Big data analysis and coupled human-natural systems modeling to examine the influence of socioeconomic and environmental factors on protected areas - Zarria-Samanamud, Melody Rocio, author; Boone, Randall, advisor; Bowser, Gillian, advisor; Havrilla, Caroline, committee member; Jones, Kelly, committee member; Klein, Julia, committee member; Young, Kenneth, committee member (Colorado State University. Libraries, 2025)
This dissertation aims to deepen our understanding of how human and environmental factors affect protected areas through a social-ecological systems approach. This dissertation comprises two topics. The first consists of determining the level of landscape changes in protected areas and identifying the anthropogenic and environmental factors associated with these changes. The other topic explores the potential impacts of climate change and land management on ecosystems, agropastoral families' livelihoods, and livestock grazing behavior in the Peruvian Andes. I used a social-ecological systems analytical approach to have an interdisciplinary perspective on how the biophysical and socioeconomic contexts of protected areas impact their conservation effectiveness and influence the pressures they face. My analyses used innovative analytical approaches, including big data analysis and agent-based modeling, to offer new insights into these critical issues. In Chapter 2, I quantified changes in the landscape of protected areas worldwide and identified the critical anthropogenic and biophysical factors associated with these changes. I estimated landscape metrics for about 11,000 protected areas for 2000 and 2020 using open-source spatial data and performed random forest analyses. Changes in the landscape of protected areas and their associated socioeconomic and environmental factors differed by region and cover classes. In general, landscape changes were mainly influenced by anthropogenic factors, such as the level of human development, agricultural expansion, population density, and the protected area's regulation level. The main biophysical factors critical in explaining landscape changes were slope and precipitation. In Chapter 3, I examined the ecological impacts of climate change in a mountain landscape in the Andes of Peru. I parametrized an ecosystem-process model (L-Range) to Andean environmental conditions to capture ecosystem responses to climate change. Climate change impacts on Andean ecosystems vary by cover class, topographic position, and climate scenario. Shrublands and woodlands will become more productive, whereas wetlands are projected to experience a decline in primary production. However, under the most extreme climate scenario, all cover classes will undergo a reduction in primary production. In Chapter 4, I explored the potential economic and ecological impacts of various land management scenarios in a valley of Huascaran National Park in the Andes of Peru used as grazing lands by a local community. I built the Agent-based model of laNd management Dynamics and Ecosystem Services (ANDES) that represents livestock grazing behavior, grazing management, and household economies. I coupled the ANDES/L-Range models to deepen my understanding of how new management scenarios and future climate conditions would impact ecosystems and families' economies. Families' incomes were reduced under the scenarios involving a reduction in livestock population. The biomass availability was markedly higher only under the scenarios that involved livestock population reduction and the implementation of new rotational grazing schemes. These findings reveal that not only livestock numbers should be adjusted but also livestock distribution. In Chapter 5, I analyzed how different grazing management schemes impact livestock forage consumption, grazing behavior, and body condition of cattle and sheep. I analyzed information derived from the Livestock Grazing Behavior sub-model of ANDES. Livestock responses to grazing management varied by species. Forage consumption and body condition were the highest under the scenarios that implied livestock population reduction. Moreover, livestock mortality was the lowest under these scenarios. In general, the below-optimal performance of livestock across all management scenarios suggests adjusting stocking rate and grazing frequency. The key insights derived from Chapters 3, 4, and 5 are as follows. The Andean ecosystems' response to climate change will exhibit considerable variability. While a reduction in primary production is anticipated across most cover classes, except for woodlands, the impacts of climate change will also be influenced by the ecosystem's landscape setting. Livestock management practices, particularly those that involve reducing livestock numbers, will result in better animal body condition. The implementation of regulatory policies, such as reducing livestock populations and limiting park land access, will have significant economic repercussions on families, especially middle-aged and elderly individuals, whose income primarily relies on livestock production. My study provides critical information for the sustainable management and conservation of protected areas and can serve as the basis for designing integrative policies that balance conservation and sustainable development. The development of conservation and sustainability policies must address the factors impacting protected areas and their surroundings. To achieve this, these policies should incorporate diverse perspectives and foster engagement with local communities.
Keywords: climate change; Peruvian Andean ecosystems; sustainable management; landscape analysis; agent-based model; random forest