This readme.txt file was generated on 2020/05/14 by Erin O'Connell and Jessica Savage ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Plant phenology, growth, freezing damage, and carbon gain data observed from 2017 to 2018 on wood plants growing at Bagley Nature Area in Duluth, MN 2. Author Information Principal Investigator Contact Information Name: Jessica A. Savage Institution: University of Minnesota Address: 1035 Kirby Drive, 207 Swenson Science Building, Duluth, MN 55812 Email: jsavage@d.umn.edu ORCID: 0000-0002-7756-7166 First Author Contact Information Name: Erin O'Connell Institution: University of Minnesota Address: 1035 Kirby Drive, 207 Swenson Science Building, Duluth, MN 55812 Email: oconn877@d.umn.edu ORCID: 0000-0002-7983-7959 3. Date of data collection (single date, range, approximate date) 2017/02/16-2018/11/11 4. Geographic location of data collection (where was data collected?): Bagley Nature Area, Duluth, MN 5. Information about funding sources that supported the collection of the data: National Science Foundation (IOS:1656318), the University of Minnesota – Duluth, and the Integrated Biosciences Graduate Program -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: Manuscript copyright held by Biological Invasions. 2. Links to publications that cite or use the data: O'Connell, E. and Savage, J. (2020). Extended leaf phenology has limited benefits for invasive species growing at northern latitudes. Biological Invasions 22(10): 2957-2974. https://doi.org/10.1007/s10530-020-02301-w 3. Links to other publicly accessible locations of the data: None 4. Links/relationships to ancillary data sets: None 5. Was data derived from another source? If yes, list source(s): Yes, data in the file "Freezing," under the variables "Native_distribution_min_temp" and "Exotic_distribution_min_temp" were derived from: GBIF.org (2018). GBIF Home Page. https://www.gbif.org [8 JUN 2018] Fick SE, Hijmans RJ. (2017). Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. Int J Climatol 37(12):4302–4315. doi: 10.1002/joc.5086 6. Recommended citation for the data: O'Connell, E. and Savage, J. (2020). Plant phenology, growth, freezing damage, and carbon gain data observed from 2017 to 2018 on wood plants growing at Bagley Nature Area in Duluth, MN. Retrieved from the Data Repository for the University of Minnesota. https://doi.org/10.13020/5dp7-5a20. -------------------- DATA & FILE OVERVIEW -------------------- 1. File List A. Filename: Freezing Short description: This file contains data on freezing damage and minimum temperatures in the species' native and exotic ranges. B. Filename: Phenology_and_growth Short description: This file contains data on spring and fall leaf phenology, branch and basal growth, and plant height. C. Filename: Carbon_gain_total Short description: This file contains data on photosynthetic light response curves, leaf area, and modeled seasonal carbon gain. D. Filename: Canopy_gain_daily Short description: This file contains data on daily leaf area and daily modeled carbon gain. 2. Relationship between files: All of these files are data collected during a two year project at Bagley Nature Area, Duluth MN investigating phenology, growth, freezing tolerance, and carbon gain of invasive and native shrubs. 3. Additional related data collected that was not included in the current data package: Yes, there there are two additional data packages: O'Connell, Erin and Savage, Jessica A. (2020). Understory light environment measured in 2017 and 2018 at Bagley Nature Area in Duluth, MN. O'Connell, Erin and Savage, Jessica A. (2020). Maximum carbon assimilation model for understory wood plants growing at Bagley Nature Area in Duluth, MN. 4. Are there multiple versions of the dataset? yes/no Yes, data in the files "Phenology_and_growth" and "Carbon_gain_total" are also included in the data package, O'Connell, Erin and Savage, Jessica A. (2020). Maximum carbon assimilation model for understory wood plants growing at Bagley Nature Area in Duluth, MN. -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: See descriptions under "Variable Lists" below and publication for details. A. Freezing To model the minimum temperature in each species' range, occurrence data was acquired from the Global Biodiversity Information Facility (GBIF.org) for all 8 species. The minimum temperature of the coldest month in those locations was aquired from WorldClim (WorldClim.org). Branches were cut underwater and 5-cm segments placed in water-filled rose tubes. The samples were frozen at -5°C per hour and held at a minimum temperature for three hours. One control from each individual remained at 7°C in the refrigerator. To assess freezing damage using electrolyte leakage, 1-cm stem segments were excised from the frozen and control young leaf samples and placed in test tubes with 10 mL of Milli-Q water. After 22-26 hours in a 22°C water bath, conductivity of all samples was measured. All samples were then autoclaved at 121°C for 20 minutes, incubated in the water bath for an additional 22-26 hours, and remeasured. To assess freezing damage using chlorophyll fluorescence, young and mature leaves were held at 7°C for 24 hours after freezing and dark adapted for at least two hours before measuring chlorophyll fluorescence with a mini-PAM II (Heinz Walz GmbH, Effeltrich, Germany). B. Phenology_and_growth Total stems per plant were counted for on ten plants per species in May 2018. Percent spring leaf development (five phenophases) and fall leaf senescence (leaf drop, color change, or photosystem function loss) were monitored weekly on ten plants per species in 2017 and 2018. Specific leaf area (SLA) was measured from 6-15 fully expanded leaves for on ten plants per species in summer 2017. Branch elongation was measured monthly (June, July, August, and November) on six new branches on ten plants per species in 2017. Basal diameter of the 1-3 largest stems per plant was measured at the widest point using calipers in June and September 2018. C. Carbon_gain_model_total and Carbon_gain_model_daily Photosynthetic light response curves were measured on six plants per species for immature/expanding leaves in early June and for mature leaves in mid-August 2017. Measurements were made on sun leaves between 8am and 2pm during sunny days using a portable gas exchange system (6400, LI-COR, Lincoln, NE) with a red-blue light source (6400-02B). Leaf area was measured on 6-15 fully expanded leaves for ten plants per species in summer 2017. Leaves were scanned and measured using imageJ. Total number of leaves were estimated for six plants per species in August 2017. Total number of stems per plant were counted for six plants per species in May 2018. 2. Methods for processing the data: See descriptions under "Variable Lists" below and publication for details. A. Freezing: Climatic suitability was modeled with Maxent based on the coldest temperatures in known locations for each species' native and exotic (if applicable) ranges. Freezing damage measured with electrolyte leakage was estimated using the index of injury. The lethal temperature at which the tissue experienced 50% of maximum freezing damage (LT50) was determined by fitting a 3-parameter logistic curve in JMP or a self-starting nonlinear least squares logistic model in R, with temperature predicting freezing damage. Measurements were standardized relative to the maximum measured damage. B. Phenology_and_growth: Phenological event dates were determined by fitting self-starting models in R (bud burst: gaussian models; leaf out and senescence: logistic models) and extrapolating the date when the plant reached the relevant percent threshold. Specific leaf area (SLA) is leaf area (measurements taken in imageJ on scanned leaves) divided by dry leaf mass. C. Carbon_gain_model_total and Carbon_gain_model_daily: Maximum carbon assimilation was modeled in R. Photosynthetic light response curves were fit in R with a non-rectangular hyperbola using least squares regression. Daily light levels were then multiplied by carbon assimilation rates from light response curves. The resulting daily carbon gain was multiplied by total leaf area and corrected in the spring for expanding leaves and in the fall for senescing leaves. Daily carbon gain was partioned into seasonal carbon gain based on overstory canopy openness. 3. Instrument- or software-specific information needed to interpret the data: NA 4. Standards and calibration information, if appropriate: NA 5. Environmental/experimental conditions: Measurements in the file "Carbon_gain_total" (variables under II. Photosynthetic light response curves) were made between 8am and 2pm on sunny days. The auto program LightCurve was used with 10 light levels between 0 and 2000 μmol photons s-1 m-2. The following conditions were maintained: leaf temperature = 20°C, CO2 concentration = 400 μmol mol-1, water content = 12-15 mmol, and flow rate = 50 – 200 μmol s-1. 6. Describe any quality-assurance procedures performed on the data: All data entry was double checked. 7. People involved with sample collection, processing, analysis and/or submission: Erin O'Connell, Jessica Savage, Alex Peichel, Natalie McMann, Collin Monette, Kennedy Mosher, Thomas Kiecker, Max Bonfig, Shauna Blake, Sydney Hudzinski, Rishika Quick-Singh, and Nihaar Joshi --------------------------------------- DATA-SPECIFIC INFORMATION FOR: Freezing --------------------------------------- 1. Number of variables: 7 2. Number of cases/rows: 8 3. Missing data codes: Code/symbol: NA Definition: Data not available. 4. Variable List A. Name: Species Description: Scientific name of the species [Genus_species]. B. Name: Status Description: Origin of the species. Species native to North America are designated as "native," and species native to Europe or Asia and invasive in North America are designated as "invasive." C. Name: Native_distribution_min_temp Description: Coldest temperature [degrees Celsius] during the coldest month in each species' native range. Values are from climate suitability models built in Maxent based on known locations. D. Name: Exotic_distribution_min_temp Description: Coldest temperature [degrees Celsius] during the coldest month in each invasive species' North American range. Values are from climate suitability models built in Maxent based on known locations. E. Name: Young_leaf_LT50_EL Description: Lethal temperature [degrees Celsius] at which young leaves experienced 50% of maximum freezing damage, as assessed with electrolyte leakage. F. Name: Young_leaf_LT50_CF Description: Lethal temperature [degrees Celsius] at which young leaves experienced 50% of maximum freezing damage, as assessed with chlorophyll fluorescence. G. Name: Mature_leaf_LT50_CF Description: Lethal temperature [degrees Celsius] at which mature leaves experienced 50% of maximum freezing damage, as assessed with chlorophyll fluorescence. --------------------------------------------------- DATA-SPECIFIC INFORMATION FOR: Phenology_and_growth --------------------------------------------------- 1. Number of variables: 14 2. Number of cases/rows: 80 3. Missing data codes: Code/symbol: NA Definition: Data not available. 4. Variable List I. General A. Name: Species Description: Scientific name of the species [Genus_species]. B. Name: Plant_ID Description: Unique number given to each plant observed in the study. C. Name: Status Description: Origin of the species. Species native to North America are designated as "native," and species native to Europe or Asia and invasive in North America are designated as "invasive." D. Name: Plant_height Description: Plant height [cm] measured during fall 2018 using transect tape. E. Name: Stem_count Description: Number of stems counted in spring of 2017. F. Name: SLA Description: Specific leaf area [cm^2 g^-1] measured during summer 2017. II. Leaf phenology G. Name: Julian_day_budburst_2017 Description: Julian day when 30% of the buds exhibited visible green leaf tips in 2017. Values were interpolated from self-starting gaussian models fit to weekly observations in R. Days were rounded to nearest whole number. H. Name: Julian_day_leafout_2017 Description: Julian day when 30% of the leaves were reflexed and petioles were extended in 2017. Values were interpolated from self-starting nonlinear least squares logistic models fit to weekly observations in R. Days were rounded to nearest whole number. I. Name: Julian_day_75%_leaf_senescence_2017 Description: Julian day when 75% of the leaves senesced (i.e. dropped, changed color, and/or lost photsystem function) in 2017. Values were interpolated from self-starting nonlinear least squares logistic models fit in R to weekly percent senescence observations. Days were rounded to nearest whole number. J. Name: Julian_day_budburst_2018 Description: Julian day when 30% of the buds exhibited visible green leaf tips in 2018. Values were interpolated from self-starting gaussian models fit in R. Days were rounded to nearest whole number. K. Name: Julian_day_leafout_2018 Description: Julian day when 30% of the leaves were reflexed and petioles were extended in 2018. Values were interpolated from self-starting nonlinear least squares logistic models fit in R. Days were rounded to nearest whole number. L. Name: Julian_day_75%_leaf_senescence_2018 Description: Julian day when 75% of the leaves senesced (i.e. dropped, changed color, and/or lost photsystem function) in 2018. Values were interpolated from self-starting nonlinear least squares logistic models fit in R to weekly percent senescence observations. Days were rounded to nearest whole number. III. Growth M. Name: Branch_AGR Description: Absolute growth rate (AGR) of branch length [mm day^-1]. Branch elongation was measured monthly in 2017 (June to November) and fit to asymptotic curves in R. The resulting asymptote was used as the total branch length when calculating AGR according to the equation: AGR = Branch_Length / (Julian_day_50%_leaf_senescence - Julian_day_leaf_emergence). N. Name: Basal_RGR Description: Relative growth rate (RGR) of basal area [ln mm^2 day^-1]. Diameters of the 1-3 largest stems were measured in the widest direction in June and September 2018. Diameters were converted to area, averaged, multiplied by Stem_count, and then used to calulated RGR, according to the equation RGR = (ln(Area_Sep) - ln(Area_Jun)) / (Date_Sep - Date_Jun). Negative growth rates were replaced with zeros. ------------------------------------------------ DATA-SPECIFIC INFORMATION FOR: Carbon_gain_total ------------------------------------------------ 1. Number of variables: 20 2. Number of cases/rows: 47 3. Missing data codes: Code/symbol: NA Definition: Data not available. 4. Variable List I. General A. Name: Species Description: Scientific name of the species [Genus_species]. B. Name: Plant_ID Description: Unique number given to each plant observed in the study. II. Photosynthetic light response curves C. Name: Young_leaf_Amax Description: Maximum carbon assimilated [umol CO2 m^-2 s^-1] at high light levels by young sun leaves in June 2017. Light response curves were fit in R with a non-rectangular hyperbola using least squares regression. D. Name: Young_leaf_quantYld Description: Quantum yield [mol CO2 mol photon^-1] of young leaves measured in June 2017. This is the initial slope during the light limiting portion of the light response curve. E. Name: Young_leaf_Rd Description: Dark respiration rate [umol CO2 m^-2 s^-1] of young leaves measured in June 2017. This is the absolute value of the y-intercept of the light response curve. F. Name: Young_leaf_theta Description: Dimensionless curvature parameter of photosynthetic light response curves for young leaves measured in June 2017. G. Name: Mature_leaf_Amax Description: Maximum carbon assimilated [umol CO2 m^-2 s^-1] at high light levels by mature sun leaves in August 2017. Light response curves were fit in R with a non-rectangular hyperbola using least squares regression. H. Name: Mature_leaf_quantYld Description: Quantum yield [mol CO2 mol photon^-1] of mature leaves measured in August 2017. This is the initial slope during the light limiting portion of the light response curve. I. Name: Mature_leaf_Rd Description: Dark respiration rate [umol CO2 m^-2 s^-1] of mature leaves measured in August 2017. This is the absolute value of the y-intercept of the light response curve. J. Name: Mature_leaf_theta Description: Dimensionless curvature parameter of photosynthetic light response curves for mature leaves measured in August 2017. III. Leaf area K. Name: Leaf_count Description: Number of leaves per plant counted in August 2017. L. Name: Ave_leaf_area Description: Average leaf area [cm^2] of 6-15 fully expanded leaves per plant collected summer 2017. Individual leaf area was measured in imageJ from scanned leaves. M. Name: Total_leaf_area Description: Total leaf area [m^2] per plant; the product of Leaf_count multiplied by Ave_leaf_area and converted to meters. V. Carbon gain N. Name: Spring_C_gain Description: Modeled total carbon gain [mol CO2 plant^-1 season^-1] in the spring, before the overstory canopy closes. O. Name: Summer_C_gain Description: Modeled total carbon gain [mol CO2 plant^-1 season^-1] in the summer, after the overstory canopy closes and before the overstory canopy reopens. P. Name: Fall_C_gain Description: Modeled total carbon gain [mol CO2 plant^-1 season^-1] in the fall, after the overstory canopy reopens. Q. Name: Total_C_gain Description: Modeled total carbon gain [mol CO2 plant^-1 year^-1] during a one year. R. Name: Percent_spring_C_gain Description: Relative proportion of modeled yearly carbon gained in the spring, before the overstory canopy closes. S. Name: Percent_summer_C_gain Description: Relative proportion of modeled yearly carbon gained in the summer, after the overstory canopy closes and before the overstory canopy reopens. T. Name: Percent_fall_C_gain Description: Relative proportion of modeled yearly carbon gained in the fall, after the overstory canopy reopens. ------------------------------------------------ DATA-SPECIFIC INFORMATION FOR: Carbon_gain_daily ------------------------------------------------ 1. Number of variables: 11 2. Number of cases/rows: 10,899 3. Missing data codes: Code/symbol: NA Definition: Data not available. 4. Variable List A. Name: Species Description: Scientific name of the species [Genus_species]. B. Name: Plant_ID Description: Unique number given to each plant included in the carbon gain model. C. Name: Date Description: Date [MM/DD/YYYY] model input. D. Name: Julian_day Description: Day of the year [104 - 344] model input. E. Name: Leaf_age Description: Leaf age based on percent leaf expansion: YOUNG < 95% expanded and MATURE > 95% expanded. Leaf age determines whether the June (YOUNG) or August (MATURE) light response curves were used as inputs for calculating carbon gain on a given day. F. Name: Season Description: Season based on percent overstory canopy openness: SPR (spring) > 25 % canopy openness, SUM (summer) < 25% canopy openness, and FALL (autumn) > 25 % canopy openness. G. Name: Total_leaf_area Description: Total leaf area [m^2] per plant; the product of total leaf area multiplied by average leaf area. H. Name: Aday Description: Modeled daily carbon gain [mol CO2 m^-2 day^-1], not accounting for leaf area. I. Name: Aleaf Description: Modeled daily carbon gain per leaf [mol CO2 leaf^-1 day^-1], not accounting for leaf number. J. Name: Aplant Description: Modeled total carbon gain per plant [mol CO2 plant^-1 day^-1]. This variable was reported in the publication (Fig. 4). K. Name: Astem Description: Modeled total carbon gain per stem [mol CO2 stem^-1 day^-1]. Calculated by dividing Aplant by number of stems.