Table 1: Metadata for the 12 paleoclimate proxies.

Location Plot Proxy Latitude Longitude Temporal resolution DOI Reference
Eastern Beringia
United States of America 		1 pollen 62.5 -137.5 100.6 https://doi.org/10.1139/E08-036 A. E. Viau, K. Gajewski, M. C. Sawada, J. Bunbury, Low- and high-frequency climate variability in eastern Beringia during the past 25,000 years. Canadian Journal of Earth Sciences 45, 1435-1453 (2009)
NGRIP
Greenland 		2 d18O 75.1 -42.3 20.0 https://doi.org/10.1016/j.quascirev.2006.08.002
https://doi.org/10.1016/j.quascirev.2007.01.016 		Andersen, K. K. et al., The Greenland Ice Core Chronology 2005, 15–42ka. Part 1: constructing the time scale. Quaternary Science Reviews 25, 3246-3257 (2006)
S. O. Rasmussen et al., Synchronization of the NGRIP, GRIP, and GISP2 ice cores across MIS 2 and palaeoclimatic implications. Quaternary Science Reviews 27, 18-28 (2008)
Cariaco Basin
Venezuala 		3 Mg/Ca 10.7 -65.0 109.9 https://doi.org/10.1126/science.1088470 D. W. Lea, D. K. Pak, L. C. Peterson, K. A. Hughen, Synchroneity of Tropical and High-Latitude Atlantic Temperatures over the Last Glacial Termination. Science 301, 1361 (2003).
Western tropical Atlantic
Brazil 		4 Mg/Ca -4.6 -36.6 111.5 https://doi.org/10.1016/j.epsl.2005.11.012 S. Weldeab, R. R. Schneider, M. Kölling, Deglacial sea surface temperature and salinity increase in the western tropical Atlantic in synchrony with high latitude climate instabilities. Earth and Planetary Science Letters 241, 699-706 (2006).
Chilean margin
Chile 		5 UK’37 -41.0 -74.5 112.3 https://doi.org/10.1016/j.epsl.2007.04.040 F. Lamy et al., Modulation of the bipolar seesaw in the Southeast Pacific during Termination 1. Earth and Planetary Science Letters 259, 400-413 (2007).
Nile Delta
Egypt 		6 TEX86 31.7 34.1 316.3 https://doi.org/10.1029/2009PA001740 I. S. Castañeda et al., Millennial-scale sea surface temperature changes in the eastern Mediterranean (Nile River Delta region) over the last 27,000 years. Paleoceanography 25, (2010).
Lake Tanganyika
Africa 		7 TEX86 -6.7 29.6 221.4 https://doi.org/10.1126/science.1160485 J. E. Tierney et al., Northern Hemisphere Controls on Tropical Southeast African Climate During the Past 60,000 Years. Science 322, 252 (2008).
Chinese loess plateau
China 		8 MBT/CBT 34.9 113.3 397.4 https://doi.org/10.1016/j.epsl.2010.11.010 F. Peterse et al., Decoupled warming and monsoon precipitation in East Asia over the last deglaciation. Earth and Planetary Science Letters 301, 256-264 (2011).
Western Pacific
Phillipines 		9 Mg/Ca 6.3 125.8 56.4 https://doi.org/10.1126/science.1143791 L. Stott, A. Timmermann, R. Thunell, Southern Hemisphere and Deep-Sea Warming Led Deglacial Atmospheric CO2
Rise and Tropical Warming. Science 318, 435 (2007).
EDML
Antarctica 		10 d18O -75.0 0.0 102.6 https://doi.org/10.1016/j.quascirev.2009.11.010
https://doi.org/10.1016/j.quascirev.2009.10.009 		B. Lemieux-Dudon et al., Consistent dating for Antarctic and Greenland ice cores. Quaternary Science Reviews 29, 8-20 (2010).
B. Stenni et al., The deuterium excess records of EPICA Dome C and Dronning Maud Land ice cores (East Antarctica). Quaternary Science Reviews 29, 146-159 (2010).
Vostok
Antarctica 		11 dD -78.5 108.0 62.0 https://doi.org/10.1038/20859 J. R. Petit et al., Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399, 429-436 (1999).
Campbell Island
New Zealand 		12 pollen -52.6 169.1 83.8 https://doi.org/10.1038/ngeo931 M. S. McGlone, C. S. M. Turney, J. M. Wilmshurst, J. Renwick, K. Pahnke, Divergent trends in land and ocean temperature in the Southern Ocean over the past 18,000 years. Nature Geoscience 3, 622-626 (2010).

Details describing transformation functions used to convert climate proxies to temperature are described by Shakun et al. (1) for all proxies, except Campbell Island.

Table 2: Overlap between past and future temperature signal-to-noise ratios for RCP 8.5.

Region Overlap
(RCP 8.5) 		Area
(km2) 		Areal overlap
(km2)
African 0.27 19432753 5246843
Amazonian 0.55 8287692 4558230
Arctico-Siberian 0.64 17240102 11033665
Australian 0.34 7527856 2559471
Chinese 0.00 2232470 0
Eurasian 0.72 20448270 14722755
Guineo-Congolian 0.04 4614996 184600
Indo-Malayan 0.07 2150789 150555
Japanese 0.04 370209 14808
Madagascan 0.00 597552 0
Mexican 0.19 1926517 366038
North American 0.28 16556111 4635711
Novozelandic 0.52 469512 244146
Oriental 0.12 6066726 728007
Panamanian 0.55 1302149 716182
Papua-Melanesian 0.05 1039170 51959
Saharo-Arabian 0.31 11174174 3463994
South American 0.36 9369852 3373147
Tibetan 0.00 2690192 0

Overlap data is based on data from (2), with areas calculated using a Mollweide equal area projection with a 278 km2 pixel resolution. The last column shows the estimated area of each zoogeographic region that is projected to have experienced past rates of temperature change that are historically similar to projections for the 21st century at a coarse regional scale (i.e., the scale of the zoogeographic region).

Table 3: Results of a literature search identifying simulated mechanisms of past climate-biodiversity dynamics.

Spatial scale Biol Organization Mortality Movement Speciation Adaptation Location System/Taxa DOI Reference
Local Gene #CC3300 #FFC000 Sky Islands, Western Rocky Mountains, USA Melanoplus oregonensis https://doi.org/10.1111/j.1365-294X.2010.04702.x L. L. Knowles, D. F. Alvarado-Serrano, Exploring the population genetic consequences of the colonization process with spatio-temporally explicit models: insights from coupled ecological, demographic and genetic models in montane grasshoppers. Mol Ecol 19, 3727-3745 (2010).
Local Gene #CC3300 #FFC000 Sky Islands, Western Rocky Mountains, USA Melanoplus oregonensis https://doi.org/10.1111/ecog.02893 L. L. Knowles, R. Massatti, Distributional shifts - not geographic isolation - as a probable driver of montane species divergence. Ecography 40, 1475-1485 (2017).
Local Individual #CC3300 St. Paul Island Mammuthus primigenius https://doi.org/10.1002/ecy.2524 Y. Wang et al., Mechanistic modeling of environmental drivers of woolly mammoth carrying capacity declines on St. Paul Island. Ecology 99, 2721-2730 (2018).
Local Individual #CC3300 Central Swiss Alps Vegetation https://doi.org/10.1111/j.1365-2745.2005.01072.x *C. Heiri, H. Bugmann, W. Tinner, O. Heiri, H. Lischke, A model-based reconstruction of Holocene treeline dynamics in the Central Swiss Alps. Journal of Ecology 94, 206-216 (2006).
Local Population #CC3300 Northern Australia Homo sapiens sapiens https://doi.org/10.1038/s41559-019-0902-6 *C. J. A. Bradshaw et al., Minimum founding populations for the first peopling of Sahul. Nat Ecol Evol 3, 1057-1063 (2019).
Local Ecosystem #CC3300 Northern Greece, Southern Italy Vegetation https://doi.org/10.1016/S0304-3800(99)00219-7 J. Guiot et al., Inverse vegetation modeling by Monte Carlo sampling to reconstruct palaeoclimates under changed precipitation seasonality and CO2 conditions: application to glacial climate in Mediterranean region. Ecological Modelling 127, 119-140 (2000).
Local Ecosystem #CC3300 Otago, New Zealand Vegetation https://doi.org/10.1023/A:1013199209388 G. M. J. Hall, M. S. McGlone, Forest reconstruction and past climatic estimates for a deforested region of south-eastern New Zealand. Landscape Ecology 16, 501-521 (2001).
Local Ecosystem #CC3300 Funza palaeolake, Colombia Vegetation https://doi.org/10.1016/S0031-0182(01)00350-9 R. Marchant, A. Boom, H. Hooghiemstra, Pollen-based biome reconstructions for the past 450 000 yr from the Funza-2 core, Colombia: comparisons with model-based vegetation reconstructions. Palaeogeography, Palaeoclimatology, Palaeoecology 177, 29-45 (2002).
Local Ecosystem #CC3300 12 sites in Colombia Vegetation https://doi.org/10.1002/jqs.878 R. Marchant et al., Colombian vegetation at the Last Glacial Maximum: a comparison of model- and pollen-based biome reconstructions. Journal of Quaternary Science 19, 721-732 (2004).
Local Ecosystem #CC3300 6 sites in Colombia Vegetation https://doi.org/10.1016/j.palaeo.2005.10.028 R. Marchant, J. C. Berrío, H. Behling, A. Boom, H. Hooghiemstra, Colombian dry moist forest transitions in the Llanos Orientales—A comparison of model and pollen-based biome reconstructions. Palaeogeography, Palaeoclimatology, Palaeoecology 234, 28-44 (2006).
Local Ecosystem #CC3300 Rukiga Highlands, Uganda Vegetation https://doi.org/10.5194/cp-5-431-2009 O. Flores, E. S. Gritti, D. Jolly, Climate and CO2 modulate the C3/C4 balance and δ13C signal in simulated vegetation. Climate of the Past 5, 431-440 (2009).
Local Ecosystem #CC3300 Lake Ngamakala (Congo), Lake Victoria (Uganda), Kuruyange (Burundi) Vegetation https://doi.org/10.5194/cp-6-169-2010 E. S. Gritti et al., Simulated effects of a seasonal precipitation change on the vegetation in tropical Africa. Climate of the Past 6, 169-178 (2010).
Local Ecosystem #CC3300 Holtjärnen (Sweden), and Nautajärvi (Finland) Vegetation https://doi.org/10.1111/j.1365-2699.2010.02296.x T. Giesecke et al., The effect of past changes in inter-annual temperature variability on tree distribution limits. Journal of Biogeography 37, 1394-1405 (2010).
Local Ecosystem #CC3300 Swiss Northwestern Alps Vegetation https://doi.org/10.1111/gcb.12456 C. Schworer, P. D. Henne, W. Tinner, A model-data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics. Glob Chang Biol 20, 1512-1526 (2014).
Local Ecosystem #CC3300 Stordalen (Sweden) and Mer Bleue (Canada) Peatlands https://doi.org/10.5194/bg-14-4023-2017 N. Chaudhary, P. A. Miller, B. Smith, Modelling past, present and future peatland carbon accumulation across the pan-Arctic region. Biogeosciences 14, 4023-4044 (2017).
Local Ecosystem #CC3300 Provence, France Vegetation https://doi.org/10.1016/j.quaint.2018.02.019 D. A. Contreras et al., From paleoclimate variables to prehistoric agriculture: Using a process-based agro-ecosystem model to simulate the impacts of Holocene climate change on potential agricultural productivity in Provence, France. Quaternary International 501, 303-316 (2019).
Regional Gene #CC3300 #FFC000 Western Australia Lerista lineopunctulata https://doi.org/10.1111/evo.12159 Q. He, D. L. Edwards, L. L. Knowles, Integrative testing of how environments from the past to the present shape genetic structure across landscapes. Evolution 67, 3386-3402 (2013).
Regional Gene #CC3300 #FFC000 Northern Western U.S.A Penstemon deustus https://doi.org/10.3732/ajb.1500117 J. L. Brown et al., Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes. Am J Bot 103, 153-163 (2016).
Regional Gene #CC3300 #FFC000 California Floristic Province Quercus chrysolepis https://doi.org/10.1111/mec.13804 J. B. Bemmels, P. O. Title, J. Ortego, L. L. Knowles, Tests of species-specific models reveal the importance of drought in postglacial range shifts of a Mediterranean-climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection. Mol Ecol 25, 4889-4906 (2016).
Regional Gene #CC3300 #FFC000 Central Rocky Mountains, USA Ochotona princeps https://doi.org/10.1111/j.1365-294X.2012.05640.x J. L. Brown, L. L. Knowles, Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika. Mol Ecol 21, 3757-3775 (2012).
Regional Gene #CC3300 #FFC000 Southern Rocky Mountains, USA Carex sp. https://doi.org/10.1111/mec.13735 R. Massatti, L. L. Knowles, Contrasting support for alternative models of genomic variation based on microhabitat preference: species-specific effects of climate change in alpine sedges. Mol Ecol 25, 3974-3986 (2016).
Regional Gene #CC3300 #FFC000 Grand Terre, New Caledonia Vegetation https://doi.org/10.1371/journal.pone.0183412 *R. Tournebize et al., Two disjunct Pleistocene populations and anisotropic postglacial expansion shaped the current genetic structure of the relict plant Amborella trichopoda. PLoS One 12, e0183412 (2017).
Regional Gene #CC3300 #FFC000 Amazonia and the Atlantic Forest Anolis sp. and Polychrus marmoratus https://doi.org/10.1073/pnas.1601063113 I. Prates et al., Inferring responses to climate dynamics from historical demography in neotropical forest lizards. Proc Natl Acad Sci U S A 113, 7978-7985 (2016).
Regional Individual #CC3300 Western USA Ochotona princeps https://doi.org/10.1111/gcb.13454 P. D. Mathewson et al., Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates. Glob Chang Biol 23, 1048-1064 (2017).
Regional Individual #CC3300 South West Europe European beech https://doi.org/10.1111/geb.12085 *F. Saltré et al., Climate or migration: what limited European beech post-glacial colonization? Global Ecology and Biogeography 22, 1217-1227 (2013).
Regional Population #CC3300 #FFC000 #9BBB59 Appalachians, North America Plethodontidae sp. https://doi.org/10.1086/691796 R. Barnes, A. T. Clark, Sixty-Five Million Years of Change in Temperature and Topography Explain Evolutionary History in Eastern North American Plethodontid Salamanders. Am Nat 190, E1-E12 (2017).
Regional Community #CC3300 #FFC000 #9BBB59 #8064A2 Costa Rica Plants & Insects https://doi.org/10.1098/rstb.2010.0293 R. K. Colwell, T. F. Rangel, A stochastic, evolutionary model for range shifts and richness on tropical elevational gradients under Quaternary glacial cycles. Philos Trans R Soc Lond B Biol Sci 365, 3695-3707 (2010).
Regional Ecosystem #CC3300 Beringia Vegetation https://doi.org/10.1086/285824 S. A. Zimov et al., Steppe-Tundra Transition: A Herbivore-Driven Biome Shift at the End of the Pleistocene. The American Naturalist 146, 765-794 (1995).
Regional Ecosystem #CC3300 Sahara Vegetation https://doi.org/10.1007/s003820000065 R. Doherty, J. Kutzbach, J. Foley, D. Pollard, Fully coupled climate/dynamical vegetation model simulations over Northern Africa during the mid-Holocene. Climate Dynamics 16, 561-573 (2000).
Regional Ecosystem #CC3300 Amazonia Vegetation https://doi.org/10.1098/rstb.2003.1434 F. E. Mayle, D. J. Beerling, W. D. Gosling, M. B. Bush, Responses of Amazonian ecosystems to climatic and atmospheric carbon dioxide changes since the last glacial maximum. Philos Trans R Soc Lond B Biol Sci 359, 499-514 (2004).
Regional Ecosystem #CC3300 Amazonia Vegetation https://doi.org/10.1111/j.1365-2486.2006.01228.x D. J. Beerling, F. E. Mayle, Contrasting effects of climate and CO2on Amazonian ecosystems since the last glacial maximum. Global Change Biology 12, 1977-1984 (2006).
Regional Ecosystem #CC3300 Northern Eurasia Vegetation https://doi.org/10.1016/j.quascirev.2010.05.031 J. R. M. Allen et al., Last glacial vegetation of northern Eurasia. Quaternary Science Reviews 29, 2604-2618 (2010).
Regional Ecosystem #CC3300 East Africa Vegetation https://doi.org/10.1016/j.palaeo.2015.12.001 I. Fer, B. Tietjen, F. Jeltsch, High-resolution modelling closes the gap between data and model simulations for Mid-Holocene and present-day biomes of East Africa. Palaeogeography, Palaeoclimatology, Palaeoecology 444, 144-151 (2016).
Regional Ecosystem #CC3300 Eastern North America Temperate forest https://doi.org/10.1111/gcb.13626 C. R. Rollinson et al., Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America. Glob Chang Biol 23, 2755-2767 (2017).
Regional Ecosystem #CC3300 China Vegetation https://doi.org/10.1007/s11430-018-9338-3 H. Wu et al., Quantitative climatic reconstruction of the Last Glacial Maximum in China. Science China Earth Sciences 62, 1269-1278 (2019).
Regional Ecosystem #CC3300 Saharah Sahara vegetation https://doi.org/10.1029/2018GL079195 *Z. Lu et al., Dynamic Vegetation Simulations of the Mid‐Holocene Green Sahara. Geophysical Research Letters 45, 8294-8303 (2018).
Regional Ecosystem #CC3300 Fennoscandia Vegetation https://doi.org/10.1111/j.1365-2745.2007.01342.x *P. A. Miller et al., Exploring climatic and biotic controls on Holocene vegetation change in Fennoscandia. Journal of Ecology 96, 247-259 (2008).
Continental Gene #CC3300 #FFC000 North America Trees https://doi.org/10.1073/pnas.1901656116 *J. B. Bemmels, L. L. Knowles, C. W. Dick, Genomic evidence of survival near ice sheet margins for some, but not all, North American trees. Proc Natl Acad Sci U S A 116, 8431-8436 (2019).
Continental Community #CC3300 #FFC000 #9BBB59 #8064A2 South America Birds https://doi.org/10.1126/science.aar5452 T. F. Rangel et al., Modeling the ecology and evolution of biodiversity: Biogeographical cradles, museums, and graves. Science 361, eaar5452 (2018).
Continental Ecosystem #CC3300 Africa Vegetation https://doi.org/10.1073/pnas.0610109104 H. Wu, J. Guiot, S. Brewer, Z. Guo, C. Peng, Dominant factors controlling glacial and interglacial variations in the treeline elevation in tropical Africa. Proc Natl Acad Sci U S A 104, 9720-9724 (2007).
Continental Ecosystem #CC3300 Holarctic Vegetation https://doi.org/10.1007/s00382-008-0415-5 J. Wohlfahrt et al., Evaluation of coupled ocean–atmosphere simulations of the mid-Holocene using palaeovegetation data from the northern hemisphere extratropics. Climate Dynamics 31, 871-890 (2008).
Continental Ecosystem #CC3300 Holarctic Vegetation https://doi.org/10.1371/journal.pone.0061963 B. Huntley et al., Millennial climatic fluctuations are key to the structure of last glacial ecosystems. PLoS One 8, e61963 (2013).
Continental Ecosystem #CC3300 Holarctic Vegetation https://doi.org/10.5194/cp-11-1701-2015 M. Forrest et al., Climate-vegetation modelling and fossil plant data suggest low atmospheric CO2 in the late Miocene. Climate of the Past 11, 1701-1732 (2015).
Continental Ecosystem #CC3300 Asia Vegetation https://doi.org/10.5194/cp-13-107-2017 A. Dallmeyer et al., Biome changes in Asia since the mid-Holocene – an analysis of different transient Earth system model simulations. Climate of the Past 13, 107-134 (2017).
Global Gene #CC3300 #FFC000 Global Homo sapiens sapiens https://doi.org/10.1073/pnas.1209494109 *A. Eriksson et al., Late Pleistocene climate change and the global expansion of anatomically modern humans. Proc Natl Acad Sci U S A 109, 16089-16094 (2012).
Global Population #CC3300 #FFC000 Global Homo sapiens sapiens https://doi.org/10.1038/nature19365 *A. Timmermann, T. Friedrich, Late Pleistocene climate drivers of early human migration. Nature 538, 92-95 (2016).
Global Population #CC3300 #FFC000 Global Homo sapiens sapiens https://doi.org/10.1016/j.quascirev.2019.105867 *A. R. Vahdati, J. D. Weissmann, A. Timmermann, M. S. Ponce de León, C. P. E. Zollikofer, Drivers of Late Pleistocene human survival and dispersal: an agent-based modeling and machine learning approach. Quaternary Science Reviews 221, 105867 (2019).
Global Ecosystem #CC3300 Global Vegetation https://doi.org/10.1029/2001GL013366 J. O. Kaplan, Wetlands at the Last Glacial Maximum: Distribution and methane emissions. Geophysical Research Letters 29, 3-1-3-4 (2002).
Global Ecosystem #CC3300 Global Vegetation https://doi.org/10.1191/0959683603hl625rp M. Scholze, W. Knorr, M. Heimann, Modelling terrestrial vegetation dynamics and carbon cycling for an abrupt climatic change event. The Holocene 13, 327-333 (2016).
Global Ecosystem #CC3300 Global Vegetation https://doi.org/10.1007/s00334-007-0126-6 J. Olofsson, T. Hickler, Effects of human land-use on the global carbon cycle during the last 6,000 years. Vegetation History and Archaeobotany 17, 605-615 (2007).
Global Ecosystem #CC3300 Global Vegetation & herbivores https://doi.org/10.1038/s41559-018-0481-y D. Zhu et al., The large mean body size of mammalian herbivores explains the productivity paradox during the Last Glacial Maximum. Nat Ecol Evol 2, 640-649 (2018).
Global Ecosystem #CC3300 Global Global vegetation https://doi.org/10.1016/S0277-3791(98)00009-2 *J. Kutzbach et al., Climate and biome simulations for the past 21,000 years. Quaternary Science Reviews 17, 473-506 (1998).
Global Ecosystem #CC3300 Global Vegetation https://doi.org/10.1016/j.quascirev.2019.06.003 W. Chen et al., Response of vegetation cover to CO2 and climate changes between Last Glacial Maximum and pre-industrial period in a dynamic global vegetation model. Quaternary Science Reviews 218, 293-305 (2019).
Global Ecosystem #CC3300 Global Vegetation https://doi.org/10.1098/rstb.1998.0190 M. Claussen et al., Modelling global terrestrial vegetation–climate interaction. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 353, 53-63 (1998).
Global Ecosystem #CC3300 Global Vegetation https://doi.org/10.1111/j.1469-8137.2010.03620.x *I. C. Prentice, S. P. Harrison, P. J. Bartlein, Global vegetation and terrestrial carbon cycle changes after the last ice age. New Phytol 189, 988-998 (2011).
Note: * = indicate records found during an extended literature search. See below for details.


A literature review done on the 7th October 2019 using key terms related to:

  1. ecology and evolutionary responses to climate change;

  2. common classes of eco-evolutionary simulation models;

  3. research disciplines that actively use eco-evolutionary models in a paleo context; and

  4. the late Quaternary.

A total of 258 papers were returned from Clarivate Analytics Web of Science titles, key words and abstracts using the search term:

(mechanism OR process OR "range dynamics" OR "population dynamics" OR dispersal OR diversification OR speciation OR extinction OR movement) AND ("simulation model" OR "mechanistic model" OR "vegetation model" OR "evolutionary model" OR "metapopulation model" OR "approximate bayesian computation" OR "demographic model") AND (macroecolog* OR paleoecolog* OR biogeograph* OR phylogeograph* OR "evolutionary ecology") AND (Quaternary OR Holocene OR Pleistocene OR past OR historic)

Papers that used process-explicit models (as described by 3) to directly simulate biological responses to dynamic climate change in terrestrial systems from at least 1 k BP were retained. From these papers we recorded the spatial scale being modelled (local, regional, continental, and global), the level of biological organization being modelled (genetic, individuals, populations, communities, and ecosystems) and the key ecological and evolutionary processes being modelled (mortality, movement, adaptation, and speciation). Studies that were done at the site-level or for an area of \(\leq\) 200 km2 of a well-defined region (e.g., the Rocky Mountains) were classified as local. Study regions larger than the local scale, but less than the continental scale were classified as regional. After assessing these papers, it became clear that our literature search missed some important ecosystem level models, particularly those built at local and regional scales. To address this gap, we reran the search with 3 additional key terms in the research disciplines field: “ecosystem”, “biome”, "plant functional type*". This resulted in an additional 157 papers, from which we extracted 28 relevant articles. The results of this literature search were circulated among all authors and an additional 12 relevant papers were added to the above table. These papers are shown above with an asterisk.

References

  1. J. D. Shakun et al., Global warming preceded by increasing carbon dioxide concentrations during the last deglaciation. Nature 484, 49-54 (2012).

  2. S. C. Brown, T. M. L. Wigley, B. L. Otto-Bliesner, C. Rahbek, D. A. Fordham, Persistent Quaternary climate refugia are hospices for biodiversity in the Anthropocene. Nature Climate Change 10, 244-248 (2020).

  3. S. R. Connolly, S. A. Keith, R. K. Colwell, C. Rahbek, Process, Mechanism, and Modeling in Macroecology. Trends Ecol Evol 32, 835-844 (2017).