To determine the potential for controlling non-native Phragmites australis through use of a cut-to-drown management strategy we performed a controlled greenhouse mesocosm experiment in Ann Arbor, MI during summer 2021. Field collected Phragmites rhizomes from one site within Michigan were propagated, cuttings taken of individual stems and potted in nursery pots. Established plants were then subjected to a complete factorial combination of three submergence treatments (no submergence, partial submergence of aboveground tissues, and compete submergence of aboveground tissues) and 3 cutting treatments (no cutting, spring cutting of above ground tissues, and summer cutting of aboveground tissues). By performing weekly monitoring of plant growth, harvesting of a subset of plant tissues and overwintering of the remaining plants, we were able to examine difference in biomass production, non-structural carbohydrate content and future viability of Phragmites plants receiving different cut-to-drown treatments.

Nonnative Phragmites australis (common reed) is widely distributed across North America and insufficient knowledge of P. australis has impeded the efficiency of management. To aid in Phragmites management and future studies, we used RNA-seq data from multiple types of plant tissue to construct forty-nine P. australis transcriptomes via different assembly tools and multiple parameter settings, resulting in seven assembled transcriptomes for further comprehensive assessments. The optimal transcriptome ("cd-hit") was selected for functional annotation and downstream analyses. This data release contains the seven assembled transcriptomes, and data derived from the optimal transcriptome (functional annotations, tissue-specific expression patterns, putative transcription factors, and simple sequence repeats markers).

Nonnative Phragmites australis (common reed) is widely distributed across North America and insufficient knowledge of P. australis has impeded the efficiency of management. To aid in Phragmites management and future studies, we used RNA-seq data from multiple types of plant tissue to construct forty-nine P. australis transcriptomes via different assembly tools and multiple parameter settings, resulting in seven assembled transcriptomes for further comprehensive assessments. The optimal transcriptome (“cd-hit”) was selected for functional annotation and downstream analyses. This data release contains the seven assembled transcriptomes, and data derived from the optimal transcriptome (functional annotations, tissue-specific expression patterns, putative transcription factors, and simple sequence repeats markers).

Phragmites australis live fractional cover (LFC) maps were created of the lower Mississippi River Delta (MRD) using satellite image data. The historical 2009 to 2016 P. australis marsh LFC maps were based on yearly Landsat image data. The 2016 to 2019 P. australis marsh LFC maps were based on yearly Sentinel-2 image data.

To determine how native and non-native lineages of Phragmites australis affect and respond to soil bacteria, fungi and oomycetes, we collected live rhizomes, seeds and soil from native and non-native lineages of Phragmites from 10 sites within Michigan and Ohio, USA. We propagated these field-collected samples to carry out a reciprocal-transplant plant-soil feedback experiment with multiple microbial inhibition treatments. Specifically, we investigated how each Phragmites lineage grew in soils pre-conditioned by each lineage and soils that had been pre-sterilized. Plant biomass was the main response variable collected to determine responses to microbial soil conditioning. We also used DNA meta-barcoding to identify the effects of each plant lineage on soil microbes and link plant responses to microbial communities. Specifically, DNA was extracted from soils and fungal and bacterial DNA was amplified to identify the microbial constituents. Amplicons were sequenced using Illumina MiSeq. This dataset includes outputs of bioinformatic analysis of sequences including operational taxonomic unit (OTU) generation, OTU abundance, resolved taxonomy, and environmental metadata collected in our survey. Raw sequences were uploaded to the NCBI Sequence Read Archive under SRA accession number PRJNA719385.

During 2018, uncrewed aerial vehicles (UAVs or 'drones') were used to collect spatially referenced aerial imagery from 20 management units (sites) enrolled in the Phragmites Adaptive Management Framework, a collective learning program developed by the Great Lakes Phragmites Collaborative. Management units were located in Michigan, Ohio, and Wisconsin (USA). Invasive Phragmites australis (hereafter "Phragmites") had been managed at each management units some time previously by the landowner or land manager, and aerial imagery was then collected to create cover classifications distinguishing live and dead Phragmites from the surrounding landscape using object-based image analysis with training based on ground-truth field data and photos. Standard color (RGB) imagery was collected at all 20 management units, and near-infrared (NIR) imagery was collected at 2 of the 20 management units. Accuracy for the classifications was assessed by comparing cover classifications to ground truth data via confusion matrices. The accuracy associated with generating cover classifications by RGB and NIR imagery were also compared.

These data tables contain data collections from field experiments of Phragmites australis (ssp. australis) treated with known fungal endophytes. Tiller counts, tiller diameter, and tiller height measurements were taken every two weeks over an eight-week study period. Clones of Phragmites plants were collected from three different locations: Sandusky, Michigan; Bloomington, Indiana; and the Ottawa National Wildlife Refuge near Oak Harbor, Ohio. Additionally, data collections from a similar experiment of Phragmites australis (ssp. australis) treated with known fungal endophytes performed in a growth chamber are included. Tiller numbers and tiller heights were measured every three weeks over 15 total weeks for the growth chamber experiment. Plants from both experiments were collected and processed to determine dry weights and fungal communities were sequenced. All sequence data were submitted to GenBank (NCBI Accession Numbers: OM26200-OM262384).

The first basin-wide map of large stands of invasive Phragmites australis (common reed) in the coastal zone was created through a collaboration between the U.S. Geological Survey and Michigan Tech Research Institute (Bourgeau-Chavez et al 2013). This data set represents a revised version of that map and was created using multi-temporal PALSAR data and Landsat images from 2016-2017. In addition to Phragmites distribution, the data sets shows several land cover types including urban, agriculture, forest, shrub, emergent wetland, forested wetland, and some based on the dominant plant species (e.g., Schoenoplectus, Typha). The classified map was validated using over 400 field visits.This map covers the Green Bay peninsula and surrounding area on Lake Michigan.

The first basin-wide map of large stands of invasive Phragmites australis (common reed) in the coastal zone was created through a collaboration between the U.S. Geological Survey and Michigan Tech Research Institute (Bourgeau-Chavez et al 2013). This data set represents a revised version of that map and was created using multi-temporal PALSAR data and Landsat images from 2016-2017. In addition to Phragmites distribution, the data sets shows several land cover types including urban, agriculture, forest, shrub, emergent wetland, forested wetland, and some based on the dominant plant species (e.g., Schoenoplectus, Typha). The classified map was validated using over 400 field visits.

The first basin-wide map of large stands of invasive Phragmites australis (common reed) in the coastal zone was created through a collaboration between the U.S. Geological Survey and Michigan Tech Research Institute (Bourgeau-Chavez et al 2013). This data set represents a revised version of that map and was created using multi-temporal PALSAR data and Landsat images from 2016-2017. In addition to Phragmites distribution, the data sets shows several land cover types including urban, agriculture, forest, shrub, emergent wetland, forested wetland, and some based on the dominant plant species (e.g., Schoenoplectus, Typha). The classified map was validated using over 400 field visits.