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Camera trap time‐lapse recordings can collect vast amounts of data on wildlife in their natural settings. Transforming these data into information useful to ecologists is a major challenge. Machine learning techniques show promise for becoming important tools in the cost‐effective analysis of camera trap data, but only if they become readily available to researchers without requiring advanced computing skills and resources. We present a new suite of software tools that reduce the amount of human effort needed to segment time‐lapse, camera trap recordings in preparation for analysis. The tools incorporate a convolutional neural network trained to detect a focal species and to generate a draft video segmentation indicating the ranges of time when the focal species is present. We evaluated the utility of our neural network by comparing manual and automatic segmentations of 64 time‐lapse recordings of gopher tortoise (Gopherus polyphemus) burrows, recorded in Pinellas County, Florida, USA between 25 November 2020 and 30 November 2020. The neural network correctly found 130 of the 145 segments containing tortoises (89.7%), whereas student graders found 135 segments (93.1%). A year of experience using the new software suite in an ongoing study of gopher tortoises deploying 12 camera traps indicates one person, assisted by machine learning algorithms, can segment a week's worth of time‐lapse recordings—11.5 hours of standard‐speed video—in under 3 hours. We concluded that the use of machine learning algorithms is practical and allows researchers to process large volumes of time‐lapse data with minimal human effort. [ABSTRACT FROM AUTHOR]

Some chelonians, such as the gopher tortoise (Gopherus polyphemus), spend much of their time underground in burrows. Often, they will retreat into these burrows when approached. This predator avoidance behavior may potentially influence the spatial use patterns that researchers directly observe via manual telemetry. In an effort to record the movements of gopher tortoises using affordable methods that reduce behavioral effects, we devised a novel application for Global Positioning System (GPS) loggers, specifically that of a low‐cost recreational unit that could be modified for extended deployment (~6 months) under gopher tortoise‐conditions. We conducted a stationary testing study of these GPS loggers whereby they were deployed at specific depths (0.5 m, 1.0 m, and 2.0 m) inside inactive burrows and on the surface at our study site in southeastern Georgia, USA, during summer 2017. This stationary trial allowed us to characterize the effect of burrow depth on GPS fix success rate (FSR), mean location error (µLE), and root mean square of the location error (LERMS). We found that µLE and LERMS increased with increasing depth underground; µLE ranged from 17.34 m on the surface to 69.98 m at the 2.0‐m depth. However, following exclusion of LE outliers >3 standard deviations from each treatment mean, LERMS decreased to 8.6 m at the surface to 40.46 m at the 2.0‐m depth. The FSR varied by burrow depth from 0.51 (2.0‐m depth) to 0.99 (surface). Additionally, we provide our attachment and deployment methods as used for studying the spatial ecology of the gopher tortoise with modified recreational GPS loggers. Overall, the modified GPS loggers performed well, obtaining 146,118 successful GPS fixes on 38 individual gopher tortoises during 84 unique deployments, each approximately 3.5–6 months in duration. © 2020 The Wildlife Society. Low‐cost recreational GPS loggers can be modified for application for wildlife and have been shown to produce reliable data useful for spatial ecology and behavior studies. Field‐based location and acquisition error rates can be assessed through short‐term validation studies that will yield a quantified understanding of how habitat and wildlife behavior affect data biases. [ABSTRACT FROM AUTHOR]

The gopher tortoise (Gopherus polyphemus; hereafter, tortoise), an ecosystem engineer in open pine (Pinus spp.) woodlands of the southeastern United States, often inhabits production pine forests (PPFs), defined here as even‐aged pine forests managed primarily for timber products, which is a common forest type in the tortoise's range. As a result of frequent disturbance from forest management activities, PPFs are characterized by a shifting mosaic of vegetation conditions over time. However, it is unclear how tortoises respond to these shifting conditions, necessitating an understanding of how forest management activities affect tortoise population dynamics and movements in these landscapes. Therefore, we systematically reviewed literature to assess tortoise responses (e.g., survival, demography, movement) to silvicultural activities in PPF landscapes. Although tortoises are often able to persist in PPF landscapes, their burrows may be concentrated along roadsides, powerline rights‐of‐way, and ecotones between recently harvested and older stands. How, and whether, tortoises can effectively move around PPF landscapes to take advantage of shifting habitat conditions is not well‐understood. We discuss research gaps that must be addressed to enhance conservation efforts on PPF landscapes across ownership types. © 2019 The Wildlife Society. We reviewed and discussed and identified gaps in gopher tortoise research that may be able to enhance conservation efforts. Our in‐depth literature review identified 3 gaps in gopher tortoise research and suggested that actively managed production pine forests may provide more habitat for tortoise populations. [ABSTRACT FROM AUTHOR]

ABSTRACT: Researchers and managers often need vehicular access into areas fenced to protect wildlife, but commonly used vehicle crossings often are cumbersome, cost‐prohibitive, or inadequate at restricting target taxa. We describe a cost‐effective method using partially buried conveyor belt, which is flexible and sturdy enough to allow convenient and frequent vehicular passage across wildlife fencing while not compromising the integrity of the barrier or harming the target species. We have no evidence of any target taxa (i.e., tortoises, freshwater turtles, toads) breaching a conveyor belt barrier from projects in central Florida (2005–2012), Guadalupe County, Texas (2014–2018), or Robertson County, Texas (2014). The proposed technique is unlikely to prevent large‐bodied, saltatory, climbing, or arboreal taxa from crossing a wildlife barrier. However, this technique is applicable to many small vertebrates and any taxa for which silt‐fencing or other similar semipermanent barriers are appropriate. © 2018 The Wildlife Society. [ABSTRACT FROM AUTHOR]

ABSTRACT Red imported fire ants ( Solenopsis invicta; fire ants) are predators of turtle (Testudine) eggs and hatchlings, but little information is available indicating how and when fire ants detect turtle nests during incubation. Therefore, during 2014, we compared fire ant presence at gopher tortoise ( Gopherus polyphemus) nests in burrow aprons in early and late incubation with paired burrow aprons that did not contain eggs. To determine whether fire ants were attracted to soil disturbance associated with nesting, we compared fire ant presence at physically disturbed burrow aprons without eggs (i.e., simulated empty nests) with paired burrow aprons with no disturbance or eggs at Ichauway, Georgia, USA. We found fire ants more frequently at nests than at paired aprons early in incubation, but not late in incubation. Additionally, we found no difference in fire ant presence between simulated empty nests and paired sites. Our results indicate that fire ants are attracted to gopher tortoise nests because of a factor other than the initial soil disturbance that accompanies nest deposition, possibly the mucous and moisture released by the female as eggs are laid. © 2016 The Wildlife Society. [ABSTRACT FROM AUTHOR]

ABSTRACT Line-transect distance sampling (LTDS) is increasingly used to estimate gopher tortoise ( Gopherus polyphemus) densities. The process requires detecting tortoise burrows, and then determining occupancy. We compared 3 LTDS approaches that differ in how burrow detection and occupancy data are integrated, and 2 search strategies. Surveys were conducted at Avon Park Air Force Range in South-central Florida, USA, from April through October 2009. These include 1) LTDS using data from occupied burrows only; 2) LTDS with burrows treated as 'clusters' of size 1 or 0 depending on occupancy; 3) LTDS to estimate burrow densities, with occupancy modeling to estimate occupancy rates; and 4) 2 search strategies: standard versus expanded searches. The LTDS method produced reliable burrow density estimates, and tortoise densities were estimated most precisely and with least effort using data from occupied burrows only. However, any method could be biased if burrow occupancy is uncertain. Indeed, in the Florida scrub and pine flatwoods habitats, video-camera scoping was hindered by groundwater or obstructions, resulting in undetermined occupancy for 45% of burrows. Improving scope technologies and surveying during the dry season has improved subsequent results for xeric habitats; however, research is needed to improve detectability of tortoises in mesic habitats with flooded burrows. If occupancy is uncertain, we recommend collecting data on all burrows, irrespective of occupancy, so that burrow densities can be estimated even if occupancy cannot. We do not recommend expanding the search area with sigmoid search paths adjacent to transects owing to potential violations of assumptions, nor use of occupancy modeling, because model requirements may lead to unacceptable exclusion of data. © 2015 The Wildlife Society. [ABSTRACT FROM AUTHOR]

Adult gopher tortoises (Gopherus polyphemus) are difficult to physically restrain, particularly for examination of the upper respiratory tract and oral cavity--areas important for biological sample collection during disease surveillance studies. Collection of nasal lavage is required for determining the status of Mycoplasma infection in tortoises. Anesthesia is often necessary to provide full relaxation in order to gain access to the head and mouth for nasal lavage. Therefore, deep sedation or general anesthesia are required both for the welfare of the tortoise and to maximize the usefulness of biological samples collected. The objective of this study was to assess the utility and safety of a novel field-anesthetic combination of dexmedetomidine-ketamine-morphine (75 mc/kg; 8 mg/kg; 1mg/kg, respectively), followed by reversal with atipamezole (0.02mg/kg). Between May and October 2009 at the Joseph W. Jones Ecological Research Center in Baker County, Georgia, USA, 128 tortoises were captured and anesthetized with this protocol. Average time to first effects was 9.7 minutes, to induction was 21.6 minutes, to total recovery after administration of reversal was 92.7 minutes, and the mean time from administration of anesthesia through complete recovery for adult tortoises was 129 minutes but ranged from 40 minutes to 300 minutes. Clinical signs of upper respiratory tract disease significantly reduced the induction time such that tortoises with clinical signs lost consciousness faster than healthy tortoises. Study month significantly influenced the time to induction and time to recovery, such that as the study progressed, both parameters decreased. This anesthetic protocol proved to be an effective, reliable, repeatable, and safe method to collect quality biological samples from gopher tortoises. [ABSTRACT FROM AUTHOR]