Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps

Christopher N. Jacques; Robert W. Klaver; Tim C. Swearingen; Edward D. Davis; Charles R. Anderson; Jonathan A. Jenks; Christopher S. DePerno; Robert D. Bluett

doi:10.1002/wsb.968

USGS · 70228003

Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps

Christopher N. Jacques·Robert W. Klaver·Tim C. Swearingen·Edward D. Davis·Charles R. Anderson·Jonathan A. Jenks·Christopher S. DePerno·Robert D. Bluett

View original source ↗Export metadata ↓

Abstract

Camera-trapping data analyzed with spatially explicit capture–recapture (SCR) models can provide a rigorous method for estimating density of small populations of elusive carnivore species. We sought to develop and evaluate the efficacy of SCR models for estimating density of a presumed low-density bobcat ( Lynx rufus ) population in fragmented landscapes of west-central Illinois, USA. We analyzed camera-trapping data from 49 camera stations in a 1,458-km 2 area deployed over a 77-day period from 1 February to 18 April 2017. Mean operational time of cameras was 52 days (range = 32–67 days). We captured 23 uniquely identifiable bobcats 113 times and recaptured these same individuals 90 times; 15 of 23 (65.2%) individuals were recaptured at ≥2 camera traps. Total number of bobcat capture events was 139, of which 26 (18.7%) were discarded from analyses because of poor image quality or capture of only a part of an animal in photographs. Of 113 capture events used in analyses, 106 (93.8%) and 7 (6.2%) were classified as positive and tentative identifications, respectively; agreement on tentative identifications of bobcats was high (71.4%) among 3 observers. We photographed bobcats at 36 of 49 (73.5%) camera stations, of which 34 stations were used in analyses. We estimated bobcat density at 1.40 individuals (range = 1.00–2.02)/100 km 2 . Our modeled bobcat density estimates are considerably below previously reported densities (30.5 individuals/100 km 2 ) within the state, and among the lowest yet recorded for the species. Nevertheless, use of remote cameras and SCR models was a viable technique for reliably estimating bobcat density across west-central Illinois. Our research establishes ecological benchmarks for understanding potential effects of colonization, habitat fragmentation, and exploitation on future assessments of bobcat density using standardized methodologies that can be compared directly over time. Further application of SCR models that quantify specific costs of animal movements (i.e., least-cost path models) while accounting for landscape connectivity has great utility and relevance for conservation and management of bobcat populations across fragmented Midwestern landscapes.

Explore related subjects

Wildlife Society Bulletin Article

Source-reported bounding extent: 40.01289077952615° to 40.330842639095756° latitude; -91.2139892578125° to -90.45867919921875° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Christopher N. Jacques, Robert W. Klaver, Tim C. Swearingen, Edward D. Davis, Charles R. Anderson, Jonathan A. Jenks, Christopher S. DePerno, Robert D. Bluett. 2019-06-21. Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps. https://doi.org/10.1002/wsb.968

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Developing a low-cost drone-based method for deploying and retrieving autonomous recording units in inaccessible areas

Autonomous Recording Units (ARUs) are increasingly used in research to support passive acoustic monitoring, but deployment in remote or inaccessible locations remains logistically challenging. Traditional manual placement is labor-intensive, time-consuming, potentially hazardous, and often limited to habitat edges, creating sampling biases and restricting spatial coverage. To address placement limitations in wetland systems, we developed and field-tested a low-cost, lightweight floating platform paired with a drone-based deployment and retrieval system. The drone-deployable ARU platform, constructed from inexpensive, off-the-shelf materials (~US $21 per unit), weighed ~560 g and was mounted with an ARU (AudioMoth) at ~1.2 m above water. The platform was designed for stability, portability, and compliance with Federal Aviation Administration Part 107 regulations. Field trials were conducted across 50 operations in various types of historical rice-field impoundments along the South Carolina coast, which provide critical habitat for secretive marsh birds such as rails (e.g ., Rallus, Laterallus , and Porzana ) and bitterns (e.g ., Botaurus and Ixobrychus ). All 50 deployments and retrievals were successful, demonstrating the robustness of the method under diverse hydrologic and vegetative conditions. Deployment times were significantly shorter than retrieval times (median 6 vs. 9 min), with retrieval requiring greater precision for hook engagement. Operation times scaled predictably with distance: deployment increased by 0.93 min/100 m (R 2 = 0.94) and retrieval by 1.17 min/100 m (R 2 = 0.95). No platform damage or displacement was observed, as emergent vegetation was likely providing natural anchoring. Our approach offers an affordable and effective solution for expanding ARU coverage in large, inaccessible wetlands, reducing sampling bias and enhancing biodiversity monitoring. With continued advances in drone payload capacity, battery endurance, and beyond-visual-line-of-sight flight regulations, our workflow could be adapted for deploying multi-sensor platforms (e.g., ARUs, eDNA samplers, water and air quality sensors, plant sample collectors, insect traps, and trail cameras) to support integrated biodiversity monitoring in challenging landscapes worldwide.

South Carollina↗

USGS2026

Comparison of data handling techniques for modeling bat acoustic activity

With the proliferation of acoustic sampling to investigate bat distribution and ecology, researchers have implemented a myriad of statistical modeling approaches to interpret findings. Bats are taxa of high conservation concern; therefore, ensuring the accuracy of species-level habitat association models is critical for informing management. We sought to determine prediction differences among statistical approaches to modeling counts of acoustic detections, using generalized linear mixed models with 8 acoustic data-handling techniques. We applied each approach or combination of approaches to a rare species, the northern long-eared bat ( Myotis septentrionalis ), and a common species, the eastern red bat ( Lasiurus borealis ), from summer survey results on a landscape in south-central Pennsylvania, USA, 2024. We evaluated the accuracy of habitat association models of bat acoustic activity at the species level using cross-validation and compared resulting predictions of models using spatial correlations. We determined that filtering data by automated identification software (Kaleidoscope Pro), the maximum likelihood estimate (MLE) P -value thresholds reduced relative mean absolute error (rMAE) in cross-validation of northern long-eared bat models. Using the MLE-retained data produced the most accurate predictions over using raw data or the overly conservative match ratio data. However, for the eastern red bat, the results from the most conservative approach of only retaining data with at least a 90% match ratio from software development training sets had the lowest rMAE. We have provided evidence that the current standard of filtering data by nightly MLE can result in more accurate and informative habitat-use acoustic activity models for rare bat species.

Pennsylvania↗

USGS2026

Abundance, trends, and challenges facing mountain goats throughout their North American distribution

Recent declines among some mountain goat ( Oreamnos americanus ) populations have heightened concern about their current status and ability to cope with future challenges. We conducted a range-wide assessment of the status of mountain goats across their distribution to understand the extent and patterns of change in recent years. We queried states, provinces, National Parks, and Indigenous governments with territories and reserves containing local wild populations, requesting updates on estimated mountain goat abundance and trends over time, as well as qualitative assessments of conservation challenges. We supplemented the questionnaires with existing literature (both published and available from agency websites). We subjected a subset of mountain goat population time−series to exploratory meta-analyses, examining covariates associated with rates of change. Respondents identified 203 units within which estimates were documented, a majority of which were raw counts from aircraft; fewer jurisdictions used site-specific sightability models, mark-recapture statistics, or other approaches to account for imperfect detection. Jurisdictions updated unit-specific estimates on average every 4.0 years (SD = 2.9, Min–Max = 1–24 years). Among 152 qualitative estimates of trends of native populations, 3% were reported as having increased substantially, 10% as having increased slightly, 24% as having declined slightly, and 14% as having declined substantially (49% reported either no detectable trend or insufficient data to identify a trend). Among 133 estimates of trends of introduced or pioneering populations, 5% increased substantially, 24% increased slightly, 20% declined slightly, and 11% declined substantially (40% reported no detectable trend). Jurisdiction-wide abundance estimates were lower than those previously published in all jurisdictions except Colorado and Oregon, and in Alaska, where trends were unclear. Intrinsic rates of increase ( r ) were positively associated with the population being introduced or pioneering, negatively associated with heavy snow and, to a lesser extent, with drought, but were not associated with abundance or presence of hunter harvest. Existing evidence suggested that many local populations, especially native populations, have declined, but understanding of specific causes has been constrained by limited monitoring capacity. Greater spatiotemporal monitoring effort and detailed studies would inform appropriate strategies to address threats and future challenges to mountain goats.

Wildlife Society Bulletin↗