Ecology

Traditional ecological footprint consumption accountsTo truly reflect the ecological footprint and ecological carrying capacity of Dongying city, according to the lifestyle and consumption of Dongying city and with reference to Shandong Province Statistical Yearbook and Dongying City Statistical Yearbook, the biologically productive land is divided into arable land, forestland, grassland, water, construction land and fossil energy land, and the main consumption items of each category are shown in Fig. 3.Figure 3Traditional ecological footprint consumption accounts in Dongying city. This paper uses the carbon footprint to improve the fossil energy footprint of the traditional ecological footprint.Full size imageNPP-based correction of ecological footprint parametersThe 30 m land use of the study area was resampled to 500 m, consistent with the resolution of MOD17A3H after pre-processing with MRT and other tools. Correction of ecological footprint parameter factors in Dongying City for 2015, 2018 and 2020 based on the annual average NPP of vegetation (Table 1). This method is faster and more accurate than other methods, and the implementation of NPP calculations from the vegetation light energy use efficiency (LUE) framework to correct ecological footprint parameters is more applicable and accurate than other methods.Table 1 Average annual net primary productivity per land type in the Yellow River Delta.Full size tableYield factorThe formula for calculating the yield factor for arable land in the Yellow River Delta refers to NFA 2016:$$left{ {begin{array}{*{20}c} {Y_{j1} = frac{{Sigma A_{W} }}{{Sigma A_{N} }}} \ {A_{N} = frac{{P_{N} }}{{Y_{N} }}} \ {A_{W} = frac{{P_{N} }}{{Y_{W} }}} \ end{array} } right.$$
(1)
In Eq. (1), ({Y}_{j1}) is the yield factor of the arable land in the study area, ({A}_{N}) is the harvested area ( culture area ) of agricultural products of category (N) in the study area, ({A}_{W}) is the area required to produce an equivalent amount of this type of agricultural product based on the world average yield, ({P}_{N}) is the production of agricultural products of category (N) under the region, ({Y}_{N}) is the average yield of agricultural products of category (N) under the region, and ({Y}_{W}) is the world average production of a category of agricultural products.The NPP products from MODIS supported by remote sensing were used as the base data to correct the yield factors of woodlands and grasslands in the study area under the ecological footprint model.$$Y_{{{text{j}}2}} = overline{{NPP_{local} }} /overline{{NPP_{global} }}$$
(2)
In Eq. (2), ({Y}_{mathrm{j}2}) is the yield factor for woodland and grassland in the study area, ({NPP}_{local}) is the average annual net primary productivity of woodland and grassland in the study area in the corresponding year, and ({NPP}_{global}) is the global average NPP of woodland and grassland in the corresponding year, referring to Amthor et al.24.In addition, most of the land for construction comes from cropland, so the yield factor for construction land is the same as that for cropland25. The yield factors for the watershed were derived from the Wackernagel and Rees26 study.Balancing factorThe NPP model for provincial hectares was applied to the municipal scale. Among them, the NPP of four biologically productive lands, namely cropland, woodland, grassland and water, was weighted and summed to obtain the annual average NPP within the city area.$$overline{NPP} = frac{{mathop sum nolimits_{j} left( {A_{j} times NPP_{j} } right)}}{{mathop sum nolimits_{j} A_{j} }}$$
(3)
In Eq. (3), (overline{NPP }) is the average net primary productivity of arable land, forestland, grassland and water in Dongying, ({A}_{j}) is the area of land in category (j), and ({NPP}_{j}) is the average annual NPP of productive land in category (j).Balancing factors for arable land, woodland, grassland and water in the Yellow River Delta.$$R_{j} = frac{{NPP_{j} }}{{overline{NPP} }}$$
(4)
In Eq. (4), ({R}_{j}) is a balancing factor.The sites for construction are located in areas suitable for agricultural cultivation or directly occupy arable land, so the potential ecological productivity of urban construction land is the same as that of arable land, and therefore the equilibrium factor for construction land is equal to that of arable land27.Ecological footprint principles and improvementsEcological footprint modelEcological footprint model includes ecological footprint, ecological carrying capacity and ecological deficit. As the study area is within the city limits and the statistics have their own characteristics, adjustments have been made to the methodology for calculating the national ecological footprint accounts28. Based on the biological consumption account, the ecological footprint can be calculated for any land use type.$$EF = frac{P}{{Y_{N} }} times R_{j} times Y_{j}$$
(5)
In Eq. (5), (P) is the number of biologically productive land harvesting consumption items in a category, and ({Y}_{N}) is the average production of consumption Item (N) in the region. The ecological footprint of the construction land is measured based on the area of human infrastructure land and is equal to its ecological carrying capacity.Ecological carrying capacity is the determination of the maximum carrying capacity of an ecosystem for human activity, expressed as the sum of the biologically productive land area available in an area.$$EC = N times ec = N times sum left( {a_{j} times R_{j} times Y_{j} } right)$$
(6)
In Eq. (6), (EC) is the ecological carrying capacity per capita, and ({a}_{j}) is the per capita area of biologically productive land of category j in the region. According to the recommendations of the World Commission on Environment and Development, 12% of the ecological carrying capacity should also be deducted for biodiversity conservation. The population figures for the study area were obtained from the statistical yearbook and the seventh national census data. According to the recommendations of the World Commission on Environment and Development, 12% of the ecological carrying capacity should also be deducted for biodiversity conservation.An ecological deficit is the interpolation of the ecological footprint and ecological carrying capacity.$$ED = EF – EC$$
(7)
When (ED >0) indicates an ecological deficit, the ecological environment has exceeded the carrying capacity. Conversely, when (ED More

Nigst, P. R. et al. Early modern human settlement of Europe north of the alps occurred 43,500 years ago in a cold steppe-type environment. Proc. Natl. Acad. Sci. U.S.A. 111, 14394–14399 (2014).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pederzani, S. et al. Subarctic climate for the earliest Homo sapiens in Europe. Sci. Adv. 7, 1–11 (2021).Article 

Google Scholar 
Shao, Y. et al. Human-existence probability of the Aurignacian techno-complex under extreme climate conditions. Quat. Sci. Rev. 263, 106995 (2021).Article 

Google Scholar 
Slimak, L. et al. Modern human incursion into Neanderthal territories 54,000 years ago at Mandrin, France. Sci. Adv. 8, 1 (2022).Article 

Google Scholar 
Fewlass, H. et al. A 14C chronology for the Middle to Upper Palaeolithic transition at Bacho Kiro Cave, Bulgaria. Nat. Ecol. Evol. 4, 794–801 (2020).Article 
PubMed 

Google Scholar 
Hublin, J. J. et al. Initial Upper Palaeolithic Homo sapiens from Bacho Kiro Cave, Bulgaria. Nature 581, 299–302 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Benazzi, S. et al. Early dispersal of modern humans in Europe and implications for Neanderthal behaviour. Nature 479, 525–528 (2011).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Benazzi, S. et al. The makers of the Protoaurignacian and implications for Neandertal extinction. Science 348, 793–796 (2015).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Cortés-Sánchez, M. et al. An early Aurignacian arrival in southwestern Europe. Nat. Ecol. Evol. 3, 207–212 (2019).Article 
PubMed 

Google Scholar 
Vidal-Cordasco, M., Ocio, D., Hickler, T. & Marín-Arroyo, A. B. Publisher Correction: Ecosystem productivity affected the spatiotemporal disappearance of Neanderthals in Iberia. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01917-6 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Fu, Q. et al. An early modern human from Romania with a recent Neanderthal ancestor. Nature 524, 216–219 (2015).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wood, R. E. et al. The chronology of the earliest Upper Palaeolithic in northern Iberia: New insights from L’Arbreda, Labeko Koba and La Viña. J. Hum. Evol. 69, 91–109 (2014).Article 
CAS 
PubMed 

Google Scholar 
Hublin, J. J. The modern human colonization of western Eurasia: When and where? Quat. Sci. Rev. 118, 194–210 (2015).Article 
ADS 

Google Scholar 
Hublin, J. J. The earliest modern human colonization of Europe. Proc. Natl. Acad. Sci. U.S.A. 109, 13471–13472 (2012).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Marín-Arroyo, A. B. & Sanz-Royo, A. What Neanderthals and AMH ate: Reassessment of the subsistence across the Middle-Upper Palaeolithic transition in the Vasco-Cantabrian region of SW Europe. J. Quat. Sci. 37, 320–334 (2022).Article 

Google Scholar 
Semal, P. et al. New data on the late Neandertals: Direct dating of the Belgian Spy fossils. Am. J. Phys. Anthropol. 138, 421–428 (2009).Article 
PubMed 

Google Scholar 
Welker, F. et al. Palaeoproteomic evidence identifies archaic hominins associated with the Châtelperronian at the Grotte du Renne. Proc. Natl. Acad. Sci. 113, 11162–11167 (2016).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zilhão, J. Chronostratigraphy of the Middle-to-Upper Paleolithic transition in the Iberian Peninsula. Pyrenae Rev. Prehist. i Antig. la Mediter. Occident. 37, 7–84 (2006).
Google Scholar 
Vanhaeren, M. & d’Errico, F. Aurignacian ethno-linguistic geography of Europe revealed by personal ornaments. J. Archaeol. Sci. 33, 1105–1128 (2006).Article 

Google Scholar 
Higham, T. et al. Testing models for the beginnings of the Aurignacian and the advent of figurative art and music: The radiocarbon chronology of Geißenklösterle. J. Hum. Evol. 62, 664–676 (2012).Article 
PubMed 

Google Scholar 
Broglio, A. et al. L’art aurignacien dans la décoration de la Grotte de Fumane. Anthropologie 113, 753–761 (2009).Article 

Google Scholar 
Conard, N. J. Palaeolithic ivory sculptures from southwestern Germany and the origins of figurative art. Nature 426, 830–832 (2003).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Conard, N. J. A female figurine from the basal Aurignacian of Hohle Fels Cave in southwestern Germany. Nature 459, 248–252 (2009).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Bourrillon, R. et al. A new Aurignacian engraving from Abri Blanchard, France: Implications for understanding Aurignacian graphic expression in Western and Central Europe. Quat. Int. 491, 46–64 (2018).Article 

Google Scholar 
Tejero, J. M. & Grimaldi, S. Assessing bone and antler exploitation at Riparo Mochi (Balzi Rossi, Italy): Implications for the characterization of the Aurignacian in South-western Europe. J. Archaeol. Sci. 61, 59–77 (2015).Article 

Google Scholar 
Tejero, J. M. Spanish aurignacian projectile points: An example of the First European Paleolithic hunting weapons in osseous materials. In Osseous Projectile Weaponry Towards an Understanding of Pleistocene Cultural Variability (ed. Langley, M. C.) 55–70 (Springer, 2017).
Google Scholar 
Kitagawa, K. & Conard, N. J. Split-based points from the Swabian Jura highlight Aurignacian regional signatures. PLoS ONE 15(11), e0239865 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Floss, H., Hoyer, C. T., Heckel, C. & Tartar, É. The Aurignacian in Southern Burgundy. Palethnologie 7, 1–22 (2015).
Google Scholar 
Tartar, É. Origin and development of Aurignacian Osseous Technology in Western Europe: A review of current knowledge. Palethnologie 7, 1–20 (2015).
Google Scholar 
Bar-Yosef, O. Neanderthals and modern humans: A different interpretation. In When Neanderthals and Modern Humans Met (ed. Conard, N. J.) 467–482 (Kerns Verlag, 2006).
Google Scholar 
Flas, D. Les pointes foliacées et les changements techniques autour de la transitiondu Paléolithiquemoyen au supérieur dans leNord-Ouest de l’Europe. In (eds Toussaint, M. & Di Modica, K. S. P.) 261–276 (ERAUL 128, 2011).Nigst, P. R. The Early Upper Palaeolithic of the Middle Danube Region—Human Evolution (Leiden University, 2012).
Google Scholar 
Tsanova, T. Les débuts du Paléolithique supérieur dans l’Est des Balkans. Réflexion à partir de l’étude taphonomique et techno-économique des ensembles lithiques des sites de Bacho Kiro (couche 11), Temnata (couches VI et 4) et Kozarnika (niveau VII) (2008).Bosch, M. D. et al. New chronology for Ksâr ’Akil (Lebanon) supports Levantine route of modern human dispersal into Europe. Proc. Natl. Acad. Sci. U.S.A. 112, 7683–7688 (2015).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chu, W. et al. Aurignacian dynamics in Southeastern Europe based on spatial analysis, sediment geochemistry, raw materials, lithic analysis, and use-wear from Românești-Dumbrăvița. Sci. Rep. 12, 14152 (2022).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Conard, N. J. The timing of cultural innovations and the dispersal of modern humans in Europe. Terra Nostra 6, 82–94 (2002).
Google Scholar 
Davies, W. Re-evaluating the Aurignacian as an Expression of Modern Human Mobility and Dispersal. (eds. Mellars P, Boyle K, Bar-Yosef O, S. C.) (2001).Mellars, P. A new radiocarbon revolution and the dispersal of modern humans in Eurasia. Nature 439, 931–935 (2006).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Mellars, P. Archeology and the dispersal of modern humans in Europe: Deconstructing the ‘Aurignacian’. Evol. Anthropol. 15, 167–182 (2006).Article 

Google Scholar 
Szmidt, C. C., Normand, C., Burr, G. S., Hodgins, G. W. L. & LaMotta, S. AMS 14C dating the Protoaurignacian/Early Aurignacian of Isturitz, France. Implications for Neanderthal-modern human interaction and the timing of technical and cultural innovations in Europe. J. Archaeol. Sci. 37, 758–768 (2010).Article 

Google Scholar 
Conard, N. J. & Bolus, M. Radiocarbon dating the appearance of modern humans and timing of cultural innovations in Europe: New results and new challenges. J. Hum. Evol. 44, 331–371 (2003).Article 
PubMed 

Google Scholar 
Douka, K., Grimaldi, S., Boschian, G., del Lucchese, A. & Higham, T. F. G. A new chronostratigraphic framework for the Upper Palaeolithic of Riparo Mochi (Italy). J. Hum. Evol. 62, 286–299 (2012).Article 
PubMed 

Google Scholar 
Davies, W. & Hedges, R. E. M. Dating a type site: Fitting Szeleta Cave into its regional chronometric context. Praehistoria 9–10, 35–45 (2009).
Google Scholar 
Davies, W., White, D., Lewis, M. & Stringer, C. Evaluating the transitional mosaic: Frameworks of change from Neanderthals to Homo sapiens in eastern Europe. Quat. Sci. Rev. 118, 211–242 (2015).Article 
ADS 

Google Scholar 
Marín-Arroyo, A. B. et al. Chronological reassessment of the Middle to Upper Paleolithic transition and Early Upper Paleolithic cultures in Cantabrian Spain. PLoS ONE 13, 1–20 (2018).
Google Scholar 
Barshay-Szmidt, C., Normand, C., Flas, D. & Soulier, M. C. Radiocarbon dating the Aurignacian sequence at Isturitz (France): Implications for the timing and development of the Protoaurignacian and Early Aurignacian in western Europe. J. Archaeol. Sci. Rep. 17, 809–838 (2018).
Google Scholar 
Wood, R. et al. El Castillo (Cantabria, northern Iberia) and the Transitional Aurignacian: Using radiocarbon dating to assess site taphonomy. Quat. Int. 474, 56–70 (2018).Article 

Google Scholar 
Chu, W. The danube corridor hypothesis and the carpathian basin: Geological, environmental and archaeological approaches to characterizing aurignacian dynamics. J. World Prehist. 31, 117–178 (2018).Article 

Google Scholar 
Falcucci, A., Conard, N. J. & Peresani, M. Breaking through the aquitaine frame: A re-evaluation on the significance of regional variants during the Aurignacian as seen from a key record in southern Europe. J. Anthropol. Sci. 98, 99–140 (2020).PubMed 

Google Scholar 
Banks, W. E., d’Errico, F. & Zilhão, J. Human-climate interaction during the Early Upper Paleolithic: Testing the hypothesis of an adaptive shift between the Proto-Aurignacian and the Early Aurignacian. J. Hum. Evol. 64, 39–55 (2013).Article 
PubMed 

Google Scholar 
Badino, F. et al. An overview of Alpine and Mediterranean palaeogeography, terrestrial ecosystems and climate history during MIS 3 with focus on the Middle to Upper Palaeolithic transition. Quat. Int. 551, 7–28 (2020).Article 

Google Scholar 
Bataille, G. & Conard, N. J. Blade and bladelet production at Hohle Fels Cave, AH IV in the Swabian Jura and its importance for characterizing the technological variability of the Aurignacian in Central Europe. PLoS ONE 13, 1–47 (2018).Article 

Google Scholar 
Higham, T., Wood, R., Moreau, L., Conard, N. & Ramsey, C. B. Comments on ‘Human-climate interaction during the early Upper Paleolithic: Testing the hypothesis of an adaptive shift between the Proto-Aurignacian and the Early Aurignacian’ by Banks et al.. J. Hum. Evol. 65, 806–809 (2013).Article 
PubMed 

Google Scholar 
Teyssandier, N. & Zilhão, J. On the entity and antiquity of the Aurignacian at Willendorf (Austria): Implications for modern human emergence in Europe. J. Paleolit. Archaeol. 1, 107–138 (2018).Article 

Google Scholar 
Discamps, E., Jaubert, J. & Bachellerie, F. Human choices and environmental constraints: Deciphering the variability of large game procurement from Mousterian to Aurignacian times (MIS 5–3) in southwestern France. Quat. Sci. Rev. 30, 2755–2775 (2011).Article 
ADS 

Google Scholar 
Kuhn, S. L. & Stiner, M. C. What’s a mother to do? The division of labor among Neandertals and modern humans in Eurasia. Curr. Anthropol. 47, 953–980 (2006).Article 

Google Scholar 
Starkovich, B. M. Intensification of small game resources at Klissoura Cave 1 (Peloponnese, Greece) from the Middle Paleolithic to Mesolithic. Quat. Int. 264, 17–31 (2012).Article 

Google Scholar 
Stiner, M. Prey choice, site occupation intensity & economic diversity in the Middle–early Upper Palaeolithic at the Üçağizli Caves. Turkey. Before Farm. 3, 1–20 (2009).
Google Scholar 
Yravedra Saínz de los Terreros, J., Gómez-Castanedo, A., Aramendi-Picado, J., Montes-Barquín, R. & Sanguino-González, J. Neanderthal and Homo sapiens subsistence strategies in the Cantabrian region of northern Spain. Archaeol. Anthropol. Sci. 8, 779–803 (2016).Article 

Google Scholar 
Bertacchi, A., Starkovich, B. M. & Conard, N. J. The Zooarchaeology of Sirgenstein Cave: A Middle and Upper Paleolithic site in the Swabian Jura, SW Germany. J. Paleolit. Archaeol. 4, 7 (2021).Article 

Google Scholar 
Boscato, P. & Crezzini, J. Middle-Upper Palaeolithic transition in Southern Italy: Uluzzian macromammals from Grotta del Cavallo (Apulia). Quat. Int. 252, 90–98 (2012).Article 

Google Scholar 
Grayson, D. K. & Delpech, F. The large mammals of Roc de Combe (Lot, France): The Châtelperronian and Aurignacian assemblages. J. Anthropol. Archaeol. 27, 338–362 (2008).Article 

Google Scholar 
Morin, E. et al. New evidence of broader diets for archaic Homo populations in the northwestern Mediterranean. Sci. Adv. 5, 1–12 (2019).Article 

Google Scholar 
Münzel, S. & Conard, N. J. Change and continuity in subsistence during the Middle and Upper Palaeolithic in the Ach Valley of Swabia (South-west Germany). Int. J. Osteoarchaeol. 14, 225–243 (2004).Article 

Google Scholar 
Rendu, W. et al. Subsistence strategy changes during the Middle to Upper Paleolithic transition reveals specific adaptations of Human Populations to their environment. Sci. Rep. 9, 1–11 (2019).Article 
ADS 

Google Scholar 
Romandini, M. et al. Macromammal and bird assemblages across the late Middle to Upper Palaeolithic transition in Italy: An extended zooarchaeological review. Quat. Int. 551, 188–223 (2020).Article 

Google Scholar 
Starkovich, B. M. Paleolithic subsistence strategies and changes in site use at Klissoura Cave 1 (Peloponnese, Greece). J. Hum. Evol. 111, 63–84 (2017).Article 
PubMed 

Google Scholar 
Peresani, M. Inspecting human evolution from a cave Late Neanderthals and early sapiens at Grotta di Fumane: Present state and outlook. J. Anthropol. Sci. 100, 71–107 (2022).PubMed 

Google Scholar 
Jarvis, A. et al. Hole-Filled Seamless SRTM Data V4. https://srtm.csi.cgiar.org (International Centre for Tropical Agriculture (CIAT), 2008).Delpiano, D., Heasley, K. & Peresani, M. Assessing Neanderthal land use and lithic raw material management in discoid technology. J. Anthropol. Sci. 96, 89–110 (2018).PubMed 

Google Scholar 
Marcazzan, D., Ligouis, B., Duches, R. & Conard, N. J. Middle and Upper Paleolithic occupations of Fumane Cave (Italy): A geoarchaeological investigation of the anthropogenic features. J. Antropol. Sci. 100, 1–26 (2022).
Google Scholar 
Douka, K. et al. On the chronology of the Uluzzian. J. Hum. Evol. 68, 1–13 (2014).Article 
PubMed 

Google Scholar 
Peresani, M., Cristiani, E. & Romandini, M. The Uluzzian technology of Grotta di Fumane and its implication for reconstructing cultural dynamics in the Middle-Upper Palaeolithic transition of Western Eurasia. J. Hum. Evol. 91, 36–56 (2016).Article 
PubMed 

Google Scholar 
Peresani, M., Bertola, S., Delpiano, D., Benazzi, S. & Romandini, M. The Uluzzian in the north of Italy: Insights around the new evidence at Riparo Broion. Archaeol. Anthropol. Sci. 11, 3503–3536 (2019).Article 

Google Scholar 
Aleo, A., Duches, R., Falcucci, A., Rots, V. & Peresani, M. Scraping hide in the early Upper Paleolithic: Insights into the life and function of the Protoaurignacian endscrapers at Fumane Cave. Archaeol. Anthropol. Sci. 13, 1 (2021).Article 

Google Scholar 
Falcucci, A., Conard, N. J. & Peresani, M. A critical assessment of the Protoaurignacian lithic technology at Fumane Cave and its implications for the definition of the earliest Aurignacian. PLoS ONE 12, 1–43 (2017).Article 

Google Scholar 
Falcucci, A. & Peresani, M. A pre-Heinrich Event 3 assemblage at Fumane Cave and its contribution for understanding the beginning of the Gravettian in Italy. Quartär 66, 135–154 (2019).
Google Scholar 
Higham, T. European Middle and Upper Palaeolithic radiocarbon dates are often older than they look. Antiquity 85, 235–249 (2011).Article 

Google Scholar 
Higham, T. et al. Problems with radiocarbon dating the Middle to Upper Palaeolithic transition in Italy. Quat. Sci. Rev. 28, 1257–1267 (2009).Article 
ADS 

Google Scholar 
Cassoli, P. F. & Tagliacozzo, A. Considerazioni paleontologiche, paleoecologiche e archeologiche sui micromammiferi e gli uccelli dei livelli del Pleistocene Superiore del Riparo di Fumane (Vr) (Scavi 1988–91). Bollettino del Museo Civico di Storia Naturale di Verona 18, 349–445 (1994).
Google Scholar 
Broglio, A., De Stefani, M., Tagliacozzo, A., Gurioli, F. & Facciolo, A. Aurignacian dwelling structures, hunting strategies and seasonality in the Fumane Cave (Lessini Mountains). In Kostenki and the Early Upper Paleolithic of Eurasia: General Trends, Local Developments (eds Vasilev, S. A. et al.) 263–268 (Nestor-Historia, 2006).
Google Scholar 
Bertola, S. et al. Le territoire des chasseurs aurignaciens dans les Préalpes de la Vénétie: l’exemple de la Grotte de Fumane. In Le Concept de Territoires dans le Paléolithique Supérieur Européen (eds Djindjian, F. et al.) (BAR Intemational Series, 2009).
Google Scholar 
Jéquier, C., Livraghi, A., Romandini, M. & Peresani, M. Same but different: 20,000 years of bone retouchers from northern Italy. A diachronologic approach from neanderthals to anatomically modern humans. In The Origins of Bone Tool Technologies (eds Hutson, J. M. et al.) 269–285 (Verlag des Römisch-Germanischen Zentralmuseums, 2018).
Google Scholar 
Marín-Arroyo, A. B. A comparative study of analytic techniques for skeletal part profile interpretation at El Mirón Cave (Cantabria, Spain). Archaeofauna 18, 79–98 (2009).
Google Scholar 
Romandini, M. Analisi archeozoologica, tafonomica, paleontologica e spaziale dei livelli Uluzziani e tardo-Musteriani della Grotta di Fumane (VR). Variazioni e continuità strategico-comportamentali umane in Italia Nord Occidentale: i casi di Grotta del Col della Stria. Dip. di Biol. ed Evol. PhD thesis 505 (2012).Marean, C. W., Abe, Y., Nilssen, P. J. & Stone, E. C. Estimating the minimum number of skeletal elements (MNE) in zooarchaeology: A review and a new image-analysis GIS approach. Am. Antiq. 66, 333–348 (2001).Article 
CAS 
PubMed 

Google Scholar 
Stiner, M. C. The use of mortality patterns in archaeological studies of hominid predatory adaptations. J. Anthropol. Archaeol. 9, 305–351 (1990).Article 

Google Scholar 
Marín-Arroyo, A. B. & Morales, M. R. G. Comportamiento económico de los últimos cazadores-recolectores y primeras evidencias de domesticación en el occidente de asturias. La cueva de mazaculos II. Trab. Prehist. 66, 47–74 (2009).Article 

Google Scholar 
Simpson, E. H. Measurement of diversity. Nature 163, 688 (1949).Article 
ADS 
MATH 

Google Scholar 
Magurran, A. E. Ecological Diversity and Its Measurement (Princeton University Press, 1988).Book 

Google Scholar 
Marín-Arroyo, A. B. The use of optimal foraging theory to estimate Late Glacial site catchment areas from a central place: The case of eastern Cantabria, Spain. J. Anthropol. Archaeol. 28, 27–36 (2009).Article 

Google Scholar 
Azorit, C. Guía para la determinación de la edad del ciervo ibérico (Cervus elaphus hispanicus) a través de su dentición: Revisión metodológica y técnicas de elección. An. la Real Acad. Ciencias Vet. Andalucía Orient. 24, 235–264 (2011).
Google Scholar 
Mariezkurrena, K. Contribución al conocimiento del desarrollo de la dentición y el esqueleto poscraneal de Cervus elaphus. Munibe 35, 149–202 (1983).
Google Scholar 
Tomé, C. & Vigne, J. D. Roe deer (Capreolus capreolus) age at death estimates: New methods and modern reference data for tooth eruption and wear, and for epiphyseal fusion. Archaeofauna 12, 157–173 (2003).
Google Scholar 
Couturier, M. A. J. Le bouquetin des Alpes: Capra aegagrus ibex ibex L. (Impr. Allier, 1962).
Google Scholar 
Habermehl, K.-H. Die Altersbeurteilung beim weiblichen Steinwild (Capra ibex ibex L.) anhand der Skelettentwicklung. Anat. Histol. Embryol. J. Vet. Med. Ser. C 21, 193–198 (1992).Article 
CAS 

Google Scholar 
Pflieger, R. H. P. Le chamois, son identification et sa vie (Grand Gibier, 1982).
Google Scholar 
Binford, L. R. Nunamiut Etnoarchaeology (Academic Press, 1978).
Google Scholar 
Metcalfe, D. & Jones, K. T. A reconsideration of animal body-part utility indices. Am. Antiq. 53, 486–504 (1988).Article 

Google Scholar 
Morin, E. & Ready, E. Foraging goals and transport decisions in western Europe during the Paleolithic and Early Holocene. In Zooarchaeology and Modern Human Origins. Vertebrate Paleobiology and Paleoanthropology (eds Clark, J. L. & Speth, J. D.) 227–269 (Springer, 2013).
Google Scholar 
Lam, Y. M., Chen, X. & Pearson, O. M. Intertaxonomic variability in patterns of bone density and the differential representation of bovid, cervid, and equid elements in the archaeological record. Am. Antiq. 64, 343–362 (1999).Article 

Google Scholar 
Morin, E. Fat composition and Nunamiut decision-making: A new look at the marrow and bone grease indices. J. Archaeol. Sci. 34, 69–82 (2007).Article 

Google Scholar 
Marín-Arroyo, A. B. & Ocio, D. Disentangling faunal skeletal profiles. A new probabilistic framework. Hist. Biol. 30, 720–729 (2018).Article 

Google Scholar 
Rogers, A. R. On the value of soft bones in faunal analysis. J. Archaeol. Sci. 27, 635–639 (2000).Article 

Google Scholar 
Rogers, A. R. Analysis of bone counts by maximum likelihood. J. Archaeol. Sci. 27, 111–125 (2000).Article 

Google Scholar 
Marín-Arroyo, A. B., Ocio, D., Vidal-Cordasco, M. & Vettese, D. BaSkePro: Bayesian Model to Archaeological Faunal Skeletal Profiles. R package version 0.1.0. https://CRAN.R-project.org/package=BaSkePro (2022).Binford, L. R. Bones Ancient Men and Modern Myths (Bones (Elsevier, 1981).
Google Scholar 
Galán, A. B. & Domínguez-Rodrigo, M. An experimental study of the anatomical distribution of cut marks created by filleting and disarticulation on long bone ends. Archaeometry 55, 1132–1149 (2013).Article 

Google Scholar 
Nilssen, P. J. An Actualistic Butchery Study in South Africa and Its Implications for Reconstructing Hominid Strategies of Carcass Acquisition and Butchery in the Upper Pleistocene and Plio-Pleistocene (University of Cape Town, 2000).
Google Scholar 
Capaldo, S. D. & Blumenschine, R. J. A quantitative diagnosis of notches made by hammerstone percussion and carnivore gnawing on bovid long bones. Am. Antiq. 59, 724–748 (1994).Article 

Google Scholar 
Pickering, T. R. & Egeland, C. P. Experimental patterns of hammerstone percussion damage on bones: Implications for inferences of carcass processing by humans. J. Archaeol. Sci. 33, 459–469 (2006).Article 

Google Scholar 
Bunn, H. T. Archaeological evidence for meat-eating by Plio-Pleistocene hominids from Koobi Fora and Olduvai Gorge. Nature 291, 574–577 (1981).Article 
ADS 

Google Scholar 
Villa, P. & Mahieu, E. Breakage patterns of human long bones. J. Hum. Evol. 21, 27–48 (1991).Article 

Google Scholar 
Blumenschine, R. J. & Selvaggio, M. M. Percussion marks on bone surfaces as a new diagnostic of hominid behaviour. Nature 333, 763–765 (1988).Article 
ADS 

Google Scholar 
Galán, A. B., Rodríguez, M., de Juana, S. & Domínguez-Rodrigo, M. A new experimental study on percussion marks and notches and their bearing on the interpretation of hammerstone-broken faunal assemblages. J. Archaeol. Sci. 36, 776–784 (2009).Article 

Google Scholar 
Pickering, T. R. et al. Taphonomy of ungulate ribs and the consumption of meat and bone by 1.2-million-year-old hominins at Olduvai Gorge, Tanzania. J. Archaeol. Sci. 40, 1295–1309 (2013).Article 

Google Scholar 
Vettese, D. et al. Towards an understanding of hominin marrow extraction strategies: A proposal for a percussion mark terminology. Archaeol. Anthropol. Sci. 12, 8 (2020).Article 

Google Scholar 
Vettese, D. et al. A way to break bones? The weight of intuitiveness. PLoS ONE 16, 0259136 (2021).Article 

Google Scholar 
Coil, R., Yezzi-Woodley, K. & Tappen, M. Comparisons of impact flakes derived from hyena and hammerstone long bone breakage. J. Archaeol. Sci. 120, 105167 (2020).Article 

Google Scholar 
Stiner, M. C., Kuhn, S. L., Weiner, S. & Bar-Yosef, O. Differential burning, recrystallization, and fragmentation of archaeological bone. J. Archaeol. Sci. 22, 223–237 (1995).Article 

Google Scholar 
Mallye, J. B. et al. The Mousterian bone retouchers of Noisetier Cave: Experimentation and identification of marks. J. Archaeol. Sci. 39, 1131–1142 (2012).Article 

Google Scholar 
Blumenschine, R. J. Percussion marks, tooth marks, and experimental determinations of the timing of hominid and carnivore access to long bones at FLK Zinjanthropus, Olduvai Gorge, Tanzania. J. Hum. Evol. 29, 21–51 (1995).Article 

Google Scholar 
Domínguez-Rodrigo, M. & Piqueras, A. The use of tooth pits to identify carnivore taxa in tooth-marked archaeofaunas and their relevance to reconstruct hominid carcass processing behaviours. J. Archaeol. Sci. 30, 1385–1391 (2003).Article 

Google Scholar 
Domínguez-Rodrigo, M. & Barba, R. New estimates of tooth mark and percussion mark frequencies at the FLK Zinj site: The carnivore-hominid-carnivore hypothesis falsified. J. Hum. Evol. 50, 170–194 (2006).Article 
PubMed 

Google Scholar 
Behrensmeyer, A. K. Taphonomic and écologie information from bone weathering. Paleobiology 4, 150–162 (1978).Article 

Google Scholar 
Fisher, J. W. Bone surface modifications in zooarchaeology. J. Archaeol. Method Theory 2, 7–68 (1995).Article 

Google Scholar 
Lyman, R. L. Vertebrate Taphonomy (Cambridge University Press, 1994).Book 

Google Scholar 
Shipman, P. Life History of a Fossil: An Introduction to Taphonomy and Paleoecology (Harvard University Press, 1981).
Google Scholar 
Marín-Arroyo, A. B. et al. Archaeological implications of human-derived manganese coatings: A study of blackened bones in El Mirón Cave, Cantabrian Spain. J. Archaeol. Sci. 35, 801–813 (2008).Article 

Google Scholar 
Marín-Arroyo, A. B., Landete-Ruiz, M. D., Seva-Román, R. & Lewis, M. D. Manganese coating of the Tabun faunal assemblage: Implications for modern human behaviour in the Levantine Middle Palaeolithic. Quat. Int. 330, 10–18 (2014).Article 

Google Scholar 
Blasco, R., Rosell, J., Fernández Peris, J., Cáceres, I. & Vergès, J. M. A new element of trampling: An experimental application on the Level XII faunal record of Bolomor Cave (Valencia, Spain). J. Archaeol. Sci. 35, 1605–1618 (2008).Article 

Google Scholar 
Domínguez-Rodrigo, M., de Juana, S., Galán, A. B. & Rodríguez, M. A new protocol to differentiate trampling marks from butchery cut marks. J. Archaeol. Sci. 36, 2643–2654 (2009).Article 

Google Scholar 
Hickler, T., Prentice, I. C., Smith, B., Sykes, M. T. & Zaehle, S. Implementing plant hydraulic architecture within the LPJ dynamic global vegetation model. Glob. Ecol. Biogeogr. 15, 567–577 (2006).Article 

Google Scholar 
Zampieri, D. Segmentation and linkage of the Lessini Mountains normal faults, Southern Alps, Italy. Tectonophysics 319, 19–31 (2000).Article 
ADS 

Google Scholar 
Castiglioni, G. B. et al. The loess deposits in the Lessini plateau. In The Loess in Northern and Central Italy: A Loess Basin Between the Alps and the Mediterranean Region (ed. Cremaschi, M.) 41–59 (Centro di Studio per la Stratigrafia e Petrografia delle Alpi Centrali, 1990).
Google Scholar 
Sauro, U. Il paesaggio degli alti Lessini. Studio Geomofologico (Museo Civico di Storia Naturale, 1973).
Google Scholar 
Castiglioni, G. B. et al. Geomorphological Map of Po Plain, Scale 1:250,000 (1997).Fontana, A., Mozzi, P. & Marchetti, M. Alluvial fans and megafans along the southern side of the Alps. Sediment. Geol. 301, 150–171 (2014).Article 
ADS 

Google Scholar 
Holechek, J. L., Pieper, R. D. & Herbel, C. H. Range Management Principles and Practices 3rd edn. (Prentice-Hall, 1998).
Google Scholar 
Imhoff, M. L. et al. Global patterns in human consumption of net primary production. Nature 429, 870–873 (2004).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Change Biol. 9, 161–185 (2003).Article 
ADS 

Google Scholar 
Smith, B. et al. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11, 2027–2054 (2014).Article 
ADS 

Google Scholar 
Githumbi, E. N. et al. Pollen, people and place: Multidisciplinary perspectives on ecosystem change at Amboseli, Kenya. Front. Earth Sci. 5, 113 (2018).Article 
ADS 

Google Scholar 
Allen, J. R. M. et al. Global vegetation patterns of the past 140,000 years. J. Biogeogr. 47, 2073–2090 (2020).Article 

Google Scholar 
Armstrong, E., Hopcroft, P. O. & Valdes, P. J. A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years. Sci. Data 6, 1–16 (2019).Article 

Google Scholar 
Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data 7, 1–18 (2020).Article 

Google Scholar 
Adam, M., Weitzel, N. & Rehfeld, K. Identifying global-scale patterns of vegetation change during the last deglaciation from paleoclimate networks. Paleoceanogr. Paleoclimatol. 36, 1 (2021).Article 

Google Scholar 
Beyer, R., Krapp, M. & Manica, A. An empirical evaluation of bias correction methods for palaeoclimate simulations. Clim. Past 16, 1493–1508 (2020).Article 

Google Scholar 
Lüthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382 (2008).Article 
ADS 
PubMed 

Google Scholar 
Zobler, L. A World Soil File for Global Climate Modelling. NASA Technical Memorandum 87802 (1986).Bronk Ramsey, C. Bayesian analysis of radiocarbon dates. Radiocarbon 51, 337–360 (2009).Article 

Google Scholar 
Reimer, P. J. et al. The IntCal20 northern hemisphere radiocarbon age calibration curve (0–55 cal kBP). Radiocarbon 62, 725–757 (2020).Article 
CAS 

Google Scholar 
Andersen, K. K. et al. The Greenland ice core chronology 2005, 15–42 ka. Part 1: Constructing the time scale. Quat. Sci. Rev. 25, 3246–3257 (2006).Article 
ADS 

Google Scholar 
Svensson, A. et al. A 60,000 year Greenland stratigraphic ice core chronology. Clim. Past 4, 47–57 (2008).Article 

Google Scholar 
Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: Refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).Article 
ADS 

Google Scholar 
Higham, T. et al. The timing and spatiotemporal patterning of Neanderthal disappearance. Nature 512, 306–309 (2014).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Romandini, M., Nannini, N., Tagliacozzo, A. & Peresani, M. The ungulate assemblage from layer A9 at Grotta di Fumane, Italy: A zooarchaeological contribution to the reconstruction of Neanderthal ecology. Quat. Int. 337, 11–27 (2014).Article 

Google Scholar 
Tagliacozzo, A., Romandini, M., Fiore, I., Gala, M. & Peresani, M. 2013. Animal exploitation strategies during the Uluzzian at Grotta di Fumane (Verona, Italy). In Zooarchaeology and Modern Human Origins. Vertebrate Paleobiology and Paleoanthropology (eds Clark, J. & Speth, J.) 129–150 (Springer, 2013).
Google Scholar 
Terlato, G., Livraghi, A., Romandini, M. & Peresani, M. Large bovids on the Neanderthal menu: Exploitation of Bison priscus and Bos primigenius in northeastern Italy. J. Archaeol. Sci. Rep. 25, 129–143 (2019).
Google Scholar 
Peresani, M., Fiore, I., Gala, M., Romandini, M. & Tagliacozzo, A. Late Neandertals and the intentional removal of feathers as evidenced from bird bone taphonomy at Fumane Cave 44 ky B.P., Italy. Proc. Natl. Acad. Sci. U.S.A. 108, 3888–3893 (2011).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Fiore, I. et al. From feathers to food: Reconstructing the complete exploitation of avifaunal resources by Neanderthals at Fumane cave, unit A9. Quat. Int. 421, 134–153 (2016).Article 

Google Scholar 
Romandini, M. et al. Neanderthal scraping and manual handling of raptors wing bones: Evidence from Fumane Cave. Experimental activities and comparison. Quat. Int. 421, 154–172 (2016).Article 

Google Scholar 
López-García, J. M., dalla Valle, C., Cremaschi, M. & Peresani, M. Reconstruction of the Neanderthal and Modern Human landscape and climate from the Fumane cave sequence (Verona, Italy) using small-mammal assemblages. Quat. Sci. Rev. 128, 1–13 (2015).Article 
ADS 

Google Scholar 
Maspero, A. Ricostruzione del paesaggio vegetale attorno alla grotta di Fumane durante il Paleolitico. Annu. Stor. della Valpolicella 18, 19–26 (1998).
Google Scholar 
Malerba, G. & Giacobini, G. Analisi delle tracce di macellazione in un sito Paleolitico. L’esempio del Riparo di Fumane (Valpolicella, Verona). In Atti del: “I° Convegno Nazionale di Archeozoologia”, Rovigo 5–7 marzo 1993 97–108 (1995).Fritz, S. A. et al. Twenty-million-year relationship between mammalian diversity and primary productivity. Proc. Natl. Acad. Sci. 113, 10908–10913 (2016).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Morris, R. J. Community ecology: How green is the arctic Tundra? Curr. Biol. 18, R256–R258 (2008).Article 
CAS 
PubMed 

Google Scholar 
Holt, B. et al. The Middle-Upper Paleolithic transition in Northwest Italy: New evidence from Riparo Bombrini (Balzi Rossi, Liguria, Italy). Quat. Int. 508, 142–152 (2019).Article 

Google Scholar 
Pothier Bouchard, G., Riel-Salvatore, J., Negrino, F. & Buckley, M. Archaeozoological, taphonomic and ZooMS insights into the Protoaurignacian faunal record from Riparo Bombrini. Quat. Int. https://doi.org/10.1016/j.quaint.2020.01.007 (2020).Article 

Google Scholar 
Riel-Salvatore, J. & Negrino, F. Proto-Aurignacian Lithic technology, mobility, and human niche construction: A case study from Riparo Bombrini, Italy. In Lithic Technological Organization and Paleoenvironmental Change, Studies in Human Ecology and Adaptation (eds Robinson, E. & Sellet, F.) (Springer, 2018).
Google Scholar 
Riel-Salvatore, J. & Negrino, F. Human adaptations to climatic change in Liguria across the Middle-Upper Paleolithic transition. J. Quat. Sci. 33, 313–322 (2018).Article 

Google Scholar 
Grimaldi, S., Porraz, G. & Santaniello, F. Raw material procurement and land use in the northern Mediterranean Arc: Insight from the first Proto-Aurignacian of Riparo Mochi (Balzi Rossi, Italy). Quartar 61, 113–127 (2014).
Google Scholar 
Alaique, F. Risultati preliminari dell’analisi dei resti faunistici rinvenuti nei livelli del Paleolitico superiore di Riparo Mochi (Balzi Rossi): Scavi 1995–1996. In Atti Del 2°Convegno Nazionale Di Archeozoologia (Asti, 1997) (eds Malerba, G. et al.) 125–130 (Abaco Edizioni, 2000).
Google Scholar 
Staubwasser, M. et al. Impact of climate change on the transition of Neanderthals to modern humans in Europe. Proc. Natl. Acad. Sci. 115, 9116–9121 (2018).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Columbu, A. et al. Speleothem record attests to stable environmental conditions during Neanderthal–modern human turnover in southern Italy. Nat. Ecol. Evol. 4, 1188–1195 (2020).Article 
PubMed 

Google Scholar 
Müller, U. C. et al. The role of climate in the spread of modern humans into Europe. Quat. Sci. Rev. 30, 273–279 (2011).Article 
ADS 

Google Scholar  More

Brazil’s new government aims to achieve zero deforestation in the Amazon rainforest. This welcome initiative should be extended to the Cerrado, the world’s most biodiverse woodland savannah.
Competing Interests
The authors declare no competing interests. More

The upside-down jellyfish, Cassiopea sp. produces several hydrodynamic effects capable of altering the ecosystem which it inhabits. Not only do Cassiopea produce feeding currents capable of turning over the water column above them several times per hour3, they are also capable of releasing interstitial porewater from the benthos5. The rate of porewater release, on the order of mL h−13, is capable of increasing water column NH4 levels by almost 30% under certain conditions3. In this study, we investigated two hypothetical mechanisms for this porewater release, and found that a combination of the morphology of the bell and the pulsing behavior of the jellyfish was responsible for releasing porewater from directly below the bell via a suction-pumping mechanism.The Bernoulli hypothesis4, a low-pressure zone surrounding the animal due to a velocity gradient between the substrate boundary and the incurrent flow of the Cassiopea sp. feeding current, predicted porewater release from the substrate surface surrounding the perimeter of the animal. While porewater is entrained from the perimeter of the bell into the feeding current4 lateral expulsion of porewater due to the suction pump mechanism would produce a visually similar flow of porewater. A horizontal flow of water does occur near the bottom1, but this flow is restricted to a narrow region near the bell and velocities were low compared to the vertical excurrent jet (Fig. 4). To test the effect of Bernoulli’s principle, we measured the effect on porewater release rates of an impermeable ring-shaped barrier surrounding the animal in order to inhibit benthic-pelagic fluid flux other than directly under the animal (Fig. 2A) using labeled fluorescein per the methods of Durieux et al.3, which were adapted from those of Jantzen et al.5 (Fig. 2). If the Bernoulli mechanism contributed to porewater liberation this treatment should have reduced the porewater release rate, but the release rates observed were not significantly different from the control treatment (2.23 mL h−1 ± 1.27 s.d., Fig. 2D).The suction pumping hypothesis5, a mechanism using the exumbrellar cavity as a suction pump that draws porewater vertically upward beneath the bell and then expels it laterally, would expect to see the majority of porewater released from directly under the bell of Cassiopea sp. This mechanism is supported by bell morphology5 and the appearance of deep porewater at the benthic surface of the exumbrellar cavity5. In our, an impermeable disk was placed underneath the animal to obstruct the flow predicted by the suction pump hypothesis (Fig. 2B). Additionally, we made a 6 mm perforation in the bells of the jellyfish to interfere with the ability to form the sub-ambient pressure in the exumbrellar space necessary for suction pumping to occur (Fig. 2C). Both treatments resulted in a significant decrease in porewater liberation, with flows indistinguishable from the absence of any animal (Fig. 2D), supporting the suction-pumping hypothesis.Since the suction pumping mechanism requires pressure fluctuations in the exumbrellar space, we also directly measured the water pressure below the jellyfish. The initiation of the power stroke of bell pulsation coincides with a sudden decrease in water pressure in the exumbrellar space (Fig. 3A,B) of a mean magnitude of 43.4 Pa (± 13.6 s.d.). These pressure fluctuations appear to be unaffected by animal size (Fig. 3D,E), although the rate of porewater release is known to scale with bell diameter3. Note that the muscles responsible for bell contraction in Cassiopea sp. are roughly 2-dimensional sheets13 with a thickness of one cell14 and therefore the cross-sectional area also does not scale with diameter. Our experiments were performed on smooth acrylic rather than sand, so that the conditions here were optimal for the formation of a tight seal with the bottom. However, the magnitude of this difference is likely to be small, as Cassiopea sp. produce copious amounts of mucus, which can compensate for small-scale surface roughness. In addition, the duration of each individual bell pulse is short1, so given the fine pore size of a sand or mud substrate, it is unlikely that subambient pressure would have the opportunity to dissipate enough to affect the high suction impulse produced.While not statistically significant, bell perforation did lead to data suggesting a decrease in exumbrellar pressure fluctuations (Fig. 3C), which could explain the reduction in porewater release observed (Fig. 2C). The fact that some pressure fluctuation was seen despite a complete lack of porewater release suggests that a minimum magnitude of pressure fluctuation might be necessary for suction pumping to occur. Furthermore, the effect may have been reduced by the ability of injured Cassiopea to produce copious amounts of mucus, which could have acted to minimize the impact of bell perforation. These parallel lines of reasoning firmly suggest that suction-pumping is, in fact, the dominant mechanism by which Cassiopea sp. release porewater.The suction-pumping mechanism for the release of porewater has broad-ranging ecological implications. Release rates should increase additively with population density, and the rate of bell pulsation should correlate with the rate of porewater liberation. The additive relationship to population density is important, since Cassiopea can occur at high densities of up to 100 animals m−23. Furthermore, while the Bernoulli mechanism predicted that interstitial water movement would be limited to the upper layers of the benthos, the suction pump mechanism has the potential to release porewater from deeper sediment strata. This deep flushing should expand the oxygen penetration depth downward, affecting factors such as respiration and sediment stability15. Given the fact that Cassiopea are capable of moving along the substrate5,16 this also means that the oxygen penetration depth is likely to fluctuate over time, favoring organisms that are able to adapt their metabolism or are able to relocate themselves17.Given that porewater at the field site in Long Key, Florida, from which the animals in this study were collected, has mean ammonium concentrations of 72 μM, 160 times higher than the surrounding water column11, any benthic-pelagic coupling mechanisms in this habitat could alter nitrogen dynamics, especially given the fact that many marine primary producers preferentially take up ammonium, the most reduced state of nitrogen available, as a nitrogen source18. Cassiopea sp. animal size and population densities are known to correlate with anthropogenic disturbances, and it is suggested that this is due to an increase in nutrient availability in these areas6. In addition to prey capture, Cassiopea sp. could be supplementing their nitrogen demand through the release of nutrient-rich interstitial porewater, from which Cassiopea sp. can directly absorb ammonium and other nutrients such as phosphate and trace metals5. In fact, jellyfish presence significantly reduced porewater ammonium levels near the animal5, suggesting that nutrient-rich porewater was replaced by down-welling low-nutrient surface water. The observed benthic locomotion of Cassiopea5,16 may be a mechanism to avoid remaining in locations where they have depleted this nutrient resource3. It has been reported that Cassiopea sp. affect benthic nutrient transport on a more general level, increasing ammonium uptake and decreasing nitrate uptake of the bottom sediments19. Water column nutrient levels also varied significantly between presence and absence of Cassiopea sp., and also between light and dark treatments in the presence of Cassiopea sp.20. The addition of jellyfish increased the efflux of ammonium from the benthos during the dark treatments, but reduced ammonium concentrations in the water column during light treatments20. It is entirely possible that absorption of nutrients by Cassiopea sp.5 in order to meet daytime metabolic demand resulted in the animals reducing water column ammonium concentrations in these experiments20.In addition, Cassiopea sp. have been shown to increase spatial heterogeneity of interstitial oxygen and nutrient fluxes20, making it comparable to other biogenic processes like bioturbation. Bioturbation typically oxygenates the upper layers of substrate, increasing the nitrification zone21, and also increases 3-dimensional heterogeneity of oxygen and nutrient concentrations, allowing for more complex nutrient dynamics21. The transport of interstitial porewater from specific regions under individual jellyfish could well produce a similar effect. The porewater release rates can also be compared to that of abiotic processes, such as wind-wave driven flow over sediment wave ripples, which have been shown to liberate porewater at rates of up to 140 L m−2 day−1, or three orders of magnitude greater than diffusion alone, on shallow, exposed coastlines such as beaches22. Environmental mixing would be lower in the sheltered mangrove habitats where Cassiopea sp. are found, since at our study site wind wave height was reduced from 5.4 cm in the bay to 0.07 cm in the mangroves3. In these coastal habitats, the sediment often acts as a nutrient sink, causing certain nutrients to become limiting to primary producers. Some fringe mangrove forests along coastlines in both Florida and Belize have been shown to be N-limited, for example23,24. If these nutrients are then released back into the water column, they potentially increase primary productivity in the system occupied by Cassiopea sp. Depending on the system, this could either increase production or cause eutrophication, potentially altering productivity on a local or regional scale, as has been observed when nutrients are released from the benthos by winds25 or bioturbation26.The mechanics of suction-pumping also imply that interstitial porewater release rate will correlate with bell pulse rate. Pulse rate correlates with water temperature (Fig. 5B), which would suggest that Cassiopea sp. can release greater quantities of nutrient-rich porewater during the summer months. This was confirmed by a recent study on the related species, Cassiopea medusa from Lake Macquarie, Australia8. By extension, our model suggests that pulsing, and therefore porewater release, should cease entirely below 18ºC. In fact, at our site in Lido Key, population densities of Cassiopea sp. declined rapidly once water temperatures dropped this low (Fig. 6). This same temperature of 18 °C was determined independently to be the threshold at which Cassiopea sp. polyp feeding was inhibited10. As such, it is likely that winter minimum temperatures of 18ºC represent a limiting condition on Cassiopea sp. range expansion. Studies on Cassiopea medusa, suggested thermal stress and bell degradation at 16 °C8. As global climates warm, we can expect both a poleward shift of Cassiopea sp. Range9,27 and an increase in transport rates of porewater and its associated benthic nutrients throughout this range, leading to increased productivity, and potentially exacerbating eutrophication in some regions.We determined that a suction-pumping mechanism is responsible for the interstitial porewater release by Cassiopea, suggesting that release rates are independent of population density, but affected by pulse rate. The potential role of bell pulse rate was investigated further, and we found correlations between bell pulse rate and both animal size and water temperature. As a result, we expect that porewater liberation would demonstrate seasonal variations, with lower rates during the winter and reaching a maximum during the summer months. Cassiopea are able to release nutrient-rich porewater in the shallow quiescent habitats they inhabit, and through their feeding current mix these nutrients throughout the water column. Since this effect varies seasonally, it is likely that further study will show that these jellyfish are responsible for a complex system of nutrient dynamics in their ecosystem. More

Des Marais, D. J. The biogeochemistry of hypersaline microbial mats. Adv. Microb. Ecol. 14, 251–274 (1995).Article 

Google Scholar 
Belnap, J., Welter, J., Grimm, N., Barger, N. & Ludwig, J. Linkages between microbial and hydrologic processes in arid and semiarid watersheds. Ecology 86, 298–307 (2005).Article 

Google Scholar 
Houghton, J. et al. Spatial variability in photosynthetic and heterotrophic activity drives locale δ13Corg fluctuations and carbonate precipitation in hypersaline microbial mats. Geobiology 12, 557–574 (2014).Article 

Google Scholar 
Allwood, A., Walter, M., Burch, I. & Kamber, B. 3.43 billion-year-old stromatolite reef from the Pilbara Craton of Western Australia: ecosystem-scale insights to early life on Earth. Precambrian Res. 158, 198–227 (2007).Article 
ADS 

Google Scholar 
Al-Najjar, M. et al. Spatial patterns and links between microbial community composition and function in cyanobacterial mats. Front. Microbiol. 5, 406 (2014).Article 

Google Scholar 
Warren-Rhodes, K., Dungan, J., Piatek, J. & McKay, C. Ecology and spatial pattern of cyanobacterial island patches in the Atacama Desert. J. Geophys. Res. Biogeosciences 112, G04S15 (2007).Article 

Google Scholar 
Allwood, A., Walter, M., Kamber, B., Marshall, C. & Burch, I. Stromatolite reef from the early Archaean era of Australia. Nature 441, 714–718 (2006).Article 
ADS 

Google Scholar 
Meslier, V. et al. Fundamental drivers for endolithic microbial community assemblies in the hyperarid Atacama Desert. Environ. Microbiol. 20, 1765–1781 (2018).Article 

Google Scholar 
Finstad, K. et al. Microbial community structure and the persistence of cyanobacterial populations in salt crusts of the hyperarid Atacama Desert from genome-resolved metagenomics. Front. Microbiol. 8, 1435 (2017).Article 

Google Scholar 
Wilhelm, M. et al. Constraints on the metabolic activity of microorganisms in Atacama surface soils inferred from refractory biomarkers: Implications for Martian habitability and biomarker detection. Astrobiology 18, 955–966 (2018).Dillon, J. et al. Spatial and temporal variability in a stratified microbial mat community. FEMS Microbiol. Ecol. 68, 46–58 (2009).Article 

Google Scholar 
Rillig, M. & Antonovics, J. Microbial biospherics: the experimental study of ecosystem function and evolution. Proc. Natl Acad. Sci. USA 116, 11093–11098 (2019).Article 
ADS 

Google Scholar 
Sephton, M. & Carter, J. The chances of detecting life on Mars. Planet. Space Sci. 112, 15–22 (2015).Article 
ADS 

Google Scholar 
Naveh, Z., & Lieberman, A. S. Landscape Ecology: Theory and Application (Springer, 2013).Mony, C., Vandenkoornhuyse, P., Bohannan, B. J. M., Peay, K. & Leibold, M. A. A landscape of opportunities for microbial ecology research. Front. Microbiol. 11, 2964 (2020).Article 

Google Scholar 
Summons, R. et al. Preservation of Martian organic and environmental records: final report of the Mars Biosignature Working Group. Astrobiology 11, 157–181 (2011).Article 
ADS 

Google Scholar 
Farmer, J. & Des Marais, D. J. Exploring for a record of ancient Martian life. J. Geophys. Res. 104, 26,977–26,995 (1999).Article 
ADS 

Google Scholar 
Stoker et al. We should search for extant life on Mars in this decade. Bull. AAS 53 (2021); https://doi.org/10.3847/25c2cfeb.36ef5e33Jakowsky, B. et al. Mars, the nearest habitable world—a comprehensive program for future Mars exploration. Bull. AAS 53 (2021); https://doi.org/10.3847/25c2cfeb.e5222017Hinman, N. et al. Surface morphologies in a Mars analog Ca sulfate salar, High Andes, Northern Chile. Front. Astron. Space Sci. 8, 797591 (2022).Article 

Google Scholar 
Cabrol, N. et al. Record solar UV irradiance in the tropical Andes. Front. Environ. Sci. 2, 19 (2014).Article 

Google Scholar 
Phillips, M.S. et al. Planetary mapping using Deep Learning: a method to evaluate feature identification confidence applied to habitats in Mars-analogue terrain. Astrobiology 23 (2023).Wierzchos, J. et al. Adaptation strategies of endolithic chlorophototrophs to survive the hyperarid and extreme solar radiation environment of the Atacama Desert. Front. Microbiol. 6, 934 (2015).Article 

Google Scholar 
Lynch, K. et al. Near-infrared spectroscopy of lacustrine sediments in the Great Salt Lake Desert: an analog study for Martian paleolake basins. J. Geophys. Res. Planets 120, 599–623 (2015).Article 
ADS 

Google Scholar 
El-Maarry, M., Pommerol, A. & Thomas, N. Analysis of polygonal cracking patterns in chloride-bearing terrains of Mars: indicators of ancient playa settings. J. Geophys. Res. 113, 2263–2278 (2013).Article 

Google Scholar 
Onstott, T. et al. Paleo-rock-hosted life on Earth and the search on Mars: a review and strategy for exploration. Astrobiology 19, 1230–1262 (2019).Article 
ADS 

Google Scholar 
Davila, A. & Schulze-Makuch, D. The last possible outposts for life on Mars. Astrobiology 16, 159–168 (2016).Article 
ADS 

Google Scholar 
Osterloo, M. M. et al. Geologic context of proposed chloride-bearing materials on Mars. J. Geophys. Res. 115, E10012 (2010).Article 
ADS 

Google Scholar 
Flauhaut, J., Martinot, M., Bishop, J.L., Davies, G.R. & Potts, N.J. Remote sensing and in situ mineralogic survey of the Chilean salars: an analog to Mars evaporate deposits? Icarus 282, 152–173 (2017).Bosak, T., Moore, K., Gong, J. & Grotzinger, J. Searching for biosignatures in sedimentary rocks from early Earth and Mars. Nat. Rev. Earth Environ. 2, 490–506 (2021).Article 
ADS 

Google Scholar 
Balci, N. et al. Biotic and abiotic imprints on Mg-rich stromatolites: lessons from Lake Salda, SW Turkey. Geomicrobiol. J. 37, 401–425 (2020).Article 

Google Scholar 
Williams, A., Buck, B., Soukup, D. & Merkler, D. Geomorphic controls on biological soil crust distribution: a conceptual model from the Mojave Desert (USA). Geomorphology 195, 99–109 (2013).Article 
ADS 

Google Scholar 
Warren, J. Evaporites: a Geological Compendium 2nd edn (Springer, 2016).Wierzchos, J. et al. Microbial colonization of Ca sulfate crusts in the hyperarid core of the Atacama Desert: implications for the search for life on Mars. Geobiology 9, 44–60 (2010).Article 

Google Scholar 
Robinson, C. K. et al. Microbial diversity and the presence of algae in halite endolithic communities are correlated to atmospheric moisture in the hyper-arid zone of the Atacama Desert. Environ. Microbiol. 17, 299–315 (2013).Article 

Google Scholar 
Jørgesen, B. & Des Marais, D. Optical properties of benthic photosynthetic communities: fiber-optic studies of cyanobacterial mats. Limnol. Oceanogr. 33, 99–113 (1988).Article 
ADS 

Google Scholar 
Szynkiewicz, A., Moore, C., Glamoclija, M., Bustos, D. & Pratt, L. Origin of coarsely crystalline gypsum domes in a saline playa environment at the White Sands National Monument, New Mexico. J. Geophys. Res. 115, F02021 (2010).Article 
ADS 

Google Scholar 
Walker, J., Spear, J. & Pace, N. Geobiology of a microbial endolithic community in the Yellowstone geothermal environment. Nature 434, 1011–1013 (2005).Article 
ADS 

Google Scholar 
Rasuk, M. et al. Microbial characterization of microbial ecosystems associated to evaporites domes of gypsum in Salar de Llamara in Atacama Desert. Microb. Ecol. 68, 483–494 (2014).Article 

Google Scholar 
Chen, L., Papandreou, G., Kokkinos, I., Murphy, K. & Yuille, A. Semantic image segmentation with deep convolutional nets and fully connected CRFs. Preprint at arXiv https://arxiv.org/abs/1412.7062 (2014).Chan, M. et al. Exploring, mapping and data management integration of habitable environments in astrobiology. Frontiers in Microbiology 10, 147 (2019).Farmer, J. in From Habitability to Life on Mars 1–12 (Elsevier, 2018).Hays, L. et al. Biosignature preservation and detection in Mars analog environments. Astrobiology 17, 363–400 (2017).Article 
ADS 

Google Scholar 
Fairen, A. et al. Astrobiology through the ages of Mars: the study of terrestrial analogues to understand the habitability of Mars. Astrobiology 10, 821 (2010).Article 
ADS 

Google Scholar 
Green, J. et al. Call for a framework for reporting evidence for life beyond Earth. Nature 598, 575–579 (2021).Article 
ADS 

Google Scholar 
He, K., Xiangyu, Z., Shaoqing, R. & Jian, S. Delving deep into rectifiers: surpassing human-level performance on ImageNet classification. In 2015 IEEE International Conference on Computer Vision (ICCV) 1026–1034 (IEEE, 2015).Adams, J. B. & Filice, A. L. Spectral reflectance 0.4 to 2.0 microns of silicate rock powders. J. Geophys. Res. 72, 5705–5715 (1967).National Academies of Sciences, Engineering & Medicine. Origins, Worlds and Life: a Decadal Strategy for Planetary Science and Astrobiology 2023–2032 (National Academies Press, 2022).Rodríguez Albornoz, C. Geology and Controls on Microbiota of the Salar de Pajonales (7.209.000–7.226.500 N.–510.000–530.000 E), Antofagasta, Northern Chile. Master’s thesis, Univ. Católica del Norte Antofagasta (2018).Naranjo, J., Villa, V. & Venegas, C. Geology of the Salar de Pajonales Area and Cerro Moño. Antofagasta and Atacama Regions (Geological Maps of Chile Basic Geology Series No. 153 (1: 100.000), National Geological Service, Geology and Mining Subsection, 2013).Schween, J., Hoffmeister, D. & Löhnert, U. Filling the observational gap in the Atacama Desert with a new network of climate stations. Glob. Planet. Chang. 184, 103034 (2020).Gutiérrez, F. & Cooper, A. Surface morphology of gypsum karst. Treatise Geomorphol. 6, 425–437 (2013).Article 

Google Scholar 
Bishop, J. L. et al. Spectral properties of Ca-sulfates: gypsum, bassanite and anhydrite. Am. Mineral. 99, 2105–2115 (2014).Article 
ADS 

Google Scholar 
Green, A., Berman, M., Switzer, P. & Craig, M. D. A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Trans. Geosci. Remote Sens. 26, 65–74 (1988).Article 
ADS 

Google Scholar 
Davis, W., Pater, I. & McKay, C. P. Rain infiltration and crust formation in the extreme arid zone of the Atacama Desert, Chile. Planet. Space Sci. 58, 616–622 (2010).Article 
ADS 

Google Scholar 
McKay, C. P. et al. Temperature and moisture conditions for life in the extreme arid region of the Atacama Desert: four years of observation including the El Niño of 1997–1998. Astrobiology 3, 393–406 (2003).Article 
ADS 

Google Scholar 
Warren-Rhodes, K., Rhodes, K., Liu, S., Zhou, P. & McKay, C. Nanoclimate environment of cyanobacterial communities in China’s hot and cold hyperarid deserts. J. Geophys. Res. 112, G01016 (2007).Article 
ADS 

Google Scholar 
Warren-Rhodes, K. et al. Physical ecology of hypolithic communities in the central Namib Desert: the role of fog, rain, rock habitat and light. J. Geophys. Res. 118, 1451–1460 (2013).Article 

Google Scholar 
Lange, O., Kilian, E. & Ziegler, H. Water vapor uptake and photosynthesis of lichens: performance differences in species with green and blue–green algae as phycobionts. Oecologia 71, 104–110 (1986).Article 
ADS 

Google Scholar 
Lange, O. L., Meyer, A. & Büdel, B. Net photosynthesis activation of a desiccated cyanobacterium without liquid water in high air humidity alone. Experiments with a Microcoleus sociatus isolated from a desert soil crust. Funct. Ecol. 8, 52–57 (1994).Article 

Google Scholar 
Palmer, R. & Friedmann, E. I. Water relations and photosynthesis in the cryptoendolithic microbial habitat of hot and cold deserts. Microb. Ecol. 18, 111–118 (1990).Article 

Google Scholar 
Potts, M. & Friedmann, E. Effects of water stress on cryptoendolithic cyanobacteria from hot desert rocks. Arch. Microbiol. 130, 267–271 (1981).Article 

Google Scholar 
Tracy, C. et al. Microclimate and limits to photosynthesis in a diverse community of hypolithic cyanobacteria in northern Australia. Environ. Microbiol. 12, 592–607 (2010).Article 

Google Scholar 
Azúa-Bustos, A. et al. Hypolithic cyanobacteria supported mainly by fog in the coastal range of the Atacama Desert. Microb. Ecol. 51, 568–581 (2011).Article 

Google Scholar 
Rull, F. et al. ExoMars Raman Laser Spectrometer for ExoMars. Proc. SPIE 8152, 81520J (2011).Kontoyannis, C. G., Orkoula, M. & Koutsoukos, P. Quantitative analysis of sulphated calcium carbonates using Raman spectrometry and X-ray powder diffraction. Analyst 122, 33–38 (1997).Lopez-Reyes, G. et al. Analysis of the scientific capabilities of the ExoMars Raman Laser Spectrometer Instrument. Eur. J. Mineral. 25, 721–733 (2013).Hunt, G. Spectral signatures of particulate minerals in the visible and near infrared. Geophysics 42, 501–513 (1977).Article 
ADS 

Google Scholar 
Bishop, J. L. in Remote Compositional Analysis: Techniques for Understanding Spectroscopy, Mineralogy, and Geochemistry of Planetary Surfaces (eds Bishop, J. L. et al.) 68–101 (Cambridge Univ. Press, 2019).Morris, R. V. et al. Evidence for pigmentary hematite on Mars based on optical, magnetic and Mössbauer studies of superparamagnetic (nanocrystalline) hematite. J. Geophys. Res. 94, 2760–2778 (1989).Article 
ADS 

Google Scholar 
Bishop, J. L., Pieters, C. M. & Burns, R. G. Reflectance and Mössbauer spectroscopy of ferrihydrite–montmorillonite assemblages as Mars soil analog materials. Geochim. Cosmochim. Acta 57, 4583–4595 (1993).Article 
ADS 

Google Scholar 
Levin, S. A. The problem of pattern and scale in ecology. Ecology 73, 1943–1967 (1992).Article 

Google Scholar 
Underwood, A. J., Chapman, M. G. & Connell, S. D. Observations in ecology: you can’t make progress on processes without understanding the patterns. J. Exp. Mar. Biol. Ecol. 250, 97–115 (2000).Article 

Google Scholar 
Turner, M. G. Landscape ecology: the effect of pattern on process. Annu. Rev. Ecol. Syst. 20, 171–197 (1989).Article 

Google Scholar 
Turner, M. G., Gardner, R. H. & O’Neill, R. V. Landscape Ecology in Theory and Practice (Springer, 2001).Wiens, J. A., Chr, N., Van Horne, B. & Ims, R. A. Ecological mechanisms and landscape ecology. Oikos 66, 369–380 (1993).Article 

Google Scholar 
Urban, D., O’Neill, R. & Shugart, H. Landscape ecology. BioScience 37, 119–127 (1987).Article 

Google Scholar 
Underwood, A. J. et al. Experiments in Ecology: their Logical Design and Interpretation using Analysis of Variance (Cambridge Univ. Press, 1997).Quinn, G. P., & Keough, M. J. Experimental Design and Data Analysis for Biologists (Cambridge Univ. Press, 2002).Neyman, J. & Pearson, E. S. On the problem of the most efficient tests of statistical hypotheses. Philos. Trans. R. Soc. Lond. A 231, 289–337 (1933).Article 
ADS 
MATH 

Google Scholar 
Zar, J. H. Biostatistical Analysis 5th edn (Prentice-Hall/Pearson, 2010).Ripley, B. D. Journal of the Royal Statistical Society Series B (Methodological) 39, 172-212 (1977).Royle, J. A. & Nichols, J. D. Estimating abundance from repeated presence–absence data or point counts. Ecology 84, 777–790 (2003).Article 

Google Scholar 
Krebs, C. Ecological Methodology 2nd edn (Addison-Wesley, 1999).Warren-Rhodes, K., Dungan, J., Piatek, J. & McKay, C. Ecology and spatial pattern of cyanobacterial community island patches in the Atacama Desert. J. Geophys. Res. 112, G04S15 (2007).Article 

Google Scholar 
Belnap, J., Phillips, S., Witwicki, D. & Miller, M. Visually assessing the level of development and soil surface stability of cyanobacterially dominated biological soil crusts. J. Arid Environ. 72, 1257–1264 (2008).Article 
ADS 

Google Scholar 
Warren-Rhodes, K. et al. Hypolithic cyanobacteria, dry limit of photosynthesis, and microbial ecology in the hyperarid Atacama Desert. Microb. Ecol. 52, 389–398 (2006).Article 

Google Scholar 
Yingst, R. et al. Is a linear or a walkabout protocol more efficient when using a rover to choose biologically relevant samples in a small region of interest? Astrobiology 20, 327–347 (2020).Article 
ADS 

Google Scholar 
Shen, J., Wyness, A., Claire, M. & Zerkle, A. Spatial variability of microbial communities and salt distributions across a latitudinal gradient in the Atacama Desert. Microb. Ecol. 82, 442–458 (2021).Article 

Google Scholar 
Barrett, J. et al. Variation in biogeochemistry and soil biodiversity across spatial scales in a polar desert ecosystem. Ecology 85, 3105–3118 (2004).Article 

Google Scholar 
Pointing, S. B. et al. Highly specialized microbial diversity in hyper-arid polar desert. Proc. Natl Acad. Sci. USA 106, 19964–19969 (2009).Article 
ADS 

Google Scholar 
Chiodini, R. et al. Microbial population differentials between mucosal and submucosal intestinal tissues in advanced Crohn’s disease of the ileum. PloS ONE 10, e0134382 (2015).Article 

Google Scholar 
Rivas, L. A. et al. A 200-antibody microarray biochip for environmental monitoring: searching for universal microbial biomarkers through immunoprofiling. Anal. Chem. 80, 7970–7979 (2008).Article 

Google Scholar 
Sanchez-Garcia, L. et al. Microbial biomarker transition in high-altitude sinter mounds from El Tatio (Chile) through different stages of hydrothermal activity. Front. Microbiol. 9, 3350 (2019).Article 

Google Scholar 
Parro, V. et al. SOLID3, a multiplex antibody microarray-based optical sensor instrument for in situ life detection in planetary exploration. Astrobiology 11, 15–28 (2011).Article 
ADS 

Google Scholar 
Parro, V. et al. A microbial oasis in the hypersaline Atacama subsurface discovered by a life detector chip: implications for the search for life on Mars. Astrobiology 11, 969–996 (2011).Article 
ADS 

Google Scholar 
Blanco, Y., Moreno-Paz, M., Aguirre, J. & Parro, V. in Hydrocarbon and Lipid Microbiology Protocols (eds McGenity, T. J. et al.) Ch. 159 (Springer, 2017).Moreno-Paz, M. et al. Detecting nonvolatile life and nonlife-derived organics in a carbonaceous chrondrite analogue with a new multiplex immunoassay and its relevance for planetary exploration. Astrobiology 18, 1041–1056 (2018).Article 
ADS 

Google Scholar 
Ekwealor, J. & Fisher, K. Life under quartz: hypolithic mosses in the Mojave Desert. PLoS ONE 15, e0235928 (2020).Article 

Google Scholar 
Williams, A., Buck, B. & Beyene, M. Biological soil crusts in the Mojave Desert, USA: micromorphology and pedogenesis. Soil Sci. Soc. Am. 76, 1685–1695 (2012).Article 

Google Scholar 
Archer, S. et al. Endolithic microbial diversity in sandstone and granite from the McMurdo Dry Valleys, Antarctica. Polar Biol. 40, 997–1006 (2017).Article 

Google Scholar 
Noffke, N., Gerdes, G., Klenke, T. & Krumbein, W. Microbially induced sedimentary structures—a new category within the classification of primary sedimentary structures. J. Sediment. Res. 71, 649–656 (2001).Article 
ADS 

Google Scholar 
Fierer, N. & Jackson, R. The diversity and biogeography of soil bacterial communities. Proc. Natl Acad. Sci. USA 103, 626–631 (2006).Article 
ADS 

Google Scholar 
Caruso, T. et al. Stochastic and deterministic processes interact in the assembly of desert microbial communities on a global scale. ISME J. 5, 1406–1413 (2011).Article 

Google Scholar 
Valverde et al. Prokaryotic community structure and metabolisms in shallow subsurface of Atacama Desert playas and alluvial fans after heavy rains: repairing and preparing for next dry period. Front. Microbiol. 10, 1641 (2019).Article 

Google Scholar 
Sun, H. Endolithic microbial life in extreme cold climate: snow is required, but perhaps less is more. Biology 2, 693–701 (2013).Maier, S. et al. Photoautotrophic organisms control microbial abundance, diversity and physiology in different types of biological soil crusts. ISME J. 12, 1032–1046 (2018).Article 

Google Scholar 
Roldan, M., Ascaso, C. & Weirzchos, J. Fluorescent fingerprint of endolithic phototrophic cyanobacteria living within halite rocks in the Atacama Desert. Appl. Environ. Microbiol. 80, 2998–3006 (2014).Article 
ADS 

Google Scholar 
Cockell, C. et al. 0.25 Ga salt deposits preserve geological signatures of habitable conditions and ancient lipids. Astrobiology 20, 864–877 (2019).Article 
ADS 

Google Scholar 
Ripley, B. D. Spatial Statistics (Wiley, 1981).Gelfand, A. E., Diggle, P., Guttorp, P., & Fuentes, M. (eds) Handbook of Spatial Statistics (CRC Press, 2010).Dixon, P. M. in Encyclopedia of Environmetrics, 1796-1803 (Wiley, 2006).Baddeley, A., Rubak, E. & Turner, R. Spatial point patterns: methodology and applications with R. J. Stat. Softw. 75, 2 (2016).Wood, S. Generalized Additive Models: an Introduction with R Ch 3–5 (Chapman and Hall/CRC, 2006).Simon, R. & Wood, N. GAMS in practice: mgcv. In Generalized Additive Models: an Introduction with R 2nd ed (eds Blitzstein, J., Faraway, J., Tanner, M. & Zidek, J.) Ch 7 (Chapman and Hall/CRC, 2017).Fang, X. & Chan, K.-S. Generalized Additive Models with Spatio-temporal Data (Univ. Iowa); https://stat.uiowa.edu/sites/stat.uiowa.edu/files/techrep/tr396.pdfLeCun, Y. et al. Backpropagation applied to handwritten zip code recognition. Neural Comput. 1, 541–551 (1989).Article 

Google Scholar 
Roberts, M. et al. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. 3, 199–217 (2021).Article 

Google Scholar 
Shelhamer, E., Long J. & Darrell, T. Fully convolutional networks for semantic segmentation. Preprint at arXiv https://arxiv.org/abs/1605.06211 (2016).Gal, Y. & Ghahramani, Z. Dropout as a Bayesian approximation: representing model uncertainty in deep learning. Preprint at arXiv https://arxiv.org/abs/1506.02142 (2016).Bishop, J. L. & Murad, E. in Volcano–Ice Interactions on Earth and Mars (eds Smellie, J. L. & Chapman, M. G.) 357–370 (Special Publication No. 202, Geological Society, 2002).Buzgar, N., Buzatu, A. & Sanislav, I. V. The Raman study of certain sulfates. An. Stiintificie Univ. Al. I. Cuza IASI Geol. 55, 5–23 (2009).Jehlicka, J., Edwards, H. & Oren, A. Raman spectroscopy of microbial pigments. Appl. Environ. Microbiol. 80, 3286–3295 (2013). More

Forbes, B. C. & Kumpula, T. The ecological role and geography of reindeer (Rangifer tarandus) in Northern Eurasia. Geogr. Compass 3, 1356–1380 (2009).Article 

Google Scholar 
Post, E. & Pedersen, C. Opposing plant community responses to warming with and without herbivores. Proc. Natl Acad. Sci. USA 105, 12353–12358 (2008).Article 
CAS 

Google Scholar 
Berkes, F., Colding, J. & Folke, C. Navigating Social-Ecological Systems: Building Resilience for Complexity and Change (Cambridge Univ. Press, 2003).Tremblay, R., Landry-Cuerrier, M. & Humphries, M. M. Culture and the social-ecology of local food use by Indigenous communities in northern North America. Ecol. Soc. 25, 8 (2020).Kenny, T.-A., Fillion, M., Simpkin, S., Wesche, S. & Chan, L. Caribou (Rangifer tarandus) and Inuit nutrition security in Canada. Ecohealth 15, 590–607 (2018).Article 

Google Scholar 
Benson, K. Gwich’in Knowledge of Porcupine Caribou: State of Current Knowledge and Gaps Assessment (Department of Cultural Heritage, Gwich’in Tribal Council, 2019); https://thelastgreatherd.com/wp-content/uploads/2020/06/GTC-current-knowledge-and-gaps-assessment.pdfParlee, B. & Caine, K. When the Caribou Do Not Come: Indigenous Knowledge and Adaptive Management in the Western Arctic (UBC Press, 2018).Herds: Status of Herds (CircumArctic Rangifer Monitoring and Assessment Network, accessed 3 November 2021); https://carma.caff.is/herdsFesta-Bianchet, M., Ray, J. C., Boutin, S., Côté, S. D. & Gunn, A. Conservation of caribou (Rangifer tarandus) in Canada: an uncertain future. Can. J. Zool. 89, 419–434 (2011).Article 

Google Scholar 
Gunn, A. Voles, lemmings and caribou: population cycles revisited? Rangifer 23, 105–111 (2003).Article 

Google Scholar 
Ferguson, M. A. D., Williamson, R. G. & Messier, F. Inuit knowledge of long-term changes in a population of Arctic tundra caribou. Arctic 51, 201–219 (1998).Article 

Google Scholar 
Beaulieu, D. Dene traditional knowledge about caribou cycles in the Northwest Territories. Rangifer 32, 59–67 (2012).Article 

Google Scholar 
Mallory, C. D. & Boyce, M. S. Observed and predicted effects of climate change on Arctic caribou and reindeer. Environ. Rev. 26, 13–25 (2018).Article 

Google Scholar 
Uboni, A. et al. Long-term trends and role of climate in the population dynamics of Eurasian reindeer. PLoS ONE 11, e0158359 (2016).Article 

Google Scholar 
Chapin, F. S. III et al. Directional changes in ecological communities and social-ecological systems: a framework for prediction based on Alaskan examples. Am. Nat. 168, S36–S49 (2006).Article 

Google Scholar 
Tengö, M. et al. Weaving knowledge systems in IPBES, CBD and beyond – lessons learned for sustainability. Curr. Opin. Environ. Sustain. 26, 17–25 (2017).Article 

Google Scholar 
Berkes, F. Sacred Ecology 4th edn (Routledge, 2018).Stuart Chapin, F. III et al. Earth stewardship: science for action to sustain the human-earth system. Ecosphere 2, 89 (2011).Parlee, B. L., Sandlos, J. & Natcher, D. C. Undermining subsistence: barren-ground caribou in a ‘tragedy of open access’. Sci. Adv. 4, e1701611 (2018).Article 

Google Scholar 
Johnson, J. T. et al. Weaving Indigenous and sustainability sciences to diversify our methods. Sustain. Sci. 11, 1–11 (2016).Article 
CAS 

Google Scholar 
Reid, A. J. et al. ‘Two-eyed seeing’: an Indigenous framework to transform fisheries research and management. Fish Fish. 22, 243–261 (2021).Article 

Google Scholar 
Tengö, M., Brondizio, E. S., Elmqvist, T., Malmer, P. & Spierenburg, M. Connecting diverse knowledge systems for enhanced ecosystem governance: the multiple evidence base approach. AMBIO 43, 579–591 (2014).Article 

Google Scholar 
Aminpour, P. et al. The diversity bonus in pooling local knowledge about complex problems. Proc. Natl Acad. Sci. USA 118, e2016887118 (2021).Article 
CAS 

Google Scholar 
Henri, D. A. et al. Weaving Indigenous knowledge systems and Western sciences in terrestrial research, monitoring and management in Canada: a protocol for a systematic map. Ecol. Solut. Evid. 2, e12057 (2021).Article 

Google Scholar 
Ljubicic, G. J., Mearns, R., Okpakok, S. & Robertson, S. Nunami iliharniq (learning from the land): reflecting on relational accountability in land-based learning and cross-cultural research in Uqšuqtuuq (Gjoa Haven, Nunavut). Arct. Sci. 8, 252–291 (2022).Article 

Google Scholar 
Stern, E. R. & Humphries, M. M. Interweaving local, expert, and Indigenous knowledge into quantitative wildlife analyses: a systematic review. Biol. Conserv. 266, 109444 (2022).Article 

Google Scholar 
Bourgeon, L., Burke, A. & Higham, T. Earliest human presence in North America dated to the last glacial maximum: new radiocarbon dates from Bluefish Caves, Canada. PLoS ONE 12, e0169486 (2017).Article 

Google Scholar 
Kuhnlein, H. V., McDonald, M., Spigelski, D., Vittrekwa, E. & Erasmus, B. in Indigenous Peoples’ Food Systems: the Many Dimensions of Culture, Diversity and Environment for Nutrition and Health (eds Kuhnlein, H. V. et al.) Ch. 3 (FAO, Centre for Indigenous Peoples’ Nutrition and Environment, 2009).Porcupine Caribou Technical Committee. Porcupine Caribou Annual Summary Report 2018–2019 (Porcupine Caribou Management Board, Whitehorse, Yukon, 2019); https://pcmb.ca/wp-content/uploads/2020/06/PCH_annual_summ_report_Nov29_2019_FINAL.pdfIPCC. Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).Zhang, X. et al. in Canada’s Changing Climate Report (eds Bush, E. & Lemmen, D. S.) Ch. 4 (Government of Canada, 2019).Griffith, B. et al. in Arctic Refuge Coastal Plain Terrestrial Wildlife Research Summaries Biological Science Report USGS/BRD BSR-2002-0001 (eds Douglas, D. C. et al.) 8–37 (US Geological Survey, 2002).Russell, D. & Gunn, A. Vulnerability Analysis of the Porcupine Caribou Herd to Potential Development of the 1002 lands in the Arctic National Wildlife Refuge, Alaska (Environment Yukon, Canadian Wildlife Service and GNWT Department of Environment and Natural Resources, 2019); https://pcmb.ca/wp-content/uploads/2021/10/Russell-and-Gunn-PCH-vulnerability-analysis-2019.pdfKruse, J. A. et al. Modeling sustainability of Arctic communities: an interdisciplinary collaboration of researchers and local knowledge holders. Ecosystems 7, 815–828 (2004).Berman, M., Nicolson, C., Fofinas, G., Tetlichi, J. & Martin, S. Adaptation and sustainability in a small Arctic community: results of an agent-based simulation model. Arctic 57, 401–414 (2004).Article 

Google Scholar 
Kofinas, G., Aklavik, Arctic Village, Old Crow & Fort McPherson. in The Earth is Faster Now: Indigenous Observations of Arctic Environmental Change (eds Krupnik, I. & Jolly, D.) 55–91 (Arctic Research Consortium of the United States, 2002).Eamer, J. in Bridging Scales and Knowledge Systems: Concepts and Applications in Ecosystem Assessment (eds Reid, W. V. et al.) 185–206 (Island Press, 2006).Shipley, B. Cause and Correlation in Biology: a User’s Guide to Path Analysis, Structural Equations and Causal Inference with R 2nd edn (Cambridge Univ. Press, 2016).Parlee, B. & Furgal, C. Well-being and environmental change in the Arctic: a synthesis of selected research from Canada’s International Polar Year program. Clim. Change 115, 13–34 (2012).Article 

Google Scholar 
Kofinas, G. P. The Costs of Power Sharing: Community Involvment in Canadian Porcuine Caribou Co-management. PhD thesis, Univ. of British Columbia (1998).Ford, J. D. et al. Including indigenous knowledge and experience in IPCC assessment reports. Nat. Clim. Change 6, 349–353 (2016).Article 

Google Scholar 
Brinkman, T. J. et al. Arctic communities perceive climate impacts on access as a critical challenge to availability of subsistence resources. Clim. Change 139, 413–427 (2016).Article 

Google Scholar 
McNeil, P., Russell, D. E., Griffith, B., Gunn, A. & Kofinas, G. Where the wild things are: seasonal variation in caribou distribution in relation to climate change. Rangifer 25, 51–63 (2005).Berman, M. & Kofinas, G. Hunting for models: grounded and rational choice approaches to analyzing climate effects on subsistence hunting in an Arctic community. Ecol. Econ. 49, 31–46 (2004).Article 

Google Scholar 
Hansen, B. B. et al. Climate events synchronize the dynamics of a resident vertebrate community in the High Arctic. Science 339, 313–315 (2013).Article 
CAS 

Google Scholar 
Collings, P., Marten, M. G., Pearce, T. & Young, A. G. Country food sharing networks, household structure, and implications for understanding food insecurity in Arctic Canada. Ecol. Food Nutr. 55, 30–49 (2016).Article 

Google Scholar 
BurnSilver, S., Magdanz, J., Stotts, R., Berman, M. & Kofinas, G. Are mixed economies persistent or transitional? Evidence using social networks from Arctic Alaska. Am. Anthropol. 118, 121–129 (2016).Article 

Google Scholar 
Baggio, J. A. et al. Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion. Proc. Natl Acad. Sci. USA 113, 13708–13713 (2016).Article 
CAS 

Google Scholar 
Gagnon, C. A. et al. Merging Indigenous and scientific knowledge links climate with the growth of a large migratory caribou population. J. Appl. Ecol. 57, 1644–1655 (2020).Article 

Google Scholar 
Houde, N. The six faces of traditional ecological knowledge: challenges and opportunities for Canadian co-management arrangements. Ecol. Soc. 12, 34 (2007).Article 

Google Scholar 
Fancy, S. G., Pank, L. F., Whitten, K. R. & Regelin, W. L. Seasonal movements of caribou in Arctic Alaska as determined by satellite. Can. J. Zool. 67, 644–650 (1989).Article 

Google Scholar 
Porcupine Caribou Technical Committee. Porcupine Caribou Annual Summary Report 2014 (Porcupine Caribou Management Board, Whitehorse, Yukon, 2014); https://pcmb.ca/wp-content/uploads/2021/07/PCH_annual_summ_report_2014_2015_NOV19_FINAL.pdfEastland, W. G. Influence of Weather on Movements and Migrations of Caribou. PhD thesis, Univ. of Alaska (1991).Tyler, N. J. C. Climate, snow, ice, crashes, and declines in populations of reindeer and caribou (Rangifer tarandus L.). Ecol. Monogr. 80, 197–219 (2010).Article 

Google Scholar 
Hansen, B. B., Aanes, R. & Saether, B. E. Feeding-crater selection by high-arctic reindeer facing ice-blocked pastures. Can. J. Zool. 88, 170–177 (2010).Article 

Google Scholar 
Solberg, E. J. et al. Effects of density-dependence and climate on the dynamics of a Svalbard reindeer population. Ecography 24, 441–451 (2001).Article 

Google Scholar 
Hansen, B. B., Aanes, R., Herfindal, I., Kohler, J. & Sæther, B.-E. Climate, icing, and wild arctic reindeer: past relationships and future prospects. Ecology 92, 1917–1923 (2011).Article 

Google Scholar 
Langlois, A. et al. Detection of rain-on-snow (ROS) events and ice layer formation using passive microwave radiometry: a context for Peary caribou habitat in the Canadian Arctic. Remote Sens. Environ. 189, 84–95 (2017).Article 

Google Scholar 
Russell, D. E., Gunn, A. & White, R. G. CircumArctic collaboration to monitor caribou and wild reindeer. Arctic 68, 6–10 (2015).Article 

Google Scholar 
Russell, D. E. et al. CARMA’s MERRA-based caribou range climate database. Rangifer 33, 145–152 (2013).Article 

Google Scholar 
ArcGIS version 10 (Environmental Systems Resource Institute, 2010).Cai, J., Russell, D. & Whitfield, P. Methodology and Algorithms for Constructing CARMA Bio-climate Tables (Simon Fraser Univ., 2011).Stenseth, N. C. & Mysterud, A. Weather packages: finding the right scale and composition of climate in ecology. J. Anim. Ecol. 74, 1195–1198 (2005).Article 

Google Scholar 
Pebesma, E. J. & Bivand, R. S. Classes and methods for spatial data in R. R News 5, 9–13 (2005).Bivand, R. S., Pebesma, E. J. & Gomez-Rubio, V. Applied Spatial Data Analysis with R 2nd edn (Springer, 2013).Bivand, R. S., Keitt, T. & Rowlingson, B. Rgdal: Bindings for the Geospatial Data Abstraction Library. R package version 0.8-16 (R Foundation for Statistical Computing, 2014); https://cran.r-project.org/web/packages/rgdal/index.htmlBivand, R. S. & Rundel, C. Rgeos: Interface to Geometry Engine – Open Source (GEOS). R package version 0.3-4 (R Foundation for Statistical Computing, 2014); https://cran.r-project.org/web/packages/rgeos/index.htmlLefcheck, J. S. piecewise SEM: piecewise structural equation modelling in R for ecology, evolution and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

Google Scholar 
Shipley, B. Confirmatory path analysis in a generalized multilevel context. Ecology 90, 363–368 (2009).Article 

Google Scholar 
Thomas, D. W. et al. Common paths link food abundance and ectoparasite loads to physiological performance and recruitment in nestling blue tits. Funct. Ecol. 21, 947–955 (2007).Article 

Google Scholar 
Shipley, B. The AIC model selection method applied to path analytic models compared using a d-separation test. Ecology 94, 560–564 (2013).Article 

Google Scholar 
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: a Practical Information-Theoretic Approach (Springer, 2002).Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods Ecol. Evol. 593, 103–113 (2010).Article 

Google Scholar  More

Goal and scope of the studyThe goal of this study was to assess the planetary footprints of GHG mitigation strategies for the global production of plastics. To calculate planetary footprints, we apply LCA in combination with the planetary boundaries framework as proposed by ref. 22. As GHG mitigation strategies, we consider recycling, bio-based production and production via CCU, and compare their planetary footprints to the planetary footprints of fossil-based plastics. We use a bottom-up model covering >90% of global plastic production for 2030 (and 2050, Supplementary Information, section 3). The bottom-up model builds on the plastic production system from ref. 10 and includes plastic production, the supply chain and the disposal of plastics at the end of life.Functional unitIn LCA, the functional unit quantifies the functions of the investigated product system. In this study, the function of the product system is the production and disposal of >90% of global plastics. To cover >90% of global plastics, we define the functional unit as the yearly global production and disposal of 14 large-volume plastics (summarized in Supplementary Table 5). We estimated the yearly production volumes for 2030 and 2050 based on the production volumes in 2015 and the annual growth rates shown in Supplementary Table 5.Our assessment includes plastic disposal. However, the production and disposal of plastics do not necessarily occur in the same year. For instance, while polyolefins used for plastic packaging have an average lifetime of 6 months, the average lifetime of polyurethane used in construction is 35 years11. Including the lifetime of plastics, and hence, the temporal difference between production and disposal, would lead to an increasing plastic stock. An increasing stock, in turn, represents a carbon sink during the production year that appears to enable the production of net-negative GHG emission plastics based on biomass or CCU. However, the plastic stock is not a permanent carbon sink, which would be required for producing net-negative GHG emission plastics55. To avoid misleading conclusions about net-negative bio- and CCU-based plastics, we assign the planetary footprints from disposal to the year of plastic production. Thereby, we conservatively assess the planetary footprints of plastics.In addition, we address the challenge highlighted in ref. 56 that the increasing demand for plastics renders determining the absolute sustainability of plastics difficult. We meet this challenge by assuming a steady-state production system with a recurring functional unit in the same amount every year. We thereby analyse discrete scenarios with constant consumption levels for plastics. Therefore, our conclusions depend on the accuracy of the demand forecasts and apply only to the production volumes considered.System boundariesWe use cradle-to-grave system boundaries, including plastic production and supply chain, potential recycling and final disposal at the end of life. Assessing the use phase of plastics is not possible because of a lack of data. The versatile properties of plastics result in a wide range of applications that cannot be represented in a single study. Furthermore, it would be necessary to consider not only the emissions of the use phase (probably relatively small) but also the system-wide environmental consequences of using plastics in each application compared to other materials. Thus, a consequential assessment of the plastic use phase is desirable but beyond the scope of this study.The plastics supply chain includes several intermediate chemicals such as monomers, solvents or other reactants. The bottom-up model covers the production of all intermediate chemicals in the foreground system. As a background system, we use aggregated datasets from the LCA database ecoinvent. A list of all intermediate chemicals and all aggregated datasets can be found in Supplementary Information, section 1. In addition, the foreground system of the bottom-up model does not include environmental impacts from infrastructure and transportation because of a lack of data. However, we consider the environmental impacts of infrastructure and transportation from other industrial sectors by aggregated datasets, for example, from electricity generation and biomass cultivation.The bottom-up model includes the best available fossil-based technologies and the following technologies for plastic disposal and virgin production based on biomass and CCU.Plastic waste disposalThe bottom-up model includes three options for plastic waste disposal: landfilling, incineration with energy recovery and recycling. Plastic waste can occur in several forms: as sorted fraction of municipal solid waste, as mixed plastics and residues from sorting, and as residues from mechanical recycling. For all fractions, we include waste incineration with energy recovery and landfilling.Landfilled plastic waste is assumed to degrade by approximately 1% of the contained carbon, which is in line with the ecoinvent database45. Mechanical recycling is only modelled for sorted fractions of packaging waste owing to impurities of mixed and non-packaging wastes. In contrast, chemical recycling can be applied to all plastic fractions. In this study, we model chemical recycling as pyrolysis to refinery feedstock, that is, naphtha. The pyrolysis has yields of 29 to 69% depending on the type of plastic (details in Supplementary Information, section 1). Furthermore, we include options for chemical recycling of plastic waste to monomers, which are still early-stage technologies. To derive the minimal necessary recycling rate in Fig. 5, we apply an optimistic scenario with a 95% yield of chemical recycling processes following common modelling in life-cycle inventories of chemicals (Supplementary Information, section 3)57. All calculations are constrained to maximum recycling rates of 94% as the remaining 6% are assumed to be the minimal landfilling rate until the middle of the century11. The assumption is based on historical trends in end-of-life treatment of plastics.Bio-based productionBio-based GHG mitigation is frequently discussed in the literature and is often associated with competition with the food industry58. To avoid competition with the food industry, the bottom-up model is restricted to lignocellulosic biomass as feedstock, that is, energy crops, forest residues and by-products from other industrial biomass processes (for example, bagasse). In this study, unless mentioned otherwise, we model biomass as energy crops because of their potential for large-scale application (Supplementary Information, section 3). However, we conduct a sensitivity analysis for other lignocellulosic biomass sources to assess the sustainability of bio-based plastics in more detail.For each biomass type, we account for the carbon uptake during the biomass growth phase by giving a credit corresponding to the biomass carbon content. We do not consider land use change emissions as current literature lacks an assessment of land use change effects on other Earth-system processes besides climate change.For biomass processing, we include the following high-maturity processes: gasification to syngas and fermentation to ethanol, and the subsequent conversion to methanol and ethylene (Supplementary Table 1). Methanol and ethylene can be further converted to propylene and aromatics, which all together represent the building blocks for all plastics in this study.CCU-based productionCCU-based plastic production particularly requires CO2 and hydrogen. For CO2 supply, we consider CO2 capture from highly concentrated point sources within the plastics supply chain. Highly concentrated point sources include the conventional fossil-based processes, ammonia production, steam methane reforming, ethylene oxide production, the bio-based processes for ethanol and syngas, and plastic waste incineration. Capturing from processes within the plastics supply chain is limited by the amount of CO2 emitted by these processes and avoids the corresponding emissions. For these processes, we considered the energy demand for compressing the CO2 with 0.4 MJ of electricity59. For waste incineration, we consider a decrease in energy output when capturing CO2. All further CO2 sources are conservatively approximated by direct air capture. For 1 kg CO2 captured via direct air capture, we include an uptake of 1 kg of CO2 equivalent while considering the energy demand of 1.29 MJ electricity and 4.19 MJ heat60.Hydrogen for CCU is produced by water electrolysis, with an overall efficiency of 67%61. Previous studies have already shown that renewable electricity is required for CCU to be environmentally beneficial13. Thus, we conduct a sensitivity analysis for multiple electricity technologies to assess their influence on the sustainability of CCU-based plastics (Supplementary Information).For CCU-based production, we include high-maturity technologies, such as CO2-based methanol and methane, as well as subsequent production of olefins and aromatics (Supplementary Table 1). We do not consider CCS as an additional scenario, as fossil resources and storage capacities are ultimately limited. Therefore, CCS may serve as an interim solution for GHG mitigation but stands in contrast to long-term sustainability as the goal of this study.Pathway definitionWe assess nine pathways for the plastics industry towards sustainability. Pathway 1 is fossil-based plastic production (current recycling rate of 23%) that serves as a reference. We also include two pathways that combine all circular technologies: Pathway 2, which minimizes the climate change impact (climate-optimal), and pathway 3, which minimizes the maximal transgression of the share of SOS of the plastics industry (balanced) (Fig. 2). To assess the impact of switching from fossil to renewable feedstocks, we introduce pathway 4, which is bio-based, and pathway 5, which is CCU-based (Fig. 3). Pathways 4 and 5 include the current recycling rate of 23%. In addition, we introduce three pathways with the maximum recycling rates of 94%: pathway 6, in which the remaining virgin production is based on fossil resources; pathway 7, in which it is based on biomass; and pathway 8, in which it is based on CO2 (Fig. 3). Pathway 9 combines biomass, CCU and recycling, and additionally includes chemical recycling of polymers to monomers to calculate the minimal recycling rate to achieve sustainable plastics (Fig. 5).The planetary boundaries frameworkWe follow the recommendations for absolute environmental sustainability assessment in ref. 29 and choose the planetary boundaries framework for the assessment. The planetary boundaries framework suits the goal of the study best because of its precautionary principles for the definition of environmental thresholds, the SOS. We assess eight of the nine Earth-system processes suggested in ref. 21, namely, climate change, ocean acidification, changes in biosphere integrity, the biogeochemical flow of nitrogen and phosphorus (referred to as N cycle and P cycle), aerosol loading, freshwater use, stratospheric ozone depletion, and land-system change. We do not assess the Earth-system process of novel entities since neither control variables nor the boundary itself is yet adequately defined22. We consider the global boundaries for the Earth-system processes in line with the scope of this study. These global boundaries and the corresponding calculation of planetary footprints are subject to assumptions and thus incorporate uncertainty (Supplementary Information, section 2).For the two subprocesses for climate change (namely, atmospheric CO2 concentration and energy imbalance at the top-of-atmosphere), we only consider the energy imbalance at the top-of-atmosphere quantified by radiative forcing. We focus on radiative forcing, as the control variable is more inclusive and fundamental, and the global limits are stricter than for atmospheric CO2 concentration21. Thereby, we conservatively assess climate change.Biosphere integrity is divided into functional and genetic diversity of species. Preserving functional diversity ensures a stable ecosystem by maintaining all ecosystem services. We assess the functional diversity of species using the method proposed in ref. 18. The method covers the mean species abundance loss caused by the two main stressors, direct land use and GHG emissions, as a proxy for the biodiversity intactness index. Genetic diversity provides the long-term ability of the biosphere to persist under and adapt to gradual changes of the environment21. Genetic diversity is often approximated by the global extinction rate. However, using the global extinction rate does not fully cover variation of genetic composition, resulting in high uncertainties when quantifying genetic diversity18. Thus, we focus on functional diversity.Downscaling of the safe operating spaceAs the plastics industry accounts for only a fraction of all human activities, we assign a share of the SOS to plastics. The plastics industry should operate within its assigned share to be considered environmentally sustainable. To assign a share of SOS to the plastics industry, we apply utilitarian downscaling principles. Utilitarian downscaling principles are tailored to maximize welfare in society29. We approximate welfare by consumption expenditure on plastics as an economic indicator for consumer preferences and human needs62. An extensive discussion on the other downscaling principles and their implications can be found in Supplementary Information.Although the final consumption expenditures on plastics are negligible, the industry consumes plastics to produce other goods and services. Accordingly, plastics are produced mostly in the upstream supply chain to support the final consumption of other goods and services. Thus, consuming other goods and services induces plastic production. To account for this inducement of plastic production, we used the total global plastic production xplastics to represent the global intermediate and final consumption expenditure on plastics. For this purpose, we use the gross output vector x of the product-by-product input–output table of EXIOBASE for the year 2020 (ref. 63). To calculate the share of SOS of the plastics industry, we divide the total global plastic production xplastics by the gross world product. The gross world product equals the total global final consumption expenditure. Analogously, we also consider the end-of-life treatment of plastics to be consistent with the system boundaries of the environmental assessment.We estimate the share of SOS for the plastics industry for 2030 and 2050 based on data for the year 2020. Accordingly, we assume that the market share of the plastics industry and, therefore, its share of SOS do not change in the coming years despite the increasing production volume of plastics. Thereby, we implicitly assume that all industries grow equally economically. Alternatively, economic forecasting models could estimate future market shares of plastics. However, applying economic forecasting models is complex, and the results would still be highly uncertain, especially if industry pursues low-carbon technology pathways. Therefore, estimating future market shares is beyond the scope of this study.Technology choice modelTo calculate the planetary footprint of plastics, we use a bottom-up model of the plastics industry. The model builds on the technology choice model (TCM) that allows for linear optimization of production systems27. The TCM represents the production system based on the following elements: technologies, intermediate flows, elementary flows and final demands. Ref. 27 describes each element in detail.The TCM is based on the established computational structure of LCA64. This structure arranges the data that represent the physical production system in the technology matrix A and the elementary flow matrix B. In the technology matrix A, columns represent technologies, and rows represent intermediate flows. Therefore, the coefficient aij of the A matrix corresponds to an intermediate flow i that is either produced (aij  > 0) or consumed (aij  More

Higham, T. E. et al. Linking ecomechanical models and functional traits to understand phenotypic diversity. Trends Ecol. Evol. 36, 860–873 (2021).Article 
PubMed 

Google Scholar 
Kearney, M. R., Jusup, M., McGeoch, M. A., Kooijman, S. A. & Chown, S. L. Where do functional traits come from? The role of theory and models. Funct. Ecol. 35, 1385–1396 (2021).Article 
CAS 

Google Scholar 
Mayr, E. Geographical character gradients and climatic adaptation. Evolution 10, 105–108 (1956).Article 

Google Scholar 
Gaston, K. J., Chown, S. L. & Evans, K. L. Ecogeographical rules: elements of a synthesis. J. Biogeogr. 35, 483–500 (2008).Article 

Google Scholar 
Chown, S. L. & Gaston, K. J. Macrophysiology for a changing world. Proc. R. Soc. B 275, 1469–1478 (2008).Article 
PubMed 
PubMed Central 

Google Scholar 
Rubalcaba, J. G. & Jimeno, B. Biophysical models unravel associations between glucocorticoids and thermoregulatory costs across avian species. Funct. Ecol. 36, 64–72 (2022).Article 
CAS 

Google Scholar 
Anderson, R. O., White, C. R., Chapple, D. G. & Kearney, M. R. A hierarchical approach to understanding physiological associations with climate. Glob. Ecol. Biogeogr. 31, 332–346 (2022).Article 

Google Scholar 
Angilletta, M. J. Jr, Niewiarowski, P. H. & Navas, C. A. The evolution of thermal physiology in ectotherms. J. Therm. Biol. 27, 249–268 (2002).Article 

Google Scholar 
Olalla‐Tárraga, M. Á., Rodríguez, M. Á. & Hawkins, B. A. Broad‐scale patterns of body size in squamate reptiles of Europe and North America. J. Biogeogr. 33, 781–793 (2006).Article 

Google Scholar 
Amado, T., Moreno Pinto, M. G. & Olalla‐Tárraga, M. Á. Anuran 3D models reveal the relationship between surface area‐to‐volume ratio and climate. J. Biogeogr. 46, 1429–1437 (2019).
Google Scholar 
Castro, K. M. S. A. et al. Water constraints drive allometric patterns in the body shape of tree frogs. Sci. Rep. 11, 1218 (2021).Clusella-Trullas, S., Terblanche, J. S., Blackburn, T. M. & Chown, S. L. Testing the thermal melanism hypothesis: a macrophysiological approach. Funct. Ecol. 22, 232–238 (2008).Ghalambor, C. K., Huey, R. B., Martin, P. R., Tewksbury, J. J. & Wang, G. Are mountain passes higher in the tropics? Janzen’s hypothesis revisited. Integr. Comp. Biol. 46, 5–17 (2006).Article 
PubMed 

Google Scholar 
Bennett, J. M. et al. The evolution of critical thermal limits of life on Earth. Nat. Commun. 12, 1198 (2021).Sunday, J. M. et al. Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation. Proc. Natl Acad. Sci. USA 111, 5610–5615 (2014).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Muñoz, M. M. The Bogert effect, a factor in evolution. Evolution 76, 49–66 (2021).Article 
PubMed 

Google Scholar 
Bogert, C. M. Thermoregulation in reptiles, a factor in evolution. Evolution 3, 195–211 (1949).Article 
CAS 
PubMed 

Google Scholar 
Huey, R. B., Hertz, P. E. & Sinervo, B. Behavioral drive versus behavioral inertia in evolution: a null model approach. Am. Nat. 161, 357–366 (2003).Article 
PubMed 

Google Scholar 
Kearney, M. R. & Porter, W. P. NicheMapR—an R package for biophysical modelling: the microclimate model. Ecography 40, 664–674 (2017).Article 

Google Scholar 
Messier, J., McGill, B. J., Enquist, B. J. & Lechowicz, M. J. Trait variation and integration across scales: is the leaf economic spectrum present at local scales? Ecography 40, 685–697 (2017).Article 

Google Scholar 
Ricklefs, R. E. & Schluter, D. (eds) Species Diversity in Ecological Communities: Historical and Geographical Perspectives (Univ. Chicago Press, 1993).Angilletta, M. J. Jr, Steury, T. D. & Sears, M. W. Temperature, growth rate, and body size in ectotherms: fitting pieces of a life-history puzzle. Integr. Comp. Biol. 44, 498–509 (2004).Article 
PubMed 

Google Scholar 
Pincheira-Donoso, D. The balance between predictions and evidence and the search for universal macroecological patterns: taking Bergmann’s rule back to its endothermic origin. Theory Biosci. 129, 247–253 (2010).Article 
PubMed 

Google Scholar 
Slavenko, A. et al. Global patterns of body size evolution in squamate reptiles are not driven by climate. Glob. Ecol. Biogeogr. 28, 471–483 (2019).Article 

Google Scholar 
Stevenson, R. D. Body size and limits to the daily range of body temperature in terrestrial ectotherms. Am. Nat. 125, 102–117 (1985).Article 

Google Scholar 
Rubalcaba, J. G., Gouveia, S. F. & Olalla‐Tárraga, M. A. A mechanistic model to scale up biophysical processes into geographical size gradients in ectotherms. Glob. Ecol. Biogeogr. 28, 793–803 (2019).Article 

Google Scholar 
Rubalcaba, J. G. & Olalla‐Tárraga, M. Á. The biogeography of thermal risk for terrestrial ectotherms: scaling of thermal tolerance with body size and latitude. J. Anim. Ecol. 89, 1277–1285 (2020).Article 
PubMed 

Google Scholar 
Pincheira-Donoso, D., Hodgson, D. J. & Tregenza, T. The evolution of body size under environmental gradients in ectotherms: why should Bergmann’s rule apply to lizards? BMC Evol. Biol. 8, 68 (2008).Jablonski, D. Biotic interactions and macroevolution: extensions and mismatches across scales and levels. Evolution 62, 715–739 (2008).Article 
PubMed 

Google Scholar 
Kearney, M. R., Porter, W. P. & Huey, R. B. Modelling the joint effects of body size and microclimate on heat budgets and foraging opportunities of ectotherms. Methods Ecol. Evol. 12, 458–467 (2021).Article 

Google Scholar 
Campbell-Staton, S. C., Bare, A., Losos, J. B., Edwards, S. V. & Cheviron, Z. A. Physiological and regulatory underpinnings of geographic variation in reptilian cold tolerance across a latitudinal cline. Mol. Ecol. 27, 2243–2255 (2018).Article 
CAS 
PubMed 

Google Scholar 
Boretto, J. M., Fernández, J. B., Cabezas-Cartes, F., Medina, M. S. & Ibargüengoytía, N. R. in Lizards of Patagonia (eds Morando, M. & Avila, L. J.) 335–371 (Springer, 2020).Deutsch, C. A. et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl Acad. Sci. USA 105, 6668–6672 (2008).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Araújo, M. B. et al. Heat freezes niche evolution. Ecol. Lett. 16, 1206–1219 (2013).Article 
PubMed 

Google Scholar 
Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).Article 
PubMed 

Google Scholar 
Hoffmann, A. A., Chown, S. L. & Clusella‐Trullas, S. Upper thermal limits in terrestrial ectotherms: how constrained are they? Funct. Ecol. 27, 934–949 (2013).Article 

Google Scholar 
Sunday, J. et al. Thermal tolerance patterns across latitude and elevation. Philos. Trans. R. Soc. B 374, 20190036 (2019).Article 

Google Scholar 
Huey, R. B. & Slatkin, M. Cost and benefits of lizard thermoregulation. Q. Rev. Biol. 51, 363–384 (1976).Article 
CAS 
PubMed 

Google Scholar 
Vasseur, D. A. et al. Increased temperature variation poses a greater risk to species than climate warming. Proc. R. Soc. B 281, 20132612 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Porter, W. P., Mitchell, J. W., Beckman, W. A. & DeWitt, C. B. Behavioral implications of mechanistic ecology. Oecologia 13, 1–54 (1973).Article 
CAS 
PubMed 

Google Scholar 
Hertz, P. E., Huey, R. B. & Stevenson, R. D. Evaluating temperature regulation by field-active ectotherms: the fallacy of the inappropriate question. Am. Nat. 142, 796–818 (1993).Article 
CAS 
PubMed 

Google Scholar 
Fey, S. B. et al. Opportunities for behavioral rescue under rapid environmental change. Glob. Change Biol. 25, 3110–3120 (2019).Article 

Google Scholar 
Martin, T. L. & Huey, R. B. Why ‘suboptimal’ is optimal: Jensen’s inequality and ectotherm thermal preferences. Am. Nat. 171, E102–E118 (2008).Article 
PubMed 

Google Scholar 
R Core Team. A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).Campbell, G. S. & Norman, J. M. An Introduction to Environmental Biophysics 2nd edn (Springer-Verlag, 1998).Mao, J. & Yan, B. Global Monthly Mean Leaf Area Index Climatology, 1981–2015 (ORNL DAAC, 2019).Meiri, S. et al. Are lizards feeling the heat? A tale of ecology and evolution under two temperatures. Glob. Ecol. Biogeogr. 22, 834–845 (2013).Article 

Google Scholar 
Marino, S., Hogue, I. B., Ray, C. J. & Kirschner, D. E. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theor. Biol. 254, 178–196 (2008).Article 
PubMed 
PubMed Central 

Google Scholar 
Renardy, M., Hult, C., Evans, S., Linderman, J. J. & Kirschner, D. E. Global sensitivity analysis of biological multiscale models. Curr. Opin. Biomed. Eng. 11, 109–116 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Carnell, R. lhs: Latin hypercube samples. R package version 1.1.1 (2020).Meiri, S. Traits of lizards of the world: variation around a successful evolutionary design. Glob. Ecol. Biogeogr. 27, 1168–1172 (2018).Article 

Google Scholar 
Clusella-Trullas, S., Blackburn, T. M. & Chown, S. L. Climatic predictors of temperature performance curve parameters in ectotherms imply complex responses to climate change. Am. Nat. 177, 738–751 (2011).Article 
PubMed 

Google Scholar 
Bennett, J. M. et al. GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms. Sci. Data 5, 180022 (2018).Roll, U. et al. The global distribution of tetrapods reveals a need for targeted reptile conservation. Nat. Ecol. Evol. 1, 1677–1682 (2017).Article 
PubMed 

Google Scholar 
Tonini, J. F. R., Beard, K. H., Ferreira, R. B., Jetz, W. & Pyron, R. A. Fully-sampled phylogenies of squamates reveal evolutionary patterns in threat status. Biol. Conserv. 204, 23–31 (2016).Article 

Google Scholar 
Ives, A. R. R2s for correlated data: phylogenetic models, LMMs, and GLLMs. Syst. Biol. 68, 234–251 (2019).Article 
PubMed 

Google Scholar 
Johnson, T. F., Isaac, N. J. B., Paviolo, A. & González-Suárez, M. Handling missing values in trait data. Glob. Ecol. Biogeogr. 30, 51–62 (2020).Article 

Google Scholar 
Goolsby, E. W., Bruggeman, J. & Ané, C. Rphylopars: fast multivariate phylogenetic comparative methods for missing data and within‐species variation. Methods Ecol. Evol. 8, 22–27 (2017).Article 

Google Scholar 
Koenker, R. et al. Package ‘quantreg’ (R-CRAN, 2018); https://cran.r-project.org/web/packages/quantreg/quantreg.pdfGriffith, D. A. & Peres-Neto, P. R. Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses. Ecology 87, 2603–2613 (2006).Article 
PubMed 

Google Scholar 
Bivand, R. R packages for analyzing spatial data: a comparative case study with areal data. Geogr. Anal. 54, 488–518 (2022).Article 

Google Scholar 
Rubalcaba, J. G. et al. Data: ‘Climate drives global functional trait variation in lizards’. figshare https://doi.org/10.6084/m9.figshare.19949315 (2022). More