Doctoral Dissertation Research: Impacts of Tropical Forest Degradation on Carbon Stocks, Habitat Structure, and Avifauna

University Of Maryland, College Park, College Park MD

Investigators

Abstract

NATIONAL SCIENCE FOUNDATION GEOGRAPHY SPATIAL SCIENCES (GSS) PROGRAM ABSTRACT This doctoral dissertation research will investigate how forest degradation from fire and logging impacts carbon stocks, habitat structure, and avifaunal communities across the landscape. The long-term consequences of these trends remain poorly understood because of the sampling limitations of traditional field-based methods. This project will use innovative methods that combine acoustic and LiDAR remote sensing with field-based and satellite observations in order to characterize degradation impacts over previously unavailable spatial and temporal scales. The synergy between LiDAR and acoustic remote sensing has the transformative potential to revamp the way biodiversity is monitored by facilitating simultaneous multiple sampling over extended temporal periods. Outcomes from this research project will be useful in providing a more holistic understanding of the rapidly changing dynamics of tropical forests that will help meet the global challenges of reducing biomass and biodiversity degradation. The project includes a strong educational component that will facilitate the transfer of key computational and remote sensing skills to undergraduate science, technology, engineering, and mathematics (STEM) students through an apprenticeship program initiated by the doctoral student. As a Doctoral Dissertation Research Improvement award, this award will provide support to enable a promising student to establish a strong independent research career. In the Amazon Basin of Brazil, one of the most biologically diverse regions of the world, forests have been heavily altered by over four decades of deforestation for agriculture, fire and logging activities. Understanding the impacts to biodiversity from forest degradation and the long-term habitat suitability of degraded forests is critical for efforts to reduce or minimize further damage to these environmentally sensitive areas. The doctoral student whose dissertation research will be supported by this award will focus on three core questions: (1) How does fire and logging impact carbon stocks and habitat structure? (2) What are the magnitudes of carbon losses and trajectories of carbon recovery following logging and fire activities? (3) How do avian communities respond to fire and logging, and what can be inferred about the biodiversity benefits of avoided degradation? The student will answer these questions by analyzing a time-series of satellite imagery to reconstruct the history of forest degradation and recovery that are reflected in contemporary LiDAR, forest inventory data, and bioacoustic recordings. She will integrate acoustic signal processing and Bayesian hierarchical occupancy modeling to characterize the distribution of biomass and biodiversity across the impacted forested areas.