in

A predictive timeline of wildlife population collapse

  • Ceballos, G. et al. Accelerated modern human-induced species losses: entering the sixth mass extinction. Sci. Adv. 1, e1400253 (2015).

    Article 

    Google Scholar 

  • Dereniowska, M. & Meinard, Y. The unknownness of biodiversity: its value and ethical significance for conservation action. Biol. Conserv. 260, 109199 (2021).

    Article 

    Google Scholar 

  • Maron, M. et al. Towards a threat assessment framework for ecosystem services. Trends Ecol. Evol. 32, 240–248 (2017).

    Article 

    Google Scholar 

  • Tilman, D. et al. Future threats to biodiversity and pathways to their prevention. Nature 546, 73–81 (2017).

    Article 
    CAS 

    Google Scholar 

  • Taborsky, B. et al. Towards an evolutionary theory of stress responses. Trends Ecol. Evol. 36, 39–48 (2021).

    Article 

    Google Scholar 

  • van de Leemput, I. A., Dakos, V., Scheffer, M. & van Nes, E. H. Slow recovery from local disturbances as an indicator for loss of ecosystem resilience. Ecosystems 21, 141–152 (2018).

    Article 

    Google Scholar 

  • Fagan, W. F. & Holmes, E. E. Quantifying the extinction vortex. Ecol. Lett. 9, 51–60 (2005).

    Google Scholar 

  • Williams, N. F., McRae, L., Freeman, R., Capdevila, P. & Clements, C. F. Scaling the extinction vortex: body size as a predictor of population dynamics close to extinction events. Ecol. Evol. 11, 7069–7079 (2021).

    Article 

    Google Scholar 

  • Clements, C. F. & Ozgul, A. Indicators of transitions in biological systems. Ecol. Lett. 21, 905–919 (2018).

    Article 

    Google Scholar 

  • Shaffer, M. L. in Challenges in the Conservation of Biological Resources (eds. Decker, D. J., Krasny, M. E., Goff, G. R., Smith, C. R. & Gross, D. W.) 107–118 (Routledge, 2019).

  • Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009).

    Article 
    CAS 

    Google Scholar 

  • Gardner, T. A. et al. The cost-effectiveness of biodiversity surveys in tropical forests. Ecol. Lett. 11, 139–150 (2008).

    Article 

    Google Scholar 

  • Coulson, T., Mace, G. M., Hudson, E. & Possingham, H. The use and abuse of population viability analysis. Trends Ecol. Evol. 16, 219–221 (2001).

    Article 
    CAS 

    Google Scholar 

  • Clements, C. F., Drake, J. M., Griffiths, J. I. & Ozgul, A. Factors influencing the detectability of early warning signals of population collapse. Am. Nat. 186, 50–58 (2015).

    Article 

    Google Scholar 

  • Patterson, A. C., Strang, A. G. & Abbott, K. C. When and where we can expect to see early warning signals in multispecies systems approaching tipping points: insights from theory. Am. Nat. 198, E12–E26 (2021).

    Article 

    Google Scholar 

  • Vinton, A. C., Gascoigne, S. J. L., Sepil, I. & Salguero-Gómez, R. Plasticity’s role in adaptive evolution depends on environmental change components. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2022.08.008 (2022).

  • Levin, S. A. The problem of pattern and scale in ecology: the Robert H. MacArthur Award lecture. Ecology 73, 1943–1967 (1992).

    Article 

    Google Scholar 

  • Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).

    Article 

    Google Scholar 

  • Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M. & Charnov, E. L. Effects of size and temperature on metabolic rate. Science 293, 2248–2251 (2001).

    Article 
    CAS 

    Google Scholar 

  • Haberle, I., Marn, N., Geček, S. & Klanjšček, T. Dynamic energy budget of endemic and critically endangered bivalve Pinna nobilis: a mechanistic model for informed conservation. Ecol. Model. 434, 109207 (2020).

    Article 

    Google Scholar 

  • Gislason, H., Daan, N., Rice, J. C. & Pope, J. G. Size, growth, temperature and the natural mortality of marine fish. Fish Fish. 11, 149–158 (2010).

    Article 

    Google Scholar 

  • Jennings, S. & Blanchard, J. L. Fish abundance with no fishing: predictions based on macroecological theory. J. Anim. Ecol. 73, 632–642 (2004).

    Article 

    Google Scholar 

  • Valderrama, D. & Fields, K. H. Flawed evidence supporting the metabolic theory of ecology may undermine goals of ecosystem-based fishery management: the case of invasive Indo-Pacific lionfish in the western Atlantic. ICES J. Mar. Sci. 74, 1256–1267 (2017).

    Article 

    Google Scholar 

  • Marshall, D. J. & McQuaid, C. D. Warming reduces metabolic rate in marine snails: adaptation to fluctuating high temperatures challenges the metabolic theory of ecology. Proc. R. Soc. B 278, 281–288 (2011).

    Article 

    Google Scholar 

  • Rombouts, I., Beaugrand, G., Ibaňez, F., Chiba, S. & Legendre, L. Marine copepod diversity patterns and the metabolic theory of ecology. Oecologia 166, 349–355 (2011).

    Article 

    Google Scholar 

  • Allen, A. P. & Gillooly, J. F. The mechanistic basis of the metabolic theory of ecology. Oikos 116, 1073–1077 (2022).

    Article 

    Google Scholar 

  • Lawton, J. H. From physiology to population dynamics and communities. Funct. Ecol. 5, 155–161 (1991).

    Article 

    Google Scholar 

  • Ames, E. M. et al. Striving for population-level conservation: integrating physiology across the biological hierarchy. Conserv. Physiol. 8, coaa019 (2020).

    Article 

    Google Scholar 

  • Berger-Tal, O. et al. Integrating animal behavior and conservation biology: a conceptual framework. Behav. Ecol. 22, 236–239 (2011).

    Article 

    Google Scholar 

  • Baruah, G., Clements, C. F., Guillaume, F. & Ozgul, A. When do shifts in trait dynamics precede population declines? Am. Nat. 193, 633–644 (2019).

    Article 

    Google Scholar 

  • Dakos, V. et al. Methods for detecting early warnings of critical transitions in time series illustrated using simulated ecological data. PLoS ONE 7, e41010 (2012).

    Article 
    CAS 

    Google Scholar 

  • Ward, R. J., Griffiths, R. A., Wilkinson, J. W. & Cornish, N. Optimising monitoring efforts for secretive snakes: a comparison of occupancy and N-mixture models for assessment of population status. Sci. Rep. 7, 18074 (2017).

    Article 

    Google Scholar 

  • Thompson, W. Sampling Rare or Elusive Species: Concepts, Designs, and Techniques for Estimating Population Parameters (Island Press, 2013).

  • Clements, C. F., Blanchard, J. L., Nash, K. L., Hindell, M. A. & Ozgul, A. Body size shifts and early warning signals precede the historic collapse of whale stocks. Nat. Ecol. Evol. 1, 0188 (2017).

    Article 

    Google Scholar 

  • Burant, J. B., Park, C., Betini, G. S. & Norris, D. R. Early warning indicators of population collapse in a seasonal environment. J. Anim. Ecol. 90, 1538–1549 (2021).

    Article 

    Google Scholar 

  • Tuomainen, U. & Candolin, U. Behavioural responses to human-induced environmental change. Biol. Rev. 86, 640–657 (2011).

    Article 

    Google Scholar 

  • Mazza, V., Dammhahn, M., Lösche, E. & Eccard, J. A. Small mammals in the big city: behavioural adjustments of non-commensal rodents to urban environments. Glob. Change Biol. 26, 6326–6337 (2020).

    Article 

    Google Scholar 

  • Hendry, A. P., Farrugia, T. J. & Kinnison, M. T. Human influences on rates of phenotypic change in wild animal populations. Mol. Ecol. 17, 20–29 (2008).

    Article 

    Google Scholar 

  • Speakman, J. R., Król, E. & Johnson, M. S. The functional significance of individual variation in basal metabolic rate. Physiol. Biochem. Zool. 77, 900–915 (2004).

    Article 

    Google Scholar 

  • Péron, G. et al. Evidence of reduced individual heterogeneity in adult survival of long-lived species. Evolution 70, 2909–2914 (2016).

    Article 

    Google Scholar 

  • Fleming, A. H., Clark, C. T., Calambokidis, J. & Barlow, J. Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current. Glob. Change Biol. 22, 1214–1224 (2016).

    Article 

    Google Scholar 

  • Kirkwood, T. B. L., Rose, M. R., Harvey, P. H., Partridge, L. & Southwood, S. R. Evolution of senescence: late survival sacrificed for reproduction. Phil. Trans. R. Soc. Lond. B 332, 15–24 (1991).

    Article 
    CAS 

    Google Scholar 

  • Mallela, A. & Hastings, A. The role of stochasticity in noise-induced tipping point cascades: a master equation approach. Bull. Math. Biol. 83, 53 (2021).

    Article 

    Google Scholar 

  • Burthe, S. J. et al. Do early warning indicators consistently predict nonlinear change in long-term ecological data? J. Appl. Ecol. 53, 666–676 (2016).

    Article 

    Google Scholar 

  • Vucetich, J. A. & Waite, T. A. Erosion of heterozygosity in fluctuating populations. Conserv. Biol. 13, 860–868 (1999).

    Article 

    Google Scholar 

  • Kramer, A. M. & Drake, J. M. Experimental demonstration of population extinction due to a predator-driven Allee effect. J. Anim. Ecol. 79, 633–639 (2010).

    Article 

    Google Scholar 

  • Oram, E. & Spitze, K. Depth selection by Daphnia pulex in response to Chaoborus kairomone. Freshw. Biol. 58, 409–415 (2013).

    Article 

    Google Scholar 

  • Trites, A. W. & Donnelly, C. P. The decline of Steller sea lions Eumetopias jubatus in Alaska: a review of the nutritional stress hypothesis. Mammal. Rev. 33, 3–28 (2003).

    Article 

    Google Scholar 

  • Sibly, R. M., Barker, D., Hone, J. & Pagel, M. On the stability of populations of mammals, birds, fish and insects. Ecol. Lett. 10, 970–976 (2007).

    Article 

    Google Scholar 

  • Dakos, V. et al. Ecosystem tipping points in an evolving world. Nat. Ecol. Evol. 3, 355–362 (2019).

    Article 

    Google Scholar 

  • Dingemanse, N. J., Kazem, A. J. N., Réale, D. & Wright, J. Behavioural reaction norms: animal personality meets individual plasticity. Trends Ecol. Evol. 25, 81–89 (2010).

    Article 

    Google Scholar 

  • Tanner, R. L. & Dowd, W. W. Inter-individual physiological variation in responses to environmental variation and environmental change: integrating across traits and time. Comp. Biochem. Physiol. A 238, 110577 (2019).

    Article 
    CAS 

    Google Scholar 

  • Patrick, S. C., Martin, J. G. A., Ummenhofer, C. C., Corbeau, A. & Weimerskirch, H. Albatrosses respond adaptively to climate variability by changing variance in a foraging trait. Glob. Change Biol. 27, 4564–4574 (2021).

    Article 
    CAS 

    Google Scholar 

  • Fayet, A. L., Clucas, G. V., Anker‐Nilssen, T., Syposz, M. & Hansen, E. S. Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin. J. Anim. Ecol. https://doi.org/10.1111/1365-2656.13442 (2021).

  • Pierce, C. L. Predator avoidance, microhabitat shift, and risk-sensitive foraging in larval dragonflies. Oecologia 77, 81–90 (1988).

    Article 
    CAS 

    Google Scholar 

  • Leibold, M. & Tessier, A. J. Contrasting patterns of body size for Daphnia species that segregate by habitat. Oecologia 86, 342–348 (1991).

    Article 

    Google Scholar 

  • Charmantier, A. & Gienapp, P. Climate change and timing of avian breeding and migration: evolutionary versus plastic changes. Evol. Appl. 7, 15–28 (2014).

    Article 

    Google Scholar 

  • Kopp, M. & Matuszewski, S. Rapid evolution of quantitative traits: theoretical perspectives. Evol. Appl. 7, 169–191 (2014).

    Article 

    Google Scholar 

  • Williams, J. W., Ordonez, A. & Svenning, J.-C. A unifying framework for studying and managing climate-driven rates of ecological change. Nat. Ecol. Evol. 5, 17–26 (2021).

    Article 

    Google Scholar 

  • Jaureguiberry, P. et al. The direct drivers of recent global anthropogenic biodiversity loss. Sci. Adv. 8, eabm9982 (2022).

    Article 

    Google Scholar 

  • Chevin, L.-M., Collins, S. & Lefèvre, F. Phenotypic plasticity and evolutionary demographic responses to climate change: taking theory out to the field. Funct. Ecol. 27, 967–979 (2013).

    Article 

    Google Scholar 

  • Ferriere, R. & Legendre, S. Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory. Phil. Trans. R. Soc. B 368, 20120081 (2013).

    Article 

    Google Scholar 

  • Rebecchi, L., Boschetti, C. & Nelson, D. R. Extreme-tolerance mechanisms in meiofaunal organisms: a case study with tardigrades, rotifers and nematodes. Hydrobiologia 847, 2779–2799 (2020).

    Article 

    Google Scholar 

  • Hansson, B. & Westerberg, L. On the correlation between heterozygosity and fitness in natural populations. Mol. Ecol. 11, 2467–2474 (2002).

    Article 

    Google Scholar 

  • Mammola, S., Carmona, C. P., Guillerme, T. & Cardoso, P. Concepts and applications in functional diversity. Funct. Ecol. 35, 1869–1885 (2021).

    Article 
    CAS 

    Google Scholar 

  • McClanahan, T. R. et al. Highly variable taxa-specific coral bleaching responses to thermal stresses. Mar. Ecol. Prog. Ser. 648, 135–151 (2020).

    Article 

    Google Scholar 

  • Reside, A. E. et al. Beyond the model: expert knowledge improves predictions of species’ fates under climate change. Ecol. Appl. 29, e01824 (2019).

    Article 

    Google Scholar 

  • Desjonquères, C., Gifford, T. & Linke, S. Passive acoustic monitoring as a potential tool to survey animal and ecosystem processes in freshwater environments. Freshw. Biol. 65, 7–19 (2020).

    Article 

    Google Scholar 

  • Sequeira, A. M. M. et al. A standardisation framework for bio-logging data to advance ecological research and conservation. Methods Ecol. Evol. 12, 996–1007 (2021).

    Article 

    Google Scholar 

  • Shimada, T. et al. Optimising sample sizes for animal distribution analysis using tracking data. Methods Ecol. Evol. 12, 288–297 (2021).

    Article 

    Google Scholar 

  • Wauchope, H. S. et al. Evaluating impact using time-series data. Trends Ecol. Evol. 36, 196–205 (2021).

    Article 

    Google Scholar 

  • Krause, D. J., Hinke, J. T., Perryman, W. L., Goebel, M. E. & LeRoi, D. J. An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system. PLoS ONE 12, e0187465 (2017).

    Article 

    Google Scholar 

  • Besson, M. et al. Towards the fully automated monitoring of ecological communities. Ecol. Lett. https://doi.org/10.1111/ele.14123 (2022).

    Article 

    Google Scholar 

  • Cavender-Bares, J. et al. Integrating remote sensing with ecology and evolution to advance biodiversity conservation. Nat. Ecol. Evol. 6, 506–519 (2022).

    Article 

    Google Scholar 

  • Ingram, D. J., Ferreira, G. B., Jones, K. E. & Mace, G. M. Targeting conservation actions at species threat response thresholds. Trends Ecol. Evol. 36, 216–226 (2021).

    Article 

    Google Scholar 

  • Keith, S. A. et al. Synchronous behavioural shifts in reef fishes linked to mass coral bleaching. Nat. Clim. Change 8, 986–991 (2018).

    Article 

    Google Scholar 

  • Drake, J. M. & Griffen, B. D. Early warning signals of extinction in deteriorating environments. Nature 467, 456–459 (2010).

    Article 
    CAS 

    Google Scholar 

  • Enquist, B. J. et al. in Advances in Ecological Research Vol. 52 (eds Pawar, S. et al.) 249–318 (Academic Press, 2015).

  • Wei, W. W. S. Multivariate Time Series Analysis and Applications (John Wiley & Sons, 2018).

  • Holmes, E. E., Ward, E. J. & Wills, K. MARSS: multivariate autoregressive state-space models for analyzing time-series data. R J. 4, 11–19 (2012).

    Article 

    Google Scholar 

  • Zhu, M., Yamakawa, T. & Sakai, T. Combined use of trawl fishery and research vessel survey data in a multivariate autoregressive state-space (MARSS) model to improve the accuracy of abundance index estimates. Fish. Sci. 84, 437–451 (2018).

    Article 
    CAS 

    Google Scholar 

  • Lai, G., Chang, W.-C., Yang, Y. & Liu, H. Modeling long- and short-term temporal patterns with deep neural networks. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval 95–104, https://doi.org/10.1145/3209978.3210006 (ACM, 2018).

  • Bury, T. M. et al. Deep learning for early warning signals of tipping points. Proc. Natl Acad. Sci. USA 118, e2106140118 (2021).

    Article 
    CAS 

    Google Scholar 

  • Lara-Benítez, P., Carranza-García, M. & Riquelme, J. C. An experimental review on deep learning architectures for time series forecasting. Int. J. Neural Syst. 31, 2130001 (2021).

    Article 

    Google Scholar 

  • Guo, Q. et al. Application of deep learning in ecological resource research: theories, methods, and challenges. Sci. China Earth Sci. 63, 1457–1474 (2020).

    Article 

    Google Scholar 

  • Rogers, T. L., Johnson, B. J. & Munch, S. B. Chaos is not rare in natural ecosystems. Nat. Ecol. Evol. 6, 1105–1111 (2022).

    Article 

    Google Scholar 

  • Samplonius, J. M. et al. Phenological sensitivity to climate change is higher in resident than in migrant bird populations among European cavity breeders. Glob. Change Biol. 24, 3780–3790 (2018).

    Article 

    Google Scholar 

  • Menzel, A. et al. Climate change fingerprints in recent European plant phenology. Glob. Change Biol. 26, 2599–2612 (2020).

    Article 

    Google Scholar 

  • Koleček, J., Adamík, P. & Reif, J. Shifts in migration phenology under climate change: temperature vs. abundance effects in birds. Clim. Change 159, 177–194 (2020).

    Article 

    Google Scholar 

  • Altermatt, F. et al. Big answers from small worlds: a user’s guide for protist microcosms as a model system in ecology and evolution. Methods Ecol. Evol. 6, 218–231 (2015).

    Article 

    Google Scholar 

  • Beermann, A. J. et al. Multiple-stressor effects on stream macroinvertebrate communities: a mesocosm experiment manipulating salinity, fine sediment and flow velocity. Sci. Total Environ. 610611, 961–971 (2018).

    Article 

    Google Scholar 

  • Clements, C. F. & Ozgul, A. Including trait-based early warning signals helps predict population collapse. Nat. Commun. 7, 10984 (2016).

    Article 
    CAS 

    Google Scholar 

  • Jacquet, C. & Altermatt, F. The ghost of disturbance past: long-term effects of pulse disturbances on community biomass and composition. Proc. R. Soc. B 287, 20200678 (2020).

    Article 

    Google Scholar 

  • Greggor, A. L. et al. Research priorities from animal behaviour for maximising conservation progress. Trends Ecol. Evol. 31, 953–964 (2016).

    Article 

    Google Scholar 

  • Couvillon, M. J., Schürch, R. & Ratnieks, F. L. W. Waggle dance distances as integrative indicators of seasonal foraging challenges. PLoS ONE 9, e93495 (2014).

    Article 

    Google Scholar 

  • Hamilton, C. D., Lydersen, C., Ims, R. A. & Kovacs, K. M. Predictions replaced by facts: a keystone species’ behavioural responses to declining Arctic sea-ice. Biol. Lett. 11, 20150803 (2015).

    Article 

    Google Scholar 

  • Holt, R. E. & Jørgensen, C. Climate change in fish: effects of respiratory constraints on optimal life history and behaviour. Biol. Lett. 11, 20141032 (2015).

    Article 

    Google Scholar 

  • Gauzens, B. et al. Adaptive foraging behaviour increases vulnerability to climate change. Preprint at https://doi.org/10.1101/2021.05.05.442768 (2021).

  • Lenda, M., Witek, M., Skórka, P., Moroń, D. & Woyciechowski, M. Invasive alien plants affect grassland ant communities, colony size and foraging behaviour. Biol. Invasions 15, 2403–2414 (2013).

    Article 

    Google Scholar 

  • Hertel, A. G. et al. Don’t poke the bear: using tracking data to quantify behavioural syndromes in elusive wildlife. Anim. Behav. 147, 91–104 (2019).

    Article 

    Google Scholar 

  • Tini, M. et al. Use of space and dispersal ability of a flagship saproxylic insect: a telemetric study of the stag beetle (Lucanus cervus) in a relict lowland forest. Insect Conserv. Divers. 11, 116–129 (2018).

    Article 

    Google Scholar 

  • Kunc, H. P. & Schmidt, R. Species sensitivities to a global pollutant: a meta-analysis on acoustic signals in response to anthropogenic noise. Glob. Change Biol. 27, 675–688 (2021).

    Article 

    Google Scholar 

  • Anestis, A., Lazou, A., Pörtner, H. O. & Michaelidis, B. Behavioral, metabolic, and molecular stress responses of marine bivalve Mytilus galloprovincialis during long-term acclimation at increasing ambient temperature. Am. J. Physiol. 293, R911–R921 (2007).

    CAS 

    Google Scholar 

  • Pacherres, C. O., Schmidt, G. M. & Richter, C. Autotrophic and heterotrophic responses of the coral Porites lutea to large amplitude internal waves. J. Exp. Biol. 216, 4365–4374 (2013).

    Google Scholar 

  • Ban, S. S., Graham, N. A. J. & Connolly, S. R. Evidence for multiple stressor interactions and effects on coral reefs. Glob. Change Biol. 20, 681–697 (2014).

    Article 

    Google Scholar 

  • Singh, R., Prathibha, P. & Jain, M. Effect of temperature on life-history traits and mating calls of a field cricket, Acanthogryllus asiaticus. J. Therm. Biol. 93, 102740 (2020).

    Article 

    Google Scholar 

  • Pellegrini, A. Y., Romeu, B., Ingram, S. N. & Daura-Jorge, F. G. Boat disturbance affects the acoustic behaviour of dolphins engaged in a rare foraging cooperation with fishers. Anim. Conserv. 24, 613–625 (2021).

    Article 

    Google Scholar 

  • McMahan, M. D. & Grabowski, J. H. Nonconsumptive effects of a range-expanding predator on juvenile lobster (Homarus americanus) population dynamics. Ecosphere 10, e02867 (2019).

    Article 

    Google Scholar 

  • Vilhunen, S., Hirvonen, H. & Laakkonen, M. V.-M. Less is more: social learning of predator recognition requires a low demonstrator to observer ratio in Arctic charr (Salvelinus alpinus). Behav. Ecol. Sociobiol. 57, 275–282 (2005).

    Article 

    Google Scholar 

  • Ortega, Z., Mencía, A. & Pérez-Mellado, V. Rapid acquisition of antipredatory responses to new predators by an insular lizard. Behav. Ecol. Sociobiol. 71, 1 (2017).

    Article 

    Google Scholar 

  • Fox, R. J., Donelson, J. M., Schunter, C., Ravasi, T. & Gaitán-Espitia, J. D. Beyond buying time: the role of plasticity in phenotypic adaptation to rapid environmental change. Phil. Trans. R. Soc. B 374, 20180174 (2019).

    Article 

    Google Scholar 

  • Pigeon, G., Ezard, T. H. G., Festa-Bianchet, M., Coltman, D. W. & Pelletier, F. Fluctuating effects of genetic and plastic changes in body mass on population dynamics in a large herbivore. Ecology 98, 2456–2467 (2017).

    Article 

    Google Scholar 

  • Lomolino, M. V. & Perault, D. R. Body size variation of mammals in a fragmented, temperate rainforest. Conserv. Biol. 21, 1059–1069 (2007).

    Article 

    Google Scholar 

  • Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L. & Heinsohn, R. Declining body size: a third universal response to warming? Trends Ecol. Evol. 26, 285–291 (2011).

    Article 

    Google Scholar 

  • Sheridan, J. A. & Bickford, D. Shrinking body size as an ecological response to climate change. Nat. Clim. Change 1, 401–406 (2011).

    Article 

    Google Scholar 

  • Thoral, E. et al. Changes in foraging mode caused by a decline in prey size have major bioenergetic consequences for a small pelagic fish. J. Anim. Ecol. 90, 2289–2301 (2021).

    Article 

    Google Scholar 

  • Stirling, I. & Derocher, A. E. Effects of climate warming on polar bears: a review of the evidence. Glob. Change Biol. 18, 2694–2706 (2012).

    Article 

    Google Scholar 

  • Spanbauer, T. L. et al. Body size distributions signal a regime shift in a lake ecosystem. Proc. R. Soc. B 283, 20160249 (2016).

    Article 

    Google Scholar 

  • Bjorndal, K. A. et al. Ecological regime shift drives declining growth rates of sea turtles throughout the West Atlantic. Glob. Change Biol. 23, 4556–4568 (2017).

    Article 

    Google Scholar 

  • Eshun-Wilson, F., Wolf, R., Andersen, T., Hessen, D. O. & Sperfeld, E. UV radiation affects antipredatory defense traits in Daphnia pulex. Ecol. Evol. 10, 14082–14097 (2020).

    Article 

    Google Scholar 

  • Zhang, H., Hollander, J. & Hansson, L.-A. Bi-directional plasticity: rotifer prey adjust spine length to different predator regimes. Sci. Rep. 7, 10254 (2017).

    Article 

    Google Scholar 

  • Simbula, G., Vignoli, L., Carretero, M. A. & Kaliontzopoulou, A. Fluctuating asymmetry as biomarker of pesticides exposure in the Italian wall lizards (Podarcis siculus). Zoology 147, 125928 (2021).

    Article 

    Google Scholar 

  • Leary, R. F. & Allendorf, F. W. Fluctuating asymmetry as an indicator of stress: implications for conservation biology. Trends Ecol. Evol. 4, 214–217 (1989).

    Article 
    CAS 

    Google Scholar 

  • Gavrilchuk, K. et al. Trophic niche partitioning among sympatric baleen whale species following the collapse of groundfish stocks in the Northwest Atlantic. Mar. Ecol. Prog. Ser. 497, 285–301 (2014).

    Article 

    Google Scholar 

  • Kershaw, J. L. et al. Declining reproductive success in the Gulf of St. Lawrence’s humpback whales (Megaptera novaeangliae) reflects ecosystem shifts on their feeding grounds. Glob. Change Biol. 27, 1027–1041 (2021).

    Article 
    CAS 

    Google Scholar 

  • Rode, K. D., Amstrup, S. C. & Regehr, E. V. Reduced body size and cub recruitment in polar bears associated with sea ice decline. Ecol. Appl. 20, 768–782 (2010).

    Article 

    Google Scholar 

  • Obbard, M. E. et al. Re-assessing abundance of Southern Hudson Bay polar bears by aerial survey: effects of climate change at the southern edge of the range. Arct. Sci. 4, 634–655 (2018).

    Article 

    Google Scholar 

  • Hutchings, J. A. The cod that got away. Nature 428, 899–900 (2004).

    Article 
    CAS 

    Google Scholar 

  • Zhang, F. Early warning signals of population productivity regime shifts in global fisheries. Ecol. Indic. 115, 106371 (2020).

    Article 

    Google Scholar 

  • Fulton, G. R. The Bramble Cay melomys: the first mammalian extinction due to human-induced climate change. Pac. Conserv. Biol. 23, 1–3 (2017).

    Article 

    Google Scholar 


  • Source: Ecology - nature.com

    Formation of necromass-derived soil organic carbon determined by microbial death pathways

    Mycelial nutrient transfer promotes bacterial co-metabolic organochlorine pesticide degradation in nutrient-deprived environments