Repository logo
 

Assessing plant diversity to enable continental-scale monitoring and forecasting

Simple item page
dc.contributor.authorBarnett, David T., author
dc.contributor.authorStohlgren, Thomas, advisor
dc.contributor.authorEvangelista, Paul, committee member
dc.contributor.authorMartin, Patrick, committee member
dc.contributor.authorMorisette, Jeffery, committee member
dc.date.accessioned2017-09-14T16:04:11Z
dc.date.available2017-09-14T16:04:11Z
dc.date.issued2017
dc.description.abstractThe 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.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierBarnett_colostate_0053A_14232.pdf
dc.identifier.urihttps://hdl.handle.net/10217/183871
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.titleAssessing plant diversity to enable continental-scale monitoring and forecasting
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineEcology
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Barnett_colostate_0053A_14232.pdf
Size:
2.23 MB
Format:
Adobe Portable Document Format
Download

Collections

2000-2019
Theses and Dissertations