First Advisor

Yangdong Pan

Date of Publication

3-30-2018

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Environmental Science and Management

Department

Environmental Science and Management

Language

English

Subjects

Chum salmon -- Habitat -- Alaska -- Chichagof Island -- Mathematical models, Pink salmon -- Habitat -- Alaska -- Chichagof Island -- Mathematical models, Habitat (Ecology) -- Alaska -- Chichagof Island, Stream conservation -- Alaska -- Chichagof Island, Chum salmon -- Spawning -- Alaska -- Chichagof Island, Pink salmon -- Spawning -- Alaska -- Chichagof Island

DOI

10.15760/etd.6136

Physical Description

1 online resource (viii, 93 pages)

Abstract

In response to the increasing need for ecosystem services throughout the Southeast Alaska region, decision makers are tasked with balancing the need for natural resources with salmon conservation. However, accurate historical and current information on salmonid population abundance, freshwater distribution, and habitat quality are sparse with limited resolution for large portions of this remote and rugged landscape. Here, I created Intrinsic Potential (IP) models for chum and pink salmon to predict the potential for portions of coastal rivers to provide high-quality spawning habitat. I developed IP models for both species from field redd surveys and synthetic habitat variables derived from 1-m resolution digital elevation models. The surveys were performed at 49 study reaches in five coastal drainage basins on the north end of Chichagof Island, Southeast Alaska. I used a spatially balanced random sampling design that included field surveys for redds during two field seasons with contrasting precipitation patterns and disparate adult salmon escapements. The IP models predict probable spawning habitat for both species based on persistent landform characteristics and hydrologic processes that control the formation and distribution of spawning habitat across the landscape. Selection of persistent reach variables for both species IP models was informed by principal component analysis (PCA), resource selection ratios, random forest modeling, and regression models of field and synthetic variable comparisons. I observed primarily one spawning strategy by chum salmon associated with mainstem channels, and two distinct spawning strategies for pink salmon related to small moderate-gradient channels and tributaries, and lower drainage basin mainstem channels. The relationships suggest that chum and pink salmon primarily selected for unconstrained channel types in large-and small-size channels, with chum salmon being more selective toward the larger mainstem channels, and pink salmon selecting for smaller channels and tributaries. The prediction of chum salmon redd presence within a specific reach for both high and low streamflow regimes was explained by channel gradient, floodplain width, and mean annual flow in order of importance. In general, chum salmon redds were observed in larger unconstrained low-gradient floodplain reaches where accumulation of deposited gravels and adequate flow produce habitat heterogeneity suitable for spawning. Pink salmon redd presence for both survey years was explained by channel gradient, reach elevation, and mean annual flow, in order of importance. Specifically, when flows allowed upstream access, spawning pink salmon utilized smaller moderate-gradient channels where substrate size and flows were better suited to their smaller body size. Remotely sensed persistent fish habitat data is valuable information for helping understand fish population distributions across the landscape. These synthetic metrics enabled the identification and evaluation of persistent landscape features as probable predictors of IP. Validation of LiDAR-derived channel characteristics indicated channel lengths measured from the DEM were 12% longer than field measured channel length, primarily for channels wider than 10 meters. Thus, understanding the limitations of the data is important so that decision makers do not unintentionally set unrealistic objectives. This research highlights the utility of using IP models with high resolution remote sensing to expand known distributions and quality of spawning habitat for these two species in Southeast Alaska coastal streams.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. 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).

Persistent Identifier

https://archives.pdx.edu/ds/psu/26223

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