DOI: 10.5061/dryad.j3tx95xr4
title: Data from: Pheasants 365: A review of seasonal ring-necked pheasant habitat in central North America

description: Ring-necked pheasants, an economically important game species in North
 America, are facing population declines in agriculturally dominated areas
 due to intensification of production systems. There is a significant body
 of research on pheasant habitat requirements, much of which aims to
 address declines by guiding management decisions to improve habitat
 conditions. Pheasants, like many species, have differing resource needs
 throughout the year based on their life history and seasonal changes to
 the landscape; however, many studies have only focused on one or two of
 the three key ecological seasons – breeding, brood-rearing, or
 overwintering. We conducted a literature review using the Web of Science
 database to synthesize results from studies investigating pheasant habitat
 in central North America in a seasonal context in order to provide a
 year-round perspective on pheasant habitat management. Our results show
 the importance of grasslands and small grains during nesting and
 brood-rearing season, while wetlands and food plots become important
 during the winter months. Grassland structure is a crucial component of
 nesting habitat, with pheasants selecting for high litter content, high
 VOR, and tall vegetation for nesting in 90% of studies that included those
 variables; while during brood-rearing chicks had higher success in
 grasslands with a higher percentage of forbs and more bare ground. No
 strong relationship was found with woodlands during any season, positive
 or negative. Row crops showed mixed results during nesting and brooding,
 as they are frequently used but not preferred, while during the winter row
 crops and other agricultural lands such as pasture and hay fields were
 largely negatively related to pheasant resource use, abundance, and/or
 survival. This review aims to guide management decisions regarding
 pheasant habitat by providing a season-specific synthesis of the
 literature within the Great Plains and Midwestern USA.
description: The geographic scope of this review was the Great Plains and
 Midwest Region of the United States. In recognition of the variability and
 subjectivity in delineating the boundaries of these regions, we used the
 Great Plains Region outlined by Lavin <em>et al</em>. (2011)
 and the Midwest Region definition provided by National Geographic
 (O’Conner, 2024). Notably, there is an overlap between the two regions,
 with portions of North Dakota, South Dakota, Nebraska, and Kansas
 occurring in both regions. We specified the combined extent of these
 regions as our study area due to their relative similarities in land use,
 topography, and climate, as well as history of supporting pheasant
 populations. The temporal extent of the review was from 1970 –
 2023. A systematic literature search was conducted
 according to the PRISMA guidelines for ecology and evolution (O’Dea et
 al., 2021) using the Web of Science ‘all databases’ search function.
 Search terms and Boolean operators used are reported in Table 1.
 Subsequently, search results were refined to only include peer-reviewed
 articles originating from the United States. This yielded a total of 174
 articles, which were then subjected to manual review by two independent
 reviewers to determine if they met inclusion criteria. Papers were
 included if any portion of the study was conducted within the study area
 described above. Additional inclusion criteria included: (1) the study
 must appear in a peer-reviewed journal; (2) must present original research
 on pheasant habitat, resource use, or survival directly related to
 habitat; (3) must study wild, in-situ pheasant populations; (4) no genetic
 studies were included; (5) no diet analyses were included; (6)
 multi-species studies were included only if they reported species-specific
 results; (7) biogeographic studies were included only if they evaluated
 habitat or resource use as a driver of changes in range or distribution.
 Books, reports, theses, dissertations, grey literature, magazines,
 newsletters, fact sheets, conferences, seminar or symposium proceedings,
 assessment projects, reviews, guides, and bibliographies were excluded.
 Studies using a mix of wild and captive or translocated pheasants were
 excluded if the majority of pheasants were captive or translocated. The
 selection process was executed independently by two authors, with outcomes
 cross-checked to ensure consistent application of the inclusion criteria.
 After this manual selection, 65 papers remained and were analyzed. The
 abstract, methods, and results of each study were thoroughly reviewed and
 summarized in Microsoft Excel. After the relevant information was
 extracted from each paper, it was synthesized in R (R Core Team, 2024) and
 interpreted for trends, differences, and commonalities.
 Land cover types were hierarchically classified in order to
 standardize the results of each study for quantitative analysis. Grassland
 includes both public grasslands and Conservation Reserve Program (CRP)
 fields; woody cover includes shrublands, woodlands, and shelterbelts;
 wetland includes herbaceous and woody wetlands; linear features include
 roadsides, fencerows, waterways, and train rights-of-way; and agricultural
 grassland includes hay fields, alfalfa, and pastures. Wheat and wheat
 stubble were incorporated into the small grains category. Percentage or
 abundance of litter and forbs were included as grassland structural
 components due to their relevance in the literature to microhabitat and
 nest site selection (Matthews et al., 2012a). For each analysed paper,
 each land cover category was designated as “positive”, “negative”,
 “variable”, “no effect found”, or “not included in analysis”; where,
 positive/negative are defined as having a positive or negative correlation
 with pheasant abundance, occupancy, habitat selection, survival, or
 nest/brood success at at least one spatial scale. A land cover category
 was labelled as ‘no effect found” if it was measured during the study but
 did not appear in the top model or a relationship was found to be
 insignificant (p &lt; 0.05). A land cover category was labelled as
 “variable” if the direction of the relationship changed based on scale,
 study area, or some other studied variable (i.e. row crops showed a
 positive relationship with pheasant abundance at the home range scale but
 a negative relationship at the landscape scale).
description: # Data from: Pheasants 365: A review of seasonal ring-necked pheasant
 habitat in central North America
 [https://doi.org/10.5061/dryad.j3tx95xr4](https://doi.org/10.5061/dryad.j3tx95xr4) ## Description of the data and file structure This data was collected as part of a comprehensive literature review titled "Pheasants 365: A review of seasonal ring-necked pheasant habitat in central North America" by Barg *et al* (2025). This review collected published, peer-reviewed literature regarding ring-necked pheasant habitat in the Great Plains and Midwestern North America in order to identify seasonal trends and locate gaps in our knowledge of seasonal pheasant habitat. The data was collected from the Web of Science using boolean search terms regarding pheasants and habitat, and then the data was manually filtered to select relevant studies based on a set of predetermined criteria. The Excel file lists the final sixty-five studies that were found to meet the requirements of the review. The study methodology, focal season(s) and results were summarized from the selected studies in R and Excel to understand literature trends.  ### Files and variables #### File: LitReviewDataCollection_finalpub.csv **Description:** This spreadsheet contains the publication information, year, location and results of each study included in this review.  ##### Variables * Authors: Article authors * Article Title: Article title * Source Title: Journal name * DOI: Individual DOI or URL for each paper * Publication Year: Year that the article was printed * State: The state in which the data was collected * Great Plains: A Yes or No column defining if the data was collected in the Great Plains region * Midwest: A Yes or No column defining if the data was collected in the Midwest region * Male: A Yes or No column defining if the paper focused on male pheasants * Female: A Yes or No column defining if the paper focused on female pheasants * Both: A Yes or No column defining if the paper focused on both male and female pheasants * Juvenile: A Yes or No column defining if the paper focused on juvenile pheasants * Nests: A Yes or No column defining if the paper focused on pheasant nest site selection or success * annual: A Yes or No column defining if the paper was conducted on an annual basis, rather than seasonal * Breeding/nesting: A yes or No column defining if the paper included results for the breeding and nesting seasons * Brood rearing: A yes or No column defining if the paper included results for the brood-rearing season * Overwintering: A yes or No column defining if the paper included results for the winter season * method: Which method of data collection was used. i.e. radio telemetry, point counts, nest searching, etc.  * method 2: A secondary method column for papers that used more than one data collection method * Results: A short description of key results from the paper * Metric: What form the data took and which metric was used. i.e. survival, habitat use, counts, etc. * Metric 2: A secondary metric column for papers that used more than one metric. * Grass - Configuration: The remaining columns all name a land cover type that appears in the pheasant literature. Each row contains a number from 1 to 6, which denotes whether or not the land cover type was included in each study and if it was found to be positive, negative, no effect, or the effect changed within the study.  * Key: A key defining the previously stated notations from 1-6.  * Meaning: What each number in the key means for analysis. * Missing values are indicated by blank cells, these occur primarily in the Method 2 and Metric 2 columns, as not all studies used multiple methods or metrics.  ## Code/software The code was created and run in R version 4.4.0 (2024-04-24 ucrt) within Rstudio. R is a free and open programming language used for statistical analysis and data visualization. The following packages were used to run the code: tidyverse, ggplot2, and janitor.  Download the CSV file containing the data *LitReviewDataCollection_finalpub.csv* and the R script LitReviewCode_final.R via zenodo.  After opening the script in Rstudio, set your working directory to the folder where the CSV data is located. The code should run as-is.