Author ORCID Identifier

https://orcid.org/0009-0005-1249-7012

Date Available

4-27-2023

Year of Publication

2023

Degree Name

Master of Science (MS)

Document Type

Master's Thesis

College

Agriculture, Food and Environment

Department/School/Program

Plant and Soil Sciences

First Advisor

Dr. Samuel Ray Smith

Abstract

Botanical composition of pastures has been measured with numerous methods over the last century, but there have been limited direct comparisons between methods. The objective of this study was to compare botanical composition methods, to determine the most accurate and efficient method, and to access pasture composition change over time. Six farms with two pastures each were monitored across the state of Kentucky. Sampling occurred fall 2020 through fall 2022, three times a year using the following methods: step point, visual estimation, occupancy grid, and point quadrat (used as a reference method). The occupancy grid showed the highest similarity to the point quadrat method, was less prone to over and under-estimation, and had the highest correlation coefficient, 0.87 to 0.99 across all species. The correlation across species between the point quadrat and visual estimation was 0.75 to 0.98 and 0.40 to 0.90 with the step point method. Monitoring of species change over time showed an expected shift from C3 to C4 species during the warmer months of the growing season, but this shift was most dramatic under drought conditions and overgrazing. Drought conditions caused a significant (p = < 0.05) increase in C4 species during the final two sampling periods. These conditions confounded with less-than-ideal management strategies caused estimated dry matter yield to decline over the study period. In conclusion, occupancy grid was most similar to point quadrat method and was the most efficient method of botanical analysis. C3 and C4 species change over time was most affected by climate and pasture management.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2023.104

Funding Information

This project was funded by a Non-Assistance Cooperative Agreement with the United States Department of Agriculture Agricultural Research Service Food Animal Production Unit, Lexington, KY (2/06/19 215 Dinkins 5042-21000-003-00D)

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