Other Forestry and Forest Sciences Commons^™

Is There A More Effective Design For Quadrat To Increase Ease Of Use And Vegetation Density?, Scott M. Burke Jr., Kristen M Bellisario

Discovery Undergraduate Interdisciplinary Research Internship

Quadrats are a special tool in the ecology field that allows the measurement of vegetation density for further data analysis of a habitat. The larger the quadrat cross-sectional area, the better the results of the data, which in turn can make the quadrat hard to carry through field sites. In wildlife corridor research, quadrat surveys provide a quantitative metric for habitat suitability. In this work, we consider the efficiency and ease-of-use benefits for field work in the design of a collapsible version of a quadrat using a House of Quality (standard metric for new design requirements) to assess the customer …

Limited Soil Water Recharge In Summer Affects Seasonal Isotopic Signatures Of Tree Xylem Water, Marius G. Floriancic, Gregory R. Goldsmith, Harsh Beria, Scott T. Allen, James W. Kirchner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Recent studies have reported that xylem waters in forest trees during the summer growing season are often isotopically similar to winter, rather than summer, precipitation. Several hypotheses have been proposed to explain this observation, which can be viewed as a form of ecohydrological separation, but empirical tests spanning space and time remain limited. We hypothesise that variations in the seasonal origin of precipitation found in tree xylem waters can be explained by seasonal differences in soil water recharge. We test this hypothesis by evaluating to what extent climatic aridity can explain seasonal signals in extensive surveys of the isotope ratios …

Integrating Belowground Recovery Into Tropical Forest Restoration Design And Monitoring, Lauren Toro, Leland K. Werden, Shalom D. Addo-Danso, Kelly M. Andersen, Sarah Batterman, Matilde M. Bragadini, Pooja Choksi, Rebecca J. Cole, Liza S. Comita, Daniela Cusack, Daisy H. Dent, Lee H. Dietterich, Joshua B. Fisher, Katrin Fleischer, Lucia Fuchslueger, Nohemi Huanca-Nunez, Janey R. Lienau, Lindsay A. Mcculloch, Ember M. Morrissey, Jennifer S. Powers, Mareli Sánchez-Juliá, Oscar Valverde-Barrantes, Anita Weissflog, Michelle Y. Wong

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

There is growing recognition that tropical forest restoration is key for sequestering carbon and enhancing ecosystem resilience. Soils, roots, and soil biota are central to ecosystem function and services, but belowground recovery is largely overlooked in restoration monitoring frameworks. Here, we outline current understanding of the links between above- and belowground recovery in tropical forests by examining how belowground properties before and after intervention influence recovery; by evaluating whether aboveground recovery can serve as a proxy for belowground dynamics; and by proposing a blueprint for monitoring dynamic soil physical (bulk density, aggregate stability), chemical (organic matter or carbon, pH), and …

Assessment Of Spatial Autocorrelation And Scalability In Fine-Scale Wildfire Random Forest Prediction Models, Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfire prediction models that can be applied across diverse regions at fine scales (<  100 m) are critical for wildfire management. Remote sensing offers a path forward by providing heterogeneous and dynamic measurements of fuel load, type, and flammability. Machine learning methods such as random forests provide an empirical framework that are high-accuracy, computationally efficient, interpretable and able to model complex ecological relationships. Here we use high resolution (70 m, every 3–5 days) remote sensing observations of evapotranspiration and evaporative stress index, which represent plant water stress, from Ecosystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS), as well as topography and weather data, to predict burn severity and occurrence for 8 large wildfires that burned 3715 km² from 2021 and 2022 in New Mexico, USA. These fires ranged from low to high burn intensity, and covered a diverse range of ecoregions (deserts, grasslands, forests), plant species, and topographies. We used a single model to predict the burn severity of all wildfires one week before occurrence. The prediction accuracy was greatest when using all predictors (ECOSTRESS, weather, topography) (R² = 0.77). We assessed the role of spatial autocorrelation in driving model performance by: (1) increasing the sample spacing of our dataset, (2) …

Assessing The Influence Of Afforestation On Soil Quality And Soil Organic Carbon: A Case Study In Rashaya District, Lebanon, Mohammad Saleh, Wael Mostafa, Safaa Baydoun, Hisham Salman, Jamilah Borjac

BAU Journal - Science and Technology

Afforestation is a promising strategy for improving soil quality and enhancing carbon sequestration, contributing to climate change mitigation efforts. This study assessed the impact of afforestation on soil parameters in two afforested areas and one natural forest, compared with adjacent non-forested sites in Rashaya al-Wadi, Lebanon. Soil samples (0–30 cm depth) were analyzed for texture, pH, electrical conductivity (EC), soil organic matter (SOM), soil organic carbon (SOC), organic nitrogen (ON), mineral nitrogen (MN), and available phosphorus (AP) using ISO and standardized protocols at the Lebanese Agricultural Research Institute (LARI). The findings indicate that afforestation significantly increased SOM, SOC, and ON, …

Covered In Snow, Katelynn M. Rogers

Masters Theses

Covered in Snow is a photographic exploration into the ripple effect of maternal loss and environmental decay in my hometown of Canton, Ohio. In the wake of a miscarriage, the woods I had grown up within began calling to me, urging me to return. Unbeknownst to me, a series of accidental deaths of women had been happening throughout these trees my entire life, their stories only coming to the surface as I looked to the trees for solace. This series of inexplicable deaths in the woods I so desperately loved began to alter my relationship to the trees, a distrust …

The State Of Municipal Scale Highest Use Urban Wood Reclamation Projects, Bradley C. Almond

Graduate Liberal Studies Theses and Dissertations

Millions of urban trees are downed annually for various reasons, such as storms, disease, or development. We are all witnesses to the loss of trees as we see the piles of woody waste assembled on the curbside, ready for public works pickup. Today, most urban wood waste ends up in landfills, mulching/chipping facilities, or firewood production. Each of these alternatives results in the release of sequestered carbon back into the atmosphere.

The initial research led to successful diversion from landfills to mulch and firewood operations. Then, the research shifted to converting urban wood waste for its best use, which outlined …

Climate Constrains The Enhancement Of Co2 Fertilization On Forest Gross Primary Productivity, Xinyuan Wei, Daniel J. Hayes, Christopher R. Schwalm, Joshua B. Fisher, Deborah N. Huntzinger, Lei Ma, Rodrigo Vargas, Nathaniel A. Brunsell

Mathematics, Physics, and Computer Science Faculty Articles and Research

Forest gross primary production (GPP) is influenced by the interplay between climate conditions and atmospheric CO₂ levels, which interact in complex ways, generating both compensating and amplifying effects. In this study, eddy covariance flux measurements from 50 forest ecosystems were integrated with simulations from 14 terrestrial biosphere models to investigate how climate conditions and atmospheric CO₂ concentrations regulate forest GPP. This approach bridges site-level observations with biome-scale model estimates to develop a global understanding. Our findings suggest that in boreal and cold temperate regions, temperature primarily constrains the enhancement of the CO₂ fertilization on forest GPP; however, …

Monitoring Mangrove Dynamics And Evaluating Future Afforestation Potential In The Egyptian Red Sea, Rasha M. Abou Samra, Mansour Almazroui, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Mangrove forests are vital for ecosystem services and coastal management but face stressors from anthropogenic activities and climate change. This study estimates the extent and afforestation potential of mangroves along the Egyptian Red Sea coast from 1984 to 2022 using NDVI derived from Landsat-5 and Sentinel-2 data in Google Earth Engine. Aboveground biomass (AGB), belowground biomass (BGB), carbon (C) stock, and CO₂ sequestration potential were evaluated using Sentinel-2 and elevation data. Future afforestation suitability (2020–2050) under SSP2-4.5 and SSP5-8.5 scenarios was assessed with the MaxEnt model. Mangrove area increased from 0.95 km² in 1984 to 1.46 km^{2 …}

Soil-Based Emissions And Context-Specific Climate Change Planning To Support The United Nations (Un) Sustainable Development Goal (Sdg) On Climate Action: A Case Study Of Georgia (Usa), Davis G. Nelson

All Theses

Soil-based emissions from land conversions are often overlooked in climate planning. The objectives of this study were to use quantitative data on soil-based greenhouse gas (GHG) emissions for the state of Georgia (GA) (USA) to examine context-specific (temporal, biophysical, economic, and social) climate planning and legal options to deal with these emissions. Currently, 30% of the land in GA has experienced anthropogenic land degradation (LD) primarily due to agriculture (64%). All seven soil orders were subject to various degrees of anthropogenic LD. Increases in overall LD between 2001 and 2021 indicate a lack of land degradation neutrality (LDN) in GA. …

Forest Above-Ground Biomass Estimation Using Nasa Gedi Lidar Waveforms And Global Tree Allometry, Ian Grant

Theses and Dissertations

Above-ground forest biomass plays a crucial role in global carbon cycles, yet accurately estimating biomass at global scales remains challenging. This thesis addresses two key challenges in processing NASA’s Global Ecosystem Dynamics Investigation (GEDI) space-borne lidar data to estimate above-ground biomass density (AGBD): accounting for global variation in forest structure and developing robust physical interpretations of lidar returns. The first component of the thesis analyzes global patterns of tree allometry using the Tallo tree allometry dataset, examining relationships between tree dimensions across biomes, continents, and plant functional types. This analysis reveals consistent allometry across continents for some biomes (e.g., tropical …

Coffee Farmgate Price And Post-Harvest Processing In Honduras., Isaac Desouza

Theses and Dissertations--Agricultural Economics

Volatile commodity markets and changing climate expose coffee farmers to price and production risk. Proponents recommend specialty coffee as a strategy to combat price risk, because its unique attributes differentiate it from commodity coffee. Extrinsic and intrinsic attributes define specialty coffee and affect prices at many levels of the supply chain. Despite much work on extrinsic attributes, little is known about how intrinsic attributes relate to farmgate price. Post-harvest processing is itself an intrinsic trait and driver of coffee quality. In 2024 we surveyed 261 coffee farmers from La Paz, Honduras, to uncover relationships between capital, post-harvest processing, and farmgate …

An Assessment Of The California Logging Workforce, Kendra Jean Gerstenberg

Cal Poly Humboldt theses and projects

There is limited literature describing the capacity and capabilities of the logging workforce in California. This study examines the logging workforce in California to quantify the number of logging crews, assess demographic diversity, and evaluate capacity and capabilities. The target population was California Licensed Timber Operators (LTOs) who have the legal right to harvest timber. A survey was developed and distributed to LTOs on the CAL FIRE database. Surveys were also distributed at regional logging conferences or collected by phone. Data were analyzed using Statistical Package for the Social Sciences (SPSS) and emergent coding for follow-up interviews was conducted. There …

An Evaluation Of Fuel Model Accuracy And Multi-Scale Mitigation Strategies In The Wildland-Urban Interface Of Southern Humboldt County, Julia I. Cavalli

Cal Poly Humboldt theses and projects

Strategic placement of fuel treatments is critical for mitigating wildfire risk and reducing potential structure losses in wildland-urban interface (WUI) communities. As wildfire activity accelerates across the western United States, the need to identify high-impact fuel treatment locations grows increasingly urgent. Concurrently, housing development in the WUI is expanding, intensifying the exposure of homes and infrastructure to wildfire threats. In response, many communities are looking to mitigate the likelihood and severity of losses during wildfire events. The success of these efforts depends, in part, on robust data to support strategic placement of effective treatments that reduce fuel availability.

This study …

Modeling Forest Stewardship In Goukdi’N: An Assessment Of Carbon, Wildlife Habitat, And Fire Resilience In A University Forest, Benjamin Stock

Cal Poly Humboldt theses and projects

This thesis presents a forest management plan for Goukdi’n (also known as the Jacoby Creek Forest University Tract), a coast redwood–tanoak–Douglas-fir forest within the ancestral homelands of the Wiyot Tribe. This project addresses the need for a forest stewardship approach that supports ecological resilience, cultural values, and long-term forest health in a landscape shaped by industrial logging, fire exclusion, and decades of under-management. To evaluate potential management pathways, forest growth modeling was conducted using the USFS Forest Vegetation Simulator (FVS) to compare three management prescriptions focused on carbon storage, fire resilience, and structural heterogeneity and a no-action alternative. Model outputs …

Modelling The Hydrologic Impact Of Land Cover On Stormwater Detention Basins In Harris County, Tx, Kabita Sapkota

Electronic Theses and Dissertations

Harris County on the upper Gulf Coast in Southeast Texas is susceptible to both riverine and coastal flooding due to intense, short-duration thunderstorms, slow-moving frontal systems, and tropical hurricanes. Low-lying terrain, clay soils with poor drainage, high annual rainfall, and a widespread network of bayous and streams all contribute to frequent flooding. To reduce the impacts of urbanization and the loss of surface storage, the Harris County Flood Control District (HCFCD) built detention basins throughout the county to temporarily store stormwater runoff and release it slowly, lowering peak flows and preventing downstream flooding and erosion. These basins vary in land …

Collaborative Wildfire Governance Within The Southwest Idaho Wildfire Crisis Strategy Landscape: Survey Results 2025, Mahmood Muttaqee, Cody R. Evers, Lindsay K. Campbell, Max Nielsen-Pincus, Olivia Awbrey, Kathryn Hixson, Michelle Johnson, Erika Svendsen

Environmental Science and Management Faculty Publications and Presentations

Collaboration plays a critical role in wildfire risk mitigation efforts. This study examines collaborative wildfire governance networks within Southwest Idaho, a priority landscape designated in 2022 under the USDA Forest Service's Wildfire Crisis Strategy (WCS). Through survey data from 64 respondents, the Fueling Adaptation study aimed to identify the structure, capacity, and gaps in governance networks addressing wildfire risk in Southwest Idaho and understand how WCS investments have influenced wildfire management in the area. The findings reveal a growing governance network centered on the USDA Forest Service and the Idaho Department of Lands and supported by numerous non-governmental organizations and …

Assessing The Potential For Bigleaf Maple Syrup Production In Humboldt County, Ca, David A. Reinhart, Juan A. Ramos-Cool, Liam H. Richardson

Undergraduate Scholarship

The bigleaf maple (Acer macrophyllum, Pursh) is the largest maple of the Pacific Northwest. While it has generally been treated as a nuisance in timber harvesting operations, a small amount of research has been conducted on its sugaring ability in Oregon, Washington, and British Columbia. This research has yet to reach further south in the species' range. This study aims to help a California landowner understand which maple trees on his property produce the most maple sap, to gauge what environmental factors contribute to maple sap production, and to find greater implications for the production of maple sap …

Tree Crown Economics Of Broadleaf Deciduous Forests, Yiting Fan

Graduate Theses, Dissertations, and Problem Reports (ETD)

Tree crown architecture, a critical determinant of forest ecosystem processes such as photosynthesis, evapotranspiration, and spectral reflectance, is shaped by adaptive trade-offs in resource use and environmental responses. However, significant gaps remain in our understanding of how these traits vary across species, environmental gradients, and temporal scales. This dissertation addresses these gaps by employing remote sensing data across three interconnected studies. Together, these studies advance tree crown economic theory, highlighting how crown traits mediate trade-offs between light capture and water-use efficiency and how these traits influence forest responses to global change. Collectively, this dissertation offer insights for improving models that …

Machine Learning And Uass For Managing Autumn Olive (Elaeagnus Umbellata) On Reclaimed Surface Mines, Sean Michael Keane

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research introduces an innovative approach for managing autumn olive (Elaeagnus umbellata) on reclaimed surface mines through the integration of machine learning algorithms and unmanned aerial systems. The proliferation of autumn olive presents significant ecological challenges on disturbed landscapes, necessitating more efficient detection and control methods. This study evaluated Random Forest classification and deep learning approaches using the U-Net architecture for identifying autumn olive across four phenological stages using high-resolution imagery. The RGB U-Net model achieved F1-scores of 0.927, 0.912, and 0.871 for autumn olive detection during peak, late, and senescence stages respectively, outperforming both multispectral and vegetation …