DOI: 10.5061/dryad.v15dv425m
title: Data for: Impact of invasive Typha and wetland interspersion on muskrat declines in North America

description: Muskrat (Ondatra zibethicus) populations are declining in North America.
 The exact cause of these declines is largely unknown. Along a similar
 timeframe, wetlands have been experiencing an invasion of cattail (Typha)
 throughout the continent. Specifically, T. x glauca, a hybrid of native T.
 latifolia and non-native T. angustifolia, has been increasing in range and
 abundance. This hybrid is associated with many negative impacts on wetland
 ecosystems, including reductions in biodiversity, open water habitat, and
 interspersion of water and emergent vegetation, the latter of which is an
 important habitat feature for muskrats. We sought to determine the impact
 of invasive T. x glauca on muskrat populations. We sampled 39
 Typha-dominated marshes in southern Ontario, Canada to test the hypotheses
 that muskrats are declining in North America due to: (1) the increased
 relative abundance of T. x glauca in marshes, and (2) reduced wetland
 interspersion, which is associated with T. x glauca invasions. We
 estimated muskrat population density using house counts, sampled Typha
 communities to determine the relative abundance of T. x glauca, and
 measured interspersion using remote sensing techniques. We found that
 muskrat population density was positively associated with interspersion,
 but not associated with the relative abundance of T. x glauca. However,
 most sites were highly dominated by T. x glauca, limiting our inference.
 Our findings suggest that changing wetland structure may be contributing
 to muskrat population declines in North America, but more research is
 needed to determine the full impact of T. x glauca invasions on muskrat
 population declines. 
description: Muskrat house density was estimated by collecting aerial imagery
 at study sites in March 2021 and February 2022 and using the imagery to
 identify muskrat houses at each site. We used a random-sampling approach
 whereby a grid of 1-hectare cells was overlaid on each study site and
 cells that did not represent suitable muskrat habitat were eliminated;
 from the remaining cells, we randomly selected 10 cells to sample (only a
 few sites had less than 10 suitable cells, in which case all suitable
 cells were sampled). Muskrat houses appearing in these random cells were
 included in the calculation of mean house density in houses per
 hectare. <em>Typha</em> x
 <em>glauca</em> relative abundance was estimated by sampling
 the <em>Typha </em>community in the field along predetermined
 transects at each site. Transects were accessed from the water, or in a
 few cases, on foot. Number of sampled transects ranged from 3 to 7 per
 site. Each transect was approximately 6 meters in length and was roughly
 perpendicular to the water's edge. At the start of the transect, the
 first ramet within reach with visible spikes (inflorescences) was sampled.
 Sampling consisted of obtaining a sprinkling of pollen when present,
 followed by a clipping of half of the pistillate (female) spike. Whenever
 possible, three ramets were sampled along each transect, with the first
 being collected at the water's edge, and the subsequent samples at 3
 m increments along the transect. Pistillate spikes were placed under a
 dissecting microscope and used to identify the plant based on a botanical
 key. In a few cases, pollen was placed under a compound micriscope and was
 instead used to identify the plant using the same key.
 Mean interspersion and mean proportion of open water were both
 measured using geospatial processing. This consisted of conducting land
 cover classifications of each site, identifying areas
 of <em>Typha</em>-dominated marsh, other vegetation, and open
 water. From the cells that represented suitable muskrat habitat, the
 proportion of open water was calculated for each 1-hectare cell and
 averaged across those cells. In each of those same cells, the total length
 of water polygon edges was calculated and averaged across those cells,
 This effectively represented emergent-water edge density in meters per
 hectare, which we used as a measure of interspersion.
description: # Data for "Impact of invasive Typha and wetland interspersion on
 muskrat declines in North America"
 [https://doi.org/10.5061/dryad.v15dv425m](https://doi.org/10.5061/dryad.v15dv425m) ## Description of the data and file structure Our main response variable was mean muskrat house density which was a proxy for muskrat population density. We estimated the relative abundance of T. x glauca and measured wetland interspersion to test our hypothesis that muskrat populations are declining due to the invasion of T. x glauca and the associated changes to wetland structure. We also determined the mean proportion of open water at each site which may also be impacted by T. x glauca invasions and may thus impact muskrat populations, and we classified each site based on its association with Lake Ontario hydrology, which may further play a role in muskrat abundance. ### Files and variables #### File: Data\_Melvinetal2024.csv **Description:**  This file contains all of the data we used in our analyses. ##### Variables * site: the name of the wetland (i.e. study site). * latitude: Latitude of the study site in decimal degrees. * longitude: Longitude of the study site in decimal degrees. * house_density: Mean muskrat house density in houses/ha. A proxy for muskrat population density. This is our main response variable. * glauca: The proportion of Typha samples at each site that were identified as Typha x glauca. This is one of our main predictor variables. * \#_sampled_ramets: Sample size for Typha sampling at each site. * interspersion: Mean interspersion measured as water edge density in meters per hectare. This is one of our main predictor variables. * water: Mean proportion of open water per hectare. This is a secondary predictor variable.  * wetland_type: Summarizes the association of the wetland to Lake Ontario. This is a secondary predictor variable. Coastal wetlands may be directly impacted by the hydrological effects of Lake Ontario and are very close to the lake (i.e. within 500 m). Inland wetlands are not directly impacted by the hydrological effects of Lake Ontario and are at least 10 km from the lake. ## Code/software The data may be viewed in Microsoft Excel or R. We used R version 4.2.3 and RStudio v. 2022.12 to analyze the data along with packages dplyr, Hmisc, PerformanceAnalytics, and stats.