DOI: 10.5061/dryad.kprr4xhdg
title: Data from: The role of migration in the change of Northern Hemisphere vegetation for the past 50,000 years

description: Our primary aim was to assess how dispersal limitation affected forest
 changes in the Northern Hemisphere during the last glacial cycle, and
 especially after the last deglaciation. We used the LPJ-GM 2.0 dynamic
 global vegetation model to simulate the vegetation dynamics of the
 Northern Hemisphere over the past 50,000 years. We compared two dispersal
 modes by allowing establishment as soon as suitable environmental
 conditions were realised (free dispersal), or by additionally constraining
 establishment based on potential migration speed and maturation time
 (dispersal limitation). For both dispersal modes, we inferred
 (mega-)biomes and calculated the fraction of forest cover, earliest
 post-glacial forest establishment, and the difference between dispersal
 modes (dispersal lag). To evaluate our results, we compared simulated tree
 cover with pollen-based reconstructions of European Holocene vegetation
 and of North American vegetation since the Last Glacial Maximum. We
 simulated multi-millennial dispersal lags in post-glacial establishment of
 temperate forests in Europe, boreal forests in Central Siberia, and
 scattered forest areas close to mountain chains (Rocky Mountains and north
 of Himalaya). Overall, the simulation with limited dispersal had lower
 forest extents compared to the free-dispersal simulation, especially after
 the Last Glacial Maximum, with greater mismatches following intervals of
 rapid warming, notably the onsets of GI-1 and the Holocene. Comparisons
 with pollen-based reconstructions showed that the simulation with limited
 dispersal better captured both the expansion of European temperate trees
 and the distribution of broadleaved and needleleaved trees in North
 America during the early Holocene. The lag in response of forests to rapid
 climate change has implications for past ecosystems and projections of
 future ecosystem services.
description: # Data from: The role of migration in the change of Northern Hemisphere
 vegetation for the past 50,000 years The dataset contains the input/output
 data and R code associated with the article "The role of migration in
 the change of Northern Hemisphere vegetation for the past 50,000
 years". ## Description of the data and file structure The dataset
 contains: * **analysis.R**: the R script to perform all analyses and
 generate all output figures and tables (stored in **/out_data.zip/**)
 included in the manuscript; the code contains the directory paths (and
 links) to the input data necessary to perform the analysis and informative
 comments; * **T_ann_60_0_kya.txt**: post-processed annual temperature
 (Kelvin) used in the biomization procedure (unprocessed data is the
 original paleo-climate; see **Sharing/Access information** below);
 "NA" (not applicable) refer to cells underwater; *
 **/out_data.zip/**: contains all output tables generated in the analysis
 via **analysis.R**; the output tables are comma-separated values (CSV): *
 **BiomeInference_domPFT_50_0ka.csv**: inference of biome, mega-biome, Land
 Cover Type (LCT) and dominant Plant Functional Type (PFT). Each row
 indicates a grid cell (lon-lat coordinate). Variables include: dispersal
 scenario of the simulation (either "Free Dispersal" or
 "Dispersal Limitation"); longitude (Lon) and latitude (Lat) in
 degrees; year of the simulation in years before present BP (Year);
 simulated leaf area index (LAI, unitless) of each PFT (from BNE until C4G)
 and their total (Total) extracted from **/simulations/.../lai.out**;
 boolean for the landmask, whether active (1, vegetated grid cell) or
 inactive (0, under ice or water, i.e. unvegetated); total carbon mass
 (Cmass, kg/m2) extracted from **/simulations/.../cmass.out**; aggregated
 PFTs used in the biome inference (B-tree and Tr-shrub); mean annual
 temperature used to distinguish Tundra and Desert (T_ann) extracted from
 **T_ann_60_0_kya.txt**; area of the grid cell in km2 (GridArea); threshold
 of carbon biomass used in the assignment of low-carbon biomes (CMass_thr,
 kg/m2); inferred biome (Biome); inferred mega-biome (Mega-Biome); inferred
 Land Cover Type (LCT); PFT with the highest LAI (Dominant PFT);
 "NA" (not applicable) in T_ann refer to cells underwater; *
 **BiomeInference_domPFT_slices_averNeig.csv**: inference of biome,
 mega-biome, Land Cover Type (LCT) and dominant PFT after calculating the
 average LAI-PFT values in the Moore neighborhood. Variables as above. *
 **CoverIncrease_maxima_H_BA.csv**: rate of increase in forest cover
 (Increase, in percentage) and time-point of stable forest cover across the
 Holocene (Peak, in years BP) for each scenario (Dispersal scenario:
 "Free Dispersal", or "Dispersal Limitation"), forest
 type (LCT: "Boreal Forest", "Temperate Forest") and
 area (Area: "Northern Hemisphere", "Asia",
 "Europe", "North America"), for two relevant time
 periods of rapid climate warming (Period: Holocene "H", or
 Bolling-Allerod "BA"); forest cover is calculated from Cmass and
 GridArea from **BiomeInference_domPFT_50_0ka.csv**; *
 **ForestThermalChange_LGM_LH.csv**: average and standard deviation of
 forest cover in percentage (cover_mean_LGM, cover_sd_LGM; cover_mean_LH,
 cover_sd_LH) and average and standard deviation temperature in degC
 (T_mean_LGM, T_sd_LGM; T_mean_LH, T_sd_LH) for the Last Glacial Maximum
 (LGM) and the Late Holocene (LH), and forest change (cover_change) and
 thermal difference (T_change) between the LGM and the LH, for each region
 (Area: "Northern Hemisphere", "Asia",
 "Europe", "North America"), forest type (Forest type:
 "Forest","Boreal Forest","Temperate Forest")
 and dispersal scenario ("Free Dispersal", or "Dispersal
 Limitation"); variables of forest cover are derived from
 **CoverIncrease_maxima_H_BA.csv**; temperature variables are calculated
 from the input paleo-climate (see **Sharing/Access information** below);
 "LGM" = Last Glacial Maximum; "LH" = Late Holocene; *
 **LCT_FractionBiomes_TemperatureAnomaly_NH_AS_EU_Am_500yrs.csv**: fraction
 of grid cell area (FracArea) and fraction of grid cells (FracGrid_nr)
 occupied by forest type (LCT and Mega-biomes) across different areas
 (Area: "Northern Hemisphere", "Asia",
 "Europe", "North America"), and dispersal scenario
 ("Free Dispersal", or "Dispersal Limitation") each 500
 years time-slice (Year). Added variables used in the calculation of
 fractions: total carbon mass (Cmass, kg/m2), area of the grid cell in km2
 (GridArea), number of grid cells (P.n), are extracted from
 **BiomeInference_domPFT_50_0ka.csv**. Temperature variables in degC: mean
 temperature (Temperature (Mean)), standard deviation (Temperature (S.D.)),
 temperature anomaly (Temperature Anomaly), are extracted/calculated from
 **TemperatureAnomaly_NH_AS_EU_Am_100yrs.csv**; *
 **MinimumEstablishment_LCT_MegaBiomeForests.csv**: first year of forest
 establishment (in years BP) after the LGM for boreal forest (Minimum
 Boreal Forest), temperate forests (Minimum Temperate Forest), and forests
 in general (Minimum Forest) for the two dispersal scenarios (Dispersal
 scenario: "Free Dispersal", or "Dispersal
 Limitation"). Each row indicates a grid cell (Lon / Lat); post-LGM
 establishment values are calculated from
 **BiomeInference_domPFT_50_0ka.csv**; "NA" values in Minimum
 correspond to uncolonized cells; * **REVEALS_Models_LCTs.csv**: cover
 comparison (x.diff) as difference between simulated values (x.perc) and
 REVEALS estimates (x.perc_REVEAL) of for different Land-Cover Types (x:
 OL=open land; ET=evergreen trees; ST=summergreen trees; BF=boreal forests;
 TF=temperate forests; Forest=all kinds of forests). Simulated values of
 cover percentage (x.perc) are calculated by summing the Fractional Plant
 Cover (FPC) of each LCT-equivalent PFT, where the calculation is based on
 LAI values from **/simulations/.../lai.out** for the two dispersal
 scenarios (Dispersal scenario: "Free Dispersal", or
 "Dispersal Limitation") and averaged for each REVEAL time-window
 (mid-point: Year_mid, in range: Year_lower-Year_upper). The REVEALS
 estimates (x.perc_REVEAL) overlapping the simulated grid cells (Lon / Lat)
 are extracted from the REVEALS product (see **Sharing/Access information**
 below); * **TemperatureAnomaly_NH_AS_EU_Am_100yrs.csv**: mean (Mean) and
 standard (SD) deviation of temperature in degC across areas (Area:
 "Northern Hemisphere", "Asia", "Europe",
 "North America") at each 100 years time-slice (Year) for the two
 dispersal scenarios (Dispersal scenario: "Free Dispersal", or
 "Dispersal Limitation"). Mean and SD are calculated from the
 input paleo-climate (see **Sharing/Access information** below); *
 **/simulations.zip/**: formatted output of the LPJ-GM simulations for the
 free dispersal mode (**/FREEDISP.zip/**) and the dispersal-limited mode
 (**/FIXSPEED.zip/**) used as input data in the **analysis.R**; the
 formatted output consists of leaf area index, unitless (lai.out) and
 carbon mass, kg/m2 (cmass.out) averaged each 50 years (model output
 setting) and covering the simulation domain at 0.5 degrees resolution; the
 output is organized in sub-folders at 5000-years intervals from the start
 of the simulation (slice_51000_45050, meaning from 51,000 until 45,050
 years BP) until the end of the simulation (slice_5000_50; meaning from
 5,000 until 50 years BP); * **lai.out** / **cmass.out**: each row
 indicates a grid cell (lon-lat coordinate). Variables include: longitude
 (Lon) and latitude (Lat) in degrees; year of the simulation in years
 before present BP (Year); simulated leaf area index (**lai.out**) / carbon
 mass (**cmass.out**) of each PFT (from BNE until C4G) and their total
 (Total). ## Acronyms for Plant Functional Types (PFTs) * BNE: boreal
 needle-leaved shade-tolerant evergreen tree * BINE: boreal needle-leaved
 shade-intolerant evergreen tree * BNS: boreal needle-leaved
 shade-intolerant summergreen tree * BIBS: boreal broad-leaved
 shade-intolerant summergreen tree * TeNE: temperate needle-leaved
 shade-intolerant evergreen tree * TeBS: temperate broad-leaved
 shade-tolerant summergreen tree * TeIBS: temperate broad-leaved
 shade-intolerant summergreen tree * TeBE: temperate broad-leaved
 shade-tolerant evergreen tree * BESh: boreal broad-leaved shade-intolerant
 evergreen shrub * BSSh: boreal broad-leaved shade-intolerant summergreen
 shrub * TeESh: temperate broad-leaved shade-intolerant evergreen shrub *
 TeRSh: temperate broad-leaved shade-intolerant raingreen shrub * TeSSh:
 temperate broad-leaved shade-intolerant summergreen shrub * TrESh:
 tropical broad-leaved shade-intolerant evergreen shrub * TrRSh: tropical
 broad-leaved shade-intolerant raingreen * TrBE: tropical broad-leaved
 shade-tolerant evergreen tree * TrIBE: tropical broad-leaved
 shade-intolerant evergreen tree * TrBR: tropical broad-leaved
 shade-tolerant raingreen tree * C3G: cool season grass * C4G: warm season
 grass ## Sharing/Access information Links to the external sources (and
 associated publications) used in the analysis of **analysis.R** (see also
 initial comment in the code) to generate datasets in **/out_data.zip/**
 (see above). *
 [https://catalogue.ceda.ac.uk/uuid/4ca242208e904efe830af45f1697f730](https://catalogue.ceda.ac.uk/uuid/4ca242208e904efe830af45f1697f730): input paleo-climate and landscape data from "Armstrong, E., Hopcroft, P. O., & Valdes, P. J. (2019a). A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years. Scientific Data, 6(1), 265." * [https://doi.org/10.1594/PANGAEA.937075](https://doi.org/10.1594/PANGAEA.937075): European pollen-based REVEALS land-cover reconstructions for the Holocene from: Githumbi, E., Fyfe, R., Gaillard, M. J., Trondman, A. K., Mazier, F., Nielsen, A. B., Poska, A., Sugita, S., Woodbridge, J., Azuara, J., Feurdean, A., Grindean, R., Lebreton, V., Marquer, L., Nebout-Combourieu, N., Stančikaite, M., Tanţǎu, I., Tonkov, S., Shumilovskikh, L., ... Zernitskaya, V. (2022). European pollen-based REVEALS land-cover reconstructions for the Holocene: Methodology, mapping and potentials. Earth System Science Data, 14(4), 1581-1619. [https://doi.org/10.5194/essd-14-1581-2022](https://doi.org/10.5194/essd-14-1581-2022) Corresponding author: Dr. Veiko Lehsten ([https://orcid.org/0000-0002-0649-0042](https://orcid.org/0000-0002-0649-0042))