DOI: 10.6073/pasta/96125e88963c91671f4a97d32aea9449
title: Understory plant community data from repeated plot sampling (1978-2019) in old-growth northern hardwood forest, northern Michigan (Dukes RNA, Hiawatha National Forest)

description: This data-set includes long-term, permanent-plot-based data for understory plant communities in old-growth mixed northern hardwood-hemlock forest and forested peatland in the Upper Great Lakes region. Data for over 900 understory quadrats (all associated with long-term canopy data from larger permanent plots) included multiple (2-5) remeasurements over 23-40 years, with longest periods and most remeasurements for upland forest types. The Dukes Research Natural Area (RNA) (https://www.fs.usda.gov/research/nrs/rnas/locations/dukes) in the Hiawatha National Forest (Marquette Co., MI) includes ca. 100 ha of largely unlogged, original forest. Publications cited below include more detailed information about the site. About half of the RNA supports upland forests intergrading from hemlock (Tsuga candensis) dominance to mixtures of hemlock and northern hardwoods species. Sugar maple (Acer saccharum) is dominant over much of the upland area, with, locally, significant admixtures of beech (Fagus grandifolia), yellow birch (Betula alleghaniensis), and red maple (Acer rubrum). Topographic relief is very slight with total elevational change within the RNA only about 10 m. The stand is within a few km of the western limit of the continuous range of beech. In 1935, 248 continuing forest inventory (CFI) plots (circular, 0.2 acre) were established on a regular grid throughout the RNA, and these have been the subject of repeated sampling through 2018-2019 and support continuing long-term study addressing canopy tree communities (canopy data to be deposited in a separate project). Examples of resulting publications are cited elsewhere in metadata, and can provide more detailed information about the RNA. In 1978-80, U.S. Forest Service researchers, directed by Jan Schultz and Frederick Metzger, initiated studies of understory communities, including herbaceous species and woody seedlings. Data were derived from four sub-quadrats within each of the CFI plots. These quadrats were re-established and remeasured in upland areas in 1992-94 (by Kerry D. Woods and David J. Hicks). Since then, most plots have been remeasured at least once (in peatland areas) and up to four times (in upland areas), with the most recent measurements in 2018 (all sampling by Kerry D. Woods). Understory quadrats were established 15 and 35 feet due (magnetic) east and west of permanently marked CFI plot centers. Sampling methods have varied somewhat over time as noted in data tables. Herbaceous species have been consistently sampled by estimation of percent cover by species, but cover categories varied between 1978-1980 and subsequent samplings (details in variable descriptions in data tables). In 1978-80, smallest woody seedling class (&lt;15 cm tall) were sampled by stem count and cover estimate in the same quadrats, but larger size classes were sampled by count and cover estimate for milacre (~ four square m) plots centered on the same positions. In all subsequent sampling, both woody species and herbaceous species were recorded for the square-meter quadrats only. For 1992-2018, for herbaceous species and small shrubs, data consist of cover estimates by species; for tree and tall shrub seedlings, data consisted of cover estimates and stem counts. Seedling size classes are explained in variable descriptions in data tables. Initial analyses of herbaceous understory communities from 1978 to 2009 (Woods et al. 2012) document no overall trends in total cover, but the most frequent species showed increases in overall cover. Diversity changes were not evident over the full stand or within canopy plots, but species richness showed decreasing trends for individual quadrats. There is no significant presence of invasive or non-indigenous plant species or of invasive earthworms. Deer browse appears to be low to moderate at the Dukes RNA compared to regional patterns.