Environmental Drivers of Occupancy and Detection of Olympic Mudminnow

<p>The Olympic Mudminnow <i>Novumbra hubbsi</i> is a highly endemic freshwater fish found only in Washington State, where their distribution is limited to low-elevation wetland habitats. The distributional extent of the Olympic Mudminnow is well established, but local and watershed environmental features associated with their presence or absence within the range are poorly understood, making it difficult to determine habitat needs versus availability. We surveyed 22 sites in 2 years along the Chehalis River with the objective of modeling environmental characteristics associated with occupancy by Olympic Mudminnows, while also accounting for incomplete detection. Occupancy and detection probabilities were highly similar between years, and occupancy that incorporated detection probabilities was 47% higher than naive estimates in a given year. Modeling with environmental covariates supported the importance of low temperatures for predicting the occurrence of Olympic Mudminnows at sites, and detection within sites was associated most strongly with shallow depths and low dissolved oxygen. These results are consistent with prior research indicating the preferential use of groundwater springs by Olympic Mudminnows, particularly in warmer summer months. Our research expands the existing knowledge of Olympic Mudminnow distributions by documenting main-stem-oriented populations at varying levels of abundance and suggesting habitat features that may increase occupancy and detection probabilities. The sampling and modeling approach we describe also informs development of standardized survey protocols for Olympic Mudminnows, helping to optimize resources for monitoring occupancy and abundance across their limited range.</p

LakeSoundscapes_LakexTime_Data

Data used in univariate and multivariate statistical analysis of lake soundscapes; data is summarized at the level of lake (sampling site) and time period to reflect the analyses using the manuscript. Includes site (lake)-level factors and characteristics as well as the acoustic data which was collected in the field. Acoustic data metrics were calculated using Raven Pro 1.4; refer to ReadMe file for detailed descriptions of metrics, calculation methods, and sources

LakeSoundscapes_AboveBelowWater_Data

Acoustic data collected at sites (lakes) for comparison of hydro (below water) and air (above water) sound characteristics. Data is summarized by site (field=Lake_Name) and includes total average power of all sound samples over all time periods (field=Power) as well as for each 1 kHz frequency interval (e.g. 3to4kHz_Power). All power is in decibels (db) calculated in Raven Pro 1.

LakeSoundscapes_Morton24Hours_Data

Acoustic data collected at Morton Lake over 24 hours; reported in manuscript using multivariate analysis of temporal trends. Data is summarized by hour of day (field=HourOfDay) and includes average power of the sound sample for each 1 kHz frequency interval (e.g. 3to4kHz_Power). All power is in decibels (db) calculated in Raven Pro 1.4

Relationship of above- and below-water sound.

<p>Patterns and correlation of overall sound (average power in dB) between above-water and hydrophone data by frequencies corresponding to anthrophony (•, mean: 1–3 kHz) and biophony (Ο, mean: 3–8 kHz). Regression on individual frequency intervals resulted in a significant correlation for only the 0–1 kHz band (<i>R²</i> = 0.71, <i>p</i> = 0.02, all others <i>R²</i><0.03, <i>p</i>>0.69).</p

Temporal trends in anthropogenic sound by urban category.

<p>Average power (1–2 kHz) at lakes characterized as Low (<30%, <i>n</i> = 3), Medium (30–50%, <i>n</i> = 3), and High (>50%, <i>n</i> = 4) urbanization. The threshold established by the U.S. Environmental Protection Agency (in dBA) for “outdoor annoyance and disruption” <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055661#pone.0055661-Environmental1" target="_blank">[7]</a> is shown as a reference; dBA is highly comparable in this frequency range, with a weighting value of +0–1.2 dB between 1–2 kHz; we have considered these equivalent for purposes of illustration.</p

Changes in importance of frequency intervals by time period for a single lake.

<p>Principal component analysis summarizing patterns of relative power in eight frequency intervals using all 24 time selections for Morton Lake (urbanization = 40%). Labels delineate the multivariate centroid for individual data points for each time period: Night (N), Morning (M), Day (D), and Evening (E). Inset displays the component loadings (eigenvectors) for each frequency interval.</p

Dominant frequencies and acoustic variation by urban category in multivariate space.

<p>Principal component analysis summarizing patterns of relative power in eight frequency intervals across the study lakes. Each data point represents one of four time periods at an individual lake. Urban categories are delineated with ordination hulls (90% confidence interval) according to High (solid), Medium (dotted), and Low (dashed) surrounding urbanization. Inset displays the component loadings (eigenvectors) for each frequency interval.</p

Study area, apparatus, and sampling locations.

<p>A) King County in Washington State, U.S.A., B) floating platform with microphone, and C) location of lakes across an urbanization gradient (green = forested; red = urbanized). The city of Seattle is located on the left (west) of the map.</p

Regression models for fixed effects of spatial and temporal factors on relative power of anthrophony and biophony.

<p>Regression was on mean power by time period for each lake (<i>n</i> = 40); significant fixed effects (<i>p</i><0.05) are highlighted in bold. Tests for interactions of fixed effects resulted in no significant relationships so interaction terms were removed.</p