Ecology

Macreadie, P. I. et al. The future of Blue Carbon science. Nat. Commun. 10, 3998 (2019).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Herbert, E. R., Windham-Myers, L. & Kirwan, M. L. Sea-level rise enhances carbon accumulation in United States tidal wetlands. One Earth 4, 425–433 (2021).Article 
ADS 

Google Scholar 
Rogers, K. et al. Wetland carbon storage controlled by millennial-scale variation in relative sea-level rise. Nature 567, 91–95 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Murray, N. J. et al. The global distribution and trajectory of tidal flats. Nature 565, 222–225 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Saintilan, N. et al. Thresholds of mangrove survival under rapid sea level rise. Science 368, 1118–1121 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Waycott, M. et al. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc. Natl Acad. Sci. USA 106, 12377–12381 (2009).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kirwan, M. L. & Gedan, K. B. Sea-level driven land conversion and the formation of ghost forests. Nat. Clim. Change 9, 450–457 (2019).Article 
ADS 

Google Scholar 
Raabe, E. A. & Stumpf, R. P. Expansion of tidal marsh in response to sea-level rise: Gulf Coast of Florida, USA. Estuaries Coast. 39, 145–157 (2016).Article 

Google Scholar 
Ury, E. A., Yang, X., Wright, J. P. & Bernhardt, E. S. Rapid deforestation of a coastal landscape driven by sea-level rise and extreme events. Ecol. Appl. 31, e02339 (2021).Article 
PubMed 

Google Scholar 
Mariotti, G. Revisiting salt marsh resilience to sea level rise: are ponds responsible for permanent land loss? J. Geophys. Res. Earth Surf. 121, 1391–1407 (2016).Article 
ADS 

Google Scholar 
Schepers, L., Brennand, P., Kirwan, M. L., Guntenspergen, G. R. & Temmerman, S. Coastal marsh degradation into ponds induces irreversible elevation loss relative to sea level in a microtidal system. Geophys. Res. Lett. 47, e2020GL089121 (2020).Article 
ADS 

Google Scholar 
Schieder, N. W., Walters, D. C. & Kirwan, M. L. Massive upland to wetland conversion compensated for historical marsh loss in Chesapeake Bay, USA. Estuaries Coasts 41, 940–951 (2018).Article 

Google Scholar 
Chmura, G. L., Anisfeld, S. C., Cahoon, D. R. & Lynch, J. C. Global carbon sequestration in tidal, saline wetland soils. Glob. Biogeochem. Cycles 17, 1111 (2003).Fourqurean, J. W. et al. Seagrass ecosystems as a globally significant carbon stock. Nat. Geosci. 5, 505–509 (2012).Article 
ADS 
CAS 

Google Scholar 
Mcleod, E. et al. A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front. Ecol. Environ. 9, 552–560 (2011).Article 

Google Scholar 
Smart, L. S. et al. Aboveground carbon loss associated with the spread of ghost forests as sea levels rise. Environ. Res. Lett. 15, 104028 (2020).Article 
ADS 
CAS 

Google Scholar 
Smith, A. J. & Kirwan, M. L. Sea level-driven marsh migration results in rapid net loss of carbon. Geophys. Res. Lett. 48, e2021GL092420 (2021).Article 
ADS 
CAS 

Google Scholar 
Phang, V. X. H., Chou, L. M. & Friess, D. A. Ecosystem carbon stocks across a tropical intertidal habitat mosaic of mangrove forest, seagrass meadow, mudflat and sandbar. Earth Surf. Process. Landf. 40, 1387–1400 (2015).Article 
ADS 
CAS 

Google Scholar 
Saavedra-Hortua, D. A., Friess, D. A., Zimmer, M. & Gillis, L. G. Sources of particulate organic matter across mangrove forests and adjacent ecosystems in different geomorphic settings. Wetlands 40, 1047–1059 (2020).Article 

Google Scholar 
Windham-Myers, L., Crooks, S. & Troxler, T. G. A Blue Carbon Primer: The State of Coastal Wetland Carbon Science, Practice and Policy (CRC Press, 2018).Donatelli, C., Kalra, T. S., Fagherazzi, S., Zhang, X. & Leonardi, N. Dynamics of marsh-derived sediments in lagoon-type estuaries. J. Geophys. Res. Earth Surf. 125, e2020JF005751 (2020).Article 
ADS 

Google Scholar 
Hopkinson, C. S., Morris, J. T., Fagherazzi, S., Wollheim, W. M. & Raymond, P. A. Lateral marsh edge erosion as a source of sediments for vertical marsh accretion. J. Geophys. Res. Biogeosci. 123, 2444–2465 (2018).Article 
CAS 

Google Scholar 
Mitchell, M. G. E., Bennett, E. M. & Gonzalez, A. Linking landscape connectivity and ecosystem service provision: current knowledge and research gaps. Ecosystems 16, 894–908 (2013).Article 

Google Scholar 
Pearson, R. M. et al. Disturbance type determines how connectivity shapes ecosystem resilience. Sci. Rep. 11, 1188 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Grande, T. O., Aguiar, L. M. S. & Machado, R. B. Heating a biodiversity hotspot: connectivity is more important than remaining habitat. Landsc. Ecol. 35, 639–657 (2020).Article 

Google Scholar 
Olliver, E. A. & Edmonds, D. A. Hydrological connectivity controls magnitude and distribution of sediment deposition within the Deltaic Islands of Wax Lake Delta, LA, USA. J. Geophys. Res. Earth Surf. 126, e2021JF006136 (2021).Article 
ADS 

Google Scholar 
Ward, N. D. et al. Representing the function and sensitivity of coastal interfaces in Earth system models. Nat. Commun. 11, 2458 (2020).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wohl, E. et al. Connectivity as an emergent property of geomorphic systems. Earth Surf. Process. Landf. 44, 4–26 (2019).Article 
ADS 

Google Scholar 
Kirwan, M. L. & Mudd, S. M. Response of salt-marsh carbon accumulation to climate change. Nature 489, 550–553 (2012).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Rietl, A. J., Megonigal, J. P., Herbert, E. R. & Kirwan, M. L. Vegetation type and decomposition priming mediate brackish marsh carbon accumulation under interacting facets of global change. Geophys. Res. Lett. 48, e2020GL092051 (2021).Article 
ADS 
CAS 

Google Scholar 
Kirwan, M. L., Walters, D. C., Reay, W. G. & Carr, J. A. Sea level driven marsh expansion in a coupled model of marsh erosion and migration. Geophys. Res. Lett. 43, 4366–4373 (2016).Article 
ADS 

Google Scholar 
Mariotti, G. & Fagherazzi, S. A numerical model for the coupled long-term evolution of salt marshes and tidal flats. J. Geophys. Res. Earth Surf. 115, F01004 (2010).Theuerkauf, E. J., Stephens, J. D., Ridge, J. T., Fodrie, F. J. & Rodriguez, A. B. Carbon export from fringing saltmarsh shoreline erosion overwhelms carbon storage across a critical width threshold. Estuar. Coast. Shelf Sci. 164, 367–378 (2015).Article 
CAS 

Google Scholar 
Murray, A. B. Reducing model complexity for explanation and prediction. Geomorphology 90, 178–191 (2007).Article 
ADS 

Google Scholar 
Murray, A. B. & Paola, C. A cellular model of braided rivers. Nature 371, 54–57 (1994).Article 
ADS 

Google Scholar 
Mariotti, G. & Carr, J. Dual role of salt marsh retreat: long-term loss and short-term resilience. Water Resour. Res. 50, 2963–2974 (2014).Article 
ADS 

Google Scholar 
Mudd, S. M., Howell, S. M. & Morris, J. T. Impact of dynamic feedbacks between sedimentation, sea-level rise, and biomass production on near-surface marsh stratigraphy and carbon accumulation. Estuar. Coast. Shelf Sci. 82, 377–389 (2009).Article 
ADS 
CAS 

Google Scholar 
Mudd, S. M., Fagherazzi, S., Morris, J. T. & Furbish, D. J. Flow, sedimentation, and biomass production on a vegetated salt marsh in South Carolina: toward a predictive model of marsh morphologic and ecologic evolution. Ecogeomorphology Tidal Marshes 59, 165–188 (2004).Reeves, I. R. B. et al. Impacts of seagrass dynamics on the coupled long-term evolution of barrier-marsh-bay systems. J. Geophys. Res. Biogeosci. 125, e2019JG005416 (2020).Article 
ADS 

Google Scholar 
Spivak, A. C., Sanderman, J., Bowen, J. L., Canuel, E. A. & Hopkinson, C. S. Global-change controls on soil-carbon accumulation and loss in coastal vegetated ecosystems. Nat. Geosci. 12, 685–692 (2019).Article 
ADS 
CAS 

Google Scholar 
de Broek, M. V. et al. Long-term organic carbon sequestration in tidal marsh sediments is dominated by old-aged allochthonous inputs in a macrotidal estuary. Glob. Change Biol. 24, 2498–2512 (2018).Article 
ADS 

Google Scholar 
Noyce, G. L., Kirwan, M. L., Rich, R. L. & Megonigal, J. P. Asynchronous nitrogen supply and demand produce nonlinear plant allocation responses to warming and elevated CO2. Proc. Natl Acad. Sci. USA 116, 21623–21628 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Smith, A. J., Noyce, G. L., Megonigal, J. P., Guntenspergen, G. R. & Kirwan, M. L. Temperature optimum for marsh resilience and carbon accumulation revealed in a whole-ecosystem warming experiment. Glob. Change Biol. 28, 3236–3245 (2022).Article 
CAS 

Google Scholar 
Guimond, J. & Tamborski, J. Salt marsh hydrogeology: a review. Water 13, 543 (2021).Article 
CAS 

Google Scholar 
Xin, P. et al. Surface water and groundwater interactions in salt marshes and their impact on plant ecology and coastal biogeochemistry. Rev. Geophys. 60, e2021RG000740 (2022).Article 
ADS 

Google Scholar 
Chen, Y. & Kirwan, M. L. Climate-driven decoupling of wetland and upland biomass trends on the mid-Atlantic coast. Nat. Geosci. 15, 913–918 (2022).Article 
ADS 
CAS 

Google Scholar 
Rapalee, G., Trumbore, S. E., Davidson, E. A., Harden, J. W. & Veldhuis, H. Soil Carbon stocks and their rates of accumulation and loss in a boreal forest landscape. Glob. Biogeochem. Cycles 12, 687–701 (1998).Article 
ADS 
CAS 

Google Scholar 
Stewart, C. E., Paustian, K., Conant, R. T., Plante, A. F. & Six, J. Soil carbon saturation: concept, evidence and evaluation. Biogeochemistry 86, 19–31 (2007).Article 
CAS 

Google Scholar 
Zhou, T. et al. Age-dependent forest carbon sink: Estimation via inverse modeling. J. Geophys. Res. Biogeosci. 120, 2473–2492 (2015).Article 
CAS 

Google Scholar 
Morris, J. T., Sundareshwar, P. V., Nietch, C. T., Kjerfve, B. & Cahoon, D. R. Responses of coastal wetlands to rising sea level. Ecology 83, 2869–2877 (2002).Article 

Google Scholar 
Kirwan, M. L., Temmerman, S., Skeehan, E. E., Guntenspergen, G. R. & Fagherazzi, S. Overestimation of marsh vulnerability to sea level rise. Nat. Clim. Change 6, 253–260 (2016).Article 
ADS 

Google Scholar 
Brinson, M. M., Christian, R. R. & Blum, L. K. Multiple states in the sea-level induced transition from terrestrial forest to estuary. Estuaries 18, 648–659 (1995).Article 
CAS 

Google Scholar 
Schieder, N. W. & Kirwan, M. L. Sea-level driven acceleration in coastal forest retreat. Geology 47, 1151–1155 (2019).Article 
ADS 

Google Scholar 
Leonardi, N., Ganju, N. K. & Fagherazzi, S. A linear relationship between wave power and erosion determines salt-marsh resilience to violent storms and hurricanes. Proc. Natl Acad. Sci. USA 113, 64–68 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Feagin, R. A., Martinez, M. L., Mendoza-Gonzalez, G. & Costanza, R. Salt marsh zonal migration and ecosystem service change in response to global sea level rise: a case study from an urban region. Ecol. Soc. 15, 14 (2010).Sapkota, Y. & White, J. R. Marsh edge erosion and associated carbon dynamics in coastal Louisiana: a proxy for future wetland-dominated coastlines world-wide. Estuar. Coast. Shelf Sci. 226, 106289 (2019).Article 
CAS 

Google Scholar 
Smith, K. E. L., Terrano, J. F., Khan, N. S., Smith, C. G. & Pitchford, J. L. Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements. Geomorphology 389, 107829 (2021).Article 

Google Scholar 
Bouma, T. J. et al. Short-term mudflat dynamics drive long-term cyclic salt marsh dynamics. Limnol. Oceanogr. 61, 2261–2275 (2016).Article 
ADS 

Google Scholar 
Gillis, L. G. et al. Potential for landscape-scale positive interactions among tropical marine ecosystems. Mar. Ecol. Prog. Ser. 503, 289–303 (2014).Article 
ADS 

Google Scholar 
Schuerch, M., Dolch, T., Reise, K. & Vafeidis, A. T. Unravelling interactions between salt marsh evolution and sedimentary processes in the Wadden Sea (southeastern North Sea). Prog. Phys. Geogr. Earth Environ. 38, 691–715 (2014).Article 

Google Scholar 
Gonneea, M. E. et al. Salt marsh ecosystem restructuring enhances elevation resilience and carbon storage during accelerating relative sea-level rise. Estuar. Coast. Shelf Sci. 217, 56–68 (2019).Article 
ADS 
CAS 

Google Scholar 
McTigue, N. et al. Sea level rise explains changing carbon accumulation rates in a salt marsh over the past two millennia. J. Geophys. Res. Biogeosci. 124, 2945–2957 (2019).Article 
CAS 

Google Scholar 
Wang, F., Lu, X., Sanders, C. J. & Tang, J. Tidal wetland resilience to sea level rise increases their carbon sequestration capacity in United States. Nat. Commun. 10, 5434 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, F. et al. Global blue carbon accumulation in tidal wetlands increases with climate change. Natl Sci. Rev. 8, nwaa296 (2021).Article 
CAS 
PubMed 

Google Scholar 
Ganju, N. K., Defne, Z., Elsey-Quirk, T. & Moriarty, J. M. Role of tidal wetland stability in lateral fluxes of particulate organic matter and carbon. J. Geophys. Res. Biogeosci. 124, 1265–1277 (2019).Article 
CAS 

Google Scholar 
Krauss, K. W. et al. The role of the upper tidal estuary in wetland blue carbon storage and flux. Glob. Biogeochem. Cycles 32, 817–839 (2018).Article 
ADS 
CAS 

Google Scholar 
Baustian, M. M., Stagg, C. L., Perry, C. L., Moss, L. C. & Carruthers, T. J. B. Long-term carbon sinks in marsh soils of coastal louisiana are at risk to wetland loss. J. Geophys. Res. Biogeosci. 126, e2020JG005832 (2021).Article 
ADS 

Google Scholar 
DeLaune, R. D. & White, J. R. Will coastal wetlands continue to sequester carbon in response to an increase in global sea level?: a case study of the rapidly subsiding Mississippi river deltaic plain. Clim. Change 110, 297–314 (2012).Article 
ADS 

Google Scholar 
Lovelock, C. E. & Duarte, C. M. Dimensions of Blue Carbon and emerging perspectives. Biol. Lett. 15, 20180781 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Lovelock, C. E. & Reef, R. Variable impacts of climate change on Blue Carbon. One Earth 3, 195–211 (2020).Article 
ADS 

Google Scholar 
Bernal, B. & Mitsch, W. J. Comparing carbon sequestration in temperate freshwater wetland communities. Glob. Change Biol. 18, 1636–1647 (2012).Article 
ADS 

Google Scholar 
Mack, S. K., Lane, R. R., Deng, J., Morris, J. T. & Bauer, J. J. Wetland carbon models: applications for wetland carbon commercialization. Ecol. Model. 476, 110228 (2023).Article 
CAS 

Google Scholar 
Young, I. R. & Verhagen, L. A. The growth of fetch limited waves in water of finite depth. Part 1. Total energy and peak frequency. Coast. Eng. 29, 47–78 (1996).Article 

Google Scholar 
Mariotti, G. & Fagherazzi, S. Critical width of tidal flats triggers marsh collapse in the absence of sea-level rise. Proc. Natl Acad. Sci. USA 110, 5353–5356 (2013).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Koppel, J., van de, Wal, D., van der, Bakker, J. P. & Herman, P. M. J. Self‐organization and vegetation collapse in salt marsh ecosystems. Am. Nat. 165, E1–E12 (2005).Article 
PubMed 

Google Scholar 
D’Alpaos, A., Lanzoni, S., Marani, M. & Rinaldo, A. Landscape evolution in tidal embayments: modeling the interplay of erosion, sedimentation, and vegetation dynamics. J. Geophys. Res. Earth Surf. 112, F01008 (2007).Kirwan, M. L. et al. Limits on the adaptability of coastal marshes to rising sea level. Geophys. Res. Lett. 37, L23401 (2010).Larsen, L. G. & Harvey, J. W. How vegetation and sediment transport feedbacks drive landscape change in the everglades and wetlands worldwide. Am. Nat. 176, E66–E79 (2010).Article 
PubMed 

Google Scholar 
Smith, J. A. M. The role of Phragmites australis in mediating inland salt marsh migration in a Mid-Atlantic Estuary. PLoS ONE 8, e65091 (2013).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Mariotti, G., Elsey-Quirk, T., Bruno, G. & Valentine, K. Mud-associated organic matter and its direct and indirect role in marsh organic matter accumulation and vertical accretion. Limnol. Oceanogr. 65, 2627–2641 (2020).Article 
ADS 
CAS 

Google Scholar 
Ladd, C. J. T., Duggan-Edwards, M. F., Bouma, T. J., Pagès, J. F. & Skov, M. W. Sediment supply explains long-term and large-scale patterns in salt marsh lateral expansion and erosion. Geophys. Res. Lett. 46, 11178–11187 (2019).Article 
ADS 

Google Scholar 
Törnqvist, T. E., Jankowski, K. L., Li, Y.-X. & González, J. L. Tipping points of Mississippi Delta marshes due to accelerated sea-level rise. Sci. Adv. 6, eaaz5512 (2020).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Fagherazzi, S. et al. Numerical models of salt marsh evolution: ecological, geomorphic, and climatic factors. Rev. Geophys. 50, RG1002 (2012). More

Alston, J. M. et al. Reciprocity in restoration ecology: When might large carnivore reintroduction restore ecosystems?. Biol. Conserv. 234, 82–89 (2019).Article 

Google Scholar 
Ripple, W. J. & Beschta, R. L. Large predators limit herbivore densities in northern forest ecosystems. Eur. J. Wildl. Res. 58, 733–742 (2012).Article 

Google Scholar 
Estes, J. A. & Duggins, D. O. Sea otters and kelp forests in Alaska: Generality and variation in a community ecological paradigm. Ecol. Monogr. 65, 75–100 (1995).Article 

Google Scholar 
Schmitz, O. J., Beckerman, A. P. & O’Brien, K. M. Behaviorally mediated trophic cascades: Effects of predation risk on food web interactions. Ecology 78, 1388–1399 (1997).Article 

Google Scholar 
Power, M. E. Top-down and bottom-up forces in food webs: Do plants have primacy. Ecology 73, 733–746 (1992).Article 

Google Scholar 
Travers, T., Lea, M. A., Alderman, R., Terauds, A. & Shaw, J. Bottom-up effect of eradications: The unintended consequences for top-order predators when eradicating invasive prey. J. Appl. Ecol. 58, 801–811 (2021).Article 

Google Scholar 
Stoessel, M., Elmhagen, B., Vinka, M., Hellström, P. & Angerbjörn, A. The fluctuating world of a tundra predator guild: bottom-up constraints overrule top-down species interactions in winter. Ecography (Cop.) 42, 488–499 (2019).Article 

Google Scholar 
Wolf, C. & Ripple, W. J. Rewilding the world ’s large carnivores. R. Soc. Open Sci. 5, 172235 (2018).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Krofel, M. & Jerina, K. Mind the cat: Conservation management of a protected dominant scavenger indirectly affects an endangered apex predator. Biol. Conserv. 197, 40–46 (2016).Article 

Google Scholar 
Prugh, L. R. & Sivy, K. J. Enemies with benefits: Integrating positive and negative interactions among terrestrial carnivores. Ecol. Lett. https://doi.org/10.1111/ele.13489 (2020).Article 
PubMed 

Google Scholar 
Caro, T. M. & Stoner, C. J. The potential for interspecific competition among African carnivores. Biol. Conserv. 110, 67–75 (2003).Article 

Google Scholar 
Linnell, J. D. C. & Strand, O. Interference interactions, co-existence and conservation of mammalian carnivores. Divers. Distrib. 6, 169–176 (2000).Article 

Google Scholar 
Newsome, T. M. et al. Top predators constrain mesopredator distributions. Nat. Commun. 8, 15469 (2017).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Crooks, K. & Soulé, M. Mesopredator release and avifaunal extinctions in a fragmented system. Nature 400, 563–566 (1999).Article 
ADS 
CAS 

Google Scholar 
Schoener, T. W. Resource partitioning in ecological communities. Science 185, 27–39 (1974).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Fedriani, J. M., Fuller, T. K., Sauvajot, R. M. & York, E. C. Competition and intraguild predation among three sympatric carnivores. Oecologia 125, 258–270 (2000).Article 
ADS 
PubMed 

Google Scholar 
Monterroso, P., Díaz-Ruiz, F., Lukacs, P. M., Alves, P. C. & Ferreras, P. Ecological traits and the spatial structure of competitive coexistence among carnivores. Ecology 101, 1–16 (2020).Article 

Google Scholar 
Karanth, K. U. et al. Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient. Proc. R. Soc. B Biol. Sci. 284, 20161860 (2017).Article 

Google Scholar 
Ferreiro-Arias, I., Isla, J., Jordano, P. & Benítez-López, A. Fine-scale coexistence between Mediterranean mesocarnivores is mediated by spatial, temporal, and trophic resource partitioning. Ecol. Evol. 11, 15520–15533 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Di Bitetti, M. S., De Angelo, C. D., Di Blanco, Y. E. & Paviolo, A. Niche partitioning and species coexistence in a Neotropical felid assemblage. Acta Oecol. 36, 403–412 (2010).Article 
ADS 

Google Scholar 
Carvalho, J. C. & Gomes, P. Feeding resource partitioning among four sympatric carnivores in the Peneda-Gerês National Park (Portugal). J. Zool. 263, 275–283 (2004).Article 

Google Scholar 
Gil-Sánchez, J. M., Mañá-Varela, B., Herrera-Sánchez, F. J. & Urios, V. Spatio-temporal ecology of a carnivore community in middle atlas NW of Morocco. Zoology 146, 125904 (2021).Article 
PubMed 

Google Scholar 
Monterroso, P., Alves, P. C. & Ferreras, P. Plasticity in circadian activity patterns of mesocarnivores in Southwestern Europe: Implications for species coexistence. Behav. Ecol. Sociobiol. 68, 1403–1417 (2014).Article 

Google Scholar 
Gallagher, A. J., Creel, S., Wilson, R. P. & Cooke, S. J. Energy landscapes and the landscape of fear. Trends Ecol. Evol. 32, 88–96 (2017).Article 
PubMed 

Google Scholar 
Sergio, F. & Hiraldo, F. Intraguild predation in raptor assemblages: A review. Ibis 150, 132–145 (2008).Article 

Google Scholar 
Jiménez, J. et al. Restoring apex predators can reduce mesopredator abundances. Biol. Conserv. 238, 108234 (2019).Article 

Google Scholar 
Palomares, F., Ferreras, P., Fedriani, J. M. & Delibes, M. Spatial relationships between Iberian lynx and other carnivores in an area of south-western Spain. J. Appl. Ecol. 33, 5–13 (1996).Article 

Google Scholar 
Wooster, E. I. F., Ramp, D., Lundgren, E. J., O’Neill, A. J. & Wallach, A. D. Red foxes avoid apex predation without increasing fear. Behav. Ecol. 32, 895–902 (2021).Article 

Google Scholar 
Santos, F. et al. Prey availability and temporal partitioning modulate felid coexistence in Neotropical forests. PLoS ONE 14, 1–23 (2019).Article 

Google Scholar 
Barrientos, R. & Virgós, E. Reduction of potential food interference in two sympatric carnivores by sequential use of shared resources. Acta Oecol. 30, 107–116 (2006).Article 
ADS 

Google Scholar 
MacArthur, R. H. & Pianka, E. R. On optimal use of a patchy environment. Am. Nat. 100, 603–609 (1966).Article 

Google Scholar 
López-Martín, J. M. Comparison of feeding behaviour between stone marten and common genet: living in coexistence. Martes Carniv. Communities 137–155 (2006).Sarmento, P. et al. Adapt or perish: How the Iberian lynx reintroduction affects fox abundance and behaviour. Hystrix Ital. J. Mammal. 32, 48–54 (2021).
Google Scholar 
Forsyth, D. M., Ramsey, D. S. L. & Woodford, L. P. Estimating abundances, densities, and interspecific associations in a carnivore community. J. Wildl. Manag. 83, 1090–1102 (2019).Article 

Google Scholar 
Monterroso, P. et al. Disease-mediated bottom-up regulation: An emergent virus affects a keystone prey, and alters the dynamics of trophic webs. Sci. Rep. 6, 1–9 (2016).Article 

Google Scholar 
Ritchie, E. G. et al. Ecosystem restoration with teeth: What role for predators?. Trends Ecol. Evol. 27, 265–271 (2012).Article 
PubMed 

Google Scholar 
Santos-Reis, M. et al. Relationships between stone martens, genets and cork oak woodlands in Portugal. Martens Fish. Hum.-Altered Environ. Int. Perspect. https://doi.org/10.1007/0-387-22691-5_7 (2004).Article 

Google Scholar 
Goszczyński, J., Posłuszny, M., Pilot, M. & Gralak, B. Patterns of winter locomotion and foraging in two sympatric marten species: Martes martes and Martes foina. Can. J. Zool. 85, 239–249 (2007).Article 
ADS 

Google Scholar 
Díaz-Ruiz, F., Caro, J., Delibes-Mateos, M., Arroyo, B. & Ferreras, P. Drivers of red fox (Vulpes vulpes) daily activity: Prey availability, human disturbance or habitat structure?. J. Zool. 298, 128–138 (2016).Article 

Google Scholar 
Zanón Martínez, J. I., Seoane, J., Kelly, M. J., Sarasola, J. H. & Travaini, A. Assessing carnivore spatial co-occurrence and temporal overlap in the face of human interference in a semi-arid forest. Ecol. Appl. https://doi.org/10.1002/eap.2482 (2021).Article 
PubMed 

Google Scholar 
Allen, M. L., Sibarani, M. C., Utoyo, L. & Krofel, M. Terrestrial mammal community richness and temporal overlap between tigers and other carnivores in Bukit Barisan Selatan National Park Sumatra. Anim. Biodivers. Conserv. 1, 97–107 (2020).Article 

Google Scholar 
Vilella, M., Ferrandiz-Rovira, M. & Sayol, F. Coexistence of predators in time: Effects of season and prey availability on species activity within a Mediterranean carnivore guild. Ecol. Evol. 10, 11408–11422 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Santos, N. et al. Protein metabolism and physical fitness are physiological determinants of body condition in Southern European carnivores. Sci. Rep. 10, 1–11 (2020).Article 

Google Scholar 
Ferreras, P., Travaini, A., Cristina Zapata, S. & Delibes, M. Short-term responses of mammalian carnivores to a sudden collapse of rabbits in Mediterranean Spain. Basic Appl. Ecol. 12, 116–124 (2011).Article 

Google Scholar 
Moreno, S. Reproduction of Garden Dormouse Eliomys quercinus lusitanicus, in southwest Spain. Mammalia 52, 401–408 (1988).Article 

Google Scholar 
Bakaloudis, D. E., Vlachos, C. G., Papakosta, M. A., Bontzorlos, V. A. & Chatzinikos, E. N. Diet composition and feeding strategies of the stone marten (Martes foina) in a typical mediterranean ecosystem. Sci. World J. 2012, 1–11 (2012).Article 

Google Scholar 
Pereira, L. M., Owen-Smith, N. & Moleón, M. Facultative predation and scavenging by mammalian carnivores: Seasonal, regional and intra-guild comparisons. Mamm. Rev. 44, 44–55 (2014).Article 

Google Scholar 
Gil-Sánchez, J. M., Ballesteros-Duperón, E. & Bueno-Segura, J. F. Feed ing ecology of the Iberian lynx Lynx pardinus in east ern. Acta Theriol. (Warsz) 51, 85–90 (2006).Article 

Google Scholar 
Krofel, M., Huber, D. & Kos, I. Diet of Eurasian lynx Lynx lynx in the northern Dinaric Mountains (Slovenia and Croatia). Acta Theriol. (Warsz) 56, 315–322 (2011).Article 

Google Scholar 
Virgós, E., Baniandrés, N., Burgos, T. & Recio, M. R. Intraguild predation by the eagle owl determines the space use of a mesopredator carnivore. Diversity 12, 13–15 (2020).Article 

Google Scholar 
Gordon, C. E., Feit, A., Grüber, J. & Letnic, M. Mesopredator suppression by an apex predator alleviates the risk of predation perceived by small prey. Proc. R. Soc. B Biol. Sci. 282, 20142870 (2015).Article 

Google Scholar 
Draper, J. P., Young, J. K., Schupp, E. W., Beckman, N. G. & Atwood, T. B. Frugivory and seed dispersal by carnivorans. Front. Ecol. Evol. 10, 864864 (2022).Article 

Google Scholar 
González-Varo, J. P., López-Bao, J. V. & Guitián, J. Functional diversity among seed dispersal kernels generated by carnivorous mammals. J. Anim. Ecol. 82, 562–571 (2013).Article 
PubMed 

Google Scholar 
Virgós, E., Llorente, M. & Cortés, Y. Geographical variation in genet (Genetta genetta L.) diet: A literature review. Mamm. Rev. 29, 117–126 (1999).Article 

Google Scholar 
Fedriani, J. M., Ayllón, D., Wiegand, T. & Grimm, V. Intertwined effects of defaunation, increased tree mortality and density compensation on seed dispersal. Ecography (Cop.) 43, 1352–1363 (2020).Article 

Google Scholar 
Burgos, T. et al. Predation risk can modify the foraging behaviour of frugivorous carnivores: Implications of rewilding apex predators for plant–animal mutualisms. J. Anim. Ecol. https://doi.org/10.1111/1365-2656.13682 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Escribano-Ávila, G. et al. Spanish juniper gain expansion opportunities by counting on a functionally diverse dispersal assemblage community. Ecol. Evol. 3, 3751–3763 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Gazzola, A. & Balestrieri, A. Nutritional ecology provides insights into competitive interactions between closely related Martes species. Mamm. Rev. 50, 82–90 (2020).Article 

Google Scholar 
Simón, M. A. et al. Diez años de conservación del lince ibérico, 326 (2012).Royle, J. A., Chandler, R. B., Sollmann, R. & Gardner, B. Spatial Capture-Recapture (Elsevier, 2014).
Google Scholar 
Rodríguez, A. & Calzada, J. Lynx pardinus (errata version published in 2020). The IUCN Red List of Threatened Species 2015. https://doi.org/10.2305/IUCN.UK.2015-2.RLTS.T12520A174111773.en (Accessed 27 January 2023) (2015).Gil-Sánchez, J. M. et al. The use of camera trapping for estimating Iberian lynx (Lynx pardinus) home ranges. Eur. J. Wildl. Res. 57, 1203–1211 (2011).Article 

Google Scholar 
Gerber, B. D., Karpanty, S. M. & Kelly, M. J. Evaluating the potential biases in carnivore capture-recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet. Popul. Ecol. 54, 43–54 (2012).Article 

Google Scholar 
Jiménez, J., Díaz-Ruiz, F., Monterroso, P., Tobajas, J. & Ferreras, P. Occupancy data improves parameter precision in spatial capture–recapture models. Ecol. Evol. https://doi.org/10.1002/ece3.9250 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Ferreras, P., DÍaz-Ruiz, F. & Monterroso, P. Improving mesocarnivore detectability with lures in camera-trapping studies. Wildl. Res. 45, 505–517 (2018).Article 

Google Scholar 
Ridout, M. S. & Linkie, M. Estimating overlap of daily activity patterns from camera trap data. J. Agric. Biol. Environ. Stat. 14, 322–337 (2009).Article 
MathSciNet 
MATH 

Google Scholar 
Jiménez, J. et al. Estimating carnivore community structures. Sci. Rep. https://doi.org/10.1038/srep41036 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Genovesi, P., Sinibaldi, I. & Boitani, L. Spacing patterns and territoriality of the stone marten. Can. J. Zool. 75, 1966–1971 (1997).Article 

Google Scholar 
Royle, J. A. & Converse, S. J. Hierarchical spatial capture-recapture models: Modelling population density in stratified populations. Methods Ecol. Evol. 5, 37–43 (2014).Article 

Google Scholar 
Palomares, F. & Delibes, M. Spatio-temporal ecology and behavior of European genets in southwestern Spain. J. Mammal. 75, 714–724 (1994).Article 

Google Scholar 
Camps, D. Jineta – Genetta genetta. En Encicl. Virtual los Vertebr. Españoles. Salvador. A., Barja, I. (Eds.). Mus. Nac. Ciencias Nat. Madrid. https://www.vertebradosibericos.org/ (2017).Efford, M. Density estimation in live-trapping studies. Oikos 106, 598–610 (2004).Article 

Google Scholar 
de Valpine, P. et al. Programming with models: Writing statistical algorithms for general model structures with NIMBLE. J. Comput. Graph. Stat. 26, 403–413 (2017).Article 
MathSciNet 

Google Scholar 
NIMBLE Development Team. NIMBLE user manual (2017).Morin, D. J., Waits, L. P., McNitt, D. C. & Kelly, M. J. Efficient single-survey estimation of carnivore density using fecal DNA and spatial capture-recapture: A bobcat case study. Popul. Ecol. 60, 197–209 (2018).Article 

Google Scholar 
Gelman, A. et al. Bayesian Data Analysis (CRC Press, 2013).Book 

Google Scholar 
Weitzman, M. S. Measure of the Overlap of Income Distribution of White and Negro Families in the United States. Technical report No 22 (1970).Jammalamadaka, S. R. & Sengupta, A. Topics in Circular Statistics. Series on Multivariate Analyisis Vol. 5 (World Scientific, 2001).Book 

Google Scholar 
Efron, B. & Tibshirani, R. J. An Introduction to the Bootstrap (CRC Press, 1994).Book 
MATH 

Google Scholar 
Mielke, P. W., Berry, K. J. & Johnson, E. S. Multi-response permutation proccedures for a priori classifications. Commun. Stat. Theory Methods 5, 1409–1424 (1976).Article 
MATH 

Google Scholar 
Nakagawa, S., Johnson, P. C. D. & Schielzeth, H. The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. J. R. Soc. Interface 14, 20170213 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. lme4: Linear mixed-effects models. R Packag. version 1.1.21 (2020).Barton, K. Package “MuMIn: Multi-model inference” for R. R Packag. Version 1.9.5 45 (2013). More

Dove, A. D. & Pierce, S. J. Whale Sharks: Biology, Ecology, and Conservation (CRC Press, 2021).Friedman, M. et al. 100-million-year dynasty of giant planktivorous bony fishes in the Mesozoic seas. Science 327, 990–993 (2010).Article 
CAS 
PubMed 

Google Scholar 
Friedman, M. Parallel evolutionary trajectories underlie the origin of giant suspension-feeding whales and bony fishes. Proc. R. Soc. B https://doi.org/10.1098/rspb.2011.1381 (2011).Sanderson, S. L. & Wassersug, R. in The Skull: Functional and Evolutionary Mechanisms Vol. 3 (eds Hanken, J. & Hall, B. K.) 37–112 (Univ. Chicago Press, 1993).Rowat, D. & Brooks, K. A review of the biology, fisheries and conservation of the whale shark Rhincodon typus. J. Fish Biol. 80, 1019–1056 (2012).Article 
CAS 
PubMed 

Google Scholar 
Pimiento, C., Cantalapiedra, J. L., Shimada, K., Field, D. J. & Smaers, J. B. Evolutionary pathways toward gigantism in sharks and rays. Evolution 73, 588–599 (2019).Article 
PubMed 

Google Scholar 
Stiefel, K. M. Evolutionary trends in large pelagic filter-feeders. Hist. Biol. 33, 1477–1488 (2021).Article 

Google Scholar 
Goldbogen, J. & Madsen, P. The largest of August Krogh animals: physiology and biomechanics of the blue whale revisited. Comp. Biochem. Physiol. A 254, 110894 (2021).Article 
CAS 

Google Scholar 
Jørgensen, C. B. Quantitative aspects of filter feeding in invertebrates. Biol. Rev. 30, 391–453 (1955).Article 

Google Scholar 
Radke, R. J. & Kahl, U. Effects of a filter‐feeding fish [silver carp, Hypophthalmichthys molitrix (Val.)] on phyto‐and zooplankton in a mesotrophic reservoir: results from an enclosure experiment. Freshw. Biol. 47, 2337–2344 (2002).Article 

Google Scholar 
Schiemer, F. in Perspectives in Tropical Limnology (eds Schiemer, F. & Boland, K.T.) 65–76 (SPB Academic Publishing, 1996).Carey, N. & Goldbogen, J. A. Kinematics of ram filter feeding and beat-glide swimming in the northern anchovy Engraulis mordax. J. Exp. Biol. 220, 2717–2725 (2017).PubMed 

Google Scholar 
Haines, G. E. & Sanderson, S. L. Integration of swimming kinematics and ram suspension feeding in a model American paddlefish, Polyodon spathula. J. Exp. Biol. 220, 4535–4547 (2017).PubMed 

Google Scholar 
Paig‐Tran, E. M., Kleinteich, T. & Summers, A. P. The filter pads and filtration mechanisms of the devil rays: variation at macro and microscopic scales. J. Morphol. 274, 1026–1043 (2013).Article 
PubMed 

Google Scholar 
Jacobsen, I. P. & Bennett, M. B. A comparative analysis of feeding and trophic level ecology in stingrays (Rajiformes; Myliobatoidei) and electric rays (Rajiformes: Torpedinoidei). PLoS ONE 8, e71348 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ellis, J. Occurrence of pelagic stingray Pteroplatytrygon violacea (Bonaparte, 1832) in the North Sea. J. Fish Biol. 71, 933–937 (2007).Article 

Google Scholar 
Werth, A. J. & Potvin, J. Baleen hydrodynamics and morphology of cross-flow filtration in balaenid whale suspension feeding. PLoS ONE 11, e0150106 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Orton, L. S. & Brodie, P. F. Engulfing mechanics of fin whales. Can. J. Zool. 65, 2898–2907 (1987).Article 

Google Scholar 
Shadwick, R. E., Goldbogen, J. A., Potvin, J., Pyenson, N. D. & Vogl, A. W. Novel muscle and connective tissue design enables high extensibility and controls engulfment volume in lunge-feeding rorqual whales. J. Exp. Biol. 216, 2691–2701 (2013).PubMed 

Google Scholar 
Shadwick, R. E., Goldbogen, J. A., Pyenson, N. D. & Whale, J. C. Structure and function in the lunge feeding apparatus: mechanical properties of the fin whale mandible. Anat. Rec. 300, 1953–1962 (2017).Article 

Google Scholar 
Werth, A. J., Ito, H. & Ueda, K. Multiaxial movements at the minke whale temporomandibular joint. J. Morphol. 281, 402–412 (2020).Article 
PubMed 

Google Scholar 
Lambertsen, R., Ulrich, N. & Straley, J. Frontomandibular stay of Balaenopteridae: a mechanism for momentum recapture during feeding. J. Mammal. 76, 877–899 (1995).Article 

Google Scholar 
Pyenson, N. D. et al. Discovery of a sensory organ that coordinates lunge feeding in rorqual whales. Nature 485, 498–501 (2012).Article 
CAS 
PubMed 

Google Scholar 
Goldbogen, J. A. et al. How baleen whales feed: the biomechanics of engulfment and filtration. Annu. Rev. Mar. Sci. 9, 367–386 (2017).Article 
CAS 

Google Scholar 
Bierlich, K. C. et al. A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from drones. Mar. Ecol. Prog. Ser. 673, 193–210 (2021).Article 

Google Scholar 
Slater, G. J., Goldbogen, J. A. & Pyenson, N. D. Independent evolution of baleen whale gigantism linked to Plio-Pleistocene ocean dynamics. Proc. R. Soc. B 284, 20170546 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Lockyer, C. Growth and energy budgets of large baleen whales from the Southern Hemisphere. Food Agric. Organ. 3, 379–487 (1981).
Google Scholar 
Mackintosh, A. & Wheeler, J. Southern blue and fin whales. Discover. Rep. 1, 257–540 (1929).Smith, F. A. & Lyons, S. K. How big should a mammal be? A macroecological look at mammalian body size over space and time. Phil. Trans. R. Soc. B 366, 2364–2378 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Gearty, W., McClain, C. R. & Payne, J. L. Energetic tradeoffs control the size distribution of aquatic mammals. Proc. Natl Acad. Sci. USA 115, 4194–4199 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lockyer, C. Body weights of some species of large whales. ICES J. Mar. Sci. 36, 259–273 (1976).Article 

Google Scholar 
Goldbogen, J. A. Physiological constraints on marine mammal body size. Proc. Natl Acad. Sci. USA 115, 3995–3997 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Goldbogen, J. A. et al. Why whales are big but not bigger: physiological drivers and ecological limits in the age of ocean giants. Science 366, 1367–1372 (2019).Article 
CAS 
PubMed 

Google Scholar 
Cade, D. E. et al. Social exploitation of extensive, ephemeral, environmentally controlled prey patches by super-groups of rorqual whales. Anim. Behav. 182, 251–266 (2021).Article 

Google Scholar 
Goldbogen, J. A. et al. Scaling of lunge‐feeding performance in rorqual whales: mass‐specific energy expenditure increases with body size and progressively limits diving capacity. Funct. Ecol. 26, 216–226 (2012).Article 

Google Scholar 
Kahane-Rapport, S. R. & Goldbogen, J. A. Allometric scaling of morphology and engulfment capacity in rorqual whales. J. Morphol. 279, 1256–1268 (2018).Article 
PubMed 

Google Scholar 
Kahane-Rapport, S. R. et al. Lunge filter feeding biomechanics constrain rorqual foraging ecology across scale. J. Exp. Biol. https://doi.org/10.1242/jeb.224196 (2020).McNab, B. K. Complications inherent in scaling the basal rate of metabolism in mammals. Q. Rev. Biol. 63, 25–54 (1988).Article 
CAS 
PubMed 

Google Scholar 
Boyd, I. in Marine Mammal Biology: An Evolutionary Approach (ed. Hoelzel, A. R.) 247–277 (Blackwell Science Ltd, 2002).Kleiber, M. Body size and metabolism. Hilgardia 6, 315–353 (1932).Article 
CAS 

Google Scholar 
West, G. B., Brown, J. H. & Enquist, B. J. A general model for the origin of allometric scaling laws in biology. Science 276, 122–126 (1997).Article 
CAS 
PubMed 

Google Scholar 
Corkeron, P. J. & Connor, R. C. Why do baleen whales migrate? Mar. Mamm. Sci. 15, 1228–1245 (1999).Article 

Google Scholar 
Lockyer, C. Review of baleen whale (Mysticeti) reproduction and implications for management. Rep. Int. Whal. Commn 6, 27–50 (1984).
Google Scholar 
Lockyer, C. All creatures great and smaller: a study in cetacean life history energetics. J. Mar. Biol. Assoc. UK 87, 1035–1045 (2007).Article 

Google Scholar 
Frazer, J. & Huggett, A. S. G. Specific foetal growth rates of cetaceans. J. Zool. 169, 111–126 (1973).Article 

Google Scholar 
Zhou, M. & Dorland, R. D. Aggregation and vertical migration behavior of Euphausia superba. Deep Sea Res. II 51, 2119–2137 (2004).Article 

Google Scholar 
Gough, W. T. et al. Scaling of swimming performance in baleen whales. J. Exp. Biol. 222, jeb204172 (2019).Article 
PubMed 

Google Scholar 
Cade, D. E. et al. Predator-scale spatial analysis of intra-patch prey distribution reveals the energetic drivers of rorqual whale super group formation. Funct. Ecol. 35, 894–908 (2021).Article 
CAS 

Google Scholar 
Gough, W. T. et al. Scaling of oscillatory kinematics and Froude efficiency in baleen whales. J. Exp. Biol. 224, jeb237586 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Croll, D. A., Kudela, R. & Tershy, B. R. in Whales, Whaling, and Ocean Ecosystems (eds Estes, J. A. et al.) Ch. 16 (Univ. California Press, 2006).Woodward, B. L., Winn, J. P. & Fish, F. E. Morphological specializations of baleen whales associated with hydrodynamic performance and ecological niche. J. Morphol. 267, 1284–1294 (2006).Article 
PubMed 

Google Scholar 
Webb, P. W. & De Buffrénil, V. Locomotion in the biology of large aquatic vertebrates. Trans. Am. Fish. Soc. 119, 629–641 (1990).Article 

Google Scholar 
Acevedo-Gutiérrez, A., Croll, D. & Tershy, B. High feeding costs limit dive time in the largest whales. J. Exp. Biol. 205, 1747–1753 (2002).Article 
PubMed 

Google Scholar 
Goldbogen, J. A. et al. Mechanics, hydrodynamics and energetics of blue whale lunge feeding: efficiency dependence on krill density. J. Exp. Biol. 214, 131–146 (2011).Article 
CAS 
PubMed 

Google Scholar 
Potvin, J., Cade, D. E., Werth, A. J., Shadwick, R. E. & Goldbogen, J. A. Rorqual lunge-feeding energetics near and away from the kinematic threshold of optimal efficiency. Integr. Org. Biol. 3, obab005 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pyenson, N. D. The ecological rise of whales chronicled by the fossil record. Curr. Biol. 27, R558–R564 (2017).Article 
CAS 
PubMed 

Google Scholar 
Williams, T. M. in Whales, Whaling, and Ocean Ecosystems (eds Estes, J. A. et al.) Ch. 15 (Univ. California Press, 2006).Tackaberry, J. E. et al. From a calf’s perspective: humpback whale nursing behavior on two US feeding grounds. PeerJ 8, e8538 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Huang, S.-L., Chou, L.-S. & Ni, I.-H. Comparable length at weaning in cetaceans. Mar. Mamm. Sci. 25, 875–887 (2009).Article 

Google Scholar 
Rice, D. Marine Mammals of the World: Systematics and Distribution (Society for Marine Mammalogy Special Publication, 1998).McNamara, J. M. & Houston, A. I. The effect of a change in foraging options on intake rate and predation rate. Am. Nat. 144, 978–1000 (1994).Article 

Google Scholar 
Mittelbach, G. G. Foraging efficiency and body size: a study of optimal diet and habitat use by bluegills. Ecology 62, 1370–1386 (1981).Article 

Google Scholar 
Robbins, C. T. et al. Optimizing protein intake as a foraging strategy to maximize mass gain in an omnivore. Oikos 116, 1675–1682 (2007).Article 

Google Scholar 
Werth, A. J. et al. Filtration area scaling and evolution in mysticetes: trophic niche partitioning and the curious cases of sei and pygmy right whales. Biol. J. Linn. Soc. 125, 264–279 (2018).Article 

Google Scholar 
Leslie, M. S., Peredo, C. M. & Pyenson, N. D. Norrisanima miocaena, a new generic name and redescription of a stem balaenopteroid mysticete (Mammalia, Cetacea) from the Miocene of California. PeerJ 7, e7629 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Marx, F. G. & Uhen, M. D. Climate, critters, and cetaceans: Cenozoic drivers of the evolution of modern whales. Science 327, 993–996 (2010).Article 
CAS 
PubMed 

Google Scholar 
Perrin, W. F. Why are there so many kinds of whales and dolphins? Bioscience 41, 460–462 (1991).Article 

Google Scholar 
Kot, B. W., Sears, R., Zbinden, D., Borda, E. & Gordon, M. S. Rorqual whale (Balaenopteridae) surface lunge‐feeding behaviors: standardized classification, repertoire diversity, and evolutionary analyses. Mar. Mamm. Sci. 30, 1335–1357 (2014).Article 

Google Scholar 
Segre, P. S. et al. Scaling of maneuvering performance in baleen whales: larger whales outperform expectations. J. Exp. Biol. 225, jeb243224 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Kawamura, A. A review of food of balaenopterid whales. Sci. Rep. Whales Res. Inst. 32, 155–197 (1980).
Google Scholar 
Iwata, T. et al. Tread-water feeding of Bryde’s whales. Curr. Biol. 27, R1154–R1155 (2017).Article 
CAS 
PubMed 

Google Scholar 
McMillan, C. J., Towers, J. R. & Hildering, J. The innovation and diffusion of “trap‐feeding,” a novel humpback whale foraging strategy. Mar. Mamm. Sci. 35, 779–796 (2019).Article 

Google Scholar 
Robbins, J. & Mattila, D. Estimating Humpback Whale (Megaptera novaeangliae) Entanglement Rates on the Basis of Scar Evidence (Northeast Fisheries Science Center, 2004).Horwood, J. in Encyclopedia of Marine Mammals 2nd edn (eds Wursig, B et al.) 1001–1003 (Elsevier, 2009).Haug, T., Lindstrøm, U. & Nilssen, K. T. Variations in minke whale (Balaenoptera acutorostrata) diet and body condition in response to ecosystem changes in the Barents Sea. Sarsia 87, 409–422 (2002).Article 

Google Scholar 
García-Vernet, R., Borrell, A., Víkingsson, G., Halldórsson, S. D. & Aguilar, A. Ecological niche partitioning between baleen whales inhabiting Icelandic waters. Prog. Oceanogr. 199, 102690 (2021).Article 

Google Scholar 
Cade, D. E., Carey, N., Domenici, P., Potvin, J. & Goldbogen, J. A. Predator-informed looming stimulus experiments reveal how large filter feeding whales capture highly maneuverable forage fish. Proc. Natl Acad. Sci. USA 117, 472–478 (2020).Article 
CAS 
PubMed 

Google Scholar 
Deméré, T. A., McGowen, M. R., Berta, A. & Gatesy, J. Morphological and molecular evidence for a stepwise evolutionary transition from teeth to baleen in mysticete whales. Syst. Biol. 57, 15–37 (2008).Article 
PubMed 

Google Scholar 
Stafford, K. M., Fox, C. G. & Clark, D. S. Long-range acoustic detection and localization of blue whale calls in the northeast Pacific Ocean. J. Acoust. Soc. Am. 104, 3616–3625 (1998).Article 
CAS 
PubMed 

Google Scholar 
Totterdell, J. A. et al. The first three records of killer whales (Orcinus orca) killing and eating blue whales (Balaenoptera musculus). Mar. Mamm. Sci. 38, 1286–1301 (2022).Article 

Google Scholar 
Cade, D. E., Friedlaender, A. S., Calambokidis, J. & Goldbogen, J. A. Kinematic diversity in rorqual whale feeding mechanisms. Curr. Biol. 26, 2617–2624 (2016).Article 
CAS 
PubMed 

Google Scholar 
Goldbogen, J. A. et al. Using digital tags with integrated video and inertial sensors to study moving morphology and associated function in large aquatic vertebrates. Anat. Rec. 300, 1935–1941 (2017).Article 
CAS 

Google Scholar 
Bierlich, K. et al. Comparing uncertainty associated with 1-, 2-, and 3D aerial photogrammetry-based body condition measurements of baleen whales. Front. Mar. Sci. 8, 1729 (2021).Article 

Google Scholar 
Cade, D. E. et al. Tools for integrating inertial sensor data with video bio-loggers, including estimation of animal orientation, motion, and position. Anim. Biotelemetry https://doi.org/10.1186/s40317-021-00256-w (2021).Cade, D. E., Barr, K. R., Calambokidis, J., Friedlaender, A. S. & Goldbogen, J. A. Determining forward speed from accelerometer jiggle in aquatic environments. J. Exp. Biol. 221, jeb170449 (2018).PubMed 

Google Scholar 
Wilson, R. P. et al. All at sea with animal tracks; methodological and analytical solutions for the resolution of movement. Deep Sea Res. II 54, 193–210 (2007).Article 

Google Scholar 
Potvin, J., Cade, D. E., Werth, A. J., Shadwick, R. E. & Goldbogen, J. A. A perfectly inelastic collision: bulk prey engulfment by baleen whales and dynamical implications for the world’s largest cetaceans. Am. J. Phys. 88, 851–863 (2020).Article 

Google Scholar 
Torres, W. I. & Bierlich, K. MorphoMetriX: a photogrammetric measurement GUI for morphometric analysis of megafauna. J. Open Source Softw. 5, 1825 (2020).Article 

Google Scholar 
Suter, H. & Houston, A. I. How to model optimal group size in social carnivores. Am. Nat. 197, 473–485 (2021).Article 
PubMed 

Google Scholar 
Hazen, E. L., Friedlaender, A. S. & Goldbogen, J. A. Blue whale (Balaenoptera musculus) optimize foraging efficiency by balancing oxygen use and energy gain as a function of prey density. Sci. Adv. 1, e1500469 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Doniol-Valcroze, T., Lesage, V., Giard, J. & Michaud, R. Optimal foraging theory predicts diving and feeding strategies of the largest marine predator. Behav. Ecol. 22, 880–888 (2011).Article 

Google Scholar 
Gough, W. T. et al. Fast and furious: energetic tradeoffs and scaling of high-speed foraging in rorqual whales. Integr. Org. Biol. 4, obac038 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Laws, R. M. The ecology of the Southern Ocean. Am. Sci. 73, 26–40 (1985).
Google Scholar 
Brown, S. & Lockyer, C. in Antarctic Ecology Vol. 2 (ed. Laws, R. M.) (Academic Press, 1984).Peters, R. H. The Ecological Implications of Body Size Vol. 2 Ch. 7 (Cambridge Univ. Press, 1986).Rall, B. C. et al. Universal temperature and body-mass scaling of feeding rates. Phil. Trans. R. Soc. B 367, 2923–2934 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Evans, E. & Miller, D. Comparative nutrition, growth and longevity. Proc. Nutr. Soc. 27, 121–129 (1968).Article 
CAS 
PubMed 

Google Scholar 
Farlow, J. O. A consideration of the trophic dynamics of a Late Cretaceous large‐dinosaur community (Oldman Formation). Ecology 57, 841–857 (1976).Article 

Google Scholar 
Harestad, A. S. & Bunnel, F. Home range and body weight – a reevaluation. Ecology 60, 389–402 (1979).Article 

Google Scholar 
Schoener, T. W. Sizes of feeding territories among birds. Ecology 49, 123–141 (1968).Article 

Google Scholar 
Calder, W. A. in Avian Energetics (ed. Paynter, R. A.) 86–151 (Nuttall Ornithological Club, 1974).Savage, V. M., Deeds, E. J. & Fontana, W. Sizing up allometric scaling theory. PLoS Comp. Biol. 4, e1000171 (2008).Article 

Google Scholar 
Kolokotrones, T., Savage, V., Deeds, E. J. & Fontana, W. Curvature in metabolic scaling. Nature 464, 753–756 (2010).Article 
CAS 
PubMed 

Google Scholar 
Hudson, L. N., Isaac, N. J. & Reuman, D. C. The relationship between body mass and field metabolic rate among individual birds and mammals. J. Anim. Ecol. 82, 1009–1020 (2013).Article 
PubMed 
PubMed Central 

Google Scholar  More

Donia, M. S. & Fischbach, M. A. Small molecules from the human microbiota. Science 349, 1254766 (2015).Koh, A., De Vadder, F., Kovatcheva-Datchary, P. & Bäckhed, F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 165, 1332–1345 (2016).Article 

Google Scholar 
Koppel, N., Rekdal, V. M. & Balskus, E. P. Chemical transformation of xenobiotics by the human gut microbiota. Science 356, eaag2770 (2017).Myhrstad, M. C., Tunsjø, H., Charnock, C. & Telle-Hansen, V. H. Dietary fiber, gut microbiota, and metabolic regulation—current status in human randomized trials. Nutrients 12, 859 (2020).Article 

Google Scholar 
Lin, R., Liu, W., Piao, M. & Zhu, H. A review of the relationship between the gut microbiota and amino acid metabolism. Amino Acids 49, 2083–2090 (2017).Article 

Google Scholar 
Tyson, G. W. et al. Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428, 37–43 (2004).Article 

Google Scholar 
Flint, H. J., Scott, K. P., Louis, P. & Duncan, S. H. The role of the gut microbiota in nutrition and health. Nat. Rev. Gastroenterol. Hepatol. 9, 577–589 (2012).Article 

Google Scholar 
Lloyd-Price, J. et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 569, 655–662 (2019).Article 

Google Scholar 
Yang, Q. et al. Metabolomics biotechnology, applications, and future trends: a systematic review. RSC Adv. 9, 37245–37257 (2019).Article 

Google Scholar 
Castelli, F. A. et al. Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests. Anal. Bioanal. Chem. 414, 759–789 (2022).Article 

Google Scholar 
Dias-Audibert, F. L. et al. Combining machine learning and metabolomics to identify weight gain biomarkers. Front. Bioeng. Biotechnol. 8, 6 (2020).Article 

Google Scholar 
Zheng, C., Zhang, S., Ragg, S., Raftery, D. & Vitek, O. Identification and quantification of metabolites in 1H NMR spectra by Bayesian model selection. Bioinformatics 27, 1637–1644 (2011).Article 

Google Scholar 
Information Resources Management Association. Bioinformatics: Concepts, Methodologies, Tools, and Applications (IGI Global, 2013).Johnson, C. H. & Gonzalez, F. J. Challenges and opportunities of metabolomics. J. Cell. Physiol. 227, 2975–2981 (2012).Article 

Google Scholar 
Ayling, M., Clark, M. D. & Leggett, R. M. New approaches for metagenome assembly with short reads. Brief. Bioinform. 21, 584–594 (2020).Article 

Google Scholar 
Brumfield, K. D., Huq, A., Colwell, R. R., Olds, J. L. & Leddy, M. B. Microbial resolution of whole genome shotgun and 16S amplicon metagenomic sequencing using publicly available neon data. PLoS ONE 15, e0228899 (2020).Article 

Google Scholar 
Garza, D. R., van Verk, M. C., Huynen, M. A. & Dutilh, B. E. Towards predicting the environmental metabolome from metagenomics with a mechanistic model. Nat. Microbiol. 3, 456–460 (2018).Article 

Google Scholar 
Noecker, C. et al. Metabolic model-based integration of microbiome taxonomic and metabolomic profiles elucidates mechanistic links between ecological and metabolic variation. MSystems 1, e00013–15 (2016).Article 

Google Scholar 
Yin, X. et al. A comparative evaluation of tools to predict metabolite profiles from microbiome sequencing data. Front. Microbiol. 11, 3132 (2020).Article 

Google Scholar 
Kettle, H., Louis, P., Holtrop, G., Duncan, S. H. & Flint, H. J. Modelling the emergent dynamics and major metabolites of the human colonic microbiota. Environ. Microbiol. 17, 1615–1630 (2015).Article 

Google Scholar 
Quinn, R. A. et al. Niche partitioning of a pathogenic microbiome driven by chemical gradients. Sci. Adv. 4, eaau1908 (2018).Article 

Google Scholar 
Wang, T., Goyal, A., Dubinkina, V. & Maslov, S. Evidence for a multi-level trophic organization of the human gut microbiome. PLoS Comput. Biol. 15, e1007524 (2019).Article 

Google Scholar 
Goyal, A., Wang, T., Dubinkina, V. & Maslov, S. Ecology-guided prediction of cross-feeding interactions in the human gut microbiome. Nat. Commun. 12, 1335 (2021).Mallick, H. et al. Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences. Nat. Commun. 10, 3136 (2019).Article 

Google Scholar 
Le, V., Quinn, T. P., Tran, T. & Venkatesh, S. Deep in the bowel: highly interpretable neural encoder–decoder networks predict gut metabolites from gut microbiome. BMC Genom. 21, 256 (2020).Reiman, D., Layden, B. T. & Dai, Y. MiMeNet: exploring microbiome–metabolome relationships using neural networks. PLoS Comput. Biol. 17, e1009021 (2021).Article 

Google Scholar 
Morton, J. T. et al. Learning representations of microbe–metabolite interactions. Nat. Methods 16, 1306–1314 (2019).Article 

Google Scholar 
Chen, R. T., Rubanova, Y., Bettencourt, J. & Duvenaud, D. Neural ordinary differential equations. In Advances in Neural Information Processing Systems 31, 6572–6583 (NeurIPS, 2018).Lu, Y., Zhong, A., Li, Q. & Dong, B. Beyond finite layer neural networks: bridging deep architectures and numerical differential equations. In International Conference on Machine Learning 3276–3285 (PMLR, 2018).Qiu, C., Bendickson, A., Kalyanapu, J. & Yan, J. Accuracy and architecture studies of residual neural network solving ordinary differential equations. Preprint at arXiv https://doi.org/10.48550/arXiv.2101.03583 (2021).Dutta, S., Rivera-Casillas, P. & Farthing, M. W. Neural ordinary differential equations for data-driven reduced order modeling of environmental hydrodynamics. Preprint at https://doi.org/10.48550/arXiv.2104.13962 (2021).Marsland III, R. et al. Available energy fluxes drive a transition in the diversity, stability, and functional structure of microbial communities. PLoS Comput. Biol. 15, e1006793 (2019).Article 

Google Scholar 
Franzosa, E. A. et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat. Microbiol. 4, 293–305 (2019).Article 

Google Scholar 
Swenson, T. L., Karaoz, U., Swenson, J. M., Bowen, B. P. & Northen, T. R. Linking soil biology and chemistry in biological soil crust using isolate exometabolomics. Nat. Commun. 9, 19 (2018).Article 

Google Scholar 
Litonjua, A. A. et al. Effect of prenatal supplementation with vitamin D on asthma or recurrent wheezing in offspring by age 3 years: the VDAART randomized clinical trial. JAMA 315, 362–370 (2016).Article 

Google Scholar 
Litonjua, A. A. et al. Six-year follow-up of a trial of antenatal vitamin D for asthma reduction. N. Engl. J. Med. 382, 525–533 (2020).Article 

Google Scholar 
Lee-Sarwar, K. A. et al. Integrative analysis of the intestinal metabolome of childhood asthma. J. Allergy Clin. Immunol. 144, 442–454 (2019).Article 

Google Scholar 
Lee-Sarwar, K. et al. Association of the gut microbiome and metabolome with wheeze frequency in childhood asthma. J. Allergy Clin. Immunol. 147, AB53 (2021).Article 

Google Scholar 
Harvard Willett Food Frequency Questionnaire (T.H. Chan School of Public Health, Department of Nutrition, Harvard Univ., 2015).Plan and Operation of the Third National Health and Nutrition Examination Survey, 1988–94 (National Centre for Health Statistics, 1994).Nelson, K. M., Reiber, G. & Boyko, E. J. Diet and exercise among adults with type 2 diabetes: findings from the third National Health and Nutrition Examination Survey (NHANES III). Diabetes Care 25, 1722–1728 (2002).Article 

Google Scholar 
Marriott, B. P., Olsho, L., Hadden, L. & Connor, P. Intake of added sugars and selected nutrients in the United States, National Health and Nutrition Examination Survey (NHANES) 2003-2006. Crit. Rev. Food Sci. Nutr. 50, 228–258 (2010).Article 

Google Scholar 
Moshfegh, A. Food and Nutrient Database for Dietary Studies (US Department of Agriculture, Agricultural Research Service, Food Surveys Research Group, 2022); http://www.ars.usda.gov/nea/bhnrc/fsrgRidlon, J. M., Kang, D.-J. & Hylemon, P. B. Bile salt biotransformations by human intestinal bacteria. J. Lipid Res. 47, 241–259 (2006).Article 

Google Scholar 
Bachmann, V. et al. Bile salts modulate the mucin-activated type VI secretion system of pandemic Vibrio cholerae. PLoS Negl. Trop. Dis. 9, e0004031 (2015).Article 

Google Scholar 
Ramírez-Pérez, O., Cruz-Ramón, V., Chinchilla-López, P. & Méndez-Sánchez, N. The role of the gut microbiota in bile acid metabolism. Ann. Hepatol. 16, 21–26 (2018).Article 

Google Scholar 
Jia, W., Xie, G. & Jia, W. Bile acid-microbiota crosstalk in gastrointestinal inflammation and carcinogenesis. Nat. Rev. Gastroenterol. Hepatol. 15, 111–128 (2018).Article 

Google Scholar 
Heinken, A. et al. Systematic assessment of secondary bile acid metabolism in gut microbes reveals distinct metabolic capabilities in inflammatory bowel disease. Microbiome 7, 75 (2019).Duboc, H. et al. Connecting dysbiosis, bile-acid dysmetabolism and gut inflammation in inflammatory bowel diseases. Gut 62, 531–539 (2013).Article 

Google Scholar 
Thomas, J. P., Modos, D., Rushbrook, S. M., Powell, N. & Korcsmaros, T. The emerging role of bile acids in the pathogenesis of inflammatory bowel disease. Front. Immunol. 13, 246 (2022).Kristal, A. R., Peters, U. & Potter, J. D. Is it time to abandon the food frequency questionnaire? Cancer Epidemiol. Biomarkers Prev. 14, 2826–2828 (2005).Article 

Google Scholar 
Scalbert, A. et al. The food metabolome: a window over dietary exposure. Am. J. Clin. Nutr. 99, 1286–1308 (2014).Article 

Google Scholar 
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).Article 

Google Scholar 
Callahan, B. J. et al. DADA: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).Article 

Google Scholar 
Evans, A. M. et al. High resolution mass spectrometry improves data quantity and quality as compared to unit mass resolution mass spectrometry in high-throughput profiling metabolomics. Metabolomics 4, 1 (2014).
Google Scholar 
Blum, R. E. et al. Validation of a food frequency questionnaire in Native American and Caucasian children 1 to 5 years of age. Matern. Child Health J. 3, 167–172 (1999).Article 

Google Scholar 
Kingma, D. P. & Ba, J. Adam: a method for stochastic optimization. Preprint at https://doi.org/10.48550/arXiv.1412.6980 (2014).Wang, T. wt1005203/mnode: initial release. Zenodo https://doi.org/10.5281/zenodo.7602940 (2023). More

Barnosky, A. D. et al. Has the Earth’s sixth mass extinction already arrived? Nature 471, 51–57 (2011).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Ceballos, G., Ehrlich, P. R. & Dirzo, R. Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proc. Natl Acad. Sci. USA 114, E6089–E6096 (2017).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Cowie, R. H., Bouchet, P. & Fontaine, B. The Sixth Mass Extinction: fact, fiction or speculation? Biol. Rev. 97, 640–663 (2022).Article 
PubMed 

Google Scholar 
Dirzo, R. et al. Defaunation in the anthropocene. Science 345, 401–406 (2014).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Ceballos, G. et al. Accelerated modern human–induced species losses: entering the sixth mass extinction. Sci. Adv. 1, e1400253 (2015).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Pimm, S. L. et al. The biodiversity of species and their rates of extinction, distribution, and protection. Science 344, 1246752 (2014).Article 
CAS 
PubMed 

Google Scholar 
Urban, M. et al. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Pincheira-Donoso, D. et al. Temporal and spatial patterns of vertebrate extinctions during the Anthropocene. Preprint at bioRxiv https://doi.org/10.1101/2022.05.05.490605 (2022).Brook, B. W., Sodhi, N. S. & Bradshaw, C. J. A. Synergies among extinction drivers under global change. Trends Ecol. Evol. 23, 453–460 (2008).Article 
PubMed 

Google Scholar 
Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Change 5, 215–224 (2015).Article 
ADS 

Google Scholar 
Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Warren, R. et al. Quantifying the benefit of early climate change mitigation in avoiding biodiversity loss. Nat. Clim. Change 3, 678–682 (2013).Article 
ADS 

Google Scholar 
Román-Palacios, C. & Wiens, J. J. Recent responses to climate change reveal the drivers of species extinction and survival. Proc. Natl Acad. Sci. USA 117, 4211–4217 (2020).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Gaston, K. J., Jackson, S. F., Cantú-Salazar, L. & Cruz-Piñón, G. The ecological performance of protected areas. Annu. Rev. Ecol. Evol. Syst. 39, 93–113 (2008).Article 

Google Scholar 
Saout, S. L. et al. Protected areas and effective biodiversity conservation. Science 342, 803–805 (2013).Article 
ADS 
PubMed 

Google Scholar 
Watson, J. E. M., Dudley, N., Segan, D. B. & Hockings, M. The performance and potential of protected areas. Nature 515, 67–73 (2014).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Araújo, M. B., Alagador, D., Cabeza, M., Noguésbravo, D. & Thuiller, W. Climate change threatens European conservation areas. Ecol. Lett. 14, 484–492 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Chen, Y., Zhang, J., Jiang, J., Nielsen, S. & He, F. Assessing the effectiveness of China’s protected areas to conserve current and future amphibian diversity. Divers. Distrib. 23, 146–157 (2017).Article 

Google Scholar 
Jenkins, C. N. & Joppa, L. Expansion of the global terrestrial protected area system. Biol. Conserv. 142, 2166–2174 (2009).Article 

Google Scholar 
Johnston, A. et al. Observed and predicted effects of climate change on species abundance in protected areas. Nat. Clim. Change 3, 1055–1061 (2013).Article 
ADS 

Google Scholar 
Lehikoinen, P., Santangeli, A., Jaatinen, K., Rajasärkkä, A. & Lehikoinen, A. Protected areas act as a buffer against detrimental effects of climate change-evidence from large-scale, long-term abundance data. Glob. Change Biol. 25, 304–313 (2018).Article 
ADS 

Google Scholar 
Coetzee, B. W. T., Robertson, M. P., Erasmus, B. F. N., Rensburg, B. J. V. & Thuiller, W. Ensemble models predict Important Bird Areas in southern Africa will become less effective for conserving endemic birds under climate change. Glob. Ecol. Biogeogr. 18, 701–710 (2009).Article 

Google Scholar 
Araújo, M. B., Cabeza, M., Thuiller, W., Hannah, L. & Williams, P. H. Would climate change drive species out of reserves? An assessment of existing reserve‐selection methods. Glob. Change Biol. 10, 1618–1626 (2004).Article 
ADS 

Google Scholar 
Pouzols, F. M. et al. Global protected area expansion is compromised by projected land-use and parochialism. Nature 516, 383–386 (2014).Article 
ADS 

Google Scholar 
Monzn, J., Moyer-Horner, L. & Palamar, M. B. Climate change and species range dynamics in protected areas. Bioscience 61, 752–761 (2011).Article 

Google Scholar 
Newbold, T., Oppenheimer, P., Etard, A. & Williams, J. J. Tropical and Mediterranean biodiversity is disproportionately sensitive to land-use and climate change. Nat. Ecol. Evol. 4, 1630–1638 (2020).Article 
PubMed 

Google Scholar 
Liu, X. et al. Animal invaders threaten protected areas worldwide. Nat. Commun. 11, 2892 (2020).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Carlson, C. J. et al. Climate change increases cross-species viral transmission risk. Nature 607, 555–562 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Mi, C., Huettmann, F. & Guo, Y. Climate envelope predictions indicate an enlarged suitable wintering distribution for Great Bustards (Otis tarda dybowskii) in China for the 21st century. Peerj 4, e1630–e1630 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Guisan, A. et al. Predicting species distributions for conservation decisions. Ecol. Lett. 16, 1424–1435 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Zhu, G., Papeş, M., Giam, X., Cho, S.-H. & Armsworth, P. R. Are protected areas well-sited to support species in the future in a major climate refuge and corridor in the United States? Biol. Conserv. 255, 108982 (2021).Article 

Google Scholar 
Gutiérrez, J. A. & Duivenvoorden, J. F. Can we expect to protect threatened species in protected areas? A case study of the genus Pinus in Mexico. Rev. Mexicana Biodivers. 81, 875–882 (2010).
Google Scholar 
Velásquez-Tibatá, J., Salaman, P. & Graham, C. H. Effects of climate change on species distribution, community structure, and conservation of birds in protected areas in Colombia. Reg. Environ. Change 13, 235–248 (2013).Article 

Google Scholar 
Riquelme, C. et al. Protected areas’ effectiveness under climate change: a latitudinal distribution projection of an endangered mountain ungulate along the Andes Range. Peerj 6, e5222 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Bazzichetto, M. et al. Plant invasion risk: a quest for invasive species distribution modelling in managing protected areas. Ecol. Indic. 95, 311–319 (2018).Article 

Google Scholar 
Hannah, L. et al. Protected area needs in a changing climate. Front. Ecol. Environ. 5, 131–138 (2007).Article 

Google Scholar 
Cox, N. et al. A global reptile assessment highlights shared conservation needs of tetrapods. Nature 695, 285–290 (2022).Article 
ADS 

Google Scholar 
IUCN. The IUCN red list of threatened species. http://www.iucnredlist.org/ (2021).Wake, D. B. & Vredenburg, V. T. Are we in the midst of the sixth mass extinction? A view from the world of amphibians. Proc. Natl Acad. Sci. USA 105, 11466–11473 (2008).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Cordier, J. M. et al. A global assessment of amphibian and reptile responses to land-use changes. Biol. Conserv. 253, 108863 (2021).Article 

Google Scholar 
Powers, R. P. & Jetz, W. Global habitat loss and extinction risk of terrestrial vertebrates under future land-use-change scenarios. Nat. Clim. Change 9, 323–329 (2019).Article 
ADS 

Google Scholar 
Pounds, J. A. et al. Widespread amphibian extinctions from epidemic disease driven by global warming. Nature 439, 161–167 (2006).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Scheele, B. C. et al. Amphibian fungal panzootic causes catastrophic and ongoing loss of biodiversity. Science 363, 1459–1463 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Blaustein, A. R. & Kiesecker, J. M. Complexity in conservation: lessons from the global decline of amphibian populations. Ecol. Lett. 5, 597–608 (2002).Article 

Google Scholar 
Kraus, F. Impacts from invasive reptiles and amphibians. Annu. Rev. Ecol. Evol. Syst. 46, 75–97 (2015).Article 

Google Scholar 
Alford, R. A., Bradfield, K. S. & Richards, S. J. Global warming and amphibian losses. Nature 447, E3–E4 (2007).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Hof, C., Araújo, M. B., Jetz, W. & Rahbek, C. Additive threats from pathogens, climate and land-use change for global amphibian diversity. Nature 480, 516–519 (2011).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Rohr, J. R. & Raffel, T. R. Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease. Proc. Natl Acad. Sci. USA 107, 8269–8274 (2008).Article 
ADS 

Google Scholar 
Pincheira‐Donoso, D. et al. The global macroecology of brood size in amphibians reveals a predisposition of low‐fecundity species to extinction. Glob. Ecol. Biogeogr. 30, 1299–1310 (2021).Article 

Google Scholar 
Smith, M. A. & Green, D. M. Dispersal and the metapopulation paradigm in amphibian ecology and conservation: are all amphibian populations metapopulations? Ecography 28, 110–128 (2005).Article 

Google Scholar 
Borzée, A. et al. Climate change-based models predict range shifts in the distribution of the only Asian plethodontid salamander: Karsenia koreana. Sci. Rep. 9, 11838 (2019).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Heller, N. E. & Zavaleta, E. S. Biodiversity management in the face of climate change: a review of 22 years of recommendations. Biol. Conserv. 142, 14–32 (2009).Article 

Google Scholar 
Haight, J. & Hammill, E. Protected areas as potential refugia for biodiversity under climatic change. Biol. Conserv. 241, 108258 (2020).Article 

Google Scholar 
Thomas, C. D. et al. Protected areas facilitate species’ range expansions. Proc. Natl Acad. Sci. USA 109, 14063–14068 (2012).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lawson, C. R., Bennie, J. J., Thomas, C. D., Hodgson, J. A. & Wilson, R. J. Active management of protected areas enhances metapopulation expansion under climate change. Conserv. Lett. 7, 111–118 (2014).Article 

Google Scholar 
Beale, C. M., Baker, N. E., Brewer, M. J. & Lennon, J. J. Protected area networks and savannah bird biodiversity in the face of climate change and land degradation. Ecol. Lett. 16, 1061–1068 (2013).Article 
PubMed 

Google Scholar 
D’Amen, M. et al. Will climate change reduce the efficacy of protected areas for amphibian conservation in Italy? Biol. Conserv. 144, 989–997 (2011).Article 

Google Scholar 
Singh, M. Evaluating the impact of future climate and forest cover change on the ability of Southeast (SE) Asia’s protected areas to provide coverage to the habitats of threatened avian species. Ecol. Indic. 114, 106307 (2020).Article 

Google Scholar 
Hole, D. G. et al. Projected impacts of climate change on a continent‐wide protected area network. Ecol. Lett. 12, 420–431 (2009).Article 
PubMed 

Google Scholar 
Lehikoinen, P. et al. Increasing protected area coverage mitigates climate-driven community changes. Biol. Conserv. 253, 108892 (2021).Article 

Google Scholar 
Araújo, M. B., Thuiller, W. & Pearson, R. G. Climate warming and the decline of amphibians and reptiles in Europe. J. Biogeogr. 33, 1712–1728 (2006).Article 

Google Scholar 
Girardello, M., Griggio, M., Whittingham, M. J. & Rushton, S. P. Models of climate associations and distributions of amphibians in Italy. Ecol. Res. 25, 103–111 (2010).Article 

Google Scholar 
McMenamin, S. K., Hadly, E. A. & Wright, C. K. Climatic change and wetland desiccation cause amphibian decline in Yellowstone National Park. Proc. Natl Acad. Sci. USA 105, 16988–16993 (2008).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ficetola, G. F. & Maiorano, L. Contrasting effects of temperature and precipitation change on amphibian phenology, abundance and performance. Oecologia 181, 683–693 (2016).Article 
ADS 
PubMed 

Google Scholar 
Bickford, D., Howard, S. D., Ng, D. J. J. & Sheridan, J. A. Impacts of climate change on the amphibians and reptiles of Southeast Asia. Biodivers. Conserv. 19, 1043–1062 (2010).Article 

Google Scholar 
Manne, L. L., Brooks, T. M. & Pimm, S. L. Relative risk of extinction of passerine birds on continents and islands. Nature 399, 258–261 (1999).Article 
ADS 
CAS 

Google Scholar 
Jenkins, C. N., Pimm, S. L. & Joppa, L. N. Global patterns of terrestrial vertebrate diversity and conservation. Proc. Natl Acad. Sci. USA 110, E2602–E2610 (2013).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pearson, R. G. et al. Life history and spatial traits predict extinction risk due to climate change. Nat. Clim. Change 4, 217–221 (2014).Article 
ADS 

Google Scholar 
Wauchope, H. S. et al. Protected areas have a mixed impact on waterbirds, but management helps. Nature 605, 103–107 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
WWF. Tropical and Subtropical Moist Broadleaf Forest Ecoregions (World Wide Fund for Nature, 2019).Rodrigues, A. S. L. et al. Global gap analysis: priority regions for expanding the global protected-area network. Bioscience 54, 1092–1100 (2004).Article 

Google Scholar 
Hidasi‐Neto, J., Loyola, R. & Cianciaruso, M. V. Global and local evolutionary and ecological distinctiveness of terrestrial mammals: identifying priorities across scales. Divers. Distrib. 21, 548–559 (2015).Article 

Google Scholar 
Martin, J.-L., Maris, V. & Simberloff, D. S. The need to respect nature and its limits challenges society and conservation science. Proc. Natl Acad. Sci. USA 113, 6105–6112 (2016).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Czech, B., Krausman, P. & Devers, P. Economic associations among causes of species endangerment in the United States. Bioscience 50, 593–601 (2000).Article 

Google Scholar 
CBD. First draft of the post-2020 global biodiversity framework. https://www.cbd.int/doc/c/abb5/591f/2e46096d3f0330b08ce87a45/wg2020-03-03-en.pdf (2021).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 
Ficetola, G. F. et al. An evaluation of the robustness of global amphibian range maps. J. Biogeogr. 41, 211–221 (2014).Article 

Google Scholar 
Aiello‐Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38, 541–545 (2015).Article 

Google Scholar 
Erfanian, M. B., Sagharyan, M., Memariani, F. & Ejtehadi, H. Predicting range shifts of three endangered endemic plants of the Khorassan-Kopet Dagh floristic province under global change. Sci. Rep. 11, 9159 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Brown, J. L., Cameron, A., Yoder, A. D. & Vences, M. A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar. Nat. Commun. 5, 5046 (2014).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Gaston, K. J. Rarity as double jeopardy. Nature 394, 229–230 (1998).Article 
ADS 
CAS 

Google Scholar 
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

Google Scholar 
Li, X., Liu, X., Kraus, F., Tingley, R. & Li, Y. Risk of biological invasions is concentrated in biodiversity hotspots. Front. Ecol. Environ. 14, 411–417 (2016).Article 

Google Scholar 
Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K. & Toxopeus, A. G. Where is positional uncertainty a problem for species distribution modelling? Ecography 37, 191–203 (2014).Article 

Google Scholar 
Xin, X., Wu, T. & Zhang, J. Introduction of CMIP5 experiments carried out with the climate system models of beijing climate center. Adv. Clim. Change Res. 4, 41–49 (2013).Article 

Google Scholar 
Voldoire, A. et al. The CNRM-CM5.1 global climate model: description and basic evaluation. Clim. Dyn. 40, 2091–2121 (2013).Article 

Google Scholar 
Watanabe, S. et al. MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev. 4, 845–872 (2011).Article 
ADS 

Google Scholar 
Mi, C. et al. Temperate and tropical lizards are vulnerable to climate warming due to increased water loss and heat stress. Proc. R. Soc. Lond. B. Biol. Sci. 289, 20221074 (2022).
Google Scholar 
Naimi, B. & Araújo, M. B. sdm: a reproducible and extensible R platform for species distribution modelling. Ecography 39, 368–375 (2016).Article 

Google Scholar 
Holt, B. G. et al. An update of Wallace’s zoogeographic regions of the world. Science 339, 74–78 (2013).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many?: How to use pseudo-absences in niche modelling? Methods Ecol. Evol. 3, 327–338 (2012).Article 

Google Scholar 
Andrade, A. F. A., de, Velazco, S. J. E. & Júnior, P. D. M. ENMTML: an R package for a straightforward construction of complex ecological niche models. Environ. Modell. Softw. 125, 104615 (2020).Article 

Google Scholar 
Senay, S. D., Worner, S. P. & Ikeda, T. Novel three-step pseudo-absence selection technique for improved species distribution modelling. PLos ONE 8, e71218 (2013).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Thuiller, W. BIOMOD–optimizing predictions of species distributions and projecting potential future shifts under global change. Glob. Change Biol. 9, 1353–1362 (2003).Article 
ADS 

Google Scholar 
Williams, J. N. et al. Using species distribution models to predict new occurrences for rare plants. Divers. Distrib. 15, 565–576 (2009).Article 

Google Scholar 
Graham, C. H. et al. The influence of spatial errors in species occurrence data used in distribution models. J. Appl. Ecol. 45, 239–247 (2008).Article 

Google Scholar 
Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151 (2006).Article 

Google Scholar 
Mi, C., Huettmann, F., Guo, Y., Han, X. & Wen, L. Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence. Peerj 5, e2849 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Drake, J. M., Randin, C. & Guisan, A. Modelling ecological niches with support vector machines. J. Appl. Ecol. 43, 424–432 (2006).Article 

Google Scholar 
Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).Article 

Google Scholar 
McPherson, J., Jetz, W. & Rogers, D. J. The effects of species’ range sizes on the accuracy of distribution models: ecological phenomenon or statistical artefact? J. Appl. Ecol. 41, 811–823 (2004).Article 

Google Scholar 
Wang, B. et al. Australian wheat production expected to decrease by the late 21st century. Glob. Change Biol. 24, 2403–2415 (2017).Article 
ADS 

Google Scholar 
Gallardo, B. et al. Protected areas offer refuge from invasive species spreading under climate change. Glob. Change Biol. 23, 5331–5343 (2017).Article 
ADS 

Google Scholar 
Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD – a platform for ensemble forecasting of species distributions. Ecography 32, 369–373 (2009).Article 

Google Scholar 
UNEP-WCMC, I. and. The world database on protected areas (WDPA). https://www.protectedplanet.net/en#4_43.25_111_0 (2014).Asamoah, E. F., Beaumont, L. J. & Maina, J. M. Climate and land-use changes reduce the benefits of terrestrial protected areas. Nat. Clim. Change 11, 1105–1110 (2021).Article 
ADS 

Google Scholar 
Brennan, A. et al. Functional connectivity of the world’s protected areas. Science 376, 1101–1104 (2022).You, Z. et al. Pitfall of big databases. Proc. Natl Acad. Sci. USA 115, 201813323 (2018).Article 

Google Scholar 
Nelson, A. & Chomitz, K. M. Effectiveness of strict vs. multiple use protected areas in reducing tropical forest fires: a global analysis using matching methods. PLoS ONE 6, e22722 (2011).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Albuquerque, F. & Beier, P. Rarity-weighted richness: a simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning. PLoS ONE 10, e0119905 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Tang, C. Q. et al. Identifying long-term stable refugia for relict plant species in East Asia. Nat. Commun. 9, 4488 (2018).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Kier, G. & Barthlott, W. Measuring and mapping endemism and species richness: a new methodological approach and its application on the flora of Africa. Biodivers. Conserv 10, 1513–1529 (2001).Article 

Google Scholar 
Albuquerque, F. & Gregory, A. The geography of hotspots of rarity-weighted richness of birds and their coverage by Natura 2000. PLoS ONE 12, e0174179 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Jennings, M. D. Gap analysis: concepts, methods, and recent results. Landsc. Ecol. 15, 5–20 (2000).Article 

Google Scholar 
Romero‐Muñoz, A. et al. Increasing synergistic effects of habitat destruction and hunting on mammals over three decades in the Gran Chaco. Ecography 43, 954–966 (2020).Article 

Google Scholar 
Brooks, T. M. et al. Global biodiversity conservation priorities. Science 313, 58–61 (2006).Article 
ADS 
CAS 
PubMed 

Google Scholar  More

Ellis, E. C. et al. People have shaped most of terrestrial nature for at least 12,000 years. Proc. Natl. Acad. Sci. USA 118, e2023483118 (2021).Article 
CAS 

Google Scholar 
Williams, B. A. et al. Change in terrestrial human footprint drives continued loss of intact ecosystems. One Earth 3, 371–382 (2020).Article 

Google Scholar 
Kuipers, K. J. J. et al. Habitat fragmentation amplifies threats from habitat loss to mammal diversity across the world’s terrestrial ecoregions. One Earth 4, 1505–1513 (2021).Article 

Google Scholar 
Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 7, 12558 (2016).Article 
CAS 

Google Scholar 
Watson, J. E. M. & Venter, O. Mapping the continuum of humanity’s footprint on land. One Earth 1, 175–180 (2019).Article 

Google Scholar 
Foley, J. A. et al. Global consequences of land use. Science 309, 570–574 (2005).Article 
CAS 

Google Scholar 
Glidden, C. K. et al. Human-mediated impacts on biodiversity and the consequences for zoonotic disease spillover. Curr. Biol. 31, R1342–R1361 (2021).Article 
CAS 

Google Scholar 
Grobbelaar, A. A. et al. Resurgence of yellow fever in Angola, 2015-2016. Emerg. Infect. Dis. 22, 1854–1855 (2016).Article 

Google Scholar 
Gubler, D. J. Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem in the 21st century. Trends Microbiol. 10, 100–103 (2002).Article 
CAS 

Google Scholar 
Hotez, P. J. Neglected tropical diseases in the Anthropocene: the cases of Zika, Ebola, and other infections. PLoS Negl. Trop. Dis. 10, e0004648 (2016).Article 

Google Scholar 
Paixão, E. S., Teixeira, M. G. & Rodrigues, L. C. Zika, chikungunya and dengue: the causes and threats of new and re-emerging arboviral diseases. BMJ Glob. Health 3, e000530 (2018).Article 

Google Scholar 
Rosenberg, R. et al. Vital signs: trends in reported vectorborne disease cases – United States and territories, 2004-2016. Morb. Mortal. Wk. Rep. 67, 496–501 (2018).Article 

Google Scholar 
World Malaria Report 2020: 20 Years of Global Progress and Challenges (WHO, 2020); https://apps.who.int/iris/handle/10665/337660Lambin, E. F., Tran, A., Vanwambeke, S. O., Linard, C. & Soti, V. Pathogenic landscapes: interactions between land, people, disease vectors, and their animal hosts. Int. J. Health Geogr. 9, 54 (2010).Article 

Google Scholar 
Shocket, M. S. et al. Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23 °C and 26 °C. eLife 9, e58511 (2020).Article 
CAS 

Google Scholar 
Kilpatrick, A. M. & Randolph, S. E. Drivers, dynamics, and control of emerging vector-borne zoonotic diseases. Lancet 380, 1946–1955 (2012).Article 

Google Scholar 
Franklinos, L. H. V., Jones, K. E., Redding, D. W. & Abubakar, I. The effect of global change on mosquito-borne disease. Lancet Infect. Dis. 19, e302–e312 (2019).Article 

Google Scholar 
Keys, P. W., Barnes, E. A. & Carter, N. H. A machine-learning approach to human footprint index estimation with applications to sustainable development. Environ. Res. Lett. 16, 044061 (2021).Article 

Google Scholar 
Venter, O. et al. Global terrestrial human footprint maps for 1993 and 2009. Sci. Data 3, 160067 (2016).Article 

Google Scholar 
Di Marco, M., Ferrier, S., Harwood, T. D., Hoskins, A. J. & Watson, J. E. M. Wilderness areas halve the extinction risk of terrestrial biodiversity. Nature 573, 582–585 (2019).Article 

Google Scholar 
Hill, J. E., DeVault, T. L., Wang, G. & Belant, J. L. Anthropogenic mortality in mammals increases with the human footprint. Front. Ecol. Environ. 18, 13–18 (2020).Article 

Google Scholar 
Elsen, P. R., Monahan, W. B. & Merenlender, A. M. Topography and human pressure in mountain ranges alter expected species responses to climate change. Nat. Commun. 11, 1974 (2020).Article 
CAS 

Google Scholar 
Su, J., Yin, H. & Kong, F. Ecological networks in response to climate change and the human footprint in the Yangtze River Delta urban agglomeration, China. Landsc. Ecol. 36, 2095–2112 (2021).Article 

Google Scholar 
Hansen, A. J. et al. A policy-driven framework for conserving the best of Earth’s remaining moist tropical forests. Nat. Ecol. Evol. 4, 1377–1384 (2020).Article 

Google Scholar 
Dos Santos, C. V. B., da Paixão Sevá, A., Werneck, G. L. & Struchiner, C. J. Does deforestation drive visceral leishmaniasis transmission? A causal analysis. Proc. R. Soc. B 288, 20211537 (2021).Article 

Google Scholar 
MacDonald, A. J. & Mordecai, E. A. Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing. Proc. Natl. Acad. Sci. USA 116, 22212–22218 (2019).Article 
CAS 

Google Scholar 
Honório, N. A. et al. Dispersal of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in an urban endemic dengue area in the State of Rio de Janeiro, Brazil. Mem. Inst. Oswaldo Cruz 98, 191–198 (2003).Article 

Google Scholar 
Rodrigues, N. B. et al. Brazilian Aedes aegypti as a competent vector for multiple complex arboviral coinfections. J. Infect. Dis. 224, 101–108 (2021).Article 

Google Scholar 
Weinstein, J. S., Leslie, T. F. & von Fricken, M. E. Spatial associations between land use and infectious disease: Zika virus in Colombia. Int. J. Environ. Res. Public Health 17, E1127 (2020).Article 

Google Scholar 
Heukelbach, J., Alencar, C. H., Kelvin, A. A., de Oliveira, W. K. & Pamplona de Góes Cavalcanti, L. Zika virus outbreak in Brazil. J. Infect. Dev. Countr. 10, 116–120 (2016).Article 

Google Scholar 
Lowe, R. et al. The Zika virus epidemic in Brazil: from discovery to future implications. Int. J. Environ. Res. Public Health 15, E96 (2018).Article 

Google Scholar 
Alves, M. C. G. P., de Matos, M. R., de Lourdes Reichmann, M. & Dominguez, M. H. Estimation of the dog and cat population in the State of São Paulo. Rev. Saude Publica 39, 891–897 (2005).Article 

Google Scholar 
Mordecai, E. A. et al. Thermal biology of mosquito-borne disease. Ecol. Lett. 22, 1690–1708 (2019).Article 

Google Scholar 
Gage, K. L., Burkot, T. R., Eisen, R. J. & Hayes, E. B. Climate and vectorborne diseases. Am. J. Prev. Med. 35, 436–450 (2008).Article 

Google Scholar 
Doenças e Agravos de Notificação – 2007 em Diante (SINAN) (DATASUS, Ministério da Saúde do Brasil, 2021); https://datasus.saude.gov.br/acesso-a-informacao/doencas-e-agravos-de-notificacao-de-2007-em-diante-sinan/SIVEP – MALÁRIA Notificação de Casos (Ministério da Saúde do Brasil, 2021); http://200.214.130.44/sivep_malaria/R Core Team. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2020); https://www.R-project.org/Sorichetta, A. et al. High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020. Sci. Data 2, 150045 (2015).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, 109 (2020).Article 

Google Scholar 
Souza at. al. Reconstructing three decades of land use and land cover changes in Brazilian biomes with Landsat archive and Earth Engine. Remote Sens. 12, https://doi.org/10.3390/rs12172735 (2020).Fountain-Jones, N. M. et al. How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure. J. Anim. Ecol. 88, 1447–1461 (2019).Article 

Google Scholar 
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).Article 

Google Scholar 
Genuer, R., Poggi, J.-M. & Tuleau-Malot, C. Variable selection using random forests. Pattern Recogn. Lett. 31, 2225–2236 (2010).Article 

Google Scholar 
Wei, T. et al. Package ‘corrplot’. Statistician 56, e24 (2017).
Google Scholar 
Ratner, B. The correlation coefficient: its values range between +1/−1, or do they? J. Target. Meas. Anal. Mark. 17, 139–142 (2009).Article 

Google Scholar 
Ishwaran, H. & Kogalur, U. B. Fast unified random forests for survival, regression, and classification (RF-SRC) (2019).O’Brien, R. & Ishwaran, H. A random forests quantile classifier for class imbalanced data. Pattern Recognit. 90, 232–249 (2019).Article 

Google Scholar 
Silge, J. & Mahoney, M. spatialsample: spatial resampling infrastructure. R version 0.2.1 (2023).Bhatt, S. et al. The global distribution and burden of dengue. Nature 496, 504–507 (2013).Article 
CAS 

Google Scholar 
Weaver, S. C. & Forrester, N. L. Chikungunya: evolutionary history and recent epidemic spread. Antivir. Res. 120, 32–39 (2015).Article 
CAS 

Google Scholar 
Puntasecca, C. J., King, C. H. & LaBeaud, A. D. Measuring the global burden of chikungunya and Zika viruses: a systematic review. PLoS Negl. Trop. Dis. 15, e0009055 (2021).Article 

Google Scholar 
Baeza, A., Santos-Vega, M., Dobson, A. P. & Pascual, M. The rise and fall of malaria under land-use change in frontier regions. Nat. Ecol. Evol. 1, 108 (2017).Article 

Google Scholar 
de Araújo Pedrosa, F. & de Alencar Ximenes, R. A. Sociodemographic and environmental risk factors for American cutaneous leishmaniasis (ACL) in the State of Alagoas, Brazil. Am. J. Trop. Med. Hyg. 81, 195–201 (2009).Article 

Google Scholar 
Gonçalves, N. V. et al. Cutaneous leishmaniasis: spatial distribution and environmental risk factors in the state of Pará, Brazilian Eastern Amazon. J. Infect. Dev. Countr. 13, 939–944 (2019).Article 

Google Scholar 
Leishmaniasis (Pan American Health Organization, 2022); https://www.paho.org/en/topics/leishmaniasisHarhay, M. O., Olliaro, P. L., Costa, D. L. & Costa, C. H. N. Urban parasitology: visceral leishmaniasis in Brazil. Trends Parasitol. 27, 403–409 (2011).Article 

Google Scholar  More

Verkerk, P., et al. Forest products in the global bioeconomy. The role of forest products in the global bioeconomy—Enabling substitution by wood-based products and contributing to the Sustainable Development Goals (2022). https://doi.org/10.4060/cb7274enChen, J., Ter-Mikaelian, M. T., Ng, P. Q. & Colombo, S. J. Ontario’s managed forests and harvested wood products contribute to greenhouse gas mitigation from 2020 to 2100. For. Chron. 43, 269–282 (2018).
Google Scholar 
Howard, C., Dymond, C. C., Griess, V. C., Tolkien-Spurr, D. & van Kooten, G. C. Wood product carbon substitution benefits: A critical review of assumptions. Carbon Balance Manag. 16, 1–11 (2021).Article 

Google Scholar 
Eriksson, L. O. et al. Climate change mitigation through increased wood use in the European construction sector-towards an integrated modelling framework. Eur. J. For. Res. 131, 131–144 (2012).Article 

Google Scholar 
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science (80-.) 333, 988–993 (2011).Article 
ADS 
CAS 

Google Scholar 
Chuine, I. Why does phenology drive species distribution?. Philos. Trans. R. Soc. B Biol. Sci. 365, 3149–3160 (2010).Article 

Google Scholar 
Silvestro, R. et al. From phenology to forest management: Ecotypes selection can avoid early or late frosts, but not both. For. Ecol. Manag. 436, 21–26 (2019).Article 

Google Scholar 
Buttò, V., Rossi, S., Deslauriers, A. & Morin, H. Is size an issue of time? Relationship between the duration of xylem development and cell traits. Ann. Bot. 123, 1257–1265 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Cartenì, F. et al. The physiological mechanisms behind the earlywood-to-latewood transition: A process-based modeling approach. Front. Plant Sci. 9, 1053 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Buttò, V., Rozenberg, P., Deslauriers, A., Rossi, S. & Morin, H. Environmental and developmental factors driving xylem anatomy and micro-density in black spruce. New Phytol. 230, 957–971 (2021).Article 
PubMed 

Google Scholar 
Buttó, V. et al. Regionwide temporal gradients of carbon allocation allow for shoot growth and latewood formation in boreal black spruce. Glob. Ecol. Biogeogr. 30, 1657–1670 (2021).Article 

Google Scholar 
Rathgeber, C. B. K. et al. Anatomical, developmental and physiological bases of tree-ring formation in relation to environmental factors. In Stable Isotopes in Tree Rings Vol. 8 (eds Siegwolf, R. T. W. et al.) 61–99 (Springer, Cham, 2022).Chapter 

Google Scholar 
Dória, L. C., Sonsin-Oliveira, J., Rossi, S. & Marcati, C. R. Functional trade-offs in volume allocation to xylem cell types in 75 species from the Brazilian savanna Cerrado. Ann. Bot. 130, 445–456 (2022).Article 
PubMed 

Google Scholar 
Rossi, S., Cairo, E., Krause, C. & Deslauriers, A. Growth and basic wood properties of black spruce along an alti-latitudinal gradient in Quebec, Canada. Ann. For. Sci. 72, 77–87 (2015).Article 

Google Scholar 
Shi, J. L., Riedl, B., Deng, J., Cloutier, A. & Zhang, S. Y. Impact of log position in the tree on mechanical and physical properties of black spruce medium-density fibreboard panels. Can. J. For. Res. 37, 866–873 (2007).Article 

Google Scholar 
Rathgeber, C. B. K., Decoux, V. & Leban, J. M. Linking intra-tree-ring wood density variations and tracheid anatomical characteristics in Douglas fir (Pseudotsuga menziesii (Mirb.) Franco). Ann. For. Sci. 63, 699–706 (2006).Article 

Google Scholar 
Cuny, H. E., Rathgeber, C. B. K., Frank, D., Fonti, P. & Fournier, M. Kinetics of tracheid development explain conifer tree-ring structure. New Phytol. 203, 1231–1241 (2014).Article 
PubMed 

Google Scholar 
Wodzicki, T. J. & Zajaczkowski, S. Methodical problems in studies on seasonal production of cambial xylem derivatives. Acta Soc. Bot. Pol. 39, 519–520 (1970).
Google Scholar 
Silvestro, R. et al. Upscaling xylem phenology: Sample size matters. Ann. Bot. https://doi.org/10.1093/aob/mcac110 (2022).Article 
PubMed 

Google Scholar 
Rossi, S., Girard, M. J. & Morin, H. Lengthening of the duration of xylogenesis engenders disproportionate increases in xylem production. Glob. Chang. Biol. 20, 2261–2271 (2014).Article 
ADS 
PubMed 

Google Scholar 
Gonsamo, A., Chen, J. M. & Ooi, Y. W. Peak season plant activity shift towards spring is reflected by increasing carbon uptake by extratropical ecosystems. Glob. Change Biol. 24, 2117–2128 (2018).Article 
ADS 

Google Scholar 
Dow, C. et al. Warm springs alter timing but not total growth of temperate deciduous trees. Nature 608, 552–557 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Oribe, Y., Funada, R. & Kubo, T. Relationships between cambial activity, cell differentiation and the localization of starch in storage tissues around the cambium in locally heated stems of Abies sachalinensis (Schmidt) Masters. Trees Struct. Funct. 17, 185–192 (2003).Article 

Google Scholar 
Schrader, J. et al. Polar auxin transport in the wood-forming tissues of hybrid aspen is under simultaneous control of developmental and environmental signals. Proc. Natl. Acad. Sci. USA 100, 10096–10101 (2003).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Deslauriers, A., Huang, J. G., Balducci, L., Beaulieu, M. & Rossi, S. The contribution of carbon and water in modulating wood formation in black spruce saplings. Plant Physiol. 170, 2072–2084 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Silvestro, R., Brasseur, S., Klisz, M., Mencuccini, M. & Rossi, S. Bioclimatic distance and performance of apical shoot extension: Disentangling the role of growth rate and duration in ecotypic differentiation. For. Ecol. Manag. 477, 118483 (2020).Article 

Google Scholar 
Perrin, M., Rossi, S. & Isabel, N. Synchronisms between bud and cambium phenology in black spruce: Early-flushing provenances exhibit early xylem formation. Tree Physiol. 37, 593–603 (2017).Article 
PubMed 

Google Scholar 
Begum, S., Nakaba, S., Yamagishi, Y., Oribe, Y. & Funada, R. Regulation of cambial activity in relation to environmental conditions: Understanding the role of temperature in wood formation of trees. Physiol. Plant. 147, 46–54 (2013).Article 
CAS 
PubMed 

Google Scholar 
Kagawa, A., Sugimoto, A. & Maximov, T. C. 13CO2 pulse-labelling of photoassimilates reveals carbon allocation within and between tree rings. Plant Cell Environ. 29, 1571–1584 (2006).Article 
CAS 
PubMed 

Google Scholar 
Hansen, J. & Beck, E. The fate and path of assimilation products in the stem of 8-year-old Scots pine (Pinus sylvestris L.) trees. Trees 4, 16–21 (1990).Article 

Google Scholar 
Fu, P. L., Grießinger, J., Gebrekirstos, A., Fan, Z. X. & Bräuning, A. Earlywood and latewood stable carbon and oxygen isotope variations in two pine species in Southwestern China during the recent decades. Front. Plant Sci. 7, 2050 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Anfodillo, T. et al. Widening of xylem conduits in a conifer tree depends on the longer time of cell expansion downwards along the stem. J. Exp. Bot. 63, 837–845 (2012).Article 
CAS 
PubMed 

Google Scholar 
Linares, J. C., Camarero, J. J. & Carreira, J. A. Plastic responses of Abies pinsapo xylogenesis to drought and competition. Tree Physiol. 29, 1525–1536 (2009).Article 
PubMed 

Google Scholar 
Rossi, S., Morin, H. & Deslauriers, A. Causes and correlations in cambium phenology: Towards an integrated framework of xylogenesis. J. Exp. Bot. 63, 2117–2126 (2012).Article 
CAS 
PubMed 

Google Scholar 
Li, X. et al. Age dependence of xylogenesis and its climatic sensitivity in Smith fir on the south-eastern Tibetan Plateau. Tree Physiol. 33, 48–56 (2013).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Rathgeber, C. B. K., Rossi, S. & Bontemps, J. D. Cambial activity related to tree size in a mature silver-fir plantation. Ann. Bot. 108, 429–438 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Buttò, V. et al. Comparing the cell dynamics of tree-ring formation observed in microcores and as predicted by the Vaganov-Shashkin model. Front. Plant Sci. 11, 1268 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Koga, S. & Zhang, S. Y. Relationships between wood density and annual growth rate components in balsam fir (Abies balsamea). Wood Fiber Sci. 34, 146–157 (2002).CAS 

Google Scholar 
Messier, C. et al. Functional ecology of advance regeneration in relation to light in boreal forests. Can. J. For. Res. 29, 812–823 (1999).Article 

Google Scholar 
Pothier, D., Elie, J. G., Auger, I., Mailly, D. & Gaudreault, M. Spruce budworm-caused mortality to balsam fir and black spruce in pure and mixed conifer stands. For. Sci. 58, 24–33 (2012).Article 

Google Scholar 
Paixao, C., Krause, C., Morin, H. & Achim, A. Wood quality of black spruce and balsam fir trees defoliated by spruce budworm: A case study in the boreal forest of Quebec, Canada. For. Ecol. Manag. 437, 201–210 (2019).Article 

Google Scholar 
Pretzsch, H., Biber, P., Schütze, G., Kemmerer, J. & Uhl, E. Wood density reduced while wood volume growth accelerated in Central European forests since 1870. For. Ecol. Manag. 429, 589–616 (2018).Article 

Google Scholar 
Reyer, C. et al. Projections of regional changes in forest net primary productivity for different tree species in Europe driven by climate change and carbon dioxide. Ann. For. Sci. 71, 211–225 (2014).Article 

Google Scholar 
Fang, J. et al. Evidence for environmentally enhanced forest growth. Proc. Natl. Acad. Sci. USA 111, 9527–9532 (2014).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pretzsch, H., Biber, P., Schütze, G., Uhl, E. & Rötzer, T. Forest stand growth dynamics in Central Europe have accelerated since 1870. Nat. Commun. 5, 1–10 (2014).Article 

Google Scholar 
Gao, S. et al. An earlier start of the thermal growing season enhances tree growth in cold humid areas but not in dry areas. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01668-4 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Soil Classification Working Group. The Canadian System of Soil Classification. (1998).Rossi, S., Anfodillo, T. & Menardi, R. Trephor: A new tool for sampling microcores from tree stems. IAWA J. 27, 89–97 (2006).Article 

Google Scholar 
Deslauriers, A., Morin, H. & Begin, Y. Cellular phenology of annual ring formation of Abies balsamea in the Quebec boreal forest (Canada). Can. J. For. Res. 33, 190–200 (2003).Article 

Google Scholar 
Rossi, S., Deslauriers, A. & Anfodillo, T. Assessment of cambial activity and xylogenesis by microsampling tree species: An example at the Alpine timberline. IAWA J. 27, 383–394 (2006).Article 

Google Scholar 
Filion, L. & Cournoyer, L. Variation in wood structure of eastern larch defoliated by the larch sawfly in subarctic Quebec, Canada. Can. J. For. Res. 25, 1263–1268 (1995).Article 

Google Scholar 
R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. (2015). More

Bindoff, N. L. et al. Changing ocean, marine ecosystems, and dependent communities. in IPCC special report on the ocean and cryosphere in a changing climate (eds. Pörtner, H.-O. et al.) (2019).Johnson, G. C. & Lyman, J. M. Warming trends increasingly dominate global ocean. Nat. Clim. Chang. 10, 757–761 (2020).ADS 

Google Scholar 
Doney, S. C. et al. Climate change impacts on marine ecosystems. Ann. Rev. Mar. Sci. 4, 11–37 (2012).PubMed 

Google Scholar 
Pinsky, M. L. & Mantua, N. J. Emerging adaptation approaches for climate- ready fisheries management. Oceanography 27, 146–159 (2014).
Google Scholar 
Bailey, K. M. & Houde, E. D. Predation on eggs and larvae of marine fishes and the recruitment problem. Adv. Mar. Biol. 25, 1–83 (1989).
Google Scholar 
Houde, E. D. Comparative growth, mortality, and energetics of marine fish larvae: temperature and implied latitudinal effects. Fish. Bull. 87, 471–495 (1989).
Google Scholar 
Wang, H., Shen, S., Chen, Y.-S., Kiang, Y.-K. & Heino, M. Life histories determine divergent population trends for fishes under climate warming. Nat. Commun. 11, 1–9 (2020).
Google Scholar 
Llopiz, J. K. et al. Early life history and fisheries oceanography: New questions in a changing world. Oceanography 27, 26–41 (2014).
Google Scholar 
Lasker, R. Field criteria for survival of anchovy larvae: The relation between inshore chlorophyll maximum layers and successful first feeding. Fish. Bull. 73, 453–462 (1975).
Google Scholar 
Cury, P. & Roy, C. Optimal environmental window and pelagic fish recruitment success in upwelling areas. Can. J. Fish. Aquat. Sci. 46, 670–680 (1989).
Google Scholar 
Iles, T. D. & Sinclair, M. Atlantic herring: Stock discreteness and abundance. Science 215, 627–633 (1982).ADS 
CAS 
PubMed 

Google Scholar 
Houde, E. D. Fish early life dynamics and recruitment variability. Am. Fish. Soc. Symp. 2, 17–29 (1987).ADS 

Google Scholar 
Searcy, S. P. & Sponaugle, S. Selective mortality during the larval – juvenile transition in two coral reef fishes. Ecology 82, 2452–2470 (2001).
Google Scholar 
Shima, J. S. & Findlay, A. M. Pelagic larval growth rate impacts benthic settlement and survival of a temperate reef fish. Mar. Ecol. Prog. Ser. 235, 303–309 (2002).ADS 

Google Scholar 
Bakun, A. Global climate change and intensification of coastal ocean upwelling. Science 247(198), 201 (1990).ADS 

Google Scholar 
Snyder, M. A., Sloan, L., Diffenbaugh, N. & Bell, J. Future climate change and upwelling in the California Current. Geophys. Res. Lett. 30, 1823 (2003).ADS 

Google Scholar 
Bakun, A., Field, D. B., Redondo-Rodriguez, A. & Weeks, S. J. Greenhouse gas, upwelling-favorable winds, and the future of coastal ocean upwelling ecosystems. Glob. Chang. Biol. 16, 1213–1228 (2010).ADS 

Google Scholar 
Bakun, A. & Nelson, C. The seasonal cycle of wind-stress curl in subtropical eastern boundary current regions. J. Phys. Oceanogr. 21, 1815–1834 (1991).ADS 

Google Scholar 
Shanks, A. L. & Eckert, G. L. Population persistence of California Current fishes and benthic crustaceans: A marine drift paradox. Ecol. Monogr. 75, 505–524 (2005).
Google Scholar 
Cushing, D. H. Plankton production and year-class strength in fish populations: An update of the match/mismatch hypothesis. Adv. Mar. Biol. 26, 249–293 (1990).
Google Scholar 
Carr, M. H. Habitat selection and recruitment of an assemblage of temperate zone reef fishes. J. Exp. Mar. Bio. Ecol. 146, 113–137 (1991).
Google Scholar 
Asch, R. G. Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem. Proc. Natl. Acad. Sci. U. S. A. 112, E4065–E4074 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Auth, T. D., Daly, E. A., Brodeur, R. D. & Fisher, J. L. Phenological and distributional shifts in ichthyoplankton associated with recent warming in the northeast Pacific Ocean. Glob. Chang. Biol. 24, 259–272 (2018).ADS 
PubMed 

Google Scholar 
Sydeman, W. J. et al. Climate change and wind intensification in coastal upwelling ecosystems. Science 345, 77–80 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Bond, N. A., Cronin, M. F., Freeland, H. & Mantua, N. Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophys. Res. Lett. 42, 3414–3420 (2015).ADS 

Google Scholar 
Cavole, A. et al. Biological impacts of the 2013–2015 warm water anomaly in the Northeast Pacific: Winner, losers, and the future. Oceanography 29, 273–285 (2016).
Google Scholar 
Lenarz, W. H. A history of California rockfish fisheries. In Proceeding of the International Rockfish Symposium. Anchorage, Alaska, Univ. of Alaska (1987).Brodeur, R. D., Buchanan, J. C. & Emmett, R. L. Pelagic and demersal fish predators on juvenile and adult forage fishes in the northern California Current: Spatial and temporal variations. CalCOFI Rep. 55, 96–116 (2014).
Google Scholar 
Mills, K. L., Laidig, T., Ralston, S. & Sydeman, W. J. Diets of top predators indicate pelagic juvenile rockfish (Sebastes spp.) abundance in the California Current System. Fish. Oceanogr. 16, 273–283 (2007).
Google Scholar 
Santora, J. A., Schroeder, I. D., Field, J. C., Wells, B. K. & Sydeman, W. J. Spatio-temporal dynamics of ocean conditions and forage taxa reveal regional structuring of seabird-prey relationships. Ecol. Appl. 24, 1730–1747 (2014).PubMed 

Google Scholar 
McClatchie, S. et al. Food limitation of sea lion pups and the decline of forage off central and southern California. R. Soc. Open Sci. 3, 150628 (2016).ADS 
PubMed 
PubMed Central 

Google Scholar 
Love, B. M. S., Yoklavich, M. & Thorsteinson, L. The Rockfishes of the Northeast Pacific (Univ of California Press, 2002).
Google Scholar 
Ralston, S. & Howard, D. F. On the development of year-class stength and cohort variability in two northern California rockfishes. Fish. Bull. 93, 710–720 (1995).
Google Scholar 
Wells, B. K. et al. Untangling the relationships among climate, prey, and top predators in an ocean ecosystem. Mar. Ecol. Prog. Ser. 364, 15–29 (2008).ADS 

Google Scholar 
Zabel, R. W., Levin, P. S., Tolimieri, N. & Mantua, N. J. Interactions between climate and population density in the episodic recruitment of bocaccio, Sebastes paucispinis, a Pacific rockfish. Fish. Oceanogr. 20, 294–304 (2011).
Google Scholar 
Peterson, W. T. et al. Applied fisheries oceanography: Ecosystem indicators of ocean conditions inform fisheries management in the California Current. Oceanography 27, 80–89 (2014).
Google Scholar 
Wheeler, S. G., Anderson, T. W., Bell, T. W., Morgan, S. G. & Hobbs, J. A. Regional productivity predicts individual growth and recruitment of rockfishes in a northern California upwelling system. Limnol. Oceanogr. 62, 754–767 (2016).ADS 

Google Scholar 
Ralston, S., Sakuma, K. M. & Field, J. C. Interannual variation in pelagic juvenile rockfish (Sebastes spp.) abundance – going with the flow. Fish. Oceanogr. 22, 288–308 (2013).
Google Scholar 
Schroeder, I. D. et al. Source water variability as a driver of rockfish recruitment in the california current ecosystem: Implications for climate change and fisheries management. Can. J. Fish. Aquat. Sci. 76, 950–960 (2019).CAS 

Google Scholar 
Ottmann, D., Grorud-Colvert, K., Huntington, B. & Sponaugle, S. Interannual and regional variability in settlement of groundfishes to protected and fished nearshore waters of Oregon, USA. Mar. Ecol. Prog. Ser. 598, 131–145 (2018).ADS 

Google Scholar 
Haggarty, D. R., Lotterhos, K. E. & Shurin, J. B. Young-of-the-year recruitment does not predict the abundance of older age classes in black rockfish in Barkley Sound, British Columbia. Canada. Mar. Ecol. Prog. Ser. 574, 113–126 (2017).ADS 

Google Scholar 
Checkley, D. M. & Barth, J. A. Patterns and processes in the California Current System. Prog. Oceanogr. 83, 49–64 (2009).ADS 

Google Scholar 
Jacox, M. G. et al. Forcing of multiyear extreme ocean temperatures that impacted California Current living marine resources in 2016. Bull. Am. Meteorol. Soc. 99, S27–S33 (2018).
Google Scholar 
Thompson, A. R. et al. Indicators of pelagic forage community shifts in the California Current Large Marine Ecosystem, 1998–2016. Ecol. Indic. 105, 215–228 (2019).
Google Scholar 
Du, X. & Peterson, W. T. Phytoplankton community structure in 2011–2013 compared to the extratropical warming event of 2014–2015. Geophys. Res. Lett. 45, 1534–1540 (2018).ADS 

Google Scholar 
Peterson, W. T. et al. The pelagic ecosystem in the Northern California Current off Oregon during the 2014–2016 warm anomalies within the context of the past 20 years. J. Geophys. Res. Ocean. 122, 7267–7290 (2017).ADS 

Google Scholar 
Brodeur, R. D., Auth, T. D. & Phillips, A. J. Major shifts in pelagic micronekton and macrozooplankton community structure in an upwelling ecosystem related to an unprecedented marine heatwave. Front. Mar. Sci. 6, 1–15 (2019).
Google Scholar 
Sutherland, K. R., Sorensen, H. L., Blondheim, O. N., Brodeur, R. D. & Galloway, A. W. E. Range expansion of tropical pyrosomes in the northeast Pacific Ocean. Ecology 99, 2397–2399 (2018).PubMed 

Google Scholar 
Brodeur, R. D., Hunsicker, M. E., Hann, A. & Miller, T. W. Effects of warming ocean conditions on feeding ecology of small pelagic fishes in a coastal upwelling ecosystem: A shift to gelatinous food sources. Mar. Ecol. Prog. Ser. 617–618, 149–163 (2019).ADS 

Google Scholar 
Bosley, K. L. et al. Feeding ecology of juvenile rockfishes off Oregon and Washington based on stomach content and stable isotope analyses. Mar. Biol. 161, 2381–2393 (2014).CAS 

Google Scholar 
Reilly, C. A., Echeverria, T. W. & Ralston, S. Interannual variation and overlap in the diets of pelagic juvenile rockfish (Genus: Sebastes) off central California. Fish. Bull. 90, 505–515 (1992).
Google Scholar 
Sumida, B. Y. & Moser, H. G. Food and feeding of bocaccio (Sebastes paucispinis) and comparison with Pacific hake (Merluccius productus) larvae in the California Current. Calif. Coop. Ocean. Fish. Investig. Reports 25, 112–118 (1984).
Google Scholar 
Auth, T. D., Brodeur, R. D., Soulen, H. L., Ciannelli, L. & Peterson, W. T. The response of fish larvae to decadal changes in environmental forcing factors off the Oregon coast. Fish. Oceanogr. 20, 314–328 (2011).
Google Scholar 
Frölicher, T. L. & Laufkötter, C. Emerging risks from marine heat waves. Nat. Commun. 9, 1–4 (2018).
Google Scholar 
Campana, S. E. Year-class strength and growth rate in young Atlantic cod Gadus morhua. Mar. Ecol. Prog. Ser. 135, 21–26 (1996).ADS 

Google Scholar 
Brander, K. Effects of environmental variability on growth and recruitment in cod (Gadus morhua) using a comparative approach. Oceanol. Acta 23, 485–496 (2000).
Google Scholar 
Sponaugle, S., Grorud-Colvert, K. & Pinkard, D. Temperature-mediated variation in early life history traits and recruitment success of the coral reef fish Thalassoma bifasciatum in the Florida Keys. Mar. Ecol. Prog. Ser. 308, 1–15 (2006).ADS 

Google Scholar 
Grorud-Colvert, K. & Sponaugle, S. Variability in water temperature affects trait-mediated survival of a newly settled coral reef fish. Oecologia 165, 675–686 (2011).ADS 
PubMed 

Google Scholar 
Boehlert, G. W. & Yoklavich, M. M. Effects of temperature, ration, and fish size on the growth of juvenile black rockfish, Sebastes melanops. Environ. Biol. Fishes 8, 17–28 (1983).
Google Scholar 
Chin, B., Nakagawa, M. & Yamashita, Y. Effects of feeding and temperature on survival and growth of larval black rockfish Sebastes schlegeli in rearing conditions. Aquac. Sci. 55, 619–627 (2007).
Google Scholar 
Woodbury, D. & Ralston, S. Interannual variation in growth rates and back-calculated birthdate distributions of pelagic juvenile rockfishes (Sebastes spp.) off the central California coast. Fish. Bull. 89, 523–533 (1991).
Google Scholar 
Fennie, H., Sponaugle, S., Daly, E. & Brodeur, R. Prey tell: what quillback rockfish early life history traits reveal about their survival in encounters with juvenile coho salmon. Mar. Ecol. Prog. Ser. 650, 7–18 (2020).ADS 

Google Scholar 
Laidig, T. E., Chess, J. R. & Howard, D. F. Relationship between abundance of juvenile rockfishes (Sebastes spp.) and environmental variables documented off northern California and potential mechanisms for the covariation. Fish. Bull. 105, 39–48 (2007).
Google Scholar 
Robert, D., Castonguay, M. & Fortier, L. Early growth and recruitment in Atlantic mackerel Scomber scombrus: discriminating the effects of fast growth and selection for fast growth. Mar. Ecol. Prog. Ser. 337, 209–219 (2007).ADS 

Google Scholar 
Hare, J. A. & Cowen, R. K. Size, growth, development, and survival of the planktonic larvae of Pomatomus saltatrix (Pisces: Pomatomidae). Ecology 78, 2415–2431 (1997).
Google Scholar 
Takasuka, A., Aoki, I. & Mitani, I. Evidence of growth-selective predation on larval Japanese anchovy Engraulis japonicus in Sagami Bay. Mar. Ecol. Prog. Ser. 252, 223–238 (2003).ADS 

Google Scholar 
Anderson, J. T. A review of size dependent survival during pre-recruit stages of fishes in relation to recruitment. J. Northwest Atl. Fish. Sci. 8, 55–66 (1988).
Google Scholar 
Miller, T., Crowder, L. B., Rice, J. A. & Marschall, E. A. Larval size and recruitment mechanisms in fishes: toward a conceptual framework. Can. J. Fish. Aquat. Sci. 45, 1657–1670 (1988).
Google Scholar 
Chambers, R. C. & Leggett, W. C. Size and age at metamorphosis in marine fishes: analysis of laboratory-reared winter flounder (Pseudopieuronectes americanus) with a review of variation in other species. Can. J. Fish. Aquat. Sci. 44, 1936–1947 (1987).
Google Scholar 
Kashef, N., Sogard, S., Fisher, R. & Largier, J. Ontogeny of critical swimming speeds for larval and pelagic juvenile rockfishes (Sebastes spp., family Scorpaenidae). Mar. Ecol. Prog. Ser. 500, 231–243 (2014).ADS 

Google Scholar 
Paradis, A. R., Pepin, P. & Brown, J. A. Vulnerability of fish eggs and larvae to predation: review of the influence of the relative size of prey and predator. Can. J. Fish. Aquat. Sci. 53, 1226–1235 (1996).
Google Scholar 
Purcell, J. E. Predation on fish larvae and eggs by the hydromedusa Aequorea victoria at a herring spawning ground in British Columbia. Can. J. Fish. Aquat. Sci. 46, 1415–1427 (1989).
Google Scholar 
McLeod, I. M. & Clark, T. D. Limited capacity for faster digestion in larval coral reef fish at an elevated temperature. PLoS ONE 11, 1–13 (2016).
Google Scholar 
Takahashi, M., Checkley, D. M., Litz, M. N. C., Brodeur, R. D. & Peterson, W. T. Responses in growth rate of larval northern anchovy (Engraulis mordax) to anomalous upwelling in the northern California Current. Fish. Oceanogr. 21, 393–404 (2012).
Google Scholar 
Team, R. C. R: A language and environment for statistical computing. (2013).Brady, R. X., Alexander, M. A., Lovenduski, N. S. & Rykaczewski, R. R. Emergent anthropogenic trends in California Current upwelling. Geophys. Res. Lett. 44, 5044–5052 (2017).ADS 

Google Scholar 
Peterson, W. T. & Keister, J. E. Interannual variability in copepod community composition at a coastal station in the northern California Current: A multivariate approach. Deep Res. Part II Top. Stud. Oceanogr. 50, 2499–2517 (2003).ADS 

Google Scholar 
Ammann, A. J. SMURFs: Standard monitoring units for the recruitment of temperate reef fishes. J. Exp. Mar. Bio. Ecol. 299, 135–154 (2004).
Google Scholar 
Anderson, T. W. & Carr, M. H. BINCKE: A highly efficient net for collecting reef fishes. Environ. Biol. Fishes 51, 111–115 (1998).
Google Scholar 
Kilkenny, C., Browne, W., Cuthill, I. C., Emerson, M. & Altman, D. G. Animal research: Reporting in vivo experiments: The ARRIVE guidelines. Br. J. Pharmacol. 160, 1577–1579 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Laidig, T. E. & Adams, P. B. Methods used to identify pelagic juvenile rockfish (Genus Sebastes) occuring along the coast of central California. NOAA Technical Memorandum NMFS (1991).Di Lorenzo, E. & Mantua, N. Multi-year persistence of the 2014/15 North Pacific marine heatwave. Nat. Clim. Chang. 6, 1042–1047 (2016).ADS 

Google Scholar 
Yoklavich, M. M. & Boehlert, G. W. Daily growth increments in otoliths of juvenile black rockfish, Sebastes melanops: An evaluation of autoradiography as a new method of validation. Fish. Bull. 85, 826–832 (1987).
Google Scholar 
Miller, J. A. & Shanks, A. L. Evidence for limited larval dispersal in black rockfish (Sebastes melanops): Implications for population structure and marine-reserve design. Can. J. Fish. Aquat. Sci. 61, 1723–1735 (2004).
Google Scholar 
Sponaugle, S. Daily otolith increments in the early stages of tropical fish. In Tropical Fish Otoliths: Information for Assessment, Management and Ecology (eds Green, B. et al.) 93–132 (Springer, 2009).
Google Scholar 
Laidig, T., Ralston, S. & Bence, J. R. Dynamics of growth in the early life history of shortbelly rockfish Sebastes jordani. Fish. Bull. 89, 611–621 (1991).
Google Scholar 
Thorrold, S. R. & Hare, J. A. Otolith applications in reef fish ecology. In Coral Reef Fishes: Dynamics and Diversity in a Complex Ecosystem (ed. Sale, P. F.) 243–264 (Academic Press, 2002).
Google Scholar 
Field, J. C., MacCall, A. D., Ralston, S., Love, M. S. & Miller, E. F. Bocaccionomics: The effectiveness of pre-recruit indices for assessment and management of bocaccio. Calif. Coop. Ocean. Fish. Investig. Reports 51, 77–90 (2010).
Google Scholar 
Carrascal, L. M., Galván, I. & Gordo, O. Partial least squares regression as an alternative to current regression methods used in ecology. Oikos 118, 681–690 (2009).
Google Scholar  More