Stronger El Niños reduce tropical forest arthropod diversity and function


  • Wagner, D. L. Insect declines in the Anthropocene. Annu. Rev. Entomol. 65, 457–480 (2020).

    PubMed 

    Google Scholar
     

  • Harvey, J. A. et al. Scientists’ warning on climate change and insects. Ecol. Monogr. 93, e1553 (2023).


    Google Scholar
     

  • Müller, J. et al. Weather explains the decline and rise of insect biomass over 34 years. Nature 628, 349–354 (2024).

    ADS 
    PubMed 

    Google Scholar
     

  • Stork, N. E. How many species of insects and other terrestrial arthropods are there on Earth? Annu. Rev. Entomol. 63, 31–45 (2018).

    PubMed 

    Google Scholar
     

  • Stork, N. E., Boyle, M. J. W., Wardhaugh, C. & Beaver, R. A. What can an analysis of Australian tropical rainforest bark beetles suggest about the missing millions of Earth’s insect species? Insect Conserv. Divers. 17, 1156–1166 (2024).


    Google Scholar
     

  • Ewers, R. M. et al. Logging cuts the functional importance of invertebrates in tropical rainforest. Nat. Commun. 6, 6836 (2015).

    ADS 
    PubMed 

    Google Scholar
     

  • Ashton, L. A. et al. Termites mitigate the effects of drought in tropical rainforest. Science 363, 174–177 (2019).

    ADS 
    PubMed 

    Google Scholar
     

  • van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).

    ADS 
    PubMed 

    Google Scholar
     

  • van Klink, R. et al. Disproportionate declines of formerly abundant species underlie insect loss. Nature 628, 359–364 (2024).

    ADS 
    PubMed 

    Google Scholar
     

  • Wang, B. et al. Historical change of El Niño properties sheds light on future changes of extreme El Niño. Proc. Natl Acad. Sci. USA 116, 22512–22517 (2019).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).

    ADS 

    Google Scholar
     

  • Cai, W. et al. Anthropogenic impacts on twentieth-century ENSO variability changes. Nat. Rev. Earth Environ. 4, 407–418 (2023).

    ADS 

    Google Scholar
     

  • Boyle, M. J. W. et al. Causes and consequences of insect decline in tropical forests. Nat. Rev. Biodivers. 1, 315–331 (2025).


    Google Scholar
     

  • Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809 (2017).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Seibold, S. et al. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574, 671–674 (2019).

    ADS 
    PubMed 

    Google Scholar
     

  • Saunders, M. E., Janes, J. K. & O’Hanlon, J. C. Moving on from the insect apocalypse narrative: engaging with evidence-based insect conservation. BioScience 70, 80–89 (2020).


    Google Scholar
     

  • Schowalter, T. D., Pandey, M., Presley, S. J., Willig, M. R. & Zimmerman, J. K. Arthropods are not declining but are responsive to disturbance in the Luquillo Experimental Forest, Puerto Rico. Proc. Natl Acad. Sci. USA 118, e2002556117 (2021).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Forrest, J. R. Complex responses of insect phenology to climate change. Curr. Opin. Insect Sci. 17, 49–54 (2016).

    PubMed 

    Google Scholar
     

  • Huang, B. et al. Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): upgrades, validations, and intercomparisons. J. Clim. 30, 8179–8205 (2017).

    ADS 

    Google Scholar
     

  • Yeh, S.-W. et al. ENSO atmospheric teleconnections and their response to greenhouse gas forcing. Rev. Geophys. 56, 185–206 (2018).

    ADS 

    Google Scholar
     

  • Timmermann, A. et al. El Niño–Southern Oscillation complexity. Nature 559, 535–545 (2018).

    ADS 
    PubMed 

    Google Scholar
     

  • Capotondi, A., Wittenberg, A. T., Kug, J.-S., Takahashi, K. & McPhaden, M. J. in El Niño Southern Oscillation in a Changing Climate (eds McPhaden, M. J., Santoso, A. & Cai, W.) 65–86 (American Geophysical Union, 2020).

  • Vencl, F. V. & Srygley, R. B. El Niño oscillations impact anti-predator defences to alter survival of an herbivorous beetle in a neotropical wet forest. J. Trop. Ecol. 39, e34 (2023).


    Google Scholar
     

  • França, F. M. et al. El Niño impacts on human-modified tropical forests: consequences for dung beetle diversity and associated ecological processes. Biotropica 52, 252–262 (2020).


    Google Scholar
     

  • Roubik, D. W. Ups and downs in pollinator populations: When is there a decline?. Conserv. Ecol. 5, 2 (2001).


    Google Scholar
     

  • Richardson, B. A. The bromeliad microcosm and the assessment of faunal diversity in a neotropical forest. Biotropica 31, 321–336 (1999).


    Google Scholar
     

  • Schowalter, T. D. & Ganio, L. M. Invertebrate communities in a tropical rain forest canopy in Puerto Rico following Hurricane Hugo. Ecol. Entomol. 24, 191–201 (2001).


    Google Scholar
     

  • Basset, Y. et al. Abundance, occurrence and time series: long-term monitoring of social insects in a tropical rainforest. Ecol. Indic. 150, 110243 (2023).


    Google Scholar
     

  • Wagner, D. L., Fox, R., Salcido, D. M. & Dyer, L. A. A window to the world of global insect declines: Moth biodiversity trends are complex and heterogeneous. Proc. Natl Acad. Sci. USA 118, e2002549117 (2021).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Luk, C.-L., Basset, Y., Kongnoo, P., Hau, B. C. H. & Bonebrake, T. C. Inter-annual monitoring improves diversity estimation of tropical butterfly assemblages. Biotropica 51, 519–528 (2019).


    Google Scholar
     

  • Roubik, D. W. et al. Long-term (1979–2019) dynamics of protected orchid bees in Panama. Conserv. Sci. Pract. 3, e543 (2021).


    Google Scholar
     

  • Bonebrake, T. C. et al. Warming threat compounds habitat degradation impacts on a tropical butterfly community in Vietnam. Glob. Ecol. Conserv. 8, 203–211 (2016).


    Google Scholar
     

  • Jost, L. Partitioning diversity into independent alpha and beta components. Ecology 88, 2427–2439 (2007).

    PubMed 

    Google Scholar
     

  • Sánchez González, I. et al. Niche specialization and community niche space increase with species richness in filter-feeder assemblages. Ecosphere 14, e4495 (2023).


    Google Scholar
     

  • Fox, B. J. Niche parameters and species richness. Ecology 62, 1415–1425 (1981).


    Google Scholar
     

  • Cleary, D. F. R. An examination of scale of assessment, logging and ENSO-induced fires on butterfly diversity in Borneo. Oecologia 135, 313–321 (2003).

    ADS 
    PubMed 

    Google Scholar
     

  • Detto, M., Wright, S. J., Calderón, O. & Muller-Landau, H. C. Resource acquisition and reproductive strategies of tropical forest in response to the El Niño–Southern Oscillation. Nat. Commun. 9, 913 (2018).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Petráková, L. et al. Discovery of a monophagous true predator, a specialist termite-eating spider (Araneae: Ammoxenidae). Sci. Rep. 5, 14013 (2015).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yin, Z.-W., Cai, C.-Y., Huang, D.-Y. & Li, L.-Z. Specialized adaptations for springtail predation in Mesozoic beetles. Sci. Rep. 7, 98 (2017).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Forbes, A. A., Bagley, R. K., Beer, M. A., Hippee, A. C. & Widmayer, H. A. Quantifying the unquantifiable: why Hymenoptera, not Coleoptera, is the most speciose animal order. BMC Ecol. 18, 21 (2018).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tsang, T. P. N., Ponisio, L. C. & Bonebrake, T. C. Increasing synchrony opposes stabilizing effects of species richness on terrestrial communities. Divers. Distrib. 29, 849–861 (2023).


    Google Scholar
     

  • Dell, A. I., Pawar, S. & Savage, V. M. Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy. J. Anim. Ecol. 83, 70–84 (2014).

    PubMed 

    Google Scholar
     

  • Staab, M. et al. Insect decline in forests depends on species’ traits and may be mitigated by management. Commun. Biol. 6, 338 (2023).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Prather, C. M. & Belovsky, G. E. Herbivore and detritivore effects on rainforest plant production are altered by disturbance. Ecol. Evol. 9, 7652–7659 (2019).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Coley, P. D. & Barone, J. A. Herbivory and plant defenses in tropical forests. Annu. Rev. Ecol. Systemat. 27, 305–335 (1996).


    Google Scholar
     

  • Boulton, C. A., Lenton, T. M. & Boers, N. Pronounced loss of Amazon rainforest resilience since the early 2000s. Nat. Clim. Change 12, 271–278 (2022).

    ADS 

    Google Scholar
     

  • Gómez-Zurita, J., Hunt, T., Kopliku, F. & Vogler, A. P. Recalibrated tree of leaf beetles (Chrysomelidae) indicates independent diversification of angiosperms and their insect herbivores. PLoS ONE 2, e360 (2007).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lancaster, L. T. Host use diversification during range shifts shapes global variation in Lepidopteran dietary breadth. Nat. Ecol. Evol. 4, 963–969 (2020).

    PubMed 

    Google Scholar
     

  • Forister, M. L. et al. The global distribution of diet breadth in insect herbivores. Proc. Natl Acad. Sci. USA 112, 442–447 (2015).

    ADS 
    PubMed 

    Google Scholar
     

  • Gibson, L. et al. Primary forests are irreplaceable for sustaining tropical biodiversity. Nature 478, 378–381 (2011).

    ADS 
    PubMed 

    Google Scholar
     

  • Outhwaite, C. L., McCann, P. & Newbold, T. Agriculture and climate change are reshaping insect biodiversity worldwide. Nature 605, 97–102 (2022).

    ADS 
    PubMed 

    Google Scholar
     

  • Boyle, M. J. W. et al. Tropical beetles more sensitive to impacts are less likely to be known to science. Curr. Biol. 34, R770–R771 (2024).

    PubMed 

    Google Scholar
     

  • Barlow, J. et al. The future of hyperdiverse tropical ecosystems. Nature 559, 517–526 (2018).

    ADS 
    PubMed 

    Google Scholar
     

  • Eppley, T. M. et al. Tropical field stations yield high conservation return on investment. Conserv. Lett. 60, e13007 (2024).


    Google Scholar
     

  • Dornelas, M. et al. BioTIME: a database of biodiversity time series for the Anthropocene. Glob. Ecol. Biogeogr. 27, 760–786 (2018).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chao, A. et al. Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecol. Monogr. 84, 45–67 (2014).


    Google Scholar
     

  • Olson, J. S. Energy storage and the balance of producers and decomposers in ecological systems. Ecology 44, 322–331 (1963).


    Google Scholar
     

  • van Groenigen, K. J., Osenberg, C. W. & Hungate, B. A. Increased soil emissions of potent greenhouse gases under increased atmospheric CO2. Nature 475, 214–216 (2011).

    ADS 
    PubMed 

    Google Scholar
     

  • R Core Team. R: A Language and Environment for Statistical Computing http://www.R-project.org/ (R Foundation for Statistical Computing, 2023).

  • Oksanen, J. et al. Vegan: community ecology package (2022).

  • Wood, S. N. Generalized Additive Models: An Introduction with R (Chapman and Hall/CRC, 2017).

  • Wood, S. N. Stable and efficient multiple smoothing parameter estimation for generalized additive models. J. Am. Stat. Assoc. 99, 673–686 (2004).

    MathSciNet 

    Google Scholar
     

  • Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S (Springer, 2002).

  • Bailey, P. & Emad, A. wCorr: Weighted correlations cran.r-project.org/web/packages/wCorr/index.html (2023).

  • Wickham, H. Ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).

  • Wilke, C. & Wiernik, B. ggtext: Improved text rendering support for ‘ggplot2’ cran.r-project.org/web/packages/ggtext/index.html (2022).

  • Wilke, C. cowplot: Streamlined plot theme and plot annotations for ‘ggplot2’ cran.r-project.org/web/packages/cowplot/index.html (2024).

  • Simpson, G. gratia: Graceful ggplot-based graphics and other functions for GAMs fitted using mgcv cran.r-project.org/web/packages/gratia/index.html (2024).

  • Wood, S. N. Thin plate regression splines. J. R. Stat. Soc. B 65, 95–114 (2003).

    MathSciNet 

    Google Scholar
     

  • Box G. E. P., Jenkins, G. M. & Reinsel, G. C. Time Series Analysis: Forecasting and Control (Holden-Day, 1994).

  • Jones, R. H. Longitudinal Data with Serial Correlation: A State-Space Approach (Chapman and Hall, 1993).

  • Dunn, P. K. & Smyth, G. K. Series evaluation of Tweedie exponential dispersion model densities. Stat. Comput. 15, 267–280 (2005).

    MathSciNet 

    Google Scholar
     

  • Wootton, K. L. & Stouffer, D. B. Species’ traits and food-web complexity interactively affect a food web’s response to press disturbance. Ecosphere 7, e01518 (2016).


    Google Scholar
     

  • Mally, R. et al. Historical invasion rates vary among insect trophic groups. Curr. Biol. 34, 5374–5381.e3 (2024).

    PubMed 

    Google Scholar
     

  • GBIF.Org user. Occurrence download 29229815. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.6C2QQG (2025).

  • GBIF.Org user. Occurrence download 2557474. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.R6MNY5 (2025).

  • GBIF.Org user. Occurrence download 241682722. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.5KF5NR (2025).

  • GBIF.Org user. Occurrence download 305626069. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.JPEWKC (2025).

  • GBIF.Org user. Occurrence download 66151475. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.4S7VFE (2025).

  • GBIF.Org user. Occurrence download 207807231. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.4E6SKK (2025).

  • GBIF.Org user. Occurrence download 379594148. The Global Biodiversity Information Facility https://doi.org/10.15468/DL.2TP7Y3 (2025).

  • Sharp, A. C. et al. Compiled datasets for “Stronger El Niños reduce tropical forest arthropod diversity and function” [Data set]. Zenodo https://doi.org/10.5281/zenodo.14863367 (2025).

  • Sharp, A. C. dradamsharp/Stronger-El-Ninos-reduce-tropical-forest-arthropod-diversity-and-function: analysis for ‘Stronger El Niños reduce tropical forest arthropod diversity and function’ (Release). Zenodo https://doi.org/10.5281/zenodo.15428849 (2025).



  • Source link

    More From Forest Beat

    Assessing the implications of habitat transformations on human-large carnivore interactions outside...

    Frank, B., Glikman, J. A. & Marchini, S. Human–Wildlife Interactions: Turning Conflict into Coexistence - Google Books. Cambridge University Press vol. 23 (2019).Nyhus,...
    Biodiversity
    12
    minutes

    Unlocking historical plant interactions in herbarium collections

    Davis, C. C. The herbarium of the future. Trends Ecol. Evol. 38, 412–423 (2023). ...
    Biodiversity
    24
    minutes

    Conserve marine migratory species to protect ecological links between land and...

    At the third United Nations Ocean Conference in June, UN member states committed to reducing the flow of pollutants from rivers to oceans...
    Biodiversity
    0
    minutes

    Elucidating the impact of soil’s physico-chemical properties and seasonal variation on...

    Earthworm populationA total of 347 earthworms were collected, (217 from agricultural sites and 130 from non-agricultural sites). The earthworms belonged to three ecological...
    Biodiversity
    11
    minutes
    spot_imgspot_img