Browsing by Author "Evangelista, Paul, committee member"
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Item Open Access A study of low cloud climate feedbacks using a generalized higher-order closure subgrid model(Colorado State University. Libraries, 2013) Firl, Grant J., author; Randall, David A., advisor; Denning, Scott, committee member; Johnson, Richard, committee member; Evangelista, Paul, committee memberOne of the biggest uncertainties in projections of future climate is whether and how low cloudiness will change and whether that change will feed back on the climate system. Much of the uncertainty revolves around the difference in scales between the processes that govern low cloudiness and the processes that can be resolved in climate models, a fact that relegates shallow convection to the parameterization realm with varying levels of success. A new subgrid-scale parameterization, named THOR, has been developed in an effort to improve the representation of low cloudiness via parameterization in climate models. THOR uses the higher-order closure approach to determine the statistics describing subgrid-scale processes. These statistics are used to determine a trivariate double-Gaussian PDF among vertical velocity, ice-liquid water potential temperature, and total water specific humidity. With this information, one can diagnose what portion of the grid cell is cloudy, subgrid-scale cloud water content, and subgrid-scale vertical cloud water flux. In addition, samples are drawn from the trivariate PDF in order to drive the microphysics and radiation schemes. Although schemes similar to THOR have been developed over the past decade, THOR includes several novel concepts, like the generalization of the saturation curve to include condensation over both ice and liquid substrates, the determination of the PDF parameters from the given turbulence statistics, the introduction of a stochastic parcel entrainment process for the turbulence length scale, and a sub-column approach for calculating radiative transfer using the PDF. The new model is validated by simulating five test cases spanning a wide range of boundary layer cloud types, from stratocumulus to cumulus and the transition between the two. The results are compared to an ensemble of LES models running the same cases, with particular attention paid to turbulence statistics and cloud structure. For all cloud types tested, THOR produces results that are generally within the range of LES results, indicating that the single-column THOR is able to reproduce the gross characteristics of boundary layer clouds nearly as well as three-dimensional LES. Sensitivity to vertical grid spacing, diagnostic/prognostic third- order moments, choice of turbulence length scale entrainment process, and whether or not PDF sampling is used to drive the microphysics and radiation schemes is assessed for all test cases. Simulation of the cumulus regime was degraded when vertical grid spacing exceeded 200 m, when more third-order moments were predicted, when higher parcel entrainment rates were assumed, and when PDF sampling for the microphysics scheme was omitted. Simulation of stratocumulus was degraded with grid spacing larger than 100 m, when PDF sampling for microphysics was omitted, and when PDF sampling for radiation was included. Lastly, THOR is used to study low cloud climate feedbacks in the northeastern Pacific Ocean in the context of the CGILS project. Initial conditions and forcings are supplied at 13 points along the GPCI cross-section that spans from the ITCZ northeast to the coast of California transecting regions of shallow cumuli and stratocumuli, for both the current climate and a climate with a +2K SST perturbation. A change in net cloud radiative forcing of 0-8 W/m2 was simulated along the cross-section for the perturbed climate, representing neutral to weak positive feedback. The responsible mechanism appeared to be increased boundary layer entrainment and stratocumulus decoupling leading to reduced maximum cloud cover in the cumulus regime and reduced liquid water path in the stratocumulus regime.Item Open Access Assessing plant diversity to enable continental-scale monitoring and forecasting(Colorado State University. Libraries, 2017) Barnett, David T., author; Stohlgren, Thomas, advisor; Evangelista, Paul, committee member; Martin, Patrick, committee member; Morisette, Jeffery, committee memberThe Earth System is dynamic. It influences and is influenced by physical, chemical, and geological processes, but it may be the least understood of these systems. The biosphere interacts with the physical Earth System on diurnal and seasonal scales, and over decades and centuries. The living system interacts with itself and other systems at a variety of scales. At large, continental scales, exchange between biotic elements and the atmosphere and surface water control climate, hydrology, and productivity. At small scales plants interact with each other and exchange energy and matter with the atmosphere and soil. Understanding the Earth System requires comparable methods and analysis across scales and over decades. This is particularly true given that the Earth System is increasingly facing changes in climate and disturbances, the redistribution of species, and land-use change. The National Ecological Observatory Network (NEON) is a platform designed to enable an understanding of the causes and consequences of change on ecology. By simultaneously measuring the drivers of change and ecological responses – organisms, atmosphere, and soil – it will enable the ecological community to better understand the nature of interactions and support forecasts of future states. This work describes questions, analysis, and testing for the development of the plant diversity observations to be made by NEON. Models and forecasts require information from each of the sites that comprise NEON. The study design that directs spatial distribution of plots for sampling diversity relies on a random design that is stratified by land cover with replication intended to detect differences in trends between sites over thirty years. A classic power analysis that relied on prototype data and satellite imagery to parameterize temporal and spatial variability indicated that a sample size of 30 plots per site would sufficiently differentiate trends across sites. Results from multiple sites collecting data according to the design demonstrated that patterns of spatial variation were higher than expected and that a larger sample size would be required to satisfy the specified test. Plant diversity data collected according to the design also must be comparable within and across sites. Variations in level of effort challenge the statistical comparison of plant species richness data. Comparing richness where the coverage - as defined by slope of the species accumulation curve – provides a statistically rigorous and biologically meaningful point of comparison. To sample such that species accumulation curves terminated at a slope of seven, plots were allocated proportional to the square-root of the strata area within each site. When comparing plant species richness data collected according to the proposed allocation from six it was found that only 30% of the within-site species accumulation curves terminated at a slope of seven, and only 33% of the species accumulation curves at the scale of the site terminated at a slope of seven. Ensuring the creation of a design that generates data capable of describing extant status and future states will require iteration and continued evaluation. A method for ensuring plots are located such that change will be detected was evaluated by generating species distribution models of two invasive plant species, Pennisetum clandestinum and Holcus lanatus as predicted by topography and extant and future climate data. The models suggested that suitable habitat for Pennisetum clandestinum may decrease in extent while suitable habitat for Holcus lanatus may expand at the site over time. To adequately document and improve understanding of the causes and consequence of habitat expansion, additional sampling plots could be placed in areas vulnerable to by Holcus lanatus in the future. Similarly, any resources available for the control of plant species invasion may be better expended on Holcus lanatus. This is one example of the many uses of NEON data to assist land managers.Item Open Access Assessment of Gullele Botanic Gardens conservation strategy in Addis Ababa, Ethiopia research from the Peace Corps Masters International Progam(Colorado State University. Libraries, 2013) Reeder, Carl M., author; Laituri, Melinda, advisor; Evangelista, Paul, committee member; Daivs, Jessica, committee member; Sturtevant, Robert, committee memberMonitoring of current and future conditions is critical for a conservation area to quantify results and remain competitive against alternative land uses. This study aims to monitor and evaluate the objectives of the Gullele Botanic Gardens (GBG) in Addis Ababa, Ethiopia. The following report advances the understanding of existing understory and tree species in GBG and aims to uncover various attributes of the conservation forest. To provide a baseline data-set for future research and management practices, this report focused on species composition and carbon stock analysis of the area. Species-specific allometric equations to estimate above-ground biomass for Juniperus procera and Eucalyptus globulus are applied in this study to test the restoration strategy and strength of applied allometry to estimate carbon stock of the conservation area. The equations and carbon stock of the forest were evaluated with the following hypothesis: Removal of E. globulus of greater than 35cm DBH would impact the carbon storage (Mg ha-1) significantly as compared to the overall estimate. Conservative estimates found E. globulus accounted for 68% of the total carbon. Results of both the carbon stock and species composition analyses were used to delineate forest stands with a Geographic Information System. Ultimately, the strategy of GBG to restore native stand structure and understory species to the area will be advanced by the organization of forest stands delineated by this study.Item 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 memberWoodland 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.Item Open Access Characterizing distributions and drivers of emergent aquatic vegetation in Minnesota(Colorado State University. Libraries, 2020) LaRoe, Jillian, author; Vogeler, Jody C., advisor; Tinkham, Wade, committee member; Evangelista, Paul, committee memberThe emergent aquatic vegetation (EAV) communities across the lakes of Minnesota serve critical functions within ecosystems by providing habitat and forage for native waterfowl and fish species, moderating water chemistry, and serving as a cultural and economic resource. Communities of EAV are changing dramatically in response to alterations in hydrologic flow regimes, nutrient availability, biological homogenization, and near-shore development. To address the conservation of these communities at a spatial scale relevant for landscape management, the changes need to be evaluated at local and regional scales. Previous efforts to map and monitor EAV have utilized field surveys, aerial imagery, multispectral imagery, and synthetic aperture radar (SAR). However, it is difficult to apply the findings of previous studies to broader spatial scales because they lack field surveys, clear or repeatable methodologies, rigorous validation, and/or applying methods to broad spatial extents, all of which are all necessary for providing direct implications for landscape level management. The first chapter of this thesis aimed to overcome these challenges and create statewide maps of EAV in Minnesota at a spatial resolution relevant to landscape management at both broad and local scales. We paired detailed field surveys of EAV communities with Sentinel-1 SAR and Sentinel-2 Multispectral Imager to create annual maps of EAV across the lakes of Minnesota at a 10 m spatial resolution in 2017 and 2018. We created two random forest models, a species model predicting general classes of EAV and a water model identifying open water regions across hydrologic features in Minnesota. We validated both classification models using withheld field sample locations to measure overall accuracy as well as individual class user's and producer's accuracies. The species and water map predictions were combined into a final map representing water and EAV classes each year. We also evaluated each map by the area-based percentage of overlap between model predictions and field surveys which ranged from 54.5 to 90.1% agreement. The 2017 map was further evaluated using an area-based weighted probability with an overall accuracy of 89.9% (±0.7%). The methods and promising results highlighted by this study set the stage for subsequent analyses at broader spatial scales to quantify temporal shifts or trends in EAV communities. The combination of these diverse and detailed datasets provides methods for generating annual maps of EAV distribution across Minnesota, and ultimately provide a tool to support landscape-scale conservation efforts of EAV communities in Minnesota. The second chapter investigated the influence of systemic drivers related to the decline of northern wild rice (Zizania palustris L.) over the last century. Wild rice is an environmental indicator species that is sensitive to hydrologic changes and disturbances and serves an essential role in ecological, cultural, and economic systems in Minnesota. Due to the previous lack of comprehensive information regarding its extent and distribution, previous efforts to study its decline have been limited to small regions or small samples of lakes across the state. We utilized 2018 presence maps of wild rice from the first chapter and summarized wild rice cover across 366 lakes. Then, we employed a suite of spatial, hydrological, ecological, and environmental variables summarized at a variety of spatial scales within a three-step modeling framework to select the most significant drivers of wild rice cover, explore interactions between drivers, and account for inherent spatial autocorrelation in the datasets. A final spatial lag model revealed that dispersal and population connectivity had the strongest relationships with wild rice cover on each lake. While further exploration may better quantify this relationship, land managers should consider the degree of connectivity between wild rice lakes and their spatial configuration on the landscape during conservation planning to maximize population resilience. Our results suggest that it may be more suitable to approach populations as connected habitat regions, in contrast to the more widely accepted notion that wild rice lakes are self-contained or independent populations.Item Open Access Evalutating the effects of wildfire in piñon-juniper woodlands on bighorn sheep habitat and vegetation composition(Colorado State University. Libraries, 2014) Wilson, Benjamin R., author; Boone, Randall, advisor; Evangelista, Paul, committee member; Wittemyer, George, committee memberI evaluated the efficacy of using woodland fire to alter vegetation composition in a manner that augments desert bighorn sheep (Ovis canadensis nelsoni) habitat in the Black Ridge Canyons Wilderness Area in western Colorado. I applied generalized linear mixed models to estimate pre-fire ewe habitat selection and then simulated a hypothetical widespread fire to spatially predict where fire would be most beneficial in expanding habitat. I found that ewes were avoiding habitats with high woodland canopy cover, the habitat most likely to be removed by fire. Given the removal of all woodlands, it is likely that habitat expansion would occur in areas near topographic escape terrain. Coupled with this analysis, I addressed concerns regarding potential negative effects of fire in this system by comparing vegetation composition of unburned habitats to burned habitats that were treated with a native seed mixture. I found that foliar cover in burned areas was on average two times greater than in unburned areas and that post-fire seeding efforts likely allowed for these differences to be proportionally similar between native and non-native grass species. My results provide an encompassing view on the effects of fire for a common management situation in which both land and wildlife values are of mutual interest.Item Open Access Gap analysis of India's Western Ghats protected area network: insights from new and understudied endemic species' distributions(Colorado State University. Libraries, 2018) Miltenberger, Oliver, author; Leisz, Stephen, advisor; Evangelista, Paul, committee member; Pejchar, Liba, committee memberProtected areas are a crucial tool to meet conservation goals of the 21st century, especially in biodiverse regions threatened by land use change. This study makes use of nine years of field data collected on over 300 understudied plants and amphibians endemic to the UNESCO-recognized biodiversity hotspot of the Western Ghats of India to produce a gap analysis of its protected area network. The gap analysis updates previous analyses to reassess network coverage and to improve biodiversity distribution estimates. Software for Assisted Habitat Modeling (SAHM) queries possible species distribution models (SDMs) and predictor variables for thirty-five of these species sub-grouped by range strategies. This generates parsimonious sets of predictor variables as well as performance assessments of SDMs, which then populate batch-run distribution Maximum Entropy models (Maxent). These distributions are overlain in various ensembles to produce clade and biodiversity specific insights about high and low-occurrences areas for these species. Hotspot assessments of the region are generated using ensembled distributions and are compared to the current protected area network to identify gaps in coverage for high-occurrences of these species' distributions. Most high species co-occurrences for both amphibian and plant distributions are covered by the network with the exception of three regions for amphibians and six regions for plants, two of which overlap between clades. Previous studies largely or exclusively used secondary-data for their assessments while the majority of species in this study have never been modeled or included in gap analyses. This study's assessment adds new ecological information to individual species and novel contributions to conservation planning in a threatened biodiversity hotspot. This study recommends inclusion of the seven identified high-occurrences areas in future conservation efforts for the Western Ghats and prioritization of the two areas identified as gaps in protection for both clades.Item Open Access High efficiency thermoelectric devices fabricated using quantum well confinement techniques(Colorado State University. Libraries, 2011) Jurgensmeyer, Austin Lee, author; Williams, John, advisor; Bradley, Thomas, advisor; Evangelista, Paul, committee memberExperimental results are presented of thermoelectric materials, specifically two-dimensional quantum well confinement structures, formed by ion beam sputter deposition methods. Applications of these thermoelectric devices include nearly any system that generates heat including waste heat. The targeted applications of this research include harvesting of waste heat from stand-alone generator systems and automobiles. Thermoelectric generator modules based on an in-plane orientation of nano-scale, thin-film, superlattices have demonstrated very high performance and are appropriate for a wide range of waste heat recovery applications. In this project, the first, fast, ion-beam-based deposition process was developed for producing Si/SiC (n-type) and B4C/B9C (p-type) superlattices. The deposition process uses low-cost powder targets, a simplified substrate holder with embedded heater, a QCM deposition rate monitor, and stepper-motor-controlled masks. Deposition times for individual layers are shown to be significantly shorter than those achieved in magnetron-based systems. As an example of the speed of the process, a 10-nm thick Si layer can be deposited in as little as 20 sec while a SiC layer can be deposited in less than 100 sec. Electrical resistivities, thermal conductivities and Seebeck coefficients are reported for the deposited films as well as their respective non-dimensional figures of merit (zT). Figures of merit (zT) approaching 20 at modest temperatures of ~600 K were observed. These measurements are made in-plane where enhanced Seebeck values and reduced electrical resistivities have also been reported in the literature. A method for directly measuring thermal conductivity in the plane of the superlattice is described that uses MEMs-based SiN cantilevers. Results are presented for various deposition variables, including film thickness, temperature, deposition energy, and material. Scanning white light interferometry (SWLI) and scanning electron microscopy (SEM) were used to characterize film thickness. In addition to the experimental effort, an analysis was performed to predict the performance of a thermoelectric module fabricated with the superlattice films deposited on ceramic substrates. Thermal efficiencies approaching 15% are predicted for modest cold and hot side temperatures. Thermal conduction through the substrate was found to be the largest factor limiting the performance of the modeled thermoelectric modules.Item Open Access Relating severity of a mountain pine beetle outbreak to forest management history(Colorado State University. Libraries, 2014) Vorster, Anthony, author; Stohlgren, Thomas, advisor; Kumar, Sunil, advisor; Cheng, Tony, committee member; Evangelista, Paul, committee memberThe availability of remote sensing imagery before, during, and after the recent mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic in the southern Rocky Mountains presents exciting opportunities for assessing the current state of forests and how forest management in previous decades influenced outbreak severity across the landscape. I mapped outbreak severity at a 30-m resolution using integrative spatial modeling. I predicted that: 1) outbreak severity can be accurately predicted and mapped at Fraser Experimental Forest, Colorado using stand characteristics with a boosted regression tree model, Landsat imagery, geographic information system (GIS) data, and field data; and 2) forest stands that were unmanaged since the 1950s will have higher outbreak severity compared to stands that were treated since the 1950s. Outbreak severity, measured by the ratio of dead lodgepole pine (Pinus contorta) basal area to the basal area of all trees, was mapped across Fraser Experimental Forest with a cross-validation correlation of 0.86 and a Spearman correlation with independently observed values of 0.64. The outbreak severity at stands harvested between 1954 and 1985 was lower than comparable uncut stands. Lessons learned about past treatments will inform forest management for future mountain pine beetle outbreaks.Item Open Access Social-ecological models for knowledge co-production and learning in collaborative environmental management(Colorado State University. Libraries, 2020) Steger, Cara Elizabeth, author; Klein, Julia A., advisor; Boone, Randall B., committee member; Evangelista, Paul, committee member; Fernández-Giménez, Maria, committee memberIn a rapidly changing world, human communities struggle to address complex environmental problems that are multidimensional, without clear definitions or solutions, and that require collaboration among actors with potentially conflicting objectives. Collaborative approaches to environmental management engage diverse actors who work together to produce shared understanding and novel solutions to these challenging problems. Collaborative approaches encourage participants to learn from each other and reflect on that learning, which can improve their collective ability to cope with variability brought on by global environmental change. Modeling is increasingly used by academics and development practitioners to encourage and inform collaborative environmental management, yet there has been insufficient attention paid to how collaborative modeling processes interact with the social and cultural factors that shape environmental outcomes. This dissertation engages at the intersection of science and culture to examine the use of social-ecological models in the context of collaborative environmental management. First, I present a snapshot of current barriers and best practices in collaborative or transdisciplinary environmental work, using a global survey to inform a conceptual model of knowledge co-production and learning. I then apply this conceptual model in a case study of a community-managed Afroalpine grassland in the Ethiopian highlands known as Guassa, using a combination of cognitive, geospatial, and simulation modeling. Specifically, I bring together insights from local knowledge and remote sensing analyses to present a more holistic understanding of social and biophysical change in this area and to situate the environmental consequences in relation to locally-defined ecosystem services. I then use individual and small group mental modeling to compare how different types of people involved in managing Guassa conceptualize the key components of this social-ecological system. I describe a co-designed agent-based model of shrub encroachment into the Guassa grassland, using it to improve our understanding of the system and to explore potential management interventions. I assess the learning experienced by participants in these mental modeling and agent-based modeling exercises to advance our understanding of the kinds of learning that occur throughout a collaborative modeling process. This work informs the design and application of social-ecological models to contribute to more equitable and sustainable collaborative environmental management.Item Open Access Spatial component for the decision support systems of Colorado's forest products industry - industry cluster analysis on sawmills in northern Colorado(Colorado State University. Libraries, 2016) Richardson, Emily Anne, author; Mackes, Kurt, advisor; Wei, Yu, advisor; Coleman, Robert, committee member; Evangelista, Paul, committee memberThe Colorado State Forest Service (CSFS) has received numerous requests for a resource that provides a consolidated, up-to-date spatial representation of facilities and contractors associated with Colorado's forest products industry (CFPI). The overall purpose of this project was to provide methods for creating the spatial component to be used in the decision support systems (DSS) of CFPI. The spatial component provides visual aids and decision-making assistance in order to locate potential biomass sources, plan future forest management, estimate transportation costs, understand the accessibility of a potential treatment site, understand which processing facilities are located in closest proximity to treatment sites to maximize efficiency, find prime facility candidates for woody biomass conversion and more. The first part of this study provides methods for obtaining the necessary data and creating a series of maps to be used in the tool. State-wide trends and relationships discovered by combining various map layers are discussed. The second part of the study demonstrates the potential and utility of the decision-making tool by performing an industry cluster analysis that investigated spatial interactions of sawmills and their feedstock in northern Colorado. Variables included in the industry cluster analysis were: sawmill capacity (annual production volume in board feet), species being processed, feedstock ownership origin, distance to recent forest management activities and competition (number of sawmills occurring within a 50-mile radius of a sawmill). The analysis attempted to discover any significant relationships between these independent variables and working distance (distance sawmills are willing to travel for log procurement), the dependent variable. Information was collected through spatial analysis using the mapping tool in addition to telephone or in-person interviews with sawmills in the industry cluster area. All sawmills in the industry cluster analysis region were contacted and 12 responded to the interviews, representing over 90% of the sawmill capacity in the cluster analysis region. Two significant relationships were found, though R-squared values were around 50%, indicating weak correlations. A statistically significant relationship was found between maximum working distance and annual production volume. Another significant relationship was found between annual production volume and the number of sawmills occurring within a 50-mile radius (competition). No significant relationships were found between working distance and proximity to treatments, feedstock origin, species being processed or competition. The tool was valuable for collecting spatial information such as proximity to recent forest management sites and the number of sawmills that occur within a 50-mile radius. The industry cluster analysis provided insight for general trends of sawmills in northern Colorado and helped to recognize where further research is needed. Additionally, the data collected in the study contributes in the effort to collect sawmill data state-wide. Mapping Colorado's forest products facilities and contractors using ArcGIS software proved to be a very useful way to visualize the data and discover meaningful relationships that can be used in the decision support systems of Colorado’s forest products industry. This tool provides aid as forest management becomes more complex with insistent factors like wildfire, insects and disease, product availability in the market and wood biomass utilization. It provides a resource for a diverse set of stakeholders with many different DSS objectives including sustainability, future forest management, identifying industry hotspots and biomass availability.Item Embargo Species distribution models for and policy approaches to invasive plant ecology and management(Colorado State University. Libraries, 2024) Teich, Nathan Benjamin, author; Brown, Cynthia S., advisor; Jarnevich, Catherine, committee member; Pearse, Ian, committee member; Evangelista, Paul, committee memberThe ability of abundance-based Species Distribution Models (SDMs) to predict where invasive plants can be abundant, and to what degree, is a powerful research and management tool. Often, invasive plant abundance-based SDMs are created using similar inputs and approaches as occurrence SDMs. However, invasive plant ecology literature suggests that the factors found to control invasive plant abundance are more diverse and contextual, and therefore not entirely interchangeable with factors that control invasive plant occurrence. To ensure invasive plant abundance-based SDMs are leveraging the robust body of knowledge, this paper aims to highlight and summarize the ecological factors underpinning invasive plant abundance and reviews how those factors can be represented within abundance-based SDMs. I find that while the inclusion of invasive plant abundance governing factors often improves abundance-based SDM performance, certain governing factors are ubiquitously represented while others are less commonly accounted for in model creation despite their ecological importance. Barriers to incorporating invasive plant abundance governing factors into abundance-based SDMs often include data limitations or methodological uncertainty. Finally, we provide future research directions that would help address certain barriers and improve our ability to integrate abundance governing factors into SDMs. Invasive plants, when they become dominant components of a plant community, threaten native species and ecosystem processes. Abundance-based SDMs are gaining traction as a geospatial tool to predict where invasive plants can become abundant and have negative impacts. Biotic interactions influence invasive plant abundance locally but are often not included within the abundance-based SDM creation process. At present, it is unknown to what degree local-scale biotic interactions with other plant species determine locations where invasive plant species can become abundant. Using data from large-scale abundance observations of the invasive plant cheatgrass (Bromus tectorum) paired with data from plant communities in the western United States, we quantified the degree to which biotic interactions explain where cheatgrass is abundant beyond what would be anticipated from an abundance-based SDM created with abiotic and landscape context predictors alone. To this end, we fit Generalized Linear Models (GLMs) for different categories of cheatgrass abundance and used the predicted suitability SDM outputs alongside biotic variables, representing known competitive and facilitative interactions, to determine if including biotic interactions improved a model's explanatory power. The addition of biotic variables marginally improved GLMs for low (5-25%) and medium (25+-50%) cheatgrass abundance but displayed greater improved performance for high (50+%) cheatgrass abundance. Most notable amongst the specific biotic variables was the cover of perennial graminoid cover, representing known competitors of cheatgrass, which interacted with SDM environmental suitability to strongly reduce the probability of high cheatgrass abundance. These findings suggest that considering biotic interactions alongside SDM predicted suitability may indeed improve our ability to predict abundance locations of invasive plant species, but potentially only in specific contexts such as where that species can already achieve high abundance. Invasive plants cost the US billions of dollars each year due to ecological and economic impacts as well as management costs. One of the most common pathways of introduction and spread of invasive plants is through ornamental plant sales. While solutions such as regulations and voluntary self-bans have been implemented in some instances to mitigate this problem, widespread adoption has not occurred. As such, new alternatives should be explored. Opt-in labeling programs are commonly used throughout the agricultural industry to better inform customers about the products they are purchasing. An opt-in labeling program that consists of a partnership between retailers and governments or non-profit organizations could help reduce the spread of invasive plants by influencing customer behavior. This approach would be less costly to retailers than regulations, create new invasive plant prevention opportunities for governments and non-profits, and better inform consumers about specific invasive plant species.