DOI: 10.5061/dryad.2ngf1vj0q
title: Forest composition drives bryophyte biomass, carbon and nitrogen storage in the boreal-temperate ecotone

description: Aims: Climate change and forest management have profoundly altered forest
 ecosystem dynamics, with impacts on canopy composition and understory
 vegetation. Forest type affects bryophyte ecosystem processes,
 particularly related to carbon (C) and nitrogen (N) cycling. Within the
 boreal-temperate ecotone, the Wabanaki-Acadian Forest harbors a diverse
 canopy composition with many species at their distributional limit, making
 it sensitive to climate change and human alterations, with unknown impacts
 on bryophytes and their functions. We aimed to quantify how canopy
 composition and moisture affect forest-floor bryophyte biomass, and C and
 N stocks. Location: We sampled in 49 stands representing six forest types
 of the Wabanaki-Acadian Forest of New Brunswick (Canada): mesic and wet
 coniferous, mesic and wet deciduous, mixed, and cedar forests. Methods:
 First, we developed an allometric model to predict bryophyte bulk density.
 We then estimated bryophyte biomass and C and N contents for five
 functional groups at each site using the ground-layer indicator method and
 measured forest and soil characteristics at each site (e.g., forest
 composition, soil pH, moisture class). Linear models, multivariate,
 similarity percentages, and indicator species analyses were used for data
 analysis. Results: The highest bryophyte biomass and C and N stocks was
 found in conifer-dominated forests, especially where Sphagnum was
 abundant, whereas it was low in mixed and deciduous forests which also had
 a different functional composition. There was a strong negative non-linear
 relationship between bryophyte biomass and broadleaf litter. Conclusions:
 We provide the first reports of bryophyte biomass and C and N stocks in
 the Wabanaki-Acadian Forest, which were consistent with its latitudinal
 location at the southern edge of the boreal forest. Our findings highlight
 the connections between forest composition and bryophytes in the Acadian
 Forest and reveal the participation of forest-floor bryophytes in C and
 nutrient cycling.
description: # Forest composition drives bryophyte biomass, carbon and nitrogen storage
 in the boreal-temperate ecotone
 [https://doi.org/10.5061/dryad.2ngf1vj0q](https://doi.org/10.5061/dryad.2ngf1vj0q) ## Description of the data and file structure We aimed to quantify how canopy composition and moisture affect forest-floor bryophyte biomass, and C and N stocks. We sampled in 49 stands representing six forest types of the Wabanaki-Acadian Forest of New Brunswick (Canada): mesic and wet coniferous, mesic and wet deciduous, mixed, and cedar forests. Methods: First, we developed an allometric model to predict bryophyte bulk density from calibration samples. We then estimated bryophyte biomass and C and N contents for five functional groups at each site using the ground-layer indicator method (Smith et al. 2015) and measured forest and soil characteristics at each site (e.g., forest composition, soil pH, moisture class). Linear models, multivariate, similarity percentages, and indicator species analyses were used for data analysis. ### Files and variables #### File: Data_Acadian_Bryophytes.xlsx **Description:** Site level data, and information on bryophytes from the calibration and implementation steps of the ground layer indicator method (Smith et al. 2015), as used in the paper linked. Missing values are indicated as NA.  Column: Description (A= Calibration samples tab, B= implementation samples tab, C= Site info tab) ##### Variables * forest_type: Forest type: Wet conifer (wet_con), Mesic conifer (wet_con), Cedar forest (cedar), Conifer-deciduous mix (mixed), Wet deciduous (wet_dec), Mesic deciduous (mes_dec) (A, B, C) * site: Site code (A, B, C) * microplot: Microplot sample location: # of the closest transect (A) or # ID of the implementation microplot, 11 is located in the center of the plot and 1 is located at the end of the transect (B)  * year: Year of calibration sampling (A) or Year of implementation sampling (B) * functional_type: Bryophyte functional group: Liverworts (liverwort), Nitrogen-fixing feather mosses (nfix_feather), Sphagnum (sphagnum), Turf mosses (turfmoss), Other feather mosses (feathermoss) (A, B) * biomass_g: Dry biomass (g) (A) * area_cm2: Calibration sample area with 100% of same species cover (cm²) (A) or implementation sample area with 100% of same functional group cover (B) * depth: Calibration sample depth (cm) (A) or Implementation samples depth (cm) (B) * vol: Calibration sample volume (cm³) = area_cm² x depth (A) * SampleCODE: Calibration sample code (A) * n \_perc: sample's percentage of Nitrogen(N) (A) * c_perc: sample's percentage of Carbon(C) (A) * cn_ratio: sample's C/N ration (A) * region: region where samples were collected (B, C), Fredericton-NB = 0.5 and Moncton-NB = 1 (C) * transect: 40m-long transect used to align implementation microplot placement: 1-0 = 0º, 2-120 = 120º, 3-240 = 240º (B) * class_cover: Class cover (Peet et al. 1998) of each functional group (B) * cover_perc: Percentage of each functional group covered the microplot (%) (Peet et al. 1998) (B) * vol_cm3_parc: Volume of each functional group in the microplot (cm³) = area_cm2 x depth (B) * vol_cm3_m2: Estiamtion of the volume that each functional group covers in 1m² = vol_cm3_parc x 10 (B) * latitude: Latitude in decimal degrees North (C) * longitude: Longitude in decimal degrees West (C) * watertable: Forest type moisture based on depth to the watertable: depth to the watertable &gt; 90 cm (0.5) and depth to the watertable &lt; 90 cm (1) (C) * con_perc: Percentage of the basal area is coniferous dominant/co-dominant trees (C) * bleaf_perc: Percentage of the basal area is deciduous dominant/co-dominant trees (C) * acer - ostrya: basal area of species (m²/ha) (C) ## Access information Forest composition, soil pH and moisture classes were derived derived from the following sources: * Canadian Wood Fibre Centre – CFS, 2024. Acadia Research Forest continuous landscape inventory ground plots – data Dictionary, Version 0.0.1. * Fahmy, S.H., Hann, S.W.R., Jiao, Y., 2010. Soils of New Brunswick: the second approximation. Prepared by the Eastern Canada Soil and Water Conservation Center. Edmundston, Canada. Technical Publication Number: NBSWCC-PRC 2010-01. * GeoNB, 2015. Forest soils. Available at: [http://www.snb.ca/geonb1/e/dc/catalogue-E.asp](http://www.snb.ca/geonb1/e/dc/catalogue-E.asp) * Natural Resources Canada, Canadian Forest Service, 2021. Statistical data, forest management (New Brunswick), 1990–2020. Available at: [https://cfs.nrcan.gc.ca/statsprofile/forest/NB](https://cfs.nrcan.gc.ca/statsprofile/forest/NB). The ground layer indicator method used in this paper is described in :  * Smith, R.J., Benavides, J.C., Jovan, S., Amacher, M., McCune, B., 2015. A rapid method for landscape assessment of carbon storage and ecosystem function in moss and lichen ground layers. The Bryologist 118, 32–45. [https://doi.org/10.1639/0007-2745-118.1.032](https://doi.org/10.1639/0007-2745-118.1.032)