Date of Award

Spring 4-17-2020

Semester of Degree

May

Document Type

Open Access Thesis

Degree Name

M.S. in Environmental and Forest Biology

Department

Forest and Natural Resources Management

Major Professor

Neil Ringler

Steering Committee Member

Brian Duffy

Steering Committee Member

Stephanie Johnson

Steering Committee Member

Stephen Stehman

Abstract

Aquatic macroinvertebrates are well-established biological indicators of water quality and a major component of water quality assessment of flowing waters because of their ability to detect and integrate natural and anthropogenic changes in physical and chemical habitat. The New York State Stream Biomonitoring Unit (NYS SBU) has been collecting biological, chemical, and physical data of the state’s rivers and streams since 1972. These data have been used to develop assessment methodologies specific to segments of the river continuum. However, no associated physical parameter (e.g., substrate and instream habitat) models that could help predict water quality have been developed. The purpose of this study was to assess differences in physical variables and macroinvertebrate response to physical habitat stressors, and create models to aid in accurately assessing water quality along the river continuum. Historical data were used to identify variation in physical parameters within the longitudinal stream gradients (i.e., headwaters to non-headwaters). Catchment-scale land use data were used to identify reference versus non-reference streams, and assess if human disturbances impacted the physical parameters. Headwater streams exhibited a departure from the reference condition for substrate composition and habitat parameters, resulting in impact threshold models for each. However, non-headwaters did not show any deviation from the reference condition for substrate composition and habitat. A threshold indicator taxa analysis was performed and a community change-point was identified for each substrate and habitat parameter for non-headwater streams, resulting in a model with thresholds of concern rather than an impact threshold model. These models can be utilized in future water quality assessments in New York State to improve implementation and management.

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