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    Rare and declining bird species benefit most from designating protected areas for conservation in the UK

    Johnson, C. N. et al. Biodiversity losses and conservation responses in the Anthropocene. Science 356, 270–275 (2017).Article 
    CAS 
    PubMed 

    Google Scholar 
    Rockström, J. et al. A safe operating space for humanity. Nature 461, 472–475 (2009).Article 
    PubMed 

    Google Scholar 
    Maxwell, S. L. et al. Area-based conservation in the twenty-first century. Nature 586, 217–227 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Schulze, K. et al. An assessment of threats to terrestrial protected areas. Conserv. Lett. 11, e12435 (2018).Article 

    Google Scholar 
    Bingham, H. C. et al. (eds). Protected Planet Report 2020 (UNEP-WCMC & IUCN, 2021); https://livereport.protectedplanet.net/Buchanan, G. M., Butchart, S. H., Chandler, G. & Gregory, R. D. Assessment of national-level progress towards elements of the Aichi Biodiversity Targets. Ecol. Indic. 116, 106497 (2020).Article 

    Google Scholar 
    Xu, H. et al. Ensuring effective implementation of the post-2020 global biodiversity targets. Nat. Ecol. Evol. 5, 411–418 (2021).Article 
    PubMed 

    Google Scholar 
    Report of the Open-ended Working Group on the Post-2020 Global Biodiversity Framework on Its Third Meeting (CBD Secretariat, 2022); https://www.cbd.int/conferences/post2020/wg2020-03/documentsRodrigues, A. S. & Cazalis, V. The multifaceted challenge of evaluating protected area effectiveness. Nat. Commun. 11, 5147 (2020).Article 
    PubMed Central 
    CAS 
    PubMed 

    Google Scholar 
    Geldmann, J., Manica, A., Burgess, N. D., Coad, L. & Balmford, A. A global-level assessment of the effectiveness of protected areas at resisting anthropogenic pressures. Proc. Natl Acad. Sci. USA 116, 23209–23215 (2019).Article 
    PubMed Central 
    CAS 
    PubMed 

    Google Scholar 
    Starnes, T. et al. The extent and effectiveness of protected areas in the UK. Glob. Ecol. Conserv. 30, e01745 (2021).Article 

    Google Scholar 
    Kremen, C. et al. Aligning conservation priorities across taxa in Madagascar with high-resolution planning tools. Science 320, 222–226 (2008).Article 
    CAS 
    PubMed 

    Google Scholar 
    Cazalis, V. et al. Mismatch between bird species sensitivity and the protection of intact habitats across the Americas. Ecol. Lett. 24, 2394–2405 (2021).Article 
    PubMed 

    Google Scholar 
    Venter, O. et al. Targeting global protected area expansion for imperiled biodiversity. PLoS Biol. 12, e1001891 (2014).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    Gamero, A. et al. Tracking progress toward EU biodiversity strategy targets: EU policy effects in preserving its common farmland birds. Conserv. Lett. 10, 395–402 (2017).Article 

    Google Scholar 
    Pellissier, V. et al. Effects of Natura 2000 on nontarget bird and butterfly species based on citizen science data. Conserv. Biol. 34, 666–676 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Princé, K., Rouveyrol, P., Pellissier, V., Touroult, J. & Jiguet, F. Long-term effectiveness of Natura 2000 network to protect biodiversity: a hint of optimism for common birds. Biol. Conserv. 253, 108871 (2021).Article 

    Google Scholar 
    Cunningham, C. A., Thomas, C. D., Morecroft, M. D., Crick, H. Q. P. & Beale, C. M. The effectiveness of the protected area network of Great Britain. Biol. Conserv. 257, 109146 (2021).Article 

    Google Scholar 
    Duckworth, G. D. & Altwegg, R. Effectiveness of protected areas for bird conservation depends on guild. Divers. Distrib. 24, 1083–1091 (2018).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    Rada, S. et al. Protected areas do not mitigate biodiversity declines: a case study on butterflies. Divers. Distrib. 25, 217–224 (2019).Article 

    Google Scholar 
    Terraube, J., Van Doninck, J., Helle, P., & Cabeza, M. Assessing the effectiveness of a national protected area network for carnivore conservation. Nat. Commun. 11, 2957 (2020).Article 
    PubMed Central 
    CAS 
    PubMed 

    Google Scholar 
    Lenoir, J. et al. Species better track the shifting isotherms in the oceans than on land. Nat. Ecol. Evol. 4, 1044–1059 (2020).Article 
    PubMed 

    Google Scholar 
    van Teeffelen, A., Meller, L., van Minnen, J., Vermaat, J. & Cabeza, M. How climate proof is the European Union’s biodiversity policy? Regional Environ. Change 15, 997–1010 (2015).Article 

    Google Scholar 
    Thomas, C. D. & Gillingham, P. K. The performance of protected areas for biodiversity under climate change. Biol. J. Linn. Soc. Lond. 115, 718–730 (2015).Article 

    Google Scholar 
    Gillingham, P. K. et al. The effectiveness of protected areas in the conservation of species with changing geographical ranges. Biol. J. Linn. Soc. Lond. 115, 707–717 (2015).Article 

    Google Scholar 
    Geldmann, J. et al. Effectiveness of terrestrial protected areas in reducing habitat loss and population declines. Biol. Conserv. 161, 230–238 (2013).Article 

    Google Scholar 
    Stokstad, E. Species? Climate? Cost? Ambitious goal means trade-offs. Science 371, 555 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Brlík, V. et al. Long-term and large-scale multispecies dataset tracking population changes of common European breeding birds. Sci. Data 8, 21 (2021).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    Stanbury, A. et al. The status of bird populations: the fifth Birds of Conservation Concern in the United Kingdom, Channel Islands and Isle of Man and second IUCN Red List assessment of extinction risk for Great Britain. Br. Birds 114, 723–747 (2021).
    Google Scholar 
    Dudley, N. (ed). Guidelines for Applying Protected Area Management Categories (IUCN, 2008).Deguignet, M. et al. Measuring the extent of overlaps in protected area designations. PLoS ONE 12, e0188681 (2017).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    JNCC. Common Standards Monitoring: Introduction to the Guidance Manual (JNCC Resource Hub, 2004).Hayhow, D. B. et al. State of Nature 2019 (RSPB, 2019).Schleicher, J. et al. Statistical matching for conservation science. Conserv. Biol. 34, 538–549 (2019).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    Waldron, A. et al. Protecting 30% of the Planet for Nature: Costs, Benefits and Economic Implications (Campaign for Nature, 2020); https://helda.helsinki.fi/handle/10138/326470Franks, S. E., Roodbergen, M., Teunissen, W., Carrington Cotton, A. & Pearce‐Higgins, J. W. Evaluating the effectiveness of conservation measures for European grassland‐breeding waders. Ecol. Evol. 8, 10555–10568 (2018).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    Pearce-Higgins, J. W. et al. Site-based adaptation reduces the negative effects of weather upon a southern range margin Welsh black grouse Tetrao tetrix population that is vulnerable to climate change. Clim. Change 153, 253–265 (2019).Article 

    Google Scholar 
    Jellesmark, S. et al. A counterfactual approach to measure the impact of wet grassland conservation on U.K. breeding bird populations. Conserv. Biol. 35, 1575–1585 (2021).Article 
    PubMed 

    Google Scholar 
    Morrison, C. A. et al. Covariation in population trends and demography reveals targets for conservation action. Proc. Biol. Sci. 288, 20202955 (2021).PubMed Central 
    PubMed 

    Google Scholar 
    Donald, P. F. et al. International conservation policy delivers benefits for birds in Europe. Science 317, 810–813 (2007).Article 
    CAS 
    PubMed 

    Google Scholar 
    Martay, B. et al. Monitoring landscape-scale environmental changes with citizen scientists: Twenty years of land use change in Great Britain. J. Nat. Conserv. 44, 33–42 (2018).Article 

    Google Scholar 
    Sullivan, M. J. P., Newson, S. E. & Pearce‐Higgins, J. W. Changing densities of generalist species underlie apparent homogenization of UK bird communities. Ibis 158, 645–655 (2016).Article 

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

    Google Scholar 
    Devictor, V. et al. Differences in the climatic debts of birds and butterflies at a continental scale. Nat. Clim. Change 2, 121–124 (2012).Article 

    Google Scholar 
    Lehikoinen, P., Santangeli, A., Jaatinen, K., Rajasärkkä, A. & Lehikoinen, A. Protected areas act as a buffer against detrimental effects of climate change—evidence from large‐scale, long‐term abundance data. Glob. Change Biol. 25, 304–313 (2019).Article 

    Google Scholar 
    Gaüzère, P., Jiguet, F. & Devictor, V. Can protected areas mitigate the impacts of climate change on bird’s species and communities? Diversity Distrib. 22, 625–637 (2016).Article 

    Google Scholar 
    Neate‐Clegg, M. H. C., Jones, S. E. I., Burdekin, O., Jocque, M. & Şekercioğlu, Ç. H. Elevational changes in the avian community of a Mesoamerican cloud forest park. Biotropica 50, 805–815 (2018).Article 

    Google Scholar 
    Oliver, T. H. et al. Large extents of intensive land use limit community reorganization during climate warming. Glob. Change Biol. 23, 2272–2283 (2017).Article 

    Google Scholar 
    Hiley, J. R., Bradbury, R. B., Holling, M. & Thomas, C. D. Protected areas act as establishment centres for species colonizing the UK. Proc. Biol. Sci. 280, 20122310 (2013).PubMed Central 
    PubMed 

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

    Google Scholar 
    Grace, M. K. et al. Testing a global standard for quantifying species recovery and assessing conservation impact. Conserv. Biol. 35, 1833–1849 (2021).Article 
    PubMed 

    Google Scholar 
    Gibbons, D. W., Reid, J. B. & Chapman, R. A. The New Atlas of Breeding Birds in Britain & Ireland 1988–1991 (T. & A. D. Poyser, 1993).Balmer, D. E. et al. Bird Atlas 2007–11: the Breeding and Wintering Birds of Britain and Ireland (BTO, 2013).Gillings, S. et al. Breeding and wintering bird distributions in Britain and Ireland from citizen science bird atlases. Glob. Ecol. Biogeogr. 28, 866–874 (2019).Article 

    Google Scholar 
    Freeman, S. N., Noble, D. G., Newson, S. E. & Baillie, S. R. Modelling population changes using data from different surveys: the Common Birds Census and the Breeding Bird Survey. Bird Study 54, 61–72 (2007).Article 

    Google Scholar 
    Robinson, R. A., Julliard, R. & Saracco, J. F. Constant effort: studying avian population processes using standardised ringing. Ring. Migr. 24, 199–204 (2009).Article 

    Google Scholar 
    Cave, V. M., Freeman, S. N., Brooks, S. P., King, R. & Balmer, D. E. in Modeling Demographic Processes in Marked Populations, 949–963 (Springer, 2009).Rowland, C. S. et al. Land Cover Map 2015 (1km Percentage Aggregate Class, GB) (eds Thomson, D. L. et al) (Environmental Information Data Centre, 2017); https://doi.org/10.5285/7115bc48-3ab0-475d-84ae-fd3126c20984Rowland, C. S. et al. Land Cover Map 2015 (1km Percentage Aggregate Class, N. Ireland) (Environmental Information Data Centre, 2017); https://doi.org/10.5285/362feaea-0ccf-4a45-b11f-980c6b89a858ASTER Global Digital Elevation Model V003 (dataset). NASA EOSDIS Land Processes DAAC (NASA/METI/AIST/Japan Space Systems and U.S./Japan ASTER Science Team, 2019); https://doi.org/10.5067/ASTER/ASTGTM.003Schiavina, M., Freire, S. & MacManus, K. GHS-SMOD R2019A – GHS Settlement Layers, Updated and Refined REGIO Model 2014 in Application to GHS-BUILT R2018A and GHS-POP R2019A, Multitemporal (1975-1990-2000-2015) (European Commission Joint Research Centre, 2019); https://doi.org/10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218Robinson, R. A. BirdFacts: Profiles of Birds Occurring in Britain & Ireland (BTO, 2005).Gibbons, D. W. et al. Bird species of conservation concern in the United Kingdom, Channel Islands and Isle of Man: revising the Red Data List. RSPB Conserv. Rev. 10, 7–18 (1996).
    Google Scholar 
    Stone, B. H. et al. Population estimates of birds in Britain and in the United Kingdom. Br. Birds 90, 1–22 (1997).
    Google Scholar 
    Woodward, I. et al. Population estimates of birds in Great Britain and the United Kingdom. Br. Birds 113, 69–104 (2020).
    Google Scholar 
    R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/Joppa, L. N. & Pfaff, A. High and far: biases in the location of protected areas. PLoS ONE 4, e8273 (2009).Article 
    PubMed Central 
    PubMed 

    Google Scholar 
    Bull, J. W., Strange, N., Smith, R. J. & Gordon, A. Reconciling multiple counterfactuals when evaluating biodiversity conservation impact in social‐ecological systems. Conserv. Biol. 35, 510–521 (2020).Article 
    PubMed 

    Google Scholar 
    Jellesmark, S. et al. Assessing the global impact of targeted conservation actions on species abundance. Preprint at bioRxiv https://doi.org/10.1101/2022.01.14.476374 (2022).Wauchope, H. S. et al. Protected areas have a mixed impact on waterbirds but management helps. Nature 605, 103–107 (2022).Article 
    CAS 
    PubMed 

    Google Scholar 
    Ho, D. E., Imai, K., King, G. & Stuart, E. A. MatchIt: nonparametric preprocessing for parametric causal inference. J. Stat. Softw. 42, 1–28 (2011).Article 

    Google Scholar 
    Wood, S. N. Generalized Additive Models: an Introduction with R 2nd edn (Chapman and Hall/CRC, 2017).Hartig, F. DHARMa: Residual diagnostics for hierarchical (multi-level/mixed) regression models. R package v.0.4.4 (2021); https://CRAN.R-project.org/package=DHARMaJetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).Article 
    CAS 
    PubMed 

    Google Scholar 
    Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).Article 

    Google Scholar 
    Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Johnston, A. et al. Species traits explain variation in detectability of UK birds. Bird Study 61, 340–350 (2014).Article 

    Google Scholar 
    Hill, M. O. Diversity and evenness: a unifying notation and its consequences. Ecology 54, 427–432 (1973).Article 

    Google Scholar 
    Ho, D. E., Imai, K., King, G. & Stuart, E. A. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Anal. 15, 199–236 (2007).Article 

    Google Scholar 
    Julliard, R., Clavel, J., Devictor, V., Jiguet, F. & Couvet, D. Spatial segregation of specialists and generalists in bird communities. Ecol. Lett. 9, 1237–1244 (2006).Article 
    PubMed 

    Google Scholar 
    Devictor, V., Julliard, R., Couvet, D. & Jiguet, F. Birds are tracking climate warming, but not fast enough. Proc. Biol. Sci. 275, 2743–2748 (2008).PubMed Central 
    PubMed 

    Google Scholar  More

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    Carbon turnover gets wet

    Whether land acts as a carbon sink or source depends largely on two opposite fluxes: carbon uptake through photosynthesis and carbon release through turnover. Turnover occurs through multiple processes, including but not limited to, leaf senescence, tree mortality, and respiration by plants, microbes, and animals. Each of these processes is sensitive to climate, and ecologists and climatologists have been working to figure out how temperature regulates biological activities and to what extent the carbon cycle responds to global warming. Previous theoretical and experimental studies have yielded conflicting relationships between temperature and carbon turnover, with large variations across ecosystems, climate and time-scale1,2,3,4. Writing in Nature Geoscience, Fan et al.5 find that hydrometeorological factors have an important influence on how the turnover time of land carbon responds to changes in temperature. More

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    Reply to: Erroneous predictions of auxotrophies by CarveMe

    Machado, D. et al. Polarization of microbial communities between competitive and cooperative metabolism. Nat. Ecol. Evol. 5, 195–203 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Price, M. Erroneous predictions of auxotrophies by CarveMe. https://doi.org/10.1038/s41559-022-01936-3 (2022).Machado, D., Andrejev, S., Tramontano, M. & Patil, K. R. Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. Nucleic Acids Res. 46, 7542–7553 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Price, M. N., Deutschbauer, A. M. & Arkin, A. P. GapMind: automated annotation of amino acid biosynthesis. mSystems 5, e00291-20 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mee, M. T., Collins, J. J., Church, G. M. & Wang, H. H. Syntrophic exchange in synthetic microbial communities. Proc. Natl. Acad. Sci. USA 111, E2149–E2156 (2014).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ponomarova, O. et al. Yeast creates a niche for symbiotic lactic acid bacteria through nitrogen overflow. Cell Syst. 5, 345–357.e6 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zengler, K. & Zaramela, L. S. The social network of microorganisms—how auxotrophies shape complex communities. Nat. Rev. Microbiol. 16, 383–390 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Giri, S. et al. Metabolic dissimilarity determines the establishment of cross-feeding interactions in bacteria. Curr. Biol. 31, 5547–5557.e6 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Morris, J. J., Lenski, R. E. & Zinser, E. R. The black queen hypothesis: evolution of dependencies through adaptive gene loss. mBio 3, e00036-12 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Campbell, K. et al. Self-establishing communities enable cooperative metabolite exchange in a eukaryote. eLife 4, e09943 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    D’Souza, G. & Kost, C. Experimental evolution of metabolic dependency in bacteria. PLOS Genet. 12, e1006364 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ziesack, M. et al. Engineered interspecies amino acid cross-feeding increases population evenness in a synthetic bacterial consortium. mSystems 4, e00352-19 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ryback, B., Bortfeld-Miller, M. & Vorholt, J. A. Metabolic adaptation to vitamin auxotrophy by leaf-associated bacteria. ISME J. https://doi.org/10.1038/s41396-022-01303-x (2022). More

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    Phytoplankton in the middle

    Marine phytoplankton both follow and actively influence the environment they inhabit. Unpacking the complex ecological and biogeochemical roles of these tiny organisms can help reveal the workings of the Earth system.
    Phytoplankton are the workers of an ocean-spanning factory converting sunlight and raw nutrients into organic matter. These little organisms — the foundation of the marine ecosystem — feed into a myriad of biogeochemical cycles, the balance of which help control the distribution of carbon on the Earth surface and ultimately the overall climate state. As papers in this issue of Nature Geoscience show, phytoplankton are far from passive actors in the global web of biogeochemical cycles. The functioning of phytoplankton is not just a matter for biologists, but is also important for geoscientists seeking to understand the Earth system more broadly.Phytoplankton are concentrated where local nutrient and sea surface temperatures are optimal, factors which aren’t always static in time. Prominent temperature fluctuations, from seasonal to daily cycles, are reflected in phytoplankton biomass, with cascading effects on other parts of marine ecosystems, such as economically-important fisheries. In an Article in this issue, Keerthi et al., show that phytoplankton biomass, tracked by satellite measurements of chlorophyll for relatively small ( More

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    Algal sensitivity to nickel toxicity in response to phosphorus starvation

    Effect of phosphorus starved cultures of Dunaliella tertiolecta on growth represented as optical density under stress of nickel ionsIn the case of normal culture, phosphorus starved control culture (without nickel stress), and phosphorus-starved treated cultures, data presented in Table 1 and graphed in figure (S1, Supplementary Data) clearly showed a progressive increase in optical density with increasing culturing period in case of normal culture, phosphorus-starved control culture, and phosphorus-starved treated cultures. Our findings are consistent with those of18 who found that in phosphorus starved cultures of three algae species, Microcystic aeruginosa, Chlorella pyrenoidesa, and Cyclotella sp., the biomass, specific growth rate, and Chl-a all declined significantly.The optical density achieved during the four periods of culturing was lower in phosphorus-depleted control cultures than in normal cultures (i.e., cultures contained phosphorus). When compared to a normal control (without nickel addition), the optical density was reduced by 9.1% after 4 days of culturing under phosphorus deprivation and by 10.0 percent after 8 days of culturing. In the case of 5 mg/L dissolved nickel, however, the obtained optical density values in phosphorus starved treatment cultures rose with the increase in culturing period during all culturing periods as compared to phosphorus-starved control (without nickel addition) cultures.At 10 mg/L dissolved nickel and after 4 days of culturing, the optical density although less than those in case of concentration 5 mg/L, yet it was higher than control (− P) but by increasing the culturing period more than 4 days, the optical density was less than control (− P). Our results are similar to those of19 who observed that the decrease in cell division rate signaled the onset of P-deficiency. The cultures that showed no significant increase in cell number for at least three consecutive days under the experimental conditions were considered P-depleted. In addition20, observed that the growth rate of Dunaliella prava was found to be dramatically lowered when phosphorus was limited. The content of chlorophyll fractions, total soluble carbohydrates, and proteins all fell considerably as a result of phosphorus restriction.The results concerning the effect of dissolved nickel on the growth of Dunaliella tertiolecta under conditions of phosphorus limitation show that phosphorus starved Dunaliella had lower growth as compared to the control (phosphorus-containing culture medium). These results are in agreement with those obtained by7 who reported that the optical density of Chlorella kessleri cell suspension decreased with phosphorus deficiency compared to control. Also21, found that Chlorella vulgaris cells grew 30–40% slower in phosphorus-starved cultures than in control cultures. Furthermore22, showed that diatoms were unable to thrive when phosphorus levels were insufficient. Diatom dominances were reduced to 45 and 55% in enclosures where phosphate was not provided23 observed that, under salt stress, Chlorella’s metabolic rate was substantially lower than Dunaliella’s.It can be concluded that when microorganisms are deprived of phosphorus, dissolved nickel uptake decreases, resulting in an increase in algal metabolism24. Also25, examined the effects of phosphorus and nitrogen starvation on the life cycle of Emiliania huxleyi (Haptophyta) and proved that various biochemical pathways’ metabolic load increased under P-starvation while it decreased under N-starvation.Effect of phosphorus starved cultures of Dunaliella tertiolecta on chlorophylls content under stress of nickel ionsTable 2 and figure (S2, Supplementary Data) show the sequences of change in the amount of chlorophylls a and b in phosphorus-depleted cultures of Dunaliella tertiolecta in response to various dissolved nickel concentrations. The results show that total chlorophyll content rose steadily until the end of the experiment under normal conditions (a control containing phosphorus). These results are in harmony with those obtained by24. The ratio between chlorophylls “a” and “b” remained nearly constant till the end of the 12th day. At the 16th day of culturing, the ratio decreased from 2.9:1 to 2.4:1. On the contrary, the total chlorophylls under control (in the absence of nickel element) in case of phosphorus-starved cultures showed a progressive increase up to the 12th day. At the 12th day the total chlorophylls in case of phosphorus-starved cultures decreased by 10.7% compared to the normal control. At the 16th day, the total chlorophylls in case of untreated phosphorus starved culture decreased by 20.8% compared to those obtained at normal control26. Reported that the chlorophyll content of Chlorella sorokiniana was significantly reduced due to a lack of nitrogen and phosphorus in the medium.Table 2 Effect of different concentrations of dissolved nickel (mg/L) on chlorophylls content (µg/ml) of Dunaliella tertiolecta under the stress of phosphorus starvation.Full size tableThe total chlorophyll content of Dunaliella tertiolecta in the phosphorus-starved cultures treated with 5 mg/L of dissolved nickel increased gradually until the 12th day, when the content of the total chlorophylls reached 2.11 µg/ml, i.e., higher than the phosphorus-starved control (− P) by 15.3%. At the 16th day, the total chlorophylls, although lower than those obtained at the 12th day, were still higher than the control (− P). At a concentration of 10 mg/L of dissolved nickel, slight increase in the content of total chlorophylls was recorded from the beginning to the end of the culturing period, i.e., from the 4th to the 16th day. At the other concentrations of dissolved nickel (15, 20, and 25 mg/L), a pronounced decrease in the total chlorophylls could be observed from the 4th to the 16th day of culturing compared to control (− P). Our results are going with an agreement with those obtained by27 who found that chlorophylls were inhibited maximum at higher dissolved nickel concentrations but activated at lower values. The normal ratio between chlorophylls “a” and “b” (3:1) was upset after the 8th day of culturing under concentrations 5, 10, and 15 mg/L of dissolved nickel. At 20 and 25 mg/L of dissolved nickel, this ratio was unstable from the beginning to the end of the experiment. The fact that dissolved nickel is extremely mobile and hence only absorbed to a minimal level may explain the sensitivity of the tested alga to nickel in response to phosphorus deficiency, and an increase in phosphorus concentration favors its absorption by microorganisms28. It can be concluded that when microorganisms are deprived of phosphorus, dissolved nickel uptake decreases, resulting in an increase in algal metabolism.Effect of different concentrations of dissolved nickel on photosynthesis (O2-evolution) of phosphorus starved cells of Dunaliella tertiolecta
    Data represented in Table 3 and graphed in figure (S3, Supplementary Data S3) showed that the effect of phosphorus limitation on the photosynthetic activity of Dunaliella tertiolecta in response to five different concentrations of dissolved nickel revealed that, under phosphorus limiting conditions, the amount of O2-evolution was lower than in untreated cultures (the control). The evolution of O2 after 4 days of culturing in case of phosphorus starved control decreased by 8.7% compared to normal control, while after 12 days it decreased by 30.4%. The rate of O2-evolution at different concentrations of dissolved nickel over 5 mg/L caused successive reductions in the O2-evolution of phosphorus starved cells. Application of 5 mg/L of dissolved nickel, the results cleared that the rate of O2-evolution increased under the effect of all tested concentrations till the end of the experiment. It is clear from our data that the rate of O2-evolution depended mainly on the concentration of the nickel element and the length of culturing period. The lower the rate of O2-evolution, the higher the element’s concentration, and the longer the culturing period. This coincided with the findings of7 who found that low phosphorus treatment causes Chlorella kessleri to lose its photosynthetic activity. In this regard, it was discovered that phosphorus deficiency resulted in a decrease in photosynthetic electron transport activity29 found that the O2-evolution of Chlamydomon reinhardtii declined by 75%. This decrease reflects damage of PSII and the generation of PSII QB-non reducing centers.Table 3 Effect of different concentrations of dissolved nickel (mg/L) on photosynthetic activity (O2-evolution calculated as µ mol O2 mg chl-1 h-1) on phosphorus supplemented and starved cells of Dunaliella tertiolecta.Full size tableAlso30 found that P- deficiency has been correlated with lower photosynthetic rates. In the case of the treated phosphorus-starved cultures with lower concentrations (5 mg/L) of dissolved nickel, the rate of photosynthesis increased when compared to the phosphorus-starved control, but was less than that of the normal control (without nickel treatment). On the contrary, it was found that, in the treated phosphorus-starved cultures at concentrations of 10, 15, 20 and 25 mg/L of the tested element, the rate of photosynthesis decreased from the beginning to the end of the experiment. With increasing concentration, duration of the culturing period, and kind of element, the condition of decrease in O2-evolution became more pronounced; the same results were also recorded by24. The stimulation of growth and photosynthesis in the presence of some concentrations of dissolved nickel under phosphorus-limiting conditions is observed by31 they report that in Cu2+ sensitive Scenedesmus acutus, intracellular polyphosphate plays a key role in shielding photosynthesis from Cu2+ toxicity but not in copper resistant species.Effect of different concentrations of dissolved nickel on respiration (O2-uptake) of phosphorus starved cells of Dunaliella tertiolectaData obtained in Table 4 and graphed in figure (S4, Supplementary Data S4) concerning the rate of respiration of Dunaliella tertiolecta under phosphorus-limiting conditions was higher than that of untreated phosphorus-starved (control) for a short period of time only, i.e., after 4 days, at concentrations 5, 10 and 15 mg/L of dissolved nickel, After 8 days of culturing, the rate of O2- uptake increased only at 5 mg/L of dissolved nickel, while at the other concentrations it decreased gradually with increasing the concentration of the element. This finding is consistent with the findings of23, who discovered that Dunaliella cells increased their O2 absorption and evolution rates in the presence of 2 M salt NaCl in the media. In terms of oxygen uptake rate, Dunaliella cells demonstrated an increase in salt concentrations. In 1.5 M NaCl, it increased significantly by 60–80%.Table 4 Effect of different concentrations of dissolved nickel (mg/L) on respiration activity (O2-uptake calculated as µ mol O2 h-1) on phosphorus supplemented and starved cells of Dunaliella tertiolecta.Full size tableConcerning the increase in respiration in P-depleted green alga species cultures5 suggested that Scenedesmus, for example, can utilize the energy stored in starch and lipids for active phosphorus uptake from lake sediments. This process is aided by an increase in phosphatase production32 and these cells’ ability to operate anaerobically33. When unicellular green algae or higher plants are exposed to P deficiency, the majority of newly fixed carbon appears to be allocated to the synthesis of non-phosphorylated storage polyglucans (i.e., starch) or sucrose, with less photosynthetic activity directed to respiratory metabolism and other biosynthesis pathways34. It can be concluded from the obtained results that, when the alga was cultivated under phosphorus deficiency and treated with varied amounts of dissolved nickel, the growth was the most sensitive characteristic, followed by photosynthesis, and then dark respiration. In the few comparative studies with several species of green algae, growth was more sensitive than the other physiological processes examined. Out of them35, reported that growth was more susceptible to phosphorus deficiency in Chlorella pyrenoidosa and Asterionella gracilis than photosynthesis and respiration (the least sensitive processes). Growth was also more sensitive than photosynthesis in Nitzschia closterium 36 . Another important fact reported by37 is that under low phosphorus conditions, Dunaliella parva accumulates lipids rather than carbohydrates. These findings imply that phosphorus stress may prevent starch and/or protein production, leading to an increase in carbon flux to lipids. More

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    Sap flow of sweet cherry reveals distinct effects of humidity and wind under rain covered and netted protected cropping systems

    Jensen, M. H. & Malter, A. J. Protected Agriculture—A Global Review. World Bank Technical Paper Number 253 (World Bank, 1995).
    Google Scholar 
    Meli, T., Riesen, W. & Widmer, A. Protection of sweet cherry hedgerows with polyethylene films. Acta Hortic. 155, 463–467 (1984).Article 

    Google Scholar 
    Janick, J. (ed.) Horticultural Reviews Vol. 30, 115–162 (Wiley, 2004).
    Google Scholar 
    Janke, R. R., Altamimi, M. E. & Khan, M. The use of high tunnels to produce fruit and vegetable crops in North America. Agric. Sci. 08, 692–715. https://doi.org/10.4236/as.2017.87052 (2017).Article 

    Google Scholar 
    Alarcon, J. J. et al. Sap flow as an indicator of transpiration and the water status of young apricot trees. Plant Soil 227, 77–85. https://doi.org/10.1023/A:1026520111166 (2000).Article 
    CAS 

    Google Scholar 
    Ferrara, G. & Flore, J. Comparison between different methods for measuring tranpiration in potted apple trees. Biol. Plant. 46, 41–47 (2003).Article 

    Google Scholar 
    Nicolás, E., Torrecillas, A., Amico, J. D. & Alarcón, J. J. Sap flow, gas exchange, and hydraulic conductance of young apricot trees growing under a shading net and different water supplies. J. Plant Physiol. 162, 439–447. https://doi.org/10.1016/j.jplph.2004.05.014 (2005).Article 
    CAS 

    Google Scholar 
    Green, S. & Romero, R. Can we improve heat-pulse to measure low and reverse flows. Acta Hortic. 951, 19–30 (2012).Article 

    Google Scholar 
    Noitsakis, B. & Nastis, A. S. Seasonal changes of water potential, stomatal conductance and transpiration in the leaf of cherry trees grown in shelter. CIHEAM 12, 267–270 (1995).
    Google Scholar 
    Lang, G. A. High tunnel tree fruit production: The final frontier. HortTechnology 19, 50–55 (2009).Article 

    Google Scholar 
    Lang, G. A. Tree fruit production in high tunnels: Current status and case study of sweet cherries. Acta Hortic. 987, 73–82 (2013).Article 

    Google Scholar 
    Meland, M., Frøynes, O. & Kaiser, C. High tunnel production systems improve yields and fruit size of sweet cherry. Acta Hortic. 1161, 117–124. https://doi.org/10.17660/ActaHortic.2017.1161.20 (2017).Article 

    Google Scholar 
    Cohen, S., Moreshet, S., Guillou, L. L., Simon, J.-C. & Cohen, M. Response of citrus trees to modified radiation regime in semi-arid conditions. J. Exp. Bot. 48, 35–44. https://doi.org/10.1093/jxb/48.1.35 (1997).Article 
    CAS 

    Google Scholar 
    Zeppel, M., Murray, B. R., Barton, C. & Eamus, D. Seasonal responses of xylem sap velocity to VPD and solar radiation during drought in a stand of native trees in temperate Australia. Funct. Plant Biol. 31, 461–470 (2004).Article 

    Google Scholar 
    Bonada, M., Buesa, I., Moran, M. A. & Sadras, V. O. Interactive effects of warming and water deficit on Shiraz vine transpiration in the Barossa Valley, Australia. OENO One 52, 189–202. https://doi.org/10.20870/oeno-one.2018.52.2.2141 (2018).Article 
    CAS 

    Google Scholar 
    Wang, K. Y., Kellomaki, S., Zha, T. & Peltola, H. Annual and seasonal variation of sap flow and conductance of pine trees grown in elevated carbon dioxide and temperature. J. Exp. Bot. 56, 155–165. https://doi.org/10.1093/jxb/eri013 (2005).Article 
    CAS 

    Google Scholar 
    Laplace, S., Chu, C. & Kume, S. Wind speed response of sap flow in five subtropical trees based on wind tunnel experiments. Br. J. Environ. Clim. Change 3, 160–171. https://doi.org/10.9734/BJECC/2013/3842 (2013).Article 

    Google Scholar 
    Kellomäki, S. & Wang, K. Y. Sap flow in Scots pine growing under conditions of year-round carbon dioxide enrichment and temperature elevation. Plant, Cell Environ. 21, 969–981. https://doi.org/10.1046/j.1365-3040.1998.00352.x (2002).Article 

    Google Scholar 
    Urban, J., Ingwers, M., McGuire, M. A. & Teskey, R. O. Stomatal conductance increases with rising temperature. Plant Signal. Behav. 12, 3–6. https://doi.org/10.1080/15592324.2017.1356534 (2017).Article 
    CAS 

    Google Scholar 
    Wu, J. et al. Nocturnal sap flow is mainly caused by stem refilling rather than nocturnal transpiration for Acer truncatum in urban environment. Urban For. Urban Green. 56, 126800. https://doi.org/10.1016/j.ufug.2020.126800 (2020).Article 

    Google Scholar 
    Chen, Y.-J. et al. Time lags between crown and basal sap flows in tropical lianas and co-occurring trees. Tree Physiol. 36, 736–747. https://doi.org/10.1093/treephys/tpv103 (2015).Article 

    Google Scholar 
    Marshall, D. C. Measurment of sap flow in conifers by heat transport. Plant Physiol. 33, 385–396 (1958).Article 
    CAS 

    Google Scholar 
    Swanson, R. H. & Whitfield, W. A. A numerical analysis of heat pulse velocity theory and practice. J. Exp. Bot. 32, 221–239 (1981).Article 

    Google Scholar 
    Green, S., Clothier, B. & Jardine, B. Theory and practical application of heat pulse to measure sap flow. Am. Soc. Agron. 95, 1371–1379 (2003).Article 

    Google Scholar 
    Goodwin, I., Cornwall, D. & Green, S. R. Pear transpiration and basal crop coefficients estimated by sap flow. Acta Hortic. 951, 183–190. https://doi.org/10.17660/ActaHortic.2012.951.22 (2012).Article 

    Google Scholar 
    Fernandez, J. E. et al. Heat-pulse measurements of sap flow in olives for automating irrigation, tests, root flow and diagnostics of water stress. Agric. Water Manag. 51, 99–123 (2001).Article 

    Google Scholar 
    Green, S. R. & Clothier, B. Water use of kiwifruit vines and apple trees by the heat-pulse technique. J. Exp. Bot. 39, 115–123 (1988).Article 

    Google Scholar 
    Green, S. R. et al. Measurement of sap flow in young apple trees using the average gradient heat-pulse method. Acta Hortic. 1222, 173–178. https://doi.org/10.17660/ActaHortic.2018.1222.35 (2018).Article 

    Google Scholar 
    Green, S., Clothier, B. & Perie, E. A re-analysis of heat pulse theory across a wide range of sap flows. Acta Hortic. 846, 95–104 (2009).Article 

    Google Scholar 
    Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. Crop Evapotranspiration Guidelines for Computing Crop Water Requirements, FAO Irrigation and Drainage Paper 56 300 (FAO, 1998).
    Google Scholar 
    R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2010).Hastie, T. & Tibshirani, R. Generalized Additive Models (Chapman and Hall/CRC, 1990).MATH 

    Google Scholar 
    Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723. https://doi.org/10.1109/TAC.1974.1100705 (1974).Article 
    MathSciNet 
    MATH 

    Google Scholar 
    Sams, C. E. & Flore, J. A. The influence of leaf age, leaf position on the shoot, and environmental variables on net photosynthetic rate of sour cherry (Prunus cerasus L. ’Montmorency’). J. Am. Soc. Hortic. Sci. 107, 339–344 (1982).Article 

    Google Scholar 
    Wallberg, B. N. & Sagredo, K. X. Vegetative and reproductive development of “Lapins” sweet cherry trees under rain protective cropping. Int. Soc. Hortic. Sci. 1058, 411–417 (2014).
    Google Scholar 
    Lang, G. A. Growing sweet cherries under plastic covers and tunnels: Physiological aspects and practical considerations. Acta Hortic. 1020, 303–312. https://doi.org/10.17660/ActaHortic.2014.1020.43 (2014).Article 

    Google Scholar 
    Goodwin, I., McClymont, L., Turpin, S. & Darbyshire, R. Effectiveness of netting in decreasing fruit surface temperature and sunburn damage of red-blushed pear. N. Z. J. Crop. Hortic. Sci. 46, 334–345. https://doi.org/10.1080/01140671.2018.1432492 (2018).Article 
    CAS 

    Google Scholar 
    Mika, A., Buler, Z., Wójcik, K. & Konopacka, D. Influence of the plastic cover on the protection of sweet cherry fruit against cracking, on the microclimate under cover and fruit quality. J. Hortic. Res. 27, 31–38. https://doi.org/10.2478/johr-2019-0018 (2019).Article 
    CAS 

    Google Scholar 
    Blanco, V., Zoffoli, J. P. & Ayala, M. High tunnel cultivation of sweet cherry (Prunus avium L.): Physiological and production variables. Sci. Hortic. 251, 108–117. https://doi.org/10.1016/j.scienta.2019.02.023 (2019).Article 

    Google Scholar 
    Sams, C. E. & Flore, J. A. Net photosynthetic rate of sour cherry (Prunus cerasus L. ‘Montmorency’) during the growing season with particular reference to fruiting. Photosynth. Res. 4, 307–316. https://doi.org/10.1007/BF00054139 (1983).Article 

    Google Scholar 
    Lange, O. L., Schulze, E. D., Evenari, M., Kappen, L. & Buschbom, U. The temperature-related photosynthesis capacity of plants under desert conditions. Oecologia 17, 97–110. https://doi.org/10.1007/BF00346273 (1974).Article 
    CAS 

    Google Scholar 
    Beckman, T. G., Perry, R. L. & Flore, J. A. Short-term flooding affects gas exchange characteristics of containerized sour cherry trees. HortScience 27, 1297. https://doi.org/10.21273/hortsci.27.12.1297 (1992).Article 

    Google Scholar 
    Lei, H., Zhi-Shan, Z. & Xin-Rong, L. Sap flow of Artemisia ordosica and the influence of environmental factors in a revegetated desert area: Tengger Desert, China. Hydrol. Processes 24, 1248–1253. https://doi.org/10.1002/hyp.7584 (2010).Article 

    Google Scholar 
    Juhász, A., Hrotko, K. & Tokei, L. Air and Water Components of the Environment, 76–82.Ravi, S. & D’Odorico, P. A field-scale analysis of the dependence of wind erosion threshold velocity on air humidity. Geophys. Res. Lett. 32, 023675. https://doi.org/10.1029/2005gl023675 (2005).Article 

    Google Scholar 
    Holmes, M. & Farrell, D. South African Avocado Growers Association Yearbook Vol. 16, 59–64 (1993).Jones, H. G. Plants and Microclimate: A quantitative Approach to Environmental Plant Physiology 3rd edn. (Cambridge University Press, 2014).
    Google Scholar 
    Juhász, Á., Sepsi, P., Nagy, Z., Tőkei, L. & Hrotkó, K. Water consumption of sweet cherry trees estimated by sap flow measurement. Sci. Hortic. 164, 41–49. https://doi.org/10.1016/j.scienta.2013.08.022 (2013).Article 

    Google Scholar 
    Gussakovsky, E. E., Salomon, E., Ratner, K., Shahak, Y. & Driesenaar, A. R. J. Photoinhibition (light stress) in citrus leaves. Acta Hortic. 349, 139–143 (1993).Article 

    Google Scholar 
    Grappadelli, L. C. & Lakso, A. N. Is maximizing orchard light interception always the best choice? Acta Hortic. 732, 507–518. https://doi.org/10.17660/ActaHortic.2007.732.77 (2007).Article 

    Google Scholar  More

  • in

    Dominant phytoplankton groups as the major source of polyunsaturated fatty acids for hilsa (Tenualosa ilisha) in the Meghna estuary Bangladesh

    Valle-Levinson, A. Contemporary Issues in Estuarine Physics (Cambridge University Press, 2010).Book 

    Google Scholar 
    Singh, S. Analysis of plankton diversity and density with physico-chemical parameters of open pond in town Deeg (Bhratpur) Rajasthan, India. Int. Res. J. Biol. Sci 4, 61–69 (2015).
    Google Scholar 
    Roussel, M., Pontier, D., Cohen, J.-M., Lina, B. & Fouchet, D. Quantifying the role of weather on seasonal influenza. BMC Public Health 16, 1–14 (2016).Article 

    Google Scholar 
    Davies, O., Abowei, J. & Tawari, C. Phytoplankton community of Elechi creek, Niger Delta, Nigeria-a nutrient-polluted tropical creek. Am. J. Appl. Sci. 6, 1143–1152 (2009).Article 
    CAS 

    Google Scholar 
    Choudhury, S. & Panigrahy, R. Seasonal distribution and behavior of nutrients in the Greek and coastal waters of Gopalpur, East coast of India: Mahasagar. Bull. Natl. Inst. Oeanogr 24, 91–88 (1991).
    Google Scholar 
    Ratheesh, K., Krishnan, A., Das, R. & Vimexen, V. Seasonal phytoplankton succession in Netravathi-Gurupura estuary, Karnataka, India: Study on a three tier hydrographic platform. Estuar. Coast. Shelf Sci. 242, 106830 (2020).Article 

    Google Scholar 
    Deng, Y., Tang, X., Huang, B. & Ding, L. Effect of temperature and irradiance on the growth and reproduction of the green macroalga, Chaetomorpha valida (Cladophoraceae, Chlorophyta). J. Appl. Phycol. 24, 927–933 (2012).Article 
    CAS 

    Google Scholar 
    Gamier, J., Billen, G. & Coste, M. Seasonal succession of diatoms and Chlorophyceae in the drainage network of the Seine River: Observation and modeling. Limnol. Oceanogr. 40, 750–765 (1995).Article 

    Google Scholar 
    Meng, F. et al. Phytoplankton alpha diversity indices response the trophic state variation in hydrologically connected aquatic habitats in the Harbin Section of the Songhua River. Sci. Rep. 10, 1–13 (2020).Article 

    Google Scholar 
    Köhler, J. Growth, production and losses of phytoplankton in the lowland River Spree. I. Population dynamics. J. Plankton Res. 15, 335–349 (1993).Article 

    Google Scholar 
    Murrell, M. C. & Caffrey, J. M. High cyanobacterial abundance in three northeastern Gulf of Mexico estuaries. Gulf Caribbean Res. 17, 95–106 (2005).Article 

    Google Scholar 
    Haldar, G., Rahman, M. & Haroon, A. Hilsa, Tenualosa ilisha (Ham.) fishery of the Feni River with reference to the impacts of the flood control structure. J. Zool. 7, 51–56 (1992).
    Google Scholar 
    Hossain, M. S., Sarker, S., Chowdhury, S. R. & Sharifuzzaman, S. Discovering spawning ground of Hilsa shad (Tenualosa ilisha) in the coastal waters of Bangladesh. Ecol. Model. 282, 59–68 (2014).Article 

    Google Scholar 
    Bhaumik, U. & Sharma, A. The fishery of Indian Shad (Tenualosa ilisha) in the Bhagirathi-Hooghly river system. Fishing Chimes 31, 21–27 (2011).
    Google Scholar 
    Mitra, G. & Devsundaram, M. P. On the hilsa of Chilka Lake with note on the Hilsa in Orissa. J. Asiatic Soc. Sci. 20, 33–40 (1954).
    Google Scholar 
    Abdul, W., Phillips, M. & Beveridge, M. (WorldFish (WF), 2020).Hasan, K. M. M., Wahab, M. A., Ahmed, Z. F. & Mohammed, E. Y. The biophysical assessments of the hilsa fish (Tenualosa ilisha) habitat in the lower Meghna, Bangladesh (International Institute for Environment and Development, 2015).Begum, M. et al. Fatty acid composition of Hilsa (Tenualosa ilisha) fish muscle from different locations in Bangladesh. Thai J. Agric. Sci. 52, 172–179 (2019).
    Google Scholar 
    Jónasdóttir, S. H. Fatty acid profiles and production in marine phytoplankton. Mar. Drugs 17, 151 (2019).Article 

    Google Scholar 
    Otero, P., Ruiz-Villarreal, M., Peliz, Á. & Cabanas, J. M. Climatology and reconstruction of runoff time series in northwest Iberia: Influence in the shelf buoyancy budget off Ría de Vigo. Sci. Mar. 74, 247–266 (2010).Article 

    Google Scholar 
    Grasshoff, K., Kremling, K. & Ehrhardt, M. Methods of Seawater Analysis (Wiley, 2009).
    Google Scholar 
    Parsons, T., Maita, Y. & Lalli, C. A manual of chemical and biological methods for seawater analysis. Pergamon, Oxford sized algae and natural seston size fractions. Mar. Ecol. Prog. Ser. 199, 43–53 (1984).
    Google Scholar 
    Scor-Unesco, W. Determination of photosynthetic pigments. Determination of Photosynthetic Pigments in Sea-water, 9–18 (1966).Snow, G., Bate, G. & Adams, J. The effects of a single freshwater release into the Kromme Estuary. 2: Microalgal response. Water SA-Pretoria 26, 301–310 (2000).CAS 

    Google Scholar 
    Ward, H. B. & Whipple, G. C. Freshwater Biology Vol. 2, 12–48 (Willey, London, 1959).
    Google Scholar 
    Prescott, G. W. Algae of the western Great Lakes area. (1962).Bellinger, E. G. A Key to Common Algae: Freshwater, Estuarine and Some Coastal Species (Institution of Water and Environmental Management London, 1992).
    Google Scholar 
    Kimmerer, W. J. & Slaughter, A. M. A new electivity index for diet studies that use count data. Limnol. Oceanogr. Methods 19, 552–565 (2021).Article 

    Google Scholar 
    Pinheiro, J., Bates, D., DebRoy, S. & Sarkar, D. R Development Core Team. nlme: Linear and nonlinear mixed effects models, 2012. http://CRAN.R-project.org/package=nlme. R package version, 3.1–103 (2020).Lê, S., Josse, J. & Husson, F. FactoMineR: an R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).Article 

    Google Scholar 
    Galili, T., O’Callaghan, A., Sidi, J. & Sievert, C. heatmaply: an R package for creating interactive cluster heatmaps for online publishing. Bioinformatics 34, 1600–1602 (2018).Article 
    CAS 

    Google Scholar 
    Wickham, H., Chang, W. & Wickham, M. H. Package ‘ggplot2’. Create Elegant Data Visualisations Using the Grammar of Graphics. Version 2, 1–189 (2016).Peterson, B. G. et al. Package ‘PerformanceAnalytics’. R Team Cooperation (2018).Lewis, R. E. & Uncles, R. J. Factors affecting longitudinal dispersion in estuaries of different scale. Ocean Dyn. 53, 197–207 (2003).Article 

    Google Scholar 
    Shaha, D., Cho, Y.-K., Seo, G.-H., Kim, C.-S. & Jung, K. Using flushing rate to investigate spring-neap and spatial variations of gravitational circulation and tidal exchanges in an estuary. Hydrol. Earth Syst. Sci. 14, 1465–1476 (2010).Article 

    Google Scholar 
    Shaha, D. C., Cho, Y.-K., Kim, T.-W. & Valle-Levinson, A. Spatio-temporal variation of flushing time in the Sumjin River Estuary. Terrestr. Atmos. Ocean. Sci. 23, 119 (2012).Article 

    Google Scholar 
    Shivaprasad, A. et al. Seasonal stratification and property distributions in a tropical estuary (Cochin estuary, west coast, India). Hydrol. Earth Syst. Sci. 17, 187–199 (2013).Article 

    Google Scholar 
    Haralambidou, K., Sylaios, G. & Tsihrintzis, V. A. Salt-wedge propagation in a Mediterranean micro-tidal river mouth. Estuar. Coast. Shelf Sci. 90, 174–184 (2010).Article 
    CAS 

    Google Scholar 
    Dyer, K. R. Estuaries: A physical introduction (1973).Rahman, M. et al. Impact assessment of twenty-two days fishing ban in the major spawning grounds of Tenualosa ilisha (Hamilton, 1822) on its spawning success in Bangladesh. J. Aquac. Res. Dev. 8, 489 (2017).Article 

    Google Scholar 
    Alves, A. S. et al. Spatial distribution of subtidal meiobenthos along estuarine gradients in two southern European estuaries (Portugal). J. Mar. Biol. Assoc. U.K. 89, 1529–1540 (2009).Article 
    CAS 

    Google Scholar 
    Teixeira, H., Salas, F., Borja, A., Neto, J. & Marques, J. A benthic perspective in assessing the ecological status of estuaries: The case of the Mondego estuary (Portugal). Ecol. Ind. 8, 404–416 (2008).Article 

    Google Scholar 
    Garmendia, M. et al. Eutrophication assessment in Basque estuaries: Comparing a North American and a European method. Estuar. Coasts 35, 991–1006 (2012).Article 

    Google Scholar 
    Istvánovics, V. Eutrophication of Lakes and Reservoirs. Lake Ecosystem Ecology 47–55 (Elsevier, 2010).
    Google Scholar 
    Dodds, W. K. Eutrophication and trophic state in rivers and streams. Limnol. Oceanogr. 51, 671–680 (2006).Article 
    CAS 

    Google Scholar 
    Bricker, S., Ferreira, J. & Simas, T. An integrated methodology for assessment of estuarine trophic status. Ecol. Model. 169, 39–60 (2003).Article 
    CAS 

    Google Scholar 
    Vega, M., Pardo, R., Barrado, E. & Debán, L. Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Res. 32, 3581–3592 (1998).Article 
    CAS 

    Google Scholar 
    Huang, Y., Yang, C., Wen, C. & Wen, G. S-type dissolved oxygen distribution along water depth in a canyon-shaped and algae blooming water source reservoir: Reasons and control. Int. J. Environ. Res. Public Health 16, 987 (2019).Article 
    CAS 

    Google Scholar 
    Rahman, M. & Cowx, I. Lunar periodicity in growth increment formation in otoliths of hilsa shad (Tenualosa ilisha, Clupeidae) in Bangladesh waters. Fish. Res. 81, 342–344 (2006).Article 

    Google Scholar 
    Rahman, M. J. Population Biology and Management of hilsa shad (Tenualosa ilisha) in Bangladesh (University of Hull, 2001).Milton, D. A. & Chenery, S. R. Movement patterns of the tropical shad hilsa (Tenualosa ilisha) inferred from transects of 87Sr/86Sr isotope ratios in their otoliths. Can. J. Fish. Aquat. Sci. 60, 1376–1385 (2003).Article 

    Google Scholar 
    Rahman, S., Sarker, M. R. H. & Mia, M. Y. Spatial and temporal variation of soil and water salinity in the South-Western and South-Central Coastal Region of Bangladesh. Irrig. Drain. 66, 854–871 (2017).Article 

    Google Scholar 
    Kida, S. & Yamazaki, D. The mechanism of the freshwater outflow through the Ganges–Brahmaputra–Meghna delta. Water Resour. Res. 56, e2019WR026412 (2020).Article 

    Google Scholar 
    Sarma, V. et al. Intra-annual variability in nutrients in the Godavari estuary, India. Contin. Shelf Res. 30, 2005–2014 (2010).Article 

    Google Scholar 
    Burford, M. et al. Controls on phytoplankton productivity in a wet–dry tropical estuary. Estuar. Coast. Shelf Sci. 113, 141–151 (2012).Article 
    CAS 

    Google Scholar 
    Vitousek, P. M. et al. Towards an ecological understanding of biological nitrogen fixation. Biogeochemistry 57, 1–45 (2002).Article 

    Google Scholar 
    Galloway, J. N. & Cowling, E. B. Reactive nitrogen and the world: 200 years of change. Ambio 31, 64–71 (2002).Article 

    Google Scholar 
    Kennish, M. & De Jonge, V. in Human-Induced Problems (Uses and Abuses) 113–148 (Elsevier Inc., 2012).Alongi, D., Boto, K. & Robertson, A. Nitrogen and phosphorus cycles. Coastal and Estuarine Studies, 251–251 (1993).Wolanski, E., McLusky, D., Laane, R. & Middleburg, J. (Academic Press, 2011).Suthers, I., Rissik, D. & Richardson, A. Plankton: A Guide to Their Ecology and Monitoring for Water Quality (CSIRO Publishing, 2019).Book 

    Google Scholar 
    Mackay, D. W. & Fleming, G. Correlation of dissolved oxygen levels, fresh-water flows and temperatures in a polluted estuary. Water Res. 3, 121–128 (1969).Article 

    Google Scholar 
    Lomas, M. W. & Glibert, P. M. Temperature regulation of nitrate uptake: A novel hypothesis about nitrate uptake and reduction in cool-water diatoms. Limnol. Oceanogr. 44, 556–572 (1999).Article 
    CAS 

    Google Scholar 
    Dortch, Q. The interaction between ammonium and nitrate uptake in phytoplankton. Mar. Ecol. Prog. Ser. Oldendorf 61, 183–201 (1990).Article 
    CAS 

    Google Scholar 
    Admiraal, W., Riaux-Gobin, C. & Laane, R. W. Interactions of ammonium, nitrate, and D-and L-amino acids in the nitrogen assimilation of two species of estuarine benthic diatoms. Mar. Ecol. Prog. Ser. 40, 267–273 (1987).Article 
    CAS 

    Google Scholar 
    Rabalais, N., Turner, R., Dortch, Q., Wiseman, W. Jr. & Sen Gupta, B. Nutrient changes in the Mississippi River and system responses on the adjacent continental shelf. Estuaries 19, 386 (1996).Article 
    CAS 

    Google Scholar 
    Gholizadeh, M. H., Melesse, A. M. & Reddi, L. Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida. Sci. Total Environ. 566, 1552–1567 (2016).Article 

    Google Scholar 
    Elser, J. J. et al. Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecol. Lett. 10, 1135–1142 (2007).Article 

    Google Scholar 
    Teichberg, M. et al. Eutrophication and macroalgal blooms in temperate and tropical coastal waters: Nutrient enrichment experiments with Ulva spp. Glob. Change Biol. 16, 2624–2637 (2010).Article 

    Google Scholar 
    Valiela, I. & Bowen, J. Nitrogen sources to watersheds and estuaries: Role of land cover mosaics and losses within watersheds. Environ. Pollut. 118, 239–248 (2002).Article 
    CAS 

    Google Scholar 
    Woodland, R. J. et al. Nitrogen loads explain primary productivity in estuaries at the ecosystem scale. Limnol. Oceanogr. 60, 1751–1762 (2015).Article 

    Google Scholar 
    Howarth, R. et al. Coupled biogeochemical cycles: Eutrophication and hypoxia in temperate estuaries and coastal marine ecosystems. Front. Ecol. Environ. 9, 18–26 (2011).Article 

    Google Scholar 
    Winder, J. A. & Cheng, D. M. Quantification of Factors Controlling the Development of Anabaena Circinalis Blooms (Urban Water Research Association of Australia, 1995).
    Google Scholar 
    Descy, J.-P. Phytoplankton composition and dynamics in the River Meuse (Belgium). Arch. Hydrobiol. Supplementband. Monographische Beiträge 78, 225–245 (1987).
    Google Scholar 
    Robarts, R. D. & Zohary, T. Temperature effects on photosynthetic capacity, respiration, and growth rates of bloom-forming cyanobacteria. NZ J. Mar. Freshw. Res. 21, 391–399 (1987).Article 
    CAS 

    Google Scholar 
    Visser, P. M., Ibelings, B. W., Bormans, M. & Huisman, J. Artificial mixing to control cyanobacterial blooms: A review. Aquat. Ecol. 50, 423–441 (2016).Article 
    CAS 

    Google Scholar 
    Krishnan, A., Das, R. & Vimexen, V. Seasonal phytoplankton succession in Netravathi-Gurupura estuary, Karnataka, India: Study on a three tier hydrographic platform. Estuar. Coast. Shelf Sci. 242, 106830 (2020).Article 

    Google Scholar 
    Srinivas, L., Seeta, Y. & Reddy, M. Bacillariophyceae as ecological indicators of water quality in Manair Dam, Karimnagar, India. Int. J. Sci. Res. Sci. Tech 4, 468–474 (2018).
    Google Scholar 
    Mohanty, B. P. et al. Fatty acid profile of Indian shad Tenualosa ilisha oil and its dietary significance. Natl. Acad. Sci. Lett. 35, 263–269 (2012).Article 
    CAS 

    Google Scholar 
    De, D. et al. Nutritional profiling of hilsa (Tenualosa ilisha) of different size groups and sensory evaluation of their adults from different riverine systems. Sci. Rep. 9, 1–11 (2019).Article 
    CAS 

    Google Scholar 
    Hasan, K. M. M., Ahmed, Z. F., Wahab, M. A. & Mohammed, E. Y. Food and Feeding Ecology of hilsa (Tenualosa ilisha) in Bangladesh’s Meghna River Basin. (International Institute for Environment and Development, 2016). More