random effect. Analyses were completed using methods and R code of Miller and Mitchell (2014).

For both rounds of power analyses, the network set the type I error rate at 10% (i.e., probability that change is detected when none exists; often called alpha or significance level), and the type II error rate at 20% (i.e., probability that true change is not detected; one minus type II error = statistical power). For catch per unit effort, the desired minimum detectable effect size was 30% across a three year period, or 10% each year. In other words, a key expectation of the design is that the sample design is sufficient to allow detection of at least a 30% increase or decrease in capture rate, with 80% power and a false positive rate of 10%.

The power analysis results indicate that the desired power target could largely be met and even surpassed after three years of data collection, with the assigned false-positive rate of 10%. Based on the analysis of fall data only, the effort under the final design should allow detection of a 20% change in catch per unit effort over three years, with 80% power. The results from the fall-spring analyses, however, indicate that a greater degree of change is necessary for detection at 80% power, on the 24

order of a 31% decrease or 29% increase in capture rate. The network expects the actual detectable change to be more like that from the fall-spring analyses, because the larger dataset better represents real-world variability, even though the timing of repeat sampling events in units is different. Given that analyses will be cumulative at each 3-year reporting interval, statistical power should improve further over datasets that are 6, 9, 12, or more years long. Additionally, after the first few trend analyses, the dataset will be sufficiently large to include more covariates, such as air temperature, hours past sunrise, relative humidity and amount of recent rainfall. Including these covariates should also increase power to detect change.

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Field Methods

The Gulf Coast Network Texas Tortoise Monitoring Protocol is designed to monitor the Texas tortoise in a standardized and cost-effective manner. Methods were developed based on expert input from collaborating herpetologists Kurt Buhlmann (see Buhlmann et al. 2008) and Tracey Tuberville (Tuberville et al. 2008; Tuberville et al. 2012), and were based on procedures used in other tortoise studies, e.g., Judd and Rose (1983); Freilich et al. (2000); Hellgren et al. (2000); Kazmaier et al. (2001); U.S. Fish and Wildlife Service (2009); and Graeter et al. (2013). Although the primary goal for this project is to yield summary data for the National Park Service, it is also intended that data be compatible with regional and national efforts to allow for data sharing and comparison. The network datasets could, for example, be unified with other data sets to develop a life table for Texas tortoise, which would be a valuable tool for species management (Judd and Rose 2000).

Several SOPs outline the process of tortoise monitoring field work at Palo Alto Battlefield NHP, including preparation and close-out procedures. First, field work at Palo Alto Battlefield NHP relies on the solid foundation of qualified crew members that clearly understand safety concerns, the safety plan, and how major procedures are completed. The foundational steps in training and safety are described in SOP TORT01 Sampling Crew Training and Safety—Version 3.0 (Carlson et al. 2018d). Second, crew members prepare for fieldwork ahead of time using the equipment lists and preparation instructions detailed in SOP TORT02 Preparation for Sampling—Version 3.0 (Carlson et al. 2018e) Third, field data are collected, as described in SOP TORT03 and SOP TORT04. These two SOPs also describe how to handle tortoises to avoid undue stress on the animal and how gloves, alcohol- based hand sanitizer, and disinfectant are used to prevent tortoise pathogen transfer within the park. Finally, there is a short SOP describing the suite of post-sampling activities to be completed upon return to the network office. This is SOP TORT05 Post-sampling Activities—Version 3.0 (Carlson et al. 2018f). This SOP outlines the transitional steps between field work and the next phase of data entry, data management, analysis and report writing. Additional details on some of these steps are provided in the following sections.

Pre-season Field Preparation Recurring preparation activities include crew training and safety (SOP TORT01), communication and coordination with park staff (SOP TORT02), permitting and compliance, preparation of field equipment (SOP TORT02), and preparation for use of GPS units (described in an in-house document). The project leader is responsible for pre-season coordination with park staff, as well as logistics. The project leader contacts the network’s park contact person 1.5–2 months prior to each sampling trip to coordinate and schedule the upcoming field work. Once the specific dates for the sampling trip are selected, the project leader notifies all participants and secures vehicles for travel. Additional arrangements are also made with the park resource manager at this time. For example, park UTVs are needed to access some of the sampling units on the park, and their availability must be confirmed with park management. The resource manager and network personnel are encouraged to recruit qualified volunteers and collaborators to participate in sampling. Non-NPS participation is beneficial, given that network does not have enough staff to populate two sampling crews of 4–8 people each. Volunteers are contacted by the project leader to provide training material and confirm

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participation at least two weeks before the sampling event. Finally, the project leader shares with crew members any updates from the park resource manager about conditions at Palo Alto Battlefield NHP, and when necessary, provides detailed directions on how to reach each sampling location.

Permitting and Compliance Several months before each sampling event, the project leader must ensure the permitting requirements of Palo Alto Battlefield NHP management are met, such as a current NPS research permit for monitoring Texas tortoises. The schedule for permit completion is November of each year. If possible, permits should be requested for two or more years to reduce paperwork from year to year. The project leader will ensure that the park has the current protocol for monitoring Texas tortoise and a list of sampling locations so that any compliance issues can be addressed. Additionally, the project leader will ensure that the protocol has current approval from the NPS Institutional Animal Care and Use Committee (IACUC).

Safety The network considers the occupational health and safety of its employees, cooperators, and volunteers to be of utmost importance. The network is committed to ensuring all field crews receive adequate training on NPS safety procedures, incident reporting, and emergency response prior to fieldwork. Working in a south Texas environment dominated by thorny shrubs and cacti presents some particular safety hazards that necessitate specialized training or experience. Focal among these is the threat of rattlesnake encounters. An important tool for promoting safe conduct is the Job Hazard Analysis (JHA). This approach is consistent with NPS Director’s Order 50 and Reference Manual 50B for Occupational Health and Safety (NPS 2008). The network has two JHAs for the Texas tortoise protocol, a driving JHA and a fieldwork JHA, both of which are included as appendices to the Safety SOP (Appendix S01A—Driving Safety Job Hazard Analysis for GULN Staff and Appendix S01B—Job Hazard Analysis for PAAL Texas Tortoise Monitoring Carlson et al. 2018d). These JHAs accomplish the following objectives: (1) to identify hazards associated with field and driving conditions, and (2) to develop approaches to mitigate those hazards. Prior to leaving the office for each Texas tortoise sampling event, all network field personnel must review safety information in the JHAs and safety SOP and be refreshed on appropriate field clothing (pre-treated with insect repellent) and personal gear to bring to Brownsville. Prior to each field sampling event at the park, all participating field personnel must be briefed on the JHA contents and sign an acknowledgement form stating their understanding of the contents and agreement to follow all safety guidelines during sampling. Prior to participating in fieldwork, all NPS staff must complete NPS Operational Leadership and First Aid training.

Supplies and Equipment The SOP for fieldwork preparation (SOP TORT02) defines crew member responsibilities in assembling materials and includes two lists of equipment to bring. One list is all items required for the whole trip and a second list describes the required contents of each field pack, which are also prepared ahead of time. The project leader works with the two designated field crew leaders to organize, prepare, repair, or purchase supplies and equipment for sampling. Prior to each field sampling event, one or both of the crew leaders assemble all required field sampling supplies or equipment. The GIS specialist uploads sampling unit boundaries into the network GPS units. 28

Activities during and after Sampling Crew Roles and Activities during Visual Ground Search As described in SOP TORT03, the two field crews each have their own crew leader and data recorder/time keeper, who are responsible for directing and organizing the survey events they participate in. One of the two crew leaders is designated the primary crew leader for the trip, with some additional responsibilities for organization, communications and safety. Both crew leaders ensure that all participants are sufficiently trained and have been briefed on safety ahead of time. They also direct new crew members to work with experienced crew members for their first tortoise processing events. Finally, they may assign crew members to start at specific sections of the sampling unit so the crew is initially spread out. It is possible for one person to hold both a crew leader role and a data recorder/time keeper role for their crew during an event, although this should only be done by participants that are highly experienced in both roles.

The data recorder/time keeper controls the start time and duration of the event, adding time to the clock as tortoises are encountered (see ‘Frequency, Timing, and Schedule of Sampling’ section). At the start of an event, the data recorder/time keeper fills in the start time and weather conditions on the event-level datasheet (Appendix A—Event-Level Datasheet) and then announces that the event has begun. All participants enter the unit and begin walking their independent routes while scanning the ground and bases of plants for resting or active tortoises. All crew members are instructed to cover as much of the sampling unit as possible and to avoid following in each other’s tracks. Suggested best practices for encountering tortoises during the search are listed in SOP TORT03. Throughout the search, crew members must monitor their GPS units to remain within the sampling unit boundaries and also use their radios to communicate with other crew members as necessary. The data recorder/time keeper is contacted by radio when a new tortoise is encountered, because he or she keeps track of all encountered tortoise IDs and knows the next unused ID number for a new tortoise. To ensure that each newly found, unmarked tortoise is assigned a different ID number, the two data recorders must communicate and confirm which ID numbers have been used in their different sampling units. It is also recommended that the two crews coordinate to start and stop at roughly the same time, with most cross-crew communications via cellphone since the crews are on separate radio frequencies.

All participants, both new and experienced, search independently and are counted for their search time, even though new participants do not process tortoises on their own. When a marked tortoise is encountered, the crew member uses the diagram on the back of the observer datasheet (Appendix B—Observer Datasheet) to decipher the permanent ID code on the tortoise’s marginal scutes. If the tortoise has not been marked previously, the crew member applies the permanent markings following steps in SOP TORT04. This SOP also gives instructions on how to complete the observer datasheet and take the required photographs.

At the start of each trip, every crew member is assigned a uniquely-numbered field pack that they carry throughout each event. This pack contains all equipment needed for sampling, including the observer datasheets, camera, battery-operated drill, hanging scale, calipers, radio, emergency contact numbers, and the GPS, when not in use. Two of these items, the camera and the GPS, have the pack

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number printed on them, whereas the rest of the items are interchangeable among packs. At the start of each event, the data recorder/time keeper records each pack number along with the crew member’s name, so that photos and GPS data can easily be re-associated with an individual crew member after the trip has ended.

Disturbance to Tortoise Minimizing disturbance to Texas tortoises during fieldwork is a critical element of conducting tortoise surveys at Palo Alto Battlefield NHP. Disturbance and/or unnecessary handling can induce stress, and potentially increase the chances of tortoise mortality. To minimize disturbance, field personnel should keep handling time to the minimum necessary to measure and mark each tortoise. Wearing gloves is also required when handling tortoises, to reduce the possibility of moving pathogens that attack tortoises from one region of the park to another. Detailed instructions for interacting with and handling Texas tortoises are in SOP TORT04. The protocol’s safety and care practices for tortoises are in compliance with NPS IACUC and follow recommended standards for herpetological studies (Beaupre 2004; CCAC 2004; Graeter et al. 2013).

Digital Photography Digital photographs are an important part of data collection for Palo Alto Battlefield NHP Texas tortoise monitoring. Nine digital photos are required at each tortoise encounter, including an in situ photo; close-up photos of the tortoise from above, each side, the front, and the rear; and a close-out photo of the completed datasheet. These photos provide verification of scute markings, serve as validation of sexing post-sampling, and provide capture site habitat characteristics. Each observer is given a printed sheet of examples of each photograph on their clipboard, to ensure all required photographs are taken correctly every time. These photos are later renamed and are retained as permanent records on the network server, as described in SOP TORT07 Data Management—Version 3.0 (Granger et al. 2018a).

Post-Sampling Activities After the sampling event ends and network staff returns to the office, several steps must be completed to transition the project to the data entry and data management phase (SOP TORT05). 1. All field gear is cleaned, inventoried, evaluated for damage and put away. The project leader organizes any necessary purchases to replace lost or broken items. 2. The field data forms are transferred from the data recorders to the data manager. 3. The data manager downloads the photos from the camera. Photos are renamed while being compared to past photos of the same tortoise (if it is a recapture) as part of the post-field datasheet validation process. 4. The project leader completes datasheet validation checks for logical entries, and then signs the datasheet as accepted so they can be scanned, and data entry can follow. 5. A trip report is completed by the crew leaders and project leader. 6. The GIS specialist downloads data from the GPS units and begins organizing and quality- checking the waypoints and track logs.

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The relevant SOPs for these processes are listed in the Data Management, Analysis and Reporting section of this report. The project leader is responsible for post-field season communication and coordination with park staff, as well as logistics. No voucher specimens are planned for collection under this monitoring protocol.

Any NPS staff or volunteers injured in a non-emergency incident during field sampling will complete required Worker's Compensation paperwork within 48 hours of the incident. Field crew leaders or crew members should discuss any issues that arose with the monitoring procedures with the project leader.

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Data Management, Analysis, and Reporting

This section provides an overview of the procedures for data handling, analysis and reporting. Additional detail and context can be found in the Gulf Coast Network Data Management Plan (Granger 2007), as well as the task-specific SOPs that are referenced below.

Data and information are the basic products of scientific research. As such, this project’s success relies on the generation and management of relevant, high-quality data for current and future data users. It is also essential that the network be able to interpret and describe these data to park stakeholders, so informed decisions can be made, implemented, and communicated to the public.

The Gulf Coast Network has a comprehensive suite of data handling procedures to ensure that data are of an acceptable quality. This section of the protocol narrative and the associated SOPs document these procedures so they are implemented in a consistent manner through time. As a first step, staff must understand their assigned roles and responsibilities, and they must have access to the tools and training necessary to accomplish their tasks throughout the project life cycle. The quality of data is further improved by ensuring field crews are properly trained and equipped, as this minimizes alternative modes of data collection and reduces the frequency of incorrect or incomplete datasheets. Training instructions, responsibilities, and additional training resources are in SOP TORT01.

Data Collection and Post-field Validation of Datasheets As previously noted, data are recorded onto two types of datasheets. These are event-level datasheets and observer datasheets (Appendices A and B). One event-level datasheet is used by the data recorder per survey event, with entries made at the start and end of each survey event. This sheet is used to record sampling unit name, date, weather conditions, start time, stop time, ID numbers of all encountered tortoises, crew member names, and their pack numbers (instructions in SOP TORT03). The observer datasheets are the primary mode of data collection during the event, although location data are also stored in the GPS units and digital photographs are stored on the camera. The observer datasheets have a row for each tortoise encounter and a space at the top for observer name, sampling unit, and field pack number. Each observer needs no more than one sheet per sampling unit per event and is solely responsible for accurately and legibly recording all data elements and correctly deciphering the tortoise ID code (instructions in SOP TORT04). The final step in processing each tortoise is to photograph the entire datasheet with the new row of data completely filled in. This provides a back-up copy of the datasheet and is an indicator in the photographic sequence that the tortoise’s photo record is now closed. Before leaving the sampling unit at the end of an event, crew members give their data recorder all completed datasheets, and the data recorder reviews them immediately for completeness and legibility. This is a key step in the QA/QC process, as the ability to correct errors diminishes greatly once the team leaves the field.

Upon returning to network headquarters, each datasheet is subjected to two main post-field validation steps. First, the data manager downloads the photos and stores them in the appropriate folders on the network server. Then the data manager or the project leader views and renames the digital photos taken during each tortoise encounter. While doing so, they confirm the ID code was interpreted or drilled correctly by viewing the marking sequence of the photographed scutes. They also check that 33

the sex identification was correct. The recorded ID code for each recaptured tortoise is further validated by comparing the new photos to past photos of that tortoise that are stored on the network server, to ensure a visual match. Second, the project leader reviews all hand-written measurements to check for illogical or impossible values, based on database summaries of means and ranges for each measurement. After these steps are complete, the project leader signs the bottom of the datasheet to indicate the datasheet has passed QA/QC measures and has become an accepted datasheet. It can then be scanned and saved to the appropriate folder on the network file server. The original hard copy is returned to the data manager for storage. More detailed instructions on this process are included in the Data Management SOP (SOP TORT07).

Overview of Database Approach The Gulf Coast Network database for Texas tortoise data was developed within Microsoft Access and will continue within this platform for the foreseeable future. Basic structure of this database conforms to the I&M Division-developed Natural Resource Database Template (NRDT), which includes an established set of core tables and fields (NPS 2007). This database application has a front-end user interface and back-end file. The front-end interface contains data entry forms, queries and other data manipulation tools. The back-end file, which is linked to the front-end, holds the core data tables. For additional details, refer to SOP TORT06 Entering Data into the Database—Version 2.0 (Granger et al. 2018b) and SOP TORT07.

Data Entry The data manager directs the data entry process and all subsequent data management steps. He or she either enters the data or oversees data entry by someone trained in the database application. This individual should be familiar with the data collection procedures and preferably has participated in field work. Data entry should take place as soon as practicable following data collection. The database includes functions and utilities to help reduce data entry errors, such as look-up fields and appropriate upper and lower bounds for fields. However, care should be taken to avoid any potential entry errors. Refer to SOP TORT06 for additional details on data entry steps.

Database QA/QC The major steps in database verification and validation are outlined below. They are also described in greater detail in the data management SOP TORT07. Data are entered into the database and immediately receive a data grade of “Raw.” Once the data are 100% checked against the field sheets by the data manager and then an additional 10% of the data receive a random check at the tortoise record level, the data are then upgraded to “Provisional.” At this stage, the database has passed the verification step, reflecting accurate and complete transcription of the datasheets into the database.

The next step is database validation, which checks for impossible values and logical inconsistencies in the database. Validation steps are performed by the project leader in collaboration with the GIS specialist and data manager. During data entry, initial validation steps can be conducted for recaptured tortoises, by comparing new measurements against previous measurements already in the database. If drastic increases or decreases are seen for tortoise size or weight, those data lines are flagged as ‘Suspect’ in the database and subject to further review by the project leader. After data entry and verification steps are complete for a given visit to Palo Alto Battlefield NHP, the project 34

leader plots the data and runs summary statistics to look for outliers in tortoise morphometrics and weights. If any values or outliers are deemed impossible, they are flagged and withheld from any future data exports or data analyses on accepted data sets. Following any modifications to the database at this stage, a “corrections made” tickbox is marked by the modified data field, so that changes in the database are easily tracked.

The GIS specialist contributes to database validation by viewing tortoise locations in GIS. After the original download of data from the GPS units, he or she produces GIS layers of tortoise encounters and checks these against unit polygon boundaries. This step ensures that locational data correctly represent the sampling unit where the tortoise was encountered. Later, when location data are imported into the database, he or she also compares database locations against the original GIS version. This step ensures that the location data were imported into the database correctly.

After the project leader, data manager and GIS specialist have completed their duties in database validation, the data grade for that sampling trip is set to “Accepted.” Once the Quality Assurance Plan (QAP) for this protocol is completed, and all steps in the QAP are completed, the data grade will be changed to “certified.”

Data Processing and Data Quality Levels The data processing steps, their associated products, and their frequency of completion are listed in Table 2. Table 2 also introduces the three stages of data processing: raw, provisional, and accepted. Raw data are in their original form, either as a field datasheet, photo, or a raw entry into the database. Provisional data have undergone verification steps but are not suitable for general use. Accepted data are products from the provisional data step that have been validated, documented with metadata, and are fit for analysis and publication. See SOP TORT07 for additional details on each step.

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Table 2. Data processing steps and products for the Texas tortoise monitoring protocol.

Data stage Product name Expected frequency of Data type (going in) Processing step (going out) completion

Data- NA 1. Datasheets are filled-in by hand in the field. Raw datasheets At the end of each survey sheets event in a sampling unit

Raw 2. Datasheets are reviewed by the data recorder for Reviewed/verified At the end of each survey completeness and legibility. datasheets event in a sampling unit

Provisional 3. Datasheets are reviewed by the project leader for logical and Validated datasheets Within two weeks of returning realistic values. Tortoise IDs on the datasheet are confirmed from the field through comparisons with the photographic record. The project leader then signs and dates the bottom of the datasheet

Accepted 4. Datasheets are digitally scanned. Scanned, validated, and Within two weeks of returning accepted datasheets from the field

Accepted 5. Paper datasheets are managed as long-term records. Local storage of accepted Within one month of returning datasheets from the field

Photos/ NA 1. Nine digital photos are taken during each tortoise encounter. Raw photos At the end of each tortoise image data encounter

Raw 2. All photos are downloaded into the correct folders on the Organized digital photos Within two weeks of returning server. from the field

Provisional 3. Photos are renamed following network conventions. During this Renamed, reviewed and Within two weeks of returning process, each photo is viewed to check for correct interpretation validated digital images from the field of the ID code. New photos are compared against past photos of the same tortoise to ensure a visual match. If the datasheet name and actual ID from photos disagree, the datasheet is corrected and the photo is named with the correct tortoise ID.

Accepted 4. Photos are archived and managed as long term records. Local archive of photos Within two weeks of returning and validated image data from the field

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Table 2 (continued). Data processing steps and products for the Texas tortoise monitoring protocol.

Data stage Product name Expected frequency of Data type (going in) Processing step (going out) completion

GPS NA 1. Tortoise location waypoints and observer tracklogs are Raw waypoints and Within two weeks of returning location downloaded. tracklogs from the field data Raw 2. The GIS specialist creates shapefiles for each GPS unit and Raw shapefiles Within two weeks of returning then merges them into a single shapefile for the park visit. from the field

Provisional 3. The GIS specialist views the shapefiles in GIS and checks for Reviewed and validated Within two weeks of returning impossible location records. They or the project leader also check shapefiles/ geodatabase from the field that the spatial location of each tortoise encounter is visibly inside of the sampling unit listed on the datasheet. Inconsistencies are investigated using the tracklog, and if they cannot be corrected, impossible/illogical GPS records are flagged.

Accepted 4. The shapefiles/geodatabase are managed as long term Accepted shapefiles/ Within two weeks of returning records, with metatdata geodatabase from the field

Accepted 5. The GIS specialist extracts data from the geodatabase to Accepted UTM coordinate Within two weeks of returning create a .csv file of the UTM coordinates of each tortoise output file from the field encounter. They check the export for correctness then gives it to the data manager. This .csv file is merged with the database as the sole source of tortoise location coordinates in the database.

Database NA 1. Accepted datasheets are entered into the database. Raw, entered datasets Within several weeks of for Tortoise returning from the field monitoring Raw 2. Data verification during data entry: typist checks his/her own Partially verified datasets Within several weeks of work for accurate transcription of each page. returning from the field

Raw 3. Data verification post-data entry: another crew member Partially verified datasets Within several weeks of performs a 100% check for accurate transcription. returning from the field

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Table 2 (continued). Data processing steps and products for the Texas tortoise monitoring protocol.

Data stage Product name Expected frequency of Data type (going in) Processing step (going out) completion

Database Raw 4. Data verification post-data entry: project leader/data manager Verified data Within one month of returning for Tortoise performs a 10% check of all datasheets for a given field season from the field monitoring for accurate transcription. (continued) Provisional 5. UTM location coordinates from the GPS units are merged with Verified data including Within one month of returning each tortoise encounter in the database. After the merge is location data from the field complete, the database is checked for correct alignment of location records with tortoise IDs.

Provisional 6. Ecologist creates summary statistics and plots data to identify Partially validated data Within 2 months after the and flag outliers completion of 3 annual trips to the park

Accepted 7. Validated data are accepted and metadata are created for the Accepted data and the Within 2 months after the dataset. If all requirements in the approved QAP have been associated metadata completion of 3 annual trips to followed, they can become certified data. the park

Accepted 8. Excel spreadsheet exports of accepted data are published to Offsite archive and Within 3 months after the NPS Data Store or IRMA. publication completion of 3 annual trips to the park

Accepted 9. Data are analyzed, and reports are written based on the “Trip Report” and “Status Trip Report: within 1 month of results. and Trends Report” each trip. Status and Trends: within 4 months after the completion of 3 annual trips

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Data Documentation, Product Posting, Distribution, and Archiving All data products from the project are accompanied by metadata generated using ESRI software and that is Federal Geographic Data Committee (FGDC) compliant. Data products and metadata are posted to the Integrated Resources Management Applications (IRMA), which is the NPS clearinghouse for natural resource data and metadata. The network data manager has created a Texas Tortoise Monitoring Project that consolidates reports and data products in a single location on IRMA. SOP TORT07 provides additional information on the following topics: product posting, distribution, archiving, holding period for project data, responding to a data request, what data to share, and details for specific products.

Protected Data In the National Park Service, protected information (in the sense that the data are protected from public release under the Freedom of Information Act [FOIA]) is generally defined as information that may reveal the “nature or specific location” and lead to the harm, theft, or destruction of rare or commercially valuable park resources. Such information must not be shared outside the National Park Service, unless a signed confidentiality agreement is in place. Although the Texas tortoise is not currently listed as threatened by the U.S. Fish and Wildlife service, it is listed as threatened in the state of Texas (Rose and Judd 2014). Furthermore, the Palo Alto Battlefield NHP population is subject to various threats to its health and persistence, as outlined in the introduction to this protocol narrative. In collaboration with the park’s resource manager and the superintendent, who is the FOIA contact, the Gulf Coast Network is in the process of establishing what information, if any, should be protected from release in reports that are shared with the public. The most likely data to be protected are the specific locational data (X and Y coordinates) from Texas tortoise encounters. If it is decided to protect these data, the network will take the following steps to handle protected information while sharing information as broadly as possible (see SOP TORT07 for more details).  Before any copy of a data set, database or report is shared publicly, the data manager will remove all geographic coordinates for park tortoises.  Before any copy of a data set, database, or report is shared publicly, the data manager will delete all other data fields that may contain protected information, such as directions to a specific Texas tortoise encounter location at Palo Alto Battlefield NHP.  No digital scanned copies or photos of raw datasheets will be shared publicly, because they contain hand-written GPS coordinates.  All other information about the protected resource(s) may be freely shared, so long as the information does not reveal details about the “nature or specific location” of the protected resource(s) that are not already readily available to the general public in some form (e.g., other published material).

Data Analyses and Reporting A wide range of summaries and analyses are required to address the two monitoring objective for Texas tortoises at Palo Alto Battlefield NHP. These outputs will be presented in two formats: Trip Reports and Status and Trends Reports. Basic capture data are summarized in Trip Reports after each

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sampling event. These short reports are an internal reference for network staff and the park resource manager, and they are completed within one month after each sampling visit. Full reports on the status and trends of the tortoises at Palo Alto Battlefield NHP are produced at three-year intervals. These full reports provide the results of trend analyses and population modeling work and are published on IRMA within three months after the sixth consecutive sampling event. Full descriptions of the variables analyzed and methods used for analyses are provided in SOP TORT08 Data Analysis and Reporting—Version 3.0 (Carlson et al. 2018a) Also included in this SOP are the format, content and reporting timeframe for each of the two reports. General descriptions are provided below.

Format and Contents of the Trip Report Within one month of returning from each trip, the project leader or one of the crew leaders prepares a brief report as an internal-to-NPS reference of that trip’s working conditions and accomplishments. Because individual tortoise IDs are included in this report, its completion follows post-field datasheet validation and datasheet acceptance by the project leader (see SOP TORT07). The report includes the following sections: Weather at Palo Alto Battlefield NHP, notable conditions or events at the park, list of sampling personnel, results of the visual ground survey (including two figures and two tables; see Table 3 as an example), map of capture locations, and notes from fieldwork. The entire network crew is solicited for comment when completing this report. The project leader prepares the figures and tables and assists the crew leader on related written portions.

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Table 3. Example of the data summary table in a Texas Tortoise Monitoring Trip Report. In the pilot data set presented here, 8 person-hours (or 6 for unit #1) were spent searching each unit, but under the final design, it will be 16 person-hours for each unit, divided between two survey events per unit. Also note that some unit names are different in this pilot data set than in the final design.

Spring Spring Spring Spring Fall 2017 Fall 2017 Fall 2017 Start Time for 2018 2018 2018 2018 Recaptured Recaptured Recaptured Total Unit Name Survey Event Juvenilesa Malesa Femalesa Totala Juvenilesb Malesb Femalesb Recapturesb

Southside (1) May 16 8:56 am 2 2 4 8 0 0 0 0

Visitor Center (2) May 15 5:10 pm 0 2 5 7 0 0 0 0

Maintenance (3) May 16 10:45 am 0 1 2 3 0 1 1 2

Nilgai (4) May 16 4:35 pm 1 3 2 6 0 2 1 3

Crescent West (5) May 17 8:55 am 1 3 2 6 0 1 1 2

Crescent East (6) May 17 10:50 am 0 1 1 2 0 0 0 0

Northeast Boundary (7) May 17 5:22 pm 1 0 2 3 0 0 0 0

TOTAL – 5 12 18 35 0 4 3 7

a Captured from spring 2018 surveys b Spring 2018 captures that were recaptures from fall 2017

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Format and Contents of the Status and Trends Report The status and trends report summarizes the complete suite of data collected for each sampling event over the previous three years (e.g., catch per unit effort, sex ratio, body condition, movements) and compares these results to earlier findings. This in-depth report includes estimates of abundance, apparent survivorship, and detection probability from analysis of mark-recapture data. The format of the report generally follows that of a scientific article. The introduction summarizes background information and the network’s specific monitoring objectives for Texas tortoises. The Methods and Analyses section explains how analyses were performed (see details below). The four-part Results section includes presentation of results in figures, tables and text. Finally, a discussion section interprets the results of the report in the context of tortoise ecology and on-park management needs. The data sets used for these analyses are also included as an attachment or appendix to the report and are posted simultaneously with the report.

Because the results section is the core component of this report, its four parts are outlined below: 1. A summary of physical characteristics of the tortoises captured in this study. This includes summaries of the sex ratio and the size/body condition, and distribution of males, females and juveniles for each of the past survey events. Some of these datasets go back to pilot data collection in 2008 and others go back to spring 2014. 2. An analysis of tortoise movements within the park. This includes measuring the average and range of distances travelled by recaptured tortoises at Palo Alto Battlefield NHP, both over the past six survey events and going back to 2008. 3. Trend analyses to assess change over time in catch per unit effort and tortoise body condition. These analyses go back to fall 2018, when search effort was standardized across all units and repeat-sampling of units was implemented, and end with the most recent sampling event. Data for all seven units are combined for these analyses, and only adult tortoises are used because juveniles are so rarely captured and only the largest of them can be marked (at least 150 grams [5.3 oz]). 4. Analyses of mark-recapture data to estimate abundance, apparent survivorship, and detection probability, using tortoises that occupy lomas as an indicator of the park’s tortoise population as a whole. All data across the seven units are lumped in a single analysis, and the data set begins in fall 2018. The first several Status and Trends Reports will not examine trends in population parameters, but with time, these metrics can also be used to test for long-term changes in abundance and apparent survivorship of Texas tortoises at Palo Alto Battlefield NHP.

Analyses and Metrics of the Status and Trends Report Catch per unit effort Catch per unit effort is summarized for each year of data collection in three ways. It is summarized by each sampling event within a year (n=14 events, or two per unit), by each sampling unit surveyed that year (n=7 units per trip) and a total for the trip, any of which can be compared across years. The network generally presents catch per unit effort as the actual number of tortoises captured, because effort is equal across all units. It can also be presented as captures per person-hour, by dividing the 42

number of captures by the number of person-hours searched (8 per event, 16 per unit, or 112 for the trip).

Body condition Tortoise body condition index is calculated as the tortoise body mass divided by approximate tortoise volume (carapace length × width × height). This number is then multiplied by 1,000 (Nagy et al. 2002, 2015).

Trend analyses The Gulf Coast Network analyzes trends in tortoise body condition and catch per unit effort using linear or generalized linear mixed models that account for repeated measures on the seven focal habitat units. For the body condition analysis, each row in the data set is an individual tortoise by capture event. Random effects will be tortoise sex and the unit where the tortoise was captured. Other fixed-effect covariates may be included, such as the amount of recent rainfall or recent air temperatures. Given the potential that the most suitable set of covariates is unclear at the outset, a best-supported model will be selected from a set of candidate models, based on their Akaike Information Criteria (AIC) or comparable criteria (Burnham and Anderson 2002) and using the bbmle package for AIC (or comparable criteria) comparisons (Bolker and R Development Core Team 2014). It is noted that model selection with mixed-effects models should be performed with caution, and particularly that sample sizes must remain constant across all models and random effects must not be changed. For the analysis of catch per unit effort, each row in the data set is a specific sampling unit by search event. Random effects include sampling unit (repeated measures) and sampling year (as categorical). For the catch per unit effort analysis, covariates may be included, such as total area covered per survey event (based on 2-meter radius around crew tracklogs), air temperature or relative humidity during sampling, or other available metrics that may influence detectability over time or across units. As stated above for body condition, model selection will be used to choose the best-supported model for catch per unit effort, based on different combinations of fixed-effect covariates in a set of candidate models. Finally, after sufficient data on population parameters become available (cumulative data from three to four Status and Trends Reports), trend analyses on these data sets are completed in a similar manner. Trend analyses will be implemented in R (e.g., lme4 package; Bates et al. 2015) or within the mark-recapture model. More details are provided in SOP TORT08.

Population parameters The monitoring approach taken by the Gulf Coast Network allows for the assumption of a closed tortoise population for the two sampling events per unit on a single trip. Between trips, however, an open population must be assumed, because one year is sufficient time for tortoise births, deaths, immigration or emigration (Graeter et al. 2013). This structure of data collection allows for a variety of approaches to modelling population parameters. Closed population models, such as Lincoln- Petersen, can be used to estimate abundance within each trip. An additional option for estimating population parameters within and across years is Pollock’s robust design (Pollock 1982; Kendall et al. 1995). This approach is relatively insensitive to violations of the assumption of equal capture probabilities among individuals, and it can be implemented with Bayesian methods (e.g., Rankin et

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al. 2016) or in program MARK (White and Burnham 1999; Cooch and White 2017), including through the RMark package in R that interfaces with program MARK (Laake 2013).

We also retain the option of estimating population parameters using Cormack-Jolly-Seber models for open populations. This was the approach taken by Kazmaier et al. (2001b) in their mark-recapture study of Texas tortoises. Cormack-Jolly-Seber models can be used to model apparent survivorship and probability of capture. They can also provide estimates of abundance using the Horvitz- Thompson estimator (Manly et al. 2005; McDonald and Amstrup 2001). They can be estimated in program MARK as well as R package mra (McDonald 2012). Another set of open population estimators are Jolly-Seber models for abundance using the POPAN or Pradel lambda formulations (Program MARK or R package marked [Laake et al. 2013]). However, Jolly-Seber models are extremely sensitive to heterogeneous capture rates among individuals, which may be difficult to avoid in our study. Cormack-Jolly-Seber models are more robust to heterogeneous capture rates, though they may require larger sample sizes than our study may produce.

Many of the modelling approaches described above allow the user to include system-wide covariates (e.g., rainfall in the three months preceding the sampling event) and individual covariates (male versus female; unit of capture). The network may include both types of covariates as is appropriate, primarily to adjust for incomplete detection. When different potential models are used on a given data set, the final model will be chosen by comparing their AIC (or related information criterion, as appropriate) scores (Cooch and White 2017). The population modeling is performed on two data sets: a cumulative mark-recapture dataset (from fall 2018 to present) as well as that from just the previous six sampling events. See SOP TORT08 for a more detailed description of the modelling approaches taken and how their assumptions are addressed.

Recommended Reporting Schedule and Delivery The two types of reports produced for this project are provided at different intervals. The Trip Reports are completed and submitted to the park within three months of each field trip. These brief reports are for internal use only and not shared with the public. The Status and Trends reports are created on three-year intervals, beginning with the first such report in spring 2021. Analysis and writing can begin after all relevant datasets have passed database verification and validation steps. These steps are completed within three months of the end of the third sampling trip since the last report. For the first report, the third trip is fall 2020. Each finalized Status and Trends Report will be submitted for publication in the NPS Natural Resource Publications Management series and posted to the Integrated Resource Management Application (IRMA) hosted by the NPS Washington Support Office or National Inventory and Monitoring Division.

The network will also produce and update short Resource Brief documents at unscheduled intervals. These summaries will report on resource status, monitoring progress, salient observed events, and related matters of general interest. These reports are posted on IRMA and on the network webpage. See SOP TORT08 for an example and more details on these and other report types.

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Procedure for Revising the Protocol Over time, revisions to both the protocol narrative and SOPs are to be expected. Careful documentation of changes to the protocol and a library of previous protocol versions are essential for maintaining consistency in data collection and for appropriate treatment of the data during data summary and analysis.

The steps for changing the protocol (either the protocol narrative or the SOPs) are outlined in SOP TORT 09 Revising the Protocol—Version 3.0. The protocol narrative and each SOP contain a revision log that will be filled out each time the narrative or an SOP is revised. In this log, the staff person will briefly document when and why the change was made and will assign a new version number. The new version of the SOP or protocol narrative should then be posted to the IRMA Data Store as well as archived in the appropriate network vital signs protocol folder on the network drive.

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Personnel Requirements and Training

Sampling for Texas tortoise in Palo Alto Battlefield NHP is a network staff task with field assistance from NPS staff at Palo Alto Battlefield NHP and from University of Georgia consulting herpetologists K. Buhlmann and T. Tuberville. Assistance is often available from staff from other network parks, the United States Fish and Wildlife Service, and other local interested volunteers with reasonable experience working in south Texan thornscrub or similar habitats.

Staff Roles, Responsibilities, and Qualifications Major protocol tasks and staff responsible for each are summarized in SOP TORT01. The following sections describe the responsibilities of personnel involved in the Texas tortoise monitoring project.

Network Program Manager The network program manager is responsible for overseeing and coordinating the development and implementation of the Texas tortoise monitoring project, as well as the other vital sign protocols. They ensure that the Texas tortoise monitoring project is aligned with and contributes to overall network goals. The network program manager also provides support in budget, personnel, and logistical matters.

Project Leader A network ecologist functions as the Texas tortoise monitoring project leader, and is responsible for coordinating all aspects of the project, including communication with parks, logistics, fieldwork, data collection and management, and analysis/reporting. The project leader must be knowledgeable in tortoise ecology (with emphasis on Texas tortoise), skilled in statistics, and experienced with the monitoring techniques contained within this protocol. Specific responsibilities and tasks include:  Ensuring effective communication between park staff, field crew, and other network staff.  Corresponding and collaborating on project development with University of Georgia herpetologists.  Developing, reviewing, revising (as needed), and implementing the monitoring protocol, standard procedures, and data forms for field data collection and data handling.  Developing the field schedule and finalizing sampling dates.  Preparing datasheets used in field sampling, in collaboration with the data manager.  Arranging for repairs or replacements of any lost or damaged equipment  Ensuring field crews receive pertinent training in safety and field work. Direct instruction is typically provided by the crew leaders.  Ensuring field crew work meets the desired standards of quality.  Ensuring sampling work is done in a way that addresses safety hazards to field personnel and limits disturbance to tortoises.  Preparing figures and tables for the Trip Reports after each sampling visit and working with one of the crew leaders to complete the text.

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 Obtaining and maintaining the required NPS and State of Texas permits, including writing and submitting Investigators Annual Reports to the permit reporting system of the National Park Service.  Participating with data manager in QA/QC of data entered into database, and archiving of data (both hard copies of data forms and electronic formats).  Acting as the main point of contact concerning data content.  Analyzing data and writing the “Status and Trends Reports.”

Field Crew Leaders There are typically two field crew leaders for Texas tortoise monitoring on each trip, and they are responsible for managing the crew members under them. They are designated by the project leader and must be skilled in wildlife biology, with a strong knowledge of tortoise ecology in the southern United States. The field crew leaders assist the project leader with training the field crew on data collection; coordinate to assemble, assess, perform safety checks, and repair equipment; oversee field data collection; and oversee gear maintenance and storage. Prior to beginning fieldwork, they assign one crew member from each crew with the role of data recorder/time keeper, and they train them if necessary. A crew leader may also function as a data recorder/time keeper for their crew during an event, although this will only be done by participants that are highly experienced in both roles.

The field crew leaders must have experience training others, experience leading groups, experience with all field methods used in this protocol, and with conducting field work in challenging habitats. These people must know how to use a GPS unit, including how to mark new points. The field crew leaders must also be detail-oriented, organized and meticulous about the collection, analysis, and safeguarding of data. Of all the crew members, the crew leaders are most responsible for knowing and understanding the full contents of the protocol narrative and SOPs, including any recent changes. In this way, they can advise crew members on the ‘why’ of the monitoring project and answer any questions that arise. On each trip, there are two crew leader roles: primary and secondary crew leader. Although the primary crew leader has several additional responsibilities on that trip, the secondary crew leader must be equally capable of functioning in the capacity of primary leader.

In addition to the responsibilities of a crew member, the field crew leaders perform the following tasks:  Coordinating directly with the park resource manager or other personnel when conducting fieldwork in a given park (primary crew leader).  Ensuring that all field crew members are trained in proper data collection and gear cleaning/storage procedures (both crew leaders).  Checking for updates to the emergency numbers list for the park and printing copies along with directions to hospitals (primary crew leader).  Preparing field data forms or notebooks (both or either crew leader).  Assembling, assessing, and repairing equipment (both or either crew leader).

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 Collecting all field data accurately, according to established procedures (both crew leaders).  Ensuring sampling work is done in a way that addresses safety hazards and disturbance to tortoises (both crew leaders).  Supervising field crew member(s) assigned to the team and ensuring they are collecting data efficiently and correctly (both crew leaders).  Assigning one team member per crew with the role of data recorder/time keeper, and training them in these tasks, as necessary (primary crew leader).  Writing and submitting brief sampling trip reports to park staff (either crew leader).

Field Crew Members The field crew members are responsible for assisting with locating sampling plots, carrying gear, collecting data in the field, recording data legibly onto datasheets, handling tortoises, and using GPS units and radios. Crew members may be professionals, college graduates or students who have strong interest in or experience in ecology, biology, and/or related natural resource fields. Alternatively, crew members may simply be volunteers who have some experience with fieldwork in south Texas. Crew members involved with data collection or recording must be detail-oriented and must write legibly. All crew members must be able to work in extreme conditions of heat, humidity, cold, rain, biting/stinging insects, and venomous snakes, and be capable of making long, off-trail bushwhacking trips in rugged terrain. Specific tasks (if assigned) for which the crew members will be responsible include:  Completing mandatory training and understanding the contents of pertinent protocols, JHAs, and SOPs.  Ensuring that all necessary gear and equipment are assembled, clean, and functional prior to each trip.  Safeguarding equipment during field operations to prevent damage or loss.  Following instructions from their crew leader and data recorder during each sampling event and throughout the Palo Alto Battlefield NHP visit.  Conducting fieldwork in a way that addresses safety hazards and minimizes stress to tortoises (see SOP TORT01 and SOP TORT04).  Collecting field data accurately and in a timely manner (see SOP TORT03 and SOP TORT04).  Correctly and legibly recording all data values on datasheet.  The crew members that serve as data recorder/time keeper have the additional duties of keeping time during each survey event, communicating the event’s start and end to the crew, adjusting search time appropriately based on the number of tortoises captured, recording data on the event-level datasheet, and collecting and storing observer-level datasheets at the end of each sampling event.

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 When not in the field, assisting data manager and project leader in accomplishing other tasks related to the project, as appropriate.

Data Manager The network data manager is responsible for populating and maintaining the database for the Texas tortoise monitoring project. He or she also oversees data entry and database management. Data entry is conducted at the main network office after field data forms and electronic files have been processed. Along with the project leader, the data manager ensures that all individuals involved in the project are aware of their data management responsibilities. Specific tasks for the data manager include:  Consulting on data management activities and field datasheet preparation and revision.  Developing, maintaining and updating the database application.  Providing oversight and training on the use of the database application.  Coordinating electronic data archival and backup procedures.  Leading datasheet and database verification and validation for QA/QC at network offices.  Providing assistance to network program manager and project leader with data summaries and analyses.  In consultation with project leader, posting of products to IRMA.

GIS Specialist The network GIS specialist is responsible for coordinating GPS data/equipment and maintaining all geospatial data and any changes to sample plot maps related to the monitoring project. Geospatial data and metadata are uploaded to IRMA with the rest of the data products under the Gulf Coast Network tortoise project. Specific tasks for which the GIS specialist is responsible include:  Maintaining all working GIS files associated with the protocol, including archiving the files on a shared network drive.  Developing sampling plot boundaries and transferring them to all hand-held GPS units for use in the field.  Creating and maintaining metadata for all geospatial data using appropriate Federal Geographic Data Committee and NPS metadata standards.  Serving as GPS expert on sampling events whenever possible.  Obtaining GPS units from the field team leader or project leader, at the end of each winter and spring field season, and downloading GPS coordinates and metadata associated with any newly marked waypoints.  Helping to maintain and prepare field equipment for sampling events.  Collaborating with project leader and data manager on spatial data analysis, QA/QC and report products.

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Training Procedures The most essential components for high-quality data collection are well-trained and experienced field crew leaders and similarly trained crew members. Prior to each sampling event, the crew leaders will assess the crew’s training needs and conduct trainings with new participants. Sampling refreshers for all participants are conducted just prior to the first sampling event of a visit to Palo Alto Battlefield NHP. New crew members must shadow experienced crew members during their first few survey events. They are not allowed to process tortoises on their own until they are proficient in the processing tasks. A more detailed list of training steps and resources is provided in SOP TORT01.

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Operational Requirements

Annual Workload and Field Schedule The annual sampling trip to Palo Alto Battlefield NHP occurs in late October or early November. The network project leader schedules specific dates of visits through coordination with park management and with consideration of network staff obligations and workloads. Each visit is preceded by a two-week period for equipment preparation and procedure review at network offices, with additional longer-term equipment and coordination tasks being performed at other times of the year by network staff on a per-task basis. Conclusion of the park sampling visit is followed by a two- week period in which equipment servicing and storage occur, and all event data and image files are processed for data management at the network offices. Several additional weeklong periods are used for network staff preparation of reports and other project activities on a per-task basis.

The field schedule consists of fourteen sampling events (seven per crew) performed during available daylight hours on three or more consecutive working days for each park trip. Two units are surveyed (one per crew) on the afternoon of the first sampling day. On the second and third days, each crew surveys two units before 1:00 p.m. and surveys one more after 3:30 p.m. (times are one hour later if the trip occurs before the end of Daylight Savings Time). The detailed sampling schedule is in Table 1. Sampling occurs in all but severe weather. Sampling is delayed during severe weather, while the crew takes shelter at the Palo Alto Battlefield NHP Visitor Center. In the event that the network cannot populate two crews of four or more members each, additional days are added to the trip, ensuring that each unit is sampled in its assigned time-block.

Facility and Equipment Needs Equipment preparation, procedural review, data entry, data management, data analysis, and project document development occur in the network offices. This work is done with available network office facilities and computers. Field sampling occurs at Palo Alto Battlefield NHP, and the park typically provides the use of two utility task vehicles (UTVs). The equipment used during sampling is supplied by the network, and it is distributed to the crews at the start of each day’s fieldwork. Additional general field equipment (snake chaps and sticks, safety glasses, first-aid kit, additional consumable supplies) is provided by the network. Palo Alto Battlefield NHP Visitor Center facilities serve as the human support element for field crew, including water fountains and restrooms. Travel to and from Palo Alto Battlefield NHP is by government vehicles. A list of field equipment is provided in SOP TORT02.

Budget Personnel expenses for field work are based on using one ecologist (GS-12), one data-manager (GS- 11), one GIS specialist (GS-11), one bio-tech (GS-7), and one bio-tech (GS-5) for one sampling trip per year to Palo Alto Battlefield NHP, plus some additional project-related work per year in the network offices. Once every three years, three additional weeks of project-related work will be needed by the network ecologist to complete the Status and Trends Report; for budgeting purposes, this is divided across years as one additional week per year. It is likely that several weeks of additional time will be needed during the development of the first Status and Trends report. Other

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project budget elements include travel, meals and incidental expenses (M&IE) and lodging near Palo Alto Battlefield NHP for network staff (and possibly two other NPS staff from other network parks), professional reimbursement expenses for participation by two collaborating scientists, equipment replacement, and consumable supplies for sampling events.

Personnel Costs The three weeks per network staff member (five people) includes pre-sampling preparation, travel to and from Palo Alto Battlefield NHP, performance of field sampling, post-sampling equipment servicing and data processing, and team time spent on generating data analysis and reports. Park personnel costs are covered by the park for their participating staff. We estimate that at least 30% of network staff time is spent on data review, processing, management, analysis and reporting. Additional time may be allocated for collaborative work with outside data analysts and consulting herpetologists.

Travel Costs The network team (five persons) travels approximately 600 miles each way (Lafayette to Palo Alto Battlefield NHP) once each year using two network vehicles, and brings the network’s UTV. Lodging totals to 21 nights per year, based on seven people (five GULN, two other NPS) × three nights. M&IE totals to 26.25 M&IE days per year, based on seven people × 3.75 days. Travel costs for the UGA herpetologists are paid via a professional services contract used to compensate them for their time.

Equipment and Supply Costs Most field equipment is long-lasting and used in more than one monitoring effort by the network (GPS units, hand-radios, cameras, snake chaps and sticks, weighing scales, calipers, drills). Even so, individual items may need to be replaced from time to time. Each sampling visit entails purchase of additional small batteries, hand cleaner and other consumables.

Project Funding Table 4 indicates that Palo Alto Battlefield NHP provides support by dedicating the park resource manager for four workdays per year. Other network parks, such as San Antonio Mission National Historical Park (SAAN) or Padre Island National Seashore (PAIS), likewise provide support by dedicating one resource management staff member for four work days per year, plus providing a government vehicle to support that individual driving to and from Palo Alto Battlefield NHP on one trip each year. Table 4 depicts the funding allocation & elements for tortoise monitoring at the park. Data in this table reflect FY2018 usage and allocation for one park sampling visit as a working example of project costs.

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Table 4. Estimated annual budget for monitoring Texas tortoise at Palo Alto Battlefield NHP [na = not available or not applicable].

Budget Expenditures Time allotted % of time Cost in Cost in dollars Category spent on DMa dollars DMa (2014)

Permanent NPS Network Coordinator (GS13) 2 days report review 100% $970 $970 Personnel Ecologist Project Leader 4 days sampling, 2 day data QA/QC, 1 week for annual 82% $7,505 $9,152 (GS12) report writing, plus 1 week per year for Status and Trends writing and analysis (once every 3 years)

Data Manager (GS11) 4 days sampling, 4 days data QA/QC and archiving 50% $1,376 $2,752

GIS Specialist (GS11) 4 days sampling, 4 days data processing and archiving 50% $1,376 $2,752

BioTech (GS 7) 4 days sampling, 2 days prepping/packing equipment 0% $0 $1,392 BioTech (GS 5) 4 days sampling, 2 days prepping/packing equipment 0% $0 $1,152

Park Personnel Resource Management Staff na na na In-Kind support

Operations/ 2 UTVs Provided by park na na In-Kind support Equipment GPS units 10 units@$300/unit na na $3,000b

Sampling Equipment (calipers, 10 complete sets@$400/set – na na $4,000b drills, batteries, scales, cameras, gloves, PPE)

Travel Lodging and M&IE 7x$570 once/year na na $3,502 (permanent employees)

Other (UGA time and travel 4 days sampling na na $5,000 partners)

TOTAL na na na $11,227c $33,672

a DM = data management, including analysis and reporting activities. b These items are start-up costs; ongoing costs would be a portion of this amount for repair or replacement. c More than 33% of the tortoise protocol budget is dedicated to data management.

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Appendix A: Event-Level Datasheet

Figure A-1. Example of Event-Level Datasheet.

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Appendix B: Observer Datasheet, Half-sheet Size

Figure B-1. Example of Observer Datasheet Half-sheet size, front.

Figure B-2. Example of Observer Datasheet Half-sheet size, back. 65

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