Browsing by Author "Wei, Yu, committee member"

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Open Access
A revision of the genus Pachyrhinus Schoenherr 1823 (Coleoptera: Curculionidae) in the Nearctic region
(Colorado State University. Libraries, 2016) Benzel, Joseph, author; Kondratieff, Boris, advisor; Bright, Donald, committee member; Gilligan, Todd, committee member; Wei, Yu, committee member
This paper presents a revision of the North American species of the broad nosed weevil genus Pachyrhinus (Coleoptera: Curculionidae) Schönherr, 1823, which includes eight currently recognized species. Pachyrhinus is considered a minor pest of Pinus spp. Three species of Pachyrhinus are now recognized in North America: P. elegans (Couper, 1865), P. californicus (Horn, 1876), and P. cinereus (Casey, 1888). Pachyrhinus lateralis (Casey, 1888) and P. miscix (Fall, 1901) are considered synonyms of P. elegans. Pachyrhinus crassicornis (Casey, 1888) and P. albidus (Fall, 1901) are synonyms of P. cinereus. The previous synonymy of P. ferrugineus (Casey, 1888) with P. californicus was confirmed. The revision includes detailed images of diagnostic characters as well as scanning electron micrographs of scale morphology for all species.
Open Access
Burn scars and burnt s'mores: the impact of wildfire on camping demand in the years after a fire occurs
(Colorado State University. Libraries, 2021) Lee, Marissa, author; Suter, Jordan, advisor; Bayham, Jude, advisor; Flores, David, committee member; Wei, Yu, committee member
While the impacts of wildfire are widely felt and expected to increase in the coming years, less is known about the long-term impacts on recreation sites, specifically campgrounds. Wildfires inhibit the ability of individuals to recreate during wildfire season and subsequent years, due to unsafe conditions as the environment recovers. Changing wildfire suppression strategies may also affect households' ability and desire to recreate. At the same time, the number of individuals recreating is expected to increase in the coming years. As people continue to recreate and fires increase in intensity and frequency, we contribute to the discussion on wildfire's impact on recreation. We evaluate the impact of wildfire on U.S. Forest Service campgrounds in the western United States over the 15 years after a fire occurs. We construct a dataset of camping reservations from 2008-2017 and the percentage of burned area within 10 kilometer of a campground from fires occurring 1984 onward. We find that wildfires significantly decrease reservations up to six years after the fire occurs. The loss in campground utilization from decreases in reservations have negative impacts at the aggregate and local levels. A typical campground experiencing wildfire has 8% of its buffered area burned. Over the 10 years of reservation data that we evaluate, fires impact an average of 60 campgrounds annually. Summing across the affected campgrounds and fires that occur in a typical year suggests the USFS can expect to lose $50,109 in the years after fires occur at treated campgrounds, not accounting for substitution to other campgrounds. Further, we can expect a typical campground treated by fire to lose 59 campers in the six years after fire. We can expect the negative impact to increase as recreation and wildfire risk increase in the future. Depressed spending due to a reduction of campers can negatively impact communities that depend on the influx of visitors during the camping season. Reduced camping in these areas can potentially reduce employment, creating larger income gaps between urban and rural communities.
Open Access
Change in piñon-juniper woodland cover since Euro-American settlement: expansion versus contraction associated with soil properties
(Colorado State University. Libraries, 2019) Amme, Noah, author; Redmond, Miranda, advisor; Evangelista, Paul, committee member; Wei, Yu, committee member
Woodland and forest ecosystems across western North America have experienced increased density and expansion since the early 1900s, including in the widely distributed piñon-juniper vegetation type of the U.S. Southwest. Fire suppression and grazing are often cited as the main drivers of these historic changes and have led to extensive tree-reduction treatments across the region. However, much of the scientific literature on piñon-juniper expansion dates back only to the early 1900s, which is generally a half a century after Euro-American settlement. This study uses General Land Office (GLO) surveys to establish piñon-juniper woodland extent in the late 19th century at the incipient stages of Euro-American settlement in southeastern Colorado and compares this data with 2017 aerial imagery of woodland cover. We found substantial amounts of woodland contraction as well as expansion: approximately 61% of historically dense woodland is now savanna or open (treeless) whereas approximately 57% of historically open areas are now savannas or woodlands, although analyses at finer spatial scales suggest considerably more contraction relative to expansion. We assessed change in woodland cover and extent as a function of soil type, a dominant biophysical control, and found that the highest rates of expansion occurred upon shallow, rocky soil types with low soil available water capacity (AWC). These low soil AWC areas support little herbaceous vegetation and thus had less grazing pressure and were unlikely to carry frequent surface fires historically, suggesting that fire suppression and grazing were not the primary drivers of expansion. Meanwhile, the significant contractions in woodland extent occurred on deeper, upland soils with higher soil AWC, which support greater herbaceous cover and were likely where early settlement and treecutting was prevalent. Our results provide mixed support for the often widespread assumption of woodland expansion since Euro-American settlement and suggest that the expansion that has occurred in our study area is unlikely a result of past grazing or fire suppression. This paper uses important, underutilized sources of ecological data in order to more directly assess the earliest effects of Euro-American settlement on one of the U.S. Southwest's most prevalent and important vegetation types.
Open Access
Deep learning for short-term prediction of wildfire using geostationary satellite observations
(Colorado State University. Libraries, 2024) Saqer, Yousef, author; Chen, Haonan, advisor; Azimi-Sadjadi, Mahmood R., committee member; Wei, Yu, committee member
The aim of this thesis is to utilize the Geostationary Operational Environmental Satellite (GOES) data for predictions regarding the intensity and potential path of wildfires. Using GOES to identify wildfires and extracting data from those events to help train a deep learning model. Three fires were selected for training the deep learning model: the Sequoia, Calwood, and Maui fires. The GOES data of the fires was obtained from band 7 which operates in the Shortwave Window or 3.9μm wavelength, band 7 is able to capture hotspots which is beneficial for wildfire prediction. The radiance data from band 7 is pulled from an Amazon Web Service (AWS) and becomes part of a dataset of 2513 samples. The data is then stacked to form a time series of approximately two hours and converted into a compressed h5 file. The pipeline distributes the dataset by taking in twenty five minutes of input data and feeding four different models to predict seventy five minutes, one hundred minutes, and one hundred and twenty five minutes of data. The data is then fed into a deep learning model utilizing a model known as Self Attention Gated Recurrent Unit (SaGRU). The SaGRU is tested four times, once for predicting seventy five minutes, once for predicting one hundred minutes, and twice for one hundred and twenty five minutes. The models were then compared against each other regarding Mean Squared Error (MSE) and Mean Absolute Error (MAE) along with the Normalized Mean Squared Error (NME) and the Normalized Mean Absolute Error (NMAE). Each metric was taken along multiple thresholds comparing the performance when hotspots are present and when hotspots are absent. The resultant showed that regardless of the sequence length, there was minimal negative impact on early predictions, but as the predicted sequence increased significant loss could be seen on the later predicted frames.
Open Access
Ecosystem service valuation for wildfire mitigation prioritization decision-making in Colorado
(Colorado State University. Libraries, 2020) Chamberlain, James Luther, IV, author; Jones, Kelly, advisor; Beck, Scott, committee member; Wei, Yu, committee member
Wildfire presents a sizeable threat to ecosystem service values in Colorado and the Western U.S. If ecosystem services (ES), or the benefits that we obtain from natural ecosystems, are to be fully accounted for and protected in wildfire management, they must be properly valued. Monetary valuation has hitherto been the primary method for capturing the market and non-market value of an ES. Monetary valuation, while a powerful tool, is not applicable for all ES. Socio-cultural valuation, or non-monetary valuation, attempts to expand the scope of what ES can be valued and how they are valued for decision-makers. In this two-part thesis I explore both monetary and non-monetary valuation of ES in Colorado. Chapter One is an original research study that utilizes public participatory geospatial information systems (PPGIS) methods to capture socio-cultural ES values at risk of wildfire in the Big Thompson watershed. This study uses participatory data collection and spatial hotspot analysis, combining public ES perceptions and modeled wildfire risk data to locate potential priority zones for incorporating social values into wildfire management. Chapter Two is a cost-benefit analysis that I contributed to as part of a larger team that uses economic valuation to assess the values at risk from wildfire in the water catchments surrounding the Denver metropolitan area. In this study, the net economic benefits of wildfire mitigation investments carried out by the Forests to Faucets partnership were measured under different modeling assumptions. The research across these two chapters represents two different, but complimentary ways to incorporate a wide range of ES values into wildfire risk assessments.
Open Access
Evaluating and correcting sensor change artifacts in the SNOTEL temperature records, southern Rocky Mountains, Colorado
(Colorado State University. Libraries, 2017) Ma, Chenchen, author; Fassnacht, Steven, advisor; Kampf, Stephanie, advisor; Wei, Yu, committee member
In many high elevation mountain regions, documented warming rates have been greater than the global surface average. These warming rates directly affect the snowpack, runoff, ecosystems, agriculture and species that rely on a high elevation snowpack. Temperature records from the snow telemetry (SNOTEL) network across the Southern Rocky Mountains in the western United States have high warming rates, which may have been affected by systematic inhomogeneities in the temperature data caused by sensor changes. This study evaluates the maximum, average, and minimum temperature trends from 68 long-term SNOTEL stations across Colorado for the period from the 1980s through 2015 using the non-parametric Mann-Kendall/Theil-Sen's analyses before and after the temperature records were corrected for the sensor-caused inhomogeneities. Three homogenization methods were tested using a simple temperature index snow accumulation and melt model. Results show that the significant warming trends found in the original datasets, especially in minimum temperature (average increase of 1.2 °C per decade), decreased (to an average of 0.5 °C per decade) after homogenization. Step-like shifts in temperature datasets were observed in SNOTEL temperature records at the time of temperature sensor change, which created a discontinuity in the temperature dataset. The temperature-index snow model simulated snow water equivalent (SWE) well (more than 93% of the calibrated stations within the "good" and "very good" performance category for all three statistical-evaluation periods based on the Nash-Sutcliffe coefficient of efficiency, NSCE) using the new temperature sensor dataset. However, these models did not perform as well when using the original (pre-sensor change) and homogenized temperatures, with 23% of stations for the original temperature data and 44-69% of stations for two homogenized temperature datasets within the "good" and "very good"temperature data, but they did not fully correct for the effects of sensor change on the temperature records. The NSCE and bias statistics from SWE modeling using the original and homogenized datasets suggest that the homogenization methods evaluated in this study are applicable for many of the SNOTEL stations in Colorado but not all, and need to be applied with caution. Potential users of temperature products from the SNOTEL network should also be very careful when choosing time periods for future climate change research and assessments. More long-term climate monitoring stations should be installed in high elevation mountain regions to document and investigate elevation-dependent warming.
Open Access
Evaluating the efficiency, equity, and effectiveness of wildfire suppression strategy using the microeconomic toolkit
(Colorado State University. Libraries, 2024) Bryan, Calvin R., author; Bayham, Jude, advisor; Manning, Dale T., committee member; Goemans, Chris, committee member; Wei, Yu, committee member
Most economic research related to wildfires focuses on their impact on people and populations. In my dissertation, I use economic tools to evaluate the efficiency and equity of wildfire suppression strategy. In the first chapter, I investigate whether socioeconomic factors of a community (income, race, age, etc.) are correlated with allocations of suppression effort. I use spatial data on retardant drops from large airtankers (LATs) and demographic information from the Census Bureau to find that communities threatened by wildfire with fewer minority residents, but more low-income residents, are more likely to receive LAT drops. I then find that socioeconomic factors aren't correlated with the decision to use LATs in suppression after conditioning on biophysical factors like fuels and burn probability. In my second chapter, I study whether the media's attention to wildfire influences suppression strategy. I instrument for the effect of media attention using the incidence of catastrophic events that would distract the media to find that media scrutiny of a wildfire has no tangible effect on the decision to use aviation on a fire. Finally, most economic research on wildfire suppression strategy has focused on the costs; little exists on its benefits. I use causal inference methods leveraging satellite data on wildfire growth and intensity, along with the spatial data on aerial suppression effort mentioned previously, to find that large airtankers are effective at limiting the physical extent of wildfire's spread, reducing the intensity of flames as it grows, and slows its spread.
Open Access
Internalizing the social costs of smoke emissions into strategic fuels planning models
(Colorado State University. Libraries, 2016) Rossi, David J., author; Rideout, Douglas, advisor; Wei, Yu, committee member; Kling, Robert, committee member; Kirsch, Andy, committee member
Emissions of fine particulate matter from prescribed burns are a growing concern for wildland fire managers. Stringent air quality regulations and community discern over the emissions from prescribed fire smoke often severely restrict the ability to implement restorative and precautionary fuels treatments. While some extent of emissions are unavoidable, strategic planning can help reduce their impacts. Estimating the cost of smoke and incorporating it into landscape level fire planning may reduce the burden on wildland fire officials confronted with a complex set of choices and constraints. Currently, no decision-support systems are available for strategically incorporating the cost of smoke in fire planning at the landscape level. A decision model is developed to address this void by estimating the value of fire and fuels management at the landscape level by including the cost of smoke in cellular level estimates social returns. By working with locally defined emission standards and translating them into a cost per unit of smoke impact, I was able to internalize the external impact of smoke emissions into a strategic fuels planning model by reprioritizing the optimal selection of landscape grid cells to target for prescribed fire investments. This has the potential to aid the fire planner in analyzing trade-offs for prescribed fire management. In a case study at King's Canyon National Park, emissions standards are used to estimate a relative unit cost of impact (per unit of emissions). The unit cost is subtracted from cellular estimates of marginal social returns to re-prioritize the spatial design of landscape scale fuel treatments.
Open Access
Methods for incorporating population dynamics and decision theory in cackling goose management
(Colorado State University. Libraries, 2016) Williams, Perry J., author; Kendall, William L., advisor; Hooten, Mevin B., committee member; Schmutz, Joel A., committee member; Wei, Yu, committee member
To view the abstract, please see the full text of the document.
Open Access
Modeling burn probability patterns for large fires
(Colorado State University. Libraries, 2013) Ziesler, Pamela Sue, author; Rideout, Douglas B., advisor; Reich, Robin, committee member; Wei, Yu, committee member; Kling, Robert, committee member
I present a set of techniques for modeling burn probability patterns for large wildland fires. The resulting models address an important goal of a large fire risk analysis by estimating large fire burn probabilities. The intent was to develop models of burn probability using data that are widely available or easily calculated and that achieve acceptable predictive performance. Two models were successfully estimated using variables that may be extracted directly or easily calculated from standard GIS layers and other sources and they had `good' predictive ability with AUCs of 0.81 and 0.83. The ultimate intended use for the models is strategic program planning when information about future fire weather and event durations is unavailable and estimates of the average probabilistic shape and extent of large fires on a landscape are needed. Four primary objectives were to: estimate models from historical fire data that are appropriate for strategic program planning, incorporate the effect of barriers to the spread of fires across a landscape, account for the average effect of weather streams and management actions on large fires without using detailed information on weather, fire duration or management tactics, and investigate methods for addressing the spreading, connected nature of large fires on a landscape within a regression model. Models like these can provide finer detail than most landscape-wide models of burn probability and they have advantages over simulation methods because they do not require multiple runs of spread simulation models or information on fire duration or hourly weather events. To model burn probability patterns, I organized historical fire data from Yellowstone National Park, U.S.A. into a set of grids; one grid per fire. I incorporated explanatory variables such as fuel type, topography data and fire season indicators and I captured some spatial relationships through the use of distance, direction and other geometric variables. The data set observations are highly correlated and I investigated two approaches to account for and incorporate this correlation: one employed an autoregressive covariance structure and the other utilized a variable to account for the effects that neighboring cells may have on average burn probability. The two approaches yielded models with estimated coefficients that are consistent with fire behavior theory and that reflect how fires usually behave on the study site landscape. Both models compared well with the predictive ability of other fire probability models in the literature. Based on their predictive performance, this was a successful first attempt at addressing the research objectives and for estimating regression models to predict burn probability patterns for large fires.
Open Access
Optimizing brush pile disposal on western USFS land
(Colorado State University. Libraries, 2024) Axlund, Caleb E., author; Suter, Jordan, advisor; McCollum, Daniel W., committee member; Bayham, Jude, committee member; Wei, Yu, committee member
This research evaluates the social costs of burning piled biomass and the economic trade-offs of alternative removal strategies. Timber harvesting and forest thinning often leave behind branches and other tree parts, which are piled and burned, resulting in what are known as brush or slash piles. These piles pose significant costs to nearby communities and have global environmental impacts, including greenhouse gas (GHG) emissions and reduced local air quality (Wiedinmyer et al., 2006; Ganguly et al., 2018; Pierobon et al., 2022). The United States Forest Service (USFS) is testing a new device called the 'Charboss' that removes excess brush and repurposes it as biochar, a substance with potential environmental and agricultural benefits. Analyzing the external social costs of burning brush piles is crucial for assessing the economic viability of future brush removal strategies. By using social costs as a gauge, this study employs an optimization model to maximize benefits while minimizing the associated costs of this new forest management technology. Private investment and social planners' perspectives are considered when determining optimal deployment strategies. This study examines various scenarios for deploying the USFS device cost-effectively and concludes that, under certain assumptions, it can significantly benefit local communities and global environmental health.
Open Access
Sandhill crane population monitoring, modeling, and harvest decision making
(Colorado State University. Libraries, 2015) Gerber, Brian Daniel, author; Kendall, William L., advisor; Wei, Yu, committee member; Hooten, Mevin B., committee member; Doherty, Paul D., committee member
To view the abstract, please see the full text of the document.
Open Access
Simulating cut to length forest treatment effects on fire behavior over steep slopes
(Colorado State University. Libraries, 2023) Pittman, Kyle Tait, author; Jathar, Shantanu, advisor; Hoffman, Chad, advisor; Linn, Rod, committee member; Windom, Bret, committee member; Wei, Yu, committee member
The increase of wildfire size and behavior in many western U.S. forests is due to increased fuel loads resulting from the past century's fire suppression, logging, and grazing policies of the 20th century, along with compounding climactic changes including increased drought and temperatures. Fuel hazard treatments are the key land management tool used to reduce fire intensity and severity however these treatments are often not possible on steep terrain of over 30% slope. Cable tethered cut to length machinery opens new avenues for managers to treat forests in steep slopes, but there is limited data on how effective the treatments will be. I conducted a numerical experiment using the wildfire model, FIRETEC, coupled with the atmospheric dynamics model, HIGRAD, to understand the complex interactions of wind, topography, and fire behaviors of two cut to length forest treatments on slopes of up to 60%. Results show that treatments can effectively reduce some fire behaviors such as heat release and canopy consumption when compared to untreated forests on slopes. However, increased sub canopy wind penetration along the slopes following treatments results in marginal fire severity reduction regarding biomass consumption and variable results on rates of spread. The results of these numerical experiments indicate that CTL treatment can effectively reduce some fire behavior and severity, however the effects were marginal and additional research is needed to better understand treatment's effects.
Open Access
Spatial modeling of site productivity and plant species diversity using remote sensing and geographical information system
(Colorado State University. Libraries, 2011) Mohamed, Adel Ahmed Hassan, author; Reich, Robin M., advisor; Khosla, Rajiv, advisor; Andales, Allan, committee member; Wei, Yu, committee member
The primary objective of this study was to describe the variability in site productivity of the diverse forests found in the state of Jalisco, Mexico. This information is fundamental for the management and sustainability of the species-rich forests in the state. The study also contributes to developing conservation-management program for the plant species diversity in Elba protected area in Egypt. The objective of chapter 1 was to develop site productivity index (SPI) curves for eight major forest types in the state of Jalisco, Mexico, using the height-diameter relationship of the dominant trees. Using permanent plot data, selected height-diameter functions were evaluated for their predictive performance within each of the major forest types. An important finding of this study was that a simple linear model could be used to describe the height-diameter relationship of the dominant trees in all of the major forest types considered in this study. SPI varied significantly among forest types, which are largely determined by the trends in temperature and precipitation. SPI decreased with increasing temperature and increased with increasing precipitation. The height-diameter relationship of the dominant trees was independent of stand density, and the more productive sites are able to sustain higher levels of basal area and volume, than the less productive sites. Trees on more productive sites had less taper than trees on less productive sites; and stand density did not influence the form or taper of the dominant trees. Chapter 2 evaluates methods to model the spatial distribution of site productivity in eight major forest types found in the state of Jalisco, Mexico. A site productivity index (SPI) based on the height-diameter relationship of dominant trees was used to estimate the site productivity of 818 forests plots located throughout the state. A combination of regression analysis and a tree-based stratified design was used to describe the relationship between SPI and environmental variables which included soil attributes (pH, sand, and silt), topography (elevation, aspect, and slope), and climate (temperature and precipitation). The final model explained 59% of the observed variability in SPI. GIS layers representing SPI for each forest type, along with associated estimates of the prediction variance are developed. Chapter 3 characterizes plant species richness on four major transects in Elba protected area in Egypt. Species data recorded on 63 sample plots were used to characterize the plant species richness by species group (trees, shrubs and subshrubs). Poisson regression was used to identify explanatory variables for estimating species richness of each species group. Important variables included the location of the line transect (A, B, C, and D), soil texture (gravel, sand, silt and clay), pH, and elevation. The final model explained 23%, 58%, and 52% in the variability of species richness for shrubs, subshrubs, and trees, respectively. The results of the study will contribute to the development of an inventory and monitoring program aimed at the conservation and management of species diversity in Elba protected area of Egypt.
Open Access
Time-since-death and its effect on wood from beetle-killed Engelmann spruce in southwest Colorado
(Colorado State University. Libraries, 2016) Vaughan, Damon, author; Mackes, Kurt, advisor; Wei, Yu, committee member; Rastall, Patrick, committee member
Spruce beetles (Dendroctonus rufipennis) have caused extensive mortality on 1.5 million acres in Colorado during the current epidemic. There is considerable interest in harvesting treatments aimed at removing dead trees for reasons of fire risk, watershed health, and human dimensions. The byproducts from these treatments can either be viewed as a difficult and costly disposal problem or an opportunity for the recovery of forest products. However, a major barrier to the latter option is the lack of knowledge about how the material changes with time standing dead. Ten plots were selected on the Rio Grande National Forest (RGNF), from which 86 Engelmann spruce (Picea engelmannii) trees were felled and sampled. Tree rings were analyzed to determine Time-Since-Death (TSD) on all study trees. TSD and other variables such as diameter, elevation, and bark retention were used to develop models predicting the deterioration rate from beetle mortality (seasoning check, heart rot, and sap rot). In a separate mill study, eleven trees from the RGNF were milled to dimensional lumber to determine the lumber tally, prevalence of blue stain, and lumber grade breakdown. Checking was found to be most strongly correlated with tree diameter, and the effect of TSD was most pronounced at larger diameters. Higher elevations and increased bark retention served to reduce or slow checking. Sap rot was found to increase with TSD, but heart rot was not. Many study trees had moisture contents suitable for the development of rot. In the mill study, older dead trees produced a lower percentage of select structural lumber than control trees. Net Scribner was a poor predictor of lumber tally; gross Scribner and product potential cubic were more accurate. Results from this study may help land managers maximize sawtimber recovery by prioritizing treatment areas. Information such as tree diameter, TSD, and elevation will allow foresters to better differentiate stands that have already been subject to severe deterioration from those that will in short order.