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Browsing by Author "Stohlgren, Thomas, advisor"

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    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 member
    The 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.
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    Mapping Tamarix: new techniques for field measurements, spatial modeling and remote sensing
    (Colorado State University. Libraries, 2009) Evangelista, Paul H., author; Romme, William, advisor; Stohlgren, Thomas, advisor
    Native riparian ecosystems throughout the southwestern United States are being altered by the rapid invasion of Tamarix species, commonly known as tamarisk. The effects that tamarisk has on ecosystem processes have been poorly quantified largely due to inadequate survey methods. I tested new approaches for field measurements, spatial models and remote sensing to improve our ability measure and to map tamarisk occurrence, and provide new methods that will assist in management and control efforts. Examining allometric relationships between basal cover and height measurements collected in the field, I was able to produce several models to accurately estimate aboveground biomass. The best two models were explained 97% of the variance (R 2 = 0.97). Next, I tested five commonly used predictive spatial models to identify which methods performed best for tamarisk using different types of data collected in the field. Most spatial models performed well for tamarisk, with logistic regression performing best with an Area Under the receiver-operating characteristic Curve (AUC) of 0.89 and overall accuracy of 85%. The results of this study also suggested that models may not perform equally with different invasive species, and that results may be influenced by species traits and their interaction with environmental factors. Lastly, I tested several approaches to improve the ability to remotely sense tamarisk occurrence. Using Landsat7 ETM+ satellite scenes and derived vegetation indices for six different months of the growing season, I examined their ability to detect tamarisk individually (single-scene analyses) and collectively (time-series). My results showed that time-series analyses were best suited to distinguish tamarisk from other vegetation and landscape features (AUC = 0.96, overall accuracy = 90%). June, August and September were the best months to detect unique phenological attributes that are likely related to the species' extended growing season and green-up during peak growing months. These studies demonstrate that new techniques can further our understanding of tamarisk's impacts on ecosystem processes, predict potential distribution and new invasions, and improve our ability to detect occurrence using remote sensing techniques. Collectively, the results of my studies may increase our ability to map tamarisk distributions and better quantify its impacts over multiple spatial and temporal scales.
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    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 member
    The 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.