Read the following excerpt from a journalistic article about environmental conservation in Ecuador:
"In the cloud forests of the Chocó Andino biosphere reserve in northwestern Ecuador, conservation biologists have recently deployed autonomous acoustic monitoring devices across varying forest plots. These solar-powered sensors record the ambient soundscapes—the complex cacophony of birdcalls, amphibian vocalizations, and insect hums—twenty-four hours a day. Rather than relying on traditional visual surveys that are constrained by steep topography and dense fog, researchers use machine-learning algorithms to decode thousands of hours of audio data. Initial findings reveal that while secondary forests regenerated over the past fifteen years exhibit an overall sound volume comparable to pristine old-growth forests, their acoustic diversity index is markedly distinct: mid-frequency canopy calls from specialist songbirds remain largely absent, replaced instead by the ubiquitous drones of generalist insect species. The researchers emphasize that restoring physical tree cover does not instantly replicate the intricate acoustic and ecological niches established over centuries."
Based on the passage, what can most reasonably be inferred about the recovery of deforested ecosystems in the Chocó Andino reserve?
- AAutonomous solar-powered recording devices are more cost-effective to deploy than manual field surveys.
- A full restoration of structural canopy does not guarantee the immediate return of specialized fauna that depend on mature forest dynamics.Cevap
- CSecondary forests will permanently fail to sustain native avian species regardless of future conservation management.
- DPassive acoustic sensors and machine-learning algorithms represent an entirely flawless method for measuring all forms of biodiversity.