Philippa Kaur

DOC changes under photocatalytic degradation
The changes in DOC during photocatalysis are illustrated in Figs. 1–2 and Table S1. DOC removal after 180-min irradiation varied from 16.76 to 60.88% depending on the experimental conditions. All observed degradation trends followed a pseudo-first-order kinetic model (R2 = 0.96–1.00), which has also been reported in other studies to describe the photodegradation of DOM15,16,17. The effects of ZnO dosage, pH level, and presence of inorganic anions on the degradation of DOM are described in detail in the following sub-sections.
Figure 1

Effect of ZnO dosage and pH on DOC removal for photocatalytic degradation of DOM: (a) degradation curves, (b) removal %, and (c) degradation rates.

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Figure 2

Effect of inorganic anions on DOC removal for photocatalytic degradation of DOM with 0.2 g/L ZnO at pH 7: (a) degradation curves, (b) removal %, and (c) degradation rates.

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Effect of ZnO dosage
The relationship between ZnO dosage and DOC degradation is presented in Fig. 1 and Table S1. When ZnO dosage increased from 0.1 to 0.3 g/L, DOC removal and apparent degradation rate (kapp) were ∆ 21.42% and 2.49-fold higher at pH 4, ∆ 29.64% and 2.53-fold higher at pH 7, and ∆ 27.62% and 2.28-fold higher at pH 10, respectively. It is assumed that more active sites become available with increasing ZnO dosage, thus facilitating the generation of OH and consequently greater DOC removal and a higher degradation rate.
Effect of pH
As illustrated in Fig. 1 and Table S1, DOC removal and kapp were highest at a pH of 7 for all ZnO dosage levels. This observation could be explained by the ionization of DOM and the zeta potential (ZP) of ZnO at different pH levels. The acidic functional groups (e.g., –COOH and –OHphenolic) in HA molecules would become more ionized as the aqueous pH increases because pKa,-COOH and pKa,-OH have been reported to be 4.7 and 12.5, respectively (Eqs. 2)20:

$${text{HOOC}} cdots -{text{HA}}- cdots {text{OH}} to^{ – } {text{OOC}} cdots- {text{HA}} – cdots {text{O}}^{ – } , + , 2{text{H}}^{ + }$$
(2)

HAs are negatively charged over a wide pH range (2.0–10.7) 21, while the ZP of ZnO is positive at a pH range of 6.7–9.3 and negative otherwise (the pHZPC of ZnO = 9.0 ± 0.3) 22. Thus, at pH 7, where the dominant charges of ZnO and HA oppose each other, the electrostatic attraction between HA molecules and the ZnO surface would lead to the more rapid exposure of the HAs to reactive species (especially ·OH), resulting in the maximum DOC removal and photodegradation rate. On the other hand, at a pH of 4 and 10, both the HAs and ZnO are negatively charged, thus the repulsive force between the HA molecules and the ZnO surface would be strong. Therefore, there would be limited opportunities for the HA molecules to contact with reactive species near the ZnO surface, reducing removal and kapp.
In addition, it was found in the present study that DOC removal was always higher at pH 10 than at pH 4 for the same ZnO dosage. It has been reported that ZnO aggregation occurs at pH 4 (pHZPC of ZnO = 9.0 ± 0.3)22, which would slow the mass transport rate and consequently reduce the active surface area of ZnO. In addition, acidic conditions (i.e., less OH−) are less favorable for the formation of ·OH via the hole oxidation of OH−, lowering the efficiency of the attack of ·OH on DOM and the photocatalytic oxidation rate15, 16. These two reasons lead to lower total DOC removal and a lower photodegradation rate at a pH of 4.
Effect of inorganic anions
Figure 2 and Table S1 show the effects of inorganic ions on DOC removal. When fitting a pseudo-first-order kinetics model (R2 = 0.96–0.99), the presence of Cl−, SO42−, and HCO3− anions inhibited DOC removal. This occurred possibly because of two reasons. First, the ZnO surface is positively charged at pH 7, and the anions can be easily adsorbed onto the positively charged surface of the catalyst by electrostatic attraction, leading to the competitive adsorption. Second, the anions acted as free radical scavengers by reducing the availability of positive holes and by competitively reacting with ·OH6, 23,24,25, as given by the following reactions (Eq. 3–10) (Table S2):

$${text{Cl}}^{ – } + {text{h}}_{{{text{VB}}}}^{ + } to {text{ Cl}}^{ cdot }$$
(3)

$${text{Cl}}^{ – } + { }^{ cdot } {text{OH}} to {text{ HOCl}}^{ cdot – } ;;;;;;;;;{ }left( {k = 4.3 times 10^{9} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(4)

$${text{HOCl}}^{ cdot – } to {text{Cl}}^{ – } + { }^{ cdot } {text{OH }};;;;;;;; left( {k = 6.1 times 10^{9} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(5)

$${text{SO}}_{4}^{2 – } + {text{ h}}_{{{text{VB}}}}^{ + } { } to {text{ SO}}_{4}^{ cdot – }$$
(6)

$${text{SO}}_{4}^{2 – } +^{ cdot } {text{OH}} to {text{ SO}}_{4}^{ cdot – } + {text{ OH}}^{ – } { }left( {k = 1.18 times 10^{6} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(7)

$${text{HCO}}_{3}^{ – } + {text{h}}_{{{text{VB}}}}^{ + } to {text{CO}}_{3}^{ cdot – } + {text{ H}}_{2} {text{O}}$$
(8)

$${text{HCO}}_{3}^{ – } +^{ cdot } {text{OH}} to {text{ CO}}_{3}^{ cdot – } + {text{ H}}_{2} {text{O }}left( {k = 8.5 times 10^{6} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(9)

The strength of the inhibition effect followed the order of HCO3−  > SO42−  > Cl−  > no ions, possibly because HCO3− had the strongest capturing effect on ·OH (k = 8.5 × 106)25. The HCO3− quenched the ({h}_{VB}^{+}), which prevented the generation of ·OH (i.e., it inhibited the ({h}_{VB}^{+}) + H2O → ·OH + H+ reaction) and may, in turn, have led to the formation of ({CO}_{3}^{cdot-}) via the oxidation of ({HCO}_{3}^{cdot-}) by ({h}_{VB}^{+}) (Eq. 8), with a lower reactivity (E° = 1.78 V) than ·OH26. ({CO}_{3}^{cdot-}) has a weaker oxidative ability than ·OH and rarely reacts with organic matter, thus decreasing the reaction rate significantly6. In addition, HCO3- anions form a strong combination on the surface of the catalyst and can significantly inhibit the adsorption of HAs on the catalyst due to the weak absorption competition between HCO3− and HAs6.
Change in UV254
The degradation process as measured using UV254 is summarized in Figs. S2, S3 and Table S1. All photodegradation rates fit a pseudo-first-order kinetics model (R2 = 0.93–1.00), and there was a strong correlation between UV254 and DOC (R2 = 0.92–0.98), suggesting that chromophoric DOM accounted for the most significant proportion of DOC removal16. The effects of ZnO dosage, pH level (Fig. S2), and the presence of inorganic anions (Fig. S3) on UV254 removal and photodegradation rate were analogous to those described in the previous section. The highest in UV254 removal was 96.54% after 180 min of irradiation with a ZnO dosage of 0.3 g/L, a pH of 7, and no additional inorganic anions.
Total removal and the photodegradation rate calculated based on UV254 were much higher than those calculated using DOC concentration under all experimental conditions, which may be because the terminal functional groups of the aromatic compounds (e.g., hydroxyl and carboxyl) reinforced the adoption affinity of the surface of the catalyst particles15,16,17 and/or some of the DOM chromophores were partially transformed into non-UV-absorbing compounds (e.g., low-molecular-weight organic acids, alcohols, etc.) in the photochemical reaction13, 24.
The rapid reduction in UV254 with irradiation time (Fig. S2) suggests that the DOM chromophores, which mostly consisted of large aromatic rings, might have been rapidly broken down into smaller non-aromatic structures12, 25. The UV/Vis absorption spectra of DOM showed, as expected, rapid decrease with reaction time, and the remained absorption in UV range, even after 180-min irradiation implies the necessity of experimental optimizations (such as reaction time, power of light source, dosage of catalyst, etc.) for complete mineralization.
Change in SUVA254
Figure 3 presents the changes in SUVA254 during irradiation. Initially, the SUVA254 values were all higher than 4, ranging from 4.37 to 4.98, indicating that the organic matter was primarily composed of hydrophobic compounds with high molecular weights (HMWs)9, 26. There was a substantial reduction in SUVA254 (over 90% of initial values) after 180 min of irradiation in most of the samples except for two (pH 4 and pH 10 with 0.1 g/L ZnO). This was because of the preferential removal of aromatic chromophores over aliphatic moieties, followed by the transition of the DOM to non- or less-UV-absorbing substances28. This reduction in SUVA254 also indicates that HMW DOM was rapidly decomposed into organic compounds of lower molecular weight (LMW), which is supported by the lower DOC removal values compared to UV254-measured removal for the same reaction time27. A strong linear correlation (R2 = 0.92–0.98) was found between SUVA254 and DOC, and similar effects of ZnO dosage, pH level, and the presence of inorganic anions were observed.
Figure 3

Changes of SUVA254 of DOM during photocatalysis under different ZnO dosages and pHs: (a) SUVA254 and (b) a total reduction (%).

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Change in EEMs
The changes in the EEMs of the DOM over 180 min of irradiation under optimal conditions (0.2 g/L ZnO and pH 7) are presented in Fig. S4. It was observed that the broad and strong peak at emission wavelengths above ~ 350 nm, commonly referred to as the humic-like peak, decreased significantly with increasing irradiation time. After 180 min, the fluorescence intensity for the measured wavelengths was almost zero, with no clear peaks.
The lower fluorescence intensity in the EEM plots of the DOM was likely due to the preferential photocatalytic degradation of the HMW fraction27, which led to an increase in the LMW fraction. This was supported by size-exclusion chromatography using DOC and UV254 detection, which also observed a reduction in fluorescence intensity with lower molecular weights based on the synchronous scan spectra of Aldrich HA fractions obtained with ultrafiltration after photocatalysis27. Moreover, the photocatalytic degradation of the HMW compounds in the DOM was similar to the previously reported photocatalytic degradation of NOM from a bog lake29. The photocatalytic degradation of DOM followed a similar sequence to other oxidation processes, such as the chlorination of NOM30 and the photocatalytic degradation of commercial HA using TiO2 and a solar UV-light simulator27.
Behavior of the components during photocatalysis
EEM-PARAFAC components
Using 125 EEM samples from 25 experiments, two components (C1 and C2) were identified using PARAFAC modeling (Fig. S5 and Table S3). It was considered reasonable to extract two fluorophores from the samples because Sigma-Aldrich HA is known to be pedogenic with quite uniform sources31. C1 produced a maximum peak at an Ex/Em of 261 nm/ ≥ 500 nm, exhibiting a broad excitation spectrum and gradual emission above 350 nm, while C2 peaked at an Ex/Em of  pH 10  > pH 4 with 0.1 g/L ZnO and the order pH 10  > pH 7  > pH 4 with 0.2 g/L ZnO. With a ZnO dosage of 0.3 g/L, total removal followed the order pH 10  > pH 7  > pH 4, while the photodegradation rate followed the order pH 7  > pH 4  > pH 10 (Fig. 4). A difference from previous results was also observed for the addition of inorganic anions. In the presence of inorganic anions, total Fmax removal and the photodegradation rate followed the order Cl−  > no anions  > SO42−  > HCO3−. The highest total Fmax removal was 99.36% after 180 min irradiation at a ZnO dosage of 0.3 g/L and a pH of 10, with no additional inorganic anions (Fig. 5).
Because the degradation behavior of both PARAFAC components followed a first-order exponential decay process, their photocatalytic degradation and kinetic rates could be directly compared. Total Fmax removal and the photodegradation rate of C1 were higher than those of C2, which can be explained by the excitation and emission wavelengths of each component. Although both C1 and C2 were both identified as terrestrial humic-like organic matter, C1 represents a combination of peak A and peak C, exhibiting longer excitation and emission wavelengths than C2. With peaks at longer wavelengths, C1 may be associated with the structural condensation and polymerization of DOM15, 32. Indeed, more pronounced fluorescence at longer emission wavelengths in the EEMs of larger sized and/or more hydrophobic DOM fractions has been previously reported33. Therefore, the results indicate the preferential adsorption of more hydrophobic and larger DOM molecules onto minerals and/or nanoparticles, which has also been reported in previous studies15, 34. In addition, because C2 has shorter excitation wavelengths than C1, it would be less excited by visible light than C1.
Total DOM removal and photodegradation rates calculated using DOC, UV254, and the PARAFAC components were also compared (Fig. 6). It was interesting to observe that the total removal and photodegradation rates calculated using the Fmax of the two PARAFAC components were higher than those calculated using DOC and UV254. In particular, under optimal conditions (0.2 g/L ZnO, pH 7, and no inorganic anions), the total removal of C1 (100%) and C2 (98.97%) was observed to be higher than total UV254 removal (95.54%) and much higher than total DOC removal (43.04%), while the photodegradation rate of C1 was 11.27-fold and 8.55-fold higher than the photodegradation rates calculated with DOC and UV254, respectively. Similarly, the photodegradation rate of C2 was 1.90-fold and 1.44-fold higher than the photodegradation rates calculated with DOC and UV254, respectively. The more rapid degradation of fluorescence components compared to UV-absorbing moieties (i.e., UV254) could be explained by the fluorescence arising from the π*–π transitions in DOM molecules and its rapid extinction under UV irradiation15, 16.
Figure 6

Changes in DOC, UV254, and two EEM-PARAFAC components during photocatalytic degradation of DOM with 0.2 g/L ZnO at pH 7 under artificial sunlight: (a) degradation curves and (b) removal % and degradation rates.

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The proposed reaction mechanism for the ZnO-assisted photocatalytic degradation of DOM under artificial sunlight is presented in Fig. S6. When ZnO is irradiated with artificial light containing photonic energy (hv), valence band hole (({h}_{VB}^{+})) and conduction band electron (({e}_{CB}^{-})) pairs are produced, as given in Eq. (10)11. The ({h}_{VB}^{+}) reacts with H2O and hydroxide ions to yield ·OH (Eqs. 12 and 13)7,8,9. The reduction of dissolved or adsorbed O2 to ({O}_{2}^{cdot-}) by ({e}_{CB}^{_}) is depicted in Eq. (14)7,8,9. The ({O}_{2}^{cdot-}) is converted to H2O2 via disproportionation with protons (Eq. 15) or forms ({HO}_{2}^{cdot}) via protonation, which has a short lifetime due to the rapid reaction with ({O}_{2}^{cdot-}) or ({HO}_{2}^{cdot}) to form the more stable H2O2 (Eqs. 16 and 17)7,8,9, 35. The one-electron reduction of H2O2 produces ·OH (Eq. 19), while H2O2 can also react with ({O}_{2}^{cdot-}) to form ·OH (Eqs. 20 and 21)7,8,9. The generated ·OH is a powerful oxidizing agent that can attack DOM at or near the ZnO surface (Eq. 23). The reaction of ·OH with HAs (as a representative form of DOM) results in the release of LMW acids, amino acids, and ammonia36. The ({O}_{2}^{cdot-}) can also oxidize the DOM molecules (Eq. 24)16. Moreover, upon absorbing light, DOM can act as a photosensitizer in the generation of reactive species such as singlet oxygen (1O2), ·OH, and triplet DOM states (3DOM*), as given in Eqs. (25–28)37. 3DOM* is a potent oxidant of many aquatic contaminants that react with target organic substances directly through electron and energy transfer mechanisms to generate reactive oxygen species such as 1O2, ·OH, and H2O237, thus significantly influencing on the degradation of various fluorophores.

$$ZnO+hv to {h}_{VB}^{+}+{e}_{CB}^{-}$$
(10)

$${H}_{2}Oto {OH}^{-}+{H}^{+}$$
(11)

$${text{h}}_{{{text{VB}}}}^{ + } + {text{ H}}_{2} {text{O}} to { }^{ cdot } {text{OH }} + {text{ H}}^{ + }$$
(12)

$${text{h}}_{{{text{VB}}}}^{ + } + {text{ OH}}^{ – } to { }^{ cdot } {text{OH}}$$
(13)

$${text{e}}_{{{text{CB}}}}^{_} + {text{ O}}_{2} { } to {text{ O}}_{2}^{ cdot – }$$
(14)

$${text{O}}_{2}^{ cdot – } + 2{text{H}}^{ + } + {text{e}}_{{{text{CB}}}}^{_} { } to {text{H}}_{2} {text{O}}_{2}$$
(15)

$${text{O}}_{2}^{ cdot – } + {text{H}}^{ + } to {text{HO}}_{2}^{ cdot } ;;;;;;left( {k = 2.1 times 10^{10} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(16)

$${text{HO}}_{2}^{ cdot } + {text{HO}}_{2}^{ cdot } to {text{H}}_{2} {text{O}}_{2} + {text{O}}_{2} ;;;;;;;;left( {k = 8.3 times 10^{5} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(17)

$$^{ cdot } {text{OH }} +^{ cdot } {text{OH}} to {text{H}}_{2} {text{O}}_{2} ;;;;;;;;;;;;left( {k = 5.5 times 10^{9} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(18)

$${text{H}}_{2} {text{O}}_{2} + {text{H}}^{ + } + {text{e}}_{{{text{CB}}}}^{_} to { }^{ cdot } {text{OH }} + {text{ H}}_{{2}} {text{O}}$$
(19)

$${text{H}}_{2} {text{O}}_{2} + {text{O}}_{2}^{ cdot – } to {text{OH}}^{ – } + {text{O}}_{2} + ^{ cdot } {text{OH}} ;;;;;;;left( {k = 0.13{text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(20)

$${text{H}}_{2} {text{O}}_{2} + {text{hv}} to {2}^{ cdot } {text{OH}}$$
(21)

$${text{H}}_{2} {text{O}}_{2} +^{ cdot } {text{OH}} to {text{H}}_{{2}} {text{O}};;;;;;;left( {k = 2.7 times 10^{7} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(22)

$${text{DOM }} +^{ cdot } {text{OH}} to {text{CO}}_{{2}} + {text{ H}}_{{2}} {text{O }} + {text{ Products}};;;;;;;;left( {k = 1.7 times 10^{8} {text{ Mc}}^{ – 1} {text{s}}^{ – 1} } right)$$
(23)

$${text{DOM }} + {text{O}}_{2}^{ cdot – } to {text{CO}}_{2} + {text{ H}}_{{2}} {text{O }} + {text{ Products}}$$
(24)

$${text{DOM }} + {text{ hv}} to^{{1}} {text{DOM}}^{*} to^{{3}} {text{DOM}}^{*}$$
(25)

$$^{{3}} {text{DOM}}^{*} + {text{ O}}_{{2}} to^{{1}} {text{DOM }} +^{{1}} {text{O}}_{{2}}$$
(26)

$${text{DOM}} + {text{ O}}_{2}^{ cdot – } to {text{DOM}}^{ cdot – } + {text{O}}_{2}$$
(27)

$$2{text{O}}_{2}^{ cdot – } + 2{text{H}}^{ + } { } to {text{ H}}_{2} {text{O}}_{2} + {text{ O}}_{2} ;;;;;;;;;;left( {k = 4.0 times 10^{4} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(28)

The effects of photolysis, adsorption, and photocatalysis on the degradation of DOM was also assessed. Figure 7 compares the results for total removal and the degradation rate for these three processes. The total DOM removal and degradation rate calculated with DOC are illustrated in Fig. 7a. After 180-min irradiation, total DOM removal was 2.92% for photolysis, 10.15% for adsorption, and 43.04% for photocatalysis. The photocatalytic rate was 18.6-fold and 5.5-fold higher than that for photolysis and adsorption. The DOM removal and degradation rate calculated with UV254 (Fig. 7b) also revealed that photocatalysis was more effective than the other two processes. Specifically, total DOM removal was 4.03% for photolysis, 19.46% for adsorption, and 95.45% for photocatalysis, while the degradation rate was 93.6-fold and 17.0-fold higher than that of photolysis and adsorption, respectively. Based on these results, we can conclude that adsorption by ZnO only and photolysis only play a minor role in DOM removal, while the synergistic effects of photocatalysis are vital to this process.
Figure 7

Comparison of photolysis, photocatalysis and adsorption of DOM with 0.2 g/L ZnO at pH 7: (a) DOC concentrations and (b) UV254 values.

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1.
Dyck, A. J. & Sumaila, U. R. Economic impact of ocean fish populations in the global fishery. J. Bioeconomics 12, 227–243 (2010).
Google Scholar 
2.
Golden, C. D. et al. Nutrition: fall in fish catch threatens human health. Nature 534, 317–320 (2016).
Google Scholar 

3.
Teh, L. C. L. & Pauly, D. Who brings in the fish? The relative contribution of small-scale and industrial fisheries to food security in Southeast Asia. Front. Mar. Sci. 5, 44 (2018).
Google Scholar 

4.
Gillett, R. Fisheries in the Economies of Pacific Island Countries and Territories (Pacific Community, 2016).

5.
Kawarazuka, N. & Béné, C. Linking small-scale fisheries and aquaculture to household nutritional security: an overview. Food Secur. 2, 343–357 (2010).
Google Scholar 

6.
Sale, P. F. et al. Transforming management of tropical coastal seas to cope with challenges of the 21st century. Mar. Pollut. Bull. 85, 8–23 (2014).
Google Scholar 

7.
Bell, J. D. et al. Planning the use of fish for food security in the Pacific. Mar. Policy 33, 64–76 (2009).
Google Scholar 

8.
Hicks, C. C. et al. Harnessing global fisheries to tackle micronutrient deficiencies. Nature 574, 95–98 (2019).
Google Scholar 

9.
Kennedy, G., Nantel, G. & Shetty, P. The scourge of “hidden hunger”: global dimensions of micronutrient deficiencies. Food Nutr. Agric. 32, 8–16 (2003).
Google Scholar 

10.
Teh, L. S. L., Teh, L. C. L. & Sumaila, U. R. Quantifying the overlooked socio-economic contribution of small-scale fisheries in Sabah, Malaysia. Fish. Res. 110, 450–458 (2011).
Google Scholar 

11.
Pauly, D. & Zeller, D. Sea Around Us Concepts, Design and Data. Sea Around Us http://www.seaaroundus.org (2015).

12.
Béné, C. Small-scale fisheries: assessing their contribution to rural livelihoods in developing countries. FAO Fish. Circ. 1008, 46 (2006).
Google Scholar 

13.
Williams, P. & Reid, C. Overview of tuna fisheries in the western and central Pacific Ocean, including economic conditions-2017. WCPFC Sci. Comm. SC14-2018/GN-WP-01 66pp (2018).

14.
Pacific Islands Forum Fisheries Agency (FFA). Tuna Development Indicators 2016. https://ffa.int/system/files/FFA Tuna Development Indicators Brochure.pdf (Pacific Islands Forum Fisheries Agency, 2017).

15.
Teh, L. C. L. & Sumaila, U. R. Contribution of marine fisheries to worldwide employment. Fish Fish. 14, 77–88 (2013).
Google Scholar 

16.
Jentoft, S. Life above water—essays on human experiences of small-scale fisheries. TBTI Global Book Series 1 (2019).

17.
Kurien, J. SSF guidelines: the beauty of the small. Samudra Rep. 72, 30–36 (2016).
Google Scholar 

18.
Teh, L. S. L., Teh, L. C. L. & Sumaila, U. R. A global estimate of the number of coral reef fishers. PLoS One 8, e65397 (2013).
Google Scholar 

19.
Alberti, M. et al. Research on coupled human and natural systems (CHANS): approach, challenges, and strategies. Bull. Ecol. Soc. Am. 92, 218–228 (2011).
Google Scholar 

20.
Liu, J., Hull, V., Luo, J., Yang, W. & Liu, W. Multiple telecouplings and their complex interrelationships. Ecol. Soc. 20, 44 (2015).
Google Scholar 

21.
Cinner, J. & McClanahan, T. R. Socioeconomic factors that lead to overfishing in small-scale coral reef fisheries of Papua New Guinea. Environ. Conserv. 33, 73–80 (2006).
Google Scholar 

22.
McClanahan, T. R., Hicks, C. C. & Darling, E. S. Malthusian overfishing and efforts to overcome it on Kenyan coral reefs. Ecol. Appl. 18, 1516–1529 (2008).
Google Scholar 

23.
Gardner, T. A., Côté, I. M., Gill, J. A., Grant, A. & Watkinson, A. R. Long-term region-wide declines in Caribbean corals. Science 301, 958–960 (2003).
Google Scholar 

24.
Islam, M. S. & Tanaka, M. Impacts of pollution on coastal and marine ecosystems including coastal and marine fisheries and approach for management: a review and synthesis. Mar. Pollut. Bull. 48, 624–649 (2004).
Google Scholar 

25.
Hodgson, G. & Dixon, J. A. Logging Versus Fisheries and Tourism in Palawan: An Environmental and Economic Analysis (East-West Environment and Policy Institute, 1988).

26.
Hodgson, G. & Dixon, J. A. in Resources & Environment in Asia’s Marine Sector (ed. Marsh, J. B.) 421–446 (CRC, 1992).

27.
Côté, I. M., Green, S. J. & Hixon, M. A. Predatory fish invaders: insights from Indo-Pacific lionfish in the western Atlantic and Caribbean. Biol. Conserv. 164, 50–61 (2013).
Google Scholar 

28.
Lehodey, P., Senina, I., Calmettes, B., Hampton, J. & Nicol, S. Modelling the impact of climate change on Pacific skipjack tuna population and fisheries. Clim. Change 119, 95–109 (2013).
Google Scholar 

29.
Asch, R. G., Cheung, W. W. L. & Reygondeau, G. Future marine ecosystem drivers, biodiversity, and fisheries maximum catch potential in Pacific Island countries and territories under climate change. Mar. Policy 88, 285–294 (2018).
Google Scholar 

30.
Jones, M. C. & Cheung, W. W. L. Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES J. Mar. Sci. 72, 741–752 (2015).
Google Scholar 

31.
Lam, V. W. Y., Cheung, W. W. L., Reygondeau, G. & Sumaila, U. R. Projected change in global fisheries revenues under climate change. Sci. Rep. 6, 32607 (2016).
Google Scholar 

32.
Cinner, J. E. et al. Building adaptive capacity to climate change in tropical coastal communities. Nat. Clim. Change 8, 117–123 (2018).
Google Scholar 

33.
Barange, M. et al. Impacts of Climate Change on Fisheries and Aquaculture. Synthesis of Current Knowledge, Adaptation and Mitigation Options (Food and Agriculture Organization of the United Nations, 2018).

34.
Pörtner, H.-O. et al. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (Intergovernmental Panel on Climate Change (IPCC), 2019).

35.
Bindoff, N. L. et al. Detection and Attribution of Climate Change: From Global to Regional (Intergovernmental Panel on Climate Change (IPCC), 2013).

36.
Bindoff, N. L., Cheung, W. W. L. & Kairo, J. G. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate Ch. 5 (eds Pörtner, H.-O. et al.) (Intergovernmental Panel on Climate Change (IPCC), 2019).

37.
Rodgers, K. B., Lin, J. & Frölicher, T. L. Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model. Biogeosciences 12, 3301–3320 (2015).
Google Scholar 

38.
Frölicher, T. L., Rodgers, K. B., Stock, C. A. & Cheung, W. W. L. Sources of uncertainties in 21st century projections of potential ocean ecosystem stressors. Glob. Biogeochem. Cycles 30, 1224–1243 (2016).
Google Scholar 

39.
Pörtner, H.-O. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Ch. 6 (eds Field, C. B. et al.) 411–484 (Cambridge Univ. Press, 2014).

40.
Abram, N. et al. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate Ch. 1 (Intergovernmental Panel on Climate Change (IPCC), 2019).

41.
Cheng, L. et al. Record-setting ocean warmth continued in 2019. Adv. Atmos. Sci. 37, 137–142 (2020).
Google Scholar 

42.
Huang, B. et al. Extended reconstructed sea surface temperature version 4 (ERSST. v4). Part I: upgrades and intercomparisons. J. Clim. 28, 911–930 (2015).
Google Scholar 

43.
Cheng, L., Abraham, J., Hausfather, Z. & Trenberth, K. E. How fast are the oceans warming. Science 363, 128–129 (2019).
Google Scholar 

44.
Intergovernmental Panel on Climate Change (IPCC). in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (ed. Pörtner, H.-O. et al) (Intergovernmental Panel on Climate Change (IPCC), 2019).

45.
Xie, S.-P. et al. Global warming pattern formation: Sea surface temperature and rainfall. J. Clim. 23, 966–986 (2010).
Google Scholar 

46.
Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Prog. Oceanogr. 141, 227–238 (2016).
Google Scholar 

47.
Frölicher, T. L. & Laufkötter, C. Emerging risks from marine heat waves. Nat. Commun. 9, 650 (2018).
Google Scholar 

48.
Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change 9, 306–312 (2019).
Google Scholar 

49.
Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).
Google Scholar 

50.
Oliver, E. C. J. et al. Longer and more frequent marine heatwaves over the past century. Nat. Commun. 9, 1324 (2018).
Google Scholar 

51.
Holbrook, N. J. et al. Keeping pace with marine heatwaves. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-020-0068-4 (2020).
Article  Google Scholar 

52.
Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under global warming. Nature 560, 360–364 (2018).
Google Scholar 

53.
Collins, M. et al. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate Ch. 6 (eds Pörtner, H.-O. et al.) (Intergovernmental Panel on Climate Change (IPCC), 2019).

54.
Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).
Google Scholar 

55.
Capotondi, A., Alexander, M. A., Bond, N. A., Curchitser, E. N. & Scott, J. D. Enhanced upper ocean stratification with climate change in the CMIP3 models. J. Geophys. Res. Oceans 117, C04031 (2012).
Google Scholar 

56.
Ganachaud, A. S. et al. in Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change (eds Bell, J. D., Johnson, J. E. & Hobday, A. J.) 101–187 (Secretariat of the Pacific Community, 2011).

57.
Stramma, L., Johnson, G. C., Sprintall, J. & Mohrholz, V. Expanding oxygen-minimum zones in the tropical oceans. Science 320, 655–658 (2008).
Google Scholar 

58.
Ito, T., Minobe, S., Long, M. C. & Deutsch, C. Upper ocean O2 trends: 1958–2015. Geophys. Res. Lett. 44, 4214–4223 (2017).
Google Scholar 

59.
Schmidtko, S., Stramma, L. & Visbeck, M. Decline in global oceanic oxygen content during the past five decades. Nature 542, 335–339 (2017).
Google Scholar 

60.
Helm, K. P., Bindoff, N. L. & Church, J. A. Observed decreases in oxygen content of the global ocean. Geophys. Res. Lett. 38, L23602 (2011).
Google Scholar 

61.
Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences 10, 6225–6245 (2013).
Google Scholar 

62.
Cocco, V. et al. Oxygen and indicators of stress for marine life in multi-model global warming projections. Biogeosciences 10, 1849–1868 (2013).
Google Scholar 

63.
Doney, S. C., Fabry, V. J., Feely, R. A. & Kleypas, J. A. Ocean acidification: the other CO2 problem. Annu. Rev. Mar. Sci. 1, 169–192 (2009).
Google Scholar 

64.
Gattuso, J.-P. et al. Contrasting futures for ocean and society from different anthropogenic CO2 emissions scenarios. Science 349, aac4722 (2015).
Google Scholar 

65.
Burger, F. A., Frölicher, T. L. & John, J. G. Increase in ocean acidity variability and extremes under increasing atmospheric CO2. Biogeosci. Discuss. https://doi.org/10.5194/bg-2020-22 (2020).

66.
Oppenheimer, M. et al. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate Ch. 4 (eds Pörtner, H.-O. et al.) (Intergovernmental Panel on Climate Change (IPCC), 2019).

67.
Moon, J. H., Song, Y. T., Bromirski, P. D. & Miller, A. J. Multidecadal regional sea level shifts in the Pacific over 1958–2008. J. Geophys. Res. Oceans 118, 7024–7035 (2013).
Google Scholar 

68.
Han, W. et al. Intensification of decadal and multi-decadal sea level variability in the western tropical Pacific during recent decades. Clim. Dyn. 43, 1357–1379 (2014).
Google Scholar 

69.
Thompson, P. R. & Mitchum, G. T. Coherent sea level variability on the North Atlantic western boundary. J. Geophys. Res. Oceans 119, 5676–5689 (2014).
Google Scholar 

70.
England, M. H. et al. Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus. Nat. Clim. Change 4, 222–227 (2014).
Google Scholar 

71.
Hamlington, B. D. et al. Uncovering an anthropogenic sea-level rise signal in the Pacific Ocean. Nat. Clim. Change 4, 782–785 (2014).
Google Scholar 

72.
McGregor, S. et al. Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming. Nat. Clim. Change 4, 888–892 (2014).
Google Scholar 

73.
Le Borgne, R. et al. in Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change (eds Bell, J. D., Johnson, J. E. & Hobday, A. J.) 189–249 (Secretariat of the Pacific Community, 2011).

74.
Steinacher, M. et al. Projected 21st century decrease in marine productivity: a multi-model analysis. Biogeosciences 7, 979–1005 (2010).
Google Scholar 

75.
Laufkötter, C. et al. Drivers and uncertainties of future global marine primary production in marine ecosystem models. Biogeosciences 12, 6955–6984 (2015).
Google Scholar 

76.
Stock, C. A., Dunne, J. P. & John, J. G. Drivers of trophic amplification of ocean productivity trends in a changing climate. Biogeosciences 11, 7125–7135 (2014).
Google Scholar 

77.
Cheung, W. W. L. & Pauly, D. in Explaining Ocean Warming: Causes, Scale, Effects and Consequences (eds Laffoley D. & Baxter J. M.) 239–253 (IUCN, 2016).

78.
Hoegh-Guldberg, O. et al. The Coral Triangle and Climate Change: Ecosystems, People and Societies at Risk (WWF Australia, 2009).

79.
Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83 (2018).
Google Scholar 

80.
Hoegh-Guldberg, O. et al. in Global Warming of 1.5°C (eds Masson-Delmotte, V. et al.) (Intergovernmental Panel on Climate Change (IPCC), 2018).

81.
Li, X., Bellerby, R., Craft, C. & Widney, S. E. Coastal wetland loss, consequences, and challenges for restoration. Anthropocene Coasts 1, 1–15 (2018).
Google Scholar 

82.
Pörtner, H.-O. et al. Climate induced temperature effects on growth performance, fecundity and recruitment in marine fish: developing a hypothesis for cause and effect relationships in Atlantic cod (Gadus morhua) and common eelpout (Zoarces viviparus). Cont. Shelf Res. 21, 1975–1997 (2001).
Google Scholar 

83.
Pörtner, H. O. & Farrell, A. P. Physiology and climate change. Science 322, 690–692 (2008).
Google Scholar 

84.
Pauly, D. & Cheung, W. W. L. Sound physiological knowledge and principles in modeling shrinking of fishes under climate change. Glob. Change Biol. 24, e15–e26 (2018).
Google Scholar 

85.
Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science 341, 1239–1242 (2013).
Google Scholar 

86.
Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change 3, 919–925 (2013).
Google Scholar 

87.
Cheung, W. W. L., Dunne, J., Sarmiento, J. L. & Pauly, D. Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J. Mar. Sci. 68, 1008–1018 (2011).
Google Scholar 

88.
Perry, A. L., Low, P. J., Ellis, J. R. & Reynolds, J. D. Climate change and distribution shifts in marine fishes. Science 308, 1912–1915 (2005).
Google Scholar 

89.
Cheung, W. W. L., Lam, V. W. Y. & Pauly, D. in Modelling Present and Climate-shifted Distribution of Marine Fishes and Invertebrates 5–50 (Fisheries Centre, 2008).

90.
Cheung, W. W. L. et al. Projecting global marine biodiversity impacts under climate change scenarios. Fish Fish. 10, 235–251 (2009).
Google Scholar 

91.
Mueter, F. J. & Litzow, M. A. Sea ice retreat alters the biogeography of the Bering Sea continental shelf. Ecol. Appl. 18, 309–320 (2008).
Google Scholar 

92.
Dulvy, N. K. et al. Climate change and deepening of the North Sea fish assemblage: a biotic indicator of warming seas. J. Appl. Ecol. 45, 1029–1039 (2008).
Google Scholar 

93.
Pörtner, H.-O. Oxygen- and capacity-limitation of thermal tolerance: a matrix for integrating climate-related stressor effects in marine ecosystems. J. Exp. Biol. 213, 881–893 (2010).
Google Scholar 

94.
Pauly, D. & Kinne, O. Gasping Fish and Panting Squids: Oxygen, Temperature and the Growth of Water-Breathing Animals Vol. 22 (International Ecology Institute, 2010).

95.
Mackenzie, C. L. et al. Ocean warming, more than acidification, reduces shell strength in a commercial shellfish species during food limitation. PLoS One 9, e86764 (2014).
Google Scholar 

96.
Rosas-Navarro, A., Langer, G. & Ziveri, P. Temperature affects the morphology and calcification of Emiliania huxleyi strains. Biogeosciences 13, 2913–2926 (2016).
Google Scholar 

97.
Pörtner, H.-O., Bock, C. & Mark, F. C. Oxygen- and capacity-limited thermal tolerance: bridging ecology and physiology. J. Exp. Biol. 220, 2685–2696 (2017).
Google Scholar 

98.
Daufresne, M., Lengfellner, K. & Sommer, U. Global warming benefits the small in aquatic ecosystems. Proc. Natl Acad. Sci. USA 106, 12788–12793 (2009).
Google Scholar 

99.
Baudron, A. R., Needle, C. L. & Marshall, C. T. Implications of a warming North Sea for the growth of haddock Melanogrammus aeglefinus. J. Fish. Biol. 78, 1874–1889 (2011).
Google Scholar 

100.
Sheridan, J. A. & Bickford, D. Shrinking body size as an ecological response to climate change. Nat. Clim. Change 1, 401–406 (2011).
Google Scholar 

101.
Cheung, W. W. L. et al. Shrinking of fishes exacerbates impacts of global ocean changes on marine ecosystems. Nat. Clim. Change 3, 254–258 (2013).
Google Scholar 

102.
Lotze, H. K. et al. Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proc. Natl Acad. Sci. USA 116, 12907–12912 (2019).
Google Scholar 

103.
Cheung, W. W. L. et al. Structural uncertainty in projecting global fisheries catches under climate change. Ecol. Model. 325, 57–66 (2016).
Google Scholar 

104.
Food and Agriculture Organization of the United Nations (FAO) The State of World Fisheries and Aquaculture 2018. Meeting the Sustainable Development Goals (Food and Agriculture Organization of the United Nations (FAO), 2018).

105.
Pauly, D. & Zeller, D. Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining. Nat. Commun. 7, 10244 (2016).
Google Scholar 

106.
Swartz, W., Sumaila, R. & Watson, R. Global ex-vessel fish price database revisited: a new approach for estimating ‘missing’ prices. Environ. Resour. Econ. 56, 467–480 (2013).
Google Scholar 

107.
Pauly, D., Christensen, V., Dalsgaard, J., Froese, R. & Torres, F. Fishing down marine food webs. Science 279, 860–863 (1998).
Google Scholar 

108.
Worm, B. et al. Rebuilding global fisheries. Science 325, 578–585 (2009).
Google Scholar 

109.
Costello, C. et al. Status and solutions for the world’s unassessed fisheries. Science 338, 517–520 (2012).
Google Scholar 

110.
Garcia, S. M. & Rosenberg, A. A. Food security and marine capture fisheries: characteristics, trends, drivers and future perspectives. Philos. Trans. R. Soc. B Biol. Sci. 365, 2869–2880 (2010).
Google Scholar 

111.
Anderson, S. C., Branch, T. A., Ricard, D. & Lotze, H. K. Assessing global marine fishery status with a revised dynamic catch-based method and stock-assessment reference points. ICES J. Mar. Sci. 69, 1491–1500 (2012).
Google Scholar 

112.
Costello, C. et al. Global fishery prospects under contrasting management regimes. Proc. Natl Acad. Sci. USA 113, 5125–5129 (2016).
Google Scholar 

113.
Thorson, J. T., Branch, T. A. & Jensen, O. P. Using model-based inference to evaluate global fisheries status from landings, location, and life history data. Can. J. Fish. Aquat. Sci. 69, 645–655 (2012).
Google Scholar 

114.
McOwen, C. J., Cheung, W. W. L., Rykaczewski, R. R., Watson, R. A. & Wood, L. J. Is fisheries production within large marine ecosystems determined by bottom-up or top-down forcing? Fish Fish. 16, 623–632 (2015).
Google Scholar 

115.
Stock, C. A. et al. Reconciling fisheries catch and ocean productivity. Proc. Natl Acad. Sci. USA 114, E1441–E1449 (2017).
Google Scholar 

116.
Free, C. M. et al. Impacts of historical warming on marine fisheries production. Science 363, 979–983 (2019).
Google Scholar 

117.
Cheung, W. W. L., Watson, R. & Pauly, D. Signature of ocean warming in global fisheries catch. Nature 497, 365–368 (2013).
Google Scholar 

118.
Cheung, W. W. L., Reygondeau, G. & Frölicher, T. L. Large benefits to marine fisheries of meeting the 1.5 C global warming target. Science 354, 1591–1594 (2016).
Google Scholar 

119.
Cheung, W. W. L., Jones, M. C., Reygondeau, G. & Frölicher, T. L. Opportunities for climate-risk reduction through effective fisheries management. Glob. Change Biol. 24, 5149–5163 (2018).
Google Scholar 

120.
Sumaila, U. R., Cheung, W. W. L., Lam, V. W. Y., Pauly, D. & Herrick, S. Climate change impacts on the biophysics and economics of world fisheries. Nat. Clim. Change 1, 449–456 (2011).
Google Scholar 

121.
Allison, E. H. et al. Vulnerability of national economies to the impacts of climate change on fisheries. Fish Fish. 10, 173–196 (2009).
Google Scholar 

122.
Bell, J. D. et al. Adaptations to maintain the contributions of small-scale fisheries to food security in the Pacific Islands. Mar. Policy 88, 303–314 (2018).
Google Scholar 

123.
The Pacific Community (SPC) Implications of Climate-driven Redistribution of Tuna for Pacific Island Economies (The Pacific Community (SPC), 2019).

124.
Blasiak, R. et al. Climate change and marine fisheries: least developed countries top global index of vulnerability. PLoS One 12, e0179632 (2017).
Google Scholar 

125.
Srinivasan, U., Cheung, W., Watson, R. & Sumaila, U. Food security implications of global marine catch losses due to overfishing. J. Bioeconomics 12, 183–200 (2010).
Google Scholar 

126.
Oyinlola, M. A., Reygondeau, G., Wabnitz, C. C. C. & Cheung, W. W. L. Projecting global mariculture diversity under climate change. Glob. Change Biol. 26, 2134–2148 (2020).
Google Scholar 

127.
Froehlich, H. E., Gentry, R. R. & Halpern, B. S. Global change in marine aquaculture production potential under climate change. Nat. Ecol. Evol. 2, 1745–1750 (2018).
Google Scholar 

128.
Porter, J. R. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Ch. 7 (eds Field, C. B. et al.) 485–533 (Cambridge Univ. Press, 2014).

129.
Gaines, S. D. et al. Improved fisheries management could offset many negative effects of climate change. Sci. Adv. 4, eaao1378 (2018).
Google Scholar 

130.
Smith, M. D. et al. Sustainability and global seafood. Science 327, 784–786 (2010).
Google Scholar 

131.
Asche, F., Bellemare, M. F., Roheim, C., Smith, M. D. & Tveteras, S. Fair enough? Food security and the international trade of seafood. World Dev. 67, 151–160 (2015).
Google Scholar 

132.
Kurien, J. Responsible Fish Trade and Food Security (Food and Agriculture Organization of the United Nations (FAO), 2005).

133.
Watson, R. A., Nichols, R., Lam, V. W. Y. & Sumaila, U. R. Global seafood trade flows and developing economies: Insights from linking trade and production. Mar. Policy 82, 41–49 (2017).
Google Scholar 

134.
Food and Agriculture Organization of the United Nations (FAO) FAO Yearbook of Fishery and Aquaculture Statistics (Food and Agriculture Organization of the United Nations (FAO), 2017).

135.
Gorez, B. West Africa: fishmeal, mealy deal. Samudra Rep. 78, 33–35 (2018).
Google Scholar 

136.
Corten, A., Braham, C.-B. & Sadegh, A. S. The development of a fishmeal industry in Mauritania and its impact on the regional stocks of sardinella and other small pelagics in Northwest Africa. Fish. Res. 186, 328–336 (2017).
Google Scholar 

137.
Merino, G., Barange, M., Mullon, C. & Rodwell, L. Impacts of global environmental change and aquaculture expansion on marine ecosystems. Glob. Environ. Change 20, 586–596 (2010).
Google Scholar 

138.
Naylor, R. L. et al. Feeding aquaculture in an era of finite resources. Proc. Natl Acad. Sci. USA 106, 15103–15110 (2009).
Google Scholar 

139.
Cashion, T., Le Manach, F., Zeller, D. & Pauly, D. Most fish destined for fishmeal production are food-grade fish. Fish Fish. 18, 837–844 (2017).
Google Scholar 

140.
New, M. B. & Wijkström, U. N. Use of fishmeal and fish oil in aquafeeds: further thoughts on the fishmeal trap. FAO Fisheries Circular No. 975 (2002).

141.
Jackson, A. & Shepherd, J. in Advancing the Aquaculture Agenda: Workshop Proceedings 331–343 (OECD, 2010).

142.
Kristofersson, D. & Anderson, J. L. Is there a relationship between fisheries and farming? Interdependence of fisheries, animal production and aquaculture. Mar. Policy 30, 721–725 (2006).
Google Scholar 

143.
Deutsch, L. et al. Feeding aquaculture growth through globalization: Exploitation of marine ecosystems for fishmeal. Glob. Environ. Change 17, 238–249 (2007).
Google Scholar 

144.
Mullon, C. et al. Modeling the global fishmeal and fish oil markets. Nat. Resour. Model. 22, 564–609 (2009).
Google Scholar 

145.
Merino, G. et al. Can marine fisheries and aquaculture meet fish demand from a growing human population in a changing climate? Glob. Environ. Change 22, 795–806 (2012).
Google Scholar 

146.
Liu, Y. & Sumaila, U. R. Can farmed salmon production keep growing? Mar. Policy 32, 497–501 (2008).
Google Scholar 

147.
Pinsky, M. L. et al. Preparing ocean governance for species on the move. Science 360, 1189–1191 (2018).
Google Scholar 

148.
Jacobs, A. China’s appetite pushes fisheries to the brink. New York Times (30 Apr 2017).

149.
Tickler, D., Meeuwig, J. J., Palomares, M.-L., Pauly, D. & Zeller, D. Far from home: Distance patterns of global fishing fleets. Sci. Adv. 4, eaar3279 (2018).
Google Scholar 

150.
Campling, L. Trade politics and the global production of canned tuna. Mar. Policy 69, 220–228 (2016).
Google Scholar 

151.
Eurofish. Overview of the Spanish fisheries and aquaculture sector. https://www.eurofish.dk/spain (2019).

152.
Arrizabalaga, H. et al. Global habitat preferences of commercially valuable tuna. Deep Sea Res. Part II Top. Stud. Oceanogr. 113, 102–112 (2015).
Google Scholar 

153.
Erauskin-Extramiana, M. et al. Large-scale distribution of tuna species in a warming ocean. Glob. Change Biol. 25, 2043–2060 (2019).
Google Scholar 

154.
FFA and SPC. Future of Fisheries: A Regional Roadmap for Sustainable Pacific Fisheries (FFA and SPC, 2015).

155.
Heltberg, R., Siegel, P. B. & Jorgensen, S. L. Addressing human vulnerability to climate change: toward a ‘no-regrets’ approach. Glob. Environ. Change 19, 89–99 (2009).
Google Scholar 

156.
Brouwer, S. et al. The Western and Central Pacific Tuna Fishery: 2018 Overview and Status of Stocks (Pacific Community, 2019).

157.
Bell, J. D. et al. Diversifying the use of tuna to improve food security and public health in Pacific Island countries and territories. Mar. Policy 51, 584–591 (2015).
Google Scholar 

158.
Senina, I. et al. Predicting skipjack tuna dynamics and effects of climate change using SEAPODYM with fishing and tagging data. Scientific Committee Twelfth Regular Session, Western and Central Pacific Fisheries Commission 1–70 (2016).

159.
Robinson, M. Climate Justice: Hope, Resilience, and the Fight for a Sustainable Future (Bloomsbury Publishing, 2018).

160.
United Nations. Transforming Our World: the 2030 agenda for sustainable development https://doi.org/10.1891/9780826190123.ap02 (2015).

161.
Pecl, G. T. et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).
Google Scholar 

162.
Singh, G. G. et al. Climate impacts on the ocean are making the Sustainable Development Goals a moving target travelling away from us. People Nat. 1, 317–330 (2019).
Google Scholar 

163.
Guillaumont, P. Assessing the economic vulnerability of small island developing states and the least developed countries. J. Dev. Stud. 46, 828–854 (2010).
Google Scholar 

164.
Narayan, S. et al. The effectiveness, costs and coastal protection benefits of natural and nature-based defences. PLoS One 11, e0154735 (2016).
Google Scholar 

165.
Moosavi, S. Ecological coastal protection: pathways to living shorelines. Procedia Eng. 196, 930–938 (2017).
Google Scholar 

166.
Mutombo, K. & Ölçer, A. A three-tier framework for port infrastructure adaptation to climate change: balancing breadth and depth of knowledge. Ocean Yearb. Online 30, 564–577 (2016).
Google Scholar 

167.
Forzieri, G. et al. Escalating impacts of climate extremes on critical infrastructures in Europe. Glob. Environ. Change 48, 97–107 (2018).
Google Scholar 

168.
Beiler, M. O., Marroquin, L. & McNeil, S. State-of-the-practice assessment of climate change adaptation practices across metropolitan planning organizations pre-and post-Hurricane Sandy. Transp. Res. Part A Policy Pract. 88, 163–174 (2016).
Google Scholar 

169.
Thorne, J. H. et al. The impact of climate change uncertainty on California’s vegetation and adaptation management. Ecosphere 8, e02021 (2017).
Google Scholar 

170.
Ziervogel, G. & Ericksen, P. J. Adapting to climate change to sustain food security. Wiley Interdiscip. Rev. Clim. Change 1, 525–540 (2010).
Google Scholar 

171.
Heenan, A. et al. A climate-informed, ecosystem approach to fisheries management. Mar. Policy 57, 182–192 (2015).
Google Scholar 

172.
Poulain, F., Himes-Cornell, A. & Shelton, C. in Impacts of Climate Change on Fisheries and Aquaculture. Synthesis of Current Knowledge, Adaptation and Mitigation Options FAO Fisheries and Aquaculture Technical Paper 627 Ch. 25 535–566 (Food and Agriculture Organization of the United Nations (FAO), 2018).

173.
Bell, J. et al. Impacts and effects of ocean warming on the contributions of fisheries and aquaculture to food security (IUCN, 2016).

174.
Cochrane, K. L., Andrew, N. L. & Parma, A. M. Primary fisheries management: a minimum requirement for provision of sustainable human benefits in small-scale fisheries. Fish Fish. 12, 275–288 (2011).
Google Scholar 

175.
Free, C. M. et al. Realistic fisheries management reforms could mitigate the impacts of climate change in most countries. PLoS One 15, e0224347 (2020).
Google Scholar 

176.
Armitage, D. Adaptive capacity and community-based natural resource management. Environ. Manage. 35, 703–715 (2005).
Google Scholar 

177.
MECM/MFMR. Solomon Islands National Plan of Action. Coral Triangle Initiative on Coral Reefs, Fisheries and Food Security (Solomon Islands Government, 2010).

178.
Bell, J. D. et al. Optimising the use of nearshore fish aggregating devices for food security in the Pacific Islands. Mar. Policy 56, 98–105 (2015).
Google Scholar 

179.
Tilley, A. et al. Nearshore fish aggregating devices show positive outcomes for sustainable fisheries development in Timor-Leste. Front. Mar. Sci. 6, 487 (2019).
Google Scholar 

180.
Mills, D. J. et al. Developing Timor-Leste’s Coastal Economy: Assessing Potential Climate Change Impacts and Adaptation Options. Final Report to the Australian Government Coral Triangle Initiative on Coral Reefs, Fisheries and Food Security National Initiative (WorldFish, 2013).

181.
Pomeroy, R. S. Community-based and co-management institutions for sustainable coastal fisheries management in Southeast Asia. Ocean Coast. Manag. 27, 143–162 (1995).
Google Scholar 

182.
Foale, S., Cohen, P., Januchowski-Hartley, S., Wenger, A. & Macintyre, M. Tenure and taboos: origins and implications for fisheries in the Pacific. Fish Fish. 12, 357–369 (2011).
Google Scholar 

183.
Tompkins, E. L. & Adger, W. N. Does adaptive management of natural resources enhance resilience to climate change? Ecol. Soc. 9, 10 (2004).
Google Scholar 

184.
Biggs, R. et al. Toward principles for enhancing the resilience of ecosystem services. Annu. Rev. Environ. Resour. 37, 421–448 (2012).
Google Scholar 

185.
Cohen, P. J. & Foale, S. J. Sustaining small-scale fisheries with periodically harvested marine reserves. Mar. Policy 37, 278–287 (2013).
Google Scholar 

186.
Carvalho, P. G. et al. Optimized fishing through periodically harvested closures. J. Appl. Ecol. 56, 1927–1936 (2019).
Google Scholar 

187.
Cinner, J. E. et al. Evaluating social and ecological vulnerability of coral reef fisheries to climate change. PLoS One 8, e74321 (2013).
Google Scholar 

188.
Ford, J. D. et al. Including indigenous knowledge and experience in IPCC assessment reports. Nat. Clim. Change 6, 349–353 (2016).
Google Scholar 

189.
McNamara, K. E. & Westoby, R. Local knowledge and climate change adaptation on Erub Island, Torres Strait. Local Environ. 16, 887–901 (2011).
Google Scholar 

190.
Miller, D. D., Ota, Y., Sumaila, U. R., Cisneros-Montemayor, A. M. & Cheung, W. W. L. Adaptation strategies to climate change in marine systems. Glob. Change Biol. 24, e1–e14 (2018).
Google Scholar 

191.
Weeks, R. & Jupiter, S. D. Adaptive comanagement of a marine protected area network in Fiji. Conserv. Biol. 27, 1234–1244 (2013).
Google Scholar 

192.
Ogier, E. M. et al. Fisheries management approaches as platforms for climate change adaptation: comparing theory and practice in Australian fisheries. Mar. Policy 71, 82–93 (2016).
Google Scholar 

193.
Bruno, J. F., Côté, I. M. & Toth, L. T. Climate change, coral loss, and the curious case of the parrotfish paradigm: why don’t marine protected areas improve reef resilience? Annu. Rev. Mar. Sci. 11, 307–334 (2019).
Google Scholar 

194.
Oremus, K. L. et al. Governance challenges for tropical nations losing fish species due to climate change. Nat. Sustain. 3, 277–280 (2020).
Google Scholar 

195.
Mendenhall, E. et al. Climate change increases the risk of fisheries conflict. Mar. Policy 117, 103954 (2020).
Google Scholar 

196.
Moore, B. R. et al. Defining the stock structures of key commercial tunas in the Pacific Ocean I: current knowledge and main uncertainties. Fish. Res. https://doi.org/10.1016/j.fishres.2020.105525 (2020).

197.
Moore, B. R. et al. Defining the stock structures of key commercial tunas in the Pacific Ocean II: Sampling considerations and future directions. Fish. Res. https://doi.org/10.1016/j.fishres.2020.105524 (2020).

198.
Gattuso, J.-P. et al. Ocean solutions to address climate change and its effects on marine ecosystems. Front. Mar. Sci. 5, 337 (2018).
Google Scholar 

199.
Sumaila, U. R. et al. Benefits of the Paris Agreement to ocean life, economies, and people. Sci. Adv. 5, eaau3855 (2019).
Google Scholar 

200.
Gallo, N. D., Victor, D. G. & Levin, L. A. Ocean commitments under the Paris Agreement. Nat. Clim. Change 7, 833–838 (2017).
Google Scholar 

201.
Mcleod, E. et al. A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front. Ecol. Environ. 9, 552–560 (2011).
Google Scholar 

202.
Herr, D. & Landis, E. Coastal Blue Carbon Ecosystems. Opportunities for Nationally Determined Contributions. Policy Brief (IUCN, 2016).

203.
Goldstein, A. et al. Protecting irrecoverable carbon in Earth’s ecosystems. Nat. Clim. Change 10, 287–295 (2020).
Google Scholar 

204.
Pendleton, L. et al. Estimating global “blue carbon” emissions from conversion and degradation of vegetated coastal ecosystems. PLoS One 7, e43542 (2012).
Google Scholar 

205.
Zarate-Barrera, T. G. & Maldonado, J. H. Valuing blue carbon: carbon sequestration benefits provided by the marine protected areas in Colombia. PLoS One 10, e0126627 (2015).
Google Scholar 

206.
Wylie, L., Sutton-Grier, A. E. & Moore, A. Keys to successful blue carbon projects: lessons learned from global case studies. Mar. Policy 65, 76–84 (2016).
Google Scholar 

207.
Locatelli, T. et al. Turning the tide: how blue carbon and payments for ecosystem services (PES) might help save mangrove forests. Ambio 43, 981–995 (2014).
Google Scholar 

208.
Barbesgaard, M. C. Blue carbon: ocean grabbing in disguise? Transnational Institute https://www.tni.org/en/publication/blue-carbon-ocean-grabbing-in-disguise (2016).

209.
Sharp, M. The benefits of fish aggregating devices in the Pacific. SPC Fish. Newsl. 135, 28–36 (2011).
Google Scholar 

210.
Grafton, R. Q. Adaptation to climate change in marine capture fisheries. Mar. Policy 34, 606–615 (2010).
Google Scholar 

211.
Kurien, J. Voluntary guidelines for securing sustainable small-scale fisheries in the context of food security and poverty eradication: summary (Food and Agriculture Organization of the United Nations (FAO), 2015).

212.
Castree, N. et al. Changing the intellectual climate. Nat. Clim. Change 4, 763–768 (2014).
Google Scholar 

213.
Allison, E. H. & Bassett, H. R. Climate change in the oceans: Human impacts and responses. Science 350, 778–782 (2015).
Google Scholar 

214.
Bobrowsky, P., Cronin, V. S., Di Capua, G., Kieffer, S. W. & Peppoloni, S. 11. The emerging field of geoethics. Sci. Integr. Ethics Geosci. 73, 175 (2017).
Google Scholar 

215.
Bohle, M. One realm: thinking geoethically and guiding small-scale fisheries? Eur. J. Dev. Res. 31, 253–270 (2019).
Google Scholar 

216.
UNEP-WCMC, WorldFish Centre, WRI & TNC. Global distribution of warm-water coral reefs, compiled from multiple sources including the Millennium Coral Reef Mapping Project. Version 4.0. Includes contributions from IMaRS-USF and IRD (2005), IMaRS-USF (2005) and Spalding et al. (2001) (UN Environment World Conservation Monitoring Centre, 2018).

217.
UNEP-WCMC & Short, F. T. Global distribution of seagrasses (version 5.0). Fourth update to the data layer used in Green and Short (2003) (UNEP World Conservation Monitoring Centre, 2017).

218.
Giri, C. et al. Status and distribution of mangrove forests of the world using earth observation satellite data (version 1.3, updated by UNEP-WCMC). Glob. Ecol. Biogeogr. 20, 154–159 (2011).
Google Scholar 

219.
Mcowen, C. J. et al. A global map of saltmarshes. Biodivers. Data J. 5, e11764 (2017).
Google Scholar 

220.
Lehodey, P. et al. in Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change (eds Bell, J. D., Johnson, J. E. & Hobday, A. J.) 433–492 (Secretariat of the Pacific Community, 2011).

221.
Lehodey, P. et al. Modelling the impact of climate change including ocean acidification on Pacific yellowfin tuna. Scientific Committee Thirteenth Regular Session, Western and Central Pacific Fisheries Commission 1–25 (2017).

222.
Senina, I. et al. Impact of climate change on tropical Pacific tuna and their fisheries in Pacific Islands waters and high seas areas. Scientific Committee Fourteenth Regular Session, Western and Central Pacific Fisheries Commission 1–43 (2018).

223.
Bell, J. D. et al. Mixed responses of tropical Pacific fisheries and aquaculture to climate change. Nat. Clim. Change 3, 591–599 (2013).
Google Scholar 

224.
Bell, J. D. et al. in Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change (eds Bell, J. D., Johnson, J. E. & Hobday, A. J.) 733–801 (Secretariat of the Pacific Community, 2011).

225.
Bell, J. D. et al. in Impacts of Climate Change on Fisheries and Aquaculture. Synthesis of Current Knowledge, Adaptation and Mitigation Options FAO Fisheries and Aquaculture Technical Paper 627 Ch. 14 305–324 (Food and Agriculture Organization of the United Nations (FAO), 2018).

226.
Scott, F., Scott, R., Yao, N., Pilling, G. M. & Hampton, J. Considering uncertainty when testing and monitoring WCPFC harvest strategies. Scientific Committee Fifteenth Regular Session, Western Central Pacific Fisheries Commission 1–23 (2019).

227.
Pratchett, M. S. et al. Vulnerabilty of coastal fisheries in the tropical Pacific to climate change (eds Bell, J. D., Johnson, J. E. & Hobday, A. J.) in Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change 493–576 (Secretariat of the Pacific Community, 2011).

228.
Gasalla, M. A., Abdallah, P. R. & Lemos, D. in Climate Change Impacts on Fisheries and Aquaculture. A Global Analysis. Vol. 1 (eds Philips, B. F. & Pérez-Ramírez, M.) 455–477 (Wiley, 2017).

229.
Popova, E. et al. From global to regional and back again: common climate stressors of marine ecosystems relevant for adaptation across five ocean warming hotspots. Glob. Change Biol. 22, 2038–2053 (2016).
Google Scholar 

230.
Schulz, C. et al. Physical, ecological and human dimensions of environmental change in Brazil’s Pantanal wetland: synthesis and research agenda. Sci. Total Environ. 687, 1011–1027 (2019).
Google Scholar 

231.
Barros, D. F. & Albernaz, A. L. M. Possible impacts of climate change on wetlands and its biota in the Brazilian Amazon. Braz. J. Biol. 74, 810–820 (2014).
Google Scholar 

232.
Johnson, J. E. et al. Climate change adaptation: vulnerability and challenges facing small-scale fisheries on small islands. FAO Fish. Aquacult. Proc. 61, 65–80 (2019).
Google Scholar 

233.
Martins, I. M. & Gasalla, M. A. Perceptions of climate and ocean change impacting the resources and livelihood of small-scale fishers in the South Brazil Bight. Clim. Change 147, 441–456 (2018).
Google Scholar 

234.
Martins, I. M., Gammage, L. C., Jarre, A. & Gasalla, M. A. Different but similar? Exploring vulnerability to climate change in Brazilian and South African small-scale fishing communities. Hum. Ecol. 47, 515–526 (2019).
Google Scholar 

235.
Gasalla, M. A. Six decades of change in the South Brazil Bight Ecosystem in Proc. 3rd GLOBEC Open Science Meeting: From Ecosystem Function to Ecosystem Prediction (2008).

236.
Dahlet, L. I., Downey-Breedt, N., Arce, G., Sauer, W. H. H. & Gasalla, M. A. Comparative study of skipjack tuna Katsuwonus pelamis (Scombridae) fishery stocks from the South Atlantic and western Indian oceans. Sci. Mar. 83, 19–30 (2019).
Google Scholar 

237.
Araújo, F. G., Teixeira, T. P., Guedes, A. P. P., de Azevedo, M. C. C. & Pessanha, A. L. M. Shifts in the abundance and distribution of shallow water fish fauna on the southeastern Brazilian coast: a response to climate change. Hydrobiologia 814, 205–218 (2018).
Google Scholar 

238.
Gasalla, M. A. An overview of climate change effects in South Brazil Bight fisheries in Proc. 6th World Fisheries Congress (2012).

239.
Santos, L. C. M., Gasalla, M. A., Dahdouh-Guebas, F. & Bitencourt, M. D. Socio-ecological assessment for environmental planning in coastal fishery areas: a case study in Brazilian mangroves. Ocean Coast. Manag. 138, 60–69 (2017).
Google Scholar 

240.
Zou, D. & Gao, K. in Seaweeds and Their Role in Globally Changing Environments (eds Seckbach, J., Einav, R. & Israel, A.) 115–126 (Springer, 2010).

241.
Ramaglia, A. C., de Castro, L. M. & Augusto, A. Effects of ocean acidification and salinity variations on the physiology of osmoregulating and osmoconforming crustaceans. J. Comp. Physiol. B 188, 729–738 (2018).
Google Scholar 

242.
Freduah, G., Fidelman, P. & Smith, T. F. The impacts of environmental and socio-economic stressors on small scale fisheries and livelihoods of fishers in Ghana. Appl. Geogr. 89, 1–11 (2017).
Google Scholar 

243.
Bunce, M., Rosendo, S. & Brown, K. Perceptions of climate change, multiple stressors and livelihoods on marginal African coasts. Environ. Dev. Sustain. 12, 407–440 (2010).
Google Scholar 

244.
Burke, L.M., Reytar, K., Spalding, M. & Perry, A. Reefs at risk revisited: World Resources Institute. (2017).

245.
Roberts, C. M. et al. Marine biodiversity hotspots and conservation priorities for tropical reefs. Science 295, 1280–1284 (2002).
Google Scholar 

246.
Lam, V. W. Y., Cheung, W. W. L., Swartz, W. & Sumaila, U. R. Climate change impacts on fisheries in West Africa: implications for economic, food and nutritional security. Afr. J. Mar. Sci. 34, 103–117 (2012).
Google Scholar 

247.
Barange, M. et al. Impacts of climate change on marine ecosystem production in societies dependent on fisheries. Nat. Clim. Change 4, 211–216 (2014).
Google Scholar 

248.
Blanchard, J. L. et al. Potential consequences of climate change for primary production and fish production in large marine ecosystems. Philos. Trans. R. Soc. B Biol. Sci. 367, 2979–2989 (2012).
Google Scholar 

249.
Belhabib, D., Lam, V. W. Y. & Cheung, W. W. L. Overview of West African fisheries under climate change: impacts, vulnerabilities and adaptive responses of the artisanal and industrial sectors. Mar. Policy 71, 15–28 (2016).
Google Scholar  More

1.
Sears, M. W., Raskin, E. & Angilletta, M. J. Jr. The world is not flat: defining relevant thermal landscapes in the context of climate change. Integr. Comp. Biol. 51, 666–675 (2011).
PubMed  Google Scholar 
2.
du Plessis, K. L., Martin, R. O., Hockey, P. A. R., Cunningham, S. J. & Ridley, A. R. The costs of keeping cool in a warming world: implications of high temperatures for foraging, thermoregulation and body condition of an arid-zone bird. Glob. Change Biol. 18, 3063–3070 (2012).
ADS  Google Scholar 

3.
Araújo, M. B. et al. Heat freezes niche evolution. Ecol. Lett. 16, 1206–1219 (2013).
PubMed  Google Scholar 

4.
Speakman, J. R. & Król, E. Maximal heat dissipation capacity and hyperthermia risk: neglected key factors in the ecology of endotherms. J. Anim. Ecol. 79, 726–746 (2010).
PubMed  Google Scholar 

5.
Daghir, N. J. Poultry production in hot climates 2nd edn. (CAB International, Wallingford, 2008).
Google Scholar 

6.
Nyoni, N. M. B., Grab, S. & Archer, E. R. M. Heat stress and chickens: climate risk effects on rural poultry farming in low-income countries. Clim. Dev. 11, 83–90. https://doi.org/10.1080/17565529.2018.1442792 (2018).
Article  Google Scholar 

7.
Laszlo, A. The effects of hyperthermia on mammalian cell structure and function. Cell Prolif. 25, 59–87 (1992).
CAS  PubMed  Google Scholar 

8.
Roti Roti, J. L. Cellular responses to hyperthermia (40–46 C): Cell killing and molecular events. Int. J. Hyperthermia 24, 3–15 (2008).
ADS  PubMed  Google Scholar 

9.
Feder, M. E. & Hofmann, G. E. Heat-shock proteins, molecular chaperones, and the stress response: evolutionary and ecological physiology. Annu. Rev. Physiol. 61, 243–282 (1999).
CAS  PubMed  Google Scholar 

10.
Hochachka, P. W. & Somero, G. N. Biochemical Adaptation (Princeton University Press, Princeton, 1984).
Google Scholar 

11.
Pörtner, H. Climate change and temperature-dependent biogeography: oxygen limitation of thermal tolerance in animals. Naturwissenschaften 88, 137–146 (2001).
ADS  PubMed  Google Scholar 

12.
Pörtner, H.-O. Oxygen-and capacity-limitation of thermal tolerance: a matrix for integrating climate-related stressor effects in marine ecosystems. J. Exp. Biol. 213, 881–893 (2010).
PubMed  Google Scholar 

13.
Clusella-Trullas, S., Blackburn, T. M. & Chown, S. L. Climatic predictors of temperature performance curve parameters in ectotherms imply complex responses to climate change. Am. Nat. 177, 738–751 (2011).
PubMed  Google Scholar 

14.
McKechnie, A. E. & Wolf, B. O. The physiology of heat tolerance in small endotherms. Physiology 34, 302–313 (2019).
CAS  PubMed  Google Scholar 

15.
Arad, Z. & Marder, J. Strain differences in heat resistance to acute heat stress, between the bedouin desert fowl, the white leghorn and their crossbreeds. Comp. Biochem. Physiol. A 72, 191–193 (1982).
Google Scholar 

16.
Randall, W. C. Factors influencing the temperature regulation of birds. Am. J. Physiol. 139, 56–63 (1943).
Google Scholar 

17.
Tieleman, B. I., Williams, J. B., LaCroix, F. & Paillat, P. Physiological responses of Houbara bustards to high ambient temperatures. J. Exp. Biol. 205, 503–511 (2002).
PubMed  Google Scholar 

18.
Chappell, M. A. & Bartholomew, G. A. Activity and thermoregulation of the antelope ground squirrel Ammospermophilus leucurus in winter and summer. Physiol. Zool. 54, 215–223 (1981).
Google Scholar 

19.
Lovegrove, B. G., Heldmaier, G. & Ruf, T. Perspectives of endothermy revisited: the endothermic temperature range. J. Therm. Biol 16, 185–197 (1991).
Google Scholar 

20.
Cory Toussaint, D. & McKechnie, A. E. Interspecific variation in thermoregulation among three sympatric bats inhabiting a hot, semi-arid environment. J. Comp. Physiol. B 182, 1129–1140 (2012).
PubMed  Google Scholar 

21.
Dawson, W. R. In University of California Publications in Zoology Vol. 59 (eds Bartholomew, G. A. et al.) 81–123 (University of California Press, California, 1954).
Google Scholar 

22.
Paulissen, M. A. Ontogenetic comparison of body temperature selection and thermal tolerance of Cnemidophorus sexlineatus. J. Herpetol. 22, 473–476 (1988).
Google Scholar 

23.
Weathers, W. W. Energetics and thermoregulation by small passerines of the humid, lowland tropics. Auk 114, 341–353 (1997).
Google Scholar 

24.
Southwick, E. E. Remote sensing of body temperature in a captive 25-g bird. Condor 75, 464–466 (1973).
Google Scholar 

25.
Elliott, C. C. H. In Quelea quelea: Africa’s bird pest (eds Bruggers, R. L. & Elliott, C. C. H.) (Oxford University Press, Oxford, 1989).
Google Scholar 

26.
Craig, A. J. F. K. In Roberts birds of southern Africa (eds Hockey, P. A. R. et al.) 1025–1026 (The Trustees of the John Voelcker Bird Book Fund, Cape Town, 2005).
Google Scholar 

27.
Whitfield, M. C., Smit, B., McKechnie, A. E. & Wolf, B. O. Avian thermoregulation in the heat: scaling of heat tolerance and evaporative cooling capacity in three southern African arid-zone passerines. J. Exp. Biol. 218, 1705–1714 (2015).
PubMed  Google Scholar 

28.
McKechnie, A. E. et al. Avian thermoregulation in the heat: efficient evaporative cooling allows for extreme heat tolerance in four southern Hemisphere columbids. J. Exp. Biol. 219, 2145–2155 (2016).
PubMed  Google Scholar 

29.
Smith, E. K., O’Neill, J. J., Gerson, A. R., McKechnie, A. E. & Wolf, B. O. Avian thermoregulation in the heat: resting metabolism, evaporative cooling and heat tolerance in Sonoran Desert songbirds. J. Exp. Biol. 220, 3290–3300 (2017).
PubMed  Google Scholar 

30.
Smit, B. et al. Avian thermoregulation in the heat: phylogenetic variation among avian orders in evaporative cooling capacity and heat tolerance. J. Exp. Biol. 221, jeb174870 (2018).
PubMed  Google Scholar 

31.
Karasov, W. H. In Studies in Avian Biology (eds Morrison, M. L. et al.) 391–415 (Cooper Ornithological Society, California, 1990).
Google Scholar 

32.
Swanson, D. L., Drymalski, M. W. & Brown, J. R. Sliding vs static cold exposure and the measurement of summit metabolism in birds. J. Therm. Biol 21, 221–226 (1996).
Google Scholar 

33.
Kemp, R. & McKechnie, A. E. Thermal physiology of a range-restricted desert lark. J. Comp. Physiol. B 189, 131–141. https://doi.org/10.1007/s00360-018-1190-1 (2019).
Article  PubMed  Google Scholar 

34.
Lighton, J. R. B. Measuring Metabolic Rates: A Manual for Scientists (Oxford University Press, Oxford, 2008).
Google Scholar 

35.
Walsberg, G. E. & Wolf, B. O. Variation in the respirometry quotient of birds and implications for indirect calorimetry using measurements of carbon dioxide production. J. Exp. Biol. 198, 213–219 (1995).
CAS  PubMed  Google Scholar 

36.
Tracy, C. R., Welch, W. R., Pinshow, B. & Porter, W. P. Properties of air: a manual for use in biophysical ecology. 4th Ed. The University of Wisconsin Laboratory for Biophysical Ecology: Technical Report (2010).

37.
R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2019).

38.
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: Linear and Nonlinear Mixed Effects Models. R Package Version 3. 57. (2009).

39.
Muggeo, V. M. R. Segmented: an R package to fit regression models with broken-line relationships. R News 8(1), 20–25 (2008).
Google Scholar 

40.
McKechnie, A. E. et al. Avian thermoregulation in the heat: evaporative cooling in five Australian passerines reveals within-order biogeographic variation in heat tolerance. J. Exp. Biol. 220, 2436–2444 (2017).
PubMed  Google Scholar 

41.
O’Connor, R. S., Wolf, B. O., Brigham, R. M. & McKechnie, A. E. Avian thermoregulation in the heat: efficient evaporative cooling in two southern African nightjars. J Comp Physiol B 187, 477–491 (2017).
PubMed  Google Scholar 

42.
Hoffmann, A. A., Chown, S. L. & Clusella-Trullas, S. Upper thermal limits in terrestrial ectotherms: how constrained are they? Funct. Ecol. 27, 934–949 (2013).
Google Scholar 

43.
Tieleman, B. I., Williams, J. B. & Bloomer, P. Adaptation of metabolic rate and evaporative water loss along an aridity gradient. Proc. R. Soc. Lond. 270, 207–214 (2003).
Google Scholar 

44.
Xie, S., Tearle, R. & McWhorter, T. J. Heat shock protein expression is upregulated after acute heat exposure in three species of Australian desert birds. Avian Biol. Res. 11, 263–273 (2018).
Google Scholar 

45.
Czenze, Z. J. et al. Regularly-drinking desert birds have greater evaporative cooling capacity and higher heat tolerance limits than non-drinking species. Funct. Ecol. https://doi.org/10.1111/1365-2435.13573 (2020).
Article  Google Scholar 

46.
Midtgård, U. Scaling of the brain and the eye cooling system in birds: a morphometric analysis of the rete ophthalmicum. J. Exp. Zool. 225, 197–207 (1983).
PubMed  Google Scholar 

47.
Kilgore, D. L., Bernstein, M. H. & Hudson, D. M. Brain temperatures in birds. J Comp Physiol 110, 209–215 (1976).
Google Scholar 

48.
Bernstein, M. H., Curtis, M. B. & Hudson, D. M. Independence of brain and body temperatures in flying American kestrels, Falco sparverius. Am. J. Physiol. 237, R58–R62 (1979).
CAS  PubMed  Google Scholar 

49.
Kregel, K. C. Invited review: heat shock proteins: modifying factors in physiological stress responses and acquired thermotolerance. J. Appl. Physiol. 92, 2177–2186 (2002).
CAS  PubMed  Google Scholar 

50.
McKechnie, A. E. et al. Avian thermoregulation in the heat: evaporative cooling capacity in an archetypal desert specialist, Burchell’s sandgrouse (Pterocles burchelli). J. Exp. Biol. 219, 2137–2144 (2016).
PubMed  Google Scholar 

51.
Talbot, W. A., McWhorter, T. J., Gerson, A. R., McKechnie, A. E. & Wolf, B. O. Avian thermoregulation in the heat: evaporative cooling capacity of arid-zone Caprimulgiformes from two continents. J. Exp. Biol. 220, 3488–3498 (2017).
PubMed  Google Scholar 

52.
McWhorter, T. J. et al. Avian thermoregulation in the heat: evaporative cooling capacity and thermal tolerance in two Australian parrots. J. Exp. Biol. 221, jeb168930 (2018).
PubMed  Google Scholar 

53.
Talbot, W. A., Gerson, A. R., Smith, E. K., McKechnie, A. E. & Wolf, B. O. Avian thermoregulation in the heat: metabolism, evaporative cooling and gular flutter in two small owls. J. Exp. Biol. 221, jeb171108 (2018).
PubMed  Google Scholar 

54.
Smith, E. K., O’Neill, J., Gerson, A. R. & Wolf, B. O. Avian thermoregulation in the heat: resting metabolism, evaporative cooling and heat tolerance in Sonoran Desert doves and quail. J. Exp. Biol. 218, 3636–3646 (2015).
PubMed  Google Scholar  More

1.
El-Naggar, M. Y. et al. Electrical transport along bacterial nanowires from Shewanella oneidensis MR-1. Proc. Natl. Acad. Sci. USA 107, 18127–18131 (2010).
ADS  CAS  PubMed  Google Scholar 
2.
Du Toit, A. Exporting electrons. Nat. Rev. Microbiol. 16, 657 (2018).
PubMed  Google Scholar 

3.
Lovley, D. R. Microbial fuel cells: novel microbial physiologies and engineering approaches. Curr. Opin. Biotechnol. 17, 327–332 (2006).
CAS  PubMed  Google Scholar 

4.
Myers, J. M. & Myers, C. R. Role for outer membrane cytochromes OmcA and OmcB of Shewanella putrefaciens MR-1 in reduction of manganese dioxide. Appl. Environ. Microbiol. 67, 260–269 (2001).
CAS  PubMed  PubMed Central  Google Scholar 

5.
Bond, D. R. & Lovley, D. R. Electricity production by Geobacter sulfurreducens attached to electrodes. Appl. Environ. Microbiol. 69, 1548–1555 (2003).
CAS  PubMed  PubMed Central  Google Scholar 

6.
Rabaey, K., Boon, N., Siciliano, S. D., Verhaege, M. & Verstraete, W. Biofuel cells select for microbial consortia that self-mediate electron transfer. Appl. Environ. Microbiol. 70, 5373–5382 (2004).
CAS  PubMed  PubMed Central  Google Scholar 

7.
Rabaey, K., Boon, N., Höfte, M. & Verstraete, W. Microbial phenazine production enhances electron transfer in biofuel cells. Environ. Sci. Technol. 39, 3401–3408 (2005).
ADS  CAS  PubMed  Google Scholar 

8.
Potter, M. C. Electrical effects accompanying the decomposition of organic compounds. Proc. R. Soc. B Biol. Sci. 84, 260–276 (1911).
ADS  Google Scholar 

9.
Logan, B. E. & Regan, J. M. Microbial fuel cells—challenges and applications. Environ. Sci. Technol. 40, 5172–5180 (2006).
ADS  CAS  PubMed  Google Scholar 

10.
Trapero, J. R., Horcajada, L., Linares, J. J. & Lobato, J. Is microbial fuel cell technology ready? An economic answer towards industrial commercialization. Appl. Energy 185, 698–707 (2017).
CAS  Google Scholar 

11.
Reimers, C. E., Tender, L. M., Fertig, S. & Wang, W. Harvesting energy from the marine sediment−water interface. Environ. Sci. Technol. 35, 192–195 (2001).
ADS  CAS  PubMed  Google Scholar 

12.
Tender, L. M. et al. Harnessing microbially generated power on the seafloor. Nat. Biotechnol. 20, 821–825 (2002).
CAS  PubMed  Google Scholar 

13.
Kubota, K. et al. Operation of sediment microbial fuel cells in Tokyo Bay, an extremely eutrophicated coastal sea. Bioresour. Technol. Rep. 6, 39–45 (2019).
Google Scholar 

14.
Chun, C. L., Payne, R. B., Sowers, K. R. & May, H. D. Electrical stimulation of microbial PCB degradation in sediment. Water Res. 47, 141–152 (2013).
CAS  PubMed  Google Scholar 

15.
Gajda, I., Greenman, J. & Ieropoulos, I. A. Recent advancements in real-world microbial fuel cell applications. Curr. Opin. Electrochem. 11, 78–83 (2018).
CAS  PubMed  PubMed Central  Google Scholar 

16.
Bond, D. R., Holmes, D. E., Tender, L. M. & Lovley, D. R. Electrode-reducing microorganisms that harvest energy from marine sediments. Science 295, 483–485 (2002).
ADS  CAS  PubMed  Google Scholar 

17.
Froelich, P. N. et al. Early oxidation of organic matter in pelagic sediments of the eastern equatorial Atlantic: suboxic diagenesis. Geochim. Cosmochim. Acta 43, 1075–1090 (1979).
ADS  CAS  Google Scholar 

18.
Hasvold, Ø et al. Sea-water battery for subsea control systems. J. Power Sources 65, 253–261 (1997).
ADS  CAS  Google Scholar 

19.
Li, H. et al. Pilot-scale benthic microbial electrochemical system (BMES) for the bioremediation of polluted river sediment. J. Power Sources 356, 430–437 (2017).
ADS  CAS  Google Scholar 

20.
Sherafatmand, M. & Ng, H. Y. Using sediment microbial fuel cells (SMFCs) for bioremediation of polycyclic aromatic hydrocarbons (PAHs). Bioresour. Technol. 195, 122–130 (2015).
CAS  PubMed  Google Scholar 

21.
Sajana, T. K., Ghangrekar, M. M. & Mitra, A. Application of sediment microbial fuel cell for in situ reclamation of aquaculture pond water quality. Aquac. Eng. 57, 101–107 (2013).
Google Scholar 

22.
Sajana, T. K., Ghangrekar, M. M. & Mitra, A. Effect of operating parameters on the performance of sediment microbial fuel cell treating aquaculture water. Aquac. Eng. 61, 17–26 (2014).
Google Scholar 

23.
Giles, H. Using Bayesian networks to examine consistent trends in fish farm benthic impact studies. Aquaculture 274, 181–195 (2008).
Google Scholar 

24.
Karakassis, I., Tsapakis, M., Hatziyanni, E., Papadopoulou, K. N. & Plaiti, W. Impact of cage farming of fish on the seabed in three Mediterranean coastal areas. ICES J. Mar. Sci. 57, 1462–1471 (2000).
Google Scholar 

25.
Nøhr Glud, R., Gundersen, J. K., Barker Jørgensen, B., Revsbech, N. P. & Schulz, H. D. Diffusive and total oxygen uptake of deep-sea sediments in the eastern South Atlantic Ocean: in situ and laboratory measurements. Deep. Res. I 41, 1767–1788 (1994).
Google Scholar 

26.
Van Duyl, F. C., Kop, A. J., Kok, A. & Sandee, A. J. J. The impact of organic matter and macrozoobenthos on bacterial and oxygen variables in marine sediment boxcosms. Neth. J. Sea Res. 29, 343–355 (1992).
Google Scholar 

27.
Brooks, K. M. & Mahnken, C. V. Interactions of Atlantic salmon in the Pacific northwest environment II. Organic wastes. Fish. Res. 62, 255–293 (2003).
Google Scholar 

28.
Mackin, J. E. & Swider, K. T. Organic matter decomposition pathways and oxygen consumption in coastal marine sediments. J. Mar. Res. 47, 681–716 (1989).
CAS  Google Scholar 

29.
Holmer, M. & Kristensen, E. Impact of marine fish cage farming on metabolism and sulfate reduction of underlying sediments. Mar. Ecol. Prog. Ser. 80, 191–201 (1992).
ADS  CAS  Google Scholar 

30.
Carroll, M. L., Cochrane, S., Fieler, R., Velvin, R. & White, P. Organic enrichment of sediments from salmon farming in Norway: Environmental factors, management practices, and monitoring techniques. Aquaculture https://doi.org/10.1016/S0044-8486(03)00475-7 (2003).
Article  Google Scholar 

31.
Hargrave, B. T. Empirical relationships describing benthic impacts of salmon aquaculture. Aquac. Environ. Interact. 1, 33–46 (2010).
Google Scholar 

32.
Bagarinao, T. Sulfide as an environmental factor and toxicant: tolerance and adaptations in aquatic organisms. Aquat. Toxicol. 24, 21–62 (1992).
CAS  Google Scholar 

33.
Hargrave, B. T., Holmer, M. & Newcombe, C. P. Towards a classification of organic enrichment in marine sediments based on biogeochemical indicators. Mar. Pollut. Bull. 56, 810–824 (2008).
CAS  PubMed  Google Scholar 

34.
Ryckelynck, N., Stecher, H. A. & Reimers, C. E. Understanding the anodic mechanism of a seafloor fuel cell: Interactions between geochemistry and microbial activity. Biogeochemistry 76, 113–139 (2005).
Google Scholar 

35.
Ishii, S. et al. Identifying the microbial communities and operational conditions for optimized wastewater treatment in microbial fuel cells. Water Res. 47, 7120–7130 (2013).
CAS  PubMed  Google Scholar 

36.
Fader, G.B.J. & Miller, R.O. Surficial Geology, Halifax Harbour, Nova Scotia. Bulletin of the Geological Survey of Canada (2008).

37.
Grant, J., Emerson, C. W., Hargrave, B. T. & Shortle, J. L. Benthic oxygen consumption on continental shelves off eastern Canada. Cont. Shelf Res. 11, 1083–1097 (1991).
ADS  Google Scholar 

38.
Logan, B. E. Microbial fuel cells. In Treatise on Water Science, Vol. 4 (ed. Wilderer, P.) 641–665 (Wiley, New York, 2010).
Google Scholar 

39.
Taillefert, M. et al. Early diagenesis in the sediments of the Congo deep-sea fan dominated by massive terrigenous deposits: part II—Iron—sulfur coupling. Deep. Res. II Top. Stud. Oceanogr. 142, 151–166 (2017).
ADS  CAS  Google Scholar 

40.
Canfield, D. E., Raiswell, R. & Bottrell, S. The reactivity of sedimentary iron minerals toward sulfide. Am. J. Sci. 292, 659–683 (1992).
ADS  CAS  Google Scholar 

41.
Boudreau, B. P. Diagenetic models and their implementation: modelling transport and reactions in aquatic sediments (Springer, Berlin Heidelberg, 1996).
Google Scholar 

42.
Glud, R. N. Oxygen dynamics of marine sediments. Mar. Biol. Res. 4, 243–289 (2008).
Google Scholar 

43.
Berg, P., Risgaard-petersen, N. & Silkeborg, D. Interpretation of measured concentration profiles in sediment pore water. Limnol. Oceanogr. 43, 1500–1510 (1998).
ADS  CAS  Google Scholar 

44.
Hargrave, B. T. Seasonal changes in oxygen uptake by settled particulate matter and sediments in a marine bay. J. Fish. Res. Board Can. 35, 1621–1628 (1978).
CAS  Google Scholar 

45.
Viggi, C. C. et al. Bridging spatially segregated redox zones with a microbial electrochemical snorkel triggers biogeochemical cycles in oil-contaminated River Tyne (UK) sediments. Water Res. 127, 11–21 (2017).
CAS  PubMed  Google Scholar 

46.
Brüchert, V. & Arnosti, C. Anaerobic carbon transformation: Experimental studies with flow-through cells. Mar. Chem. 80, 171–183 (2003).
Google Scholar 

47.
Arnosti, C. Microbial extracellular enzymes and their role in dissolved organic matter cycling. Aquat. Ecosyst. https://doi.org/10.1016/b978-012256371-3/50014-7 (2003).
Article  Google Scholar 

48.
Lehman, R. M. & O’Connell, S. P. Comparison of extracellular enzyme activities and community composition of attached and free-living bacteria in porous medium columns. Appl. Environ. Microbiol. 68, 1569–1575 (2002).
CAS  PubMed  PubMed Central  Google Scholar 

49.
Reimers, C. E. et al. Microbial fuel cell energy from an ocean cold seep. Geobiology 4, 123–136 (2006).
CAS  Google Scholar 

50.
Jørgensen, B. B., Findlay, A. J. & Pellerin, A. The biogeochemical sulfur cycle of marine sediments. Front. Microbiol. 10, 849 (2019).
PubMed  PubMed Central  Google Scholar 

51.
Lovley, D. R. Happy together: Microbial communities that hook up to swap electrons. ISME J. 11, 327–336 (2017).
CAS  PubMed  Google Scholar 

52.
Finster, K., Liesack, W. & Thamdrup, B. Elemental sulfur and thiosulfate disproportionation by Desulfocapsa sulfoexigens sp. nov., a new anaerobic bacterium isolated from marine surface sediment. Appl. Environ. Microbiol. 64, 119–125 (1998).
CAS  PubMed  PubMed Central  Google Scholar 

53.
Kelly, D. P., Shergill, J. K., Lu, W. P. & Wood, A. P. Oxidative metabolism of inorganic sulfur compounds by bacteria. Int. J. Gen. Mol. Microbiol. 71, 95–107 (1997).
CAS  Google Scholar 

54.
Keeley, N. B., Forrest, B. M. & Macleod, C. K. Novel observations of benthic enrichment in contrasting flow regimes with implications for marine farm monitoring and management. Mar. Pollut. Bull. 66, 105–116 (2013).
CAS  PubMed  Google Scholar 

55.
Cranford, P., Brager, L., Elvines, D., Wong, D. & Law, B. A revised classification system describing the ecological quality status of organically enriched marine sediments based on total dissolved sulfides. Mar. Pollut. Bull. 154, 111088 (2020).
CAS  PubMed  Google Scholar 

56.
Soetaert, K., Hofmann, A. F., Middelburg, J. J., Meysman, F. J. R. & Greenwood, J. The effect of biogeochemical processes on pH. Mar. Chem. 105, 30–51 (2007).
CAS  Google Scholar 

57.
Seitaj, D. et al. Cable bacteria generate a firewall against euxinia in seasonally hypoxic basins. Proc. Natl. Acad. Sci. USA 112, 13278–13283 (2015).
ADS  CAS  PubMed  Google Scholar 

58.
Di Toro, D. M. et al. Acid volatile sulfide predicts the acute toxicity of cadmium and nickel in sediments. Environ. Sci. Technol. 26, 96–101 (1992).
ADS  Google Scholar 

59.
Brooks, K. M. & Mahnken, C. V. W. Interactions of Atlantic salmon in the Pacific Northwest environment. III. Accumulation of zinc and copper. Fish. Res. 62, 295–305 (2003).
Google Scholar 

60.
Fitridge, I., Dempster, T., Guenther, J. & de Nys, R. The impact and control of biofouling in marine aquaculture: A review. Biofouling 28, 649–669 (2012).
PubMed  Google Scholar 

61.
FOA. The State of World Fisheries and Aquaculture 2016. Contributing to food security and nutrition for all (2016).

62.
Millero, F. J., Plese, T. & Fernandez, M. The dissociation of hydrogen sulfide in seawater. Limnol. Oceanogr. 33, 269–274 (1988).
ADS  CAS  Google Scholar  More

1.
van Valen, L. M. Resetting the Phanerozoic community evolution. Nature 307, 93–106 (1984).
Google Scholar 
2.
Alroy, J. Dynamics of origination and extinction in the marine fossil record. Proc. Natl Acad. Sci. USA 105, 11536–11542 (2008).
CAS  PubMed  Google Scholar 

3.
Foote, M. Origination and extinction through the Phanerozoic: a new approach. J. Geol. 111, 125–148 (2003).
Google Scholar 

4.
Gilinsky, N. L. Volatility and the Phanerozoic decline of background extinction intensity. Paleobiology 20, 445–458 (1994).
Google Scholar 

5.
Lieberman, B. S. & Melott, A. L. Declining volatility, a general property of disparate systems: from fossils, to stocks, to the stars. Palaeontology 56, 1297–1304 (2013).
Google Scholar 

6.
Knope, M. L., Bush, A. M., Frishkoff, L. O., Heim, N. A. & Payne, J. L. Ecologically diverse clades dominate the oceans via extinction resistance. Science 367, 1035–1038 (2020).
CAS  PubMed  Google Scholar 

7.
Janzen, D. H. On ecological fitting. Oikos 45, 308–310 (1985).
Google Scholar 

8.
Agosta, S. J. & Klemens, J. A. Ecological fitting by phenotypically flexible genotypes: implications for species associations, community assembly and evolution. Ecol. Lett. 11, 1123–1134 (2008).
PubMed  Google Scholar 

9.
Nielsen, S. N. & Müller, F. in Handbook of Ecosystem Theories and Management (eds Jørgensen, S. E. & Müller, F.) 195–216 (CRC Press, 2000).

10.
Hui, C. et al. Defining invasiveness and invasibility in ecological networks. Biol. Invasions 18, 971–983 (2016).
Google Scholar 

11.
Foote, M. et al. Rise and fall of species occupancy in Cenozoic fossil mollusks. Science 318, 1131–1134 (2007).
CAS  PubMed  Google Scholar 

12.
Foote, M. Symmetric waxing and waning of marine invertebrate genera. Paleobiology 33, 517–529 (2007).
Google Scholar 

13.
Liow, L. H. & Stenseth, N. C. The rise and fall of species: implications for macroevolutionary and macroecological studies. Proc. R. Soc. Lond. B 274, 2745–2752 (2007).
Google Scholar 

14.
Zliobaite, I., Fortelius, M. & Stenseth, N. C. Reconciling taxon senescence with the Red Queen’s hypothesis. Nature 552, 92–95 (2017).
CAS  PubMed  Google Scholar 

15.
Gillespie, R. G. et al. Comparing adaptive radiations across space, time, and taxa. J. Hered. 111, 1–20 (2020).
PubMed  Google Scholar 

16.
Losos, J. B. Adaptive radiation, ecological opportunity, and evolutionary determinism: American Society of Naturalists EO Wilson Award address. Am. Nat. 175, 623–639 (2010).
PubMed  Google Scholar 

17.
Yoder, J. B. et al. Ecological opportunity and the origin of adaptive radiations. J. Evol. Biol. 23, 1581–1596 (2010).
CAS  PubMed  Google Scholar 

18.
Erwin, D. H. Novelty and innovation in the history of life. Curr. Biol. 25, R930–R940 (2015).
CAS  PubMed  Google Scholar 

19.
Gould, S. J. & Vrba, E. S. Exaptation—a missing term in the science of form. Paleobiology 8, 4–15 (1982).
Google Scholar 

20.
Cooper, A. & Fortey, R. Evolutionary explosions and the phylogenetic fuse. Trends Ecol. Evol. 13, 151–156 (1998).
CAS  PubMed  Google Scholar 

21.
Jablonski, D. & Bottjer, D. J. in Major Evolutionary Radiations (eds Taylor, P. D. & Larwood, G. P.) 17–57 (Systematics Association, 1990).

22.
Jablonski, D. Approaches to macroevolution: 1. general concepts and origin of variation. Evol. Biol. 44, 427–450 (2017).
PubMed  PubMed Central  Google Scholar 

23.
Uyeda, J. C., Hansen, T. F., Arnold, S. J. & Pienaar, J. The million-year wait for macroevolutionary bursts. Proc. Natl Acad. Sci. USA 108, 15908–15913 (2011).
CAS  PubMed  Google Scholar 

24.
Kröger, B., Desrochers, A. & Ernst, A. The reengineering of reef habitats during the Great Ordovician Biodiversification Event. PALAIOS 32, 584–599 (2017).
Google Scholar 

25.
Robeck, H. E., Maley, C. C. & Donoghue, M. J. Taxonomy and temporal diversity patterns. Paleobiology 26, 171–187 (2000).
Google Scholar 

26.
Hendricks, J. R., Saupe, E. E., Myers, C. E., Hermsen, E. J. & Allmon, W. D. The generification of the fossil record. Paleobiology 40, 511–528 (2014).
Google Scholar 

27.
Wagner, P. J., Aberhan, M., Hendy, A. & Kiessling, W. The effects of taxonomic standardization on sampling-standardized estimates of historical diversity. Proc. R. Soc. B 274, 439–444 (2007).
PubMed  Google Scholar 

28.
Plotnick, R. E. & Wagner, P. J. Roundup of the usual suspects: common genera in the fossil record and the nature of the wastebasket taxa. Paleobiology 32, 126–146 (2006).
Google Scholar 

29.
Bambach, R. K., Bush, M. A. & Erwin, D. H. Autecology and the filling of ecospace: key metazoan radiations. Palaeontology 50, 1–22 (2007).
Google Scholar 

30.
Knope, M. L., Heim, N. A., Frishkoff, L. O. & Payne, J. L. Limited role of functional differentiation in early diversification of animals. Nat. Commun. 6, 6455 (2015).
CAS  PubMed  PubMed Central  Google Scholar 

31.
Sepkoski, J. J. A kinetic model of Phanerozoic taxonomic diversity. III Post-Paleozoic families and mass extinctions. Paleobiology 10, 246–267 (1984).
Google Scholar 

32.
Alroy, J. The shifting balance of diversity among major marine animal groups. Science 329, 1191–1194 (2010).
CAS  PubMed  Google Scholar 

33.
Liow, L. H. & Nichols, J. D. in The Paleontological Society Short Course, October 30th 2010 (eds Alroy, J. & Hunt, G.) 81–94 (Cambridge Univ. Press, 2010).

34.
Kiessling, W. & Kocsis, Á. T. Adding fossil occupancy trajectories to the assessment of modern extinction risk. Biol. Lett. 12, 20150813 (2016).
PubMed  PubMed Central  Google Scholar 

35.
Fridley, J. D., Vandermast, D. B., Kuppinger, D. M., Manthey, M. L. & Peet, R. K. Co-occurrence based assessment of habitat generalists and specialists: a new approach for the measurement of niche width. J. Ecol. 95, 707–722 (2007).
Google Scholar 

36.
Hofmann, R., Tietje, M. & Aberhan, M. Diversity partitioning in Phanerozoic benthic marine communities. Proc. Natl Acad. Sci. USA 116, 79–83 (2019).
PubMed  Google Scholar 

37.
Bottjer, D. J., Hagadorn, J. W. & Dornbos, S. Q. The Cambrian substrate revolution. GSA Today 10, 1–7 (2000).
Google Scholar 

38.
Knoll, A. H. & Follows, M. J. A bottom-up perspective on ecosystem change in Mesozoic oceans. Proc. R. Soc. B 283, 20161755 (2016).
PubMed  Google Scholar 

39.
Bambach, R. K. Seafood through time: changes in biomass, energetics, and productivity in the marine ecosystem. Paleobiology 19, 372–397 (1993).
Google Scholar 

40.
Westrop, S. R. The life habits of the Ordovician illaenine trilobite Bumastoides. Lethaia 16, 15–24 (1983).
Google Scholar 

41.
O’Dea, A. & Jackson, J. Environmental change drove macroevolution in cupuladriid bryozoans. Proc. R. Soc. B 276, 3629–3634 (2009).
PubMed  Google Scholar 

42.
Rasmussen, C. M. Ø., Kröger, B., Nielsen, M. L. & Colmenar, J. Cascading trend of Early Paleozoic marine radiations paused by Late Ordovician extinctions. Proc. Natl Acad. Sci. USA 116, 7207 (2019).
PubMed  Google Scholar 

43.
Bush, A. M. & Bambach, R. K. Sustained Mesozoic–Cenozoic diversification of marine Metazoa: a consistent signal from the fossil record. Geology 43, 979–982 (2015).
Google Scholar 

44.
Leibold, M. A. & McPeek, M. A. Coexistence of the niche and neutral perspectives in community ecology. Ecology 87, 1399–1410 (2006).
PubMed  Google Scholar 

45.
McPeek, M. A. The ecological dynamics of clade diversification and community assembly. Am. Nat. 172, E270–E284 (2008).
PubMed  Google Scholar 

46.
Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).
Google Scholar 

47.
Wagner, P. J., Aberhan, M., Hendy, A. & W, K. The effects of taxonomic standardization on occurrence-based estimates of diversity. Proc. R. Soc. Lond. B 274, 439–444 (2007).
Google Scholar 

48.
Cohen, K. M., Harper, D. A. T. & Gibbard, P. L. ICS International Chronostratigraphic Chart 2018/08 (International Commission on Stratigraphy, IUGS, 2018); www.stratigraphy.org

49.
Nichols, J. D. & Pollock, K. H. Estimating taxonomic diversity, extinction rates, and speciation rates from fossil data using capture–recapture models. Paleobiology 9, 150–163 (1983).
Google Scholar 

50.
Connolly, S. R. & Miller, A. I. Joint estimation of sampling and turnover rates from fossil databases: capture–mark–recapture methods revisited. Paleobiology 27, 767–751 (2001).
Google Scholar 

51.
Schwarz, C. J. & Arnason, A. N. A general methodology for the analysis of capture–recapture experiments in open populations. Biometrics 52, 860–873 (1996).
Google Scholar 

52.
Pradel, R. Utilization of capture–mark–recapture for the study of recruitment and population growth rate. Biometrics 52, 703–709 (1996).
Google Scholar 

53.
Liow, L. H., Reitan, T. & Harnik, P. G. Ecological interactions on macroevolutionary time scales: clams and brachiopods are more than ships that pass in the night. Ecol. Lett. 18, 1030–1039 (2015).
PubMed  Google Scholar 

54.
Alroy, J. A more precise speciation and extinction rate estimator. Paleobiology 41, 633–639 (2015).
Google Scholar 

55.
Kocsis, Á. T., Reddin, C. J., Alroy, J. & Kiessling, W. The r package divDyn for quantifying diversity dynamics using fossil sampling data. Methods Ecol. Evol. 10, 735–743 (2019).
Google Scholar 

56.
Cornette, J. L. & Lieberman, B. S. Random walks in the history of life. Proc. Natl Acad. Sci. USA 101, 187–191 (2004).
CAS  PubMed  Google Scholar 

57.
Fuller, W. A. Introduction to Statistical Time Series (Wiley, 2009).

58.
Manthey, M. & Fridley, J. D. Beta diversity metrics and the estimation of niche width via species co-occurrence data: reply to Zeleny. J. Ecol. 97, 18–22 (2009).
Google Scholar  More

1.
Grimm, N. B. et al. Global change and the ecology of cities. Science 319, 756–760 (2008).
ADS  CAS  PubMed  Google Scholar 
2.
McKinney, M. L. Urbanization, biodiversity, and conservation. Bioscience 52, 883 (2002).
Google Scholar 

3.
Lowry, H., Lill, A. & Wong, B. B. M. Behavioural responses of wildlife to urban environments: behavioural responses to urban environments. Biol. Rev. 88, 537–549 (2013).
PubMed  Google Scholar 

4.
Sih, A. Understanding variation in behavioural responses to human-induced rapid environmental change: a conceptual overview. Anim. Behav. 85, 1077–1088 (2013).
Google Scholar 

5.
Sih, A., Ferrari, M. C. O. & Harris, D. J. Evolution and behavioural responses to human-induced rapid environmental change: behaviour and evolution. Evol. Appl. 4, 367–387 (2011).
PubMed  PubMed Central  Google Scholar 

6.
Lapiedra, O., Chejanovski, Z. & Kolbe, J. J. Urbanization and biological invasion shape animal personalities. Glob. Change Biol. 23, 592–603 (2017).
ADS  Google Scholar 

7.
Sih, A., Stamps, J., Yang, L. H., McElreath, R. & Ramenofsky, M. Behavior as a key component of integrative biology in a human-altered world. Integr. Comp. Biol. 50, 934–944 (2010).
PubMed  Google Scholar 

8.
Alberti, M. Eco-evolutionary dynamics in an urbanizing planet. Trends Ecol. Evol. 30, 114–126 (2015).
PubMed  Google Scholar 

9.
Sol, D., Lapiedra, O. & González-Lagos, C. Behavioural adjustments for a life in the city. Anim. Behav. 85, 1101–1112 (2013).
Google Scholar 

10.
Tuomainen, U. & Candolin, U. Behavioural responses to human-induced environmental change. Biol. Rev. 86, 640–657 (2011).
PubMed  Google Scholar 

11.
Seferta, A., Guay, P.-J., Marzinotto, E. & Lefebvre, L. Learning differences between feral pigeons and zenaida doves: the role of neophobia and human proximity. Ethology 107, 281–293 (2001).
Google Scholar 

12.
Sol, D., Bacher, S., Reader, S. M. & Lefebvre, L. Brain size predicts the success of mammal species introduced into novel environments. Am. Nat. 172, S63–S71 (2008).
PubMed  Google Scholar 

13.
Sol, D., Duncan, R. P., Blackburn, T. M., Cassey, P. & Lefebvre, L. Big brains, enhanced cognition, and response of birds to novel environments. Proc. Natl. Acad. Sci. 102, 5460–5465 (2005).
ADS  CAS  PubMed  Google Scholar 

14.
Webster, S. J. & Lefebvre, L. Problem solving and neophobia in a columbiform–passeriform assemblage in Barbados. Anim. Behav. 62, 23–32 (2001).
Google Scholar 

15.
Lowry, H., Lill, A. & Wong, B. B. M. Tolerance of auditory disturbance by an avian urban adapter, the noisy miner: tolerance of auditory disturbance by an avian urban adapter. Ethology 117, 490–497 (2011).
Google Scholar 

16.
Rodríguez-Prieto, I., Martín, J. & Fernández-Juricic, E. Individual variation in behavioural plasticity: direct and indirect effects of boldness, exploration and sociability on habituation to predators in lizards. Proc. R. Soc. B 278, 266–273 (2011).
PubMed  Google Scholar 

17.
Réale, D., Reader, S. M., Sol, D., McDougall, P. T. & Dingemanse, N. J. Integrating animal temperament within ecology and evolution. Biol. Rev. 82, 291–318 (2007).
PubMed  Google Scholar 

18.
Gosling, S. D. From mice to men: what can we learn about personality from animal research?. Psychol. Bull. 127, 45–86 (2001).
CAS  PubMed  Google Scholar 

19.
Koolhaas, J. M. et al. Coping styles in animals: current status in behavior and stress-physiology. Neurosci. Biobehav. Rev. 23, 925–935 (1999).
CAS  PubMed  Google Scholar 

20.
Sih, A., Cote, J., Evans, M., Fogarty, S. & Pruitt, J. Ecological implications of behavioural syndromes: ecological implications of behavioural syndromes. Ecol. Lett. 15, 278–289 (2012).
PubMed  Google Scholar 

21.
Wolf, M. & Weissing, F. J. Animal personalities: consequences for ecology and evolution. Trends Ecol. Evol. 27, 452–461 (2012).
PubMed  Google Scholar 

22.
Hardman, S. I. & Dalesman, S. Repeatability and degree of territorial aggression differs among urban and rural great tits (Parus major). Sci. Rep. 8, 5042 (2018).
ADS  PubMed  PubMed Central  Google Scholar 

23.
Wilson, D. S., Coleman, K., Clark, A. B. & Biederman, L. Shy-bold continuum in pumpkinseed sunfish (Lepomis gibbosus): an ecological study of a psychological trait. J. Comp. Psychol. 107, 250–260 (1993).
Google Scholar 

24.
Wilson, A. D. M. & Godin, J.-G.J. Boldness and intermittent locomotion in the bluegill sunfish Lepomis macrochirus. Behav. Ecol. 21, 57–62 (2010).
Google Scholar 

25.
Ward, A. J. W., Hart, P. J. B. & Webster, M. M. Boldness is influenced by social context in threespine sticklebacks (Gasterosteus aculeatus). Behaviour 144, 351–371 (2007).
Google Scholar 

26.
Dammhahn, M. & Almeling, L. Is risk taking during foraging a personality trait? A field test for cross-context consistency in boldness. Anim. Behav. 84, 1131–1139 (2012).
Google Scholar 

27.
Sih, A., Bell, A. M., Johnson, J. C. & Ziemba, R. E. Behavioral syndromes: an integrative overview. Q. Rev. Biol. 79, 241–277 (2004).
PubMed  Google Scholar 

28.
Smith, B. R. & Blumstein, D. T. Fitness consequences of personality: a meta-analysis. Behav. Ecol. 19, 448–455 (2008).
Google Scholar 

29.
Dingemanse, N. J., Both, C., Drent, P. J. & Tinbergen, J. M. Fitness consequences of avian personalities in a fluctuating environment. Proc. R. Soc. Lond. B 271, 847–852 (2004).
Google Scholar 

30.
Sinn, D. L., Apiolaza, L. A. & Moltschaniwskyj, N. A. Heritability and fitness-related consequences of squid personality traits. J. Evol. Biol. 19, 1437–1447 (2006).
CAS  PubMed  Google Scholar 

31.
Ariyomo, T. O., Carter, M. & Watt, P. J. Heritability of boldness and aggressiveness in the zebrafish. Behav. Genet. 43, 161–167 (2013).
PubMed  Google Scholar 

32.
van Oers, K., de Jong, G., Drent, P. J. & van Noordwijk, A. J. A genetic analysis of avian personality traits: correlated response to artificial selection. Behav. Genet. 34, 611–619 (2004).
PubMed  Google Scholar 

33.
Réale, D. & Festa-Bianchet, M. Predator-induced natural selection on temperament in bighorn ewes. Anim. Behav. 65, 463–470 (2003).
Google Scholar 

34.
Grand, T. C. Risk-taking behaviour and the timing of life history events: consequences of body size and season. Oikos 85, 467 (1999).
Google Scholar 

35.
Fraser, D. F., Gilliam, J. F., Daley, M. J., Le, A. N. & Skalski, G. T. Explaining leptokurtic movement distributions: intrapopulation variation in boldness and exploration. Am. Nat. 158, 124–135 (2001).
CAS  PubMed  Google Scholar 

36.
Mazza, V., Jacob, J., Dammhahn, M., Zaccaroni, M. & Eccard, J. A. Individual variation in cognitive style reflects foraging and anti-predator strategies in a small mammal. Sci. Rep. 9, 10157 (2019).
ADS  PubMed  PubMed Central  Google Scholar 

37.
Patrick, S. C. & Weimerskirch, H. Personality, foraging and fitness consequences in a long lived seabird. PLoS ONE 9, e87269 (2014).
ADS  PubMed  PubMed Central  Google Scholar 

38.
Brown, J. S. & Kotler, B. P. Hazardous duty pay and the foraging cost of predation: foraging cost of predation. Ecol. Lett. 7, 999–1014 (2004).
Google Scholar 

39.
Godin, J. G. & Dugatkin, L. A. Female mating preference for bold males in the guppy, Poecilia reticulata. Proc. Natl. Acad. Sci. 93, 10262–10267 (1996).
ADS  CAS  PubMed  Google Scholar 

40.
Ariyomo, T. O. & Watt, P. J. Disassortative mating for boldness decreases reproductive success in the guppy. Behav. Ecol. 24, 1320–1326 (2013).
Google Scholar 

41.
Collins, S. M., Hatch, S. A., Elliott, K. H. & Jacobs, S. R. Boldness, mate choice and reproductive success in Rissa tridactyla. Anim. Behav. 154, 67–74 (2019).
Google Scholar 

42.
Mettke-Hofmann, C., Winkler, H. & Leisler, B. The Significance of ecological factors for exploration and neophobia in parrots. Ethology 108, 249–272 (2002).
Google Scholar 

43.
Burstal, J., Clulow, S., Colyvas, K., Kark, S. & Griffin, A. S. Radiotracking invasive spread: are common mynas more active and exploratory on the invasion front?. Biol Invasions https://doi.org/10.1007/s10530-020-02269-7 (2020).
Article  Google Scholar 

44.
Carter, A. J., Feeney, W. E., Marshall, H. H., Cowlishaw, G. & Heinsohn, R. Animal personality: what are behavioural ecologists measuring?. Biol. Rev. 88, 465–475 (2013).
PubMed  Google Scholar 

45.
Perals, D., Griffin, A. S., Bartomeus, I. & Sol, D. Revisiting the open-field test: what does it really tell us about animal personality?. Anim. Behav. 123, 69–79 (2017).
Google Scholar 

46.
Cote, J., Fogarty, S., Weinersmith, K., Brodin, T. & Sih, A. Personality traits and dispersal tendency in the invasive mosquitofish (Gambusia affinis ). Proc. R. Soc. B 277, 1571–1579 (2010).
PubMed  Google Scholar 

47.
Dingemanse, N. J., Both, C., Drent, P. J., van Oers, K. & van Noordwijk, A. J. Repeatability and heritability of exploratory behaviour in great tits from the wild. Anim. Behav. 64, 929–938 (2002).
Google Scholar 

48.
Dingemanse, N. J. et al. Individual experience and evolutionary history of predation affect expression of heritable variation in fish personality and morphology. Proc. R. Soc. B. 276, 1285–1293 (2009).
PubMed  Google Scholar 

49.
Careau, V. et al. Genetic correlation between resting metabolic rate and exploratory behaviour in deer mice (Peromyscus maniculatus): pace-of-life in a muroid rodent. J. Evol. Biol. 24, 2153–2163 (2011).
CAS  PubMed  Google Scholar 

50.
Korsten, P., van Overveld, T., Adriaensen, F. & Matthysen, E. Genetic integration of local dispersal and exploratory behaviour in a wild bird. Nat. Commun. 4, 2362 (2013).
ADS  PubMed  Google Scholar 

51.
Drent, P. J., van Oers, K. & van Noordwijk, A. J. Realized heritability of personalities in the great tit (Parus major). Proc. R. Soc. Lond. B 270, 45–51 (2003).
Google Scholar 

52.
Dingemanse, N. J. & Réale, D. Natural selection and animal personality. Behavior 142, 1159–1184 (2005).
Google Scholar 

53.
Both, C., Dingemanse, N. J., Drent, P. J. & Tinbergen, J. M. Pairs of extreme avian personalities have highest reproductive success. J. Anim. Ecol. 74, 667–674 (2005).
Google Scholar 

54.
Mutzel, A., Dingemanse, N. J., Araya-Ajoy, Y. G. & Kempenaers, B. Parental provisioning behaviour plays a key role in linking personality with reproductive success. Proc. R. Soc. B 280, 20131019 (2013).
CAS  PubMed  Google Scholar 

55.
Dingemanse, N. J., Both, C., van Noordwijk, A. J., Rutten, A. L. & Drent, P. J. Natal dispersal and personalities in great tits (Parus major). Proc. R. Soc. Lond. B 270, 741–747 (2003).
Google Scholar 

56.
Haughland, D. L. & Larsen, K. W. Exploration correlates with settlement: red squirrel dispersal in contrasting habitats. J. Anim. Ecol. 73, 1024–1034 (2004).
Google Scholar 

57.
Alford, R. A., Brown, G. P., Schwarzkopf, L., Phillips, B. L. & Shine, R. Comparisons through time and space suggest rapid evolution of dispersal behaviour in an invasive species. Wildl. Res. 36, 23 (2009).
Google Scholar 

58.
Hoset, K. S. et al. Natal dispersal correlates with behavioral traits that are not consistent across early life stages. Behav. Ecol. 22, 176–183 (2011).
Google Scholar 

59.
Debeffe, L. et al. Exploration as a key component of natal dispersal: dispersers explore more than philopatric individuals in roe deer. Anim. Behav. 86, 143–151 (2013).
Google Scholar 

60.
Schirmer, A., Herde, A., Eccard, J. A. & Dammhahn, M. Individuals in space: personality-dependent space use, movement and microhabitat use facilitate individual spatial niche specialization. Oecologia 189, 647–660 (2019).
ADS  PubMed  PubMed Central  Google Scholar 

61.
Schirmer, A., Hoffmann, J., Eccard, J. A. & Dammhahn, M. My niche: individual spatial niche specialization affects within- and between-species interactions. Proc. R. Soc. B 287, 20192211 (2020).
PubMed  Google Scholar 

62.
Duckworth, R. A. & Badyaev, A. V. Coupling of dispersal and aggression facilitates the rapid range expansion of a passerine bird. Proc. Natl. Acad. Sci. 104, 15017–15022 (2007).
ADS  CAS  PubMed  Google Scholar 

63.
Carrete, M. & Tella, J. L. Behavioral correlations associated with fear of humans differ between rural and urban burrowing owls. Front. Ecol. Evol. 5, 54 (2017).
Google Scholar 

64.
Evans, J., Boudreau, K. & Hyman, J. Behavioural syndromes in urban and rural populations of song sparrows. Ethology 116, 588–595 (2010).
Google Scholar 

65.
Miranda, A. C., Schielzeth, H., Sonntag, T. & Partecke, J. Urbanization and its effects on personality traits: a result of microevolution or phenotypic plasticity?. Glob. Change Biol. 19, 2634–2644 (2013).
ADS  Google Scholar 

66.
Reil, D. et al. Puumala hantavirus infections in bank vole populations: host and virus dynamics in Central Europe. BMC Ecol. 17, 9 (2017).
PubMed  PubMed Central  Google Scholar 

67.
Andrzejewski, R., Babińska-Werka, J., Gliwicz, J. & Goszczyński, J. Synurbization processes in population of Apodemus agrarius. I. Characteristics of populations in an urbanization gradient. Acta Theriol. 23, 341–358 (1978).
Google Scholar 

68.
Babińska-Werka, J. Food of the striped field mouse in different types of urban green areas. Acta Theriol. 26, 285–299 (1981).
Google Scholar 

69.
Liro, A. Variation in weights of body and internal organs of the field mouse in a gradient of urban habitats. Acta Theriol. 30, 359–377 (1985).
Google Scholar 

70.
Sikorski, M. D. Craniometric variation of Apodemus agrarius (Pallas, 1771) in urban green areas. Acta Theriol. 27, 71–81 (1982).
Google Scholar 

71.
Babińska-Werka, J., Gliwicz, J. & Goszczyński, J. Demographic processes in an urban population of the striped field mouse. Acta Theriol. 26, 275–283 (1981).
Google Scholar 

72.
Gortat, T., Rutkowski, R., Gryczynska-Siemiatkowska, A., Kozakiewicz, A. & Kozakiewicz, M. Genetic structure in urban and rural populations of Apodemus agrarius in Poland. Mamm. Biol. 78, 171–177 (2013).
Google Scholar 

73.
McKinney, M. L. Urbanization as a major cause of biotic homogenization. Biol. Conserv. 127, 247–260 (2006).
Google Scholar 

74.
Moule, H., Michelangeli, M., Thompson, M. B. & Chapple, D. G. The influence of urbanization on the behaviour of an Australian lizard and the presence of an activity-exploratory behavioural syndrome: impact of urbanization on the delicate skink. J. Zool. 298, 103–111 (2016).
Google Scholar 

75.
Boon, A. K., Réale, D. & Boutin, S. Personality, habitat use, and their consequences for survival in North American red squirrels Tamiasciurus hudsonicus. Oikos 117, 1321–1328 (2008).
Google Scholar 

76.
Wolf, M., van Doorn, G. S., Leimar, O. & Weissing, F. J. Life-history trade-offs favour the evolution of animal personalities. Nature 447, 581–584 (2007).
ADS  CAS  PubMed  Google Scholar 

77.
Fischer, J. D., Cleeton, S. H., Lyons, T. P. & Miller, J. R. Urbanization and the predation paradox: the role of trophic dynamics in structuring vertebrate communities. Bioscience 62, 809–818 (2012).
Google Scholar 

78.
Shochat, E. Credit or debit? Resource input changes population dynamics of city-slicker birds. Oikos 106, 622–626 (2004).
Google Scholar 

79.
Bateman, P. W. & Fleming, P. A. Big city life: carnivores in urban environments: urban carnivores. J. Zool. 287, 1–23 (2012).
Google Scholar 

80.
Kettel, E. F., Gentle, L. K., Quinn, J. L. & Yarnell, R. W. The breeding performance of raptors in urban landscapes: a review and meta-analysis. J. Ornithol. 159, 1–18 (2018).
Google Scholar 

81.
Vines, A. & Lill, A. Boldness and urban dwelling in little ravens. Wildl. Res. 42, 590 (2015).
Google Scholar 

82.
Uchida K, Shimamoto T, Yanagawa H, Koizumi I (2020) Comparison of multiple behavioral traits between urban and rural squirrels. Urban Ecosyst. 1, 1–10 (2020).

83.
Atwell, J. W. et al. Boldness behavior and stress physiology in a novel urban environment suggest rapid correlated evolutionary adaptation. Behav. Ecol. 23, 960–969 (2012).
PubMed  PubMed Central  Google Scholar 

84.
Bókony, V., Kulcsár, A., Tóth, Z. & Liker, A. Personality traits and behavioral syndromes in differently urbanized populations of house sparrows (Passer domesticus). PLoS ONE 7, e36639 (2012).
ADS  PubMed  PubMed Central  Google Scholar 

85.
Greenberg, R. The Role of Neophobia and Neophilia in the Development of Innovative Behaviour of Birds. In Animal Innovation (eds Reader, S. M. & Laland, K. N.) 175–196 (Oxford University Press, Oxford, 2003). https://doi.org/10.1093/acprof:oso/9780198526223.003.0008.
Google Scholar 

86.
delBarco-Trillo, J. Shyer and larger bird species show more reduced fear of humans when living in urban environments. Biol. Lett. 14, 20170730 (2018).
PubMed  PubMed Central  Google Scholar 

87.
Greggor, A. L., Clayton, N. S., Fulford, A. J. C. & Thornton, A. Street smart: faster approach towards litter in urban areas by highly neophobic corvids and less fearful birds. Anim. Behav. 117, 123–133 (2016).
PubMed  PubMed Central  Google Scholar 

88.
Seress, G., Bókony, V., Heszberger, J. & Liker, A. Response to predation risk in urban and rural house sparrows: response to predation risk in house sparrows. Ethology 117, 896–907 (2011).
Google Scholar 

89.
Rymer, T., Pillay, N. & Schradin, C. Extinction or survival? Behavioral flexibility in response to environmental change in the african striped mouse rhabdomys. Sustainability 5, 163–186 (2013).
Google Scholar 

90.
Martin, J. G. A. & Réale, D. Temperament, risk assessment and habituation to novelty in eastern chipmunks Tamias striatus. Anim. Behav. 75, 309–318 (2008).
Google Scholar 

91.
Carere, C. & Locurto, C. Interaction between animal personality and animal cognition. Curr. Zool. 57, 491–498 (2011).
Google Scholar 

92.
Sih, A. & Del Giudice, M. Linking behavioural syndromes and cognition: a behavioural ecology perspective. Philos. Trans. R. Soc. B 367, 2762–2772 (2012).
Google Scholar 

93.
Mettke-Hofmann, C. & Gwinner, E. Differential assessment of environmental information in a migratory and a nonmigratory passerine. Anim. Behav. 68, 1079–1086 (2004).
Google Scholar 

94.
Mettke-Hofmann, C., Rowe, K. C., Hayden, T. J. & Canoine, V. Effects of experience and object complexity on exploration in garden warblers (Sylvia borin). J Zool. 268, 405–413 (2006).
Google Scholar 

95.
Boyer, N., Réale, D., Marmet, J., Pisanu, B. & Chapuis, J.-L. Personality, space use and tick load in an introduced population of Siberian chipmunks Tamias sibiricus. J. Anim. Ecol. 79, 538–547 (2010).
PubMed  Google Scholar 

96.
Barber, I. & Dingemanse, N. J. Parasitism and the evolutionary ecology of animal personality. Philos. Trans. R. Soc. B 365, 4077–4088 (2010).
Google Scholar 

97.
Jones, K. A. & Godin, J.-G.J. Are fast explorers slow reactors? Linking personality type and anti-predator behaviour. Proc. R. Soc. B 277, 625–632 (2010).
PubMed  Google Scholar 

98.
Sol, D., Griffin, A. S., Bartomeus, I. & Boyce, H. Exploring or avoiding novel food resources? The novelty conflict in an invasive bird. PLoS ONE 6, e19535 (2011).
ADS  CAS  PubMed  PubMed Central  Google Scholar 

99.
Couchoux, C. & Cresswell, W. Personality constraints versus flexible antipredation behaviors: how important is boldness in risk management of redshanks (Tringa totanus) foraging in a natural system?. Behav. Ecol. 23, 290–301 (2012).
Google Scholar 

100.
Patergnani, M. et al. Environmental influence on urban rodent bait consumption. J. Pest Sci. 83, 347–359 (2010).
Google Scholar 

101.
Lehrer, E. W., Schooley, R. L. & Whittington, J. K. Survival and antipredator behavior of woodchucks (Marmota monax) along an urban-agricultural gradient. Can. J. Zool. 90, 12–21 (2012).
Google Scholar 

102.
Niemelä, P. T., Vainikka, A., Forsman, J. T., Loukola, O. J. & Kortet, R. How does variation in the environment and individual cognition explain the existence of consistent behavioral differences?. Ecol. Evol. 3, 457–464 (2013).
PubMed  Google Scholar 

103.
Garamszegi, L. Z. et al. Among-year variation in the repeatability, within- and between-individual, and phenotypic correlations of behaviors in a natural population. Behav. Ecol. Sociobiol. 69, 2005–2017 (2015).
PubMed  PubMed Central  Google Scholar 

104.
Stewart, I. D. & Oke, T. R. Local climate zones for urban temperature studies. Bull. Am. Meteorol. Soc. 93, 1879–1900 (2012).
ADS  Google Scholar 

105.
Semenov, M., Donatelli, M., Stratonovitch, P., Chatzidaki, E. & Baruth, B. ELPIS: a dataset of local-scale daily climate scenarios for Europe. Clim. Res. 44, 3–15 (2010).
Google Scholar 

106.
Hall, S. J. et al. Convergence of microclimate in residential landscapes across diverse cities in the United States. Landsc. Ecol. 31, 101–117 (2016).
Google Scholar 

107.
Janković, V. A historical review of urban climatology and the atmospheres of the industrialized world: review of urban climatology and the atmospheres of the industrialized world. WIREs Clim. Change 4, 539–553 (2013).
Google Scholar 

108.
Grimmond, S. Urbanization and global environmental change: local effects of urban warming. Geogr. J. 173, 83–88 (2007).
Google Scholar 

109.
Oke, T. R. The energetic basis of the urban heat island. Q. J. R. Meteorol. Soc. 108, 1–24 (1982).
ADS  Google Scholar 

110.
Charmantier, A., Demeyrier, V., Lambrechts, M., Perret, S. & Grégoire, A. Urbanization is associated with divergence in pace-of-life in great tits. Front. Ecol. Evol. 5, 53 (2017).
Google Scholar 

111.
Badyaev, A. V., Young, R. L., Oh, K. P. & Addison, C. Evolution on a local scale: developmental, functional, and genetic bases of divergence in bill form and associated changes in song structure between adjacent habitats. Evolution 62, 1951–1964 (2008).
PubMed  Google Scholar 

112.
Alberti, M., Marzluff, J. & Hunt, V. M. Urban driven phenotypic changes: empirical observations and theoretical implications for eco-evolutionary feedback. Philos. Trans. R. Soc. B 372, 20160029 (2017).
Google Scholar 

113.
Buchholz, S., Hannig, K., Möller, M. & Schirmel, J. Reducing management intensity and isolation as promising tools to enhance ground-dwelling arthropod diversity in urban grasslands. Urban Ecosyst. 21, 1139–1149 (2018).
Google Scholar 

114.
Seress, G., Lipovits, Á, Bókony, V. & Czúni, L. Quantifying the urban gradient: a practical method for broad measurements. Landsc. Urban Plan. 131, 42–50 (2014).
Google Scholar 

115.
Senatsverwaltung für Umwelt, Verkehr und Klimaschutz. Berlin Environmental Atlas—05.08 Biotopes (2016). https://fbinter.stadt-berlin.de/fb/index.jsp?loginkey=showMap&mapId=k_fb_berlinbtk@senstadt. Accessed 15 Dec 2019.

116.
GIS, E. A. v10. Environmental Systems Research Institute. Inc., Redlands, CA, USA (2011).

117.
Herde, A. & Eccard, J. A. Consistency in boldness, activity and exploration at different stages of life. BMC Ecol. 13, 49 (2013).
PubMed  PubMed Central  Google Scholar 

118.
Young, R. & Johnson, D. N. A fully automated light/dark apparatus useful for comparing anxiolytic agents. Pharmacol. Biochem. Behav. 40, 739–743 (1991).
CAS  PubMed  Google Scholar 

119.
Hall, C. S. Emotional behavior in the rat. I. Defecation and urination as measures of individual differences in emotionality. J. Comp. Psychol. 18, 385–403 (1934).
Google Scholar 

120.
Archer, J. Tests for emotionality in rats and mice: a review. Anim. Behav. 21, 205–235 (1973).
CAS  PubMed  Google Scholar 

121.
Walsh, R. N. & Cummins, R. A. The open-field test: a critical review. Psychol. Bull. 83, 482–504 (1976).
CAS  PubMed  Google Scholar 

122.
Cavigelli, S. A., Michael, K. C. & Ragan, C. M. Behavioral, physiological, and health biases in laboratory rodents: a basis for understanding mechanistic links between human personality and health. In Animal Personalities: Behavior, Physiology, and Evolution (eds Carere, C. & Maestripieri, D.) 441–498 (University of Chicago Press, Chicago, 2013).
Google Scholar 

123.
Gharnit, E., Bergeron, P., Garant, D. & Réale, D. Exploration profiles drive activity patterns and temporal niche specialization in a wild rodent. Behav. Ecol. 31, 772–783 (2020).
Google Scholar 

124.
Weiss, A. & Adams, M. J. Differential behavioral ecology. In Animal personalities: behavior, physiology and evolution (eds Carere, C. & Maestripieri, D.) 96–123 (University of Chicago Press, Chicago, 2013).
Google Scholar 

125.
Russell, P. A. Fear-evoking stimuli. In Fear in Animals and Man (ed. Sluckin, W.) 86–124 (Van Nostrand Reinhold Company, New York, 1979).
Google Scholar 

126.
Grossen, N. E. & Kelley, M. J. Species-specific behavior and acquisition of avoidance behavior in rats. J. Comp. Physiol. Psychol. 81, 307–310 (1972).
CAS  PubMed  Google Scholar 

127.
Mazza, V., Eccard, J. A., Zaccaroni, M., Jacob, J. & Dammhahn, M. The fast and the flexible: cognitive style drives individual variation in cognition in a small mammal. Anim. Behav. 137, 119–132 (2018).
Google Scholar 

128.
Geng, R. et al. Diet and prey consumption of breeding common Kestrel (Falco tinnunculus) in Northeast China. Prog. Nat. Sci. 19, 1501–1507 (2009).
Google Scholar 

129.
Jedrzejewska, B. & Jedrzejewski, W. Predation in Vertebrate Communities: The Bialowieza Primeval Forest as a Case Study, vol. 135 (Springer, Berlin, 2013).
Google Scholar 

130.
Sándor, A. D. & Ionescu, D. T. Diet of the eagle owl (Bubo bubo) in Braşov Romania. N.-West. J. Zool. 5, 170–178 (2009).
Google Scholar 

131.
Apfelbach, R., Blanchard, C. D., Blanchard, R. J., Hayes, R. A. & McGregor, I. S. The effects of predator odors in mammalian prey species: a review of field and laboratory studies. Neurosci. Biobehav. Rev. 29, 1123–1144 (2005).
PubMed  Google Scholar 

132.
Adibi, M. Whisker-mediated touch system in rodents: from neuron to behavior. Front. Syst. Neurosci. 13, 40 (2019).
PubMed  PubMed Central  Google Scholar 

133.
Lavenex, P. & Schenk, F. Olfactory cues potentiate learning of distant visuospatial information. Neurobiol. Learn. Mem. 68, 140–153 (1997).
CAS  PubMed  Google Scholar 

134.
Tomlinson, W. T. & Johnston, T. D. Hamsters remember spatial information derived from olfactory cues. Anim. Learn. Behav. 19, 185–190 (1991).
Google Scholar 

135.
Casarrubea, M. et al. Temporal structure of the rat’s behavior in elevated plus maze test. Behav. Brain Res. 237, 290–299 (2013).
CAS  PubMed  Google Scholar 

136.
Takahashi, A., Kato, K., Makino, J., Shiroishi, T. & Koide, T. Multivariate analysis of temporal descriptions of open-field behavior in wild-derived mouse strains. Behav. Genet. 36, 763–774 (2006).
PubMed  Google Scholar 

137.
Krupa, D. J., Matell, M. S., Brisben, A. J., Oliveira, L. M. & Nicolelis, M. A. L. Behavioral properties of the trigeminal somatosensory system in rats performing whisker-dependent tactile discriminations. J. Neurosci. 21, 5752–5763 (2001).
CAS  PubMed  PubMed Central  Google Scholar 

138.
von Heimendahl, M., Itskov, P. M., Arabzadeh, E. & Diamond, M. E. Neuronal activity in rat barrel cortex underlying texture discrimination. PLoS Biol. 5, e305 (2007).
Google Scholar 

139.
Morita, T., Kang, H., Wolfe, J., Jadhav, S. P. & Feldman, D. E. Psychometric curve and behavioral strategies for whisker-based texture discrimination in rats. PLoS ONE 6, e20437 (2011).
ADS  CAS  PubMed  PubMed Central  Google Scholar 

140.
Lavenex, P. & Schenk, F. Integration of olfactory information in a spatial representation enabling accurate arm choice in the radial arm maze. Learn. Mem. 2, 299–319 (1996).
CAS  PubMed  Google Scholar 

141.
Rangassamy, M., Dalmas, M., Féron, C., Gouat, P. & Rödel, H. G. Similarity of personalities speeds up reproduction in pairs of a monogamous rodent. Anim. Behav. 103, 7–15 (2015).
Google Scholar 

142.
Nakagawa, S. & Schielzeth, H. Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biol. Rev. 85, 935–956 (2010).
Google Scholar 

143.
Stoffel, M. A., Nakagawa, S. & Schielzeth, H. rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models. Methods Ecol. Evol. 8, 1639–1644 (2017).
Google Scholar 

144.
Faraway, J. J. Extending the Linear Model with R (Chapman & Hall/CRC, Boca Raton, 2006).
Google Scholar 

145.
Zuur, A. F. Mixed Effects Models and Extensions in Ecology with R (Springer, Berlin, 2009).
Google Scholar 

146.
Bates, D. et al. Package ‘lme4’. Convergence 12, 2 (2015).
Google Scholar 

147.
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & Team, R. C. nlme: linear and nonlinear mixed effects models. R Package Vers. 3, 111 (2013).
Google Scholar 

148.
Tabachnick, B. G. & Fidell, L. S. Principal components and factor analysis. Using Multivar. Stat. 4, 582–633 (2001).
Google Scholar 

149.
Kaiser, H. F. Unity as the universal upper bound for reliability. Percept. Mot. Skills 72, 218–218 (1991).
Google Scholar 

150.
Hadfield, J. D., Wilson, A. J., Garant, D., Sheldon, B. C. & Kruuk, L. E. B. The misuse of BLUP in ecology and evolution. Am. Nat. 175, 116–125 (2010).
PubMed  Google Scholar 

151.
Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).
Google Scholar  More

Imagination is critical to sustainable and just futures for life on Earth8,13. Writing after the West African Ebola outbreak, Professor Michael Osterholm and colleagues called for more “creative imagination” to consider future pandemic scenarios14. This feels particularly salient five years on. Purely technocratic approaches fail to engage with the emotions that motivate action towards alternative futures: fear, hope, grief and agency8,15. By building new ways of thinking about longstanding problems, inclusive and creative processes can generate positive stories about the future in ways that are empowering8,10. Imagining the future can drive societies towards change by shaping common practices, aspirations and institutions16.
Methods for imagining, such as scenarios analysis, strategic foresight and speculative fiction are commonplace in research, investment and planning8,13,17. They can help the biodiversity community address the bleak futures that are projected for biodiversity. Research can play an important role in embracing imagination by fostering novel participatory methods that enable society to explore what is possible, plausible and desirable13. All models and scenarios are wrong, some are helpful: they contain assumptions about what matters, what is known and what is unknown. Embracing and communicating these assumptions and uncertainties builds trust in science, opening up spaces for deliberation about values, trade-offs and desirable futures18.
Imagination can build the anticipatory capacity to get ahead of the curve, rather than react to crisis17. Decision makers must learn to provide anticipatory leadership that fosters shared responsibility for actions that may have greater costs now, to avert harm in the future. Enabling transformations also requires those who benefit from the status quo to acknowledge the need for change. Policy frameworks need to consider the distribution of costs and benefits over longer timescales when setting current priorities. Ultimately, society needs to accept that the future is unknowable and uncertain, but that action is needed now.
These anticipatory capacities start with asking: what are the short- and long-term drivers of change? What values should be maintained into the future? What can be done differently over the next five years? Over the next 30 years? What do we need to know and what will we never know? How can options be created and traps avoided? What are the ethical implications of action and inaction? Considering these types of questions can provide a foundation for decision making despite uncertainty.
Our stories show that choices have consequences. Some close down options. Some open up multiple pathways. Either way, choices create winners and losers. The critical challenges of the Anthropocene require humility19 and the ability to respond20. Imagination can help the biodiversity community grapple with these challenges by embracing diverse ways of thinking, listening, being and knowing. And such diversity can be the foundation of more just and sustainable futures for life on Earth. More

The Cooper bundles were found just beneath the sand surface ~15 m up from the waterline. A sand slope angle of 10∘ was measured during a site investigation which would place the burial site ~3 m vertically above the water line. This location would only be immersed during times of high water and wave action. Dredging operations took place on the river and the sand was dumped slightly upstream of the burial location and could have contributed to additional sand on top of the bills. Sand is no longer deposited on the beach and it has undergone severe erosion. Rubber bands found intact but degraded on the bundles suggests they were initially buried without any significant exposure to the elements which is known to rapidly degrade them25.
In order to determine if a seasonal diatom timeline can be used to constrain the burial of the Cooper money, the first question to be answered is: can diatoms penetrate a bundle of money buried in sand? The diatom saturated water experiment showed that penetration is possible but only for the smaller range of diatoms and only a limited distance in from the edge on the order of millimeters. No “tide lines” of diatoms or small sand fragments were found on the Cooper bill. Since we know from the experiment that diatom accumulations were likely to happen on the edges, the lack of aggregations suggests they were destroyed with the severe degradation around the edges of the bundle. The inner degraded edge where the SEM samples were taken from showed no accumulations, suggesting the bills had congealed into a solid lump (consistent with the condition that the bills were found in), preventing any further diatom infiltration.
A second line of evidence that would signal diatom infiltration while buried would be an abundance of diatoms in the bills that were also found in the surrounding sand. The extraction of the diatoms from the Tena Bar sand showed a predominance of small forms on the order of 3–5 µm. These small diatoms are consistent with species that can survive in sand due to their ability to situate in the interstitial crevices of a single sand grain26,27. Larger diatoms, of which Asterionella and Fragilaria are among the largest, have low survivability in the proportionally boulder size sand grains26. The lack of predominantly smaller diatoms on the Cooper bill suggests little to no diatom infiltration to the inner portions of the stack occurred while buried. While similar small diatoms were found on the bills, they were not a dominant category as would be expected if they were the primary source of infiltration.
If the Cooper bill used in this examination was from the top of the stack, then one could expect to find a variety of diatoms from all sources. Figure 2C indicates conclusively that the examined bill is from the middle of the stack by finding an intact Fragilaria sandwiched between two bills. Due to the congealed nature of the bills, it was not uncommon to find intact fragments of other bills adhered to the larger bill. Fragilaria at ~80 µm28 is considered a larger diatom in the Columbia River system29. It is planktonic30 and therefore has no ability to move through sand. Its size and location interior to the stack (Fig. 1) and notably with no smaller diatoms surrounding it, suggests that it came to rest there while the bill was completely exposed to river water.
If the previous experiments and investigations rule out diatom infiltration while buried, then the findings suggest that diatoms found their way onto the bills during water immersion. As shown in Fig. 4, a stack of bills once saturated, will fan out in water exposing all surfaces to micro-particles in the water environment. The exposure of the fanned out stack to the river, suggests the simplest way for large, intact but fragile diatoms to be found alone interior to the bill stack. This would have occurred prior to burial and be in the water long enough for fan out to occur.
Figure 4

(A) Stack of bills bound with a rubber band immediately after placing in still water. (B) After several minutes, the stack becomes saturated and fans out exposing individual bills to the water. Shortly thereafter the entire stack will sink to the bottom.

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The Columbia River has seasonal blooms of diatoms with different species found in winter vs summer19. If the bills were submerged for an extended period covering multiple seasons, then diatom species found on the bill should also represent multiple seasons. Table 1 shows the genera found on the Cooper bill and the dollar bill soaked in the Columbia in November. The first notable observation is that there is little overlap in genera between the two seasons.
Asterionella followed by Fragilaria are key indicators in this study. Asterionella are relatively large up to 100 µm31, planktonic diatoms that undergo radical changes in population in the Columbia River (Fig. 5) of up to 10 × during the course of the year20. They assemble into star shaped colonies that are susceptible to damage. Asterionella were found broken but associated on the Cooper bill as shown in Fig. 2A. Although in pieces, the relatively complete association of parts suggests that the diatoms landed intact on the bill and were subsequently crushed and broken after the fact. Similar associations were found elsewhere on the Cooper samples.
Figure 5

Monthly abundance of Asterionella showing population bloom in May and June. Extremely low numbers are apparent for winter months. Data compiled from three sources19,20,21 graph shows relative numbers.

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Several examples Asterionella were found on the Cooper bills and this diatom is nearly absent in November when the jump occurred20,21. There is however a very large bloom of Asterionella in early summer during the months of May and June19,21. The other diatoms identified on the Cooper bill such as Stephanodiscus are also more prevalent in the summer season21. The diatoms found on the November bill are not consistent with species found on the Cooper bill. This suggests that the Cooper bill was immersed during the summer Asterionella bloom and the length of submersion did not extend into subsequent seasons.
Trace elements are incorporated into the diatom frustule during growth and elemental availability varies in rivers during the year17. Krivtsov et al. 2000 studied the elemental variation in A. formosa and found that it varied by the season5. There were not enough recovered Asterionella from the November time frame to do a direct comparison but elemental signatures from a variety of specimens were compared between the November and Cooper bills. Figure 6 shows the diatom’s elemental spectra of calcium and sodium overlaid. The spectra were normalized to silicon and show relative abundances. The detected levels were small and near the limit of EDS sensitivity so this data is provided as qualitative. Elemental differences between the two groups showed slightly enriched calcium and a lack of sodium in the November diatoms while showing the complete opposite for the Cooper diatoms. A single fragment potentially from Asterionella or Fragilaria was found in the November sand from Tena Bar (Fig. 4B). This spectrum showed elevated levels of calcium and sodium again suggesting a difference from the A. formosa found on the Cooper bill which only showed enriched sodium. The single diatom spectrum from the March bill showed no increase in either sodium or calcium suggesting the March time frame has a different elemental abundance in the water from either the winter or Cooper sample suspected to have summer diatoms. The reproductive lifetime of a diatom is on the order of days32 so a difference in elemental abundance suggests that these three assemblages were from different seasonal periods.
Figure 6

(A) EDS spectra overlay showing the sodium line. Red lines are spectra from the Cooper bill diatoms showing elevated sodium levels, green lines are from November samples. Blue line is the single Asterionella spectra from the November sand sample showing no enrichment in either sodium or calcium. (B) Calcium line showing elevated presence of calcium for November diatoms while Cooper samples show lower levels. Each group of diatoms showed opposite enrichment of sodium and calcium. Data is relative and qualitative.

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