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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Velocity-based macrorefugia indices for Canadian tree species

Authors: Campbell, Elizabeth; Wang, Tongli; Raymundo Sanchez, Angeles Ana Paula; Stralberg, Diana;

Velocity-based macrorefugia indices for Canadian tree species

Abstract

Velocity-based macrorefugia indices for Canadian tree species Data description Velocity-based microrefugia metrics for 25 North American tree species (15 eastern, 10 western) were developed for three future time periods (2011-2040, 2041-2070, 2071-2100), four greenhouse gas emission scenarios (SSP1.26, SSP2.45, SSP3.70, and SSP5.85), and 13 global climate models (ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM-ESM2-1, EC-Earth3, GFDL-ESM4, GISS-E2-1-G, INM-CM5-0, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL) based on species distribution model projections by Campell and Wang (2024) and using the approach described in Stralberg et al. (2018). Each species distribution projection was reclassified into presence/absence using the threshold suggested by Zhao et al. (2023). Backward and forward biotic velocity (Carroll et al., 2015) for each species was calculated using the nearest-analog velocity algorithm defined by Hamann et al. 2015 and applied to binary presence/absence rasters representing current and projected future distributions. Presence thresholds were based on mean probability of occurrence in the baseline period. To convert biotic velocity into an index of microrefugia ranging from 0 to 1, a distance-decay function was applied to the distance value at each pixel, i.e., the shortest distance from a projected future location to the current distribution. The distance-decay function was based on a fat-tailed distribution (c= 0.5, and alpha = 8333.33) parameterized to result in a mean migration rate of 500 m/year or 50 km/century (details in Stralberg et al. 2018). Refugia index values were calculated separately for each GCM and then averaged to produce an overall index. Code (updated from Stralberg et al. 2018) is available at: https://doi.org/10.5281/zenodo.14662106 Macrorefugia indices are provided as GeoTIFFs with a 1-km resolution (East or West folders), and map images are provided in PNG format (refugiaTreeMaps folder). All data layers are in the Albers Conic Equal Area projection (EPSG: 102008). Files are named as follows: Spp_TypeRefugia_X_Y_Z where: Spp = tree species seven-letter code (eastern)* or common name (western)** Type = backward or forward refugia X = baseline Y= shared socioeconomic pathway (SSP1.26, SSP2.45, SSP3.70, and SSP5.85) Z = year (2040, 2070, 2100) *Eastern tree species codes: ABIEBAL = Abies balsamea (balsam fir) ACERRUB = Acer rubrum (red maple) ACERSAC = Acer saccharum (sugar maple) BETUALL = Betula alleghaniensis (yellow birch) FAGUGRA = Fagus grandifolia (American beech) LARILAR = Larix laricina (tamarack) PICEENE = Picea engelmannii (Engelmann spruce) PICEGLA = Picea glauca (white spruce) PICEMAR = Picea mariana (black spruce) PICERUB = Picea rubens (red spruce) PINUBAN = Pinus banksiana (jack pine) PINURES = Pinus resinosa (red pine) PINUSTR = Pinus strobus (eastern white pine) POPUTRE = Populus tremuloides (trembling aspen) THUJOCC = Thuja occidentalis (eastern white-cedar) **Western tree species comon names Douglas-fir = Pseudotsuga menziesii Engelmann spruce = Picea engelmannii grand fir = Abies grandis lodgepole pine = Pinus contorta Pacific silver fir = Abies amabilis red alder = Alnus rubra Sitka spruce = Picea sitchensis subalpine fir = Abies lasiocarpa western hemlock = Tsuga heterophylla western redcedar = Thuja plicata References Carroll, C., Lawler, J. J., Roberts, D. R., & Hamann, A. (2015). Biotic and Climatic Velocity Identify Contrasting Areas of Vulnerability to Climate Change. PLOS ONE, 10(10), e0140486. https://doi.org/10.1371/journal.pone.0140486 Hamann, A., Roberts, D. R., Barber, Q. E., Carroll, C., & Nielsen, S. E. (2015). Velocity of climate change algorithms for guiding conservation and management. Global Change Biology, 21(2), 997–1004. https://doi.org/10.1111/gcb.12736 Stralberg, D., Carroll, C., Pedlar, J. H., Wilsey, C. B., McKenney, D. W., & Nielsen, S. E. (2018). Macrorefugia for North American trees and songbirds: Climatic limiting factors and multi-scale topographic influences. Global Ecology and Biogeography, 27(6), 690–703. https://doi.org/10.1111/geb.12731 Wang, T., & Campbell, E. (2024). Climate niche model projections for Canadian Tree species. https://climatena.ca/mapVersion Zhao, Y., O’Neill, G.A., and Wang, T. (2023). Predicting fundamental climate niches of forest trees based on species occurrence data. Ecological indicators, 148. https://doi.org/10.1016/j.ecolind.2023.110072

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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