Work

Do thermal drones outperform traditional surveys in detecting and estimating population density of sloths?

Year: 2025

Type: article

Abstract: • Thermal drones significantly enhance sloth detection efficiency. • Drones detect sloths 3× faster and in twice as many sites as ground surveys. • Drone surveys cut operational costs, offsetting upfront expenses in the medium term. • Combining drones with ground surveys is recommended for accurate density estimates. Wildlife population surveys are crucial for conservation but require significant time and resources, especially for elusive species like the threatened maned sloth (Bradypus torquatus). We evaluated the efficiency and effectiveness of thermal drones versus traditional ground-based surveys for detecting and estimating maned sloth populations, across seven 10.5-hectare forest plots in Bahia, Brazil. Thermal drones detected 10 individuals in six plots (86%) over 13.8 h, while ground-based surveys detected nine individuals in three plots (43%) over 51.7 h. Detection rate were significantly higher for thermal drones (0.70 ± 0.45 individuals/hour) than ground-based method (0.17 ± 0.22 individuals/hour; p = 0.006), though density estimates were similar. Drone survey costs were initially four times higher but had lower operational costs per area (2.7×) and per sloth detected (3.2×), achieving financial return after surveying 740 ha or detecting 38 sloths. Drones were three times faster for individual detection and twice as efficient for identifying occupied sites, reducing costs and improving results. However, combining drones with ground surveys or increasing sampling effort with drones is recommended for accurate density estimates. This technology may be particularly advantageous for medium- to long-term studies and large-scale surveys, enhancing population monitoring and conservation of arboreal mammals like the maned sloth.

Source: Perspectives in Ecology and Conservation

DOI: 10.1016/j.pecon.2025.10.002

Authors: Gabriel Nascimento dos Santos, Camila Righetto Cassano, Gabriela Alves-Ferreira, Luciana Franco Veríssimo, Gastón Andrés Fernandez Giné

Institution: Universidade Estadual de Santa Cruz

Language: English

Topic: Wildlife Ecology and Conservation

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Life on land

Open Access status: diamond