FACTORS SHAPING BEACHES IN THE GALAPAGOS ISLANDS
Stephen J. Walsh, Laura Brewington, Phil Page, Brian Frizzelle
Project Goals
The goals of the project are to (1) describe a beach vulnerability framework for assessing the Galapagos Islands, with implication for other similarly challenged island ecosystems, and (2) assess the collection and fusion of digital spatial technologies and corresponding data sets to assess beaches through the application of high spatial resolution, remote sensing systems, such as (a) WorldView 2 satellite imagery of coastal settings and nearshore bathymetry, (b) a 3-D laser scanner to measure terrain conditions through the generation of ultra-high-resolution digital elevation models (DEMs) and super dense point clouds, and (c) optical, multispectral, and thermal remote sensing systems on-board unmanned aerial vehicles (UAV) to assess animal use patterns of beaches, tourism visitation sites, and urban settings linked to local residents and national and international tourists. The social and ecological vulnerability of beaches is influenced by their geographic remoteness, land use/land cover, human use intensity, orientation to the ocean, geomorphology (i.e., beach form and nearshore bathymetry), terrain configuration, spatial and ecological connectivity, diversity and endemism relative to disturbances, and the human dimension linked to consumptive behaviors, economic development, and conservation management.
FISHERIES MODELING
Stephen J. Walsh, Kim Engie, Phil Page, Brian Frizzelle
Model Overview
Contemporary fisheries in the Galapagos is the product of the legacy of overfishing, when the lobster and sea cucumber fisheries were severely crippled through overexploitation. Associated with the degradation of the fisheries industry in the Galapagos, tourism has expanded considerably, thereby creating economic opportunities for individuals, households, and communities. Our Agent-Based Model (ABM) considers strategies of household livelihood alternatives in the Galapagos with the central proposition that fishers are being “pushed” and “pulled” into the tourism industry, but not all fishers are able to obtain alternate employment nor do all want to transition to full or part-time employment in non-fishing activities. The processes embedded in the model examine fisheries as a social–ecological system, where livelihood transitions are modeled, and the multi-dimensional drivers of change are explored.
The Galapagos Fishers ABM (GF-ABM) simulates the decision- making processes of Fishers (Fisher agents) with regards to employment choices and an alternate household livelihood strategy that would move those most qualified into tourism, given a variety of circumstances, desires, and personal characteristics. The GF-ABM contains a demographic element that models basic changes at the Household level (Household agents). The model also contains an employment management component in which Fisher agents select jobs among three general employment sectors—fisheries, tourism, and government. The tourism and government sectors each have three tiers of jobs that require increasing agent skills. Fishers make their employment decisions based on their preference to remain in fishing, availability of jobs in the three employment sectors, and their personal/professional qualifications that facilitate their movement among the employment sectors. Households contain members that are non- Fisher agents, and Fishers belong to households. Income and expenses are calculated for Fishers and Household agents. The capitalized terms below highlight selected model components. There are eight parameters related to demographic change.
SYNTHESIS OF DRIVERS, PATTERNS, AND TRAJECTORIES OF LCLUC IN ISLAND ECOSYSTEMS (supported through grants from NASA-Land Cover Land Use Change Program)
Stephen J. Walsh, Richard E. Bilsborrow, Laura Brewington, Yang Shao, Hernando Mattei, Francisco Laso, Phil Page, Brian Frizzelle
Project Goals
Our project is designed to synthesize land cover/land use change (LCLUC) patterns on islands and to assess the drivers of change. The following summarizes are approach: (1) Perform a meta-analysis of global islands by focusing on the socio-economic, geographic, and biophysical drivers of LCLUC, and assess the role of satellite remote sensing for characterizing the composition, pattern, and structure of LCLUC on islands; (2) Primary Island Sites (Hawaiian Islands, Galapagos Islands, Puerto Rico) are characterized by an assembled social-ecological data set, including, population census data, tourism data, environmental data, and a blended multi-resolution, satellite image stack; (3) Develop a dynamic systems model of the Primary Island Sites, informed through statistical analyses and case study models, and determine if a single synthetic model can be generated that is capable of capturing social-ecological dynamics to understand the drivers of LCLUC on each island; (4) Once the operating protocols have been tested and dynamic system models developed for the Primary Island Sites, we will perform sensitivity analyses to assess model performance by varying data inputs of stocks, flows, rates of exchange, and feedback loops to determine the impacts of variables on model outcomes; (5) Expand the analysis of the generalizability of the model by fitting it to Maui Island, Hawaii using population census data, tourism data, environmental data GIS data layers, and satellite assets to assess LCLUC patterns and the drivers of change. Through the analysis of the Primary and Secondary Island Sites, we explain the impacts of tourism, demographics, environmental, and economic transitions on broader LCLUC issues, decision-making, and the politics of change.
HIGH RESOLUTION COMMERCIAL SATELLITE IMAGERY FOR ISLANDS STUDIES (supported through a grant from NASA-Land Cover/Land Use Change Program
Stephen J. Walsh, Laura Brewington, Yang Shao, Francisco Laso, Phil Page, (2019),
Project Goals
Characterize the human dimension on islands through an image time-series generated from Digital Globe and Planet Labs data, particularly, small-scale agriculture and the rural-urban transition in geographically restricted settings. Endangered Galapagos Tortoises are subjected to considerable habitat transformation and fragmentation along their migratory pathways. Forage abundance and patterns of consumption determine individual conditions, size, and fitness, mediated by population dynamics, competition from other individuals, evolutionary trajectories of species and ecosystems, and land cover/land use patterns. Findings include the following:
- Identify regions of remaining native forests in or near the agricultural zone of the Galapagos.
- Identify the distribution of invasive plant species like Psidium guajava, Rubus niveus, Zygsigum jambos, and Pennisetum purpureum that threaten agricultural lands and adjacent protected areas.
- Identify the distribution of Erythrina smithiana living fences in Santa Cruz, which might act as an obstacle for migrating tortoise populations.
- Identify the distribution of economically significant agricultural land cover like cattle ranching pastures, annual crops, tree crops, and cash crops such as coffee.
- Small-scale agriculture mapping at the farm and parcel level are vastly improved, both in the spatial structure of crop types & their compositional analysis.
- PlanetScope data provided effective mapping of household farms, small scale agricultural plots, unimproved local roads & trails, invasive plant species, and migration trails of Giant Tortoises as well as barriers to their movement.