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USGS · 70256731

Using noninvasive genetics for estimating density and assessing diet of urban and rural coyotes in Florida, USA

Abstract

Coyotes ( Canis latrans ) are expanding their range and due to conflicts with the public and concerns of Coyotes affecting natural resources such as game or sensitive species, there is interest and often a demand to monitor Coyote populations. A challenge to monitoring is that traditional invasive methods involving live-capture of individual animals are costly and can be controversial. Natural resource management agencies can benefit from contemporary noninvasive genetic sampling approaches aimed at determining key aspects of Coyote ecology (e.g., population density and food habits). However, the efficacy of such approaches under different environmental conditions is poorly understood. Our objectives were to 1) examine accumulation and nuclear DNA degradation rates of Coyote scats in metropolitan and rural sites in Florida to help optimize methods to estimate population density; and 2) explore new genetic methods for determining diet of Coyotes based on vertebrate, plant, and invertebrate species DNA identified in scat. Recently developed DNA metabarcoding approaches make it possible to simultaneously identify DNA from multiple prey species in predator scat samples, but an exploration of this tool for assessing Coyote diet has not been pursued. We observed that scat accumulation rates (0.02 scats/km/day) did not vary between sites and fecal DNA amplification success decreased and genotyping errors increased over time with exposure to sun and precipitation. DNA sampling allowed us to generate a Coyote density estimate for the urban environment of eight Coyotes per 100 km2, but lack of recaptures in the rural area precluded density estimation. DNA metabarcoding showed promise for assessing diet contributions of vertebrate species to Coyote diet. Feral Swine (Sus scrofa) were detected as prey at higher frequencies than previously reported. We identify several considerations that can be used to optimize future noninvasive sampling efforts for Coyotes in the southeastern United States. We also discuss strengths and drawbacks of utilizing DNA metabarcoding for assessing diet of generalist carnivores such as Coyotes.

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90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 24.546468° to 31.000682° latitude; -87.634938° to -80.031362° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeXRIS

B.M. Kluever, M.B. Main, S.W. Breck, Robert Charles Lonsinger, J.H. Humphrey, J.W. Fischer, M.P. Milleson, A.J. Piaggio. 2022. Using noninvasive genetics for estimating density and assessing diet of urban and rural coyotes in Florida, USA. https://pubs.usgs.gov/publication/70256731

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Factors affecting benthic macroinvertebrate health in the City of Roanoke, Virginia, 2020–2023

Major waterways in the City of Roanoke (City) have failed to meet Virginia’s aquatic life designated use since 1996. Segments of the upper Roanoke River lack healthy benthic macroinvertebrate communities which prompted a total maximum daily load (TMDL) study by the Virginia Department of Environmental Quality (VDEQ) to identify the most probable stressor(s) causing the impairment. Excess fine sediment was identified as the most probable stressor impairing benthic macroinvertebrates on portions of the Roanoke River in 2006, and a watershed implementation plan published in 2016 required communities within the impaired watershed to implement projects that would reduce the load of fine sediment entering the Roanoke River. Additional benthic macroinvertebrate sampling and stream habitat assessments along the Roanoke River and Tinker Creek (a tributary to the Roanoke River that flows through the City) revealed continued impaired conditions, and subsequent stressor identification analysis was completed in 2023. Samples collected downstream of the City on the Roanoke River and Tinker Creek generally showed more impaired conditions relative to samples collected at locations upstream of the City. Based on this evaluation, sediment and sediment-bound polychlorinated biphenyls (PCBs) were identified as probable stressors while specific conductance, total nitrogen, and sediment metals were possible stressors in Tinker Creek; however, only a sediment TMDL target was identified to address impaired benthic macroinvertebrate communities. In the Roanoke River upstream of the Niagara Dam, sediment and total phosphorus were identified as probable stressors, sediment polycyclic aromatic hydrocarbons and sediment PCB were considered possible stressors; however, the TMDL target was only for total phosphorus. The City partnered with the U.S. Geological Survey (USGS) in 2016 to continuously monitor water quality and streamflow conditions on a major tributary of Tinker Creek, Lick Run, and by 2020, four similar monitoring stations were installed on the Roanoke River and Tinker Creek near the locations of benthic macroinvertebrate sampling. Monitored parameters included streamflow and/or gage height (water level), water temperature, pH, dissolved oxygen, specific conductance, and turbidity. Turbidity is a measure of the relative clarity of the water and was previously used to model suspended-sediment concentrations at the monitoring stations. The City also contracted Kirk Environmental, LLP (KE) to collect benthic macroinvertebrate samples and stream habitat assessments near the locations of the water-quality monitoring stations. Identified benthic macroinvertebrates were used to calculate the Virginia Stream Condition Index (SCI), a multi-metric index composed of eight biological attributes that represent elements of the structure and function of the benthic macroinvertebrate community that measure diversity, composition, and tolerance to pollution. Study objective: In this report, benthic macroinvertebrate samples and stream habitat assessment scores collected at four locations on the Roanoke River and Tinker Creek by KE and the VDEQ between 2020 and 2023 were compared to measured water-quality and streamflow conditions prior to sampling to evaluate patterns between benthic macroinvertebrate health, water quality, and hydrology.

Virginia