Ecology

Data were analyzed from samples collected, processed, and published previously [21, 25, 29] and have been summarized here. The present analysis, which consisted of sequence data processing, the calculation of taxon-specific isotopic signatures, and subsequent analyses, reflects original work.Sample collection and isotope incubationTo generate experimental data, three replicate soil samples were collected from the top 10 cm of plant-free patches in four ecosystems along the C. Hart Merriam elevation gradient in Northern Arizona. From low to high elevation, these sites are located in the following environments: desert grassland (GL; 1760 m), piñon-pine juniper woodland (PJ; 2020 m), ponderosa pine forest (PP; 2344 m), and mixed conifer forest (MC; 2620 m). Soil samples were air-dried for 24 h at room temperature, homogenized, and passed through a 2 mm sieve before being stored at 4 °C for another 24 h. This produced three distinct but homogenous soil samples from each of the four ecosystems that were subject to experimental treatments. Three treatments were applied to bring soils to 70% water-holding capacity: water alone (control), water with glucose (C treatment; 1000 µg C g−1 dry soil), or water with glucose and a nitrogen source (CN treatment; [NH4]2SO4 at 100 µg N g−1 dry soil). To track growth through isotope assimilation, both 18O-enriched water (97 atom %) and 13C-enriched glucose (99 atom %) were used. In all treatments isotopically heavy samples were paired with matching “light” samples that received water with a natural abundance isotope signatures. For 18O incubations, this design resulted in three soil samples per ecosystem per treatment (across four ecosystems and three treatments, n = 36) while 13C incubations were limited to only C and CN treatments (n = 24). Previous analyses suggest that three replicates is sufficient to detect growth of 10 atom % 18O in microbial DNA with a power of 0.6 and a growth of 5 atom % 18O with a power of 0.3 (12 and 6 atom % respectively for 13C) [30]. All soils were incubated in the dark for one week. Following incubation, soils were frozen at −80 °C for one week prior to DNA extraction.Quantitative stable isotope probingThe procedure of qSIP (quantitative stable isotope probing) is described here but has been applied to these samples as previously published [17, 21, 25]. DNA extraction was performed on soils using a DNeasy PowerSoil HTP 96 Kit (MoBio Laboratories, Carlsbad, CA, USA) and following manufacturer’s protocol. Briefly, 0.25 g of soils from each sample were carefully added to deep, 96-well plates containing zirconium dioxide beads and a cell lysis solution with sodium dodecyl sulfate (SDS) and shaken for 20 min. Following cell lysis, supernatant was collected and centrifuged three times in fresh 96-well plates with reagents separating DNA from non-DNA organic and inorganic materials. Lastly, DNA samples were collected on silica filter plates, rinsed with ethanol and eluted into 100 µL of a 10 mM Tris buffer in clean 96-well plates. To quantify the degree of 18O or 13C isotope incorporation into bacterial DNA (excess atom fraction or EAF), the qSIP protocol [31] was used, though modified slightly as reported previously [21, 24, 32]. Briefly, microbial growth was quantified as the change in DNA buoyant density due to incorporation of the 18O or 13C isotopes through the method of density fractionation by adding 1 µg of DNA to 2.6 mL of saturated CsCl solution in combination with a gradient buffer (200 mM Tris, 200 mM KCL, 2 mM EDTA) in a 3.3 mL OptiSeal ultracentrifuge tube (Beckman Coulter, Fullerton, CA, USA). The solution was centrifuged to produce a gradient of increasingly labeled (heavier) DNA in an Optima Max bench top ultracentrifuge (Beckman Coulter, Brea, CA, USA) with a Beckman TLN-100 rotor (127,000 × g for 72 h) at 18 °C. Each post-incubation sample was thus converted from a continuous gradient into approximately 20 fractions (150 µL) using a modified fraction recovery system (Beckman Coulter). The density of each fraction was measured with a Reichart AR200 digital refractometer (Reichert Analytical Instruments, Depew, NY, USA). Fractions with densities between 1.640 and 1.735 g cm−3 were retained as densities outside this range generally did not contain DNA. In all retained fractions, DNA was cleaned and purified using isopropanol precipitation and the abundance of bacterial 16S rRNA gene copies was quantified with qPCR using primers specific to bacterial 16S rRNA genes (Eub 515F: AAT GAT ACG GCG ACC ACC GAG TGC CAG CMG CCG CGG TAA, 806R: CAA GCA GAA GAC GGC ATA CGA GGA CTA CVS GGG TAT CTA AT). Triplicate reactions were 8 µL consisting of 0.2 mM of each primer, 0.01 U µL−1 Phusion HotStart II Polymerase (Thermo Fisher Scientific, Waltham, MA), 1× Phusion HF buffer (Thermo Fisher Scientific), 3.0 mM MgCl2, 6% glycerol, and 200 µL of dNTPs. Reactions were performed on a CFX384 Touch Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) under the following cycling conditions: 95 °C at 1 min and 44 cycles at 95 °C (30 s), 64.5 °C (30 s), and 72 °C (1 min). Separate from qPCR, retained sample-fractions were subject to a similar amplification step of the 16S rRNA gene V4 region (515F: GTG YCA GCM GCC GCG GTA A, 806R: GGA CTA CNV GGG TWT CTA AT) in preparation for sequencing with the same reaction mix but differing cycle conditions – 95 °C for 2 min followed by 15 cycles at 95 °C (30 s), 55 °C (30 s), and 60 °C (4 min). The resulting 16S rRNA gene V4 amplicons were sequenced on a MiSeq sequencing platform (Illumina, Inc., San Diego, CA, USA). DNA sequence data and sample metadata have been deposited in the NCBI Sequence Read Archive under the project ID PRJNA521534.Sequence processing and qSIP analysisIndependently from previous publications, we processed raw sequence data of forward and reverse reads (FASTQ) within the QIIME2 environment [33] (release 2018.6) and denoised sequences within QIIME2 using the DADA2 pipeline [34]. We clustered the remaining sequences into amplicon sequence variants (ASVs, at 100% sequence identity) against the SILVA 138 database [35] using a pre-trained open-reference Naïve Bayes feature classifier [36]. We removed samples with less than 3000 sequence reads, non-bacterial lineages, and global singletons and doubletons. We converted ASV sequencing abundances in each fraction to the number of 16S rRNA gene copies per gram dry soil based on qPCR abundances and the known amount of dry soil equivalent added to the initial extraction. This allowed us to express absolute population densities, rather than relative abundances. Across all replicates, we identified 114 543 unique bacterial ASVs.We calculated the 18O and 13C excess atom fraction (EAF) for each bacterial ASV using R version 4.0.3 [37] and data.table [38] with custom scripts available at https://www.github.com/bramstone/. Negative enrichment values were corrected using previously published methods [17]. ASVs that appeared in less than two of the three replicates of an ecosystem-treatment combination (n = 3) and less than three density fractions within those two replicates were removed to avoid assigning spurious estimates of isotope enrichment to infrequent taxa. Any ASVs filtered out of one ecosystem-treatment group were allowed to be present in another if they met the frequency threshold. Applying these filtering criteria, we limited our analysis towards 3759 unique bacterial ASVs which accounted for a small proportion of the total diversity but represented 68.0% of all sequence reads, and encompassed most major bacterial groups (Supplementary Fig. 1).Analysis of life history strategies and nutrient responseAll statistical tests were conducted in R version 4.0.3 [37]. We assessed the ability of phylum-level assignment of life history strategy to predict growth in response to C and N addition, as proxied by the incorporation of heavy isotope during DNA replication [39, 40]. Phylum-level assignments (Table 1) were based on the most frequently observed behavior of lineages with a representative phylum (or subphylum) as compiled previously [23]. We averaged 18O EAF values of bacterial taxa for each treatment and ecosystem and then subtracted the values in control soils from values in C-amended soils to determine C response (∆18O EAFC) and from the 18O EAF of bacteria in CN-amended soils to determine C and N response (Δ18O EAFCN). Because an ASV must have a measurable EAF in both the control and treatment for a valid Δ18O EAF to be calculated, we were only able to resolve the nutrient response for 2044 bacterial ASVs – 1906 in response to C addition and 1427 in response to CN addition.We used Gaussian finite mixture modeling, as implemented by the mclust R package [41], to demarcate plausible multi-isotopic signatures for oligotrophs and copiotrophs. For each treatment, we calculated average per-taxon 13C and 18O EAF values. To compare both isotopes directly, we divided 18O EAF values by 0.6 based on the estimate that this value (designated as µ) represents the fraction of oxygen atoms in DNA derived from the 18O-water, rather than from 16O within available C sources [42]. Two mixture components, corresponding to oligotrophic and copiotrophic growth modes, were defined using the Mclust function using ellipsoids of equal volume and shape. We observed several microorganisms with high 18O enrichment but comparatively low 13C enrichment, potentially indicating growth following the depletion of the added glucose, and that were reasonably clustered as oligotrophs in our mixture model.We tested how frequently mixture model clustering of each microorganism’s growth (based on average 18O–13C EAF in a treatment) could predict its growth across replicates (n = 12 in each treatment—although individual). We applied the treatment-level mixture models defined above to the per-taxon isotope values in each replicate, recording when a microorganism’s life history strategy in a replicate agreed with the treatment-level cluster, and when it didn’t. We used exact binomial tests to test whether the number of “successes” (defined as a microorganism being grouped in the same life history category as its treatment-level cluster) was statistically significant. To account for type I error across all individual tests (one per ASV per treatment), we adjusted P values in each treatment using the false-discovery rate (FDR) method [43].To determine the extent that life history categorizations may be appropriately applied at finer levels of taxonomic resolution, we constructed several hierarchical linear models using the lmer function in the nlme package version 3.1-149 [44]. To condense growth information from both isotopes into a single analysis, 18O and 13C EAF values were combined into a single variable using principal components analysis separately for each treatment. Across the C and CN treatments, the first principal component (PC1) was able to explain – respectively – 86% and 91% of joint variation of 18O and 13C EAF values. In all cases, we applied PC1 as the response variable and treated taxonomy and ecosystem as random model terms to limit the potential of pseudo-replication to bias significance values. We used likelihood ratio analysis and Akaike information criterion (AIC) values to compare models where life history strategy was determined based on observed nutrient responses at different taxonomic levels (Eq. 1) against a model with the same random terms but without any life history strategy data (Eq. 2). Separate models were applied to each treatment. To reduce model overfitting, we removed families represented by fewer than three bacterial ASVs as well as phyla represented by only one order. In addition, we removed bacterial ASVs with unknown taxonomic assignments (following Morrissey et al. [21]). This limited our analysis to 1 049 ASVs in the C amendment and 984 in the CN amendment.$${{{{{rm{PC}}}}}}{1}_{{18{{{{{rm{O}}}}}} – 13{{{{{rm{C}}}}}}}}sim {{{{{rm{strategy}}}}}} + 1|{{{{{rm{phylum}}}}}}/{{{{{rm{class}}}}}}/{{{{{rm{order}}}}}}/{{{{{rm{family}}}}}}/{{{{{rm{genus}}}}}}/{{{{{rm{eco}}}}}}$$
(1)
$${{{{{rm{PC}}}}}}{1}_{{18{{{{{rm{O}}}}}} – 13{{{{{rm{C}}}}}}}}sim 1 + 1|{{{{{rm{phylum}}}}}}/{{{{{rm{class}}}}}}/{{{{{rm{order}}}}}}/{{{{{rm{family}}}}}}/{{{{{rm{genus}}}}}}/{{{{{rm{eco}}}}}}$$
(2)
Here, life history strategy was defined at each taxonomic level using the mixture models above and based on the mean 18O and 13C EAF values of each bacterial lineage (Supplemental Fig. 2). We compared these models with the no-strategy model (Eq. 2) directly using likelihood ratio testing. More

Pitois, S. G., Lynam, C. P., Jansen, T., Halliday, N. & Edwards, M. Bottom-up effects of climate on fish populations: data from the Continuous Plankton Recorder. Mar. Ecol. Prog. Ser. 456, 169–186 (2012).ADS 

Google Scholar 
Ruzicka, J. J. et al. Interannual variability in the Northern California Current food web structure: changes in energy flow pathways and the role of forage fish, euphausiids, and jellyfish. Prog. Oceanogr. 102, 19–41 (2012).ADS 

Google Scholar 
Lauria, V., Attrill, M. J., Brown, A., Edwards, M. & Votier, S. C. Regional variation in the impact of climate change: evidence that bottom-up regulation from plankton to seabirds is weak in parts of the Northeast Atlantic. Mar. Ecol. Prog. Ser. 488, 11–22 (2013).ADS 

Google Scholar 
Heneghan, R. F., Everett, J. D., Blanchard, J. L. & Richardson, A. J. Zooplankton are not fish: improving zooplankton realism in size-spectrum models mediates energy transfer in food webs. Front. Mar. Sci. https://doi.org/10.3389/fmars.2016.00201 (2016).Lehette, P., Tovar-Sánchez, A., Duarte, C. M. & Hernández-León, S. Krill excretion and its effect on primary production. Mar. Ecol. Prog. Ser. 459, 29–38 (2012).ADS 
CAS 

Google Scholar 
Arístegui, J., Duarte, C. M., Reche, I. & Gómez-Pinchetti, J. L. Krill excretion boosts microbial activity in the Southern Ocean. PLoS ONE 9, e89391 (2014).ADS 

Google Scholar 
Tovar-Sánchez, A., Duarte, C. M., Hernández-León, S. & Sañudo-Wilhelmy, S. A. Krill as a central node for iron cycling in the Southern Ocean. Geophys. Res. Lett. 34, 1–4 (2007).Schmidt, K. et al. Seabed foraging by Antarctic krill: Implications for stock assessment, bentho-pelagic coupling, and the vertical transfer of iron. Limnol. Oceanogr. 56, 1411–1428 (2011).ADS 
CAS 

Google Scholar 
Cavan, E. L. et al. The importance of Antarctic krill in biogeochemical cycles. Nat. Commun. 10, 4742 (2019). This Review demonstrates how the dominant grazer in Antarctica plays a critical role in biogeochemical cycles.ADS 
CAS 

Google Scholar 
Ratnarajah, L., Nicol, S. & Bowie, A. R. Pelagic iron recycling in the southern ocean: exploring the contribution of marine animals. Front. Mar. Sci. https://doi.org/10.3389/fmars.2018.00109 (2018).Halfter, S., Cavan, E. L., Swadling, K. M., Eriksen, R. S. & Boyd, P. W. The role of zooplankton in establishing carbon export regimes in the southern ocean – a comparison of two representative case studies in the subantarctic region. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.567917 (2020).Schmidt, K. et al. Zooplankton gut passage mobilizes lithogenic iron for ocean productivity. Curr. Biol. 26, 2667–2673 (2016).CAS 

Google Scholar 
Brun, P. et al. Climate change has altered zooplankton-fuelled carbon export in the North Atlantic. Nat. Ecol. Evol. 3, 416–423 (2019).
Google Scholar 
Chust, G. et al. Are Calanus spp. shifting poleward in the North Atlantic? A habitat modelling approach. ICES J. Mar. Sci. 71, 241–253 (2014).
Google Scholar 
Batten, S. D. & Walne, A. W. Variability in northwards extension of warm water copepods in the NE Pacific. J. Plankton Res. 33, 1643–1653 (2011).
Google Scholar 
Fu, W., Randerson, J. T. & Moore, J. K. Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models. Biogeosciences 13, 5151–5170 (2016).ADS 

Google Scholar 
Tagliabue, A. et al. Persistent uncertainties in ocean net primary production climate change projections at regional scales raise challenges for assessing impacts on ecosystem services. Front. Clim. https://doi.org/10.3389/fclim.2021.738224 (2021).Edwards, M. & Richardson, A. J. Impact of climate change on marine pelagic phenology and trophic mismatch. Nature 430, 881–884 (2004).ADS 
CAS 

Google Scholar 
Mackas, D. L. et al. Changing zooplankton seasonality in a changing ocean: comparing time series of zooplankton phenology. Prog. Oceanogr. 97-100, 31–62 (2012).ADS 

Google Scholar 
Freer, J. J., Daase, M. & Tarling, G. A. Modelling the biogeographic boundary shift of Calanus finmarchicus reveals drivers of Arctic Atlantification by subarctic zooplankton. Glob. Change Biol. 28, 429–440 (2021).
Google Scholar 
Daufresne, M., Lengfellner, K. & Sommer, U. Global warming benefits the small in aquatic ecosystems. Proc. Natl Acad. Sci. USA 106, 12788–12793 (2009).ADS 
CAS 

Google Scholar 
Brandão, M. C. et al. Macroscale patterns of oceanic zooplankton composition and size structure. Sci. Rep. 11, 15714 (2021). This study showed that zooplankton abundance and median size decreased towards warmer and less productive environments due to changes in copepod composition, but some groups displayed the opposite relationships potentially due to alternative feeding strategies.ADS 

Google Scholar 
Campbell, M. D. et al. Testing Bermann’s rule in marine copepods. Ecography 44, 1283–1295 (2021). This global study found that temperature better predicted copepod size than did latitude or oxygen, with body size decreasing by 43.9% across the temperature range (−1.7 to 30 °C).
Google Scholar 
Barange, M. et al. Impacts of Climate Change on Fisheries and Aquaculture. Synthesis of Current Knowledge, Adaptation, and Mitigation Options. (FAO, 2018).Atkinson, A. et al. Questioning the role of phenology shifts and trophic mismatching in a planktonic food web. Prog. Oceanogr. 137, 498–512 (2015).ADS 

Google Scholar 
Thackeray, S. J. et al. Phenological sensitivity to climate across taxa and trophic levels. Nature 535, 241–245 (2016).ADS 
CAS 

Google Scholar 
Sasaki, M. & Dam, H. G. Global patterns in copepod thermal tolerance. J. Plankton Res. 43, 598–609 (2021).
Google Scholar 
Dam, H. G. et al. Rapid, but limited, zooplankton adaptation to simultaneous warming and acidification. Nat. Clim. Change 11, 780–786 (2021).ADS 

Google Scholar 
Cooley, S. et al. Ocean and Coastal Ecosystems and their Services. In: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. (Cambridge University Press, 2022). This IPCC report synthesizes changes in zooplankton phenology compared to other marine life.Mackas, D. L., Goldblatt, R. & Lewis, A. G. Interdecadal variation in developmental timing of Neocalanus plumchrus populations at Ocean Station P in the subarctic North Pacific. Can. J. Fish. Aquat. Sci. 55, 1878–1893 (1998).
Google Scholar 
Edwards, M. et al. Ecological Status Report: results from the CPR survey 2007/2008. 1-12 (2009).Richardson, A. J. In hot water: zooplankton and climate change. ICES J. Mar. Sci. 65, 279–295 (2008).
Google Scholar 
Costello, J. H., Sullivan, B. K. & Gifford, D. J. A physical–biological interaction underlying variable phenological responses to climate change by coastal zooplankton. J. Plankton Res. 28, 1099–1105 (2006).
Google Scholar 
Chevillot, X. et al. Toward a phenological mismatch in estuarine pelagic food web? PLoS ONE 12, e0173752 (2017).
Google Scholar 
Ji, R., Edwards, M., Mackas, D. L., Runge, J. A. & Thomas, A. C. Marine plankton phenology and life history in a changing climate: current research and future directions. J. Plankton Res. 32, 1355–1368 (2010).
Google Scholar 
Thibodeau, P. S. et al. Long-term observations of pteropod phenology along the Western Antarctic Peninsula. Deep Sea Res. Part I: Oceanogr. Res. Pap. 166, 103363 (2020).
Google Scholar 
Beaugrand, G., Reid Philip, C., Ibañez, F., Lindley, J. A. & Edwards, M. Reorganization of North Atlantic marine copepod biodiversity and climate. Science 296, 1692–1694 (2002).ADS 
CAS 

Google Scholar 
Edwards, M. et al. North Atlantic warming over six decades drives decreases in krill abundance with no associated range shift. Commun. Biol. 4, 644 (2021). This regional study showed that ocean warming is causing a decrease in krill abundance but no poleward movement in range.
Google Scholar 
Chivers, W. J., Walne, A. W. & Hays, G. C. Mismatch between marine plankton range movements and the velocity of climate change. Nat. Commun. 8, 14434 (2017).ADS 
CAS 

Google Scholar 
Lindley, J. A. & Daykin, S. Variations in the distributions of Centropages chierchiae and Temora stylifera (Copepoda: Calanoida) in the north-eastern Atlantic Ocean and western European shelf waters. ICES J. Mar. Sci. 62, 869–877 (2005).
Google Scholar 
Atkinson, A. et al. Krill (Euphausia superba) distribution contracts southward during rapid regional warming. Nat. Clim. Change 9, 142–147 (2019). This regional study shows that the dominant grazer in Antarctic waters, Antarctic krill is moving southward due to regional warming.ADS 

Google Scholar 
Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature 432, 100–103 (2004).ADS 
CAS 

Google Scholar 
Pakhomov, E. A., Froneman, P. W., Wassmann, P., Ratkova, T. & Arashkevich, E. Contribution of algal sinking and zooplankton grazing to downward flux in the Lazarev Sea (Southern Ocean) during the onset of phytoplankton bloom: a lagrangian study. Mar. Ecol. Prog. Ser. 233, 73–88 (2002).ADS 

Google Scholar 
Tarling, G. A., Ward, P. & Thorpe, S. E. Spatial distributions of Southern Ocean mesozooplankton communities have been resilient to long-term surface warming. Glob. Change Biol. 24, 132–142 (2017). This study shows that 16 mesozooplankton taxa in the in the southwest Atlantic sector of the Southern Ocean are resilient to ocean warming.ADS 

Google Scholar 
Atkinson, A. et al. Stepping stones towards Antarctica: switch to southern spawning grounds explains an abrupt range shift in krill. Glob. Change Biol. 28, 1359–1375 (2021).
Google Scholar 
Jonkers, L., Hillebrand, H. & Kucera, M. Global change drives modern plankton communities away from the pre-industrial state. Nature 570, 372–377 (2019).ADS 
CAS 

Google Scholar 
Yebra, L. et al. Spatio-temporal variability of the zooplankton community in the SW Mediterranean 1992–2020: Linkages with environmental drivers. Prog. Oceanogr. 209, 1–10 (2022).Cowen, T. et al. Report on the status and trends of the Southern Ocean zooplankton based on the SCAR Southern Ocean Continuous Plankton Recorder (SO-CPR) survey. (2020).Corona, S., Hirst, A., Atkinson, D. & Atkinson, A. Density-dependent modulation of copepod body size and temperature–size responses in a shelf sea. Limnol. Oceanogr. 66, 3916–3927 (2021).ADS 

Google Scholar 
Horne, C. R., Hirst, A. G., Atkinson, D., Neves, A. & Kiørboe, T. A global synthesis of seasonal temperature–size responses in copepods. Glob. Ecol. Biogeogr. 25, 988–999 (2016).
Google Scholar 
Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Prog. Oceanogr. 141, 227–238 (2016).ADS 

Google Scholar 
Brodeur, R. D., Auth, T. D. & Phillips, A. J. Major shifts in pelagic micronekton and macrozooplankton community structure in an upwelling ecosystem related to an unprecedented marine heatwave. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00212 (2019).Lavaniegos, B. E., Jiménez-Herrera, M. & Ambriz-Arreola, I. Unusually low euphausiid biomass during the warm years of 2014–2016 in the transition zone of the California Current. Deep Sea Res. Part II: Top. Stud. Oceanogr. 169-170, 104638 (2019).
Google Scholar 
Peterson, W. T. et al. The pelagic ecosystem in the Northern California Current off Oregon during the 2014–2016 warm anomalies within the context of the past 20 years. J. Geophys. Res.: Oceans 122, 7267–7290 (2017).ADS 

Google Scholar 
O’ Loughlin, J. H. O. et al. Implications of Pyrosoma atlanticum range expansion on phytoplankton standing stocks in the Northern California Current. Prog. Oceanogr. 188, 1–9 (2020).Robertson, R. R. & Bjorkstedt, E. P. Climate-driven variability in Euphausia pacifica size distributions off northern California. Prog. Oceanogr. 188, 102412 (2020).
Google Scholar 
Stephens, J. A., Jordan, M. B., Taylor, A. H. & Proctor, R. The effects of fluctuations in North Sea flows on zooplankton abundance. J. Plankton Res. 20, 943–956 (1998).
Google Scholar 
Greene, C. H. & Pershing, A. J. The response of Calanus finmarchicus populations to climate variability in the Northwest Atlantic: basin-scale forcing associated with the North Atlantic Oscillation. ICES J. Mar. Sci. 57, 1536–1544 (2000).
Google Scholar 
Saba, G. K. et al. Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula. Nat. Commun. 5, 4318 (2014).ADS 
CAS 

Google Scholar 
Steinberg, D. K. et al. Long-term (1993–2013) changes in macrozooplankton off the Western Antarctic Peninsula. Deep Sea Res. Part I: Oceanogr. Res. Pap. 101, 54–70 (2015).ADS 

Google Scholar 
Steinke, K. B., Bernard, K. S., Ross, R. M. & B, Q. L. Environmental drivers of the physiological condition of mature female Antarctic krill during the spawning season: implications for krill recruitment. Mar. Ecol. Prog. Ser. 669, 65–82 (2021).ADS 

Google Scholar 
Brodeur, R. D. et al. Rise and fall of jellyfish in the eastern Bering Sea in relation to climate regime shifts. Prog. Oceanogr. 77, 103–111 (2008).ADS 

Google Scholar 
Quiñones, J. et al. Climate-driven population size fluctuations of jellyfish (Chrysaora plocamia) off Peru. Mar. Biol. 162, 2339–2350 (2015).
Google Scholar 
Lynam, C. P., Attrill, M. J. & Skogen, M. D. Climatic and oceanic influences on the abundance of gelatinous zooplankton in the North Sea. J. Mar. Biol. Assoc. UK 90, 1153–1159 (2009).
Google Scholar 
Schmidt, K. et al. Increasing picocyanobacteria success in shelf waters contributes to long-term food web degradation. Glob. Change Biol. 26, 5574–5587 (2020).ADS 

Google Scholar 
Laglera, L. M. et al. Iron partitioning during LOHAFEX: Copepod grazing as a major driver for iron recycling in the Southern Ocean. Mar. Chem. 196, 148–161 (2017).CAS 

Google Scholar 
Cavan, E. L., Henson, S. A., Belcher, A. & Sanders, R. Role of zooplankton in determining the efficiency of the biological carbon pump. Biogeosciences 14, 177–186 (2017).ADS 
CAS 

Google Scholar 
Valdés, V. et al. Nitrogen and phosphorus recycling mediated by copepods and response of bacterioplankton community from three contrasting areas in the western tropical South Pacific (20° S). Biogeosciences 15, 6019–6032 (2018).ADS 

Google Scholar 
Steinberg, D. K. & Landry, M. R. Zooplankton and the Ocean Carbon Cycle. Annu. Rev. Mar. Sci. 9, 413–444 (2017). This Review synthesizes the role of zooplankton within the ocean carbon cycle.ADS 

Google Scholar 
Ratnarajah, L. et al. Understanding the variability in the iron concentration of Antarctic krill. Limnol. Oceanogr. 61, 1651–1660 (2016).ADS 

Google Scholar 
Bernard, K. S., Steinberg, D. K. & Schofield, O. M. Summertime grazing impact of the dominant macrozooplankton off the Western Antarctic Peninsula. Deep Sea Res. Part I: Oceanogr. Res. Pap. 62, 111–122 (2012).ADS 

Google Scholar 
Böckmann, S. et al. Salp fecal pellets release more bioavailable iron to Southern Ocean phytoplankton than krill fecal pellets. Curr. Biol. 31, 2737–2746.e2733 (2021).
Google Scholar 
Cabanes, D. J. E. et al. First Evaluation of the Role of Salp Fecal Pellets on Iron Biogeochemistry. Front. Mar. Sci. https://doi.org/10.3389/fmars.2016.00289 (2017).Ratnarajah, L. Regenerated iron: how important are different zooplankton groups to oceanic productivity. Curr. Biol. 31, R848–R850 (2021).CAS 

Google Scholar 
Giering, S. L., Steigenberger, S., Achterberg, E. P., Sanders, R. & Mayor, D. J. Elevated iron to nitrogen recycling by mesozooplankton in the Northeast Atlantic Ocean. Geophys. Res. Lett. 39, 1–5 (2012).Svensen, C. et al. Zooplankton communities associated with new and regenerated primary production in the Atlantic inflow North of Svalbard. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00293 (2019).Darnis, G. & Fortier, L. Zooplankton respiration and the export of carbon at depth in the Amundsen Gulf (Arctic Ocean). J. Geophys. Res. Oceans 117, 1–12 (2012).Miquel, J.-C. et al. Downward particle flux and carbon export in the Beaufort Sea, Arctic Ocean; the role of zooplankton. Biogeosciences 12, 5103–5117 (2015).ADS 

Google Scholar 
Hernández-León, S. et al. Carbon export through zooplankton active flux in the Canary Current. J. Mar. Syst. 189, 12–21 (2019).
Google Scholar 
Gorgues, T., Aumont, O. & Memery, L. Simulated changes in the particulate carbon export efficiency due to diel vertical migration of zooplankton in the North Atlantic. Geophys. Res. Lett. 46, 5387–5395 (2019).ADS 
CAS 

Google Scholar 
Steinberg, D. K. et al. Zooplankton vertical migration and the active transport of dissolved organic and inorganic carbon in the Sargasso Sea. Deep Sea Res. Part I: Oceanogr. Res. Pap. 47, 137–158 (2000).ADS 
CAS 

Google Scholar 
Lebrato, M., Molinero, J.-C., Mychek-Londer, J. G., Gonzalez, E. M. & Jones, D. O. B. Gelatinous carbon impacts benthic megafaunal communities in a continental margin. Front. Mar. Sci. https://doi.org/10.3389/fmars.2022.902674 (2022).Lebrato, M. & Jones, D. O. B. Mass deposition event of Pyrosoma atlanticum carcasses off Ivory Coast (West Africa). Limnol. Oceanogr. 54, 1197–1209 (2009).ADS 
CAS 

Google Scholar 
Kobari, T. et al. Impacts of ontogenetically migrating copepods on downward carbon flux in the western subarctic Pacific Ocean. Deep Sea Res. Part II: Top. Stud. Oceanogr. 55, 1648–1660 (2008).ADS 

Google Scholar 
Wilson, S. E., Steinberg, D. K. & Buesseler, K. O. Changes in fecal pellet characteristics with depth as indicators of zooplankton repackaging of particles in the mesopelagic zone of the subtropical and subarctic North Pacific Ocean. Deep Sea Res. Part II: Top. Stud. Oceanogr. 55, 1636–1647 (2008).ADS 

Google Scholar 
Laurenceau-Cornec, E. et al. The relative importance of phytoplankton aggregates and zooplankton fecal pellets to carbon export: insights from free-drifting sediment trap deployments in naturally iron-fertilised waters near the Kerguelen Plateau. Biogeosciences 12, 1007–1027 (2015).ADS 

Google Scholar 
Manno, C., Stowasser, G., Enderlein, P., Fielding, S. & Tarling, G. The contribution of zooplankton faecal pellets to deep-carbon transport in the Scotia Sea (Southern Ocean). Biogeosciences 12, 1955–1965 (2015).ADS 

Google Scholar 
Cavan, E. et al. Attenuation of particulate organic carbon flux in the Scotia Sea, Southern Ocean, is controlled by zooplankton fecal pellets. Geophys. Res. Lett. 42, 821–830 (2015).ADS 
CAS 

Google Scholar 
Lebrato, M. et al. Jelly biomass sinking speed reveals a fast carbon export mechanism. Limnol. Oceanogr. 58, 1113–1122 (2013).ADS 

Google Scholar 
Ducklow, H. W., Steinberg, D. K. & Buesseler, K. O. Upper ocean carbon export and the biological pump. Oceanography 14, 50–58 (2001).
Google Scholar 
Yebra, L. et al. Zooplankton production and carbon export flux in the western Alboran Sea gyre (SW Mediterranean). Prog. Oceanogr. 167, 64–77 (2018).ADS 

Google Scholar 
Yebra, L. et al. Mesoscale physical variability affects zooplankton production in the Labrador Sea. Deep Sea Res. Part I: Oceanogr. Res. Pap. 56, 703–715 (2009).ADS 
CAS 

Google Scholar 
Beaugrand, G., Edwards, M. & Legendre, L. Marine biodiversity, ecosystem functioning, and carbon cycles. Proc. Natl Acad. Sci. USA 107, 10120–10124 (2010).ADS 
CAS 

Google Scholar 
Benson, A. J. & Trites, A. W. Ecological effects of regime shifts in the Bering Sea and eastern North Pacific Ocean. Fish. Fish. 3, 95–113 (2002).
Google Scholar 
Coyle, K. O. & Pinchuk, A. I. Climate-related differences in zooplankton density and growth on the inner shelf of the southeastern Bering Sea. Prog. Oceanogr. 55, 177–194 (2002).ADS 

Google Scholar 
Duffy-Anderson, J. T. et al. Return of warm conditions in the southeastern Bering Sea: Phytoplankton – Fish. PLoS ONE 12, e0178955 (2017).
Google Scholar 
Odebrecht, C., Secchi, E. R., Abreu, P. C., Muelbert, J. H. & Uiblein, F. Biota of the Patos Lagoon estuary and adjacent marine coast: long-term changes induced by natural and human-related factors. Mar. Biol. Res. 13, 3–8 (2017).
Google Scholar 
Eisner, L. B. et al. Seasonal, interannual, and spatial patterns of community composition over the eastern Bering Sea shelf in cold years. Part I: zooplankton. ICES J. Mar. Sci. 75, 72–86 (2018).
Google Scholar 
Trueblood, L. A. Salp metabolism: temperature and oxygen partial pressure effect on the physiology of Salpa fusiformis from the California Current. J. Plankton Res. 41, 281–291 (2019).CAS 

Google Scholar 
Hernández-León, S. & Ikeda, T. in Respiration in aquatic ecosystems. p. 57-82 (Oxford University Press, 2005).Lewandowska, A. M. et al. Effects of sea surface warming on marine plankton. Ecol. Lett. 17, 614–623 (2014).
Google Scholar 
O’Connor, M. I., Piehler, M. F., Leech, D. M., Anton, A. & Bruno, J. F. Warming and resource availability shift food web structure and metabolism. PLoS Biol. 7, e1000178 (2009).
Google Scholar 
Chen, B., Landry, M. R., Huang, B. & Liu, H. Does warming enhance the effect of microzooplankton grazing on marine phytoplankton in the ocean? Limnol. Oceanogr. 57, 519–526 (2012).ADS 
CAS 

Google Scholar 
Paul, C., Matthiessen, B. & Sommer, U. Warming, but not enhanced CO2 concentration, quantitatively and qualitatively affects phytoplankton biomass. Mar. Ecol. Prog. Ser. 528, 39–51 (2015).ADS 
CAS 

Google Scholar 
Sommer, U. & Lewandowska, A. Climate change and the phytoplankton spring bloom: warming and overwintering zooplankton have similar effects on phytoplankton. Glob. Change Biol. 17, 154–162 (2010).ADS 

Google Scholar 
Beaugrand, G. et al. Prediction of unprecedented biological shifts in the global ocean. Nat. Clim. Change 9, 237–243 (2019).ADS 

Google Scholar 
Sterner, R. W. & Elser, J. J. Ecological Stoichiometry: The Biology of Elements from Molecules to the Biosphere (Princeton University Press, 2002).Matsumoto, K., Tanioka, T. & Rickaby, R. Linkages between dynamic phytoplankton C:N:P and the ocean carbon cycle under climate change. Oceanography 33, 44–52 (2020).
Google Scholar 
Finkel, Z. V. et al. Phytoplankton in a changing world: cell size and elemental stoichiometry. J. Plankton Res. 32, 119–137 (2010).CAS 

Google Scholar 
Bank, T. W. Blue Economy. https://www.worldbank.org/en/topic/oceans-fisheries-and-coastal-economies#1 (2021).Burthe, S. et al. Phenological trends and trophic mismatch across multiple levels of a North Sea pelagic food web. Mar. Ecol. Prog. Ser. 454, 119–133 (2012).ADS 

Google Scholar 
Durant, J. M. et al. Contrasting effects of rising temperatures on trophic interactions in marine ecosystems. Sci. Rep. 9, 15213 (2019).ADS 

Google Scholar 
Otero, J. et al. Basin-scale phenology and effects of climate variability on global timing of initial seaward migration of Atlantic salmon (Salmo salar). Glob. Change Biol. 20, 61–75 (2014).ADS 

Google Scholar 
Kovach, R. P., Ellison, S. C., Pyare, S. & Tallmon, D. A. Temporal patterns in adult salmon migration timing across southeast Alaska. Glob. Change Biol. 21, 1821–1833 (2014).ADS 

Google Scholar 
Chust, G. et al. Earlier migration and distribution changes of albacore in the Northeast Atlantic. Fish. Oceanogr. 28, 505–516 (2019).
Google Scholar 
McQueen, K. & Marshall, C. T. Shifts in spawning phenology of cod linked to rising sea temperatures. ICES J. Mar. Sci. 74, 1561–1573 (2017).
Google Scholar 
Kanamori, Y., Takasuka, A., Nishijima, S. & Okamura, H. Climate change shifts the spawning ground northward and extends the spawning period of chub mackerel in the western North Pacific. Mar. Ecol. Prog. Ser. 624, 155–166 (2019).ADS 

Google Scholar 
Henderson, M. E., Mills, K. E., Thomas, A. C., Pershing, A. J. & Nye, J. A. Effects of spring onset and summer duration on fish species distribution and biomass along the Northeast United States continental shelf. Rev. Fish. Biol. Fish. 27, 411–424 (2017).
Google Scholar 
Beaugrand, G., Brander, K. M., Alistair Lindley, J., Souissi, S. & Reid, P. C. Plankton effect on cod recruitment in the North Sea. Nature 426, 661–664 (2003).ADS 
CAS 

Google Scholar 
Kang, Y. S., Kim, J. Y., Kim, H. G. & Park, J. H. Long-term changes in zooplankton and its relationship with squid, Todarodes pacificus, catch in Japan/East Sea. Fish. Oceanogr. 11, 337–346 (2002).
Google Scholar 
Mackas, D. et al. Zooplankton time series from the Strait of Georgia: results from year-round sampling at deep water locations, 1990–2010. Prog. Oceanogr. 115, 129–159 (2013).ADS 

Google Scholar 
Daly, E. A., Brodeur, R. D. & Auth, T. D. Anomalous ocean conditions in 2015: impacts on spring Chinook salmon and their prey field. Mar. Ecol. Prog. Ser. 566, 169–182 (2017).ADS 

Google Scholar 
Feuilloley, G. et al. Concomitant changes in the environment and small pelagic fish community of the Gulf of Lions. Prog. Oceanogr. 186, 102375 (2020).
Google Scholar 
Yebra, L. et al. Molecular identification of the diet of Sardina pilchardus larvae in the SW Mediterranean Sea. Mar. Ecol. Prog. Ser. 617-618, 41–52 (2019).ADS 
CAS 

Google Scholar 
Record, N. et al. Copepod diapause and the biogeography of the marine lipidscape. J. Biogeogr. 45, 2238–2251 (2018).
Google Scholar 
Yebra, L. et al. Zooplankton biomass depletion event reveals the importance of small pelagic fish top-down control in the Western Mediterranean Coastal Waters. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.608690 (2020).Friedland, K. D. et al. Pathways between primary production and fisheries yields of large marine ecosystems. PLoS ONE 7, e28945 (2012).Santora, J. A. et al. Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. Nat. Commun. 11, 536 (2020).ADS 
CAS 

Google Scholar 
Piatt, J. et al. Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016. PLOS ONE 15, e0226087 (2020).Meyer-Gutbrod, E., Greene, C., Davies, K. & Johns, D. G. Ocean regime shift is driving collapse of the North Atlantic Right Whale Population. Oceanography 34, 22–31 (2021).
Google Scholar 
Beltran, R. S. et al. Seasonal resource pulses and the foraging depth of a Southern Ocean top predator. Proc. R. Soc. B 288, 1–9 (2021).Everett, J. D. et al. Modeling what we sample and sampling what we model: challenges for zooplankton model assessment. Front. Mar. Sci. https://doi.org/10.3389/fmars.2017.00077 (2017). This article synthesizes key information required for better parameterize zooplankton in various models.Gibbs Samantha, J. et al. Algal plankton turn to hunting to survive and recover from end-Cretaceous impact darkness. Sci. Adv. 6, eabc9123 (2020).Kwiatkowski, L. et al. Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections. Biogeosciences 17, 3439–3470 (2020).ADS 
CAS 

Google Scholar 
Mitra, A. et al. Bridging the gap between marine biogeochemical and fisheries sciences; configuring the zooplankton link. Prog. Oceanogr. 129, 176–199 (2014).ADS 

Google Scholar 
Gentleman, W., Leising, A., Frost, B., Strom, S. & Murray, J. Functional responses for zooplankton feeding on multiple resources: a review of assumptions and biological dynamics. Deep Sea Res. Part II: Top. Stud. Oceanogr. 50, 2847–2875 (2003).ADS 
CAS 

Google Scholar 
Chenillat, F., Rivière, P. & Ohman, M. D. On the sensitivity of plankton ecosystem models to the formulation of zooplankton grazing. PLOS ONE 16, e0252033 (2021).CAS 

Google Scholar 
Stemmann, L. & Boss, E. Plankton and particle size and packaging: from determining optical properties to driving the biological pump. Annu. Rev. Mar. Sci. 4, 263–290 (2012).ADS 
CAS 

Google Scholar 
Kiørboe, T., Saiz, E., Tiselius, P. & Andersen, K. H. Adaptive feeding behavior and functional responses in zooplankton. Limnol. Oceanogr. 63, 308–321 (2017).ADS 

Google Scholar 
Grigor, J. J. et al. Non-carnivorous feeding in Arctic chaetognaths. Prog. Oceanogr. 186, 102388 (2020).
Google Scholar 
Yeh, H. D., Questel, J. M., Maas, K. R. & Bucklin, A. Metabarcoding analysis of regional variation in gut contents of the copepod Calanus finmarchicus in the North Atlantic Ocean. Deep Sea Res. Part II: Top. Stud. Oceanogr. 180, 104738 (2020).
Google Scholar 
Novotny, A., Zamora-Terol, S. & Winder, M. DNA metabarcoding reveals trophic niche diversity of micro and mesozooplankton species. Proc. R. Soc. B 288, 1–10 (2021).Käse, L. et al. Metabarcoding analysis suggests that flexible food web interactions in the eukaryotic plankton community are more common than specific predator–prey relationships at Helgoland Roads, North Sea. ICES J. Mar. Sci. 78, 3372–3386 (2021).
Google Scholar 
Greco, M., Morard, R. & Kucera, M. Single-cell metabarcoding reveals biotic interactions of the Arctic calcifier Neogloboquadrina pachyderma with the eukaryotic pelagic community. J. Plankton Res. 43, 113–125 (2021).CAS 

Google Scholar 
Serra-Pompei, C., Soudijn, F., Visser, A. W., Kiørboe, T. & Andersen, K. H. A general size- and trait-based model of plankton communities. Prog. Oceanogr. 189, 102473 (2020).
Google Scholar 
Heneghan, R. F. et al. A functional size-spectrum model of the global marine ecosystem that resolves zooplankton composition. Ecol. Model. 435, 109265 (2020).CAS 

Google Scholar 
Ward, B. A. et al. EcoGEnIE 1.0: plankton ecology in the cGEnIE Earth system model. Geosci. Model Dev. 11, 4241–4267 (2018).ADS 
CAS 

Google Scholar 
Sosik, H. M. & Olson, R. J. Automated taxonomic classification of phytoplankton sampled with imaging-in-flow cytometry. Limnol. Oceanogr. Methods 5, 204–216 (2007).
Google Scholar 
Lombard, F. et al. Globally consistent quantitative observations of planktonic ecosystems. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00196 (2019).Pitois, S. G. et al. A first approach to build and test the Copepod Mean Size and Total Abundance (CMSTA) ecological indicator using in-situ size measurements from the Plankton Imager (PI). Ecol. Indic. 123, 107307 (2021).Irisson, J.-O., Ayata, S.-D., Lindsay, D. J., Karp-Boss, L. & Stemmann, L. Machine learning for the study of plankton and marine snow from images. Annu. Rev. Mar. Sci. 14, 277–301 (2022).ADS 

Google Scholar 
Cornils, A. et al. Testing the usefulness of optical data for zooplankton long-term monitoring: Taxonomic composition, abundance, biomass and size spectra from ZooScan image analysis. Limnol. Oceanogr. Methods 20, 428–450 (2022).Henson, S. A., C, B. & R, L. Observing climate change trends in ocean biogeochemistry: when and where. Glob. Change Biol. 22, 1561–1571 (2016).ADS 

Google Scholar 
García-Comas, C. et al. Zooplankton long-term changes in the NW Mediterranean Sea: Decadal periodicity forced by winter hydrographic conditions related to large-scale atmospheric changes? J. Mar. Syst. 87, 216–226 (2011).
Google Scholar 
Vucetich, J. A., Nelson, M. P. & Bruskotter, J. T. What drives declining support for long-term ecological research? BioScience 70, 168–173 (2020).
Google Scholar 
Lindenmayer, D. B. et al. Value of long-term ecological studies. Austral Ecol. 37, 745–757 (2012).
Google Scholar 
Giron-Nava, A. et al. Quantitative argument for long-term ecological monitoring. Mar. Ecol. Prog. Ser. 572, 269–274 (2017).ADS 

Google Scholar 
Hughes, B. B. et al. Long-term studies contribute disproportionately to ecology and policy. BioScience 67, 271–281 (2017).
Google Scholar 
Berline, L., Siokou-Frangou, I. & Marasovic, I. Intercomparison of six Mediterranean zooplankton time series. Prog. Oceanogr. 97-100, 76–91 (2012).ADS 

Google Scholar 
Beaugrand, G. et al. Synchronous marine pelagic regime shifts in the Northern Hemisphere. Philos. Trans. R. Soc. B: Biol. Sci. 370, 20130272 (2015).
Google Scholar 
Mackas, D. L. & Beaugrand, G. Comparisons of zooplankton time series. J. Mar. Syst. 79, 286–304 (2010).
Google Scholar 
O’Brien, T. D., Lorenzoni, L., Isensee, K. & Valdés, L. What are Marine Ecological Time Series Telling Us About The Ocean? A Status Report. (2017).Ratnarajah, L. Map of BioEco Observing networks/capability (https://eurosea.eu/download/eurosea-d1-2-bioeco-observing-networks/?wpdmdl=3580&refresh=637b1a59bb2011669012057, 2021).Wright, R. M., Le Quéré, C., Buitenhuis, E. T., Pitois, S. & Gibbons, M. J. Role of jellyfish in the plankton ecosystem revealed using a global ocean biogeochemical model. Biogeosciences 18, 1291–1320 (2021).ADS 
CAS 

Google Scholar 
Buitenhuis, E. T. et al. MAREDAT: towards a world atlas of MARine Ecosystem DATa. Earth Syst. Sci. Data 5, 227–239 (2013).ADS 

Google Scholar 
O’Brien, T. D. COPEPOD: The Global Plankton Database. An overview of the 2014 database contents, processing methods, and access interface. U.S. Dep. Commerce, NOAA Tech. Memo. NMFS-F/ST-37, 29p. (2014).Pitois, S. G., Bouch, P., Creach, V. & van der Kooij, J. Comparison of zooplankton data collected by a continuous semi-automatic sampler (CALPS) and a traditional vertical ring net. J. Plankton Res. 38, 931–943 (2016).
Google Scholar 
Wiebe, P. H. & Benfield, M. C. From the Hensen net toward four-dimensional biological oceanography. Prog. Oceanogr. 56, 7–136 (2003).ADS 

Google Scholar 
Boss, E. et al. Recommendations for plankton measurements on oceansites moorings with relevance to other observing sites. Front. Mar. Sci. https://doi.org/10.3389/fmars.2022.929436 (2022).Pollina, T. et al. PlanktoScope: affordable modular quantitative imaging platform for citizen oceanography. Front. Mar. Sci. https://doi.org/10.3389/fmars.2022.949428 (2022).Pitois, S. G. et al. Comparison of a cost-effective integrated plankton sampling and imaging instrument with traditional systems for mesozooplankton sampling in the Celtic Sea. Front. Mar. Sci. https://doi.org/10.3389/fmars.2018.00005 (2018).Ohman, M. D. et al. Zooglider: an autonomous vehicle for optical and acoustic sensing of zooplankton. Limnol. Oceanogr.: Methods 17, 69–86 (2018).
Google Scholar 
Picheral, M. et al. The Underwater Vision Profiler 6: an imaging sensor of particle size spectra and plankton, for autonomous and cabled platforms. Limnol. Oceanogr. Methods 20, 115–129 (2021).
Google Scholar 
Picheral, M. et al. The Underwater Vision Profiler 5: an advanced instrument for high spatial resolution studies of particle size spectra and zooplankton. Limnol. Oceanogr. Methods 8, 462–473 (2010).
Google Scholar 
Richardson, A. et al. in Guidelines for the study of climate change effects on HABs Vol. 88 23 (UNESCO-IOC/SCOR, 2022).Drago, L. et al. Global distribution of zooplankton biomass estimated by in situ imaging and machine learning. Front. Mar. Sci. https://doi.org/10.3389/fmars.2022.894372 (2022).Forest, A. et al. Ecosystem function and particle flux dynamics across the Mackenzie Shelf (Beaufort Sea, Arctic Ocean): an integrative analysis of spatial variability and biophysical forcings. Biogeosciences 10, 2833–2866 (2013).ADS 

Google Scholar 
Haëntjens, N. et al. Detecting mesopelagic organisms using biogeochemical-argo floats. Geophys. Res. Lett. 47, 1–10 (2020).Clayton, S. et al. Bio-GO-SHIP: the time is right to establish global repeat sections of ocean biology. Front. Mar. Sci. https://doi.org/10.3389/fmars.2021.767443 (2022).Miloslavich, P. et al. Essential ocean variables for global sustained observations of biodiversity and ecosystem changes. Glob. Change Biol. 24, 2416–2433 (2018).ADS 

Google Scholar 
McPhaden, M. J., Santoso, A. & Cai, W. El Niño Southern Oscillation in a Changing Climate: Glossary (John Wiley & Sons, Inc, 2021). More

Saponari, M. et al. Infectivity and transmission of Xylella fastidiosa by Philaenus spumarius (Hemiptera: Aphrophoridae) in Apulia, Italy. J. Econ. Entomol. 107, 1316–1319. https://doi.org/10.1603/EC14142 (2014).Article 

Google Scholar 
Cornara, D., Bosco, D. & Fereres, A. Philaenus spumarius: When an old acquaintance becomes a new threat to European agriculture. J. Pest Sci. 91, 957–972. https://doi.org/10.1007/s10340-018-0966-0 (2018).Article 

Google Scholar 
Weaver, C. R. & King, D. Meadow spittlebug, Philaenus leucophthalmus (L.). Ohio Agric. Exp. Stn. Res. Bull. 741, 258 (1954).
Google Scholar 
Halkka, A., Halkka, L., Halkka, O., Roukka, K. & Pokki, J. Lagged effects of North Atlantic Oscillation on spittlebug Philaenus spumarius (Homoptera) abundance and survival. Glob. Change Biol. 12, 2250–2262. https://doi.org/10.1111/j.1365-2486.2006.01266.x (2006).Article 

Google Scholar 
Cruaud, A. et al. Using insects to detect, monitor and predict the distribution of Xylella fastidiosa: A case study in Corsica. Sci. Rep. 8, 15628. https://doi.org/10.1038/s41598-018-33957-z (2018).Article 
CAS 

Google Scholar 
Godefroid, M. et al. Climate tolerances of Philaenus spumarius should be considered in risk assessment of disease outbreaks related to Xylella fastidiosa. J. Pest Sci. 2021, 1–14. https://doi.org/10.1007/s10340-021-01413-z (2021).Article 

Google Scholar 
Farigoule, P. et al. Vectors as sentinels: Rising temperatures increase the risk of Xylella fastidiosa outbreaks. Biology 11, 1299. https://doi.org/10.3390/biology11091299 (2022).Article 

Google Scholar 
Drosopoulos, S. & Asche, M. Biosystematic studies on the spittlebug genus Philaenus with the description of a new species. Zool. J. Linn. Soc. 101, 169–177. https://doi.org/10.1111/j.1096-3642.1991.tb00891.x (1991).Article 

Google Scholar 
Godefroid, M. & Durán, J. M. Composition of landscape impacts the distribution of the main vectors of Xylella fastidiosa in southern Spain. J. Appl. Entomol. 146, 666–675. https://doi.org/10.1111/jen.13003 (2022).Article 

Google Scholar 
Karban, R. & Strauss, S. Y. Physiological tolerance, climate change, and a northward range shift in the spittlebug, Philaenus spumarius. Ecol. Entomol. 29, 251–254. https://doi.org/10.1111/j.1365-2311.2004.00576.x (2004).Article 

Google Scholar 
Chmiel, S. M. & Wilson, M. C. Estimation of the lower and upper developmental threshold temperatures and duration of the nymphal stages of the meadow Spittlebug, Philaenus spumarius. Environ. Entomol. 8, 682–685. https://doi.org/10.1093/ee/8.4.682 (1979).Article 

Google Scholar 
Yurtsever, S. On the polymorphic meadow spittlebug, Philaenus spumarius (L.) (Homoptera: Cercopidae). Turk. J. Zool. 24, 447–460 (2000).
Google Scholar 
Ahmed, D. D. & Davidson, R. H. Life history of the meadow spittlebug in Ohio. J. Econ. Entomol. 43, 905–908. https://doi.org/10.1093/jee/43.6.905 (1950).Article 

Google Scholar 
Whittaker, J. B. Cercopid spittle as a microhabitat. Oikos 21, 59–64. https://doi.org/10.2307/3543839 (1970).Article 

Google Scholar 
Drosopoulos, S. New data on the nature and origin of colour polymorphism in the spittlebug genus Philaenus (Hemiptera: Aphorophoridae). Ann. Soc. Entomol. Fr. NS 39, 31–42. https://doi.org/10.1080/00379271.2003.10697360 (2003).Article 

Google Scholar 
Bodino, N. et al. Phenology, seasonal abundance, and host-plant association of spittlebugs (Hemiptera: Aphrophoridae) in vineyards of Northwestern Italy. Insects 12, 1012. https://doi.org/10.3390/insects12111012 (2021).Article 

Google Scholar 
Cornara, D. et al. Natural areas as reservoir of candidate vectors of Xylella fastidiosa. Bull. Insectol. 74, 173–180 (2021).
Google Scholar 
Gargani, E. et al. A five-year survey in Tuscany (Italy) and detection of Xylella fastidiosa subspecies multiplex in potential insect vectors, collected in Monte Argentario. Redia 104, 75–88. https://doi.org/10.19263/REDIA-104.21.09 (2021).Article 

Google Scholar 
Morente, M. et al. Distribution and relative abundance of insect vectors of Xylella fastidiosa in olive groves of the iberian peninsula. Insects 9, 175. https://doi.org/10.3390/insects9040175 (2018).Article 

Google Scholar 
Delong, D. et al. Spittle-insect vectors of Pierce’s disease virus. I. Characters, distribution, and food plants. Hilgardia 19, 339–356 (1950).Article 

Google Scholar 
Bodino, N. et al. Phenology, seasonal abundance and stage-structure of spittlebug (Hemiptera: Aphrophoridae) populations in olive groves in Italy. Sci. Rep. 9, 1–17. https://doi.org/10.1038/s41598-019-54279-8 (2019).Article 
CAS 

Google Scholar 
Wiegert, R. G. Population energetics of meadow spittlebugs (Philaenus spumarius L.) as affected by migration and habitat. Ecol. Monogr. 34, 217–241. https://doi.org/10.2307/1948501 (1964).Article 

Google Scholar 
Dongiovanni, C. et al. Plant selection and population trend of spittlebug immatures (Hemiptera: Aphrophoridae) in olive groves of the Apulia region of Italy. J. Econ. Entomol. 112, 67–74. https://doi.org/10.1093/jee/toy289 (2019).Article 

Google Scholar 
Bodino, N. et al. Spittlebugs of mediterranean olive groves: Host-plant exploitation throughout the year. Insects 11, 130. https://doi.org/10.3390/insects11020130 (2020).Article 

Google Scholar 
Villa, M., Rodrigues, I., Baptista, P., Fereres, A. & Pereira, J. A. Populations and host/non-host plants of spittlebugs nymphs in olive orchards from northeastern Portugal. Insects 11, 720. https://doi.org/10.3390/insects11100720 (2020).Article 

Google Scholar 
Antonatos, S. et al. Seasonal appearance, abundance, and host preference of Philaenus spumarius and Neophilaenus campestris (Hemiptera: Aphrophoridae) in olive groves in Greece. Environ. Entomol. 50, 1474–1482. https://doi.org/10.1093/ee/nvab093 (2021).Article 

Google Scholar 
Hasbroucq, S., Casarin, N., Ewelina, C., Bragard, C. & Grégoire, J.-C. Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium. Belg. J. Entomol. 92, 2569 (2020).
Google Scholar 
Mesmin, X. et al. Interaction networks between spittlebugs and vegetation types in and around olive and clementine groves of Corsica; implications for the spread of Xylella fastidiosa. Agric. Ecosyst. Environ. 334, 107979. https://doi.org/10.1016/j.agee.2022.107979 (2022).Article 

Google Scholar 
Albre, J., García-Carrasco, J. M. & Gibernau, M. Ecology of the meadow spittlebug Philaenus spumarius in the Ajaccio region (Corsica)—I: Spring. Bull. Entomol. Res. 111, 246–256. https://doi.org/10.1017/S0007485320000711 (2021).Article 

Google Scholar 
Andersson, P., Löfstedt, C. & Hambäck, P. A. Insect density–plant density relationships: A modified view of insect responses to resource concentrations. Oecologia 173, 1333–1344. https://doi.org/10.1007/s00442-013-2737-1 (2013).Article 

Google Scholar 
Hambäck, P. A., Inouye, B. D., Andersson, P. & Underwood, N. Effects of plant neighborhoods on plant–herbivore interactions: Resource dilution and associational effects. Ecology 95, 1370–1383. https://doi.org/10.1890/13-0793.1 (2014).Article 

Google Scholar 
Otway, S. J., Hector, A. & Lawton, J. H. Resource dilution effects on specialist insect herbivores in a grassland biodiversity experiment. J. Anim. Ecol. 74, 234–240 (2005).Article 

Google Scholar 
Lago, C. et al. Flight performance and the factors affecting the flight behaviour of Philaenus spumarius the main vector of Xylella fastidiosa in Europe. Sci. Rep. 11, 17608. https://doi.org/10.1038/s41598-021-96904-5 (2021).Article 
CAS 

Google Scholar 
Casarin, N. et al. Investigating dispersal abilities of Aphrophoridae in European temperate regions to assess the threat of potential Xylella fastidiosa-based pathosystems. J. Pest Sci. https://doi.org/10.1007/s10340-022-01562-9 (2022).Article 

Google Scholar 
Bodino, N. et al. Dispersal of Philaenus spumarius (Hemiptera: Aphrophoridae), a vector of Xylella fastidiosa, in olive grove and meadow agroecosystems. Environ. Entomol. 50, 267–279. https://doi.org/10.1093/ee/nvaa140 (2020).Article 
CAS 

Google Scholar 
Santoiemma, G., Tamburini, G., Sanna, F., Mori, N. & Marini, L. Landscape composition predicts the distribution of Philaenus spumarius, vector of Xylella fastidiosa, in olive groves. J. Pest. Sci. 92, 1101–1109. https://doi.org/10.1007/s10340-019-01095-8 (2019).Article 

Google Scholar 
Cappellari, A. et al. Spatio-temporal dynamics of vectors of Xylella fastidiosa subsp. pauca across heterogeneous landscapes. Entomol. Gen. 42, 515–521. https://doi.org/10.1127/entomologia/2022/1427 (2022).Article 

Google Scholar 
Avosani, S., Tattoni, C., Mazzoni, V. & Ciolli, M. Occupancy and detection of agricultural threats: The case of Philaenus spumarius, European vector of Xylella fastidiosa. Agric. Ecosyst. Environ. 324, 107707. https://doi.org/10.1016/j.agee.2021.107707 (2022).Article 

Google Scholar 
Allier, C. & Lacoste, A. Processus dynamiques de reconstitution dans la série du Quercus ilex en Corse. In Vegetation Dynamics in Grasslans, Healthlands and Mediterranean Ligneous Formations 83–91 (Springer, 1981).Delbosc, P., Bioret, F. & Panaïotis, C. Plant landscape of Corsica: Typology and mapping plant landscape of Cap Corse region and Biguglia Pond (Springer Nature, 2020).Book 

Google Scholar 
Chessel, D., Dufour, A.-B. & Thioulouse, J. The ade4 package—I: One-table methods. R. News 4, 5–10 (2004).
Google Scholar 
Biedermann, R. & Niedringhaus, R. The Plant-and Leafhoppers of Germany: Identification Key to All Species (Wabv Fründ, 2009).
Google Scholar 
Stöckmann, M., Biedermann, R., Nickel, H. & Niedringhaus, R. The Nymphs of the Planthoppers and Leafhoppers of Germany (WABV, 2013).
Google Scholar 
INRAE-CBGP. Arthemis DB@se – ARTHropod Ecology, Molecular Identification and Systematics. https://arthemisdb.supagro.inrae.frhttps://doi.org/10.15454/TBGRIB. Accessed 2021.Xu, T. & Hutchinson, M. ANUCLIM version 6.1 user guide. Aust. Natl. Univ. Fenner Sch. Environ. Soc. Canberra 2011, 256 (2011).
Google Scholar 
Quintana-Seguí, P. et al. Analysis of near-surface atmospheric variables: Validation of the SAFRAN analysis over France. J. Appl. Meteorol. Climatol. 47, 92–107. https://doi.org/10.1175/2007JAMC1636.1 (2008).Article 

Google Scholar 
Hijmans, R. J., Phillips, S., Leathwick, J. & Elith, J. Dismo: Species Distribution Modeling https://CRAN.R-project.org/package=dismo (2017).Faraway, J. J. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Chapman and Hall/CRC, 2006).MATH 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R. J. 9, 378–400. https://doi.org/10.3929/ethz-b-000240890 (2017).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing https://www.R-project.org/ (2019).Hardin, J. W. & Hilbe, J. M. Generalized Linear Models and Extensions 4th edn. (Stata Press, 2018).MATH 

Google Scholar 
Harrison, X. A. Using observation-level random effects to model overdispersion in count data in ecology and evolution. PeerJ 2, e616. https://doi.org/10.7717/peerj.616 (2014).Article 

Google Scholar 
Bolker, B. M. et al. Generalized linear mixed models: A practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135. https://doi.org/10.1016/j.tree.2008.10.008 (2009).Article 

Google Scholar 
Hartig, F. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level/Mixed) Regression Models https://CRAN.R-project.org/package=DHARMa (2020).Lüdecke, D., Ben-Shachar, M. S., Patil, I., Waggoner, P. & Makowski, D. performance: An R package for assessment, comparison and testing of statistical models. J. Open Sourc. Softw. 6, 3139. https://doi.org/10.21105/joss.03139 (2021).Article 

Google Scholar 
Fox, J. & Weisberg, S. An {R} Companion to Applied Regression Third edn, https://socialsciences.mcmaster.ca/jfox/Books/Companion/ (Sage, Thousand Oaks CA, 2019).Lenth, R. V. Emmeans: Estimated Marginal Means, Aka Least-Squares Means https://CRAN.R-project.org/package=emmeans (2021).Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biom. J. 50, 346–363. https://doi.org/10.1002/bimj.200810425 (2008).Article 
MATH 

Google Scholar 
Fernández-Mazuecos, M. & Vargas, P. Ecological rather than geographical isolation dominates Quaternary formation of Mediterranean Cistus species. Mol. Ecol. 19, 1381–1395. https://doi.org/10.1111/j.1365-294X.2010.04549.x (2010).Article 
CAS 

Google Scholar 
Berenbaum, M. R. & Feeny, P. P. 1. Chemical mediation of host-plant specialization: The papilionid paradigm. In Specialization, Speciation, and Radiation (ed. Tilmon, K.) 3–19 (University of California Press, 2008). https://doi.org/10.1525/california/9780520251328.003.0001.Kapantaidaki, D. E., Antonatos, S., Evangelou, V., Papachristos, D. P. & Milonas, P. Genetic and endosymbiotic diversity of Greek populations of Philaenus spumarius, Philaenus signatus and Neophilaenus campestris, vectors of Xylella fastidiosa. Sci. Rep. 11, 3752. https://doi.org/10.1038/s41598-021-83109-z (2021).Article 
CAS 

Google Scholar 
Mesmin, X. et al. Ooctonus vulgatus (Hymenoptera, Mymaridae), a potential biocontrol agent to reduce populations of Philaenus spumarius (Hemiptera, Aphrophoridae) the main vector of Xylella fastidiosa in Europe. PeerJ 8, e8591. https://doi.org/10.7717/peerj.8591 (2020).Article 

Google Scholar 
Denancé, N. et al. Several subspecies and sequence types are associated with the emergence of Xylella fastidiosa in natural settings in France. Plant Pathol. 66, 1054–1064. https://doi.org/10.1111/ppa.12695 (2017).Article 
CAS 

Google Scholar 
EFSA, Delbianco, A., Gibin, D., Pasinato, L. & Morelli, M. Update of the Xylella spp host plant database—systematic literature search up to 31 December 2020. EFSA J. 19, 6. https://doi.org/10.2903/j.efsa.2021.6674 (2021).Article 

Google Scholar 
Soubeyrand, S. et al. Inferring pathogen dynamics from temporal count data: The emergence of Xylella fastidiosa in France is probably not recent. New Phytol. 219, 824–836. https://doi.org/10.1111/nph.15177 (2018).Article 

Google Scholar 
Roy, J. & Sonié, L. Germination and population dynamics of Cistus species in relation to fire. J. Appl. Ecol. 29, 647–655. https://doi.org/10.2307/2404472 (1992).Article 

Google Scholar 
Whittaker, J. B. Density regulation in a population of Philaenus spumarius (L.) (Homoptera: Cercopidae). J. Anim. Ecol. 42, 163–172. https://doi.org/10.2307/3410 (1973).Article 

Google Scholar 
Chapman, D. et al. Improving knowledge of Xylella fastidiosa vector ecology: modelling vector occurrence and abundance in the wider landscape in Scotland. Project Final Report. PHC2020/04, Scotland’s Centre of Expertise for Plant Health (PHC) https://doi.org/10.5281/zenodo.6523478 (2022).Saponari, M., Giampetruzzi, A., Loconsole, G., Boscia, D. & Saldarelli, P. Xylella fastidiosa in olive in Apulia: Where we stand. Phytopathology 109, 175–186. https://doi.org/10.1094/PHYTO-08-18-0319-FI (2019).Article 
CAS 

Google Scholar 
López-Mercadal, J. et al. Collection of data and information in Balearic Islands on biology of vectors and potential vectors of Xylella fastidiosa (GP/EFSA/ALPHA/017/01). EFSA Supp. Publ. 18, 10. https://doi.org/10.2903/sp.efsa.2021.EN-6925 (2021).Article 

Google Scholar  More

Roemmich, D. et al. Unabated planetary warming and its ocean structure since 2006. Nat. Clim. Change 5, 240–245 (2015).Article 
ADS 

Google Scholar 
Frölicher, T. L. et al. Dominance of the Southern Ocean in anthropogenic carbon and heat uptake in CMIP5 models. J. Clim. 28, 862–886 (2015).Article 
ADS 

Google Scholar 
Buesseler, K. O. & Boyd, P. W. Shedding light on processes that control particle export and flux attenuation in the twilight zone of the open ocean. Limnol. Oceanogr. 54, 1210–1232 (2009).Article 
ADS 
CAS 

Google Scholar 
Arteaga, L., Haentjens, N., Boss, E., Johnson, K. S. & Sarmiento, J. L. Assessment of export efficiency equations in the Southern Ocean applied to satellite-based net primary production. J. Geophys. Res.-Oceans 123, 2945–2964 (2018).Article 
ADS 

Google Scholar 
Siegel, D. A. et al. Prediction of the export and fate of global ocean net primary production: the EXPORTS science plan. Front. Marine Sc. 3, 22 (2016).Perissinotto, R. & Pakhomov, E. A. The trophic role of the tunicate Salpa thompsoni in the Antarctic marine ecosystem. J. Mar. Syst. 17, 361–374 (1998).Article 

Google Scholar 
Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature 432, 100–103 (2004).Article 
ADS 
CAS 

Google Scholar 
Perissinotto, R. & Pakhomov, E. A. Contribution of salps to carbon flux of marginal ice zone of the Lazarev sea, southern ocean. Mar. Biol. 131, 25–32 (1998).Article 
CAS 

Google Scholar 
Phillips, B., Kremer, P. & Madin, L. P. Defecation by Salpa thompsoni and its contribution to vertical flux in the Southern Ocean. Mar. Biol. 156, 455–467 (2009).Article 

Google Scholar 
Stone, J. P. & Steinberg, D. K. Salp contributions to vertical carbon flux in the Sargasso Sea. Deep-Sea Res. Part I 113, 90–100 (2016).Article 
CAS 

Google Scholar 
Ramaswamya, V., Sarin, M. M. & Rengarajan, R. Enhanced export of carbon by salps during the northeast monsoon period in the northern Arabian Sea. Deep-Sea Res. Part II 52, 1922–1929 (2005).Article 
ADS 

Google Scholar 
Smith, K. L. et al. Large salp bloom export from the upper ocean and benthic community response in the abyssal northeast Pacific: day to week resolution. Limnol. Oceanogr. 59, 745–757 (2014).Article 
ADS 
CAS 

Google Scholar 
Madin, L. P. & Kremer, P. Determination of the filter feeding rates of salps (Tunicata, Thaliacea). ICES J. Mar. Sci. 52, 583–595 (1995).Article 

Google Scholar 
Wiebe, P. H., Madin, L. P., Haury, L. R., Harbison, G. R. & Philbin, L. M. Diel vertical migration by Salpa aspera and its potential for large-scale particulate organic matter transport to the deep-sea. Mar. Biol. 53, 249–255 (1979).Article 

Google Scholar 
Dadon-Pilosof, A., Lombard, F., Genin, A., Sutherland, K. R. & Yahel, G. Prey taxonomy rather than size determines salp diets. Limnol. Oceanogr. 64, 1996–2010 (2019).Article 
ADS 

Google Scholar 
Stukel, M. R., Décima, M., Selph, K. E. & Gutiérrez-Rodríguez, A. Size-specific grazing and competitive interactions between large salps and protistan grazers. Limnol. Oceanogr. 66, 2521–2534 (2021).Madin, L. P. Production, composition and sedimentation of salp fecal pellets in oceanic waters. Mar. Biol. 67, 39–45 (1982).Article 

Google Scholar 
Michaels, A. F. & Silver, M. W. Primary production, sinking fluxes and the microbial food web. Deep-Sea Res. Part I 35, 473–490 (1988).Article 
ADS 

Google Scholar 
Luo, J. Y. et al. Gelatinous zooplankton‐mediated carbon flows in the global oceans: a data‐driven modeling study. Glob. Biogeochem. Cycle 34, e2020GB006704 (2020).Kremer, P. & Madin, L. P. Particle retention efficiency of salps. J. Plankton Res. 14, 1009–1015 (1992).Article 

Google Scholar 
Harbison, G. R. & Gilmer, R. W. Feeding rates of pelagic tunicate Pegea confederata and 2 other salps. Limnol. Oceanogr. 21, 517–528 (1976).Article 
ADS 
CAS 

Google Scholar 
Harbison, G. R. & McAlister, V. L. The filter-feeding rates and particle retention efficiencies of 3 species of Cyclosalpa (Tunicata, Thaliacea). Limnol. Oceanogr. 24, 875–892 (1979).Article 
ADS 

Google Scholar 
Mullin, M. M. In situ measurement of filtering rates of the salp Thalia democratica, on phytoplankton and bacteria. J. Plankton Res. 5, 279–288 (1983).Article 

Google Scholar 
Deibel, D. Clearance rates of the salp Thalia democratica fed naturally occurring particles. Mar. Biol. 86, 47–54 (1985).Article 

Google Scholar 
Fender, C. K. et al. Prey size spectra and predator:prey ratios of 7 species of New Zealand salps. Mar. Biol. (in press).Chiswell, S. M., Bostock, H. C., Sutton, P. J. H. & Williams, M. J. M. Physical oceanography of the deep seas around New Zealand: a review. N.Z. J. Mar. Freshw. Res. 49, 286–317 (2015).Article 

Google Scholar 
Henschke, N. et al. Salp-falls in the Tasman Sea: a major food input to deep-sea benthos. Mar. Ecol. Prog. Ser. 491, 165–175 (2013).Article 
ADS 

Google Scholar 
Childerhouse, S., Dix, B. & Gales, N. Diet of new Zealand sea lions (Phocarctos hookeri) at the Auckland islands. Wildl. Res. 28, 291–298 (2001).Article 

Google Scholar 
Horn, P. L., Burrell, T., Connell, A. & Dunn, M. R. A comparison of the diets of silver (Seriolella punctata) and white (Seriolella caerulea) warehou. Mar. Biol. Res. 7, 576–591 (2011).Article 

Google Scholar 
Horn, P. L., Forman, J. S. & Dunn, M. R. Dietary partitioning by two sympatric fish species, red cod (Pseudophycis bachus) and sea perch (Helicolenus percoides), on Chatham Rise, New Zealand. Mar. Biol. Res. 8, 624–634 (2012).Article 

Google Scholar 
Forman, J. S., Horn, P. L. & Stevens, D. W. Diets of deepwater Oreos (Oreosomatidae) and orange roughy Hoplostethus atlanticus. J. Fish. Biol. 88, 2275–2302 (2016).Article 
CAS 

Google Scholar 
Carroll, E. L. et al. Multi-locus DNA metabarcoding of zooplankton communities and scat reveal trophic interactions of a generalist predator. Sci. Rep. 9, 1–14 (2019).Savoye, N. et al. 234Th sorption and export models in the water column: a review. Mar. Chem. 100, 234–249 (2006).Article 
CAS 

Google Scholar 
Sutton, P. J. H. The Southland Current: a subantarctic current. N.Z. J. Mar. Freshw. Res. 37, 645–652 (2003).Article 

Google Scholar 
Foxton, P. The distribution and life history of Salpa thompsoni Foxton with observations on a related species, Salpa gerlachei Foxton. Discovery Rep. 34, 1–116 (1966).Loeb, V. J. & Santora, J. A. Population dynamics of Salpa thompsoni near the Antarctic Peninsula: growth rates and interannual variations in reproductive activity (1993–2009). Prog. Oceanogr. 96, 93–107 (2012).Article 
ADS 

Google Scholar 
Pakhomov, E. A. & Hunt, B. P. V. Trans-Atlantic variability in ecology of the pelagic tunicate Salpa thompsoni near the Antarctic Polar Front. Deep-Sea Res. Part II 138, 126–140 (2017).Article 

Google Scholar 
Lüskow, F., Pakhomov, E. A., Stukel, M. R. & Décima, M. Biology of Salpa thompsoni at the Chatham Rise, New Zealand: demography, growth, and diel vertical migration. Mar. Biol. 167, 1–18 (2020).Pakhomov, E. A. & Froneman, P. W. Zooplankton dynamics in the eastern Atlantic sector of the Southern Ocean during the austral summer 1997/1998—Part 2: grazing impact. Deep-Sea Res. Part II 51, 2617–2631 (2004).Article 
ADS 

Google Scholar 
Iversen, M. H. et al. Sinkers or floaters? Contribution from salp pellets to the export flux during a large bloom event in the Southern. Ocean. Deep-Sea Res. Part II 138, 116–125 (2017).Article 
CAS 

Google Scholar 
Buesseler, K. O., Boyd, P. W., Black, E. E. & Siegel, D. A. Metrics that matter for assessing the ocean biological carbon pump. Proc. Natl Acad. Sci. USA 117, 9679 (2020).Article 
ADS 
CAS 

Google Scholar 
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).Article 

Google Scholar 
Hall, J., Safi, K. & Cumming, A. Role of microzooplankton grazers in the subtropical and subantarctic waters to the east of New Zealand. N.Z. J. Mar. Freshw. Res. 38, 91–101 (2004).Article 

Google Scholar 
Zeldis, J. R. & Décima, M. Mesozooplankton connect the microbial food web to higher trophic levels and vertical export in the New Zealand Subtropical Convergence Zone. Deep-Sea Res. Part I 155, 103146 (2020).Article 
CAS 

Google Scholar 
Hall, J. A., James, M. R. & Bradford-Grieve, J. M. Structure and dynamics of the pelagic microbial food web of the Subtropical Convergence region east of New Zealand. Aquat. Micro. Ecol. 20, 95–105 (1999).Article 

Google Scholar 
Bradford-Grieve, J. M. et al. Pelagic ecosystem structure and functioning in the subtropical front region east of New Zealand in austral winter and spring 1993. J. Plankton Res. 21, 405–428 (1999).Article 

Google Scholar 
Nodder, S. & Gall, M. Pigment fluxes from the Subtropical Convergence region, east of New Zealand: relationships to planktonic community structure. N.Z. J. Mar. Freshw. Res. 32, 441–465 (1998).Article 
CAS 

Google Scholar 
Nodder, S. D., Chiswell, S. M. & Northcote, L. C. Annual cycles of deep-ocean biogeochemical export fluxes in subtropical and subantarctic waters, southwest Pacific Ocean. J. Geophys. Res.: Oceans 121, 2405–2424 (2016).Article 
ADS 
CAS 

Google Scholar 
Kiko, R. et al. Biological and physical influences on marine snowfall at the equator. Nat. Geosci. 10, 852-+ (2017).Article 
ADS 
CAS 

Google Scholar 
Kelly, R. P., Shelton, A. O. & Gallego, R. Understanding PCR processes to draw meaningful conclusions from environmental DNA studies. Sci. Rep. 9, 12133 (2019).Article 
ADS 

Google Scholar 
Caron, D. A., Madin, L. P. & Cole, J. J. Composition and degradation of salp fecal pellets: implications for vertical flux in oceanic environments. J. Mar. Res. 47, 829–850 (1989).Article 
CAS 

Google Scholar 
Sempere, R., Yoro, S., Wambeke, F. V. & Charriere, B. Microbial decomposition of large organic particles in the northwestern Mediterranean Sea: an experimental approach. Mar. Ecol. Prog. Ser. 198, 61–72 (2000).Article 
ADS 

Google Scholar 
Dell’Anno, A. & Corinaldesi, C. Degradation and turnover of extracellular DNA in marine sediments: ecological and methodological considerations. Appl. Environ. Microbiol. 70, 4384–4386 (2004).Article 
ADS 

Google Scholar 
Torti, A., Lever, M. A. & Jørgensen, B. B. Origin, dynamics, and implications of extracellular DNA pools in marine sediments. Mar. Genomics 24, 185–196 (2015).Article 

Google Scholar 
Norris, R. Sediments of the Chatham Rise. N.Z. Dep. Sci. Ind. Res. Res. Bull. 159, 38 (1964).
Google Scholar 
Waite, A. M., Safi, K. A., Hall, J. A. & Nodder, S. D. Mass sedimentation of picoplankton embedded in organic aggregates. Limnol. Oceanogr. 45, 87–97 (2000).Article 
ADS 

Google Scholar 
Gafar, N. A. & Schulz, K. G. A three-dimensional niche comparison of Emiliania huxleyi and Gephyrocapsa oceanica: reconciling observations with projections. Biogeosciences 15, 3541–3560 (2018).Article 
ADS 
CAS 

Google Scholar 
Eynaud, F., Giraudeau, J., Pichon, J. J. & Pudsey, C. J. Sea-surface distribution of coccolithophores, diatoms, silicoflagellates and dinoflagellates in the South Atlantic Ocean during the late austral summer 1995. Deep-Sea Res. Part I 46, 451–482 (1999).Article 

Google Scholar 
Hagino, K., Okada, H. & Matsuoka, H. Coccolithophore assemblages and morphotypes of Emiliania huxleyi in the boundary zone between the cold Oyashio and warm Kuroshio currents off the coast of Japan. Mar. Micropaleontol. 55, 19–47 (2005).Article 
ADS 

Google Scholar 
Rhodes, L. L., Peake, B. M., Mackenzie, A. L. & Marwick, S. Coccolithophores Gephyrocapsa oceanica and Emiliana Huxleyi (Prymnesiophyceae = Haptophyceae) in New Zealand’s coastal waters: characteristics of blooms and growth in laboratory culture. N.Z. J. Mar. Freshw. Res. 29, 345–357 (1995).Article 

Google Scholar 
Ziveri, P., de Bernardi, B., Baumann, K.-H., Stoll, H. M. & Mortyn, P. G. Sinking of coccolith carbonate and potential contribution to organic carbon ballasting in the deep ocean. Deep-Sea Res. Part II 54, 659–675 (2007).Article 
ADS 

Google Scholar 
Buesseler, K. O. et al. VERTIGO (VERtical Transport In the Global Ocean): a study of particle sources and flux attenuation in the North Pacific. Deep Sea Res. II 55, 1522–1539 (2008).Article 
ADS 

Google Scholar 
Billett, D. S. M., Lampitt, R. S., Rice, A. L. & Mantoura, R. F. C. Seasonal sedimentation of phytoplankton to the deep-sea benthos. Nature 302, 520–522 (1983).Article 
ADS 
CAS 

Google Scholar 
Martin, J. H., Fitzwater, S. E., Gordon, R. M., Hunter, C. N. & Tanner, S. J. Iron, primary production and carbon nitrogen fluxes during the JGOFS North Atlantic Bloom Experiment. Deep-Sea Res. Part II 40, 115–134 (1993).Article 
ADS 
CAS 

Google Scholar 
Buesseler, K. O. et al. The effect of marginal ice-edge dynamics on production and export in the Southern Ocean along 170 degrees W. Deep-Sea Res. Part II 50, 579–603 (2003).Article 
ADS 
CAS 

Google Scholar 
Kiko, R. et al. Zooplankton-mediated fluxes in the eastern tropical north. Atl. Front. Mar. Sci. 7, 21 (2020).
Google Scholar 
Kelly, T. B. et al. The importance of mesozooplankton diel vertical migration for sustaining a mesopelagic food web. Front. Mar. Sci. 6, 508 (2019).Maiti, K., Charette, M. A., Buesseler, K. O. & Kahru, M. An inverse relationship between production and export efficiency in the Southern Ocean. Geophys. Res. Lett. 40, 1557–1561 (2013).Article 
ADS 

Google Scholar 
Loeb, V. et al. Effects of sea-ice extent and krill or salp dominance on the Antarctic food web. Nature 387, 897–900 (1997).Article 
ADS 
CAS 

Google Scholar 
Steinberg, D. K. et al. Long-term (1993–2013) changes in macrozooplankton off the Western Antarctic Peninsula. Deep-Sea Res. Part I 101, 54–70 (2015).Article 

Google Scholar 
Cabanes, D. J. E. et al. First evaluation of the role of salp fecal pellets on iron biogeochemistry. Front. Mar. Sci. 3, 10 (2017).Article 

Google Scholar 
Belcher, A. et al. Krill faecal pellets drive hidden pulses of particulate organic carbon in the marginal ice zone. Nat. Commun. 10, 1–8 (2019).Manno, C. et al. Continuous moulting by Antarctic krill drives major pulses of carbon export in the north Scotia Sea, Southern Ocean. Nat. Commun. 11, 6051 (2020).Article 
ADS 
CAS 

Google Scholar 
Law, C. S. et al. Did dilution limit the phytoplankton response to iron addition in HNLCLSi sub-Antarctic waters during the SAGE experiment? Deep-Sea Res. Part II 58, 786–799 (2011).Article 
ADS 
CAS 

Google Scholar 
Gutiérrez‐Rodríguez, A. et al. Decoupling between phytoplankton growth and microzooplankton grazing enhances productivity in Subantarctic waters on Campbell Plateau, southeast of New Zealand. J. Geophys. Res.: Oceans 125, e2019JC015550 (2020).Sherman, J., Gorbunov, M. Y., Schofield, O. & Falkowski, P. G. Photosynthetic energy conversion efficiency in the West Antarctic Peninsula. Limnol. Oceanogr. 65, 1–14 (2020).Peterson, B. J. Aquatic primary productivity and the 14C-CO2 method: a history of the productivity problem. Annu Rev. Ecol. Syst. 11, 359–385 (1980).Article 

Google Scholar 
Landry, M. R. & Hassett, R. P. Estimating the grazing impact of marine microzooplankton. Mar. Biol. 67, 283–288 (1982).Article 

Google Scholar 
Landry, M. R., Haas, L. W. & Fagerness, V. L. Dynamics of microbial plankton communities—experiments in Kaneohe Bay, Hawaii. Mar. Ecol. Prog. Ser. 16, 127–133 (1984).Article 
ADS 
CAS 

Google Scholar 
Gutierrez-Rodriguez, A., Latasa, M., Estrada, M., Vidal, M. & Marrase, C. Carbon fluxes through major phytoplankton groups during the spring bloom and post-bloom in the Northwestern Mediterranean Sea. Deep Sea Res. Part I 57, 486–500 (2010).Article 
CAS 

Google Scholar 
Gutierrez-Rodriguez, A. & Latasa, M. Pigment-based measurements of phytoplankton rates. in Phytoplankton Pigments Characterization, Chemotaxonomy and Applications in Oceanography (eds Roy, S. et al.) (Cambridge University Press, 2011) 472–495.Lorenzen, C. J. Determination of chlorophyll and pheo-pigments: spectrophotometric equations. Limnol. Oceanogr. 12, 343–346 (1967).Article 
ADS 
CAS 

Google Scholar 
Conover, R. J., Durvasula, R., Roy, S. & Wang, R. Probable loss of chlorophyll-derived pigments during passage through the gut of zooplankton, and some of the consequences. Limnol. Oceanogr. 31, 878–887 (1986).Article 
ADS 
CAS 

Google Scholar 
Latasa, M. A simple method to increase sensitivity for RP-HPLC phytoplankton pigment analysis. Limnol. Oceanogr. Meth 12, 46–53 (2014).Article 

Google Scholar 
Caporaso, J. G., Paszkiewicz, K., Field, D., Knight, R. & Gilbert, J. A. The Western English Channel contains a persistent microbial seed bank. ISME J. 6, 1089–1093 (2012).Article 
CAS 

Google Scholar 
Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581-+ (2016).Article 
CAS 

Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).Article 
CAS 

Google Scholar 
McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).Oksanen, J. et al. vegan: community ecology package. R package version 2.5-6. (2019).Piredda, R. et al. Diversity and temporal patterns of planktonic protist assemblages at a Mediterranean Long Term Ecological Research site. FEMS Microbiol. Ecol. 93, fiw200 (2017).Guillou, L. et al. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 41, D597–D604 (2013).Article 
CAS 

Google Scholar 
Pike, S. M., Buesseler, K. O., Andrews, J. & Savoye, N. Quantification of Th-234 recovery in small volume sea water samples by inductively coupled plasma-mass spectrometry. J. Radioanal. Nucl. Chem. 263, 355–360 (2005).Article 
CAS 

Google Scholar 
Benitez-Nelson, C. R. et al. Testing a new small-volume technique for determining Th-234 in seawater. J. Radioanal. Nucl. Chem. 248, 795–799 (2001).Article 
CAS 

Google Scholar 
Bone, Q. The Biology of Pelagic Tunicates (Oxford University Press, 1998).Foxton, P. An aid to the detailed examination of salps [Tunicata: Salpidae]. J. Mar. Biol. Assoc. UK 45, 679–681 (1965).Article 

Google Scholar 
Thompson, H. Pelagic Tunicates of Australia (Commonwealth Council for Scientific and Industrial Research, 1948).Iguchi, N. & Ikeda, T. Metabolism and elemental composition of aggregate and solitary forms of Salpa thompsoni (Tunicata: Thaliacea) in waters off the Antarctic Peninsula during austral summer 1999. J. Plankton Res. 26, 1025–1037 (2004).Article 
CAS 

Google Scholar 
von Harbou, L. et al. Salps in the Lazarev Sea, Southern Ocean: I. feeding dynamics. Mar. Biol. 158, 2009–2026 (2011).Article 

Google Scholar 
Pakhomov, E. A., Dubischar, C. D., Strass, V., Brichta, M. & Bathmann, U. V. The tunicate Salpa thompsoni ecology in the Southern Ocean. I. Distribution, biomass, demography and feeding ecophysiology. Mar. Biol. 149, 609–623 (2006).Article 

Google Scholar 
Huntley, M. E., Sykes, P. F. & Marin, V. Biometry and trophodynamics of Salp thompsoni Foxton (Tunicata, Thaliacea) near the Antarctic peninsula in austral summer 1983–1984. Polar Biol. 10, 59–70 (1989).Article 

Google Scholar 
Knauer, G. A., Martin, J. H. & Bruland, K. W. Fluxes of particulate carbon, nitrogen, and phosphorus in the upper water column of the northeast Pacific. Deep Sea Res. Part I 26, 97–108 (1979).Article 
ADS 
CAS 

Google Scholar 
Karl, D. M. et al. Seasonal and interannual variability in primary production and particle flux at Station ALOHA. Deep-Sea Res. Part II 43, 539–568 (1996).Article 
ADS 
CAS 

Google Scholar  More

During the COVID-19 pandemic, behavioral restrictions were imposed, after which various health problems were reported in many countries45,46. The pandemic has also increased food insecurity worldwide; consequently, panic buying has been observed in many countries, including Japan47. However, even in such situations, we found that diversity in local food access, ranging from self-cultivation to direct-to-consumer sales, was significantly associated with health and food security variables. Specifically, our results revealed the following five key discussion points.Urban agriculture in walkable neighborhoods bore fruit for health and food system resilience. However, the magnitude of its contribution differed depending on the type of urban agricultureThe results of this study showed that those who grew food by themselves at allotment farms and home gardens had significantly better subjective well-being and physical activity levels than those who did not. This result is in line with previous studies conducted during times free from the impact of infectious disease pandemics38,39,40. The use of direct sales was not related to subjective well-being but was significantly associated with physical activity. The reason might be that farm stand users tend to live in areas with farmland and travel to purchase fruits and vegetables at farm stands on foot or by bicycle. This result is consistent with that of a previous study demonstrating that the food environment in neighborhoods is an important component in promoting physical activity17.Our results also showed that those who grew food by themselves at allotment farms and those who purchased local foods at farm stands were significantly less anxious about the availability of fresh food both during the state of emergency and in the future than their counterparts. In contrast, home garden users showed significant differences only for the state of emergency. This result might be due to the differences in the size and yield of cultivation at allotment farms and home gardens. One lot in allotment farms in Tokyo can produce as much as or more than the average annual vegetable consumption per household in Japan48. However, home gardens are generally smaller and produce limited fresh foods for consumption, which may have influenced food security concerns.As in other countries, Japan imports much food from overseas and is deeply integrated into the large-scale global food system. However, as shown in this study, urban agriculture in Japanese suburbs forms small-scale, decentralized, and community-based local food systems. This multilayered food system can complement the disruptions and shortages of the global system when various problems occur for climatic, sociopolitical, or other reasons, such as pandemics. In fact, our empirical evidence suggests that urban agriculture in walkable neighborhoods, particularly allotment farms and direct-to-consumer sales at farm stands, contributed to the mitigation of food security concerns in neighborhood communities. This means that urban agriculture could enhance the resilience of the urban food system at a time when the global food system has been disrupted due to a pandemic. This validates recent discussions about the potential of urban agriculture to facilitate food system resilience10. Furthermore, our findings imply that the types of urban agriculture employed matter in determining the degree of contribution to food system resilience.To summarize the overall results, urban agriculture in walkable neighborhoods bore fruit for health and food system resilience during the COVID-19 pandemic. However, different types of urban agriculture exhibited varying associations with health and resilience. Allotment farms were positively related to all of the following: subjective well-being, physical activity, and food security concerns, both during the state of emergency and in the future. Home gardens were positively related to subjective well-being, physical activity, and food security concerns only during the state of emergency. Farm stands were positively related to physical activity and food security concerns both during the state of emergency and in the future.These differences may be due to the characteristics of the respective spaces. It is suggested that this diversity of urban agriculture has led to different types of people benefiting from various kinds of urban agriculture. Allotment farms were found to be associated with high subjective well-being, physical activity, and food security, but they may not be feasible for those who do not have enough physical strength because users are responsible for cultivating their lots, which measure 10–30 square meters40. In contrast, home gardens can be created even by those who are not confident in their physical strength. In fact, our study showed that women and older people engaged in home gardening more than men and younger people. In addition, direct-to-consumer sales at farm stands are the easiest way to obtain local fresh foods for those who do not have the time and space for allotment farms and home gardens. The need for urban agriculture has been argued in many countries2,3. However, little attention has been paid to its scale, accessibility, and diversity. Our study suggests that it is worthwhile to create diverse food production spaces within walkable neighborhoods while considering the diversity of people who access these spaces.Compared to other urban greenery and food retailers, the benefits of urban agriculture on subjective well-being and food security could be greaterCompared to the use of other urban green spaces, including urban parks, our results indicated that self-cultivation at allotment farms and home gardens was more strongly associated with subjective well-being. Previous studies have offered limited perspectives on the differences among various types of urban green spaces33. Our study further suggests that urban parks, allotment farms, and home gardens are differently associated with human health. However, as the reason was not determined, further research is needed.Furthermore, compared to other food retailers, such as supermarkets, convenience stores, and co-op deliveries, allotment farms and farm stands were more strongly associated with less anxiety about fresh food availability in the future. The availability of local fresh foods within walkable neighborhoods might have mitigated food security concerns because residents could grow food by themselves or directly observe farmers’ production processes, which may have made the difference from purchasing at places where the food systems were not visible.Flexibility in work style might promote urban agriculture in walkable neighborhoodsThere was an association between work style—working from home—and access to local food. According to the Ministry of Health, Labor and Welfare (https://www.mhlw.go.jp/english), 52% of Tokyo office workers worked from home during the first emergency declaration. Long commute times and high train congestion rates have been a problem in Tokyo suburbs, but remote workers have gained more time at and around their homes by reducing their commute times, increasing their opportunities to access local food in their walkable neighborhoods. Those who worked from home sought outdoor activities for refreshment and exercise and used a variety of urban green spaces during the pandemic49. Allotment farms and home gardens might be used as such urban green spaces. This result is consistent with previous studies assessing the characteristics of Canadian gardeners during the COVID-19 pandemic28,30.Until now, urban planners and policymakers have rarely taken work style into account. However, the flexibility of work styles and work hours may bring new insights; for example, those who work from home may become important players in urban agriculture. It has been pointed out that cities have a large hidden potential for urban agriculture by cultivating underused lands50. Our study suggests that such underused lands could be converted into productive urban landscapes for remote workers to engage in farming or gardening in between jobs as a hobby or as a side business.Food equity might be improved by urban agriculture in walkable neighborhoodsLocal fresh food is generally considered more expensive than junk food in high-income countries, creating social issues of food inequity. Therefore, past discussions on urban agriculture and food security have focused primarily on low-income households in socioeconomically disadvantaged areas24,25,26.In contrast, our study covered people from all income groups and found no statistically significant relationship between access to local food and income. This finding might be due to two urban cultural backgrounds regarding local food in Tokyo, that is, accessibility and affordability. First, residential segregation by income levels is not noteworthy in Tokyo and people from various income brackets live mixed in the same neighborhoods51. Therefore, most urban residents living in the suburbs have geographically equitable opportunities to access local foods. Second, local foods sold at farm stands are affordable. Prices are almost the same or cheaper than buying food at food retailers. While prices increase because of middleman margins related to shipping in the wholesale market, such increases are unnecessary when selling directly to consumers at farm stands. In addition, the allotment farm lots are not expensive to rent, particularly those operated by local municipalities (Supplementary Note 1).These two backgrounds make local fresh food physically and economically accessible to consumers of all income levels, resulting in food equity. This is particularly important because the concept of food system resilience includes the equitability perspective27.The integration of urban agriculture into walkable neighborhoods is a fruitful wayWhile the current discussion on walkable neighborhoods does not emphasize urban agriculture, our evidence indicated its effectiveness. The concept of walkable neighborhoods (e.g., the 15-min city model) stresses the decarbonization benefit of limiting vehicle travel, as well as the health benefits of promoting walking and cycling13,14,15,16. In addition, our research indicated that urban agriculture in walkable neighborhoods benefited health and well-being by increasing recreational outdoor opportunities to neighborhood communities, including remote workers. It also contributed to food system resilience by providing local foods to all people, including low-income households, when the global food system was disrupted due to the pandemic. Furthermore, recent studies on urban agriculture reported the decarbonization benefit of reducing carbon footprints in food production and distribution7,8. Small-scale and community-based urban agriculture in walkable neighborhoods might especially bring this benefit because neighborhood communities travel to farms on foot or by bicycle, which means almost no emission by distribution. While urban green spaces have various health benefits32,33,34,35, urban agriculture also contributes to food system resilience as well as carbon emission reduction, which makes it unique.Urban agriculture was once considered a failure of urban planning in Japan because it symbolized uncontrolled sprawl. This is analogous to the Western view, as urban agriculture was once considered the ultimate oxymoron1. However, our empirical evidence suggests that the urban‒rural mixture at neighborhood scales is a reasonable urban form that contributes to the resilience of the urban food system and to the health and well-being of neighborhood communities. It is no longer a failure of urban planning but a legacy of urban sprawl in the current urban context.Our study showed that integrating urban agriculture into walkable neighborhoods is a fruitful way of creating healthier cities and developing more resilient urban food systems during times of uncertainty. In cities where there is no farmland in intraurban areas, it would be considered effective to utilize underused spaces such as vacant lots and rooftops as productive urban landscapes. In growing cities where urban areas are still expanding, it would be advantageous to conserve agricultural landscapes within their urban fabrics. Our study could provide referential insights and robust evidence for urban policy to integrate urban agriculture into walkable neighborhoods.This study has potential limitations, including the timing of the survey and the measurement method that was utilized. We conducted the survey between June 4 and 8, 2020, just after the end of the first declaration of a state of emergency by the Japanese government. During this period, the main cultivation activities were planting and growing, and the harvest was just beginning. This seasonal constraint may have influenced the results. Because the survey was conducted during the pandemic, we used subjective methods to measure health and well-being status. However, the results might be different using objective methods52, thus further research is necessary. In addition, a longitudinal study is needed to determine whether the trends observed in this study were specific to the emergency period or whether they will persist after the COVID-19 pandemic. More

Analytical method validationThe results of the precision study with relative standard deviation (RSD), and accuracy are shown in Table 1. Through the precision study we found the value of RSD as less than 5%. Moreover, accuracy was done with percent recovery experiments. The results showed that the percentage recoveries for spiked samples were in the range of 95.7–103.7%.Table 1 Shows percent (%) recovery and relative standard deviation.Full size tablePhysicochemical properties and water quality indexThe investigations of the water quality properties of the Narora channel are shown in Table 2. The temperature, TDS, turbidity, and alkalinity were within the standards of the country18 and WHO19 (taken from UNEPGEMS). While pH and dissolved oxygen (D.O) were above the recommended standards indicating poor water quality. Moreover, the detected heavy metals were in the following order Ni  > Fe  > Cd  > Zn  > Cr  > Cu  > Mn. Among these heavy metals Mn, Cu, and Zn were within the recommended limits whereas Cr, Fe, Ni, and Cd were crossing the limits18 contributing to the poor quality. Furthermore, the WQI calculation will give more insights into the overall quality of water as it explains the combined effect of several physicochemical properties12. Its calculation is done simply by converting numerous variables of water quality into a single number12,20. In addition to this, WQI simplifies all the data and helps in clarifying water quality issues by combining the complex data and producing a score that shows the status of water quality2,12,21. The WQI classifies water quality status into five groups such as if WQI  Cu  > Zn  > Fe  > Zn  > Ni  > Cr from root to stalk; and Mn  > Cd  > Zn  > Cu  > Fe  > Ni  > Cr from stalk to leaves.Table 5 Heavy metal concentrations in Eichhornia crassipes (mg/kg.dw).Full size tableFigure 3MPI values in E. crassipes.Full size imageTable 6 Bioaccumulation factor (BAF), transfer factor (TF), and mobility factor (MF) in plant E. crassipes.Full size tableThese factors BAF, TF, and MF are utilized to monitor the level of anthropogenic pollution in plants and their surrounding medium2,15,32,34,35. BAF shows the concentrations of heavy metals bioaccumulated by plants from the water. If the BAF  > 1 it indicates hyperaccumulation36. So, in the present study, all the concerned heavy metals were hyperaccumulated in the plant. The TF elucidates the capability of the plant to translocate the accumulated metals to its other parts. The roots of E. crassipes showed the highest translocation capacity for Ni (1.57) as well as Zn (1.30) to other parts. If the value of TF exceeds 1, then it represents the high accumulation efficiency37,38, therefore, plants will be considered as the hyperaccumulators for the Ni and Zn. Although the Cd was the highest accumulated metal in the plant, it could have been because of its may be because of its low TF. Whereas, TF values lower than 1 for Cr, Mn, Fe, Cu, and Cd pointed out that this plant’s roots act as a non-hyperaccumulator for these heavy metals. Furthermore, the highest MF values were depicted for Mn in both cases which reflects that E. crassipes can suitably be used for phytoextraction of Mn as well as for Cd, Zn, Fe, Ni, and Cu. The BAF, TF, and MF of Cr are low in the present study, which implies that roots are limiting the Cr. Moreover, if the BAF ≤ 1.00 then it shows the capability of absorption only rather than accumulation36,37. In addition, if the values of BAF, TF, and MF exceed 1, plants can also work for phytoextraction. Furthermore, if the BAF  > 1 and TF  More

All the materials followed relevant institutional and national guidelines and legislation.MitesWe used a T. kanzawai population collected from trifoliate orange trees (Poncirus trifoliata [L.] Raf.) in 2018 in Kyoto, Japan, and a T. urticae population collected from chrysanthemum plants (Chrysanthemum morifolium Ramat.) in 1998 in Nara, Japan. These populations were reared on adaxial surfaces of kidney bean (Phaseolus vulgaris L.) primary leaves, which were pressed onto water-saturated cotton in Petri dishes (90 mm diameter, 14 mm depth). The water-saturated cotton served as a barrier to prevent mites from escaping. The dishes were maintained at 25 °C, 50% relative humidity, and a 16L:8D photoperiod. All experiments were conducted under these conditions. We only used mated adult females (i.e., the dispersal stage) of T. kanzawai or T. urticae mites.CaterpillarsWe used caterpillars of four lepidopteran species: Bombyx mori L., P. Xuthus, Spodoptera litura Fabricius and T. oldenlandiae. We collected eggs and larvae of T. oldenlandiae from C. japonica in 2021 in Kyoto, Japan, and reared them on C. japonica leaves until pupation. Theretra oldenlandiae shares Vitaceae host plants with T. kanzawai and T. urticae8,15. We collected eggs and larvae of P. xuthus from Ptelea trifoliata in 2021 in Kyoto, Japan, and reared them on Citrus unshiu Markov. leaves until pupation. Papilio. xuthus and T. kanzawai share P. trifoliata as a host plant in Kyoto (Kinto, personal observation).We obtained commercial populations of the B. mori Kinshu × Showa strain (Ueda-sanshu Co., Ltd, Nagano, Japan) or the w1-pnd strain. We reared B. mori larvae on an artificial diet produced at the Kyoto Institute of Technology. Although T. kanzawai use Morus alba, a food plant for the B. mori strain, the mite and the strain never encounter one another in the wild, because the B. mori strain has been domesticated for hundreds of years.We obtained a sub-cultured population of S. litura from the Kyoto Institute of Technology. We reared first to fourth instars of S. litura on an artificial diet (Insecta LFM, Nosan Insect Materials, Kanagawa, Japan), while final instars were fed P. vulgaris leaves. Because S. litura feeds on various wild and cultivated plants22,23, it may share some host plants with T. kanzawai and T. urticae, both of which also feed on many host plant species8,9,10.We reared caterpillars of T. oldenlandiae, P. xuthus, and S. litura in 900 mL transparent plastic cups and caterpillars of B. mori in transparent plastic containers (140 × 220 × 35 mm). All caterpillars were maintained under the same laboratory conditions described above.PlantsWe used several parts of P. vulgaris plants in the following experiments. This species is a preferred food for both mite species16,17 and S. litura24, but the other three caterpillar species do not feed on it (Kinto, personal observation). We thus used P. vulgaris rather than shared host plants, because some caterpillars and mites (T. urticae and P. xuthus, for example) do not share any host plant.Avoidance of caterpillar traces on leaf surfaces by spider mitesTo examine whether spider mites avoid settling on host plant surfaces bearing caterpillar traces, we conducted dual-choice tests using paired adjacent leaf squares with and without caterpillar traces. We did not use whole plants because, in practice, it was difficult to induce caterpillar traces on whole plants. We used two spider mite species (T. kanzawai and T. urticae) and four caterpillar species (T. oldenlandiae, P. xuthus, B. mori, and S. litura). We cut a 10 × 20 mm leaf piece from a fully expanded primary kidney bean leaf and then cut the piece into two equal squares (10 × 10 mm). To introduce caterpillar traces to one square, we arranged them on a separate piece of paper towel on water-saturated cotton. This procedure was necessary because the caterpillars used were larger than individual leaf squares. Then we placed a fourth or final instar caterpillar on the squares and induced the caterpillar to walk across every leaf square three times (Fig. 1a). We carefully removed all caterpillar-produced silk threads from the squares. Within 30 min, we arranged the square (trace +) to touch against the other square (trace −) on water-saturated cotton in a Petri dish. Subsequently, a 2- to 4-day-old mated adult female of T. kanzawai or T. urticae was introduced onto a pointed piece of Parafilm in contact with both leaf edges using a fine brush (Fig. 1a). We recorded the leaf square onto which the mite had settled at 2 h after its introduction, as preliminary observations confirmed that all females would settle on a particular leaf within that period. Each female mite and pair of leaf squares were used only once. All tests described below were conducted between 13:00 and 17:00 h, when adult female spider mites actively disperse by walking. There were 14 replicates using traces of T. oldenlandiae, 48 of P. xuthus, 20 of B. mori, and 26 of S. litura for T. kanzawai, as well as 18, 32, 16, and 47, respectively, for T. urticae. Data were subjected to two-tailed binomial tests with the common null hypothesis that a spider mite would settle on the two squares with equal probability (i.e., 0.5).Figure 1(a) Procedure used to observe avoidance of caterpillar traces by spider mites. (b) Experimental setup used to observe avoidance of B. mori traces on plant stems by T. kanzawai. (c) Experimental setup used to observe avoidance of B. mori trace extracts by T. kanzawai.Full size imageDuration of B. mori trace avoidance by T. kanzawai
To examine whether the effects of caterpillar traces on spider mite avoidance decline over time, we used T. kanzawai mites and B. mori caterpillars. We used B. mori because populations can be easily maintained over many generations. We prepared bean leaf squares with B. mori traces in the same manner descried above and preserved the traced square on water-saturated cotton for 0 h (n = 30), 24 h (n = 29), 48 h (n = 28), or 72 h (n = 28). Then we arranged the square (trace +) to lie in close proximity to the control square (trace −) that had been preserved for the same periods of time. Then we compared the avoidance response of T. kanzawai females in the same manner described above.Avoidance of B. mori traces on plant stems by T. kanzawai
To examine whether T. kanzawai females avoid walking along plant stems bearing caterpillar traces, we used Y-shaped kidney bean stems (Fig. 1b). We cut symmetric bean plants ca. 15 days after sowing from their base and inserted them perpendicularly into a 5 mL glass bottle filled with water and wet cotton. To induce caterpillar traces on one branch of the stem, we allowed a silkworm to crawl from the branching point to the far end of one branch three times for each stem (n = 20). Then we introduced a T. kanzawai adult female at a release point 35 mm below the branch point (Fig. 1b). We recorded the branch along which the female walked to the far end. Each female mite and each Y-shaped stem were used only once. The numbers of females were compared using binomial tests in the same manner described above.Avoidance of B. mori trace extracts by T. kanzawai
To extract chemical traces of caterpillar, we introduced 10 third instar B. mori to a glass Petri dish (120 mm diameter, 60 mm depth). After 1 h, we removed all caterpillars and washed the inside bottom of the dish with 1.0 mL acetone. We replicated the procedure twice using different individuals to combine all extracts and to acquire enough extract for the following experiment.To examine avoidance of B. mori trace extracts by T. kanzawai females, we conducted dual-choice experiments using T-shaped pathways of filter paper (35 × 35 mm; width, 2 mm; Fig. 1c). Using disposable micropipettes (Drummond Scientific Co., PA, USA), 1.75 caterpillar equivalents (i.e., 60 µL) of acetone extract were applied to an alternately selected branch (17.5 mm long) of each pathway (i.e., 0.10 caterpillar equivalent/mm), with control acetone applied to the other branch. We applied each solution dropwise at the junction point to minimize mixing. After evaporating the solvent from those pathways, we perpendicularly suspended them (Fig. 1c) and introduced an adult female mite at 2 days post-maturation onto the bottom of each pathway using a fine brush and recorded the branch along which the female first walked to the far end. Each female mite and each T-shaped filter paper were used only once, with 19 replicates. Each female mite made a choice within 10 min. The avoidance response of T. kanzawai was analysed in the same manner described above.Indirect effects of B. mori traces on T. kanzawai via plantsTo determine whether B. mori traces on plants indirectly affect the performance of T. kanzawai on plants, we introduced 70–80 randomly selected quiescent female deutonymphs of T. kanzawai onto kidney bean leaf disks. Immediately after synchronized adult emergence, we introduced the same number of adult males to allow mating; the detailed procedure is described elsewhere25. After 24 h, we transferred the females singly onto 10 × 10 mm bean leaf squares with or without B. mori traces prepared as described above. Because the number of eggs laid within a certain period is considered the most sensitive performance index of spider mite females26,27, any plant-mediated indirect interaction, such as defence induction in response to caterpillar traces, should result in lower egg numbers laid by the test females. We counted the eggs laid on the leaf squares 24 h after their introduction. One female that laid no eggs during the 24 h period (n = 1, trace +) was excluded from the analysis. We obtained 33 and 36 replicates for the trail+ and trail– conditions, respectively. We compared the numbers of eggs laid on leaves with and without B. mori traces using a generalized linear model with a Poisson error distribution using the SAS 9.22 software (SAS Institute Inc., Cary, NC, USA).EthicsThis article does not contain any studies with human participants or animals. More

Arunrat, N., Sereenonchai, S., Chaowiwat, W. & Wang, C. Climate change impact on major crop yield and water footprint under CMIP6 climate projections in repeated drought and flood areas in Thailand. Sci. Total Environ. 807, 150741 (2022).ADS 
CAS 

Google Scholar 
Chandio, A. A., Shah, M. I., Sethi, N. & Mushtaq, Z. Assessing the effect of climate change and financial development on agricultural production in ASEAN-4: the role of renewable energy, institutional quality, and human capital as moderators. Environ. Sci. Pollut. Res. 29, 13211–13225 (2022).
Google Scholar 
Masood, N., Akram, R., Fatima, M., Mubeen, M., Hussain, S., Shakeel, M., Khan, N., Adnan, M., Wahid, A., Shah, A. N. and Ihsan, M. Z. (2022) Insect pest management under climate change. In Building climate resilience in agriculture. Springer, ChamOzdemir, D. The impact of climate change on agricultural productivity in Asian countries: A heterogeneous panel data approach. Environ. Sci. Pollut. Res. 29, 8205–8217 (2022).
Google Scholar 
Aidoo, O. F. et al. Climate-induced range shifts of invasive species (Diaphorina citri Kuwayama). Pest Manag. Sci. 78, 2534–2549 (2022).CAS 

Google Scholar 
Hebbar, K. B. et al. Predicting the Potential Suitable Climate for Coconut (Cocos nucifera L.) Cultivation in India under Climate Change Scenarios Using the MaxEnt Model. Plants. 11, 731 (2022).
Google Scholar 
Martín-Vélez, V. & Abellán, P. Effects of climate change on the distribution of threatened invertebrates in a Mediterranean hotspot. Insect Conserv. Divers. 15, 370–379 (2022).
Google Scholar 
Williams, J. J., Freeman, R., Spooner, F. & Newbold, T. Vertebrate population trends are influenced by interactions between land use, climatic position, habitat loss and climate change. Glob. Chang. Biol. 28, 797–815 (2022).CAS 

Google Scholar 
Aidoo, O. F. et al. Lethal yellowing disease: insights from predicting potential distribution under different climate change scenarios. J. Plant Dis. Prot. 128, 1313–1325 (2021).
Google Scholar 
Sofaer, H. R. et al. Development and delivery of species distribution models to inform decision-making. Bioscience 69, 544–557 (2019).
Google Scholar 
Mead FW, The Asiatic citrus psyllid, Diaphorina citri Kuwayama (Homoptera: Psyllidae). Florida Department of Agriculture Conservation Service, Division of Plant Industry Entomological Circular No. 180.Bové, J. M. Huanglongbing: A destructive, newly-emerging, century-old disease of citrus. Plant Pathol. J. 1, 7–37 (2006).
Google Scholar 
Li, S., Wu, F., Duan, Y., Singerman, A. & Guan, Z. Citrus greening: Management strategies and their economic impact. HortScience 55, 604–612 (2020).
Google Scholar 
Jia, H. et al. Genome editing of the disease susceptibility gene Cs LOB 1 in citrus confers resistance to citrus canker. Plant Biotechnol. J. 15, 817–823 (2017).CAS 

Google Scholar 
Ehsani, R., Dewdney, M. & Johnson, E. Controlling HLB with thermotherapy: What have we learned so far?. Citrus Ind. News 9, 26–28 (2016).
Google Scholar 
Spreen, T. H., Baldwin, J. P. & Futch, S. H. An economic assessment of the impact of Huanglongbing on citrus tree plantings in Florida. J. Hortic. Sci. 49, 1052–1055 (2014).
Google Scholar 
Djeddour, D., Pratt, C., Constantine, K., Rwomushana, I. and Day, R., (2021) The Asian citrus greening disease (Huanglongbing). Evidence note on invasiveness and potential economic impacts for East Africa. CABI Working Paper, 24, 94Hu, J., Jiang, J. & Wang, N. Control of citrus Huanglongbing via trunk injection of plant defense activators and antibiotics. Phytopathology 108, 186–195 (2018).CAS 

Google Scholar 
Fan, G. C. et al. Evaluation of thermotherapy against Huanglongbing (citrus greening) in the greenhouse. J. Integr. Agric. 15, 111–119 (2016).
Google Scholar 
Nguyen, V. A., Bartels, D. & Gilligan, C. Modelling the spread and mitigation of an emerging vector-borne pathogen: citrus greening in the US. Biorxiv https://doi.org/10.1101/2022.05.04.490566 (2022).Article 

Google Scholar 
Milosavljević, I. et al. Post-release evaluation of Diaphorencyrtus aligarhensis (Hymenoptera: Encyrtidae) and Tamarixia radiata (Hymenoptera: Eulophidae) for biological control of Diaphorina citri (Hemiptera: Liviidae) in Urban California, USA. Agronomy 12, 583 (2022).
Google Scholar 
Maluta, N., Castro, T. & Lopes, J. R. S. Entomopathogenic fungus disrupts the phloem-probing behavior of Diaphorina citri and may be an important biological control tool in citrus. Sci. Rep. 12, 1–10 (2022).
Google Scholar 
Hall, D. G., Richardson, M. L., Ammar, E. D. & Halbert, S. E. Asian citrus psyllid, Diaphorina citri, vector of citrus huanglongbing disease. Entomol. Exp. Appl. 146, 207–223 (2013).
Google Scholar 
Vázquez-García, M. et al. Insecticide resistance in adult Diaphorina citri Kuwayama1 from lime orchards in central west Mexico. Southwest. Entomol. 38, 579–596 (2013).
Google Scholar 
Naeem, A., Freed, S., Jin, F. L., Akmal, M. & Mehmood, M. Monitoring of insecticide resistance in Diaphorina citri Kuwayama (Hemiptera: Psyllidae) from citrus groves of Punjab Pakistan. Crop Prot. 86, 62–68 (2016).CAS 

Google Scholar 
Hulme, P. E. et al. Grasping at the routes of biological invasions: A framework for integrating pathways into policy. J. Appl. Ecol. 45, 403–414 (2008).
Google Scholar 
Oke, A. O., Oladigbolu, A. A., Kunta, M., Alabi, O. J. & Sétamou, M. First report of the occurrence of Asian citrus psyllid Diaphorina citri (Hemiptera: Liviidae), an invasive species in Nigeria. West Africa. Sci. Rep. 10, 1–8 (2020).
Google Scholar 
Tang, Y.Q. (1990) On the parasite complex of Diaphorina citri Kuwayama (Homoptera: Psyllidae) in Asian-Pacific and other areas. In proceedings 4th international conference on citrus rehabilitation, Chiang Mai, Thailand. 4: 240 245Chien, C. C., Chiu, S. C. & Ku, S. C. Biological control of Diaphorina citri in Taiwan. Fruits 44, 401–407 (1989).
Google Scholar 
Hoddle, M. S. Foreign exploration for natural enemies of Asian citrus psyllid, Diaphorina citri (Hemiptera: Psyllidae), in the Punjab of Pakistan for use in a classical biological control program in California USA. Pakistan Entomol. 34, 1–5 (2012).
Google Scholar 
Étienne, J., Quilici, S., Marival, D., Franck, A. & Gonzalez Fernandez, C. Biological control of Diaphorina citri (Hemiptera: Psyllidae) in Guadeloupe by imported Tamarixia radiata (Hymenoptera: Eulophidae). Fruits 56, 307–315 (2001).
Google Scholar 
Qureshi, J. A., Rogers, M. E., Hall, D. G. & Stansly, P. A. Incidence of invasive Diaphorina citri (Hemiptera: Psyllidae) and its introduced parasitoid Tamarixia radiata (Hymenoptera: Eulophidae) in Florida citrus. J. Econ. Entomol. 102, 247–256 (2009).
Google Scholar 
Chen, X., Triana, M. & Stansly, P. A. Optimizing production of Tamarixia radiata (Hymenoptera: Eulophidae), a parasitoid of the citrus greening disease vector Diaphorina citri (Hemiptera: Psylloidea). Biol. Control. 105, 13–18. https://doi.org/10.1016/j.biocontrol.2016.10.010 (2017).Article 

Google Scholar 
Kistner, E. J., Amrich, R., Castillo, M., Strode, V. & Hoddle, M. S. Phenology of Asian citrus psyllid (Hemiptera: Liviidae), with special reference to biological control by Tamarixia radiata, in the residential landscape of southern California. J. Econ. Entomol. 109, 1047–1057. https://doi.org/10.1093/jee/tow021 (2016).Article 

Google Scholar 
Ramos Aguila, L. C. et al. Temperature-dependent biological control effectiveness of Tamarixia radiata (Hymenoptera: Eulophidea) under laboratory conditions. J. Econ. Entomol. 114, 2009–2017 (2021).
Google Scholar 
Ramos Aguila, L. C. et al. Temperature-dependent demography and population projection of Tamarixia radiata (Hymenoptera: Eulophidea) reared on Diaphorina citri (Hemiptera: Liviidae). J. Econ. Entomol. 113, 55–63 (2020).
Google Scholar 
Ashraf, H. J. et al. Comparative microbiome analysis of Diaphorina citri and its associated parasitoids Tamarixia radiata and Diaphorencyrtus aligarhensis reveals Wolbachia as a dominant endosymbiont. Environ. Microbiol. 24, 1638–1652 (2022).CAS 

Google Scholar 
Chow, A. & Sétamou, M. Parasitism of Diaphorina citri (Hemiptera: Liviidae) by Tamarixia radiata (Hymenoptera: Eulophidae) on residential citrus in Texas: Importance of colony size and instar composition. Biol. Control 165, 104796 (2022).
Google Scholar 
Ajene, I. J. et al. Habitat suitability and distribution potential of Liberibacter species (“Candidatus Liberibacter asiaticus” and “Candidatus Liberibacter africanus”) associated with citrus greening disease. Environ. Microbiol. 26, 575–588 (2020).
Google Scholar 
Shabani, F., Kumar, L. & Ahmadi, M. A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area. Ecol. Evol. 6, 5973–5986 (2016).
Google Scholar 
Kearney, M. & Porter, W. Mechanistic niche modelling: Combining physiological and spatial data to predict species’ ranges. Ecol 12, 334–350 (2009).
Google Scholar 
Byeon, D. H., Jung, S. & Lee, W. H. Review of CLIMEX and MaxEnt for studying species distribution in South Korea. J. Asia-Pac. Biodivers. 1, 325–333 (2018).
Google Scholar 
Kriticos, D. J., Yonow, T. & McFadyen, R. E. The potential distribution of Chromolaena odorata (Siam weed) in relation to climate. Weed Res 45, 246–254 (2005).
Google Scholar 
Wharton, T. N. & Kriticos, D. J. The fundamental and realized niche of the Monterey pine aphid, Essigella californica (Essig) (Hemiptera: Aphididae): implications for managing softwood plantations in Australia. Divers. Distrib. 10, 253–262 (2004).
Google Scholar 
Sutherst, R., Maywald, G. and Kriticos, D., CLIMEX version 3: user’s guide. (2007).Ramirez-Cabral, N. Y., Kumar, L. & Shabani, F. Global alterations in areas of suitability for maize production from climate change and using a mechanistic species distribution model (CLIMEX). Sci. Rep. 7, 1–3 (2017).CAS 

Google Scholar 
McCalla, K. A., Keçeci, M., Milosavljević, I., Ratkowsky, D. A. & Hoddle, M. S. The influence of temperature variation on life history parameters and thermal performance curves of Tamarixia radiata (Hymenoptera: Eulophidae), a parasitoid of the Asian citrus psyllid (Hemiptera: Liviidae). J. Econ. Entomol. 112, 1560–1574 (2019).
Google Scholar 
Gonzalez-Cabrera, J., Moreno-Carrillo, G., Sanchez-Gonzalez, J. A. & Bernal, H. C. Natural and augmented parasitism of tamarixia radiata (Hymenoptera Eulophidae) in Urban Areas of western Mexico. Entomol. Sci. 53, 486–492. https://doi.org/10.18474/JES17-112.1 (2018).Article 

Google Scholar 
Chavez, Y. et al. Tamarixia radiata (Waterston) and Cheilomenes sexmaculata (Fabricius) as biological control agents of Diaphorina citri Kuwayama in Ecuador. Chil. J. Agric. Res. 77, 180–184. https://doi.org/10.4067/S0718-58392017000200180 (2017).Article 

Google Scholar 
Flores, D. & Ciomperlik, M. Biological control using the ectoparasitoid, Tamarixia radiata, against the Asian citrus psyllid, Diaphorina citri, in the lower Rio Grande valley of Texas. Southwest. Entomol. 42, 49–59. https://doi.org/10.3958/059.042.0105 (2017).Article 

Google Scholar 
Parra, J. R., Alves, G. R., Diniz, A. J. & Vieira, J. M. Tamarixia radiata (Hymenoptera: Eulophidae) × Diaphorina citri (Hemiptera: Liviidae): Mass rearing and potential use of the parasitoid in Brazil. J. Integr. Pest. Manag. https://doi.org/10.1093/jipm/pmw003 (2016).Article 

Google Scholar 
Diniz, A. J. F., Otimização da criação de Diaphorina citri Kuwayama, 1908 (Hemiptera: Liviidae) e de Tamarixia radiata (Waterston, 1922) (Hymenoptera: Eulophidae), visando a produção em larga escala do parasitoide e avalliação do seu estabelecimento em campo. Tese (Doutorado em Entomologia)—Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo, São Paulo. (2013)Hoddle, M. S. & Pandey, R. Host range testing of Tamarixia radiata (Hymenoptera: Eulophidae) sourced from the Punjab of Pakistan for classical biological control of Diaphorina citri (Hemiptera: Liviidae: Euphyllurinae: Diaphorinini) in California. J. Econ. Entomol. 107, 125–136. https://doi.org/10.1603/EC13318 (2014).Article 

Google Scholar 
Gómez-Torres, M. L., Nava, D. E. & Parra, J. R. Thermal hygrometric requirements for the rearing and release of Tamarixia radiata (Waterston) (Hymenoptera, Eulophidae). Rev. Bras. Entomol. 58, 291–295. https://doi.org/10.1590/S0085-56262014000300011 (2014).Article 

Google Scholar 
Gómez-Torres, M. L., Nava, D. E. & Parra, J. R. Life table of Tamarixia radiata (Hymenoptera: Eulophidae) on Diaphorina citri (Hemiptera: Psyllidae) at different temperatures. J. Econ. Entomol. 105, 338–343 (2012).
Google Scholar 
Chong, J. H., Roda, A. L. & Mannion, C. M. Density and natural enemies of the Asian Citrus Psyllid, Diaphorina citri (Hemiptera: Psyllidae), in the residential landscape of Southern Florida. J. Agric. Urban Entomol. 27, 33–49. https://doi.org/10.3954/11-05.1 (2010).Article 

Google Scholar 
Pluke, R. W., Qureshi, J. A. & Stansly, P. A. Citrus flushing patterns, Diaphorina citri (Hemiptera: Psyllidae) populations and parasitism by Tamarixia radiata (Hymenoptera: Eulophidae) in Puerto Rico. Florida Entomol. 91, 36–42 (2008).
Google Scholar 
Ashraf, H. J. et al. Genetic diversity of Tamarixia radiata populations and their associated endosymbiont Wolbachia species from China. Agronomy 11, 2018 (2021).CAS 

Google Scholar 
Jung, J. M., Lee, W. H. & Jung, S. Insect distribution in response to climate change based on a model: Review of function and use of CLIMEX. Entomol. Res. 46, 223–235 (2016).
Google Scholar 
Kriticos, D. J. et al. CLIMEX Version 4, 184p (2015).
Google Scholar 
Gomez-Marco, F., Gebiola, M., Baker, B. G., Stouthamer, R. & Simmons, G. S. Impact of the temperature on the phenology of Diaphorina citri (Hemiptera: Liviidae) and on the establishment of Tamarixia radiata (Hymenoptera: Eulophidae) in urban areas in the lower Colorado Desert in Arizona. Environ. Entomol. 48, 514–523 (2019).
Google Scholar 
Vieira, J. M. Biologia em temperaturas alternantes e exigências térmicas de Diaphorina citri Kuwayama, 1908 (Hemiptera: Liviidae) e Tamarixia radiata (Waterston, 1922) (Hymenoptera: Eulophidae) visando ao seu zoneamento em regiões citrícolas do estado (Doctoral dissertation, Universidade de São Paulo).Castillo, J., Jacas, J. A., Peña, J. E., Ulmer, B. J. & Hall, D. G. Effect of temperature on life history of Quadrastichus haitiensis (Hymenoptera: Eulophidae), an endoparasitoid of Diaprepes abbreviatus (Coleoptera: Curculionidae). Biol. Control. 36, 189–196 (2006).
Google Scholar 
McFarland, C. D. & Hoy, M. A. Survival of Diaphorina citri (Homoptera: Psyllidae), and its two parasitoids, Tamarixia radiata (Hymenoptera: Eulophidae) and Diaphorencyrtus aligarhensis (Hymenoptera: Encyrtidae), under different relative humidities and temperature regimes. Fla. Entomol. 84, 227–233 (2001).
Google Scholar 
Fauvergue, X. & Quilici, S. Etude de certains parametres de la biologie de Tamarixia radiata (Waterston, 1992)(Hymenoptera: Eulophidae), ectoparasitoide primaire de Diaphorina citri Kuwayama (Hemiptera: Psyllidae) vecteur du greening des agrumes. Paris Fruits 46, 179–179 (1991).
Google Scholar 
Araújo, F. H. et al. Modelling climate suitability for Striga asiatica, a potential invasive weed of cereal crops. Crop Prot. 1(160), 106050 (2022).
Google Scholar 
Silva, D. A. & RS, Kumar L, Shabani F and Picanço MC,. Potential risk levels of invasive Neoleucinodes elegantalis (small tomato borer) in areas optimal for open-field Solanum lycopersicum (tomato) cultivation in the present and under predicted climate change. Pest Manag. Sci 73, 616–627 (2017).
Google Scholar 
Kumar, S., Neven, L. G. & Yee, W. L. Evaluating correlative and mechanistic niche models for assessing the risk of pest establishment. Ecosphere 5, 1–23. https://doi.org/10.1890/ES14-00050.1 (2014).Article 
CAS 

Google Scholar 
Kriticos, D. J. et al. CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods Ecol. Evol. 1, 53–64 (2012).
Google Scholar 
Santana Júnior PA, Worldwide spatial distribution of Tuta absoluta (Lepidoptera: Gelechiidae) and its natural enemies under current and future climatic change conditions through modelling. 136 f 2019 (Tese (Doutorado em Fitotecnia) – Universidade Federal de Viçosa, 2019).
Google Scholar 
Kriticos, D. J., Maywald, G. F., Yonow, T., Zurcher, E. J., Herrmann, N. I. and Sutherst, R. W., CLIMEX Version 4: Exploring the effects of climate on plants, animals and diseases. CSIRO, Canberra.156, (2015)Ramos Aguila, L. C. et al. Temperature-dependent demography and population projection of Tamarixia radiata (Hymenoptera: Eulophidea) reared on Diaphorina citri (Hemiptera: Liviidae). J. Econ. Entomol. 113, 55–63 (2019).
Google Scholar 
Oliveira, R. C., Modelagem de nicho ecológico para Helicoverpa punctigera (Wallengren, 1860) (Lepidoptera: Noctuidae) no mundo: Potencial invasão e riscos diante das mudanças climáticas. (2021). http://www.repositorio.ufc.br/handle/riufc/61961Bazzocchi, G. G., Lanzoni, A., Burgio, G. & Fiacconi, M. R. Effects of temperature and host on the pre-imaginal development of the parasitoid Diglyphus isaea (Hymenoptera: Eulophidae). Biol. Control 26, 74–82 (2003).
Google Scholar 
Hondo, T., Koike, A. & Sugimoto, T. Comparison of thermal tolerance of seven native species of parasitoids (Hymenoptera: Eulophidae) as biological control agents against Liriomyza trifolii (Diptera: Agromyzidae) in Japan. Appl. Entomol. Zool. 41, 73–82 (2006).
Google Scholar 
Duale, A. Effect of temperature and relative humidity on the biology of the stem borer parasitoid Pediobius furvus (Gahan) (Hymenoptera: Eulophidae) for the management of stem borers. Environ. Entomol. 34, 1–5 (2005).
Google Scholar 
Ashraf, H. J. et al. Comparative transcriptome analysis of Tamarixia radiata (Hymenoptera: Eulophidae) reveals differentially expressed genes upon heat shock. Comp. Biochem. Physiol. D: Genom. Proteom. 41, 100940 (2022).CAS 

Google Scholar 
van Doan, C. et al. Natural enemies of herbivores maintain their biological control potential under short-term exposure to future CO2, temperature, and precipitation patterns. Ecol. Evol. 11, 4182–4192 (2021).
Google Scholar 
Thomson, L. J., Macfadyen, S. & Hoffmann, A. A. Predicting the effects of climate change on natural enemies of agricultural pests. Biol. Control. 52, 296–306 (2010).
Google Scholar 
Rosenblatt, A. E. & Schmitz, O. J. Climate change, nutrition, and bottom-up and top-down food web processes. Trends Ecol. Evol. 31, 965–975 (2016).
Google Scholar 
Aidoo, O. F. et al. A machine learning algorithm-based approach (MaxEnt) for predicting invasive potential of Trioza erytreae on a global scale. Ecol. Inform. 71, 101792 (2022).
Google Scholar 
Aidoo, O. F. et al. The Impact of Climate Change on Potential Invasion Risk of Oryctes monoceros Worldwide. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2022.895906 (2022).Article 

Google Scholar 
Hao, M. et al. Global potential distribution of Oryctes rhinoceros, as predicted by Boosted Regression Tree model. Glob. Ecol. Conserv. 1(37), e02175 (2022).
Google Scholar 
Aidoo, O. F. et al. Model-based prediction of the potential geographical distribution of the invasive coconut mite, Aceria guerreronis Keifer (Acari: Eriophyidae) based on MaxEnt. Agric. For. Entomol. 24, 390–404 (2022).
Google Scholar  More