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Gold mining is a major driver of Amazonian forest loss and degradation. As mining activity encroaches on primary forest in remote and inaccessible areas, satellite imagery provides crucial data for monitoring mining‐related deforestation. High‐resolution imagery, in particular, has shown promise for detecting artisanal gold mining at the forest frontier. An important next step will be to establish relationships between satellite‐derived land cover change and biodiversity impacts of gold mining. In this study, we set out to detect artisanal gold mining using high‐resolution imagery and relate mining land cover to insects, a taxonomic group that accounts for the majority of faunal biodiversity in tropical forests. We applied an object‐based image analysis (OBIA) to classify mined areas in an Indigenous territory in Guyana, using PlanetScope imagery with ~3.7 m resolution. We complemented our OBIA with field surveys of insect family presence or absence in field plots (n = 105) that captured a wide range of mining disturbances. Our OBIA was able to identify mined objects with high accuracy (>90% balanced accuracy). Field plots with a higher proportion of OBIA‐derived mine cover had significantly lower insect family richness. The effects of mine cover on individual insect taxa were highly variable. Insect groups that respond strongly to mining disturbance could potentially serve as bioindicators for monitoring ecosystem health during and after gold mining. With the advent of global partnerships that provide universal access to PlanetScope imagery for tropical forest monitoring, our approach represents a low‐cost and rapid way to assess the biodiversity impacts of gold mining in remote landscapes.

La enseãanza y el aprendizaje de los conceptos de campo, potencial y energía plantea especiales dificultades a estudiantes y docentes. Informamos sobre un estudio en el área de la electricidad y el magnetismo. Se analiza la comprensión de aspectos básicos de aquellos conceptos alcanzada por alumnos de segundo año de carreras de Ingeniería que habían completado el cursado de la asignatura y aprobado las evaluaciones correspondientes. Los resultados muestran la necesidad de complementar más la instrucción con abordajes cualitativos, conceptuales, comprensivos, que en la instrucción habitual suelen ser postergados por tratamientos casi excluyentemente centrados en formalismos matemáticos cuyo signicado físico no queda claro ante los estudiantes.

This paper presents the first data on vocalizations of the Long-snouted Bat Platalina genovensium. It is also the first published study on ultrasound analysis of any bat from Peru. The recordings of vocalizations were obtained from flying bats while in their roosts. These roosts were found in two locations near the city of Lima. Each echolocation call was composed of FM fast pulses of 1.30 ms of extremely low intensity (-10 to -35 dB one m away from the recording device), in sequences of 12.90 pulses per second, with 28.58 kHz bandwidth in average, discontinuous, average interpulse of 67.56 ms, and an energy peak in 89.21 kHz. The pulses present a harmonic above 190 kHz. Both, Discrete Fourier Transform and Analysis of the Energy Distribution in frequency bands were used to obtain a predictive equation. This equation is able to predict duration call for 70-80 kHz, 90-100 kHz, and 110-120 kHz energy frequency bands. So, if 110-120 kHz frequency band increases 4%, then duration call decreases 0.2 ms, whereas if 70-80 y 90-100 kHz frequency band increases, then duration call also does it in 0.1 ms. This equation can be used to identify and monitor this species. It also allows us to determine how P. genovensium adapts its energy frequency bands in order to avoid overlap between pulse and echoes.