Bio
I am a PhD student in the Department of Biology at Stanford University where my academic advisor is Dr. Chris Field. I am also a graduate student researcher in Dr. Gregory Asner’s lab in the Carnegie Institution’s Department of Global Ecology at Stanford University. I graduated with a Bachelor's of Science from the University of Vermont , with a concentration in tropical botany. Following this I obtained my Master's of Science in forestry from the University of Florida at Gainesville, with a concentration in tropical forestry and remote sensing. My doctoral interests are in tropical forest degradation and recovery at different spatial and temporal scales. Given the broad nature of this study area my dissertation chapters encompass: (1) using Landsat imagery to assess forest fragmentation and edge effects over the Brazilian Amazon, (2) using Quickbird satellite imagery to assess limitations to methods for biomass calculation through automated crown delineation in lowland Bolivia, and (3) fusing airborne waveform LiDAR with hyperspectral imagery to model climate-productivity interactions within a tropical forest located on a elevation gradient in Hawaii. I am involved in projects linking social sciences with forest ecology and remote sensing, including development impact assessments on the Pacific coast of Costa Rica and understanding feedbacks between soil fertility and land use decision making in the context of rapid infrastructure development in the Peruvian Amazon. Future research interests include (1) using the micro-climate and productivity models I am developing during the course of my dissertation to understand understory regeneration and herbivory dynamics in diverse neotropical forests under differing soil fertility conditions, (2) continuing canopy physiological work to better understand potential impacts of future climatic changes on tropical forest structure, function and composition, (3) understanding synergies between human-fauna interactions and land use and land cover dynamics within our tri-national frontier Amazon study area (i.e., The MAP), in particular as related to the sustainability of Castana (Brazil Nut), (4) linking human-environment interactions with spatio-temporal dynamics of wild-fires in our MAP study area, and (5) further investigation into the role of land use type and intensity in the tropics on soil fertility and the C cycle with a goal to improve the sustainability of agricultural practices.
Selected current research projects
Influence of forest architecture on carbon assimilation along an elevation gradient in Hawaii: linking field measurements, airborne waveform LiDAR, hyperspectral imagery and modeling
I develop models to extract leaf area index (LAI) from hyperspectral data using PROSAIL IDL radiative transfer model coupled with non-linear multi-variate parameterization procedures and/or vegetation indices, then link this to airborne waveform LiDAR to derive canopy leaf area density profiles. Models coded in IDL based on the 3D architecture of forest interior, as mapped through waveform LiDAR decomposition, allow detailed spatial and temporal models of microclimate, parameterized to field measurements using sensor arrays distributed throughout the forest canopy and linked to top of canopy climate stations. The microclimate model is then linked to leaf physiology via response and induction curves collected over a wide number of under to mid-canopy species growing in a variety of forest architectures. We use an elevation gradient spanning ~1000 ft to understand interactions between long (elevation gradient) and short (seasonal) climatic variation on interior forest microclimate and productivity under varying conditions of diffuse/direct photosynthetic active radiation (PAR). In addition to the basic ecological questions addressed the models developed during the course of this project will be applicable to tropical forests in general where high resolution waveform LiDAR and hyperspectral data are collected.
PI: Eben N. Broadbent, funding from NSF DDIG, Stanford University, a DOE GCEP Fellowship, and the Carnegie Institution for Science.
Status: Fieldwork, data collection and entry, model development
Smallholders in Southwest Amazonia: development policies, socioeconomic conditions and forest use.
We use an interdisciplinary approach to investigate the effects of development policies, particularly the paving of the Interoceanic Highway and land tenure, on land conversion among smallholders at the states/departments of Madre de Dios (Peru), Acre (Brazil), Pando (Bolivia), also know as the MAP area. Methods include social and biophysical surveys conducted for a stratified sample of 100 households per state/department during 2006 and 2007 and the analysis of Landsat satellite imagery for 1990, 2000 and 2007.
PI: Angelica M. Almeyda, Stanford University
Position: Co-investigator
Status: data entry and analysis, remote sensing processing
Species and community foliar nutrient dynamics during forest succession in the Bolivian Amazon.
Foliar and soil analyses were conducted within 18 forest sites spanning 5-50 years post abandonment following slash and burn agriculture. We compare changes in soil nutrient and isotopes across our chronosequence versus community and species scale foliar dynamics. A better understanding of linkages between above and below ground nutrient dynamics will allow an improved understanding of factors influencing secondary forest development in the Amazon. Such dynamics represent a substantial portion of change in the Amazon carbon budget.
PI: Eben N. Broadbent, Stanford University
Status: data analysis, writing
Social and edaphic factors influencing swidden agricultural decisions in the Peruvian Amazon.
We investigate the effects of soil and socioeconomic conditions on household land use history and decision making, in particular decisions leading to increased forest degradation or deforestatation. Our study spans over 80 sites, including both agriculture and pasture, with detailed land use histories ranging from 1 to 40 years. AutoMCU analysis of annual Landsat imagery spanning 1990 through 2006 is used to compare detailed land cover histories of our sites with fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and exposed soil
Collaborative effort between Eben N. Broadbent and Angelica M. Almeyda, funding from The Morrison Institute at Stanford University.
Status: Data entry, remote sensing imagery analysis
Land cover change effects on forest connectivity and defaunation in Manuel Antonio, Cost Rica.
We use an interdisciplinary approach to investigate the effects of land use and land cover change and tourism development on forest connectivity and fauna populations in the Manuel Antonio National Park area. We link multiple scales through multi-temporal change trajectory analysis of land cover classifications from 1979 through 2008 and questionnaire based surveys with heads of households.
PIs: William H. Durham and Rodolfo Dirzo, Stanford University, funding from the Woods Institute for the Environment, Stanford University.
Position: Co-investigator and lead author
Status: In review
