Philippa Kaur

Lindgren, A., Hugelius, G. & Kuhry, P. Extensive loss of past permafrost carbon but a net accumulation into present-day soils. Nature 560, 219–222 (2018).Article 

Google Scholar 
Nichols, J. E. & Peteet, D. M. Rapid expansion of northern peatlands and doubled estimate of carbon storage. Nat. Geosci. 12, 917–921 (2019).Article 

Google Scholar 
Bridgham, S. D. et al. The carbon balance of North American wetlands. Wetlands 26, 889–916 (2006).Article 

Google Scholar 
Dixon, M. J. R. et al. Tracking global change in ecosystem area: the wetland extent trends index. Biol. Conserv. 193, 27–35 (2016).Article 

Google Scholar 
Darrah, S. E. et al. Improvements to the Wetland Extent Trends (WET) index as a tool for monitoring natural and human-made wetlands. Ecol. Indic. 99, 294–298 (2019).Article 

Google Scholar 
Asselen, S. et al. Drivers of wetland conversion: a global meta-analysis. PLoS ONE 8, e81292 (2013).Article 

Google Scholar 
Davidson, N. C. How much wetland has the world lost? Long-term and recent trends in global wetland area. Mar. Freshw. Res. 65, 934–941 (2014).Article 

Google Scholar 
Galatowitsch, S. M. in The Wetland Book II: Distribution, Description, and Conservation (eds Finlayson, C.M. et al.) 359–367 (Springer, 2018).Limpert, K. E. et al. Reducing emissions from degraded floodplain wetlands. Front. Environ. Sci. 8, 8 (2020); https://doi.org/10.3389/fenvs.2020.00008Laine, J. et al. Effect of water-level drawdown on global climatic warming: northern peatlands. AMBIO 25, 179–184 (1996).
Google Scholar 
Ise, T. et al. High sensitivity of peat decomposition to climate change through water-table feedback. Nat. Geosci. 1, 763–766 (2008).Article 

Google Scholar 
Saunois, M. et al. The global methane budget 2000–2017. Earth. Syst. Sci. Data 12, 1561–1623 (2020).Article 

Google Scholar 
Leifeld, J. et al. Intact and managed peatland soils as a source and sink of GHGs from 1850 to 2100. Nat. Clim. Change 9, 945–947 (2019).Article 

Google Scholar 
Günther, A. et al. Prompt rewetting of drained peatlands reduces climate warming despite methane emissions. Nat. Commun. 11, 1644 (2020).Article 

Google Scholar 
Hooijer, A. et al. Subsidence and carbon loss in drained tropical peatlands. Biogeoscience 9, 1053–1071 (2012).Article 

Google Scholar 
Prananto, J. A. et al. Drainage increases CO2 and N2O emissions from tropical peat soils. Glob. Change Biol. 26, 4583–4600 (2020).Article 

Google Scholar 
Jauhiainen, J. et al. Carbon dioxide and methane fluxes in drained tropical peat before and after hydrological restoration. Ecology 89, 3503–3514 (2008).Article 

Google Scholar 
Bridgham, S. D. et al. Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales. Glob. Change Biol. 19, 1325–1346 (2013).Article 

Google Scholar 
Schuldt, R. et al. Modelling Holocene carbon accumulation and methane emissions of boreal wetlands—an Earth system model approach. Biogeosciences 10, 1659–1674 (2012).Article 

Google Scholar 
McNicol, G. et al. Effects of seasonality, transport pathway, and spatial structure on greenhouse gas fluxes in a restored wetland. Glob. Change Biol. 23, 2768–2782 (2017).Article 

Google Scholar 
Yu, K. et al. Redox window with minimum global warming potential contribution from rice soils. Soil Sci. Soc. Am. J. 68, 2086–2091 (2004).Article 

Google Scholar 
Huang, Y. et al. Tradeoff of CO2 and CH4 emissions from global peatlands under water-table drawdown. Nat. Clim. Change 11, 618–622 (2021).Article 

Google Scholar 
Ojanen, P. & Minkkinen, K. Rewetting offers rapid climate benefits for tropical and agricultural peatlands but not for forestry‐drained peatlands. Glob. Biogeochem. Cycles 34, e2019GB006503 (2020).Article 

Google Scholar 
Evans, C. D. et al. Overriding water table control on managed peatland greenhouse gas emissions. Nature 593, 548–552 (2021).
Google Scholar 
Strack, M., Keith, A. M. & Xu, B. Growing season carbon dioxide and methane exchange at a restored peatland on the Western Boreal Plain. Ecol. Eng. 64, 231–239 (2014).Article 

Google Scholar 
Karki, S. et al. Carbon balance of rewetted and drained peat soils used for biomass production: a mesocosm study. Glob. Change Biol. Bioenergy 8, 969–980 (2016).Article 

Google Scholar 
Whiting, G. J. & Chanton, J. P. Greenhouse carbon balance of wetlands: methane emission versus carbon sequestration. Tellus B 53, 521–528 (2001).
Google Scholar 
Moore, T. R. et al. A multi-year record of methane flux at the Mer Bleue Bog, Southern Canada. Ecosystems 14, 646–657 (2011).Article 

Google Scholar 
Zhu, X. et al. Ammonia oxidation pathways and nitrifier denitrification are significant sources of N2O and NO under low oxygen availability. Proc. Natl Acad. Sci. USA 110, 6328–6333 (2013).Article 

Google Scholar 
Cole, J. J. et al. Plumbing the global carbon cycle: integrating inland waters into the terrestrial carbon budget. Ecosystems 10, 171–184 (2007).Article 

Google Scholar 
Holgerson, M. A. & Raymond, P. A. Large contribution to inland water CO2 and CH4 emissions from very small ponds. Nat. Geosci. 9, 222–226 (2016).Article 

Google Scholar 
Raymond, P. A. et al. Global carbon dioxide emissions from inland waters. Nature 503, 355–359 (2013).Article 

Google Scholar 
Rosentreter, J. A. et al. Half of global methane emissions come from highly variable aquatic ecosystem sources. Nat. Geosci. 14, 225–230 (2021).Article 

Google Scholar 
Lehner, B. & Döll, P. Development and validation of a global database of lakes, reservoirs and wetlands. J. Hydrol. 296, 1–22 (2004).Article 

Google Scholar 
Schuur, E. A. et al. The effect of permafrost thaw on old carbon release and net carbon exchange from tundra. Nature 459, 556–559 (2009).Article 

Google Scholar 
Delgado-Baquerizo, M. et al. Climate legacies drive global soil carbon stocks in terrestrial ecosystems. Sci. Adv. 3, e1602008 (2017).Article 

Google Scholar 
Hengl, T. et al. SoilGrids250m: global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).Article 

Google Scholar 
Walker, X. J. et al. Increasing wildfires threaten historic carbon sink of boreal forest soils. Nature 572, 520–523 (2019).Article 

Google Scholar 
Baird, A. J. et al. Validity of managing peatlands with fire. Nat. Geosci. 12, 884–885 (2019).Article 

Google Scholar 
Ritchie, H., Roser, M. & Rosado, P. CO2 and GHG Emissions: Atmospheric Concentrations (Our World in Data, 2020); https://ourworldindata.org/atmospheric-concentrations#citationFriedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).Article 

Google Scholar 
Tian, H. et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 586, 248–256 (2020).Article 

Google Scholar 
Cook-Patton, S. C. et al. Mapping carbon accumulation potential from global natural forest regrowth. Nature 585, 545–550 (2020).Article 

Google Scholar 
Jaenicke, J. et al. Planning hydrological restoration of peatlands in Indonesia to mitigate carbon dioxide emissions. Mitig. Adapt. Strateg. Glob. Change 15, 223–239 (2010).Article 

Google Scholar 
Wohl, E. Landscape-scale carbon storage associated with beaver dams. Geophys. Res. Lett. 40, 3631–3636 (2013).Article 

Google Scholar 
Law, A. et al. Using ecosystem engineers as tools in habitat restoration and rewilding: beaver and wetlands. Sci. Total Environ. 605–606, 1021–1030 (2017).Article 

Google Scholar 
Brown, L. E. et al. Macroinvertebrate community assembly in pools created during peatland restoration. Sci. Total Environ. 569, 361–372 (2016).Article 

Google Scholar 
Finlayson, C. M. & Rea, N. Reasons for the loss and degradation of Australian wetlands. Wetl. Ecol. Manage. 7, 1–11 (1999).Article 

Google Scholar 
Liu, J. et al. Water conservancy projects in China: achievements, challenges and way forward. Glob. Environ. Change 23, 633–643 (2013).Article 

Google Scholar 
Rogelj, J. et al. in Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) Ch. 2 (IPCC, WMO, 2018).Svensson, B. H. & Rosswall, T. In situ methane production from acid peat in plant communities with different moisture regimes in a subarctic mire. Oikos 43, 341–350 (1984).Article 

Google Scholar 
Waddington, J. M. & Roulet, N. T. Atmosphere–wetland carbon exchanges: scale dependency of CO2 and CH4 exchange on the developmental topography of a peatland. Glob. Biogeochem. Cycles 10, 233–245 (1996).Article 

Google Scholar 
Kling, G. W. et al. The flux of CO2 and CH4 from lakes and rivers in Arctic Alaska. Hydrobiologia 240, 23–36 (1992).Article 

Google Scholar 
Humphreys, E. R. et al. Two bogs in the Canadian Hudson Bay lowlands and a temperate bog reveal similar annual net ecosystem exchange of CO2. Arct. Antarct. Alp. Res. 46, 103–113 (2014).Article 

Google Scholar 
Caffrey, J. M. Factors controlling net ecosystem metabolism in US estuaries. Estuaries 27, 90–101 (2004).Article 

Google Scholar 
Roberts, B. J. et al. Multiple scales of temporal variability in ecosystem metabolism rates: results from 2 years of continuous monitoring in a forested headwater stream. Ecosystems 10, 588–606 (2007).Article 

Google Scholar 
Myhre, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T.F. et al.) 710–714 (Cambridge Univ. Press, 2013).Glenn, A. J. et al. Comparison of net ecosystem CO2 exchange in two peatlands in western Canada with contrasting dominant vegetation, Sphagnum and Carex. Agric. For. Meteorol. 140, 115–135 (2006).Article 

Google Scholar 
Bond-Lamberty, B. & Thomson, A. Temperature-associated increases in the global soil respiration record. Nature 464, 579–582 (2010).Article 

Google Scholar 
Zhao, J. et al. Intensified inundation shifts a freshwater wetland from a CO2 sink to a source. Glob. Change Biol. 25, 3319–3333 (2019).Article 

Google Scholar 
Peichl, M. et al. A 12-year record reveals pre-growing season temperature and water table level threshold effects on the net carbon dioxide exchange in a boreal fen. Environ. Res. Lett. 9, 55006 (2014).Article 

Google Scholar 
Peng, Z. & Peng, G. Suitability mapping of global wetland areas and validation with remotely sensed data. Sci. China Earth Sci. 57, 2883–2892 (2014).
Google Scholar 
Zhang, B. et al. Methane emissions from global wetlands: an assessment of the uncertainty associated with various wetland extent data sets. Atmos. Environ. 165, 310–321 (2017).Article 

Google Scholar 
Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Glob. Change Biol. 23, 3581–3599 (2017).Article 

Google Scholar 
ERA5 Monthly Averaged Data on Pressure Levels from 1979 to Present (ECMWF, 2020); https://doi.org/10.24381/cds.6860a573FAOSTAT Emissions Database (FAO, 2020); http://www.fao.org/faostat/en/#data/GTQiu, C. et al. Large historical carbon emissions from cultivated northern peatlands. Sci. Adv. 7, eabf1332 (2021).Article 

Google Scholar 
Frolking, S., Roulet, N. & Fuglestvedt, J. How northern peatlands influence the Earth’s radiative budget: sustained methane emission versus sustained carbon sequestration. J. Geophys. Res. Biogeosci. 111, G01008 (2006).
Google Scholar 
Neubauer, S. C. & Megonigal, J. P. Moving beyond global warming potentials to quantify the climatic role of ecosystems. Ecosystems 18, 1000–1013 (2015).Article 

Google Scholar 
Matthews, E. & Fung, I. Methane emission from natural wetlands: global distribution, area, and environmental characteristics of sources. Glob. Biogeochem. Cycles 1, 61–86 (1987).Article 

Google Scholar 
Melton, J. R. et al. Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP). Biogeosciences 10, 753–788 (2013).Article 

Google Scholar 
Papa, F. et al. Interannual variability of surface water extent at the global scale, 1993–2004. J. Geophys. Res. Atmos. 115, D12111 (2010).Article 

Google Scholar 
Junk, W. J. et al. Current state of knowledge regarding the world’s wetlands and their future under global climate change: a synthesis. Aquat. Sci. 75, 151–167 (2013).Article 

Google Scholar 
Schroeder, R. et al. Development and evaluation of a multi-year fractional surface water data set derived from active/passive microwave remote sensing data. Remote Sens. 7, 16688–16732 (2015).Article 

Google Scholar 
Vanessa, R. et al. A global assessment of inland wetland conservation status. Bioscience 6, 523–533 (2017).
Google Scholar 
Davidson, N. et al. Global extent and distribution of wetlands: trends and issues. Mar. Freshw. Res. 69, 620–627 (2018).Article 

Google Scholar 
ArcWorld 1:3 M. Continental Coverage (ESRI, 1992); http://www.oceansatlas.org/subtopic/en/c/593/Digital Chart of the World 1:1 M (ESRI, 1993); https://www.ngdc.noaa.gov/mgg/topo/report/s5/s5Avii.htmlGlobal Wetlands (UNEP-WCMC, 1993); https://www.arcgis.com/home/item.html?id=105a402642e146eaa665315279a322d1Moreno-Mateos, D. et al. Structural and functional loss in restored wetland ecosystems. PLoS Biol. 10, e1001247 (2012).Article 

Google Scholar 
Ramsar COP12 DOC.8 Report of the Secretary General to COP12 on the Implementation of the Convention (Ramsar Convention Secretariat, 2015).Page, S. E. et al. Peatlands and global change: response and resilience. Annu. Rev. Environ. Resour. 41, 35–57 (2016).Article 

Google Scholar 
Swindles, G. T. et al. Widespread drying of European peatlands in recent centuries. Nat. Geosci. 12, 922–928 (2019).Article 

Google Scholar  More

Xia, J. et al. Terrestrial carbon cycle affected by non-uniform climate warming. Nat. Geosci. 7, 173–180 (2014).CAS 
Article 

Google Scholar 
Tang, R. et al. Increasing terrestrial ecosystem carbon release in response to autumn cooling and warming. Nat. Clim. Change 12, 380–385 (2022).CAS 
Article 

Google Scholar 
Hugelius, G. et al. Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw. Proc. Natl Acad. Sci. USA 117, 20438–20446 (2020).CAS 
Article 

Google Scholar 
Gallego-Sala, A. V. et al. Latitudinal limits to the predicted increase of the peatland carbon sink with warming. Nat. Clim. Change 8, 907–913 (2018).CAS 
Article 

Google Scholar 
Treat, C. C. et al. Widespread global peatland establishment and persistence over the last 130,000 y. Proc. Natl Acad. Sci. USA 116, 4822–4827 (2019).CAS 
Article 

Google Scholar 
Frolking, S., Roulet, N. & Fuglestvedt, J. How northern peatlands influence the Earth’s radiative budget: sustained methane emission versus sustained carbon sequestration. J. Geophys. Res. Biogeosci. 111, G01008 (2006).
Google Scholar 
Loisel, J. et al. Expert assessment of future vulnerability of the global peatland carbon sink. Nat. Clim. Change 11, 70–77 (2021).Article 

Google Scholar 
Helbig, M. et al. Direct and indirect climate change effects on carbon dioxide fluxes in a thawing boreal forest–wetland landscape. Glob. Change Biol. 23, 3231–3248 (2017).Article 

Google Scholar 
Koebsch, F. et al. Refining the role of phenology in regulating gross ecosystem productivity across European peatlands. Glob. Change Biol. 26, 876–887 (2020).Article 

Google Scholar 
Huang, Y. et al. Tradeoff of CO2 and CH4 emissions from global peatlands under water-table drawdown. Nat. Clim. Change 11, 618–622 (2021).CAS 
Article 

Google Scholar 
Evans, C. D. et al. Overriding water table control on managed peatland greenhouse gas emissions. Nature 593, 548–552 (2021).CAS 

Google Scholar 
Helfter, C. et al. Drivers of long-term variability in CO2 net ecosystem exchange in a temperate peatland. Biogeosciences 12, 1799–1811 (2015).Article 

Google Scholar 
Järveoja, J., Nilsson, M. B., Gažovič, M., Crill, P. M. & Peichl, M. Partitioning of the net CO2 exchange using an automated chamber system reveals plant phenology as key control of production and respiration fluxes in a boreal peatland. Glob. Change Biol. 24, 3436–3451 (2018).Article 

Google Scholar 
Mäkiranta, P. et al. Responses of phenology and biomass production of boreal fens to climate warming under different water-table level regimes. Glob. Change Biol. 24, 944–956 (2018).Article 

Google Scholar 
Li, Q. et al. Abiotic and biotic drivers of microbial respiration in peat and its sensitivity to temperature change. Soil Biol. Biochem. 153, 108077 (2021).CAS 
Article 

Google Scholar 
Moore, T. R. et al. Spring photosynthesis in a cool temperate bog. Glob. Change Biol. 12, 2323–2335 (2006).Article 

Google Scholar 
Korrensalo, A. et al. Species-specific temporal variation in photosynthesis as a moderator of peatland carbon sequestration. Biogeosciences 14, 257–269 (2017).CAS 
Article 

Google Scholar 
Weltzin, J. F. et al. Response of bog and fen plant communities to warming and water-table manipulations. Ecology 81, 3464–3478 (2000).Article 

Google Scholar 
Dimitrov, D. D., Grant, R. F., Lafleur, P. M. & Humphreys, E. R. Modeling the effects of hydrology on gross primary productivity and net ecosystem productivity at Mer Bleue bog. J. Geophys. Res. Biogeosci. 116, G04010 (2011).Article 
CAS 

Google Scholar 
Bubier, J., Crill, P., Mosedale, A., Frolking, S. & Linder, E. Peatland responses to varying interannual moisture conditions as measured by automatic CO2 chambers. Glob. Biogeochem. Cycles 17, 1066 (2003).Article 
CAS 

Google Scholar 
Moore, T. R. & Knowles, R. The influence of water table levels on methane and carbon dioxide emissions from peatland soils. Can. J. Soil Sci. 69, 33–38 (1989).CAS 
Article 

Google Scholar 
Nichols, D. S. Temperature of upland and peatland soils in a north central Minnesota forest. Can. J. Soil Sci. 78, 493–509 (1998).Article 

Google Scholar 
Bellisario, L. M., Moore, T. R. & Bubier, J. L. Net ecosystem CO2 exchange in a boreal peatland, northern Manitoba. Écoscience 5, 534–541 (1998).Article 

Google Scholar 
Yu, Z. et al. Peatlands and their role in the global carbon cycle. Eos 92, 97–98 (2011).Article 

Google Scholar 
Hanson, P. J. et al. Rapid net carbon loss from a whole-ecosystem warmed peatland. AGU Adv. 1, e2020AV000163 (2020).Article 

Google Scholar 
Vincent, L. A. et al. Observed trends in Canada’s climate and influence of low-frequency variability modes. J. Clim. 28, 4545–4560 (2015).Article 

Google Scholar 
Templer, P. H. et al. Climate Change Across Seasons Experiment (CCASE): a new method for simulating future climate in seasonally snow-covered ecosystems. PLoS ONE 12, e0171928 (2017).Article 
CAS 

Google Scholar 
Peichl, M. et al. A 12-year record reveals pre-growing season temperature and water table level threshold effects on the net carbon dioxide exchange in a boreal fen. Environ. Res. Lett. 9, 055006 (2014).Article 

Google Scholar 
Helbig, M., Humphreys, E. R. & Todd, A. Contrasting temperature sensitivity of CO2 exchange in peatlands of the Hudson Bay Lowlands, Canada. J. Geophys. Res. Biogeosci. 124, 2126–2143 (2019).CAS 
Article 

Google Scholar 
Griffis, T. J., Rouse, W. R. & Waddington, J. M. Interannual variability of net ecosystem CO2 exchange at a subarctic fen. Glob. Biogeochem. Cycles 14, 1109–1121 (2000).CAS 
Article 

Google Scholar 
Bubier, J. L., Crill, P. M., Moore, T. R., Savage, K. & Varner, R. K. Seasonal patterns and controls on net ecosystem CO2 exchange in a boreal peatland complex. Glob. Biogeochem. Cycles 12, 703–714 (1998).CAS 
Article 

Google Scholar 
Park, S.-B. et al. Temperature control of spring CO2 fluxes at a coniferous forest and a peat bog in Central Siberia. Atmosphere 12, 984 (2021).CAS 
Article 

Google Scholar 
Adkinson, A. C., Syed, K. H. & Flanagan, L. B. Contrasting responses of growing season ecosystem CO2 exchange to variation in temperature and water table depth in two peatlands in northern Alberta, Canada. J. Geophys. Res. Biogeosci. 116, G01004 (2011).Article 
CAS 

Google Scholar 
Heiskanen, L. et al. Carbon dioxide and methane exchange of a patterned subarctic fen during two contrasting growing seasons. Biogeosciences 18, 873–896 (2021).CAS 
Article 

Google Scholar 
Lafleur, P. M., Roulet, N. T., Bubier, J. L., Frolking, S. & Moore, T. R. Interannual variability in the peatland-atmosphere carbon dioxide exchange at an ombrotrophic bog. Glob. Biogeochem. Cycles 17, 1036 (2003).Article 
CAS 

Google Scholar 
Joiner, D. W., Lafleur, P. M., McCaughey, J. H. & Bartlett, P. A. Interannual variability in carbon dioxide exchanges at a boreal wetland in the BOREAS northern study area. J. Geophys. Res. Atmos. 104, 27663–27672 (1999).CAS 
Article 

Google Scholar 
McVeigh, P., Sottocornola, M., Foley, N., Leahy, P. & Kiely, G. Meteorological and functional response partitioning to explain interannual variability of CO2 exchange at an Irish Atlantic blanket bog. Agric. For. Meteorol. 194, 8–19 (2014).Article 

Google Scholar 
Helbig, M. et al. Increasing contribution of peatlands to boreal evapotranspiration in a warming climate. Nat. Clim. Change 10, 555–560 (2020).CAS 
Article 

Google Scholar 
Bourgault, M.-A., Larocque, M. & Garneau, M. How do hydrogeological setting and meteorological conditions influence water table depth and fluctuations in ombrotrophic peatlands? J. Hydrol. X 4, 100032 (2019).Article 

Google Scholar 
Yurova, A., Wolf, A., Sagerfors, J. & Nilsson, M. Variations in net ecosystem exchange of carbon dioxide in a boreal mire: modeling mechanisms linked to water table position. J. Geophys. Res. Biogeosci. 112, G02025 (2007).Article 
CAS 

Google Scholar 
Laine, A. M. et al. Warming impacts on boreal fen CO2 exchange under wet and dry conditions. Glob. Change Biol. 25, 1995–2008 (2019).Article 

Google Scholar 
Chivers, M. R., Turetsky, M. R., Waddington, J. M., Harden, J. W. & McGuire, A. D. Effects of experimental water table and temperature manipulations on ecosystem CO2 fluxes in an Alaskan rich fen. Ecosystems 12, 1329–1342 (2009).CAS 
Article 

Google Scholar 
Juszczak, R. et al. Ecosystem respiration in a heterogeneous temperate peatland and its sensitivity to peat temperature and water table depth. Plant Soil 366, 505–520 (2013).CAS 
Article 

Google Scholar 
Hao, D. et al. Estimating hourly land surface downward shortwave and photosynthetically active radiation from DSCOVR/EPIC observations. Remote Sens. Environ. 232, 111320 (2019).Article 

Google Scholar 
O’Donnell, J. A., Romanovsky, V. E., Harden, J. W. & McGuire, A. D. The effect of moisture content on the thermal conductivity of moss and organic soil horizons from black spruce ecosystems in interior Alaska. Soil Sci. 174, 646–651 (2009).Article 
CAS 

Google Scholar 
Nijp, J. J. et al. Rain events decrease boreal peatland net CO2 uptake through reduced light availability. Glob. Change Biol. 21, 2309–2320 (2015).Article 

Google Scholar 
Zhang, Y., Commane, R., Zhou, S., Williams, A. P. & Gentine, P. Light limitation regulates the response of autumn terrestrial carbon uptake to warming. Nat. Clim. Change 10, 739–743 (2020).CAS 
Article 

Google Scholar 
Samson, M. et al. The impact of experimental temperature and water level manipulation on carbon dioxide release in a poor fen in northern Poland. Wetlands 38, 551–563 (2018).Article 

Google Scholar 
Drever, C. R. et al. Natural climate solutions for Canada. Sci. Adv. 7, eabd6034 (2021).CAS 
Article 

Google Scholar 
Hemes, K. S., Runkle, B. R. K., Novick, K. A., Baldocchi, D. D. & Field, C. B. An ecosystem-scale flux measurement strategy to assess natural climate solutions. Environ. Sci. Technol. 55, 3494–3504 (2021).CAS 
Article 

Google Scholar 
Walker, T. W. N. et al. A systemic overreaction to years versus decades of warming in a subarctic grassland ecosystem. Nat. Ecol. Evol. 4, 101–108 (2020).Article 

Google Scholar 
Xu, B. et al. Seasonal variability of forest sensitivity to heat and drought stresses: a synthesis based on carbon fluxes from North American forest ecosystems. Glob. Change Biol. 26, 901–918 (2020).Article 

Google Scholar 
Piao, S. et al. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451, 49–52 (2008).CAS 
Article 

Google Scholar 
Joyce, P. et al. How robust Is the apparent break-down of northern high-latitude temperature control on spring carbon uptake? Geophys. Res. Lett. 48, e2020GL091601 (2021).Article 

Google Scholar 
Grant, R. F. et al. Changes in net ecosystem productivity of boreal black spruce stands in response to changes in temperature at diurnal and seasonal time scales. Tree Physiol. 29, 1–17 (2009).CAS 
Article 

Google Scholar 
Kwon, M. J. et al. Siberian 2020 heatwave increased spring CO2 uptake but not annual CO2 uptake. Environ. Res. Lett. 16, 124030 (2021).CAS 
Article 

Google Scholar 
Yu, Z., Griffis, T. J. & Baker, J. M. Warming temperatures lead to reduced summer carbon sequestration in the U.S. Corn Belt. Commun. Earth Environ. 2, 53 (2021).Article 

Google Scholar 
Wang, S. et al. Warmer spring alleviated the impacts of 2018 European summer heatwave and drought on vegetation photosynthesis. Agric. For. Meteorol. 295, 108195 (2020).Article 

Google Scholar 
Wang, T. et al. Emerging negative impact of warming on summer carbon uptake in northern ecosystems. Nat. Commun. 9, 5391 (2018).CAS 
Article 

Google Scholar 
Lin, X. et al. Siberian and temperate ecosystems shape Northern Hemisphere atmospheric CO2 seasonal amplification. Proc. Natl Acad. Sci. USA 117, 21079–21087 (2020).CAS 
Article 

Google Scholar 
Helbig, M. et al. Warming response of peatland CO2 sink is sensitive to seasonality in warming trends. Zenodo https://doi.org/10.5281/zenodo.6685222 (2022).Didan, K. MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250 m SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC (2015); https://doi.org/10.5067/MODIS/MOD13Q1.006Harris, 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 
Lees, K. J. et al. Using spectral indices to estimate water content and GPP in Sphagnum moss and other peatland vegetation. IEEE Trans. Geosci. Remote Sens. 58, 4547–4557 (2020).Article 

Google Scholar 
Bennett, A. C., McDowell, N. G., Allen, C. D. & Anderson-Teixeira, K. J. Larger trees suffer most during drought in forests worldwide. Nat. Plants 1, 15139 (2015).Article 

Google Scholar 
Page, S. E. & Baird, A. J. Peatlands and global change: response and resilience. Annu. Rev. Environ. Resour. 41, 35–57 (2016).Article 

Google Scholar 
Juottonen, H. et al. Integrating decomposers, methane-cycling microbes and ecosystem carbon fluxes along a peatland successional gradient in a land uplift region. Ecosystems https://doi.org/10.1007/s10021-021-00713-w (2021). More

Rotational velocityFigure 3 shows the effect of flow rate, nozzle diameter and number of nozzles on the rotational velocity of water in a circular tank. The results indicate that the rotational velocity increases with increasing flow rates and deceasing nozzle diameter. It could be seen that, the rotational velocity decreased from 10.1 to 5.0 cm s−1, when the nozzle diameter increased from 10 to 20 mm, respectively for 5 nozzles used, and it decreased from 5.1 to 4.0 cm s−1, when the nozzle diameter increased from 10 to 15 mm, respectively, for 10 nozzles used with 5 m3 h−1 flow rate. At 15 m3 h−1, the rotational velocity was decreased from 23.5 to 17.5, 12.0 to 7.5, 10.0 to 6.9, 7.6 to 4.7 and 5.9 to 4.0 cm s−1 when the nozzle diameter increased from 10 to 20 mm, respectively, for 5, 10, 15, 20 and 25 nozzles, respectively. The results also indicate that when the nozzle diameter increased from 20 to 25 mm, the rotational velocity decreased from 19.0 to 16.5, 12.0 to 10.0 and 7.1 to 5.5 cm s−1 for 3, 6 and 9 nozzles, respectively, with 15 m3 h−1 flow rate.Figure 3Effect of flow rate, nozzle diameter and number of nozzles on the rotational velocity of water in a circular tank.Full size imageAt 30 m3 h−1 flow rate, the highest value of the rotational velocity was 33.5 cm s−1 was found for 5 nozzles and 10 mm nozzle diameter. While, the lowest value of the rotational velocity was 7.3 cm s−1 was found for 25 nozzles and 25 mm nozzle diameter. At 45 m3 h−1 flow rate, the rotational velocity ranged from 11.0 to 49.9 cm s−1 for all treatments under study.At 60 m3 h−1 flow rate, the rotational velocity deceased from 61.0 to 50.1, 47.7 to 34.0, 36.3 to 23.0, 23.5 to 17.5, 21.0 to 15.0 and 17.0 to 11.5 cm s−1 when the nozzle diameter increased from 10 to 20 mm, respectively at 5, 10, 15, 20, 25 and 30 number of nozzles. The results also indicate that, when the nozzle diameter increased from 20 to 25 mm, the rotational velocity decreased from 56.0 to 47.0, 43.0 to 33.0, 27.0 to 22.0 and 19.0 to 16.5 cm s−1 at 3, 6, 9 and 12 nozzles, respectively.At 75 m3 h−1 flow rate, the rotational velocity deceased from 60.9 to 49.1, 48.4 to 38.0, 39.0 to 30, 31.8 to 23.0, 23.5 to 17.5 and 22.0 to 15.0 cm s−1 when the nozzle diameter increased from 10 to 20 mm, respectively for 5, 10, 15, 20, 25 and 30 nozzles, respectively. The results also indicate that, when the nozzle diameter increased from 20 to 25 mm, the rotational velocity decreased from 50.48 to 43.0 to 38.5, 33.0 to 27.5 and 23.5 to 22.0 cm s−1 for 3, 6, 9 and 12 nozzles, respectively.The results also indicate that the highest values of the rotational velocities were 10.1, 23.5, 33.5, 49.9, 60.9 and 61.0 cm s−1 were found for 5 nozzles and 10 mm nozzle diameter at 5, 15, 30, 45, 60 and 75 m3 h−1 flow rate, respectively. While, the lowest values of the rotational velocities were 4.0, 7.5 and 11.5 cm s−1 for 25 nozzles and 15 mm nozzle diameter at 5, 15 and 30 m3 h−1 flow rate, respectively. They were 11.5 and 15 cm s−1 were found for 30 nozzles and 15 mm nozzle diameter at 60 and 75 m3 h−1 flow rate, respectively. The velocity of water obtained seemed to be in the recommended range of safe and proper velocity for fish according to12. Due to it is effective compromise to allow heavy solids settle rapidly, yet sufficiently fast to create “good” hydraulics. Timmons and Youngs18 mentioned that the water velocity needed to maintain self-cleaning properties ranges from 3 to 40 cm s−1 varying greatly according to the physical properties of the biosolids. When fish swims at lower speed than its optimal, a large amount of energy will be used for higher spontaneous activity such as aggression. In contrast, when fish swim at higher speed than optimal, they become stressful, unstable, increase lactate production and fatigue6.Multiple regression analysis was carried out to obtain a relationship between the rotational velocity of water as dependent variable and different both of flow rate and nozzle diameter as independent variables. The best fit for this relationship with coefficient of determination of 0.95 and an error of 1.06% is in the following form:-$$ RV = 6.97 + 0.41Q – 0.19Dquad {text{R}}^{{2}} = 0.95 $$
(3)
where RV is the rotational velocity of water, cm s−1, Q is the water flow rate, m3 h−1, D is the nozzle diameter, mm.This equation could be applied in the range of 5 to 75 m3 h−1 water flow rate and from 10 to 25 mm of nozzle diameter.Impulse force of waterFigure 4 shows the effect of flow rate, diameter and number of nozzles on the impulse force of water in a circular tank. The results indicate that the impulse force of water increases with increasing flow rates and deceasing nozzle diameter and number of nozzles. It could be seen that, the impulse force of water decreased from 5.1 to 1.7 N, when the number of nozzles increased from 5 to 15, respectively at 10 nozzle diameter, and it decreased from 2.3 to 1.2 N, when the number of nozzles increased from 5 to 10, respectively, at 15 diameter nozzle with 5 m3 h−1 flow rate. At 15 m3 h−1, the impulse force of water was decreased from 84.7 to 9.4 N when the number of nozzles increased from 5 to 30, respectively 10 mm diameter nozzle. The results also indicate that when the number of nozzles increased from 5 to 25, the impulse force of water decreased from 14.8 to 1.4 N at 15 mm nozzle diameter, respectively, and it decreased from 9.5 to 1.9 and 5.3 to 1.3 N at 20 and 25 mm, respectively, when the number of nozzles increased from 3 to 9.Figure 4Effect of flow rate, nozzle diameter and number of nozzles on the impulse force of water in a circular tank.Full size imageAt 30 m3 h−1 flow rate, the impulse force of water deceased from 84.7 to 46.9, 56.9 to 14.8, 28.5 to 5.3, 14.9 to 3.0 and 11.8 to 2.2 N when the nozzle diameter increased from 10 to 15 mm, respectively at 5, 10, 15, 20 and 25 nozzles. The results also indicate that, when the nozzle diameter increased from 20 to 25 mm, the impulse force of water decreased from 21.4 to 14.9, 14.8 to 5.4, 5.3 to 2.2 and 2.3 to 1.9 N for 3, 6, 9 and 12 nozzles, respectively.At 45 m3 h−1 flow rate, the impulse force of water was ranged from 2.1 to 111.2 N for all treatments under this study. Also, at 60 m3 h−1 flow rate, the impulse force of water ranged from 5.1 to 151.3 N for all treatments under this study. At 75 m3 h−1 flow rate, the highest value of the impulse force of water 211.2 N was found for 5 numbers of nozzles and 10 mm nozzle diameter, respectively. While, the lowest value of the impulse force of water was 9.1 N was found for 12 nozzles and 25 mm nozzle diameter, respectively.The results also indicate that the highest value of the impulse force of water 211.2 N was found for 5 nozzles and 10 mm nozzle diameter at 75 m3 h−1 flow rate, respectively. While, the lowest value of the impulse force of water was 1.2 N was found for 10 nozzles and 15 mm nozzle diameter at 5 m3 h−1 flow rate, respectively.The results indicated that, the relationship between the rotational velocity and impulse force of water is linear relationship at the same treatments. When the rotational velocity increased from 10.7 to 37.6, 8.1 to 28.8, 10.2 to 36.0 and 11.0 to 31.9 cm s−1, the impulse force of water increased from 3.1 to 106.6, 1.8 to 31.1, 1.3 to 32.5 and 1.4 to 22.8 N, respectively, at the same treatments. The trend of these results agreed with those obtained by19.Multiple regression analysis was carried out to obtain a relationship between the impulse force of water as dependent variable and different both of flow rate and nozzle diameter as independent variables. The best fit for this relationship with coefficient of determination of 0.88 and an error of 2.13% is in the following form:-$$ F_{i} = 38.18 + 0.67Q – 2.35Dquad {text{R}}^{{2}} = 0.88 $$
(4)
This equation could be applied in the range of 5 to 75 m3 h−1 water flow rate and from 10 to 25 mm of nozzle diameter.Average velocity of waterFigure 5 shows the effect of flow rate, diameter and number of nozzles on the average velocity of water in a circular tank. The results indicate that the average velocity of water increases with increasing flow rates and deceasing nozzle diameter and number of nozzles. It could be seen that, the average velocity of water decreased from 3.32 to 1.59 cm s−1, when the number of nozzles increased from 5 to 15, respectively at 10 nozzle diameter, and it decreased from 1.13 to 1.07 cm s−1, when the number of nozzles increased from 5 to 10, respectively, at 15 diameter nozzle with 5 m3 h−1 flow rate. At 15 m3 h−1, the average velocity of water was decreased from 12.03 to 4.33 cm s−1 when the number of nozzles increased from 5 to 30, respectively 10 mm diameter nozzle. The results also indicate that when the number of nozzles increased from 5 to 25, the average velocity of water decreased from 6.93 to 2.89 cm s−1 at 15 mm nozzle diameter, respectively, and it decreased from 7.55 to 4.00 and 4.89 to 2.95 cm s−1 at 20 and 25 mm, respectively, when the number of nozzles increased from 3 to 9.Figure 5Effect of flow rate, nozzle diameter and number of nozzles on the average velocity of water in a circular tank.Full size imageAt 30 m3 h−1 flow rate, the highest value of the average velocity of water 18.51 cm s−1 was found for 5 nozzles and 10 mm nozzle diameter. While, the lowest value of the average velocity of water was 4.65 cm s−1 was found for 12 nozzles and 25 mm nozzle diameter. At 45 m3 h−1 flow rate, the average velocity of water ranged from 6.66 to 23.26 for all treatments under study, also, at 60 m3 h−1 flow rate, the average velocity of water ranged from 9.23 to 34.82 for all treatments under study. At 75 m3 h−1 flow rate, the average velocity of water ranged from 10.00 to 48.76 for all treatment of this study.The results also indicate that the highest value of the average velocity of water 48.76 cm s−1 was found for 5 nozzles and 10 mm nozzle diameter at 75 m3 h−1 flow rate, respectively. While, the lowest value of the average velocity of water was 1.07 cm s−1 was found for 10 nozzles and 15 mm nozzle diameter at 5 m3 h−1 flow rate, respectively. These results agreed with those obtained by18,20. Fish distribution in the circular tank is influenced by the heterogeneity of water velocity in the area between inlet flow and the center of the tank9. Fish distribution in the circular tank is mostly concentrated in the area between high and low velocity area. The high velocity area will be avoided by most fishes as it requires high swimming energy, while dead volumes (low velocity area) are unfavorable condition for fish (low DO and higher metabolites accumulation)21.Multiple regression analysis was carried out to obtain a relationship between the average velocity of water as dependent variable and different both of flow rate and nozzle diameter as independent variables. The best fit for this relationship with coefficient of determination of 0.91 and an error of 1.48% is in the following form:$$ V_{avg} = 6.53 + 0.26Q – 0.37Dquad {text{R}}^{{2}} = 0.91 $$
(5)
This equation could be applied in the range of 5 to 75 m3 h−1 water flow rate and from 10 to 25 mm of nozzle diameter. More

MacLachlan, N. J. & Guthrie, A. J. Re-emergence of bluetongue, African horse sickness, and other Orbivirus diseases. Vet. Res. https://doi.org/10.1051/vetres/2010007 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Koenraadt, C. J. M. et al. Bluetongue, Schmallenberg—What is next? Culicoides-borne viral diseases in the 21st Century. BMC Res. Notes 10, 77 (2014).
Google Scholar 
Dennis, S. J., Meyers, A. E., Hitzeroth, I. I. & Rybicki, E. P. African horse sickness: A review of current understanding and vaccine development in the. Viruses 11, 844 (2019).CAS 
PubMed Central 
Article 

Google Scholar 
Collins, Á. B., Doherty, M. L., Barrett, D. J. & Mee, J. F. Schmallenberg virus: A systematic international literature review (2011–2019) from an Irish perspective. Ir. Vet. J. 72, 1–22 (2019).Article 

Google Scholar 
Tkuwet, G. & Firesbhat, A. A review on African horse sickness. Eur. J. Appl. Sci. 7, 213–219 (2015).CAS 

Google Scholar 
Mellor, P. S. & Hamblin, C. African horse sickness. Vet. Res. 35, 445–466 (2004).PubMed 
Article 

Google Scholar 
Coetzee, P., Stokstad, M., Venter, E. H., Myrmel, M. & Van Vuuren, M. Bluetongue: A historical and epidemiological perspective with the emphasis on South Africa. Virol. J. 9, 198 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Cagienard, A., Griot, C., Mellor, P. S., Denison, E. & Stärk, K. D. Bluetongue vector species of Culicoides in Switzerland. Med. Vet. Entomol. 20, 239–247 (2006).CAS 
PubMed 
Article 

Google Scholar 
Oluwayelu, D., Adebiyi, A. & Tomori, O. Endemic and emerging arboviral diseases of livestock in Nigeria: A review. Parasit. Vectors 11, 1–12 (2018).Article 

Google Scholar 
Sibhat, B., Ayelet, G., Gebremedhin, E. Z., Skjerve, E. & Asmare, K. Seroprevalence of Schmallenberg virus in dairy cattle in Ethiopia. Acta Trop. 178, 61–67 (2018).PubMed 
Article 

Google Scholar 
Aklilu, N. et al. African horse sickness outbreaks caused by multiple virus types in Ethiopia. Transbound. Emerg. Dis. 61, 185–192 (2014).CAS 
PubMed 
Article 

Google Scholar 
Rojas, J. M., Rodríguez-Martín, D., Martín, V. & Sevilla, N. Diagnosing bluetongue virus in domestic ruminants: Current perspectives. Vet. Med. Res. Rep. 10, 17 (2019).
Google Scholar 
Gizaw, D., Sibhat, D., Ayalew, B. & Sehal, M. Sero-prevalence study of bluetongue infection in sheep and goats in selected areas of Ethiopia. Ethiop. Vet. J. 20, 105 (2016).Article 

Google Scholar 
Abera, T. et al. Bluetongue disease in small ruminants in south western Ethiopia: Cross-sectional sero-epidemiological study. BMC Res. Notes 11, 112 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Mellor, P. S., Boorman, J. & Baylis, M. Culicoides biting midges: Their role as arbovirus vectors. Annu. Rev. Entomol. 45, 307–340 (2000).CAS 
PubMed 
Article 

Google Scholar 
Carpenter, S., Groschup, M. H., Garros, C., Felippe-Bauer, M. L. & Purse, B. V. Culicoides biting midges, arboviruses and public health in Europe. Antivir. Res. 100, 102–113 (2013).CAS 
PubMed 
Article 

Google Scholar 
Sick, F., Beer, M., Kampen, H. & Wernike, K. Culicoides biting midges—Underestimated vectors for arboviruses of public health and veterinary importance. Viruses 11, 376 (2019).CAS 
PubMed Central 
Article 

Google Scholar 
Blanda, V. et al. Geo-statistical analysis of Culicoides spp. distribution and abundance in Sicily, Italy. Parasit. Vectors 11, 78 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Vasić, A. et al. Species diversity, host preference and arbovirus detection of Culicoides (Diptera: Ceratopogonidae) in south-eastern Serbia. Parasit. Vectors 12, 1–9 (2019).Article 

Google Scholar 
Martin, E. et al. Culicoides species community composition and infection status with parasites in an urban environment of east central Texas, USA. Parasit. Vectors 12, 1–10 (2019).Article 

Google Scholar 
Gusmão, G. M. C., Brito, G. A., Moraes, L. S., Bandeira, M. D. C. A. & Rebêlo, J. M. M. Temporal variation in species abundance and richness of Culicoides (Diptera: Ceratopogonidae) in a tropical equatorial area. J. Med. Entomol. https://doi.org/10.1093/jme/tjz015 (2019).Article 
PubMed 

Google Scholar 
Sghaier, S. et al. New species of the genus Culicoides (Diptera Ceratopogonidae) for Tunisia, with detection of Bluetongue viruses in vectors. Vet. Ital. 53, 357–366 (2017).PubMed 

Google Scholar 
Gordon, S. J. G. et al. The occurrence of Culicoides species, the vectors of arboviruses, at selected trap sites in Zimbabwe. Onderstepoort J. Vet. Res. 82, e1–e8 (2015).PubMed 
Article 
CAS 

Google Scholar 
Villard, P. et al. Modeling Culicoides abundance in mainland France: Implications for surveillance. Parasit. Vectors 12, 1–10 (2019).Article 

Google Scholar 
Diarra, M. et al. Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal. Parasit. Vectors 11, 341 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Calvete, C. et al. Spatial distribution of Culicoides imicola, the main vector of bluetongue virus, Spain. Vet. Rec. 158, 130–131 (2006).CAS 
PubMed 
Article 

Google Scholar 
Purse, B. V. et al. Modelling the distributions of Culicoides bluetongue virus vectors in Sicily in relation to satellite-derived climate variables. Med. Vet. Entomol. 18, 90–101 (2004).CAS 
PubMed 
Article 

Google Scholar 
Purse, B. V. et al. Spatial and temporal distribution of bluetongue and its Culicoides vectors in Bulgaria. Med. Vet. Entomol. 20, 335–344 (2006).CAS 
PubMed 
Article 

Google Scholar 
Leta, S. et al. Modeling the global distribution of Culicoides imicola: An ensemble approach. Sci. Rep. 9, 1–9 (2019).ADS 
CAS 
Article 

Google Scholar 
Mulatu, T. & Hailu, A. The occurrence and identification of Culicoides species in the Western Ethiopia. Acad. J. Entomol. 12, 40–43 (2019).
Google Scholar 
Khamala, C. P. M. & Kettle, D. S. The Culicoides Latreille (Diptera: Ceratopogonidae) of East Africa. Trans. R. Entomol. Soc. Lond. 123, 1–95 (1971).Article 

Google Scholar 
Venter, G. J. Specie di Culicoides (Diptera: Ceratopogonidae) vettori del virus della Bluetongue in Sud Africa. Vet. Ital. 51, 325–333 (2015).PubMed 

Google Scholar 
Mathieu, B. et al. Development and validation of IIKC: An interactive identification key for Culicoides (Diptera: Ceratopogonidae) females from the Western Palaearctic region. Parasit. Vectors 5, 137 (2012).PubMed 
PubMed Central 
Article 

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

Google Scholar 
Baylis, M., Bouayoune, H., Touti, J. & El Hasnaoui, H. Use of climatic data and satellite imagery to model the abundance of Culicoides imicola, the vector of African horse sickness virus, in Morocco. Med. Vet. Entomol. 12, 255–266 (1998).CAS 
PubMed 
Article 

Google Scholar 
Diarra, M. et al. Modelling the abundances of two major culicoides (Diptera: Ceratopogonidae) species in the Niayes area of Senegal. PLoS One 10, e0131021 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ramilo, D. W., Nunes, T., Madeira, S., Boinas, F. & da Fonseca, I. P. Geographical distribution of Culicoides (DIPTERA: CERATOPOGONIDAE) in mainland Portugal: Presence/absence modelling of vector and potential vector species. PLoS One 12, e0180606 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ben Rais Lasram, F. et al. The Mediterranean Sea as a ‘cul-de-sac’ for endemic fishes facing climate change. Glob. Chang. Biol. 16, 3233–3245 (2010).ADS 
Article 

Google Scholar 
Tiffin, P. & Ross-Ibarra, J. Goal-oriented evaluation of species distribution models accuracy and precision: True Skill Statistic profile and uncertainty maps. PeerJ PrePints https://doi.org/10.7287/peerj.preprints.488v1 (2014).Article 

Google Scholar 
Graham, M. H. Confronting multicollinearity in ecological multiple regression. Ecology 84, 2809–2815 (2003).Article 

Google Scholar 
Demissie, G. H. Seroepidemiological study of African horse sickness in southern Ethiopia. Open Sci. Repos. Vet. Med. 10, e70081919 (2013).
Google Scholar 
Zeleke, A., Sori, T., Powel, K., Gebre-Ab, F. & Endebu, B. Isolation and identification of circulating serotypes of African horse sickness virus in Ethiopia. J. Appl. Res. Vet. Med. 3, 40–43 (2005).
Google Scholar 
Ayelet, G. et al. Outbreak investigation and molecular characterization of African horse sickness virus circulating in selected areas of Ethiopia. Acta Trop. 127, 91–96 (2013).PubMed 
Article 

Google Scholar 
Gulima, D. Seroepidemiological study of bluetongue in indigenous sheep in selected districts of Amhara National Regional State, north western Ethiopia. Ethiop. Vet. J. 13, 1–15 (2009).
Google Scholar 
Borkent, A. & Dominiak, P. Catalog of the biting midges of the world (Diptera: Ceratopogonidae). Zootaxa 4787, 1–377 (2020).Article 

Google Scholar 
Borkent, A. & Wirth, W. W. World species of biting midges (Diptera: Ceratopogonidae). Bull. Am. Museum Nat. Hist. 233, 5–195 (1997).
Google Scholar 
Guichard, S. et al. Worldwide niche and future potential distribution of Culicoides imicola, a major vector of bluetongue and African horse sickness viruses. PLoS One 9, e112491 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Becker, E. E. E., Venter, G. J., Labuschagne, K., Greyling, T. & van Hamburg, H. Occurrence of Culicoides species Diptera: Ceratopogonidae) in the Khomas region of Namibia during the winter months. Vet. Ital. 48, 45–54 (2012).PubMed 

Google Scholar 
Capela, R. et al. Spatial distribution of Culicoides species in Portugal in relation to the transmission of African horse sickness and bluetongue viruses. Med. Vet. Entomol. 17, 165–177 (2003).CAS 
PubMed 
Article 

Google Scholar 
Calvete, C. et al. Modelling the distributions and spatial coincidence of bluetongue vectors Culicoides imicola and the Culicoides obsoletus group throughout the Iberian peninsula. Med. Vet. Entomol. 22, 124–134 (2008).CAS 
PubMed 
Article 

Google Scholar 
Riddin, M. A., Venter, G. J., Labuschagne, K. & Villet, M. H. Culicoides species as potential vectors of African horse sickness virus in the southern regions of South Africa. Med. Vet. Entomol. 33, 498–511 (2019).CAS 
PubMed 
Article 

Google Scholar 
Foxi, C. et al. Role of different Culicoides vectors (Diptera: Ceratopogonidae) in bluetongue virus transmission and overwintering in Sardinia (Italy). Parasit. Vectors 9, 440 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Musuka, G. N., Mellor, P. S., Meiswinkel, R., Baylis, M. & Kelly, P. J. Prevalence of Culicoides imicola and other species (Diptera: Ceratopogonidae) ateight sites in Zimbabwe: To the editor. J. S. Afr. Vet. Assoc. 72, 62–63 (2001).CAS 
PubMed 
Article 

Google Scholar 
Meiswinkel, R. The 1996 outbreak of African horse sickness in South Africa—the entomological perspective. Arch. Virol. Suppl. 14, 69–83 (1998).CAS 
PubMed 

Google Scholar 
Jean Pierre, T. et al. Characteristics, classification and genesis of vertisols under seasonally contrasted climate in the Lake Chad Basin, Central Africa. J. Afr. Earth Sci. 150, 176–193 (2019).ADS 
CAS 
Article 

Google Scholar 
Elias, E. Characteristics of Nitisol profiles as affected by land use type and slope class in some Ethiopian highlands. Environ. Syst. Res. 6, 1–15 (2017).Article 

Google Scholar 
Nachtergaele, F. The classification of leptosols in the world reference base for soil resources.Veronesi, E., Venter, G. J., Labuschagne, K., Mellor, P. S. & Carpenter, S. Life-history parameters of Culicoides (Avaritia) imicola Kieffer in the laboratory at different rearing temperatures. Vet. Parasitol. 163, 370–373 (2009).CAS 
PubMed 
Article 

Google Scholar 
Verhoef, F. A. A., Venter, G. J. & Weldon, C. W. Thermal limits of two biting midges, Culicoides imicola Kieffer and C. bolitinos Meiswinkel (Diptera: Ceratopogonidae). Parasites Vectors 7, 384 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Conte, A., Goffredo, M., Ippoliti, C. & Meiswinkel, R. Influence of biotic and abiotic factors on the distribution and abundance of Culicoides imicola and the Obsoletus Complex in Italy. Vet. Parasitol. 150, 333–344 (2007).CAS 
PubMed 
Article 

Google Scholar 
Martinez-de la Puente, J., Navarro, J., Ferraguti, M., Soriguer, R. & Figuerola, J. First molecular identification of the vertebrate hosts of Culicoides imicola in Europe and a review of its blood-feeding patterns worldwide: Implications for the transmission of bluetongue disease and African horse sickness. Med. Vet. Entomol. 31, 333–339 (2017).CAS 
PubMed 
Article 

Google Scholar 
Purse, B. V. et al. Impacts of climate, host and landscape factors on Culicoides species in Scotland. Med. Vet. Entomol. 26, 168–177 (2012).CAS 
PubMed 
Article 

Google Scholar 
Leta, S. et al. Updating the global occurrence of Culicoides imicola, a vector for emerging viral diseases. Sci. Data 6, 1–8 (2019).CAS 
Article 

Google Scholar  More

Panigada, S., Lauriano, G., Burt, L., Pierantonio, N. & Donovan, G. Monitoring winter and summer abundance of cetaceans in the Pelagos Sanctuary (northwestern Mediterranean Sea) through aerial surveys. PLoS One 6, e22878 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Moura, A. E., Sillero, N. & Rodrigues, A. Common dolphin (Delphinus delphis) habitat preferences using data from two platforms of opportunity. Acta Oecol. 38, 24–32 (2012).ADS 
Article 

Google Scholar 
Rendell, L. et al. Abundance and movements of sperm whales in the western Mediterranean basin. Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 31–40 (2014).Article 

Google Scholar 
Schipper, J. et al. The status of the world’s land and marine mammals: Diversity. Threat Knowl. 322, 225–230 (2008).CAS 

Google Scholar 
Luksenburg, J. A. & Parsons, E. C. M. Attitudes towards marine mammal conservation issues before the introduction of whale-watching: A case study in Aruba (southern Caribbean). Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 135–146 (2014).Article 

Google Scholar 
Erbe, C. et al. Managing the effects of noise from ship traffic, seismic surveying and construction on marine mammals in Antarctica. Front. Mar. Sci. 6, 25 (2019).Article 

Google Scholar 
Wurtz, M. & Simard, F. Following the food chain- an ecosystem approach to pelagic protected areas in the Mediterranean by means of cetacean presence. Rapp. Comm. Int. Mer Médit 38, 634 (2007).
Google Scholar 
Bǎnaru, D. et al. Trophic structure in the Gulf of Lions marine ecosystem (north-western Mediterranean Sea) and fishing impacts. J. Mar. Syst. 111–112, 45–68 (2013).Article 

Google Scholar 
Moore, S. E. Marine mammals as ecosystem sentinels. J. Mammal. 89, 534–540 (2008).Article 

Google Scholar 
Hooker, S. K. & Gerber, L. R. Marine reserves as a tool for ecosystem-based management: The potential importance of Megafauna. Bioscience 54, 27–39 (2004).Article 

Google Scholar 
Burek, K. A., Gulland, F. M. D. & O’Hara, T. M. Effects of climate change on Arctic marine mammal health. Ecol. Appl. 18, S126–S134 (2008).PubMed 
Article 

Google Scholar 
Laran, S. et al. Seasonal distribution and abundance of cetaceans within French waters—Part I: The North-Western Mediterranean, including the Pelagos sanctuary. Deep. Res. Part II Top. Stud. Oceanogr. 141, 20–30 (2017).ADS 
Article 

Google Scholar 
Arranz, P. et al. Diving behavior and fine-scale kinematics of free-ranging Risso’s dolphins foraging in shallow and deep-water habitats. Front. Ecol. Evol. 7, 1–15 (2019).Article 

Google Scholar 
Praca, E. & Gannier, A. Ecological niche of three teuthophageous odontocetes in the northwestern Mediterranean Sea. Ocean Sci. Discuss. 4, 785–815 (2008).ADS 

Google Scholar 
Tepsich, P., Rosso, M., Halpin, P. N. & Moulins, A. Habitat preferences of two deep-diving cetacean species in the northern Ligurian Sea. Mar. Ecol. Prog. Ser. 508, 247–260 (2014).ADS 
Article 

Google Scholar 
Gannier, A., Drouot, V. & Goold, J. C. Distribution and relative abundance of sperm whales in the Mediterranean Sea. Mar. Ecol. Prog. Ser. 243, 281–293 (2002).ADS 
Article 

Google Scholar 
Gannier, A. & Praca, E. SST fronts and the summer sperm whale distribution in the north-west Mediterranean Sea. J. Mar. Biol. Assoc. UK 87, 187–193 (2007).Article 

Google Scholar 
Azzellino, A. et al. Predictive habitat models for managing marine areas: Spatial and temporal distribution of marine mammals within the Pelagos Sanctuary (Northwestern Mediterranean sea). Ocean Coast. Manage. 67, 63–74 (2012).Article 

Google Scholar 
de Stephanis, R., Giménez, J., Carpinelli, E., Gutierrez-Exposito, C. & Cañadas, A. As main meal for sperm whales: Plastics debris. Mar. Pollut. Bull. 69, 206–214 (2013).PubMed 
Article 
CAS 

Google Scholar 
Notarbartolo-Di-Sciara, G. Sperm whales, Physeter macrocephalus, in the Mediterranean Sea: A summary of status, threats, and conservation recommendations. Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 4–10 (2014).Article 

Google Scholar 
Laran, S. & Drouot-dulau, V. Seasonal variation of striped dolphins , fin- and sperm whales ’ abundance in the Ligurian Sea (Mediterranean Sea). 345–352 (2007). https://doi.org/10.1017/S0025315407054719.Notarbartolo-Di-Sciara, G., Agardy, T., Hyrenbach, D., Scovazzi, T. & Van Klaveren, P. The Pelagos Sanctuary for Mediterranean marine mammals. Aquat. Conserv. Mar. Freshw. Ecosyst. 18, 367–391 (2008).Article 

Google Scholar 
Azzellino, A., Gaspari, S., Airoldi, S. & Nani, B. Habitat use and preferences of cetaceans along the continental slope and the adjacent pelagic waters in the western Ligurian Sea. Deep Sea Res. Part I Oceanogr. Res. Pap. 55, 296–323 (2008).ADS 
Article 

Google Scholar 
Cañadas, A., Sagarminaga, R., De Stephanis, R., Urquiola, E. & Hammond, P. S. Habitat preference modelling as a conservation tool: Proposals for marine protected areas for cetaceans in southern Spanish waters. Aquat. Conserv. Mar. Freshw. Ecosyst. 15, 495–521 (2005).Article 

Google Scholar 
Cañadas, A. & Vázquez, J. A. Conserving Cuvier’s beaked whales in the Alboran Sea (SW Mediterranean): Identification of high density areas to be avoided by intense man-made sound. Biol. Conserv. 178, 155–162 (2014).Article 

Google Scholar 
Lewis, T. et al. Sperm whale abundance estimates from acoustic surveys of the Ionian Sea and Straits of Sicily in 2003. J. Mar. Biol. Assoc. UK 87, 353 (2007).Article 

Google Scholar 
Caruso, F. et al. Size distribution of sperm whales acoustically identified during long term deep-sea monitoring in the Ionian Sea. PLoS One 10, e0144503 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Frantzis, A., Leaper, R., Alexiadou, P., Prospathopoulos, A. & Lekkas, D. Shipping routes through core habitat of endangered sperm whales along the Hellenic Trench, Greece: Can we reduce collision risks?. PLoS One 14, 1–21 (2019).
Google Scholar 
Pirotta, E., Matthiopoulos, J., Mackenzie, M., Scott-hayward, L. & Rendell, L. Modelling sperm whale habitat preference: A novel approach combining transect and follow data. Mar. Ecol. Prog. Ser. 436, 257–272 (2011).ADS 
Article 

Google Scholar 
Mussi, B., Miragliuolo, A., Zucchini, A. & Pace, D. S. Occurrence and spatio-temporal distribution of sperm whale (Physeter macrocephalus) in the submarine canyon of Cuma (Tyrrhenian Sea, Italy). Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 59–70 (2014).Article 

Google Scholar 
Arcangeli, A., Campana, I. & Bologna, M. A. Influence of seasonality on cetacean diversity, abundance, distribution and habitat use in the western Mediterranean Sea: Implications for conservation. Aquat. Conserv. Mar. Freshw. Ecosyst. 27, 995–1010 (2017).Article 

Google Scholar 
Carlucci, R. et al. Residency patterns and site fidelity of Grampus griseus (Cuvier, 1812) in the Gulf of Taranto (Northern Ionian Sea, Central-Eastern Mediterranean Sea). Mammal Res. https://doi.org/10.1007/s13364-020-00485-z (2020).Article 

Google Scholar 
Cañadas, A. et al. The challenge of habitat modelling for threatened low density species using heterogeneous data: The case of Cuvier’s beaked whales in the Mediterranean. Ecol. Indic. 85, 128–136 (2018).Article 

Google Scholar 
Aïssi, M., Ouammi, A., Fiori, C. & Alessi, J. Modelling predicted sperm whale habitat in the central Mediterranean Sea: Requirement for protection beyond the Pelagos Sanctuary boundaries. Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 50–58 (2014).Article 

Google Scholar 
Taylor, B. L. et al. Physeter macrocephalus, sperm whale (Amended version). IUCN Red List Threat. Species 8235, 1–17 (2019).
Google Scholar 
Notarbartolo Di Sciara, G., Frantzis, A., Bearzi, G. & Reeves, R. R. Physeter macrocephalus (Mediterranean subpopulation). IUCN Red List Threat. Species 2012 8235, e.T16370739A16370477 (2012).Notarbartolo di Sciara, G. & Birkun, A. J. Conserving whales, dolophins and porpoises in the Mediterranean and Black Seas. (2010).Kiszka, J. & Braulik, G. Grampus griseus. IUCN Red List Threat. Species 2018 8235, e.T9461A50356660 (2018).Gaspari, S. & Natoli, A. Grampus griseus (Mediterranean subpopulation). IUCN Red List Threat. Species 2012 e.T16378423A16378453 8235, 10 (2012).Baird, R. W., Brownell, R. L. Jr. & Taylor, B. L. Ziphius cavirostris. The IUCN Red List of Threatened Species. Popul. (English Ed.) 8235, 1–3 (2020).
Google Scholar 
Canadas, A. Ziphius cavirostris (Mediterranean subpopulation). IUCN Red List Threat. Species Version 20 (2012).Drouot, V. et al. A note on genetic isolation of Mediterranean sperm whales (Physeter macrocephalus) suggested by mitochondrial DNA. J. Cetacean Res. Manage. 6, 29–32 (2004).
Google Scholar 
Engelhaupt, D. et al. Female philopatry in coastal basins and male dispersion across the North Atlantic in a highly mobile marine species, the sperm whale (Physeter macrocephalus). Mol. Ecol https://doi.org/10.1111/j.1365-294X.2009.04355.x (2009).Article 
PubMed 

Google Scholar 
Lewis, T. et al. Abundance estimates for sperm whales in the Mediterranean Sea from acoustic line-transect surveys. J. Cetacean Res. Manage. 18, 103–117 (2018).
Google Scholar 
Rendell, L. & Frantzis, A. Mediterranean Sperm Whales, Physeter macrocephalus: The Precarious State of a Lost Tribe. In Advances in Marine Biology, Vol 75 (ed. Sad, D.) (Elsevier, 2016).
Google Scholar 
Alessi, J., Aïssi, M. & Fiori, C. Photo-identification of sperm whales in the north-western Mediterranean Sea: An assessment of natural markings. Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 11–22 (2014).Article 

Google Scholar 
Blanco, C., Raduán, M. Á. & Raga, J. A. Diet of Risso’s dolphin (Grampus griseus) in the western Mediterranean Sea. Sci. Mar. 70, 407–411 (2006).Article 

Google Scholar 
Jefferson, T. A. et al. Global distribution of Risso’s dolphin Grampus griseus: A review and critical evaluation. Mamm. Rev. 44, 56–68 (2014).Article 

Google Scholar 
Gaspari, S. & Natoli, A. Grampus griseus, Risso’s dolphin. The IUCN Red List of Threatened Species. https://www.iucnredlist.org/es/species/9461/3151471 (2012).Macias Lopez, D., Garcia Barcelona, S., Baez, J. C., De La Serna, J. M. & Ortizde Urbina, J. M. Marine mammal bycatch in Spanish Mediterranean large pelagic longline fisheries, with a focus on Risso’s dolphin (Grampus griseus). Aquat. Liv. Resour. 331, 321–331 (2012).Article 

Google Scholar 
Zucca, P. et al. Causes of stranding in four Risso’s dolphins (Grampus griseus) found beached along the North Adriatic Sea coast. Vet. Res. Commun. 29, 261–264 (2005).PubMed 
Article 

Google Scholar 
Alexiadou, P., Foskolos, I. & Frantzis, A. Ingestion of macroplastics by odontocetes of the Greek Seas, Eastern Mediterranean: Often deadly!. Mar. Pollut. Bull. 146, 67–75 (2019).CAS 
PubMed 
Article 

Google Scholar 
Jepson, P. D. et al. Gas-bubble lesions in stranded cetaceans. Nature 425, 575–576 (2003).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Mannocci, L. et al. Assessing cetacean surveys throughout the Mediterranean Sea: A gap analysis in environmental space. Sci. Rep. 8, 3126 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Báez, J., Estrada, A., Torreblanca, D. & Real, R. Predicting the distribution of cryptic species: The case of the spur-thighed tortoise in Andalusia (southern Iberian Peninsula). Biodivers. Conserv. 20, 65–78. https://doi.org/10.1007/s10531-011-0164-3 (2012).Article 

Google Scholar 
Torreblanca, E. et al. Using opportunistic sightings to infer differential spatio-temporal use of western mediterranean waters by the fin whale. PeerJ 2019, 1–20 (2019).
Google Scholar 
Russo, D., Sgammato, R. & Bosso, L. First sighting of the humpback whale Megaptera novaeangliae in the Tyrrhenian Sea and a mini-review of Mediterranean records. Hystrix Ital. J. Mammal. 27, 219–221 (2016).
Google Scholar 
Esteban, R. et al. Identifying key habitat and seasonal patterns of a critically endangered population of killer whales. J. Mar. Biol. Assoc. UK 94, 1317–1325 (2014).Article 

Google Scholar 
Folkens, P. & Reeves, R. Guide to Marine Mammals of the World (Knopf, 2005).
Google Scholar 
Real, R., Barbosa, A. M. & Vargas, J. M. Obtaining environmental favourability functions from logistic regression. Environ. Ecol. Stat. 13, 237–245 (2006).MathSciNet 
Article 

Google Scholar 
MacNally, R. Regression and model-building in conservation biology, biogeography and ecology: The distinction between—and reconciliation of—‘predictive’ and ‘explanatory’ models. Biodivers. Conserv. 20, 655–671. https://doi.org/10.1103/PhysRevD.66.085018 (2000).CAS 
Article 

Google Scholar 
Real, R., Márcia Barbosa, A. & Bull, J. W. Species distributions, quantum theory, and the enhancement of biodiversity measures. Syst. Biol. 66, 453–462 (2017).PubMed 

Google Scholar 
Praca, E., Gannier, A., Das, K. & Laran, S. Modelling the habitat suitability of cetaceans: Example of the sperm whale in the northwestern Mediterranean Sea. Deep Sea Res. Part I Oceanogr. Res. Pap. 56, 648–657 (2009).ADS 
Article 

Google Scholar 
Boisseau, O. et al. Encounter rates of cetaceans in the Mediterranean Sea and contiguous Atlantic area. J. Mar. Biol. Assoc. UK 90, 1589–1599 (2010).Article 

Google Scholar 
Hamazaki, T. Spatiotemporal prediction models of cetacean habitats in the mid-western North Atlantic Ocean (from Cape Hatteras, North Carolina, USA to Nova Scotia, Canada). Mar. Mammal Sci. 18, 920–939 (2002).Article 

Google Scholar 
Cañadas, A., Sagarminaga, R. & Garcıa-Tiscar, S. Cetacean distribution related with depth and slope in the Mediterranean waters off southern Spain. Deep Sea Res. Part I 49, 2053–2073 (2002).Article 

Google Scholar 
Fiori, C., Giancardo, L., Aïssi, M., Alessi, J. & Vassallo, P. Geostatistical modelling of spatial distribution of sperm whales in the Pelagos Sanctuary based on sparse count data and heterogeneous observations. Aquat. Conserv. Mar. Freshw. Ecosyst. 24, 41–49 (2014).Article 

Google Scholar 
Pikesley, S. K. Cetacean sightings and strandings: Evidence for spatial and temporal trends?. J. Mar. Biol. Assoc. UK 92, 1809–1820 (2012).Article 

Google Scholar 
O’Reilly, J. E. et al. Ocean color chlorophyll algorithms for SeaWiFS. J. Geophys. Res. Ocean. 103, 24937–24953 (1998).ADS 
Article 

Google Scholar 
Carton, J. A., Chepurin, G. A. & Chen, L. SODA3: A new ocean climate reanalysis. J. Clim. 31, 6967–6983 (2018).ADS 
Article 

Google Scholar 
Romero, J. & Real, R. Macroenvironmental factors as ultimate determinants of distribution of common toad and natterjack toad in the south of Spain. Ecography (Cop.) 20, 305–312 (1996).Article 

Google Scholar 
Hosmer, D. W. & Lemeshow, S. Applied Logistic Regression 2nd edn. (Wiley, 2000).MATH 
Book 

Google Scholar 
Legendre, P. & Legendre, L. Numerical Ecology (Elsevier BV, New York, 1998).MATH 

Google Scholar 
Peng, C.-Y.J., Lee, K. L. & Ingersoll, G. M. An introduction to logistic regression analysis and reporting. J. Educ. Res. 96, 3–14 (2002).Article 

Google Scholar 
Acevedo, P., Ward, A. I., Real, R. & Smith, G. C. Assessing biogeographical relationships of ecologically related species using favourability functions: A case study on British deer. Divers. Distrib. 16, 515–528 (2010).Article 

Google Scholar 
Zhang, Y., Tang, J., Ren, G., Zhao, K. & Wang, X. Global potential distribution prediction of Xanthium italicum based on Maxent model. Sci. Rep. 11, 1–10 (2021).Article 
CAS 

Google Scholar 
Ancillotto, L. et al. An African bat in Europe, Plecotus gaisleri: Biogeographic and ecological insights from molecular taxonomy and Species Distribution Models. Ecol. Evol. 10, 5785–5800 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Akaike. Information theory and an extension of the maximum likelihood principle. 199–213 (1929). More

Vázquez, D. P., Gianoli, E., Morris, W. F. & Bozinovic, F. Ecological and evolutionary impacts of changing climatic variability. Biol. Rev. 92, 22–42. https://doi.org/10.1111/brv.12216 (2017).Article 
PubMed 

Google Scholar 
Marshall, K. E. & Sinclair, B. J. The impacts of repeated cold exposure on insects. J. Exp. Biol. 215, 1607–1613. https://doi.org/10.1242/jeb.059956 (2012).Article 
PubMed 

Google Scholar 
Bale, J. & Hayward, S. Insect overwintering in a changing climate. J. Exp. Biol. 213, 980–994 (2010).CAS 
PubMed 
Article 

Google Scholar 
Kingsolver, J. G. Feeding, growth, and the thermal environment of cabbage white caterpillars, Pieris rapae L. Physiol. Biochem. Zool. 73, 621–628 (2000).CAS 
PubMed 
Article 

Google Scholar 
Stange, E. E. & Ayres, M. P. Climate change impacts: Insects (JohnWiley & Sons, 2010).
Google Scholar 
Chapman, A. D. Numbers of Living Species in Australia and the World: Report for the Department of the Environment and Heritage Canberra, Australia (Department of the Environment and Heritage, 2006).
Google Scholar 
Colinet, H., Sinclair, B. J., Vernon, P. & Renault, D. Insects in fluctuating thermal environments. Annu. Rev. Entomol. 60, 123–140. https://doi.org/10.1146/annurev-ento-010814-021017 (2015).CAS 
Article 
PubMed 

Google Scholar 
Hickling, R., Roy, D. B., Hill, J. K. & Thomas, C. D. A northward shift of range margins in British Odonata. Glob. Change Biol. 11, 502–506. https://doi.org/10.1111/j.1365-2486.2005.00904.x (2005).ADS 
Article 

Google Scholar 
Rumpf, S. B., Hülber, K., Zimmermann, N. E. & Dullinger, S. Elevational rear edges shifted at least as much as leading edges over the last century. Glob. Ecol. Biogeogr. 28, 533–543. https://doi.org/10.1111/geb.12865 (2019).Article 

Google Scholar 
Halsch, C. A. et al. Insects and recent climate change. Proc. Natl. Acad. Sci. 118, e2002543117. https://doi.org/10.1073/pnas.2002543117 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
McCain, C. M. & Garfinkel, C. F. Climate change and elevational range shifts in insects. Curr. Opin. Insect Sci. 47, 111–118. https://doi.org/10.1016/j.cois.2021.06.003 (2021).Article 
PubMed 

Google Scholar 
Angilletta, M. J. Jr. & Angilletta, M. J. Thermal Adaptation: A Theoretical and Empirical Synthesis (Oxford University Press, 2009).Book 

Google Scholar 
Angilletta, M. J. & Dunham, A. E. The temperature-size rule in ectotherms: Simple evolutionary explanations may not be general. Am. Nat. 162, 332–342. https://doi.org/10.1086/377187 (2003).Article 
PubMed 

Google Scholar 
Jensen, J. L. W. V. Sur les fonctions convexes et les inégalités entre les valeurs moyennes. Acta Math. 30, 175–193 (1906).MathSciNet 
MATH 
Article 

Google Scholar 
Ruel, J. J. & Ayres, M. P. Jensen’s inequality predicts effects of environmental variation. Trends Ecol. Evol. 14, 361–366 (1999).CAS 
PubMed 
Article 

Google Scholar 
Kingsolver, J. G. & Woods, H. A. Thermal sensitivity of growth and feeding in Manduca sexta Caterpillars. Physiol. Zool. 70, 631–638. https://doi.org/10.1086/515872 (1997).CAS 
Article 
PubMed 

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).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Bale, J. S. et al. Herbivory in global climate change research: Direct effects of rising temperature on insect herbivores. Glob. Change Biol. 8, 1–16 (2002).ADS 
Article 

Google Scholar 
Robinet, C. & Roques, A. Direct impacts of recent climate warming on insect populations. Integr. Zool. 5, 132–142 (2010).PubMed 
Article 

Google Scholar 
García-Robledo, C., Kuprewicz, E. K., Staines, C. L., Erwin, T. L. & Kress, W. J. Limited tolerance by insects to high temperatures across tropical elevational gradients and the implications of global warming for extinction. Proc. Natl. Acad. Sci. 113, 680–685. https://doi.org/10.1073/pnas.1507681113 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

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

Google Scholar 
Sandehson, D. E. The relation of temperature to the growth of insects. J. Econ. Entomol. 3, 113–140 (1910).Article 

Google Scholar 
Cook, W. C. Some Effects of Alternating Temperatures on the Growth and Metabolism of Cutworm Larvae (Oxford University Press, 1927).
Google Scholar 
Kingsolver, J. G., Ragland, G. J. & Diamond, S. E. Evolution in a constant environment: Thermal fluctuations and thermal sensitivity of laboratory and field populations of Manduca sexta. Evolution 63, 537–541. https://doi.org/10.1111/j.1558-5646.2008.00568.x (2009).Article 
PubMed 

Google Scholar 
Eldridge, W. H., Sweeney, B. W. & Law, J. M. Fish growth, physiological stress, and tissue condition in response to rate of temperature change during cool or warm diel thermal cycles. Can. J. Fish. Aquat. Sci. 72, 1527–1537 (2015).CAS 
Article 

Google Scholar 
Bernhardt, J. R., Sunday, J. M., Thompson, P. L. & O’Connor, M. I. Nonlinear averaging of thermal experience predicts population growth rates in a thermally variable environment. Proc. R. Soc. B Biol. Sci. 285, 20181076. https://doi.org/10.1098/rspb.2018.1076 (2018).Article 

Google Scholar 
Morissette, J., Swart, S., Maccormack, T. J., Currie, S. & Morash, A. J. Thermal variation near the thermal optimum does not affect the growth, metabolism or swimming performance in wild Atlantic salmon Salmo salar. J. Fish Biol. 98, 1585–1589. https://doi.org/10.1111/jfb.14348 (2021).CAS 
Article 
PubMed 

Google Scholar 
Bozinovic, F. et al. The mean and variance of environmental temperature interact to determine physiological tolerance and fitness. Physiol. Biochem. Zool. 84, 543–552 (2011).PubMed 
Article 

Google Scholar 
Boggs, C. L. The fingerprints of global climate change on insect populations. Curr. Opin. Insect Sci. 17, 69–73. https://doi.org/10.1016/j.cois.2016.07.004 (2016).Article 
PubMed 

Google Scholar 
Lemoine, N. P., Drews, W. A., Burkepile, D. E. & Parker, J. D. Increased temperature alters feeding behavior of a generalist herbivore. Oikos 122, 1669–1678. https://doi.org/10.1111/j.1600-0706.2013.00457.x (2013).Article 

Google Scholar 
Vangansbeke, D. et al. Prey consumption by phytoseiid spider mite predators as affected by diurnal temperature variations. Biocontrol 60, 595–603 (2015).Article 

Google Scholar 
Davies, C., Coetzee, M. & Lyons, C. L. Effect of stable and fluctuating temperatures on the life history traits of Anopheles arabiensis and An. quadriannulatus under conditions of inter-and intra-specific competition. Parasit. Vectors 9, 1–9 (2016).Article 

Google Scholar 
Delava, E., Fleury, F. & Gibert, P. Effects of daily fluctuating temperatures on the Drosophila-Leptopilina boulardi parasitoid association. J. Therm. Biol. 60, 95–102 (2016).PubMed 
Article 

Google Scholar 
Amarasekare, P. & Coutinho, R. M. Effects of temperature on intraspecific competition in ectotherms. Am. Nat. 184, E50–E65. https://doi.org/10.1086/677386 (2014).Article 
PubMed 

Google Scholar 
Jiang, L. & Morin, P. J. Temperature-dependent interactions explain unexpected responses to environmental warming in communities of competitors. J. Anim. Ecol. 73, 569–576 (2004).Article 

Google Scholar 
Novich, R. A., Erickson, E. K., Kalinoski, R. M. & DeLong, J. P. The temperature independence of interaction strength in a sit-and-wait predator. Ecosphere 5, 1–9 (2014).Article 

Google Scholar 
Fox, L. R. Cannibalism in natural populations. Annu. Rev. Ecol. Syst. 6, 87–106 (1975).Article 

Google Scholar 
Polis, G. A. The evolution and dynamics of intraspecific predation. Annu. Rev. Ecol. Syst. 12, 225–251 (1981).Article 

Google Scholar 
Nishimura, K. & Isoda, Y. Evolution of cannibalism: Referring to costs of cannibalism. J. Theor. Biol. 226, 293–302. https://doi.org/10.1016/j.jtbi.2003.09.007 (2004).ADS 
MathSciNet 
Article 
PubMed 
MATH 

Google Scholar 
Crumrine, P. W. Body size, temperature, and seasonal differences in size structure influence the occurrence of cannibalism in larvae of the migratory dragonfly, Anax junius. Aquat. Ecol. 44, 761–770 (2010).Article 

Google Scholar 
Reglero, P., Urtizberea, A., Torres, A. P., Alemany, F. & Fiksen, Ø. Cannibalism among size classes of larvae may be a substantial mortality component in tuna. Mar. Ecol. Prog. Ser. 433, 205–219 (2011).ADS 
Article 

Google Scholar 
Nilsson-Örtman, V., Stoks, R. & Johansson, F. Competitive interactions modify the temperature dependence of damselfly growth rates. Ecology 95, 1394–1406. https://doi.org/10.1890/13-0875.1 (2014).Article 
PubMed 

Google Scholar 
Pritchard, G. & Leggott, M. Temperature, incubation rates and the origins of dragonflies. Adv. Odonatol. 3, 121–126 (1987).
Google Scholar 
Hassall, C. & Thompson, D. J. The effects of environmental warming on Odonata: A review. Int. J. Odonatol. 11, 131–153 (2008).Article 

Google Scholar 
Johansson, F. & Crowley, P. H. Larval cannibalism and population dynamics of dragonflies. In Aquatic Insects: Challenges to Populations 36–54 (CABI, 2008).Rudolf, V. H. W. & Rasmussen, N. L. Ontogenetic functional diversity: Size structure of a keystone predator drives functioning of a complex ecosystem. Ecology 94, 1046–1056 (2013).PubMed 
Article 

Google Scholar 
Hyeun-Ji, L. & Johansson, F. Compensating for a bad start: Compensatory growth across life stages in an organism with a complex life cycle. Can. J. Zool. 94, 41–47 (2016).Article 

Google Scholar 
Sokolovska, N., Rowe, L. & Johansson, F. Fitness and body size in mature odonates. Ecol. Entomol. 25, 239–248. https://doi.org/10.1046/j.1365-2311.2000.00251.x (2000).Article 

Google Scholar 
Karl, T. R. Modern global climate change. Science 302, 1719–1723. https://doi.org/10.1126/science.1090228 (2003).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Meehl, G. A. et al. Climate Change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2007).
Google Scholar 
Meehl, G. A. More intense, more frequent, and longer lasting heat waves in the 21st century. Science 305, 994–997. https://doi.org/10.1126/science.1098704 (2004).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Khelifa, R. Spatiotemporal Pattern of Phenology Across Geographic Gradients in Insects, in Chapter 1 (Geographic Gradients in Climate Change Response Explained by Non-linear Thermal-Performance Curves) (University of Zurich, 2017).
Google Scholar 
Boudot, J. P. & Kalkman, V. Atlas of the European Dragonflies and Damselflies (KNNV Publishing, 2015).
Google Scholar 
Norling, U. Growth, winter preparations and timing of emergence in temperate zone Odonata: Control by a succession of larval response patterns. Int. J. Odonatol. 24, 1–36 (2021).Article 

Google Scholar 
Sniegula, S. & Johansson, F. Photoperiod affects compensating developmental rate across latitudes in the damselfly Lestes sponsa. Ecol. Entomol. 35, 149–157. https://doi.org/10.1111/j.1365-2311.2009.01164.x (2010).Article 

Google Scholar 
Sniegula, S., Golab, M. J. & Johansson, F. Size-mediated priority and temperature effects on intra-cohort competition and cannibalism in a damselfly. J. Anim. Ecol. 88, 637–648. https://doi.org/10.1111/1365-2656.12947 (2019).Article 
PubMed 

Google Scholar 
Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675. https://doi.org/10.1038/nmeth.2089 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Benke, A. C. A method for comparing individual growth rates of aquatic insects with special reference to the Odonata. Ecology 51, 328–331 (1970).Article 

Google Scholar 
Nilsson-Örtman, V., Stoks, R., De Block, M. & Johansson, F. Generalists and specialists along a latitudinal transect: Patterns of thermal adaptation in six species of damselflies. Ecology 93, 1340–1352. https://doi.org/10.1890/11-1910.1 (2012).Article 
PubMed 

Google Scholar 
Eklund, A. et al. Sveriges Framtida Klimat: Underlag Till Dricksvattenutredningen (SMHI, 2015).
Google Scholar 
McPeek, M. A. Determination of species composition in the Enallagma damselfly assemblages of permanent lakes. Ecology 71, 83–98. https://doi.org/10.2307/1940249 (1990).Article 

Google Scholar 
Kirillin, G. et al. FLake-global: Online lake model with worldwide coverage. Environ. Model. Softw. 26, 683–684. https://doi.org/10.1016/j.envsoft.2010.12.004 (2011).Article 

Google Scholar 
SMHI. Advanced Climate Change Scenario Service. https://www.smhi.se.R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).Suhling, F., Suhling, I. & Richter, O. Temperature response of growth of larval dragonflies–An overview. Int. J. Odonatol. 18, 15–30 (2015).Article 

Google Scholar 
Padfield, D., O’Sullivan, H. & Pawar, S. rTPC and nls.multstart: A new pipeline to fit thermal performance curves in R. Methods Ecol. Evol. 1, 1. https://doi.org/10.1111/2041-210X.13585 (2021).Article 

Google Scholar 
Kleiber, M. Body size and metabolism. Hilgardia 6, 315–353 (1932).CAS 
Article 

Google Scholar 
Hemmingsen, A. Reports of the Steno Memorial Hospital and Nordisk Insulin Laboratorium. Energy Metab. Relat. Body Size Respir. Surf. Evol. 9, 6–110 (1960).
Google Scholar 
Dell, A. I., Pawar, S. & Savage, V. M. Systematic variation in the temperature dependence of physiological and ecological traits. Proc. Natl. Acad. Sci. 108, 10591–10596 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Logan, J. D., Wolesensky, W. & Joern, A. Temperature-dependent phenology and predation in arthropod systems. Ecol. Model. 196, 471–482. https://doi.org/10.1016/j.ecolmodel.2006.02.034 (2006).Article 

Google Scholar 
Pink, M. & Abrahams, M. V. Temperature and its impact on predation risk within aquatic ecosystems. Can. J. Fish. Aquat. Sci. 73, 869–876. https://doi.org/10.1139/cjfas-2015-0302 (2016).Article 

Google Scholar 
DeAngelis, D., Cox, D. & Coutant, C. Cannibalism and size dispersal in young-of-the-year largemouth bass: Experiment and model. Ecol. Model. 8, 133–148 (1980).Article 

Google Scholar 
Fagan, W. F. & Odell, G. M. Size-dependent cannibalism in praying mantids: Using biomass flux to model size-structured populations. Am. Nat. 147, 230–268 (1996).Article 

Google Scholar 
Dong, Q. & Deangelis, D. L. Consequences of cannibalism and competition for food in a smallmouth bass population: An individual-based modeling study. Trans. Am. Fish. Soc. 127, 174–191 (1998).Article 

Google Scholar 
Verheyen, J. & Stoks, R. Temperature variation makes an ectotherm more sensitive to global warming unless thermal evolution occurs. J. Anim. Ecol. 88, 624–636. https://doi.org/10.1111/1365-2656.12946 (2019).Article 
PubMed 

Google Scholar 
Starr, S. M. & McIntyre, N. E. Effects of water temperature under projected climate change on the development and survival of Enallagma civile (Odonata: Coenagrionidae). Environ. Entomol. 49, 230–237. https://doi.org/10.1093/ee/nvz138 (2020).CAS 
Article 
PubMed 

Google Scholar 
Culler, L. E., McPeek, M. A. & Ayres, M. P. Predation risk shapes thermal physiology of a predaceous damselfly. Oecologia 176, 653–660. https://doi.org/10.1007/s00442-014-3058-8 (2014).ADS 
Article 
PubMed 

Google Scholar 
Dokulil, M. T. et al. Increasing maximum lake surface temperature under climate change. Clim. Change https://doi.org/10.1007/s10584-021-03085-1 (2021).Article 

Google Scholar 
Merritt, R. W. & Cummins, K. W. An Introduction to the Aquatic Insects of North America 2nd edn. (Kendall/Hunt Publishing Company, 1984).
Google Scholar 
Verdonschot, R. & Peeters, E. T. Preference of larvae of Enallagma cyathigerum (Odonata: Coenagrionidae) for habitats of varying structural complexity. Eur. J. Entomol. 109, 229–234 (2012).Article 

Google Scholar 
McCarty, J. P., Wolfenbarger, L. L. & Wilson, J. A. eLS 1–13 (Wiley, 2017).Book 

Google Scholar 
Holzmann, K. L. Challenges in a Changing Climate: The Effect of Temperature Variation on Growth and Competition in Damselflies Independent thesis Advanced level (degree of Master (Two Years) thesis, Uppsala University. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-467582 (2022). More

Sylvan, J. How to protect a coral reef: the public trust doctrine and the law of the sea recommended citation. Sustain. Dev. Law Policy 7, 12 (2006).
Google Scholar 
LaJeunesse, T. C. et al. Systematic revision of symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580.e6 (2018).CAS 
PubMed 
Article 

Google Scholar 
Kopp, C. et al. Highly dynamic cellular-level response of symbiotic coral to a sudden increase in environmental nitrogen. mBio 4, e00052–13 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Muscatine, L. The role of symbiotic algae in carbon and energy flux in reef corals. Coral Reef. 25, 75–87 (1990).
Google Scholar 
Dubinsky, Z. & Stambler, N. Coral reefs: an ecosystem in transition. (Springer, 2011).Wiedenmann, J. et al. Nutrient enrichment can increase the susceptibility of reef corals to bleaching. https://doi.org/10.1038/NCLIMATE1661 (2012).Suggett, D. J., Warner, M. E. & Leggat, W. Symbiotic dinoflagellate functional diversity mediates coral survival under ecological crisis. Trends Ecol. Evolution 32, 735–745 (2017).Article 

Google Scholar 
Morris, L. A., Voolstra, C. R., Quigley, K. M., Bourne, D. G. & Bay, L. K. Nutrient availability and metabolism affect the stability of coral–symbiodiniaceae symbioses. Trends Microbiol. 27, 678–689 (2019).CAS 
PubMed 
Article 

Google Scholar 
Lehnert, E. M. et al. Extensive differences in gene expression between symbiotic and aposymbiotic cnidarians. G3 (Bethesda) 4, 277–95 (2014).CAS 
Article 

Google Scholar 
Dubinsky, Z. & Berman-Frank, I. Uncoupling primary production from population growth in photosynthesizing organisms in aquatic ecosystems. in. Aquat. Sci. 63, 4–17 (2001).CAS 
Article 

Google Scholar 
Burriesci, M. S., Raab, T. K. & Pringle, J. R. Evidence that glucose is the major transferred metabolite in dinoflagellate–cnidarian symbiosis. J. Exp. Biol. 215, 3467–3477 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Davy, S. K., Allemand, D. & Weis, V. M. Cell biology of cnidarian-dinoflagellate symbiosis. Microbiol. Mol. Biol. Rev. 76, 229–61 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rädecker, N., Pogoreutz, C., Voolstra, C. R., Wiedenmann, J. & Wild, C. Nitrogen cycling in corals: the key to understanding holobiont functioning? Trends Microbiol. 23, 490–497 (2015).PubMed 
Article 
CAS 

Google Scholar 
Cui, G. et al. Host-dependent nitrogen recycling as a mechanism of symbiont control in Aiptasia. PLOS Genet. 15, e1008189 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rädecker, N. et al. Heat stress destabilizes symbiotic nutrient cycling in corals. Proc. Natl Acad. Sci. USA 118, https://doi.org/10.1073/pnas.2022653118 (2021).Weis, V. M. Cellular mechanisms of Cnidarian bleaching: stress causes the collapse of symbiosis. J. Exp. Biol. 211, 3059–3066 (2008).CAS 
PubMed 
Article 

Google Scholar 
Wooldridge, S. A. Breakdown of the coral-algae symbiosis: towards formalising a linkage between warm-water bleaching thresholds and the growth rate of the intracellular zooxanthellae. Biogeosciences Discuss. 9, 8111–8139 (2012).
Google Scholar 
Cziesielski, M. J., Schmidt‐Roach, S. & Aranda, M. The past, present, and future of coral heat stress studies. Ecol. Evol. https://doi.org/10.1002/ece3.5576 (2019).Leggat, W. et al. Differential responses of the coral host and their algal symbiont to thermal stress. PLoS ONE 6, e26687 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pinzón, J. H. et al. Whole transcriptome analysis reveals changes in expression of immune-related genes during and after bleaching in a reef-building coral. R. Soc. Open Sci. 2, 140214 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 14213 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bang, C. et al. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology 127, 1–19 (2018).PubMed 
Article 

Google Scholar 
Berkelmans, R. & van Oppen, M. J. H. The role of zooxanthellae in the thermal tolerance of corals: a “nugget of hope” for coral reefs in an era of climate change. Proc. Biol. Sci./R. Soc. 273, 2305–12 (2006).
Google Scholar 
Sampayo, E. M., Ridgway, T., Bongaerts, P. & Hoegh-Guldberg, O. Bleaching susceptibility and mortality of corals are determined by fine-scale differences in symbiont type. Proc. Natl Acad. Sci. 105, 10444–10449 (2008).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Howells, E. J. et al. Coral thermal tolerance shaped by local adaptation of photosymbionts. Nat. Clim. Change https://doi.org/10.1038/nclimate1330 (2011).Cziesielski, M. J. et al. Multi-omics analysis of thermal stress response in a zooxanthellate cnidarian reveals the importance of associating with thermotolerant symbionts. Proc. Biol. Sci. 285, 20172654 (2018).PubMed 
PubMed Central 

Google Scholar 
Baker, A. C., Starger, C. J., McClanahan, T. R. & Glynn, P. W. Corals’ adaptive response to climate change. Nature 430, 741–741 (2004).CAS 
PubMed 
Article 

Google Scholar 
Thornhill, D. J., LaJeunesse, T. C., Kemp, D. W., Fitt, W. K. & Schmidt, G. W. Multi-year, seasonal genotypic surveys of coral-algal symbioses reveal prevalent stability or post-bleaching reversion. Mar. Biol. 148, 711–722 (2006).Article 

Google Scholar 
Palumbi, S. R., Barshis, D. J., Traylor-Knowles, N. & Bay, R. A. Mechanisms of reef coral resistance to environmental stress,making its relative ability to acclimate or adapt extremely important to the to future climate change. Science 344, 895–898 (2014).CAS 
PubMed 
Article 

Google Scholar 
Herrera, M. et al. Temperature transcends partner specificity in the symbiosis establishment of a cnidarian. ISME J. 15, 141–153 (2021).CAS 
PubMed 
Article 

Google Scholar 
Howells, E. J. et al. Corals in the hottest reefs in the world exhibit symbiont fidelity not flexibility. Mol. Ecol. 29, 899–911 (2020).CAS 
PubMed 
Article 

Google Scholar 
Hume, B. C. C., Mejia-Restrepo, A., Voolstra, C. R. & Berumen, M. L. Fine-scale delineation of Symbiodiniaceae genotypes on a previously bleached central Red Sea reef system demonstrates a prevalence of coral host-specific associations. Coral Reefs 1–19 https://doi.org/10.1007/s00338-020-01917-7 (2020).Perez, S. F., Cook, C. B. & Brooks, W. R. The role of symbiotic dinoflagellates in the temperature-induced bleaching response of the subtropical sea anemone Aiptasia pallida. J. Exp. Mar. Biol. Ecol. 256, 1–14 (2001).CAS 
PubMed 
Article 

Google Scholar 
Mieog, J. C. et al. The roles and interactions of symbiont, host and environment in defining coral fitness. PLoS ONE 4, e6364 (2009).Cantin, N. E., van Oppen, M. J. H., Willis, B. L., Mieog, J. C. & Negri, A. P. Juvenile corals can acquire more carbon from high-performance algal symbionts. Coral Reefs 28, 405–414 (2009).Article 

Google Scholar 
Herrera, M. et al. Unfamiliar partnerships limit cnidarian holobiont acclimation to warming. Glob. Change Biol. 26, 5539–5553 (2020).Article 

Google Scholar 
LaJeunesse, T. et al. Closely related Symbiodinium spp. differ in relative dominance in coral reef host communities across environmental, latitudinal and biogeographic gradients. Mar. Ecol. Prog. Ser. 284, 147–161 (2004).Article 

Google Scholar 
Parkinson, J. E. & Baums, I. B. The extended phenotypes of marine symbioses: ecological and evolutionary consequences of intraspecific genetic diversity in coral-algal associations. Front. Microbiol. 5, 445 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Coffroth, M. A., Poland, D. M., Petrou, E. L., Brazeau, D. A. & Holmberg, J. C. Environmental symbiont acquisition may not be the solution to warming seas for reef-building corals. PLoS ONE 5, e13258 (2010).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Bellantuono, A. J., Granados-Cifuentes, C., Miller, D. J., Hoegh-Guldberg, O. & Rodriguez-Lanetty, M. Coral thermal tolerance: tuning gene expression to resist thermal stress. PLoS ONE 7, e50685 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sunagawa, S. et al. Generation and analysis of transcriptomic resources for a model system on the rise: the sea anemone Aiptasia pallida and its dinoflagellate endosymbiont. BMC Genomics 10, 258 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Baumgarten, S. et al. The genome of Aiptasia, a sea anemone model for coral symbiosis. Proc. Natl Acad. Sci. 112, 201513318 (2015).
Google Scholar 
Matthews, J. L. et al. Menthol-induced bleaching rapidly and effectively provides experimental aposymbiotic sea anemones (Aiptasia sp.) for symbiosis investigations. J. Exp. Biol. jeb.128934 https://doi.org/10.1242/JEB.128934 (2015).Kenkel, C. D. et al. Evidence for a host role in thermotolerance divergence between populations of the mustard hill coral (Porites astreoides) from different reef environments. Mol. Ecol. 22, 4335–4348 (2013).CAS 
PubMed 
Article 

Google Scholar 
Polato, N. R., Altman, N. S. & Baums, I. B. Variation in the transcriptional response of threatened coral larvae to elevated temperatures. Mol. Ecol. 22, 1366–1382 (2013).CAS 
PubMed 
Article 

Google Scholar 
DeSalvo, M., Sunagawa, S., Voolstra, C. R. & Medina, M. Transcriptomic resonses to heat stress and bleaching in the elkhorn coral Acropora palmata. Mar. Ecol. Prog. Ser. 402, 97–113 (2010).CAS 
Article 

Google Scholar 
Maor-Landaw, K. & Levy, O. Gene expression profiles during short-term heat stress; branching vs. massive Scleractinian corals of the Red Sea. PeerJ 4, e1814 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Yamamoto, K. et al. Control of the heat stress-induced alternative splicing of a subset of genes by hnRNP K. Genes Cells 21, 1006–1014 (2016).CAS 
PubMed 
Article 

Google Scholar 
Seneca, F. O. & Palumbi, S. R. The role of transcriptome resilience in resistance of corals to bleaching. Mol. Ecol. 24, 1467–1484 (2015).PubMed 
Article 

Google Scholar 
Meyer, E. & Weis, V. M. Study of cnidarian-algal symbiosis in the “omics” age. Biol. Bull. 223, 44–65 (2012).CAS 
PubMed 
Article 

Google Scholar 
Oakley, C. A. et al. Thermal shock induces host proteostasis disruption and endoplasmic reticulum stress in the model symbiotic Cnidarian Aiptasia. J. Proteome Res. 16, 2121–2134 (2017).CAS 
PubMed 
Article 

Google Scholar 
Robbart, M. L., Peckol, P., Scordilis, S. P., Curran, H. A. & Brown-Saracino, J. Population recovery and differential heat shock protein expression for the corals Agaricia agaricites and A-tenuifolia in Belize. Mar. Ecol. Prog. Ser. 283, 151–160 (2004).Article 

Google Scholar 
Barshis, D. J. et al. Genomic basis for coral resilience to climate change. Proc. Natl Acad. Sci. 110, 1387–1392 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Traylor-Knowles, N., Rose, N. H. & Palumbi, S. R. The cell specificity of gene expression in the response to heat stress in corals. J. Exp. Biol. 220, 1837–1845 (2017).PubMed 

Google Scholar 
Benchimol, S. p53-dependent pathways of apoptosis. Cell Death Differ. 8, 1049–1051 (2001).CAS 
PubMed 
Article 

Google Scholar 
Moya, A. et al. Functional conservation of the apoptotic machinery from coral to man: The diverse and complex Bcl-2 and caspase repertoires of Acropora millepora. BMC Genomics 17, 62 (2016).Elmore, S. Apoptosis: a review of programmed cell death. Toxicol. Pathol. 35, 495–516 (2007).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Karim, W., Nakaema, S. & Hidaka, M. Temperature effects on the growth rates and photosynthetic activities of symbiodinium cells. J. Mar. Sci. Eng. 3, 368–381 (2015).Article 

Google Scholar 
Cunning, R. & Baker, A. C. Excess algal symbionts increase the susceptibility of reef corals to bleaching. Nat. Clim. Change 3, 259–262 (2013).Article 

Google Scholar 
Rehman, A. U. et al. Symbiodinium sp. cells produce light-induced intra- and extracellular singlet oxygen, which mediates photodamage of the photosynthetic apparatus and has the potential to interact with the animal host in coral symbiosis. N. Phytologist 212, 472–484 (2016).CAS 
Article 

Google Scholar 
Lesser, K. B. & Garcia, F. A. Association between polycystic ovary syndrome and glucose intolerance during pregnancy. J. Matern. Fetal Med. 6, 303–307 (1997).CAS 
PubMed 
Article 

Google Scholar 
Dunn, S. R., Schnitzler, C. E. & Weis, V. M. Apoptosis and autophagy as mechanisms of dinoflagellate symbiont release during cnidarian bleaching: every which way you lose. Proc. R. Soc. Lond. B: Biol. Sci. 274, 3079–3085 (2007).
Google Scholar 
DeSalvo, M. K. et al. Coral host transcriptomic states are correlated with Symbiodinium genotypes. Mol. Ecol. 19, 1174–1186 (2010).CAS 
PubMed 
Article 

Google Scholar 
Levin, R. A. et al. Engineering strategies to decode and enhance the genomes of coral symbionts. Front. Microbiol. https://doi.org/10.3389/fmicb.2017.01220 (2017).Yuyama, I., Ishikawa, M., Nozawa, M., Yoshida, M. & Ikeo, K. Transcriptomic changes with increasing algal symbiont reveal the detailed process underlying establishment of coral-algal symbiosis. Sci. Rep. 8, 16802 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Sproles, A. E. et al. Sub-cellular imaging shows reduced photosynthetic carbon and increased nitrogen assimilation by the non-native endosymbiont Durusdinium trenchii in the model cnidarian Aiptasia. Environ. Microbiol. 22, 3741–3753 (2020).CAS 
PubMed 
Article 

Google Scholar 
Rädecker, N. et al. Using Aiptasia as a model to study metabolic interactions in Cnidarian-Symbiodinium symbioses. Front. Physiol. 9, 214 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Falkowski, P. G., Dubinsky, Z., Muscatine, L. & McCloskey, L. Population control in symbiotic corals. BioScience 43, 606–611 (1993).Article 

Google Scholar 
Wang & Douglas. Nitrogen recycling or nitrogen conservation in an alga-invertebrate symbiosis? J. Exp. Biol. 201, 2445–53 (1998).Loram, J. E., Trapido-Rosenthal, H. G. & Douglas, A. E. Functional significance of genetically different symbiotic algae Symbiodinium in a coral reef symbiosis. Mol. Ecol. 16, 4849–4857 (2007).CAS 
PubMed 
Article 

Google Scholar 
Karako-Lampert, S. et al. Transcriptome analysis of the scleractinian coral Stylophora pistillata. PLoS One 9, e88615 (2014).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Hillyer, K. E., Tumanov, S., Villas-Bôas, S. & Davy, S. K. Metabolite profiling of symbiont and host during thermal stress and bleaching in a model cnidarian-dinoflagellate symbiosis. J. Exp. Biol. 219, 516–27 (2016).PubMed 

Google Scholar 
Bertucci, A., Forêt, S., Ball, E. E. & Miller, D. J. Transcriptomic differences between day and night in Acropora millepora provide new insights into metabolite exchange and light-enhanced calcification in corals. Mol. Ecol. 24, 4489–4504 (2015).CAS 
PubMed 
Article 

Google Scholar 
Matthews, J. L. et al. Optimal nutrient exchange and immune responses operate in partner specificity in the cnidarian-dinoflagellate symbiosis. Proc. Natl Acad. Sci. 114, 13194–13199 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lin, M.-F., Takahashi, S., Forêt, S., Davy, S. K. & Miller, D. J. Transcriptomic analyses highlight the likely metabolic consequences of colonization of a cnidarian host by native or non-native Symbiodinium species. Biol. Open 8, bio038281 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Medrano, E., Merselis, D. G., Bellantuono, A. J. & Rodriguez-Lanetty, M. Proteomic Basis of Symbiosis: A Heterologous Partner Fails to Duplicate Homologous Colonization in a Novel Cnidarian– Symbiodiniaceae Mutualism. Front. Microbiol. 10, 1153 (2019).Schoepf, V., Stat, M., Falter, J. L. & McCulloch, M. T. Limits to the thermal tolerance of corals adapted to a highly fluctuating, naturally extreme temperature environment. Sci. Rep. 5, 17639 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Xiang, T., Hambleton, E. A., DeNofrio, J. C., Pringle, J. R. & Grossman, A. R. Isolation of clonal axenic strains of the symbiotic dinoflagellate Symbiodinium and their growth and host specificity1. J. Phycol. 49, 447–458 (2013).CAS 
PubMed 
Article 

Google Scholar 
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).CAS 
PubMed 
Article 

Google Scholar 
Pimentel, H., Bray, N. L., Puente, S., Melsted, P. & Pachter, L. Differential analysis of RNA-seq incorporating quantification uncertainty. Nat. Methods 14, 687–690 (2017).CAS 
PubMed 
Article 

Google Scholar  More

El Bilali, H., Callenius, C., Strassner, C. & Probst, L. Food and nutrition security and sustainability transitions in food systems. Food Energy Secur 8, e00154 (2019).Article 

Google Scholar 
De Raymond, A. B. & Goulet, F. Science, technology and food security: An introduction. Sci. Technol. Soc. 25, 7–18 (2020).Article 

Google Scholar 
Wang, C. et al. Occurrence of crop pests and diseases has largely increased in China since 1970. Nat. Food 3, 57–65 (2022).Article 

Google Scholar 
Deutsch, C. A. et al. Increase in crop losses to insect pests in a warming climate. Science 361, 916–919 (2018).CAS 
PubMed 
Article 

Google Scholar 
Verger, P. J. P. & Boobis, A. R. Reevaluate pesticides for food security and safety. Science 341, 717–718 (2013).CAS 
PubMed 
Article 

Google Scholar 
Humann‐Guilleminot, S. et al. A nation‐wide survey of neonicotinoid insecticides in agricultural land with implications for agri‐environment schemes. J. Appl. Ecol. 56, 1502–1514 (2019).Article 
CAS 

Google Scholar 
Haynes, K. J., Allstadt, A. J. & Klimetzek, D. Forest defoliator outbreaks under climate change: Effects on the frequency and severity of outbreaks of five pine insect pests. Glob. Change Biol. 20, 2004–2018 (2014).Article 

Google Scholar 
Sheppard, L., Bell, J. R., Harrington, R. & Reuman, D. C. Changes in large-scale climate alter spatial synchrony of aphid pests. Nat. Clim. Change 6, 610–613 (2016).Article 

Google Scholar 
Skendžić, S. et al. The impact of climate change on agricultural insect pests. Insects 12, 440 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
WASDE. World Agricultural Supply and Demand Estimates 1554–9089 (World Agricultural Outlook Board, 2012).FAOSTAT. Food and agriculture organisation of the United Nations. http://faostat.fao.org/ (2018).Bellard, C. et al. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Bebber, D. P. Range-expanding pests and pathogens in a warming world. Annu. Rev. Phytopathol. 53, 335–356 (2015).CAS 
PubMed 
Article 

Google Scholar 
Jactel, H., Koricheva, J. & Castagneyrol, B. Responses of forest insect pests to climate change: Not so simple. Curr. Opin. Insect Sci. 35, 103–108 (2019).PubMed 
Article 

Google Scholar 
Stephane, A. P., Derocles, D. H., Lunt Sophie, C. F. & Moss., B. Climate warming alters the structure of farmland tritrophic ecological networks and reduces crop yield. Mol. Ecol. 27, 4931–4946 (2018).Article 

Google Scholar 
Nechols, J. R. The potential impact of climate change on non-target risks from imported generalist natural enemies and on biological control. Bio. Control 66, 37–44 (2021).
Google Scholar 
Tian, B. et al. Elevated temperature reduces wheat grain yield by increasing pests and decreasing soil mutualists. Pest Manag. Sci. 75, 466–475 (2019).CAS 
PubMed 
Article 

Google Scholar 
Lehmann, P. et al. Complex responses of global insect pests to climate warming. Front. Ecol. Environ. 18, 141–150 (2020).Article 

Google Scholar 
Zhao, F., Zhang, W., Hoffmann, A. A. & Ma, C. Night warming on hot days produces novel impacts on development, survival, and reproduction in a small arthropod. J. Anim. Ecol. 83, 769–778 (2014).PubMed 
Article 

Google Scholar 
Marini, L. et al. Climate drivers of bark beetle outbreak dynamics in Norway spruce forests. Ecography 40, 1426–1435 (2017).Article 

Google Scholar 
Bale, J. S. et al. Herbivory in global climate change research: Direct effects of rising temperature on insect herbivores. Glob. Change Biol. 8, 1–16 (2002).Article 

Google Scholar 
Jamieson, M. A., Trowbridge, A. M., Raffa, K. F. & Lindroth, R. L. Consequences of climate warming and altered precipitation patterns for plant-insect and multitrophic interactions. Plant Physiol. 160, 1719–1727 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gagic, V. et al. Better outcomes for pest pressure, insecticide use, and yield in less intensive agricultural landscapes. Proc. Natl Acad. Sci. USA 118, 1–6 (2021).Article 
CAS 

Google Scholar 
Paredes, D. et al. Landscape simplification increases vineyard pest outbreaks and insecticide use. Ecol. Lett. 24, 73–83 (2021).PubMed 
Article 

Google Scholar 
Brattsten, L. B., Holyoke, C. W., Leeper, J. R. & Raffa, K. F. Insecticide resistance: Challenge to pest management and basic research. Science 231, 1255–1260 (1986).CAS 
PubMed 
Article 

Google Scholar 
Haddi, K. et al. Rethinking biorational insecticides for pest management: Unintended effects and consequences. Pest Manag. Sci. 76, 2286–2293 (2020).CAS 
PubMed 
Article 

Google Scholar 
Gould, F., Brown, Z. S. & Kuzma, J. Wicked evolution: Can we address the sociobiological dilemma of pesticide resistance? Science 360, 728–732 (2018).CAS 
PubMed 
Article 

Google Scholar 
Wei, N. et al. Transcriptome analysis and identification of insecticide tolerance-related genes after exposure to insecticide in Sitobion avenae. Genes 1012, 951 (2019).Article 
CAS 

Google Scholar 
Gong, X. et al. Feasibility of reinforced post-endogenous denitrification coupling with synchronous nitritation, denitrification and phosphorus removal for high-nitrate sewage treatment using limited carbon source in municipal wastewater. Chemosphere 269, 128687 (2021).CAS 
PubMed 
Article 

Google Scholar 
Tilman, D. et al. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).CAS 
PubMed 
Article 

Google Scholar 
Geiger, F. et al. Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland. Basic Appl. Ecol. 11, 97–105 (2010).CAS 
Article 

Google Scholar 
Muneret, L. et al. Evidence that organic farming promotes pest control. Nat. Sustain 1, 361–368 (2018).Article 

Google Scholar 
Lu, Y. et al. Widespread adoption of Bt cotton and insecticide decrease promotes biocontrol services. Nature 487, 362–365 (2012).CAS 
PubMed 
Article 

Google Scholar 
Chaplin‐Kramer, R., O’Rourke, M. E., Blitzer, E. J. & Kremen, C. A meta‐analysis of crop pest and natural enemy response to landscape complexity. Ecol. Lett. 14, 922–932 (2011).PubMed 
Article 

Google Scholar 
Baillod, A. B., Tscharntke, T., Clough, Y. & Batary, P. Landscape‐scale interactions of spatial and temporal cropland heterogeneity drive biological control of cereal aphids. J. Appl. Ecol. 54, 1804–1813 (2017).Article 

Google Scholar 
Gagic, V. et al. Combined effects of agrochemicals and ecosystem services on crop yield across Europe. Ecol. Lett. 20, 1427–1436 (2017).PubMed 
Article 

Google Scholar 
Zhang, W. et al. Multidecadal, county-level analysis of the effects of land use, Bt cotton, and weather on cotton pests in China. Proc. Natl Acad. Sci. USA 115, 700–7709 (2018).
Google Scholar 
Horgan, F. G. et al. Population development of rice black bug, Scotinophara latiuscula (Breddin), under varying nitrogen in a field experiment. Entomol. Gen. 37, 19–33 (2018).Article 

Google Scholar 
Butler, J., Garratt, M., & Leather, S. Fertilisers and insect herbivores: A meta‐analysis. Ann. Appl. Biol. 161, 223–233 (2012).Article 

Google Scholar 
Aqueel, M. A. et al. Effect of plant nutrition on aphid size, prey consumption, and life history characteristics of green lacewing. Insect Sci. 21, 74–82 (2014).PubMed 
Article 

Google Scholar 
Benton, T. G., Vickery, J. A. & Wilson, J. D. Farmland biodiversity: Is habitat heterogeneity the key? Trends Ecol. Evol. 18, 182–188 (2003).Article 

Google Scholar 
Winqvist, C. et al. Mixed effects of organic farming and landscape complexity on farmland biodiversity and biological control potential across Europe. J. Appl. Ecol. 48, 570–579 (2011).Article 

Google Scholar 
Tscharntke, T. et al. Landscape perspectives on agricultural intensification and biodiversity-ecosystem service management. Ecol. Lett. 8, 857–874 (2005).Article 

Google Scholar 
Meehan, T. D., Werling, B. P., Landis, D. A. & Gratton, C. Agricultural landscape simplification and insecticide use in the Midwestern United States. Proc. Natl Acad. Sci. USA 108, 11500–11505 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Macfadyen, S. et al. Do differences in food web structure between organic and conventional farms affect the ecosystem service of pest control? Ecol. Lett. 12, 229–238 (2009).PubMed 
Article 

Google Scholar 
Liu, J., Ning, J., Kuang, W. & Xu, X. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015. J. Geogr. Sci. 73, 789–802 (2018).
Google Scholar 
Ma, C., Ma, G. & Zhao, F. Impact of global warming on cereal aphids. Chin. J. Appl. Entomol. 51, 1435–1443 (2014).
Google Scholar 
Han, Z. et al. Effects of simulated climate warming on the population dynamics of Sitobion avenae (Fabricius) and its parasitoids in wheat fields. Pest Manag. Sci. 75, 3252–3259 (2019).CAS 
PubMed 
Article 

Google Scholar 
Meisner, M. H., Harmon, J. P. & Ives, A. R. Temperature effects on long‐term population dynamics in a parasitoid-host system. Ecol. Monogr. 84, 457–476 (2014).Article 

Google Scholar 
Xiao, H. et al. Exposure to mild temperatures decreases overwintering larval survival and post-diapause reproductive potential in the rice stem borer Chilo suppressalis. J. Pest Sci. 90, 117–125 (2017).Article 

Google Scholar 
Senior, V. L. et al. Phenological responses in a sycamore-aphid-parasitoid system and consequences for aphid population dynamics: A 20 year case study. Glob. Change Biol. 26, 2814–2828 (2020).Article 

Google Scholar 
Chiu, M. C., Chen, Y. H. & Kuo, M. H. The effect of experimental warming on a low‐latitude aphid, Myzus varians. Entomol. Exp. Appl. 142, 216–222 (2012).Article 

Google Scholar 
Adler, L. S., De Valpine, P., Harte, J. & Call, J. Effects of long-term experimental warming on aphid density in the field. J. Kans. Entomol. Soc. 80, 156–169 (2007).Article 

Google Scholar 
Clement, S. L., Husebye, D. S. & Eigenbrode, S. D. Aphid Biodiversity under Environmental Change 107–129 (Springer, 2010).Van der Putten, W. H., Macel, M. & Visser, M. E. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels. Philos. T. Roy. Soc. B. 365, 2025–2034 (2010).Article 

Google Scholar 
Evans, E. W. Multitrophic interactions among plants, aphids, alternate prey and shared natural enemies—a review. Eur. J. Entomol. 105, 369–380 (2013).Article 

Google Scholar 
Sigsgaard, L. A survey of aphids and aphid parasitoids in cereal fields in Denmark, and the parasitoids’ role in biological control. J. Appl. Entomol. 126, 101–107 (2002).Article 

Google Scholar 
Diehl, E., Sereda, E., Wolters, V. & Birkhofer, K. Effects of predator specialization, host plant and climate on biological control of aphids by natural enemies: a meta‐analysis. J. Appl. Ecol. 50, 262–270 (2013).Article 

Google Scholar 
Hopper, K. R. et al. Natural enemy impact on the abundance of Diuraphis noxia (Homoptera: Aphididae) in wheat in Southern France. Environ. Entomol. 24, 402–408 (1995).Article 

Google Scholar 
Latham, D. R. & Mills, N. J. Quantifying aphid predation: The mealy plum aphid Hyalopterus pruni in California as a case study. J. Appl. Ecol. 47, 200–208 (2010).Article 

Google Scholar 
Östman, Ö., Ekbom, B. & Bengtsson, J. Yield increase attributable to aphid predation by ground-living polyphagous natural enemies in spring barley in Sweden. Ecol. Econ. 45, 149–158 (2003).Article 

Google Scholar 
Snyder, W. E. & Ives, A. R. Interactions between specialist and generalist natural enemies: Parasitoids, predators, and pea aphid control. Ecology 84, 91–107 (2003).Article 

Google Scholar 
Freier, B., Triltsch, H., Möwes, M. & Moll, E. The potential of predators in natural control of aphids in wheat: results of a ten-year field study in two German landscapes. Biocontrology 52, 775–788 (2007).Article 

Google Scholar 
Barczak, T., Dębek-Jankowska, A. & Bennewicz, J. Primary parasitoid and hyperparasitoid guilds (Hymenoptera) of grain aphid (Sitobion avenae F.) in northern Poland. Arch. Biol. Sci. 66, 1141–1148 (2014).Article 

Google Scholar 
Sánchez-Bayo, F. & Wyckhuys, K. A. G. Worldwide decline of the entomofauna: A review of its drivers. Biol. Conserv. 232, 8–27 (2019).Article 

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

Google Scholar 
Zhang, W., Jiang, F. & Ou, J. Global pesticide consumption and pollution: With China as a focus. P. Intern. Acad. Ecol. Environ. Sci. 1, 125–144 (2011).CAS 

Google Scholar 
El-Wakeil, N., Gaafar, N., Sallam, A. & Volkmar, C. Side Effects of Insecticides on Natural Enemies and Possibility of their Integration in Plant Protection Strategies. Insecticides: Development of Safer and More Effective Technologies Agricultural and Biological Sciences (ed Trdan, S.) 1–56 (Intech Open Access Publisher, 2013).Peshin, R. & Dhawan, A. K. Integrated Pest Management: Innovation-Development Process (Springer Science & Business Media, 2009).Jia, B., Hong, S., Zhang, Y. & Cao, Y. Toxicity and safety of 12 insecticides to Diadegma semiclausum. J. Shanxi Agric. Sci. 43, 999–1002 (2015).
Google Scholar 
Emery, S. E. et al. High agricultural intensity at the landscape scale benefits pests, but low intensity practices at the local scale can mitigate these effects. Agric. Ecosyst. Environ. 306, 107199 (2021).Article 

Google Scholar 
Aqueel, M. A. & Leather, S. R. Effect of nitrogen fertilizer on the growth and survival of Rhopalosiphum padi (L.) and Sitobion avenae (F.)(Homoptera: Aphididae) on different wheat cultivars. Crop. Prot. 30, 216–221 (2011).Article 

Google Scholar 
Gao, J., Guo, H. J., Sun, Y. C. & Ge, F. Juvenile hormone mediates the positive effects of nitrogen fertilization on weight and reproduction in pea aphid. Pest Manag. Sci. 74, 2511–2519 (2018).CAS 
PubMed 
Article 

Google Scholar 
Barnett, K. L. & Facey, S. L. Grasslands, invertebrates, and precipitation: A review of the effects of climate change. Front. Plant. Sci. 7, 1196 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Yu, X. et al. Engineering plants for aphid resistance: Current status and future perspectives. Theor. Appl. Genet. 127, 2065–2083 (2014).CAS 
PubMed 
Article 

Google Scholar 
Martin, E. A. et al. The interplay of landscape composition and configuration: New pathways to manage functional biodiversity and agroecosystem services across Europe. Ecol. Lett. 22, 1083–1094 (2019).PubMed 
Article 

Google Scholar 
Steckel, J. et al. Landscape composition and configuration differently affect trap-nesting bees, wasps and their antagonists. Biol. Conserv. 172, 56–64 (2014).Article 

Google Scholar 
Lu, Y. H. et al. Major ecosystems in China: Dynamics and challenges for sustainable management. Environ. Manag. 48, 13–27 (2011).Article 

Google Scholar 
Wood, G. A. et al. Real-time measures of canopy size as a basis for spatially varying nitroge applications to winter wheat sown at different seed rates. Biosyst. Eng. 84, 513–531 (2003).Article 

Google Scholar 
NOAA. https://www.ncdc.noaa.gov/cdo-web/ (2018).WORLD BANK GROUP. https://climateknowledgeportal.worldbank.org/download-data (2018). More