Eco - Sustainable Tourism
Our research examines nature-based, community-based, and sustainable tourism as interconnected conservation and development strategies, particularly in tropical regions. Grounded in land-use and land-cover change, political ecology, ecological and economic anthropology, conservation and development, and tropical ecology, we investigate how tourism influences relationships among households, communities, landscapes, and natural resources. Particular attention is given to locally owned and collectively managed tourism initiatives and their effects on human well-being, cultural resources, local economies, land-use decisions, and environmental conservation across different spatial, temporal, political, and economic contexts.
We integrate quantitative and qualitative methods to evaluate these relationships. Policy analysis and socioeconomic household surveys are combined with remote sensing, GIS, and geospatial analysis. Medium- and high-resolution satellite imagery is used to measure tourism-associated patterns of deforestation, reforestation, and landscape change. Uncrewed aerial systems equipped with LiDAR and hyperspectral sensors, together with forest inventories, camera traps, and acoustic recorders, are used to examine relationships among tourism, forest structure and composition, and wildlife occurrence and abundance. Our work in Central America, for example, has evaluated how ecotourism development affects household economies, land-use dynamics, biodiversity, and the long-term sustainability of natural resources and landscapes.
We integrate quantitative and qualitative methods to evaluate these relationships. Policy analysis and socioeconomic household surveys are combined with remote sensing, GIS, and geospatial analysis. Medium- and high-resolution satellite imagery is used to measure tourism-associated patterns of deforestation, reforestation, and landscape change. Uncrewed aerial systems equipped with LiDAR and hyperspectral sensors, together with forest inventories, camera traps, and acoustic recorders, are used to examine relationships among tourism, forest structure and composition, and wildlife occurrence and abundance. Our work in Central America, for example, has evaluated how ecotourism development affects household economies, land-use dynamics, biodiversity, and the long-term sustainability of natural resources and landscapes.
Photos from the Galapagos
Monitoring of Socio-Economic-Ecological Systems
Our projects frequently seek to advance repeatable monitoring frameworks of SEES - Socio Economic Ecological Systems.
SPEC Lab members Angelica Almeyda, Andrea Chave, and Eben Broadbent working with an outstanding team to develop conceptual adaptive frameworks to test SEES - socio-economic-ecological systems.
Monitoring of Biodiversity and Threats
A representative SPEC Lab research theme is the development of integrated, multi-taxa and multi-method frameworks for understanding biodiversity patterns and threats across space and time. Permanent forest plots provide measurements of tree species composition, stem diameter, forest structure, vegetation dynamics, and microclimate. Within and around these plots, biodiversity can be monitored using complementary methods targeting different taxonomic and functional groups. Time-synchronized acoustic-recorder arrays capture two- and three-dimensional soundscapes of birds, bats, frogs, and insects; ultrasonic detectors measure bat activity; camera traps document terrestrial mammals; fruit-baited traps sample butterflies; pitfall traps target dung beetles and other ground-dwelling insects; and additional methods assess bee diversity and abundance. Combining these observations allows us to examine whether changes in one taxonomic group predict changes in others and to identify indicators capable of supporting efficient, long-term biodiversity monitoring.
These field measurements are integrated with drone-based RGB photogrammetry, LiDAR, and hyperspectral imagery to characterize three-dimensional forest structure, canopy composition, habitat heterogeneity, and land cover surrounding each monitoring plot. Dense time series of high-resolution satellite imagery extend the analysis from individual plots and local drone-mapping areas to entire landscapes, allowing us to investigate connectivity, fragmentation, forest degradation, restoration, land-cover change, and other drivers of biodiversity dynamics. This nested design links organisms and ecological communities to habitat characteristics operating from meters to landscape scales and from individual sampling periods to multiyear environmental change.
The ecological observations can then be integrated with spatially explicit household surveys, participatory mapping, policy analysis, and community-based knowledge. These approaches help identify the socioeconomic, cultural, political, and institutional drivers of environmental change, including hunting and defaunation, selective logging, mining, habitat degradation, agricultural conversion, infrastructure development, conservation, restoration, and tourism. Together, these methods support a genuinely socio-ecological monitoring framework that connects multi-taxa biodiversity, forest structure and composition, climate, landscape dynamics, human activities, and natural-resource governance across space and time.
A representative SPEC Lab research theme is the development of integrated, multi-taxa and multi-method frameworks for understanding biodiversity patterns and threats across space and time. Permanent forest plots provide measurements of tree species composition, stem diameter, forest structure, vegetation dynamics, and microclimate. Within and around these plots, biodiversity can be monitored using complementary methods targeting different taxonomic and functional groups. Time-synchronized acoustic-recorder arrays capture two- and three-dimensional soundscapes of birds, bats, frogs, and insects; ultrasonic detectors measure bat activity; camera traps document terrestrial mammals; fruit-baited traps sample butterflies; pitfall traps target dung beetles and other ground-dwelling insects; and additional methods assess bee diversity and abundance. Combining these observations allows us to examine whether changes in one taxonomic group predict changes in others and to identify indicators capable of supporting efficient, long-term biodiversity monitoring.
These field measurements are integrated with drone-based RGB photogrammetry, LiDAR, and hyperspectral imagery to characterize three-dimensional forest structure, canopy composition, habitat heterogeneity, and land cover surrounding each monitoring plot. Dense time series of high-resolution satellite imagery extend the analysis from individual plots and local drone-mapping areas to entire landscapes, allowing us to investigate connectivity, fragmentation, forest degradation, restoration, land-cover change, and other drivers of biodiversity dynamics. This nested design links organisms and ecological communities to habitat characteristics operating from meters to landscape scales and from individual sampling periods to multiyear environmental change.
The ecological observations can then be integrated with spatially explicit household surveys, participatory mapping, policy analysis, and community-based knowledge. These approaches help identify the socioeconomic, cultural, political, and institutional drivers of environmental change, including hunting and defaunation, selective logging, mining, habitat degradation, agricultural conversion, infrastructure development, conservation, restoration, and tourism. Together, these methods support a genuinely socio-ecological monitoring framework that connects multi-taxa biodiversity, forest structure and composition, climate, landscape dynamics, human activities, and natural-resource governance across space and time.
